 HYBRID – introduction  1
 
  © EMD International A/S  •   www.emd.dk   •   windPRO 4.1    •   September 2024   
15 WINDPRO HYBRID 
 
15 windPRO HYBRID ........................................................................................................ 1 
15.1  HYBRID – introduction ........................................................................................... 2 
  Introduction to HYBRID ................................................................................................... 2 
15.2  Establish basic data .............................................................................................. 7 
  Example data ................................................................................................................. 7 
15.3  Setting up the HYBRID simulation ........................................................................... 8 
  Main tab, naming and calculation type ............................................................................. 12 
  Simulation periods and resolution ................................................................................... 12 
  Calculation, Setup ......................................................................................................... 13 
  Calculation, Units .......................................................................................................... 15 
  External Grid/ Import costs ............................................................................................ 18 
  Time series, windPRO calculations ................................................................................... 21 
  Time series, loaded from METEO objects .......................................................................... 23 
  Time series, Fixed energy price and Shedding filler ........................................................... 24 
  Time series specifications; inside/outside, scaling etc. ....................................................... 25 
  Storage ....................................................................................................................... 26 
  Cost and lifetime .......................................................................................................... 28 
  Finance ....................................................................................................................... 29 
  Energy value ................................................................................................................ 31 
  Time graphs ................................................................................................................. 32 
  Result graphs ............................................................................................................... 33 
  Result to file ................................................................................................................. 38 
15.4  Indices ............................................................................................................... 43 
15.5  Cost functions ..................................................................................................... 45 
15.6  Optimizer ........................................................................................................... 45 
15.7  OPTI-Storage ...................................................................................................... 49 
  Limitations in present version of OPTI-Storage ................................................................. 51 
15.8  Reports .............................................................................................................. 51 
  Report contents ............................................................................................................ 52 
15.9  Abbreviations/explanations ................................................................................... 53 
15.10  List of figures ...................................................................................................... 54 
 
   

HYBRID – introduction 2

15.1 HYBRID – introduction

Introduction to HYBRID

The windPRO HYBRID module makes it possible to evaluate the technical and financial feasibility of

energy plants with power production. The module handles time-varying prices against fluctuations in

production and can include storage. The OPTI-Storage functionality can from windPRO 3.6 handle

arbitrage (charge when price is low, discharge when price is high) and optimal handling of grid limits

(minimize the grid limit curtailment).

Time varying production calculations within windPRO for Wind and PV are smoothly loaded from

HYBRID module. Price time series concurrent to production data must be imported to a METEO object,

similar for demand time series if relevant. (Export all to grid does not require demand time series).

To deliver renewable production directly to the demands will often give the extra benefit that taxes

and tariff costs are saved, which is what often makes a Hybrid plant feasible. Demands connected

to the production units can be handled as either INSIDE or OUTSIDE the system, which is

conveniently named the “MicroGrid”.

The module can handle scenarios from very simple systems, like if it is feasible to invest in a Solar-

PV plant, and how big the plant shall be based on a given demand, to highly complex systems with

wind, PV, other green and black production interacting together, as well as storage, external grid

and an internal demand. The grid limitations can be set and can be given a cost to expand the grid

capacity and find out if this investment is feasible, or investing in, for example, storage would be

better.

Interaction with an external grid with time-varying prices is a core feature, but it is also possible not

to have any interactions with an external grid; the so-called “island operation”. Here a special feature

is the “shedding filler”, where a green or black production plant can be set to fill the gaps, when the

other production units cannot fulfil the demand, and “load shedding” would be the solution without

the “filler”.

The basis within the module is an energy balance simulation for one year where production, price

and demand time-series must be available for the same year. This simulation is repeated for all years

in the financial simulation period, where changes during the simulation period are included. Changes

could be that the Solar-PV plant degrades year by year, energy price levels increase or some plants

or storage are brought in or taken out of the system during the simulation period. All developments

by year can be controlled by freely definable indices.

For the power price simulation there is a high flexibility. Subsidies, tariffs and energy taxes can be

included dependent on which plant makes the power, and where it is used. There might be a tariff

just for the exported part of a specific wind plants production, while a subsidy is given to all PV

production. Any possible mix can be handled.

Curtailments can be based on grid capacity as well as price. If the price is negative, the production

can be shut down, like it will be curtailed when the grid limit is reached. For both curtailment types

a value can be given per MWh. Shutting down by negative prices often is compensated while the

plant helps the grid balance. If curtailment is due to grid limits, the power might be used for heating

and assigned an appropriate value is an option. Load shedding can also be given a value. If the

demand cannot be fulfilled in some hours, this has a cost, which could be the reason for investing in

storage. If the load shedding is not assigned a cost, the storage would probably not be feasible.

Scaling factors for the different technologies are part of the simulation. It is easy to see the impact

on the lifetime net cost when having e.g., a 50% larger PV-plant or storage. Here the cost functions

are a very important new tool in windPRO. Plant costs and productions are automatically scaled based

on size (simple scaling). Some plant cost types are based on formulas. For a wind park the turbine

costs depend on specific power as well as MW, rotor area and hub height. The cabling and road costs

depend on the inter-array distance, automatically calculated from the layout (i.e., this is a

HYBRID – introduction 3

simplification as the direct and shortest distances are used). Cost functions can be calibrated by the

user. Having the real cost for a newly-built plant can be entered, and the specific costs calculated

and used for the next plant. The initial values in the cost functions are based on comprehensive

studies undertaken during 2020. The user with only a small effort will have quite realistic costs for

the designed wind and PV plants and storage systems.

With the full connection between plant sizes and costs, and loans connected to plants, it is possible

to find the optimal combination of plant sizes for handling the actual demand with the given price

structures and variations in time. The optimizer will search for the plant and storage size, that

results in lowest lifetime costs.

Below is illustrated the basic business cases that can be calculated and optimized.

Figure 1 The demand is inside the MicroGrid.

With the demand inside the MicroGrid, there might be some savings on tariffs and energy taxes,

assuming these are avoided by internal production.

External plants are plants the MicroGrid purchases power from, “owned” by external organisations.

Plants inside the MicroGrid are financed and operated by the MicroGrid owner.

For demand inside the MicroGrid there is basically no income for the MicroGrid, except export. The

reference the costs are compared to is that the demand “imports all”. In key calculations such as

NPV and IRR, the “income” for the MicroGrid is the cost the demand would have when importing

all.

HYBRID – introduction 4

Figure 2 The demand is outside the MicroGrid.

With demand outside, the MicroGrid sells to demand based on an agreed price, which could be the

marked price, but could also be a fixed price or a factor on the marked price.

Here it is simple to calculate like NPV and IRR.

The reference that is compared to in this situation is that the MicroGrid deliver to the demand based

on the agreed price, but the MicroGrid import all power from the grid. Thereby the comparison to the

reference holds the extra element that it can be seen if it is better for the MicroGrid to establish own

production units/storage OR just to purchase from grid.

HYBRID – introduction 5

Figure 3 There are no demand, all exported.

A third variant is that there is no demand. A typical situation for many plants is that all power

produced is exported. This situation can also be handled, along with storage, which can be relevant

if there is lack of grid capacity or a limit on when or how much can be exported. The storage strategy

will then be to charge storage when there is a lack of grid capacity and export to the external grid

when production is below grid export capacity. Export only occurs if the electricity price is more than

a user-defined threshold, if not, the export will be postponed. The new OPTI-Storage functionality

handles this even more better, maximizing the income.

Go to the System Integration tab and click on the HYBRID button to open the module.

HYBRID – introduction 6

Figure 4 The HYBRID Calculation tab or "controller".

This is where the main functions are controlled from and simulation results are visible for

evaluation.

On the Main tab two different “principles” of operation for the module can be selected:

Figure 5 Selection of "Basic" calculation vs. Flexible Operation Periods.

For the Basic calculation, all plants and storage are assumed to start operation in the same month

and end operation in the same month. This will be the typical setup while investigating the most

feasible composition.

Establish basic data 7

When a more specific project is to be documented, the different plants will typically have different

operation start times.

Before starting using the HYBRID module, some basic information needs to be established,

described in following section.

15.2 Establish basic data

The following data should be established prior to starting the HYBRID module:

Production time-series options to use: (with a minimum hourly resolution, down to one minute can

be handled)

• windPRO PARK time-varying calculaton for a wind plant

• windPRO Solar-PV calculation, which is always time-varying

• Windfarm calculation available as time-series from other (non-windPRO) calculations ->

import into a METEO object

• PV-farm calculation available as time-series from other (non-windPRO) calculations ->

import into a METEO object

• Other green production available as time-series -> import into a METEO object

• Black production available as time-series -> import into a METEO object

Other optional time-series: (with a minimum hourly resolution, down to one minute can be

handled)

• Price time-series, normally ONLY hourly resolution while market prices typically are hourly -

> import into a METEO object

• Demand time-series -> import into a METEO object

More time-series of each type can be added to a HYBRID simulation, except for the price time-

series.

Note that it can be an advantage to establish longer time-series than just the one concurrent year

required. Then the sensitivity to which year can be tested by selecting different starting dates for

the energy balance simulation (and price).

If simulation is in an electricity market with high renewable energy penetration, it is very important

that the price time-series and meteorological data are concurrent, especially when the prices can

be affected by the hourly wind or solar production. A more problematic issue is if the penetration

increases too much during the financial simulation period and significantly affects the price

dynamic. This can only be handled by establishment of an artificial price time-series which has the

expected dynamics. This is not a trivial task.

Note that when the HYBRID module is started, there will be two alternative options for auto

generated time-series:

• Fixed price, where a time-series is autogenerated with same price in all time stamps

• Shedding filler, where other green or black production is filling up when demand is not

fulfilled by the system due to grid import limits. This could be an island operation, for

example.

Example data

In the folder windPRO Data\Standards, there will be examples of price time-series and demand

time-series:

Setting up the HYBRID simulation 8

The demand simply follows the Denmark – west variations, scaled to 500 MWh/y.

For western Denmark 3 years+ spot market price data is downloaded. More Danish (and

neighbouring countries) data can be reached at:

https://www.energidataservice.dk/buildreport

Figure 6 Example of import filter in METEO object for electricity prices.

Figure 7 In Data setup, select relevant signals. Height irrelevant, but a “dummy” value must be

entered.

Having the data in a METEO object makes it easy to evaluate the data, and to disable erroneous

data.

The basic principle if the HYBRID module encounters disabled or missing data is to interpolate

linearly. An exception is price data, where the previous hour’s price is taken. It is a general

principle that prices are hourly, and when the simulation is in higher resolutions than one hour,

prices are not interpolated.

The demand data can be used scaled if the example is related to a much smaller or larger demand.

Example data already loaded in METEO objects can be found in the sample project (Hybrid Quick

Guide) which can be downloaded from the windPRO Samples in the Data menu in windPRO.

15.3 Setting up the HYBRID simulation

Setting up the HYBRID simulation 9

Having at least a production time-series ready, a simulation can be set up. In the following

example, a PARK calculation is performed for years 2018-20 based on hourly ERA5T data. The

project has 7 x 75kW WTGs.

The time-series will be loaded along with the demand and price time-series from example data.

Figure 8 Loading time-series and setting scale factors, if relevant.

Here the three time-series for the completed PARK calculation, and the example data from the

sample project for Demand and Prices are loaded.

The demand is scaled up by entering a scale factor of 2 in the highlighted field above to make the

demand comparable to the PARK production, so the scaled demand is ~1000 MWh/y.

What can be seen is that the production from wind plant for the simulation year (2018) is 863 MWh

(reduced with 10% loss set in the PARK calculation, but editable in the “Reduction” column).

Also a PV-plant is added for illustration purpose.

Setting up the HYBRID simulation 10

Figure 9 After simulation, the raw costs are seen.

After a simulation has been run, the value for the individual lines is calculated. This is based on

weighting the energy with prices. It can e.g. be seen that the Wind price is lower while the market

price becomes lower when there is much wind production in the marked. Solar prices are higher in

the example, but this will change when much more solar power is established. In the line Total, it is

only the production (yellow background) that is summarised. The first line Import show values of

what needs to be imported, when production do not fulfil the demand.

Penetration percentages (of scaled demand) is also seen.

These values give an initial picture of how production and demand as time-series weighted with

price time-series are converted to currency based on 2018 time-series. Changing to 2020 in the

“Time series starts” will use production, demand and prices for 2020:

Figure 10 Changing the simulation year will change demand as well as production and prices.

Figure 10 shows that production is a somewhat higher in 2020. The big difference is the price. The

value of wind production is more than halved, and the cost of demand is reduced more than one

third. This illustrates that it is of extreme importance to have a good idea of which price year to

use, one that is assumed most realistic for the future, when analysing the financial feasibility of the

HYBRID system.

The year is reverted to 2018, and the Simulate button is pressed. We now look at the financial

feasibility of the wind park in a system from a purely market price-based viewpoint.

We will get a warning, that no cost for the wind park is included.

Setting up the HYBRID simulation 11

In the drop-down choose “Edit cost function”, and create a new entry from one of the templates as

illustrated below:

Figure 11 Selection of cost function.

The cost function must be reviewed, and might be adjusted, but this is covered later in the

Chapter. In this case the costs are lowered relative to the “native” cost function for illustration

purpose.

We now press the “Simulate” button and get a first calculation result:

Figure 12 First simulation result, only wind production included.

What is seen in the financial columns are the lifetime costs:

1. Development Expenditure (DEVEX) – Grants + Capital Expenditure (CAPEX)

2. Operating Expenditure (OPEX) + Abandonment Expenditure (ABEX)

3. Interests + fees (no loan included in this simulation)

4. Purchase/Import (No purchase from external plants included in this simulation, the wind

park is assumed INSIDE the MicroGrid (can be chosen on time-series tab.)

5. Export/Curtailment

6. Subsidy (none defined in this simulation)

7. Tax/Tariffs (none defined in this simulation)

8. Total costs, SUM of the above.

On the bottom line “All imported” is shown, which is simply the cost if the demand was entirely

imported from the grid, which is the reference. Will an investment in a wind plant pay off and make

the cost of energy cheaper?

In this case the answer is “maybe”.

Setting up the HYBRID simulation 12

All imported costs total 895 kEUR during the project lifetime.

The cost of the wind park – export value is 375 kEUR and the imported from grid costs are 469

kEUR, in total 844 kEUR, 51 kEUR less than if the demand continues to import all energy for the

next 20 years, assuming the 2018 demand, production, and time-series.

The NPV is negative, however, at -52 kEUR. So, the savings are acceptable, but when discounting

with 2.5% interest rates, (default), the value of the income in the later years is low compared to

the value of the investments in the early years.

Further analyses can now be performed to further understand the financial implications of the

choices made. There are many possible questions, where the HYBRID module can deliver the

answers. We may need to look at financing the plant(s). We may need to include tariffs and taxes;

we may need to look at expectation of future price development, etc. Variations in any or all of

these will change the results of the feasibility check. These will be systematically presented and

explained in the following sections.

Main tab, naming and calculation type

Figure 13 Selection of "Basic" calculation vs Flexible operation periods.

A calculation name can be entered (always recommended for any windPRO calculation).

For the Basic calculation, all plants and storage are assumed to start operation in the same

year/month and end operation in the same year/month. This will be the typical setup while

investigating the most feasible composition.

When a more specific project is assessed, the different plants will typically have different

operational start times and some might not be operating until the final simulation year.

Simulation periods and resolution

The Time-series start is for the energy balance data, and there must be ONE full year within the

concurrent part of the time-series added. It is recommended to establish time-series so at least

two full years are available so that the sensitivity to selection of one year or another can be tested.

The price-production dynamics for the specific year can be significant in determining the energy

balance and hence the financial performance of the system. It might even be necessary to establish

a “future” price dynamic to use in the simulation. For example, if much Solar-PV is assumed to be

Setting up the HYBRID simulation 13

added to the grid in the future years, this might have a negative impact on the prices in hours with

much Sun.

The Time resolution can be set between 1 and 60 minutes. Any added time-series will be

interpolated to increase time resolution, except for the price time-series, which always is treated as

hourly. Later the output from windPRO PARK and Solar-PV will be able to deliver higher resolution

time-series based on a resampling method being developed by EMD. At present it is only possible

to deliver high time resolution output, if having high resolution data to calculate from. Also, data

from METEO objects can be high time resolution.

Operation start can be any year, typically in future.

Operation years, the number of years the MicroGrid operation is simulated.

Important to mention that the energy balance calculation is repeated for each operation year.

Characteristics such as degradation can be included as well as price developments, etc.

Calculation, Setup

Figure 14 Calculation setup collects different decision requirements.

15.3.3.1 Timeli ne handl in g

On this tab it is specified when DEVEX and CAPEX is placed in the financial simulation. The default

is that DEVEX is placed at year -1, meaning that the DEVEX costs are placed 12 months before

operation starts.

CAPEX is by default placed at year 0, meaning the first operation month. The reason for this choice

is that finance cost is arranged so interest by default is paid first time the year where CAPEX is

placed. If CAPEX is placed year -1, there will be interest and instalment costs the year before

operation starts. This would be taken by the reader of the report to be a non-logical approach. One

way around this is to include a loan Payment Grace Period, which often would be the real-world

approach, just requiring more manual data input, than if CAPEX is placed at year 0.

Indexation of the simulation year price level is optional so the price time-series can be assumed to

be the same in the first operation year as the input data. This is the default. If a second option is

selected, the indices chosen where the price developments are specified will be used for the

different prices.

15.3.3.2 Dep rec iation

There can be two types of depreciation:

Accounting depreciation is used for setting up the accounting budget, following normal accounting

principles, where the value reduction of the plant is used, not the instalment costs.

Depreciation is only used on CAPEX. In real life a part of DEVEX might have a value, that should be

depreciated – and the other way round, part of CAPEX might have a value that should not be part

Setting up the HYBRID simulation 14

of the depreciation. To compensate for this, the user can move costs between DEVEX and CAPEX to

get a realistic representation.

The depreciation time is by default the simulation time but can be manually set. If a plant is

designed for 20-year lifetime, and there is a wish to report 25 years of operation, while the plant

might run for 25 years, it can be more realistic to use the 20-year depreciation time instead of

simulation time.

For parts of plants where replacement years for a specific part of the plant, e.g. the inverter for a

Solar-PV plant, is set to 10 years, for example, this number is always used as depreciation time for

this part. It would not make sense to use a longer depreciation time for parts that are assumed

replaced before the end of the simulation period. This also means that if simulating 25 years and a

new inverter is bought in years 10 and 20, the final inverter will only be half depreciated. A scrap

value is assumed in the reporting. When taking out the ”Result to File” output data for further

processing in other packages (e.g., Microsoft Excel), the time period with data is expanded with the

added depreciation period, and the user of the data can decide how to handle this situation.

Figure 15 Example of depreciation handling with remaining lifetime of a component.

Figure 15 illustrates a 12-year simulation period, where the inverter has 5-year replacement time.

The first 12 years, the inverter + PV plant is depreciated linearly based on the PV-plant minus

inverter costs, € 6.242 per year + inverter cost/ 5 year; € 2.707, total € 8.949. These are the

depreciation costs through the simulation period 2021-2032. After 2032 there will be three years

lifetime remaining for the inverter, and the output lines are expanded with these years and inverter

depreciation included in the three remaining years after the simulation period has ended. For

manual postprocessing of data, it can be decided to include the three years cost the last simulation

year or to account for this as a scrap value.

In the accounting balance reports from HYBRID module, the last three years will not be included,

and it is indirectly assumed there is a scrap value.

Grants will be deducted from CAPEX before calculating depreciation. If a plant needs grants, it is

basically because the cost of the plant is higher than the value. Therefore, the most correct value

in the accounting balance will be the grant reduced CAPEX.

15.3.3.3 Pric e curtailm ent an d l oa d sheddi ng co st opt ion

If the energy price is negative, by default the plants are curtailed. (Curtailment price threshold set

to 0.00). Later in Section 15.3.13 Energy value, a price value for curtailment due to low prices can

Setting up the HYBRID simulation 15

be set. Often the grid operator pays compensation, when the plants help the grid system when

there is too much production. This can be based on quite complex calculations, not included here.

But with the option to curtail at a given price threshold and enter a compensation value, the

mechanism is included. Since typically only few hours in a year have negative prices the

importance of the accuracy is not that high.

Load shedding can be an issue if there are grid limitations, e.g. an island operation, or simply just

in a system where the production capacity is too low relative to demand. This is where establishing

a MicroGrid, with possible Storage, can help and reduce the shedding. To measure the value of

this, shedding can be given a cost. It might not be involving a real payment, but without a cost,

the demand simply just pays less because less is used. The shedding costs can be index-linked.

A default Solar-PV AC/DC ratio is used if Solar-PV production data are from a METEO object only

the AC time-series production is available. Since the Solar-PV DC power is used in the cost

functions, the DC power is required and calculated from the METEO time-series using this ratio.

15.3.3.4 Infl ati on

Inflation can be specified by a “project default”, selected in Index form:

Figure 16 Selection of index used as project default.

By default, when creating a new HYBRID calculation, the “No in-/decrease” is selected as default. It

will often be more convenient for the first analyses to calculate without inflation, while it is simpler

to check the results.

If, for example, “2% inflation” is selected as new default in the index list, all “No in-/decrease”

selections will be replaced with “2% inflation”. If some indices, for example, for subsidy, are

subsequently manually changed, and the default index later is changed from the manually set

values will not change.

Figure 17 Alternative inflation for "fast test".

It is also possible just to check another inflation, that replaces all with the default selection.

Thereby a fast test on a different inflation choice can be performed.

Note the indices that describes production development in time are NOT changed, only the financial

indices.

Calculation, Units

Setting up the HYBRID simulation 16

Figure 18 Select units to handle small-medium-large projects.

Depending on the size of the project to be simulated, it is convenient to choose units that match

the project size.

15.3.4.1 Currency sel ect ion

Selection of currency is by this form:

Figure 19 Selection of currencies.

Base currency for all HYBRID calculations is EUR. But any other currency can be selected to use as

input/view/report currency, recalculated based on the exchange rate in the table shown.

Setting up the HYBRID simulation 17

Figure 20 Add currencies from ISO 4217 list.

Here is as example with selected DKK and EGP, and the list will look:

Figure 21 Currency list updated with selections.

If required, a manual change can be made, e.g. DKK/EUR to 7.4500:

Setting up the HYBRID simulation 18

Figure 22 Manual update is registered in list with USER source.

The list is with currency values from e.g., early 2020, so it is recommended that the user check

actual currency exchange rates and update when relevant. Exactly which rate to use is an

individual judgement or agreement with the client for whom the calculations are performed.

External Grid/ Import costs

Figure 23 External grid / import cost specifications.

The Grid Capacity is often the bottleneck for new plants. Here import/export limitations can be

specified, partly for the MicroGrid, which might include a grid capacity expansion, and partly for the

reference situation where all power is imported from the external grid. This also might require an

expansion in case a new demand is part of the simulation which cannot be supported by the

existing grid. For the two situations grid expansion costs can be included. These costs are NOT

scaled in the case of modified system size but are assumed to have a fixed cost for the planned

system.

For the Import Energy Costs the default is to use the loaded price time-series with a factor 1.0

and offset 0.0. To convert to a fixed price the factor is changed to 0.0 and the offset is then the

fixed price. Values for Tariff and an Energy Tax can be entered. This is quite important, while this

often will be critical for determining whether the MicroGrid will be financially feasible, where saving

these costs can contribute.

For each of the input fields, a cost development index can be specified.

15.3.5.1 Cal cul at ed (Ti me d epen di ng) tariff

Tariffs often vary in time, where day hours have a higher tariff and night hours a lower tariff, to

encourage the consumer to reduce consumption during peak load hours and thereby reduce grid

expansion costs. This can be included choosing the (o) Calculated Tariff which opens this form:

Setting up the HYBRID simulation 19

Figure 24 Form for entering time depending tariffs.

In the left part more different period cost models can be added, in the right part the individual

period cost models is defined. An example:

Figure 25 Peak hours on Monday to Friday with higher tariff, Sundays, and holidays with lower.

Important: The priority is deciding. If the two lines above were swapped, all mon-friday would

get the high cost in peak hours, also on holidays, while this line would have higher priority. As

defined above, Sundays and holidays always will get the low price. All non-defined times will get

the default price, like e.g. Saturdays in the example.

The red background for the Holiday field, tell that no holidays has been defined yet. This is done in

“Edit Holidays”. Below we pick the option “Load Online”, giving access to a library for all countries:

Setting up the HYBRID simulation 20

Figure 26 Online Holidays, with subdivision for some countries, like Germany.

For e.g. Germany, the individual “Bundesländer” has different holidays, and the region must be

selected.

Figure 27 The edit holidays form after online import.

When downloading online, a complete series of holidays from 1990-2074 will be established. It is

possible to edit manually.

The view summary button creates a graphical overview of the period cost model:

Setting up the HYBRID simulation 21

Figure 28 Period cost summary.

A specific year can be selected and it is seen where the holidays appear.

Time series, windPRO calculations

The time-series is the core input. For wind parks and Solar PV-plants windPRO calculations can be

loaded. Quite precise time-series with expected production including elements such as curtailments

(for wind parks) are available. Some important information related to the two types of calculations:

For Wind Park calculations, these must be time-series calculations. Here are two variants, based

on MESO data or based on Measurements. The data used in calculation decides the possible time

resolution.

Setting up the HYBRID simulation 22

Figure 29 PARK calculation setup with features marked important for HYBRID.

The settings in “Output to PERFORMANCE CHECK…” section of this tab will determine the output to

HYBRID. If the wind farm to be used includes other turbines in the calculation, it is possible to

select individual WTGs and only these will appear when loading into HYBRID. The other turbines

might also give wake losses to the selected turbines.

The “Aggregated time-series values” decides the aggregation level. This is by default monthly

which cannot be used in HYBRID. Remember to change aggregation level to “None” or to

a maximum of 1 hour.

Finally, the “simple reduction”, above shown as 10%, but editable, by default is transferred to

HYBRID. There is no loss reduction in a PARK calculation apart from wake and curtailment losses,

therefore it is often relevant to add losses here (such as grid losses, availability, etc.).

For Solar-PV calculations a full loss specification is available in the calculation module.

Setting up the HYBRID simulation 23

Figure 30 Loss specifications in Solar-PV calculation.

When a loss is correctly specified, this loss will be deducted in the data transferred to the HYBRID

module. Although NOT the degradation loss. This must be manually added by an index:

Figure 31 Creation of a degradation index.

Figure 32 Selection of degradation index.

Time series, loaded from METEO objects

Time-series from any production calculation or demand or price time-series can be imported in

METEO objects, see the more comprehensive manual Meteorological Data Handling for details

regarding how to import data. When imported and using one of the buttons marked with the

METEO object symbol, the HYBRID module looks for relevant METEO objects.

Setting up the HYBRID simulation 24

Figure 33 Buttons marked with METEO object symbols require data loaded in METEO objects.

Figure 34 Left, if no match is found, right if relevant data is found.

Pressing a button look through the METEO objects and check if there are objects with these signal

types loaded:

• Energy Price

• Consumption (= demand)

• Production

Select the relevant option and load by clicking OK.

Aside from wind or Solar-PV production data be:

• Other Green, e.g. Hydro, Geothermal, biomass-based production, etc.

• Black, e.g. diesel generator or other fossil fuel-based production.

Common for Other Green and Black is that they can be established in two ways:

• As fixed time-series (e.g. as a constant production or run of river Hydro, based on

external simulations or measurements.). The time-series must be imported into a METEO

object, where there must be minimum one year concurrent to the simulated wind and/or

PV simulations with 1 hour time resolution or higher (down to 1 minute).

• As Shedding filler; The unit is producing when the sum of producing units, storage

discharge and import (limited by grid capacity) cannot fulfill the demand.

Hydro with storage capabilities is not handled intelligently at present. The user must establish a

production time-series, and the production will be fixed by hour.

A hydro pump storage can be handled as a storage component.

Time series, Fixed energy price and Shedding filler

There are two special time-series, auto generated by the module.

The fixed price time-series can be used e.g., for island operation mode, where there is no market

to act against. An index can be used for change in time (annual).

Figure 35 Fixed price time-series.

Setting up the HYBRID simulation 25

The shedding filler is used, if there are grid limitations, e.g., in an island operation mode, that

prevents the demand being served by the specified production units (and storage), but instead will

be served by a diesel generator or other source. This could also be a biomass-fuelled production

unit or a hydro power unit with a storage capacity that makes it possible to deliver at any time

where other units cannot deliver the demand.

The shedding filler can be specified as green or black. Whether it is green or black will influence the

reports and graphics. In relation to the filler, a cost function can be established so the investment

and operation costs (e.g. fuel costs) will be handled in the simulation. Also, the price the

production is sold for including taxes, tariffs and subsidies can be specified individually per plant,

where the energy price e.g. can be linked to the price time-series with a factor and offset. The

default is that it follows the price time-series (factor = 1 and offset = 0).

Figure 36 Shedding filler specification.

Time series specifications; inside/outside, scaling etc.

The Data type can be energy price, demand, and production, where production can be from PARK

or Solar-PV calculation or from METEO objects.

Name is auto generated from source but can be edited.

Loaded tell when the given time-series was added to the simulation.

The Start and End dates for the loaded time-series are important, as there must be at least ONE

concurrent year for all time-series used in the simulation.

Rated Power for the plant is found either in the calculation specifications or if loaded from METEO

objects by finding the highest power in the time-series.

Reduction [%] gives the option to make a general reduction of each time stamp in the time-

series. Often a wind park calculation will not be loss reduced and would then provide too high

production figures.

Figure 37 Loss deduction in PARK calculation.

By default, the figure for loss deduction in PARK Setup is carried over when reading the PARK

calculation. This can be overwritten. In future versions, PARK will handle loss deductions more

intelligently, so availability losses can be distributed in time by specific rules, for example. At

present it is possible to include curtailment losses based on rules that influence the output by time

step. Likewise wake losses are calculated by time step.

Setting up the HYBRID simulation 26

The time interval in minutes is just for information, telling which time resolution the time-series

loaded are found to have.

Development can be inserted as an index, see Section 15.4. This covers the situations where a

demand is expected to increase during the simulation period, or a PV plant production will degrade

over the simulation period, for example.

Production and demand time-series can be marked “include in scaling”, which means that the

time-series can be scaled. This means these elements can quickly be tested, so see if a larger PV

plant would be a financial better alternative, for example. The demand can be adjusted to

represent a larger population, etc. And the scalable elements can be included in auto optimization.

If there are two wind parks, one that is already there, and another planned, only the planned

would be relevant to mark “include in scaling” as only this wind park would change when optimizing

or manually setting scale factors.

Time series can be inside or outside the Micro grid

Production units INSIDE means that the MicroGrid owners invests in the production units.

Production units OUTSIDE means that the MicroGrid purchases power from the units.

An “infinite” (probably with some computer limitations) number of production units, each specified

as inside/outside.

Demand can also be specified by multiple time-series, although all must be inside OR outside. This

limitation is designed to make it possible to compare to a reference.

The “Update all” reloads the time-series in case some have been modified/updated.

Storage

Storage is a central component in a HYBRID simulation due to the time-varying production from as

well Wind as PV, a storage might improve the system. Basically, all types of storage can be

handled although the focus here will be on batteries.

Figure 38 Storage specifications.

The storage is defined by:

• Volume

• Loss (%) (standby loss)

• Charge capacity

• Charge loss (%)

• Discharge capacity

• Discharge loss (%)

• Discharge depth (%)

The size of the storage will typically be decided based on running the optimizer, see Section 15.6

Optimizer.

As a starting point, a storage size can be established based on, for example, 4-hour production

with rated power. Having 1 MW wind and/or PV production units, a 4 MWh storage volume could

make sense.

Running a simulation gives access to the Storage demand analyser, which is helpful for setting the

charge/discharge capacities:

Setting up the HYBRID simulation 27

Figure 39 Storage demand analyser for selection of charge and discharge capacity needed.

Figure 39 shows how much charge/discharge capacity that will be needed for different coverage

thresholds as a result of a simulation without storage.

Figure 40 Re-evaluation of charge/discharge selections.

With 200 kW selected for charge as well as discharge capacity, Figure 40 shows which

requirements won’t be fulfilled outside the grey shaded area. The volume is set to 1 MWh – a

thumb rule is that the storage volume should be 4-8 times the charging capacity, meaning it takes

4-8 hours for fully charging the battery. Adding a cost (see next paragraph), will give a first idea if

the storage seems to be a good idea.

Setting up the HYBRID simulation 28

Cost and lifetime

Figure 41 Adding a cost function.

The first time a new technology is added to a simulation, the only choices are “No cost” and “Edit

cost functions”. Selecting “Edit cost functions” the following form appears, where the “New” button

is expanded:

Figure 42 Establish new cost function.

Only relevant technology options will be shown. As no Storage cost function has been established

so far, there are no cost functions, but there is a “New” button, that can create a storage cost, with

sub-selection, Battery – future versions may add more options, like there are for wind and Solar-PV

at present.

Figure 43 Selected cost functions.

The simulations have more meaning when costs are added. Figure 41 shows how cost functions can

be added – by first time use first enter the “Edit cost functions”. These are described in more detail

in BASIS manual Chapter 2.18. The following describes how they are established/attached in

HYBRID.

Setting up the HYBRID simulation 29

Figure 44 The cost function gives a first rough budget for the technology.

Figure 44 shows the cost function value, the specific costs for the different “components” within the

technology. These are multiplied by the selected plant size and a “Temporary example plant cost”

is shown. Temporary, while the battery size can be changed and thereby the cost automatically will

change in the simulation.

The table on the right summarizes and the Cost of Storage (COS) as well as Levelized cost of

storage (LCOS) and is calculated based on the cost function and some key values, that can be

edited.

Clicking OK, the costs are adapted to the HYBRID simulation, with the important benefit that if the

size of the plant is changed, the costs are automatically changed. This makes it possible to

optimize the size.

Finance

Figure 45 Adding loans.

Setting up the HYBRID simulation 30

Normally energy plants are financed, as it is not that common that the investor has the cash to

invest directly. Here the “Add loan” drop-down will show a line for each added plant. The loans will

be “plant specific”, only in this way is an optimization by technology possible.

Figure 46 Main loan specifications.

In the main loan specifications, the following can be edited:

• % of investment (automatically follow the investment by scaling/optimizing)

• Period, years

• Interest rate %

These are the most important and therefore visible/editable in the list. For further details, use the

EDIT button and the more detailed form (which also appears when a new loan is added) will

appear:

Figure 47 Detailed loan specification.

Here more details can be entered.

Type:

Amortization:

Also:

• Payment grace period

Setting up the HYBRID simulation 31

• Payments per year

• Fees

can be entered.

When the loan is repaid is controlled by the simulation. This is linked to the CAPEX and therefore

the data will change automatically if the simulation period is changed. Postponing a project to start

two years later in simulation will not require a revisiting of the loan input.

If the loan period is longer than the simulation period, the loan will continue to be paid out and

costs will appear after operation end based on the simulation period. For the Result to File output,

there will be an extension of the number of years in the output file, making it possible to decide if

the final payment of the loan shall be put in the last simulation year. In the reports the loan will be

paid out in the year after the last simulation year and appear as a cost along with ABEX if included.

15.3.12.1 Financing wh en r ein ves tm ent s wit hi n cost fu ncti ons

While the financing is auto generated/updated, for example when the plant size is changed by the

scaling factors manually or through the optimizer, there are some decisions to be taken in relation

to reinvestments.

For now, reinvestments are NOT financed, but will appear as a cash cost taken from the owner’s

cash balance. See also handling of Depreciation 15.3.3.2.

Energy value

Figure 48 Input of energy value for export etc.

The value of energy that is exported can here be defined as described in Section 15.3.5 External

Grid/ Import costs.

In addition, Subsidy, Tariff and Energy Tax can be given prices per MWh.

The production used in MicroGrid (or sold to demand, if demand outside MicroGrid) can also be

given subsidy, tariff, and tax. E.g., subsidy might be given to all production from a specific

technology, not only the exported.

Curtailed due to grid or price curtailment can be given a value.

All values can be specified per plant and price indices can be attached to each price, see below:

Setting up the HYBRID simulation 32

Figure 49 Index for each cost available by “Show Cost Development”.

15.3.13.1 Sal e t o d emand

Figure 50 Sale to demand price if demand outside MicroGrid.

If the demand is outside the MicroGrid, an agreed price can be entered. This can be linked to the

price time-series or be fixed as described previously in Section 15.3.5 External Grid/ Import costs.

Time graphs

Figure 51 The scaled input data.

The first time-graph shows the raw production values after scalings and the energy price. This is

just a data presentation, without simulations.

Setting up the HYBRID simulation 33

Figure 52 Energy balance simulation time-series.

The second view includes the simulation results, like storage filling. For illustration, we have

included a grid export limit of 500 kW.

Figure 52 Energy balance simulation time-series. Shows how the different technologies produce

along with demand and storage filling. The purple line shows how the storage “prolongs” the period

where the demand is fulfilled by the local production.

Result graphs

Setting up the HYBRID simulation 34

Figure 53 The Balance by Demand and Production.

Figure 49 shows how the demand is delivered by source (left). The storage here delivers 13.8% of

the demand, 19.6% is imported from the external grid.

If there are no demand, this graph will show export instead.

The production distributed as directly used by demand, charged to storage, the exported part and

the curtailed part are shown on the right. Note the charged percentage can be lower than the

discharged, if the production is higher than the demand.

By clicking the “Excel button” the data can be extracted as the lifetime values in Wh. Note for the

left graph: The production seen is the utilized production by demand (or exported if no demand),

not the total production. See example below:

Table 1 Output from Balance graph, demand with added columns in Excel.

Lifetime Wh

MWh

MWh/y

Text

Series1

Wind: 39,2%

11744742527

11.745

587

Solar: 27,5%

8228796979

8.229

411

Other Green: 0,0%

Black: 0,0%

Import: 19,6%

5861554225

5.862

293

Discharge: 13,8%

4139405912

4.139

207

Shedding: 0,0%

Setting up the HYBRID simulation 35

Figure 54 Storage utilization graph.

Figure 54 Storage utilization graph. This indicates whether the storage seems well dimensioned and

suited for the case.

If the average filling is very low or high, the storage is probably too large or small – or if it almost

always is empty or full, it indicates that the storage not really is suited for the system.

Setting up the HYBRID simulation 36

Figure 55 Month/day Energy overview.

Figure 55 shows a very useful presentation of how the production mix matches the demand. And

how the optional storage improves the balance making the production closer to the demand.

Figure 56 The Production Use.

Setting up the HYBRID simulation 37

Figure 56 shows how the different technologies are distributed by direct use, charged to storage,

exported and curtailed.

Note the prioritisation behind this:

1. Black

2. Other Green

3. PV

4. Wind

The prioritization is “hard coded” based on following:

Black production is only assumed included if it “must run”, e.g., a base-load coal plant.

Other Green is assumed without down regulation options, e.g., run of river Hydro.

PV can be down regulated, although this is not often seen.

Wind is the most “down regulatable” and is often used to adjust to market limits.

An example: Wind and PV are producing each 50 kW, and the demand can only take 80 kW, the 50

kW PV is allocated as “direct used”, while wind is shared with 30 kW direct used and 20 kW

exported. If there is storage, and this is not full, the production will only be charged if capacities

allow. Thereby there is a second priority:

1. Direct use

2. Charged

3. Exported

4. Curtailed

With these two sets of priorities, the allocation of each Wh from each production technology is

decided and aggregated in the energy balance simulation.

Figure 57 Unfulfilled by MicroGrid to evaluate expansion options.

Setting up the HYBRID simulation 38

Figure 57 shows where the MicroGrid cannot match the demand. Both as monthly and diurnally as

annual average percentages. It is seen how much import is required, and if grid limitations, and

also load shedding will be seen as positive percentages. The export and curtailment percentages

are shown as negative values.

This suggests which technologies could be relevant to add. In the example shown above, it is the

winter months most import is needed, this show that more wind, which has highest production in

winter (in Northern Europe), could create a better balance. The diurnal pattern indicates that a

larger storage might also be helpful.

Result to file

Figure 58 Result to file output.

With the Result to File button following options are given:

Open Debug Folder…; opens a folder with the simulation results as text files.

Figure 59 Debug data folder with all relevant data from simulation.

Energy Balance and Finance; opens this window:

Figure 60 Result to file output to clipboard or file.

Data can be saved with a specified filename and location, or, more commonly, copied to the

clipboard from where all data can be pasted (<Crtl> + <v>) to any text editor or more

conveniently, to Microsoft Excel or a similar spreadsheet package.

Setting up the HYBRID simulation 39

Figure 61 Energy balance data in text file.

Note the energy balance data is minimum hourly data for typically 20 years with 50 data columns,

so it is quite a large amount of data. To check the data, it is recommended just to simulate one

year to keep the data amount reasonable. One year will normally be sufficient, while the same year

is repeated, although with index corrections and possible different plant start-stop dates.

Setting up the HYBRID simulation 40

Figure 62 The columns (53) in energy balance simulation.

1 Date time

2 WindProduction [W]

3 SolarProduction [W]

4 OtherGreenProduction [W]

5 OtherBlackProduction [W]

6 Demand [W]

7 EnergyPrice [EUR/Wh]

8 ScaledOtherGreenProduction [W]

9 ScaledOtherBlackProduction [W]

10 ScaledDemand [W]

11 ScaledWindProduction [W]

12 ScaledSolarProduction [W]

13 DirectUsed [W]

14 Balance [W]

15 AkkBalance [Wh]

16 RawCharging [W]

17 RealCharging [W]

18 AbsorbedCharging [W]

19 RawDischarging [W]

20 RealDischarging [W]

21 StorageContentPrimo [Wh]

22 StorageContentUltimo [Wh]

23 StorageStandByLoss [Wh]

24 Imported [W]

25 Exported [W]

26 CurtailedProductionLimit [W]

27 CurtailedProductionPrice [W]

28 LoadShedding [W]

29 WindDirectUsed [W]

30 WindCharge [W]

31 WindCurtailPrice [W]

32 WindExport [W]

33 WindCurtailLimit [W]

34 SolarDirectUsed [W]

35 SolarCharge [W]

36 SolarCurtailPrice [W]

37 SolarExport [W]

38 SolarCurtailLimit [W]

39 GreenDirectUsed [W]

40 GreenCharge [W]

41 GreenCurtailPrice [W]

42 GreenExport [W]

43 GreenCurtailLimit [W]

44 BlackDirectUsed [W]

45 BlackCharge [W]

46 BlackCurtailPrice [W]

47 BlackExport [W]

48 BlackCurtailLimit [W]

49 LoadSheddingAllImport [W]

50 Filler [W]

51 ExportFromStorage [W]

52 ImportToStorage [W]

53 ImportTariffPrice [EUR/Wh]

Setting up the HYBRID simulation 41

The extracted data holds for each technology what is produced and where it ends: Used by

demand, exported, price curtailed, grid limit curtailed or used by charger at storage. In addition;

import, shedding, storage content and loss, etc.

The finance data are similarly arranged, in two versions:

Each plant, dynamic; deliver data per plant in a dynamic structure.

Per technology, fixed format; deliver aggregated plants of same technology, but organised so

that the output columns always will be the same. This is suitable for post processing or checking in

Excel, for example.

Setting up the HYBRID simulation 42

Figure 63 Finance result to file output per technology and cost type etc.

The data shown in Figure 58 has had the columns broken in three parts to present the 167 columns

on one page.

Month

Electricity Price - System Import (energy) [EUR] All Wind - DevEx [EUR] All Other Green - DevEx [EUR]

Electricity Price - System Import (tax) [EUR] All Wind - CapEx [EUR] All Other Green - CapEx [EUR]

Electricity Price - System Import (tariff) [EUR] All Wind - OpEx [EUR] All Other Green - OpEx [EUR]

Electricity Price - System - Load Shedding (Wh) [Wh] All Wind - AbEx [EUR] All Other Green - AbEx [EUR]

Electricity Price - System - Load Shedding (EUR) [EUR] All Wind - Export [EUR] All Other Green - Export [EUR]

Electricity Price - System Import (Wh) [Wh] All Wind - Export subsidy [EUR] All Other Green - Export subsidy [EUR]

Electricity Price - All Import (energy) [EUR] All Wind - Export tax [EUR] All Other Green - Export tax [EUR]

Electricity Price - All Import (tax) [EUR] All Wind - Export tariff [EUR] All Other Green - Export tariff [EUR]

Electricity Price - All Import (tariff) [EUR] All Wind - Grid Curtailment [EUR] All Other Green - Grid Curtailment [EUR]

Electricity Price - All Import - Load Shedding (Wh) [Wh] All Wind - Price Curtailment [EUR] All Other Green - Price Curtailment [EUR]

Electricity Price - All Import - Load Shedding (EUR) [EUR] All Wind - Used in MicroGrid subsidy [EUR]

All Other Green - Used in MicroGrid subsidy

[EUR]

Electricity Price - All Import (Wh) [Wh] All Wind - Used in MicroGrid tariff [EUR]

All Other Green - Used in MicroGrid tariff

[EUR]

Electricity Price - System Export (energy) [EUR] All Wind - Used in MicroGrid tax [EUR]

All Other Green - Used in MicroGrid tax

[EUR]

Electricity Price - System Export (subsidy) [EUR] All Wind - [] All Other Green - []

Electricity Price - System Export (tariff) [EUR] All Wind - Purchase price [EUR] All Other Green - Purchase price [EUR]

Electricity Price - System Export (tax) [EUR] All Wind - [] All Other Green - []

All Wind - Account Depreciation [EUR]

All Other Green - Account Depreciation

[EUR]

Owners Capital - Primo [EUR] All Wind - Tax Depreciation [EUR] All Other Green - Tax Depreciation [EUR]

Cashflow - Primo [EUR] All Wind - [] All Other Green - []

Interest Owners Capital [EUR] All Wind - Grant Disbursement [EUR]

All Other Green - Grant Disbursement

[EUR]

Cashflow - Ultimo [EUR] All Wind - Loan Disbursement [EUR] All Other Green - Loan Disbursement [EUR]

Owners Capital - Ultimo [EUR] All Wind - Loan Instalment [EUR] All Other Green - Loan Instalment [EUR]

All Import - Owners Capital - Primo [EUR] All Wind - Loan Fees [EUR] All Other Green - Loan Fees [EUR]

All Import - Cashflow - Primo [EUR] All Wind - Loan Interest [EUR] All Other Green - Loan Interest [EUR]

All Import - Interest Owners Capital [EUR]

All Import - Cashflow - Ultimo [EUR] All PV - DevEx [EUR] All Black - DevEx [EUR]

All Import - Owners Capital - Ultimo [EUR] All PV - CapEx [EUR] All Black - CapEx [EUR]

Difference - Owners Capital - Primo [EUR] All PV - OpEx [EUR] All Black - OpEx [EUR]

Difference - Cashflow - Primo [EUR] All PV - AbEx [EUR] All Black - AbEx [EUR]

Difference - Interest Owners Capital [EUR] All PV - Export [EUR] All Black - Export [EUR]

Difference - Cashflow - Ultimo [EUR] All PV - Export subsidy [EUR] All Black - Export subsidy [EUR]

Difference - Owners Capital - Ultimo [EUR] All PV - Export tax [EUR] All Black - Export tax [EUR]

All PV - Export tariff [EUR] All Black - Export tariff [EUR]

All Demand - Income [EUR] All PV - Grid Curtailment [EUR] All Black - Grid Curtailment [EUR]

All Demand - Income (All import) [EUR] All PV - Price Curtailment [EUR] All Black - Price Curtailment [EUR]

All PV - Used in MicroGrid subsidy [EUR] All Black - Used in MicroGrid subsidy [EUR]

All Storage - DevEx [EUR] All PV - Used in MicroGrid tariff [EUR] All Black - Used in MicroGrid tariff [EUR]

All Storage - CapEx [EUR] All PV - Used in MicroGrid tax [EUR] All Black - Used in MicroGrid tax [EUR]

All Storage - OpEx [EUR] All PV - [] All Black - []

All Storage - AbEx [EUR] All PV - Purchase price [EUR] All Black - Purchase price [EUR]

All Storage - [] All PV - [] All Black - []

All Storage - Account Depreciation [EUR] All PV - Account Depreciation [EUR] All Black - Account Depreciation [EUR]

All Storage - Tax Depreciation [EUR] All PV - Tax Depreciation [EUR] All Black - Tax Depreciation [EUR]

All Storage - [] All PV - [] All Black - []

All Storage - Grant Disbursement [EUR] All PV - Grant Disbursement [EUR] All Black - Grant Disbursement [EUR]

All Storage - Loan Disbursement [EUR] All PV - Loan Disbursement [EUR] All Black - Loan Disbursement [EUR]

All Storage - Loan Instalment [EUR] All PV - Loan Instalment [EUR] All Black - Loan Instalment [EUR]

All Storage - Loan Fees [EUR] All PV - Loan Fees [EUR] All Black - Loan Fees [EUR]

All Storage - Loan Interest [EUR] All PV - Loan Interest [EUR] All Black - Loan Interest [EUR]

Grid Expansion - CapEx [EUR]

Grid Expansion - Account Depreciation

[EUR]

Grid Expansion - Tax Depreciation [EUR]

Grid Expansion - Grant Disbursement [EUR]

Grid Expansion - Loan Disbursement [EUR]

Grid Expansion - Loan Instalment [EUR]

Grid Expansion - Loan Fees [EUR]

Grid Expansion - Loan Interest [EUR]

Grid Expansion - All Import - CapEx [EUR]

Grid Expansion - All Import - Account Depreciation

[EUR]

Grid Expansion - All Import - Tax Depreciation

[EUR]

Grid Expansion - All Import - Grant Disbursement

[EUR]

Grid Expansion - All Import - Loan Disbursement

[EUR]

Grid Expansion - All Import - Loan Instalment

[EUR]

Grid Expansion - All Import - Loan Fees

[EUR]

Grid Expansion - All Import - Loan Interest

[EUR]

Indices 43

Below the “block overview”:

Block

Content

Electricity prices, System and Reference (All

Imported)

Cashflow and cash balance, System and Reference

Sale to demand, System and Reference

STORAGE

WIND

Other GREEN

BLACK

Grid expansion, System and Reference

A few explanations relating to the output:

There are two parallel results in the file, one for the MicroGrid (System), one for the Reference (All

imported). For the latter there are relatively few columns.

A special issue to explain:

A problem is that if the demand imports all energy, it will build up a negative cash balance year on

year. If interest is applied on a negative cash balance, there can be very high interest costs on the

cash balance for the “all imported” variant.

This would not be so in “real world”. Here the demand would pay the electricity bill year on year.

But to compare the reference to the MicroGrid interest costs on the cash balance, an accumulated

negative cash balance should be calculated for the reference to compare to the MicroGrid 1:1.

The negative cash balance is not accumulated for the reference and therefore does not get interest

costs for reference. (Except for possible grid reinforcement loan financed costs for the reference).

Similarly, we reduce the MicroGrid cash balance interest costs with the non-included reference

interest costs, so we get a 1:1 comparison.

The figures that give the difference cash balance and thereby basis for cash balance interest costs

are called “Difference_xxx” found in columns 29-33.

15.4 Indices

The index specifications can be reached from where they can be selected.

Figure 64 Indices can be selected in drop-down, or the "edit indices" chosen for defining new.

Indices 44

Figure 65 Development indices edit form.

Here any development index can be created, a fully free year by year value or a simple percentage

regulation per year.

This can be used for example for:

• Solar PV degradation – add index to production time-series

• Subsidy that is stopped after a number of years – add index to “energy value”

• Traditional inflation

For the traditional inflation a default index can be used, (which is the selected value for all financial

input fields, when starting a new calculation setup), and an index series can be chosen as the

default index and hence used for all financial development functions which are not selected

manually.

Figure 66 Overrule default inflation in a simulation.

At the setup tab, the default inflation can be overruled by a selected index. This makes it

convenient to test the impact of different inflation values.

Cost functions 45

Note that also cost functions have indices. The cost functions used will “take over” the default

index in a simulation if no manual selection is performed. This mean that the OPEX development by

default is controlled by the default index, for example.

15.5 Cost functions

Cost functions is a new very important “component” in windPRO. This makes it possible to scale all

plant costs by plant size and hence is suitable for optimizations.

The cost functions are documented in chapter 2.18 BASIS – cost functions.

The use of cost functions within HYBRID module are described in 15.3.11 Cost and lifetime.

15.6 Optimizer

A “simple” optimizer is established. This searches for the minimum lifetime costs by adjusting plant

sizes and/or storage sizes. By utilizing cost functions for the plants/storage and by making loans

linked directly to plants and scalable with investment, it is possible to find the “optimal” system.

The optimal system is identified as the system with lowest lifetime costs. There will always be

different opinions what is optimal. For example, 1 EUR might be saved by doubling the investment,

most would find this a bad idea. Hence the optimizer should be seen as a tool to help to identify

which directions to look into, including:

• Increase PV or decrease wind

• Increase storage volume or decrease charger

• Etc.

Based on the optimizer run, manual scaling modifications can be tested out where some common

sense can be included in the design. Remember also that the optimizer scales costs and production

linearly with plant sizes. This will not be fully real, if there is a limited area for a wind farm, for

example. Adding extra turbines will also likely increase wake losses and hence a linear increase in

production with plant size will not be seen.

Figure 67 Example simulation, PV-plant produces more than demand.

In Figure 66, the PV-plant produces 572 MWh/y and demand is 500 MWh/y. This “base setup” is

not feasible. NPV is negative but and the lifetime costs are 5% lower with PV plant than if “All

imported”. A challenge for the optimizer would be: How much smaller should the PV plant be to

make the project feasible.

Optimizer 46

Figure 68 Optimizer find the most feasible plant size to 44% of the original plant size.

By running the optimizer, the PV-plant is reduced from 510 kW to 226 kW. Lifetime costs are

reduced from 1.23 million EUR to 1.08 million EUR. Clicking on OK will return the new PV plant size

to the main window:

Figure 69 Overview with reduced (Optimized) PV-plant size.

The simulated total costs for the MicroGrid are 17% less than by “All imported”. NPV is 119 kEUR

and IRR 7.5%. This seems to be a reasonably good investment.

Will storage improve the returns even more?

Storage of 50 kW with Charger/discharger of 15 kW is added with a default cost function. No

financing, meaning the Owner cash finances the storage.

A first simulation show this is a slightly poorer investment than without storage. Irr 6,8%. Now we

run the optimizer, where the combined PV-plant size and storage is optimized.

Optimizer 47

Figure 70 Optimizer concludes the battery is too expensive.

Now PV plant size as well as storage is optimized. It takes quite some time while this is somewhat

more complex. The result is that the optimizer finds the storage too expensive and ends with an

optimized size of 0. And the optimized PV-plant size is the same as previous.

Now a Grant is introduced. It is assumed that a Grant of 75% of the Storage costs can be obtained.

Then the optimizer is re-run:

Figure 71 Optimised storage 75% Grant financed.

Now the optimizer finds that the Storage will be optimal by 100 kWh (reach the set limit of scale

factor 2), with charger of 15.9 kW and discharger of 7.4 kW. The PV-plant size increases from 37%

to 49% of its original size.

Optimizer 48

Figure 72 Costs for MicroGrid with storage.

The costs for MicroGrid as well as the NPV are now almost the same as when just having the

optimized PV-plant. It is not clear whether this option would be chosen from a pure investment

point of view but it might be chosen as it introduces higher system flexibility and potential

additional gains by having the storage – although this also comes with higher risks. It is now very

fast to test modifications. The result graphs can help pointing the user in the right directions.

Figure 73 Storage filling indicates the storage is some too large.

For the example shown above, Figure 72 shows 70% of the time the storage is empty. This

indicates that it would be better with a smaller storage. When supporting a PV-Plant in a Northern

Europe country storage will have many hours empty due to the long winter period with very little

Sun.

OPTI-Storage 49

Figure 74 The result shows that 4% of the demand is taken from storage. 7.5% of production filled

on storage.

15.7 OPTI-Storage

Figure 75 OPTI-storage will run a new simulation, that optimizes the storage operation.

Starting from windPRO 3.6 it is possible to use the OPTI-Storage tool. This tool can simulate an

optimal operation of the storage, where it partly:

1. Purchases electricity when it is cheap and sells when it is expensive (called arbitrage).

2. Prepare the storage for minimizing the grid limit curtailment, making sure storage is empty

before a period with high production leading to grid curtailment.

Basically, the OPTI-Storage operates the storage for maximizing earnings. If there is a conflict

between arbitrage and reduced grid curtailment, the optimizer choses the solution that maximizes

earnings. The engine behind the OPTI storage is a MILP solver.

To be able to operate the Storage similarly in “real life” good prognoses of production and prices

must be available. This is although not a major problem with the prognosis tools on the market

today. But there will also be a need for an advanced controller.

Using OPTI-Storage will create a new “Result Graph”:

(Based on modified data relative to previous example to illustrate partly with demand, partly

without (all exported)):

OPTI-Storage 50

Figure 76 Result graph shows OPTI-Storage benefit where a demand is covered.

In the graph above it is shown where the charged energy comes from and where it goes to. As

seen in the example to the left, there are more Charged MWh than discharged, due to loss in

storage. But for the right-side graph showing the value of the MWh, the discharge has a higher

value than the value of the charged. This is mainly because charging happens when prices are low,

and discharging happens when prices are high. In the example above the lifetime earnings by the

storage is round 20.000 EUR, with an expected investment and lifetime OPEX costs of storage of

30.000 EUR. But this is based on 2019 electricity prices, much has changed since.

In the example above the main purpose is fulfilling a demand, and the export from storage is

limited, while most discharge is absorbed by the demand. In a situation where all is exported the

gain by OPTI-storage operation only will be increased export, see example below:

Figure 77 Benefit by OPTI-storage operation where all is exported.

As seen in the graphic above the value of the discharge-charged is roughly the same as in the

situation with a demand. What although can add more value with a demand is saved taxes and

tariffs, which can bring feasibility in a storage investment, even with 2019 prices.

Reports 51

Figure 78 Viewing the difference OPTI-storage minus non opti.

The result table have a feature to view the difference between OPTI-storage and non opti storage

operation. Above is seen in the “total” field, how the OPTI storage operation generates 24.000 EUR

extra. This comes from 54.000 more export from storage, reduced with 3.000 less direct export

from PV (which is charged on storage) and reduced with added import from grid at a cost of 27.000

which is purchased electricity for the storage when price is low. The NPV is improved by 18.000

EUR.

The improvement by OPTI-storage is quite individual much affected by the price variations hour to

hour, the grid limitations, and the production variations. But no doubt it pays off to have an

advanced controller that can operate the storage close to optimal for maximizing earnings.

Limitations in present version of OPTI-Storage

Price curtailment is always calculated based on negative prices. Setting another value in the above

field, would not be respected fully due to predefined threshold within the optimizer. Therefore, the

price threshold must be zero before running the OPTI-Storage.

The shedding filler cannot be used along with OPTI-Storage.

The optimizer will not work in combination with OPTI-Storage.

15.8 Reports

Reports 52

The reports are built with similar structure as in other windPRO modules:

Figure 79 Report overview.

Double click on a sub report and get a preview.

Right click ->

By “Properties” options such as report language can be chosen, if multiple language modules are

installed. And for some reports with more pages, such as Plant Overview, the specific plants to be

reported can be selected.

Report contents

There are following reports from HYBRID module:

Main Results – with assumptions and main results

Energy Balance – the simulations time step by time step aggregated as annual values with

additional aggregated lifetime graphs.

Cash flow by technology – for each technology; Wind, PV, Other green, Black, Storage and grid

reinforcement, the cash flow is shown year by year. All payments in/out are aggregated by each

technology, including export, value of curtailments (if any), subsidies, taxes, tariffs related to

where energy is used, DEVEX, CAPEX, OPEX, ABEX and loan reimbursements, instalments,

interests, and fees. Grants are deducted. Also purchase of energy from external plants is included if

any.

Accounting balance – in opposite to cash flow, accounting balance holds depreciation of CAPEX

instead of CAPEX - reimbursements and loan instalments. In other words, the CAPEX is expressed

by the value reduction by year instead of the actual payments related to the CAPEX and then

expresses how the accounting will look in real life (as budget).

Plant Budget Costs – for each plant or storage a page shows how the costs based on cost

functions are established.

Indices – the used indices in the calculations are reported.

Abbreviations/explanations 53

Energy cost overview – shows the often-complex matrix of energy prices, subsidies, tariffs and

taxes that can depend on as well technology as where the energy is used.

Plant overview – shows the calculated plant configuration with key figures per technology.

Figure 80 Example from a report, illustrated in Optimize section, cash flow by technology.

Figure 75 shows how the costs for the MicroGrid will be somewhat higher than the “All import”

alternative for the first 10 years, where the loans are paid back, then it becomes lower.

The extra costs are round 5.000 EUR per year for the first 10 years, and from year 10

approximately 20.000 EUR less.

15.9 Abbreviations/explanations

DEVEX; Development expenditures

CAPEX; Capital expenditures

OPEX; Operational expenditures

ABEX; Abandonment expenditures

Shedding; Demand that is not fulfilled due to lack of grid or production capacity

Curtailment; When production is larger than can be used by demand/storage/export due to grid

limitations or if a plant is shut down due to low (negative) energy prices. Note curtailment shut

down can also be included in a PARK calculation, e.g. by sector management (closing turbines

down when too densely spaced in certain wind directions). If included in a PARK calculation, the

relevant time steps will have reduced production. This is not “seen” as curtailment by the HYBRID

calculation, where only the reductions due to the HYBRID simulation will be accounted for.

 List of figures  54
 
  © EMD International A/S  •   www.emd.dk   •   windPRO 4.1    •   September 2024   
15.10  List of figures 
Figure 1 The demand is inside the MicroGrid. .......................................................................... 3 
Figure 2  The demand is outside the MicroGrid. ....................................................................... 4 
Figure 3 There are no demand, all exported. ........................................................................... 5 
Figure 4 The HYBRID Calculation tab or "controller". ................................................................ 6 
Figure 5 Selection of "Basic" calculation vs. Flexible Operation Periods. ...................................... 6 
Figure 6 Example of import filter in METEO object for electricity prices. ...................................... 8 
Figure 7 In Data setup, select relevant signals. Height irrelevant, but a “dummy” value must be 
entered. ............................................................................................................................. 8 
Figure 8 Loading time-series and setting scale factors, if relevant. ............................................. 9 
Figure 9 After simulation, the raw costs are seen. .................................................................. 10 
Figure 10 Changing the simulation year will change demand as well as production and prices. ..... 10 
Figure 11 Selection of cost function. ..................................................................................... 11 
Figure 12 First simulation result, only wind production included. .............................................. 11 
Figure 13 Selection of "Basic" calculation vs Flexible operation periods. ..................................... 12 
Figure 14 Calculation setup collects different decision requirements. ......................................... 13 
Figure 15 Example of depreciation handling with remaining lifetime of a component. .................. 14 
Figure 16 Selection of index used as project default. ............................................................... 15 
Figure 17 Alternative inflation for "fast test". ......................................................................... 15 
Figure 18 Select units to handle small-medium-large projects. ................................................. 16 
Figure 19 Selection of currencies. ......................................................................................... 16 
Figure 20 Add currencies from ISO 4217 list. ......................................................................... 17 
Figure 21 Currency list updated with selections. ..................................................................... 17 
Figure 22 Manual update is registered in list with USER source. ................................................ 18 
Figure 23 External grid / import cost specifications. ................................................................ 18 
Figure 24 Form for entering time depending tariffs. ................................................................ 19 
Figure 25 Peak hours on Monday to Friday with higher tariff, Sundays, and holidays with lower. .. 19 
Figure 26 Online Holidays, with subdivision for some countries, like Germany. ........................... 20 
Figure 27 The edit holidays form after online import. .............................................................. 20 
Figure 28 Period cost summary. ........................................................................................... 21 
Figure 29 PARK calculation setup with features marked important for HYBRID. .......................... 22 
Figure 30 Loss specifications in Solar-PV calculation................................................................ 23 
Figure 31 Creation of a degradation index. ............................................................................ 23 
Figure 32 Selection of degradation index. .............................................................................. 23 
Figure 33 Buttons marked with METEO object symbols require data loaded in METEO objects. ..... 24 
Figure 34 Left, if no match is found, right if relevant data is found. ........................................... 24 
Figure 35 Fixed price time-series. ......................................................................................... 24 
Figure 36 Shedding filler specification. .................................................................................. 25 
Figure 37 Loss deduction in PARK calculation. ........................................................................ 25 
Figure 38 Storage specifications. .......................................................................................... 26 
Figure 39 Storage demand analyser for selection of charge and discharge capacity needed. ........ 27 
Figure 40 Re-evaluation of charge/discharge selections. .......................................................... 27 
Figure 41 Adding a cost function. ......................................................................................... 28 
Figure 42 Establish new cost function. ................................................................................... 28 
Figure 43 Selected cost functions. ........................................................................................ 28 
Figure 44 The cost function gives a first rough budget for the technology. ................................. 29 
Figure 45 Adding loans. ....................................................................................................... 29 
Figure 46 Main loan specifications. ........................................................................................ 30 
Figure 47 Detailed loan specification. .................................................................................... 30 
Figure 48 Input of energy value for export etc. ...................................................................... 31 
Figure 49 Index for each cost available by “Show Cost Development”. ...................................... 32 
Figure 50 Sale to demand price if demand outside MicroGrid. ................................................... 32 
Figure 51 The scaled input data............................................................................................ 32 
Figure 52 Energy balance simulation time-series. ................................................................... 33 
Figure 53 The Balance by Demand and Production. ................................................................. 34 

 List of figures  55
 
  © EMD International A/S  •   www.emd.dk   •   windPRO 4.1    •   September 2024   
Figure 54 Storage utilization graph. ...................................................................................... 35 
Figure 55 Month/day Energy overview. ................................................................................. 36 
Figure 56 The Production Use. .............................................................................................. 36 
Figure 57 Unfulfilled by MicroGrid to evaluate expansion options. ............................................. 37 
Figure 58 Result to file output. ............................................................................................. 38 
Figure 59 Debug data folder with all relevant data from simulation. .......................................... 38 
Figure 60 Result to file output to clipboard or file.................................................................... 38 
Figure 61 Energy balance data in text file. ............................................................................. 39 
Figure 62 The columns (53) in energy balance simulation. ....................................................... 40 
Figure 63 Finance result to file output per technology and cost type etc. ................................... 42 
Figure 64 Indices can be selected in drop-down, or the "edit indices" chosen for defining new. .... 43 
Figure 65 Development indices edit form. .............................................................................. 44 
Figure 66 Overrule default inflation in a simulation. ................................................................ 44 
Figure 67 Example simulation, PV-plant produces more than demand. ...................................... 45 
Figure 68 Optimizer find the most feasible plant size to 44% of the original plant size. ................ 46 
Figure 69 Overview with reduced (Optimized) PV-plant size. .................................................... 46 
Figure 70 Optimizer concludes the battery is too expensive. .................................................... 47 
Figure 71 Optimised storage 75% Grant financed. .................................................................. 47 
Figure 72 Costs for MicroGrid with storage. ............................................................................ 48 
Figure 73 Storage filling indicates the storage is some too large. .............................................. 48 
Figure 74 The result shows that 4% of the demand is taken from storage. 7.5% of production filled 
on storage. ........................................................................................................................ 49 
Figure 75 OPTI-storage will run a new simulation, that optimizes the storage operation. ............. 49 
Figure 76 Result graph shows OPTI-Storage benefit where a demand is covered. ....................... 50 
Figure 77 Benefit by OPTI-storage operation where all is exported............................................ 50 
Figure 78 Viewing the difference OPTI-storage minus non opti. ................................................ 51 
Figure 79 Report overview. .................................................................................................. 52 
Figure 80 Example from a report, illustrated in Optimize section, cash flow by technology. .......... 53 
 
 