Market Access for Smaller Size Intelligent Electricity Generation (MASSIG)
Gain and loss analysis
of
small RES and CHP participating
in
selected market options
Task 5.1
Version:
ver. 4.0a (2010-07-25)
Authors:
Tomasz Siewierski,
Company:
Institute of Electrical Power Engineering, Technical
University of Lodz (TUL Lodz)
Stefanowskiego Street, 18/22
90-924 Lodz, Poland
Address:
E-mail :
t.siewierski@p.lodz.pl
Belongs to:
EIE/07/164/SI2.467618 - MASSIG
Reviewer:
Thomas Erge, Fraunhofer-Institut für Solare
Energiesysteme ISE
Disclaimer
The sole responsibility for the content of this report lies with the authors. It does not
represent the opinion of the Community. The European Commission is not responsible
for any use that may be made of the information contained therein.
Abstract
In the Work Package WP5 of the MASSIG project different market options, which are
currently available for small RES and CHP producers and which have been indicated as the
most promising in the Work Package WP2 and feasible from the technical point of view (see
WP2, WP3) were here evaluated from an economic point of view.
In the Task 5.1 of WP5 various approaches for gain and loss evaluation have been studied
and a simple Excel spreadsheet tool, which helps to collect and arrange market data and to
conduct comparative cash-flow analysis, has been developed. Within a single calculation
spreadsheet it is possible to study medium and long term feasibility of different electricity and
ancillary service market options in different electricity market structures and operation
modes. The cash-flow analysis accounts for fixed and variable market participation costs
(direct and indirect participation options), financial risk in the balancing market linked to poor
forecasting and scheduling of generating units (wind power and PV), clustering and the use
of storage technologies to mitigate such risk, market lost opportunity cost linked with the
installed capacity dedicated to regulating and reserving services (for example tertiary
control). As the tool focuses on medium and long term (one year, a couple of years)
feasibility studies, it does not deal with everyday optimization of power plant’s bidding
strategies.
The tool has been applied to economic feasibility study of day ahead and intraday (if
applicable) power exchange spot market participation of real plants, like small CHP (single
plants in Denmark and Poland, cluster of small CHP units in Germany), cluster of small PV
installations in Germany, single wind plant in Poland and made-up test cases, like cluster of
wind farms in the UK or two small hydro plants in Germany. For CHP plants additional
market options concerning participation in the tertiary control were also analysed.
For the testing of the tool and evaluation methodology market data from energy and ancillary
services markets from Denmark, Germany, Poland and the United Kingdom were collected
over a period of one year (2008).
The results of the gain-loss evaluation show that for most of RES generating technologies, at
their current state of development, simple market option is not economically feasible. For the
most expensive RES technologies (e.g. photovoltaics) profits guaranteed by the current level
-2-
of feed-in tariffs exceed those which can be earned in the competitive electricity markets. For
the most competitive (from the investment point of view: wind technology), the imbalance
cost incurred in the balancing market often eliminates financial benefits derived from the
price arbitrage between feed-in tariff or must-take contracts and the wholesale electricity
markets.
In the light of conducted studies the co-generation is the undisputed competitive market
leader. Small CHP units can successfully participate both in the energy and ancillary service
markets. The degression of CHP support schemes (e.g. KWKG in Germany) reliability and
excellent operation parameters, especially when combined with fuel (e.g. biogas) or thermal
(heat) storage facilities attributes to this success.
This report presents results of the gain-loss evaluation of several test cases of small RES
and CHP plants participating in competitive wholesale market options. It combines together
information which were originally divided in the MASSIG proposal into public Deliverable 5.1
and confidential Deliverable 5.2, which was intended to deal with sensitive information. Since
all data used in test cases is public and results are not restricted by owners of the plants, all
information can be included in Deliverable 5.1 and therefore it was not necessary to prepare
confidential Deliverable 5.2.
Instead of Deliverable 5.2 TUL has prepared additional Deliverable 5.3 (Trend analysis for
factors influencing costs and revenues) which was not included in the MASSIG contract
and which extends the gain-loss evaluation into the nearest future taking into consideration
expected changes in the regulatory frameworks, market structures and operations or
electricity price trends.
-3-
1
INTRODUCTION ................................................................................................. 7
2
METHODOLOGY ................................................................................................ 8
3
TESTING ........................................................................................................... 13
3.1
A cluster of small cogeneration plants in Germany ............................................................ 13
3.2
A PV cluster in Germany......................................................................................................... 21
3.3
A small hydro plant in Germany ............................................................................................ 25
3.4
An example of a small biogas cogeneration plant in Poland ............................................. 27
3.5
An example of a small biogas cogeneration plant in Denmark .......................................... 31
3.6
An example of a single wind farm in Poland ........................................................................ 36
3.7
A wind farm cluster in the United Kingdom.......................................................................... 40
4
CONCLUSIONS ................................................................................................ 42
5
FINAL REMARKS ............................................................................................. 43
6
REFERENCES .................................................................................................. 44
-4-
LIST OF TABLES
TABLE 1. BADENOVA CHP PLANTS INCLUDED IN THE MASSIG TEST CASE.................................................. 14
TABLE 2. THE RESULTS OF THE GAIN-LOSS EVALUATION FOR THE PARTICIPATION OF THE CLUSTER OF CHP
UNITS IN THE POWER EXCHANGE DAY AHEAD SPOT MARKET................................................................ 17
TABLE 3. THE RESULTS OF THE GAIN-LOSS EVALUATION FOR THE PARTICIPATION OF THE CLUSTER OF CHP
UNITS IN THE POWER EXCHANGE INTRADAY SPOT MARKET. ................................................................. 17
TABLE 4. THE RESULTS OF THE GAIN-LOSS EVALUATION FOR THE PARTICIPATION OF THE CLUSTER OF CHP
UNITS IN THE TERTIARY CONTROL MARKET. UPWARD REGULATION. ..................................................... 17
TABLE 5. THE RESULTS OF THE GAIN-LOSS EVALUATION FOR THE PARTICIPATION OF THE CLUSTER OF CHP
UNITS IN THE TERTIARY CONTROL MARKET. DOWNWARD REGULATION................................................. 19
TABLE 6. INSTALLED CAPACITY AND DISTANCES BETWEEN PV PLANTS IN THE MASSIG PV TEST CASE. ....... 22
TABLE 7. THE RESULTS OF THE GAIN-LOSS EVALUATION FOR THE PARTICIPATION OF THE PV CLUSTER IN THE
EEX DAY AHEAD SPOT MARKET. ....................................................................................................... 22
TABLE 8. THE RESULTS OF THE GAIN-LOSS EVALUATION FOR THE PARTICIPATION OF THE PV CLUSTER IN THE
EEX INTRADAY SPOT MARKET........................................................................................................... 23
TABLE 9. THE RESULTS OF THE GAIN-LOSS ANALYSIS FOR OLDER SMALL HYDRO PLANTS PARTICIPATING IN THE
EEX DAY AHEAD SPOT MARKET. ....................................................................................................... 26
TABLE 10. THE RESULTS OF THE GAIN-LOSS ANALYSIS FOR NEWER SMALL HYDRO PLANTS PARTICIPATING IN
THE EEX DAY AHEAD SPOT MARKET.................................................................................................. 27
TABLE 11. THE RESULTS OF THE GAIN-LOSS ANALYSIS FOR CHP PLANT TRADING ITS OUTPUT IN THE POLISH
DAY AHEAD SPOT MARKET................................................................................................................. 30
TABLE 12. THE RESULTS OF THE PARTICIPATION OF A SMALL DANISH CHP PLANT IN THE NORD POOL DAY
AHEAD MARKET. ............................................................................................................................... 33
TABLE 13. THE RESULTS OF THE PARTICIPATION OF A SMALL DANISH CHP PLANT IN THE NORD POOL
INTRADAY MARKET. .......................................................................................................................... 33
TABLE 14. THE RESULTS OF THE PARTICIPATION OF A SMALL DANISH CHP PLANT IN THE ANCILLARY SERVICES
MARKET. TERTIARY CONTROL, UPWARD REGULATION......................................................................... 35
TABLE 15. THE RESULTS OF THE PARTICIPATION OF A SMALL DANISH CHP PLANT IN THE ANCILLARY SERVICES
MARKET. TERTIARY CONTROL, DOWNWARD REGULATION.................................................................... 35
TABLE 16. INSTALLED CAPACITY AND DISTANCES BETWEEN WIND PLANTS IN THE MASSIG WIND TEST CASE
[KM]. ............................................................................................................................................... 40
TABLE 17. RECENTLY INTRODUCED FEED-IN TARIFFS IN THE UK DEPEND ON THE SIZE OF THE WIND PLANT ... 41
TABLE 18. THE RESULTS OF THE GAIN-LOSS EVALUATION OF THE WIND CLUSTER IN THE UK. ....................... 41
-5-
LIST OF FIGURES
FIGURE 1. THE STRUCTURE OF ELECTRICITY MARKET SEGMENTS. ................................................................ 7
FIGURE 2. VARIOUS COMPONENTS OF THE CASH-FLOW RELATED TO ELECTRICITY SPOT, ANCILLARY SERVICES
AND PROPERTY RIGHTS TRADING. ....................................................................................................... 9
FIGURE 3. THE FLOW-CHART OF THE MASSIG GAIN-LOSS EVALUATION TOOL. ............................................ 12
FIGURE 4.VARIOUS SOURCE OF INCOME FOR DIFFERENT MARKETING OPTIONS FOR SMALL CHP PLANTS IN
GERMANY........................................................................................................................................ 14
FIGURE 5. BIOGAS FIRED DIESEL ENGINES INSTALLED IN SMALL CHP PLANTS CAN BE PROVIDERS OF
DIFFERENT NETWORK SERVICES (E.G. BALANCING POWER, VOLTAGE REGULATION, ETC.). A HEAT AND
POWER GENERATING UNIT AT FRIESENHEIM CHP POWER PLANT. ....................................................... 20
FIGURE 6. PV PANELS BECOME POPULAR AND FASHIONABLE ELEMENTS OF MODERN CITY ARCHITECTURE. AN
EXAMPLE FACADE INTEGRATED PV INSTALLATION AT SOLAR FABRIK, FREIBURG, GERMANY. ............... 21
FIGURE 7. A COMPARISON OF PROFITS GAINED BY THE PV IN THE EEX DAY AHEAD SPOT MARKET AND FROM
THE FEED-IN TARIFFS. PERFECT FORECAST, NO LOWER OFFER VOLUME LIMIT AND DIRECT TRADING (NO
BROKER COST)................................................................................................................................. 24
FIGURE 8. A COMPARISON OF PROFITS GAINED BY THE PV IN THE EEX DAY AHEAD SPOT MARKET AND FROM
THE FEED-IN TARIFFS. IMPERFECT FORECAST, NO LOWER OFFER VOLUME LIMIT AND DIRECT TRADING
(BROKER SERVICES)......................................................................................................................... 24
FIGURE 9. AN EXAMPLE OF SMALL HYDRO POWER PLANT IN BAD GASTEIN, AUSTRIA.................................... 25
FIGURE 10. BIRD EYE VIEW ON THE WASTEWATER TREATMENT COMPANY IN ŁÓDŹ. BIOGAS STORAGE TANK OF
2500M3 CAN BE SEEN IN THE BACKGROUND....................................................................................... 28
FIGURE 11. MONTHLY BALANCE BETWEEN ELECTRICITY GENERATION AND CONSUMPTION. .......................... 29
FIGURE 12. AN EXAMPLE OF INTERMITTENT DAILY BIOGAS PRODUCTION PROFILE AT GOS. .......................... 31
FIGURE 13. THE TIME-OF-DAY TARIFF FOR SMALL CHP PLANTS (BLUE – WINTER SEASON, RED – SUMMER
SEASON).......................................................................................................................................... 32
FIGURE 14. AN EXAMPLE OF A SMALL (1MW) CHP PLANT WITH INSTALLED THERMAL STORAGE FACILITY OF
300M3 (APPROXIMATELY 12.5MWHTHERMAL). ....................................................................................... 34
FIGURE 15. AN EXAMPLE OF OPTIMISATION OF THE TEST CASE PLANT HOURLY SCHEDULING AND THERMAL
STORE FACILITY OPERATION PLANNING USING ENERGYPRO SOFTWARE. ............................................. 36
FIGURE 16. THE POLISH WIND TEST CASE. SINGLE WIND FARM OF 30MW................................................... 37
FIGURE 17. THE RESULTS OF THE WIND FARM PARTICIPATION IN THE DAY AHEAD POWER EXCHANGE MARKET.
PERFECT FORECAST, NOW LOWER OFFER VOLUME LIMIT AND NO BROKER COSTS INCLUDED. ............... 38
FIGURE 18. THE RESULTS OF THE WIND FARM PARTICIPATION IN THE DAY AHEAD POWER EXCHANGE MARKET.
IMPERFECT FORECAST, 1MW OFFER LOWER LIMIT AND BROKER COST INCLUDED. ............................... 39
FIGURE 19. COMPARISON OF IMBALANCE COST OF A SINGLE POLISH WIND FARM UNDER A TWO-PRICE (2008)
VS. ONE-PRICE (2009) BALANCING MARKET SETTLEMENT [3]. ............................................................. 40
FIGURE 20. AN INCREASE OF DISTANCES BETWEEN WIND FARMS DECREASES CORRELATION AND AMPLIFIES
CLUSTERING EFFECT (REDUCTION OF FORECAST ERRORS AND REDUCTION OF IMBALANCE COSTS)....... 42
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1 Introduction
In the past small power producers generating electricity from renewable sources and small
CHP units gained their income from regulated and risk free RES and CHP support schemes
(feed-in tariffs - FIT, “green” or “red” certificates - TGC). With the currently observed gradual
degression of FIT and TGC remuneration and the growing competition among RES and CHP
(both regarding grid and support fund access) “business as usual” approach is no more
technically and economically feasible. Small power producers are expected to consider
alternative, competition based trading options and to face the risk of economic losses. The
losses are usually caused by the natural volatility of prices in the liberalised electricity market
and limited predictability and controllability of some RES generating technologies or small
heat demand driven CHP.
Figure 1. The Structure of electricity market segments.
The goal of the task 5.1 was an economic analysis of market participation options available
for smaller power producers and identified in the Work Package WP2.
To conduct the analysis a simple Excel-based calculation spreadsheet has been developed
where profits gained using competitive market options are compared with the regulated
guaranteed income from RES support schemes. The tool was then tested using real market
-7-
data and production data from real test sites and made-up cases located in four different
countries (Denmark, Germany, Poland and the United Kingdom). Both energy market and
ancillary service market participations were tested. For energy markets prices from power
exchange day ahead and intraday trading floors were used as the reference price. For
balancing markets and ancillary service markets prices published by the TSO were applied.
Accounting for seasonality and medium term power price fluctuations data of at least one full
year should be used for this kind of market options, but extended period of time for the
analysis should increase the credibility of results and mitigate the financial risk
2 Methodology
Economics offer different methods for the assessment of the profitability of investments in
competitive markets and for the measurement of the related financial risk. Among the most
popular, SPBT (Simple Payback Time), NPV (Net Present Value), IRR (Internal Rate of
Return), VAR (Value-at-Risk) and PAR (Profits-at-Risk) should be mentioned here.
Most of these methods require general economic parameters and historical data to calibrate
and fuel the calculation engines. They are usually based on discounted cash-flows including
incomes and expenses distributed in time. Some of them may apply to the calculations of
further profits and losses in either deterministic or stochastic methodology. In the end these
powerful tools are rather complicated for an untrained user and require considerable
expertise, as well as, wide range of data. This is why for the purposes of the MASSIG project
the financial analysis and the assessment of potential gains or losses resulting from the
switching from a safe RES support scheme to energy and ancillary service competitive
market, a simple and intuitive tool had to be developed.
On the other hand, the tool must account for a variety of electricity market structures and
operations and national market peculiarities (for example three different length of the
settlement period, 15 minutes in Germany, 30 minutes in the UK and 60 minutes in Denmark
and Poland). It should also include basic market strategies available for smaller power
producers, such as the clustering (aggregation of RES or CHP connected to the grid at
different geographical locations) and the use of fuel or energy storage facilities, which
facilitate more sophisticated and profitable trading strategies in different market segments.
With no significant upfront investment cost and limited period of the analysis, the cash
discounting might be neglected and calculations are based on real (undiscounted)
cash-flows.
-8-
Figure 2. Various components of the cash-flow related to electricity spot, ancillary services and
property rights trading.
The structure of the modern electricity market is rather complicated and puts together
different commercial and engineering activities (see Figure 1). The activities are linked with
fixed or variable costs and fixed or variable source of income (see Figure 2). In this way
selection of any particular market option generates particular cash-flow pattern (cash-flow
structure), which has to be quantified to assess the economic feasibility of the considered
option.
The gain-loss evaluation tool includes the following cash-flow components linked both with
the RES/CHP support scheme remuneration, as well as, with income and costs related to the
participation in different segments of the competitive market:
ƒ
Feed-in tariff payment for electricity exported to the grid - variable component
applicable to countries where FIT system has been implemented. This component is
used for the comparison with alternative competitive market options.
-9-
ƒ
Guaranteed payment for electricity collected by the last resort supplier within a must
take contract1. This solution is usually in use in countries which implemented TGC
systems, and it is a variable component.
ƒ
Income from the competitive energy market. Because OTC (Over-The-Counter,
bilateral) market data is usually hardly available, electricity prices from two trading
floors of power exchanges (day ahead and intraday) are used (variable component).
ƒ
Financial gains and losses from the balancing market, which are caused either by
uninstructed deviations from the submitted contract positions (generation schedules)
or by the minimum offer volume which can be traded via power exchange. Units
which submitted generation schedule that in the particular deliver period exceeds the
real generation are charged using System Buy Price (SBP) and suffer from negative
cash-flow component. Units which submitted generation schedule that in the
particular delivery period is smaller than the actual production are paid for the
exported energy surplus using System Sell Price (SSP). In the last case the positive
cash-flow component rarely compensates opportunity lost in the energy market as
spot market price is usually higher than the balancing market SSP. Imbalance cost
belongs to the variable components of the cash-flow.
ƒ
Availability payments for the contracted ancillary services (e.g. tertiary control). This
income could be earned by generating units actively participating in the ancillary
service markets (run by the TSO or DSO). Units, which during the power system
operation planning, have been chosen by the operator for delivering ancillary services
have to reserve certain amount of their available capacity for regulation and
reserving. They are paid “stand-by premium”, which is expected to compensate
energy market lost opportunity cost (explained below) and additional expenses
incurred by the producer on installation and maintenance of an additional equipment
(control systems, ITC systems). Availability payments belong to variable components
of the cash-flow as they depend on the amount of installed generating capacity
allocated to regulation and reserving services.
ƒ
Usage payments for contracted ancillary services (e.g. tertiary control). When
generating units selected for the provision of ancillary services (thus entitled to
availability payment described above) are in real time called by the DSO/TSO and
participate in system balancing, voltage regulation, frequency regulation, etc. they are
1
Unless there are transmission constraints, must take contract obliges the last resort supplier to
collect all electricity generated by RES or CHP plant.
- 10 -
paid usage price, which is expected to compensate additional expenses incurred
during regulation (additional wear-and-tear costs) and in some cases also
remuneration for by-product energy exported to the grid (alternatively this energy
might be settled in the balancing market). Usage payment is a variable cash-flow
component.
ƒ
Energy market lost opportunity cost that is linked with the reserved generating
capacity for upward regulation, for example, in the case of the tertiary control or the
balancing market participation. Being selected for the provision of regulation and
reserving services power producers exclude part of their installed capacity from
bidding into the spot market. This decision usually results in the decrease of market
income and this is reflected in the calculations with negative, variable cash flow
component.
ƒ
Participation in the energy or ancillary service markets may require replacing the old
metering systems and installation of a new ITC systems. Such investments create
additional fixed, non-recurrent negative cash flow component.
ƒ
Power exchange entrance fee, annual membership fee and trading costs are
negative, both recurrent (annual) and non-recurrent (entrance cost) fixed and variable
cash flow components respectively.
A detailed flow-chart for the calculation of gains and losses is shown in Figure 3 below.
For the energy market the developed tool calculates the difference between profits gained
from RES or CHP support schemes (in case of FIT) or from must take contracts (in case of
TGC system) and those which might be earned trading plants’ output using one or more
available energy market options. For the participation in the ancillary services market (mainly
tertiary control), where the final financial result depends on capacity and energy volume
during the real time control of the power system accepted by the TSO/DSO, the tool
calculates maximum and minimum possible profits and losses.
- 11 -
Start
Input Plant Data
Input Energy Market Data
Input information on RES
support schemes
Select marketing options
Select trading periods
Calculate the income
from fee-in
tariff/contract
Forecast
based?
Calculate profit from
support schemes (TGC,
AGU, KWKG)
Yes
Yes
Calculate aggregated
forecast error
Cluster?
No
No
Calculate individual
forecast errors
Partticipation
in AS
(TC/BM)
market?
Yes
Upward
regulation?
Calculate BM
profits/losses
Yes
Reserve regulation
power
No
Calculate direct income from AS market
(Availability Payment, Usage Payment)
Energy volume that will be traded at
the spot market
Energy volume that might be traded at
AS market
Calculate energy market lost
opportunity cost
Calculate profit from support schemes
(TGC, AGU, KWKG)
Calculate support schemes (TGC,
AGU, KWKG) lost opportunity cost
Offer bigger
than minimum
volume?
No
Rejected volume (to be settled at the
balancing market)
Yes
Volume traded at the spot market
Calculate income from the surrplus at
the balancing market
Calculate income from the spot
market (Day Ahead, Intraday)
+/-
Calculate the final financial balance
Display results
Stop
Figure 3. The flow-chart of the MASSIG gain-loss evaluation tool.
- 12 -
+/-
Calculate total max & min income
from the AS market
(upward regulation, downward
regulation)
The tool focuses on medium and long term (one year, a couple of years) feasibility studies,
so it does not deal with everyday optimization of power plant’s market strategies. To keep the
analysis simple and limit the scope of the essential data it is assumed that the historical
production profile of a small unit will not be affected after entering the competitive market.
For the short term optimisation of RES and CHP participation strategy in the energy or
ancillary service market special tools, such as EnergyPro developed by the EMD, should be
used (www.emd.dk). These tools allow preparation of detailed biding strategies in different
market segments making use of fuel, heat and electricity storage facilities.
3 Testing
The developed tool was tested using real costs of the participation in the wholesale market
analysed in the work package WP3, electricity production and forecast data for a number of
small power plants of different generating technologies collected in the WP4 and electricity
market balancing market and ancillary service market reference prices collected in the work
package WP5. Data regarding year 2008 has been used for the gain - loss analysis using the
developed tool. Results of the analysis of a number of test sites located in four different
countries are presented and discussed below.
3.1 A cluster of small cogeneration plants in Germany
Small CHP plants in Germany are supported within feed-in tariff system and are entitled to
additional payments like KWKG Bonus or Avoided Grid Utilisation Payments. These
payments depend on the size and age of the plant. In 2008 KWKG Bonus ranged from 0
€/MWh (big and old CHP plants) to 51.10 €/MWh (small and new CHP plants). With the
progressing decrease of funds available from feed-in tariffs and additional support scheme
payments it has become critical for older plants to consider alternative options including
trading their output in the competitive market.
- 13 -
Figure 4.Various source of income for different marketing options for small CHP plants in Germany.
For the main test case of the MASSIG project nine small CHP plants, located within the area
and in the neighbourhood of the city of Freiburg, owned by the badenova WARMEPLUS
GmbH &Co. KG and connected to EnBW distribution network, have been selected. Installed
capacity of these plants, their feed-in tariffs and bonuses are shown below in Table 1.
Table 1. Badenova CHP plants included in the MASSIG test case.
Plant Name
Installed Capacity
Location
[MW]
Feed-in tariff
KWKG Bonus
[€/MWh]
[€/MWh]
Avoided Grid
Utilization
[€/MWh]
Friesenheim
2.30
Friesenheim
63
0.0
3.5
Mauerfeld
6.14
Mauerfeld
63
8.2
3.5
Landwasser
3.50
Freiburg
63
5.6
3.5
Westband
0.42
Freiburg
63
19.4
3.5
Faulerbad
0.21
Freiburg
63
19.4
3.5
Rathaus
0.05
Freiburg
63
51.1
10
Alte Messe
0.14
Freiburg
63
19.4
10
Marienhaus
0.05
Freiburg
63
51.1
10
Weingarten
5.80
Freiburg
63
0.0
3.5
- 14 -
The following market participation options have been considered:
•
Electricity trading in the German power exchange day ahead market (EEX,
www.eex.com ),
•
Electricity trading in the German power exchange intraday market,
•
Provision of upward regulation services in the German tertiary control market,
•
Provision of downward regulation services in the German tertiary control market.
Because neither hourly heat demand data nor electricity generation forecast were available,
the forecast error and imbalance cost had to be excluded from the gain - loss evaluation
(assuming perfect forecast). Premising direct participation in the power exchange annual
membership fee and variable trading cost were accounted for, but the lower bid volume limit
at the EEX (0.1MW has been neglected). Neither strategic bidding nor optimisation of
thermal storage facilities was considered.
Results calculated by the developed tool for the spot market are shown in Table 2 (day head)
and in Table 3 (intraday). In the case of day ahead market the final result for the whole group
of plants is positive with difference of 102590 €. Only in the case of one CHP plant
(Mauerfeld) the difference between FIT and EEX is negative. However, the differences
between incomes earned under regulated FIT tariff and from trading in the day ahead spot
market are rather small, in the range of -1.16% and +8.43%. For the trading in the intraday
spot market the final results for the whole group is negative (-22176.7 €) with 3 plants making
losses after switching from FIT to EEX intraday market and 6 plants which benefit with this
move. Again differences are rather tiny in the range of -4.3% and +5.1%.
The gain-loss evaluation of the participation in the tertiary control yields the maximum and
minimum possible incomes earned from availability and usage payments assuming two
extreme cases. For upward regulation the maximum income is generated when the whole
submitted balancing volume is accepted. The minimum income is generated when all the
bids are rejected and the payment for availability is the only income from upward services.
Assuming positive downward regulation prices, for RES plants with very low operation costs,
the maximum income from the tertiary control market is generated when the plant is not
called to provide regulation services (only downward availability payment). The minimum
income from downward regulation is generated when the whole regulation volume offered is
accepted and the power plant’s output would be considerably reduced or shut down. In
countries when in some delivery periods downward regulation price might be negative (for
- 15 -
example Denmark, approximately 70 hours per year) maximum profits might be considerable
also when all downward regulation volume would be accepted. In the analysed test cases for
upward and downward regulation 10% of the unit’s forecasted production volume has been
reserved2. The results (Table 4) show that for the upward regulation the income from the
tertiary control market ranges might vary from 2612790 € (100% acceptance of submitted
offers) to -298763 € (when all offers have been rejected). Participation in downward
regulation (Table 5) shows much less risk with income varying from 53334 € to 396090 €.
2
This assumption describes an exemplary, very specific situation. In practice most CHP installations
will be able to offer much higher power volumes for the tertiary control market, when combined with
thermal stores or additional heating units (e.g. gas burners).
- 16 -
Table 2. The results of the gain-loss evaluation for the participation of the cluster of CHP units in the power exchange day ahead spot market.
Feed-In Tariff/Contract Traded Volume
Aggregated
Friesenheim
Mauerfeld
Landwasser
Westband
Faulerbad
Rathaus
Alte Messe
Marienhaus
Weingarten
[MWh]
58134.0
1888.2
4550.9
14199.9
1174.7
957.3
234.0
821.8
312.5
33994.8
Feed-In Tariff/Contract Income
[€]
3705874.5
121632.5
292855.5
897994.9
74025.8
61065.4
14780.6
52194.2
19532.9
2171792.6
[MWh]
58134.0
1888.2
4550.9
14199.9
1174.7
957.3
234.0
821.9
312.1
33994.9
Day Ahead PX Income from Energy Trade
[€]
3841971.7
123342.4
289685.9
937969.5
80321.5
64862.6
15730.1
53649.6
20508.9
2255901.1
Day Ahead PX Variable Cost
[€]
-2906.7
-94.4
-227.5
-710.0
-58.7
-47.9
-11.7
-41.1
-15.6
-1699.7
Day Ahead PX Annual Fixed Cost
€]
-30300.0
Day Ahead Financial Cost
[€]
-300.0
Total Day Ahead PX Financial Balance
[€]
3808465.0
123248.0
289458.4
937259.5
80262.7
64814.7
15718.4
53608.5
20493.3
2254201.4
Final Result
[€]
102590.5
1615.5
-3397.2
39264.6
6237.0
3749.3
937.8
1414.3
960.4
82408.7
Day Ahead PX Traded Volume
Table 3. The results of the gain-loss evaluation for the participation of the cluster of CHP units in the power exchange intraday spot market.
Aggregated
Friesenheim
Mauerfeld
Landwasser
Westband
Faulerbad
Rathaus
Alte Messe
Marienhaus
Weingarten
[MWh]
58134.0
1888.2
4550.9
14199.9
1174.7
957.3
234.0
821.8
312.0
33994.8
[€]
3705874.5
121632.5
292855.5
897994.9
74025.8
61065.4
14780.6
52194.2
19532.9
2171792.6
[MWh]
58 134.0
1888.2
4550.9
14199.9
1174.7
957.3
234.0
821.9
312.1
33994.9
Intra Day PX Income from Energy Trade
[€]
3720111.2
119077.0
280638.7
910491.6
77948.9
62863.2
15312.9
51977.8
19814.2
2181986.9
Intra Day PX Variable Cost
[€]
-5813.4
-188.8
-455.1
-1420.0
-117.5
-95.7
-23.4
-82.2
-31.2
-3399.5
Intra Day Ahead PX Annual Fixed Cost
[€]
-30 300.0
Day Ahead Financial Cost
[€]
-300.0
Total Intra Day PX Financial Balance
[€]
3683697.8
118888.2
280183.6
909071.6
77831.4
62767.5
15289.5
51895.6
19783
2178587.4
Final Result
[€]
-22176.7
-2744.3
-12671.9
11076.7
3805.6
1702.1
508.9
-298.6
250.1
6794.8
Feed-In Tariff/Contract Traded Volume
Feed-In Tariff/Contract Income
Intra Day PX Traded Volume
Table 4. The results of the gain-loss evaluation for the participation of the cluster of CHP units in the tertiary control market. Upward regulation.
Aggregated
Friesenheim
Mauerfeld
Landwasser
Westband
Faulerbad
Rathaus
Alte Messe
Marienhaus
Weingarten
Feed-In Tariff/Contract Traded Volume
[MWh]
58134.0
1888.2
4550.9
14199.9
1174.7
957.3
234.0
821.9
312.1
33994.9
Feed-In Tariff/Contract Income
[EUR]
3705874.5
121632.5
292855.5
897994.9
74025.8
61065.4
14780.6
52194.2
19532.9
2171792.7
Day Ahead PX Traded Volume
[MWh]
52320.6
1699.4
4095.8
12779.9
1057.3
861.6
210.6
739.7
280.9
30595.4
Day Ahead PX Income from Energy Trade
[EUR]
3457774.5
111008.2
260717.3
844172.6
72289.3
58376.4
14157.1
48284.6
18458.0
2030311.0
Day Ahead PX Variable Cost
[EUR]
-2616.0
-85.0
-204.8
-639.0
-52.9
-43.1
-10.5
-37.0
-14.0
-1529.8
Day Ahead PX Annual Fixed Cost
[EUR]
-30300.0
[€]
-300.0
Final Result Day Ahead Market
[EUR]
3424558.5
110923.2
260512.5
843533.6
72236.5
58333.3
14146.5
48247.6
18444.0
2028781.3
Tertiary Control Traded Offer Volume
[MWh]
5813.4
188.8
455.1
1420.0
117.5
95.7
23.4
82.2
31.2
3399.5
Tertiary Control Income Availability (Offers)
[EUR
118197.7
3619.5
7859.3
28830.9
2567.2
2035.6
493.0
1617.9
679.1
70495.1
Tertiary Control Income Usage (Offers)
[EUR]
2866455.8
92240.3
222144.7
684169.9
58825.6
47165.7
11473.9
39574.5
15487.3
1695373.8
Lost Opportunity-PX Day Ahead
[EUR]
-384197.2
-12334.2
-28968.6
-93797.0
-8032.1
-6486.3
-1573.0
-5365.0
-2050.9
-225590.1
Lost Opportunity-RES Support Scheme
[EUR]
-41441.1
-660.9
-5324.5
-12921.9
-2690.2
-2192.2
-1430.0
-2416.4
-1906.8
-11898.2
Max Profits/Losses (Offers)
[EUR]
2612790.5
95859.8
201035.4
619203.9
53360.7
42715.1
10393.9
35827.4
14115.4
1540278.8
Min Profits/Losses (Offers)
[EUR]
-307440.6
-9375.6
-26433.8
-77887.9
-8155.1
-6642.9
-2510.1
-6163.5
-3278.6
-166993.3
Day Ahead Financial Cost
- 18 -
Table 5. The results of the gain-loss evaluation for the participation of the cluster of CHP units in the tertiary control market. Downward regulation.
Aggregated
Friesenheim
Mauerfeld
Landwasser
Westband
Faulerbad
Rathaus
Alte Messe
Marienhaus
Weingarten
Feed-In Tariff/Contract Traded Volume
[MWh]
58134.0
1888.2
4550.9
14199.9
1174.7
957.3
234.0
821.9
312.1
33 994.9
Feed-In Tariff/Contract Income
[EUR]
3705874.5
121632.5
292855.5
897994.9
74025.8
61065.4
14780.6
52194.2
19532.9
2171792.7
Day Ahead PX Traded Volume
[MWh]
58134.0
1888.2
4550.9
14199.9
1174.7
957.3
234.0
821.9
312.1
33994.9
Day Ahead PX Income from Energy Trade
[EUR]
3841971.7
123342.4
289685.9
937969.5
80321.5
64862.6
15730.1
53649.6
20508.9
2255901.1
Day Ahead PX Variable Cost
[EUR]
-2906.7
-94.4
-227.5
-710.0
-58.7
-47.9
-11.7
-41.1
-15.6
-1699.7
Day Ahead PX Annual Fixed Cost
[EUR]
-30300.0
[€]
-300.0
Final Result Day Ahead Market
[EUR]
102590.5
1615.5
-3397.2
39264.6
6237.0
3749.3
937.8
1414.3
960.4
82408.7
Tertiary Control Traded Bid Volume
[MWh]
5813.4
188.8
455.1
1420.0
117.5
95.7
23.4
82.2
31.2
3399.5
Tertiary Control Income Availability (Bid)
[EUR]
53334.1
1856.6
4089.1
13228.6
984.4
769.8
204.5
797.1
263.5
31140.5
Tertiary Control Income Usage (Bid)
[EUR]
0
0
0
0
0
0
0
0
0
0
Lost Opportunity-PX Day Ahead
[EUR]
384197.2
12334.2
28968.6
93797.0
8032.1
6486.3
1573.0
5365.0
2050.9
225590.1
Lost Opportunity-RES Support Scheme
[EUR]
-41441.1
-660.9
-5324.5
-12921.9
-2690.2
-2192.2
-1430.0
-2416.4
-1906.8
-11898.2
Min Profits/Losses (Bids)
[EUR]
53334.1
1856.6
4089.1
13228.6
984.4
769.8
204.5
797.1
263.5
31140.5
Max Profits/Losses (Bids)
[EUR]
396090.2
13530.0
27733.2
94103.6
6326.4
5063.9
347.5
3745.7
407.6
244832.4
Day Ahead Financial Cost
- 19 -
Figure 5. Biogas fired diesel engines installed in small CHP plants can be providers of different
network services (e.g. balancing power, voltage regulation, etc.). A heat and power generating unit at
Friesenheim CHP power plant.
Beyond the test case study included in this report many different combinations of CHP
cluster have been studied. For the selected plants and for market data and tariff data of
2008, in all analysed configurations, switching from the CHP feed-in tariff system to the spot
market trading resulted in the increase of plant’s income3. Also the participation in the tertiary
control market, particularly in the downward regulation, seems to be very promising and safe
market option for CHP plants in Germany.
For other CHP plants, which are paid under German Renewable Act (EEG) regulation,
switching from the EEG tariff system to spot market or OTC market trading might not bring
benefits.
3
In the comparison of the feed-in tariff income the spot market income additional payments like
Avoided Grid Utilization Payment or KWKG Bonus have been included in the cash-flow in both options
3.2 A PV cluster in Germany
In many countries, as a protection against elevated investment costs and the capricious
nature (intermittency of their outputs), photovoltaic plants are next to wind plants the most
dynamically developing DG units. The rapid increase of the number of PV installations is
particularly visible in EU member states which have implemented feed-in tariff system and
initially set very high tariffs to stimulate expansion of the new and expensive RES generating
technology.
With the observed decrease of investment costs and degression of the feed-in tariffs
available for new and old PV plants, the gain - loss analysis should answer the question
whether market options are already feasible for this technology. Besides this aspect, PV
plant owners are forced to sell their electricity on the markets after the end of the limited
feed-in tariff period (20 years in Germany).
Figure 6. PV panels become popular and fashionable elements of modern city architecture. An
example facade integrated PV installation at Solar Fabrik, Freiburg, Germany.
- 21 -
A cluster of five PV installations located in the South-West Germany has been selected for a
PV test case. The nominal installed capacity and distances between plants are shown below
in Table 6.
Table 6. Installed capacity and distances between PV plants in the MASSIG PV test case.
Location
Capacity
Freiburg
Karlsruhe
Lahr
Muehlacker
Stuttgart
Capacity
[kW]
48960
36454
113420
30720
57380
Freiburg
4.9
120
38
128
130
Karlsruhe
3.7
120
85
32
62
Lahr
113.4
38
85
99
108
Muehlacker
3.1
128
32
99
31
Stuttgart
5.7
130
62
108
31
-
Two market options of trading in the German power exchange (EEX), day ahead market and
intraday market have been chosen for the analysis. The obtained results are presented in the
tables (all costs and lower volume limit for power exchange trading included) and graphs
below (broker cost and lower volume limit neglected).
Table 7. The results of the gain-loss evaluation for the participation of the PV cluster in the EEX day
ahead spot market.
Cluster
Freiburg
Karlsruhe
Lahr
Muehlacker
Stuttgart
Feed-In Tariff Volume
[MWh]
298.2
54.1
37.6
117
31.9
57.7
Feed-In Tariff Income
[EUR]
132282
23990
16672
51912
14129
25578
Day Ahead PX Traded Volume
[MWh]
172
32.1
21.6
68.7
18.1
31.8
Day Ahead PX Rejected Volume
Day Ahead PX Income from
Energy Trade
Day Ahead PX Variable Cost
[MWh]
135
22.3
17.5
50.6
15.7
29.1
[EUR]
14485
2701.1
1815.2
5774
1524.4
2670.8
[EUR]
-8.6
-1.6
-1.1
-3.4
-0.9
-1.6
Day Ahead PX Annual Fixed Cost
Balancing Market Income
(Rejected Day Ahead Offers)
Total Day Ahead PX Financial
Balance
Imbalance Profits/Losses for
Day Ahead Forecast
[EUR]
-30500
[EUR]
6712
1115.4
867.4
2519.1
777.1
1433.4
[EUR]
-9311
3814.9
2681.5
8289.7
2300.5
4102.7
[EUR]
-394.6
-200.1
-31.8
-128.9
-3.6
-30.2
[EUR]
-141988
-20375
-14022
-43751
-11832
-21506
Final Result
- 22 -
Table 8. The results of the gain-loss evaluation for the participation of the PV cluster in the EEX
intraday spot market.
Cluster
Freiburg
Karlsruhe
Lahr
Muehlacker
Stuttgart
Feed-In Tariff Volume
[MWh]
298.2
54.1
37.6
117
31.9
57.7
Feed-In Tariff Income
Intra Day PX Rejected
Volume
Intra Day PX Income from
Energy Trade
Intra Day PX Variable Cost
Intra Day Ahead PX Annual
Fixed Cost
Balancing Market Income
(Rejected Intra Day Offers)
Total Day Ahead PX
Financial Balance
Imbalance Profits/Losses for
Intra Day Forecast
[EUR]
132282
23990
16672
51912
14129
25578
[MWh]
122
23.1
16.4
40.9
14.3
27.3
[EUR]
14856.5
2683.2
2003.3
5433.5
1694.3
3042.2
[EUR]
-19
-3.4
-2.5
-7
-2.1
-3.9
[EUR]
-30500
[EUR]
6075.5
1148.1
823.2
2031
711.3
1361.8
[EUR]
-9587
3827.9
2824
7457.5
2403.5
4400.1
[EUR]
-803.7
-2084.3
-1463.3
-6664.8
-1238.1
-424.1
[EUR]
-142673
-22246
-15311
-51119
-12964
-21602
Final Result
- 23 -
40 000.00
15 948.10
20 000.00
5 185.00
0.00
‐9.70
‐3 500.00
‐20 000.00
‐40 000.00
€
‐60 000.00
‐80 000.00
‐100 000.00
‐120 000.00
‐140 000.00
Guaranteed income
‐114 668.90
‐132 282.70
DA PX income
BM income
DA PX variable cost
DA PX fixed cost
Imbalance cost
Result
Figure 7. A comparison of profits gained by the PV in the EEX day ahead spot market and from the
feed-in tariffs. Perfect forecast, no lower offer volume limit and direct trading (no broker cost).
40 000.00
24 876.90
20 000.00
0.00
0.00
‐15.86
‐7 286.30
‐20 000.00
‐40 000.00
€
‐60 000.00
‐80 000.00
‐100 000.00
‐120 000.00
‐140 000.00
‐118 207.50
‐132 282.70
‐160 000.00
Guaranteed income
DA PX income
BM income
DA PX variable cost
DA PX fixed cost
Imbalance cost
Result
Figure 8. A comparison of profits gained by the PV in the EEX day ahead spot market and from the
feed-in tariffs. Imperfect forecast, no lower offer volume limit and direct trading (broker services).
- 24 -
In all considered scenarios the final result is negative as long as the PV systems are eligible
of feed-in tariffs. Even if we neglect imbalance cost and trading costs, feed-in tariff brings
significantly more profits than the participation in the competitive electricity market and
leaving the FIT system for competitive spot market is not a feasible option for PV plants. The
situation could change in the future with recurrent and non-recurrent gradual degression of
PV tariffs (e.g. recently announced degression of -16% concerning rooftop and free standing
PV installations in Germany).
3.3 A small hydro plant in Germany
This test case has been made up using production data from two hydro plants (2.7MW and
1.8MW) originally located in Austria and market data from the German power exchange
(EEX) and from the balancing market run by one of Germans TSO - EnBW. Participation in
the day ahead market was considered as a market option. Accounting for relatively stable
output of small hydro plants (compared to other RES technologies) very simple day ahead
forecast was based on the persistency assumption (i.e. today equals tomorrow).
Figure 9. An example of small hydro power plant in Bad Gastein, Austria.
- 25 -
Profits that could be earned in the power exchange market were then compared with feed-in
tariff available to small hydro power plants in Germany. Since the feed-in tariff for hydro
plants depends on the installed capacity and on the age of the plant, two cases of new and
old hydro power plants have been analysed. Plants commissioned before 2004, which are
less than 5MW are paid 76 €/MWh and new plants of the same size receive payment of 6.65
€/MWh. No strategic bidding was considered in the analysis. It was assumed that these two
hydro plants directly participate in the power exchange trade and on top of fixed annual
power exchange fee also the cost of broker services had to be included. The results of the
evaluation are shown in the following two tables.
Table 9. The results of the gain-loss analysis for older small hydro plants participating in the EEX day
ahead spot market.
Cluster
Hydro 1
Hydro 2
Feed-In Tariff Volume
[MWh]
25683.6
15656.3
10027.3
Feed-In Tariff Income
[EUR]
1969930.2
1200835.3
769094.9
Day Ahead PX Traded Volume
[MWh]
25676.1
15644.8
10031.3
Day Ahead PX Rejected Volume
[MWh]
0.0
0.0
0.0
Day Ahead PX Income from Energy Trade
[EUR]
1741283.5
1065070.7
676212.8
Day Ahead PX Variable Cost
[EUR]
-1283.8
-782.2
-501.6
Day Ahead PX Annual Fixed Cost and broker service
[EUR]
-30500.0
-
-
4
Day Ahead Financial Cost
[EUR]
-300.0
-
-
Total Day Ahead PX Financial Balance
[EUR]
1709399.7
1064288.5
675711.3
Imbalance Profits/Losses for Day Ahead Forecast
[EUR]
688.3
2063.1
-1374.7
Final Result
[EUR]
-259842.1
-134483.8
-94758.3
4
The financial cost is linked with financial securities required from power exchange participants.
Annual interest rate of 3% was used to calculated this cost.
- 26 -
Table 10. The results of the gain-loss analysis for newer small hydro plants participating in the EEX
day ahead spot market.
Cluster
Hydro 1
Hydro 2
Feed-In Tariff Volume
[MWh]
25683.6
15656.3
10027.3
Feed-In Tariff Income
[EUR]
1707957.7
1041141.4
666816.3
Day Ahead PX Traded Volume
[MWh]
25676.1
15644.8
10031.3
Day Ahead PX Rejected Volume
[MWh]
0.0
0.0
0.0
Day Ahead PX Income from Energy Trade
[EUR]
1741283.5
1065070.7
676212.8
Day Ahead PX Variable Cost
[EUR]
-1283.8
-782.2
-501.6
Day Ahead PX Annual Fixed Cost and broker service
[EUR]
-30300.0
-
-
Day Ahead Financial Cost
[EUR]
-300.0
-
-
Total Day Ahead PX Financial Balance
[EUR]
1709399.7
1064288.5
675711.3
Imbalance Profits/Losses for Day Ahead Forecast
[EUR]
688.3
2 063.1
-1374.7
Final Result
[EUR]
2130.4
25210.1
7520.3
For old hydro plants the final result is negative (-259843€) and this means that switching
from feed-in tariff to wholesale competitive market is not economically viable. In the case of
hydro plants commissioned after 2004, which receive smaller remuneration within FIT
system the final result is on the verge of economic profitability (2130 €). The clustering of
these two plants does not bring benefits in the balancing market (no reduction of the
imbalance cost).
3.4 An example of a small biogas cogeneration plant in Poland
For the first MASSIG test case in Poland the Wastewater Treatment Plant in Łódź (Grupowa
Oczyszczalnia Ścieków w Łodzi – GOŚ, www.gos.lodz.pl) has been selected. The plant
collects 170-190 thousand m3 of sewage per day from urban and suburban area inhabited by
more than 850 thousand people. Sewage treatment process produces more than 20
thousand m3 of biogas per day. Three diesel engines (total electrical power: 2.7MW, nominal
voltage 6kV, total thermal power 3.5MW) produce electricity and heat, which are mainly
consumed on site (the plant is net importer of electricity) in the process of waste fermentation
and water purification. However, since the daily biogas production profile, as well as,
electricity and heat consumption are time-shifted, the plant becomes regularly net electricity
exporter. Heat can’t be exported because the plant is not connected to the local distribution
heating network (distance). The annual electrical energy consumption amounts to 21534
MWh and annual electrical energy production to 16784 MWh (2008). The total electrical
energy exported to the grid in 2008 reached 1005 MWh.
- 27 -
Figure 10. Bird eye view on the Wastewater Treatment Company in Łódź. Biogas storage tank of
2500m3 can be seen in the background.
In the past the plant traded its excess electricity to the local Distribution System Operator,
who plays the role of the last resort supplier, who is in charge of must take contracts with all
local RES and CHP which decide to stay out of the competitive market. The plants are
remunerated for electricity exported to the grid with the fixed price set by the Polish regulator
(Urząd Regulacji Energetyki – URE, www.ure.gov.pl). This price is annually adjusted and
calculated by Regulator as an average price in the wholesale market in the previous year.
The Polish power exchange price indexes are used to calculate this flat must take contract
price (price independent from the delivery period).
- 28 -
Figure 11. Monthly balance between electricity generation and consumption.
As an alternative to must take contract, the possibility of trading surplus of electricity through
the power exchange has been analysed. At the moment, since there is only day ahead
trading floor at the Polish power exchange, (Towarowa Giełda Energii, www.polpx.pl) the
price data of this market was used for the gain - loss evaluation and it was assumed that all
the electricity exported to the grid was traded via day ahead market. Because rather small
installed capacity (2.7MW) and 1MW bid volume lower at the day ahead market the output of
the plant has to be aggregated by the trader with outputs of other plants and the plant is not
able to operate independently in power exchange. It was also assumed that with very regular
operation cycles, limited fluctuations in hourly biogas production (Figure 12), spare
generating capacity and existing storage facilities the imbalance error might be easily
reduced to zero (no imbalance cost has been considered in the analysis). Results of the
analysis are shown below in Table 11.
- 29 -
Table 11. The results of the gain-loss analysis for CHP plant trading its output in the Polish day ahead
spot market.
Total
Gen1
Gen2
Gen3
Feed-In Tariff/Contract Traded Volume
[MWh]
1005.0
335.1
336.9
333.0
Feed-In Tariff/Contract Income
[PLZ]
129444.0
43157.9
43392.9
42893.2
Day Ahead PX Traded Volume
[MWh]
1 005.0
335.1
336.9
333.0
Day Ahead PX Income from Energy Trade
[PLZ]
195119.7
64723.6
65079.8
65316.3
Day Ahead PX Variable Cost
[PLZ]
-673.4
-224.5
-225.7
-223.1
Day Ahead PX Annual Fixed Cost
[PLZ]
-1890.0
-
-
-
Day Ahead PX Financial Balance
[PLZ]
192556.3
64499.1
64854.1
65093.1
Imbalance Profits/Losses
[PLZ]
0
0
0
0
Final Result
[PLZ]
63112.3
21341.2
21461.2
22200.0
The last row of the table shows that simple switching from „the last resort supplier” to the day
ahead spot market (without strategic bidding using storage facilities) increases plant’s
income by 50%. With an intelligent use of a bigger biogas storage tank and an additional
engine the income from the wholesale spot market could be further increased by bidding
larger energy volumes during peak hours.
- 30 -
m3/h
1000
950
900
850
800
750
700
1
2
3
4
5
6
7
8
9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
h
Figure 12. An example of intermittent daily biogas production profile at GOS.
The plant could provide balancing services on a micro scale, on the local ancillary service
market (in the distribution network), but at the moment the local ancillary service market does
not exist in Poland. Balancing services are reserved only for large generating units
connected to the transmission network and the TSO requires installation of sophisticated and
expensive ITC systems to participate in the central (single buyer) ancillary services markets.
3.5 An example of a small biogas cogeneration plant in Denmark
The Danish electricity market is the most accommodating market for small RES and CHP
plants among all the studied national markets. The distributed generation can easily access
both the wholesale market trading floors and the ancillary services markets with very short
time for activation of regulation services and acceptable costs of ITC equipment required for
participation in ancillary services. All of this results in active participation of smaller size
generating units in the wholesale energy markets and in quickly growing local ancillary
services provision.
In the scope of the MASSIG project a Danish small CHP biogas plant of 1MW, equipped with
a thermal storage tank has been studied. Participation in the Nordic power exchange market
- 31 -
(Nord Pool, www.nordpool.com) and in the tertiary control market run by the TSO
(Energienet, www.energinet.dk).
Profits gained in the wholesale energy market were compared with feed-in tariff presented in
Figure 13.
The results in Table 12 and Table 13 show that in both cases the final result is negative and
the switching from the feed-in tariff system to the competitive spot market will generate
losses. This is typical situation at the Danish market and to encourage small power
producers to leave the tariff system and sell their output in the wholesale market, the
government offers financial compensation for financial losses made in the competitive
market.
100.00
90.00
80.00
70.00
€/MWh
60.00
50.00
40.00
30.00
20.00
10.00
0.00
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
Figure 13. The time-of-day tariff for small CHP plants (blue – winter season, red – summer season).
- 32 -
Table 12. The results of the participation of a small Danish CHP plant in the Nord Pool day ahead
market.
CHP Plant
Feed-In Tariff/Contract Traded Volume
[MWh]
4 543.4
Feed-In Tariff/Contract Income
[EUR]
267245.4
Day Ahead PX Traded Volume
[MWh]
4543.4
Day Ahead PX Income from Energy Trade
[EUR]
256540.0
Day Ahead PX Variable Cost (Σ)
[EUR]
-15.0
Day Ahead PX Annual Fixed Cost
[EUR]
-3800.0
Total Day Ahead PX Financial Balance
[EUR]
252725.0
Final Result
[EUR]
-14520.4
Table 13. The results of the participation of a small Danish CHP plant in the Nord Pool intraday
market.
CHP Plant
Feed-In Tariff/Contract Traded Volume
[MWh]
4543.4
Feed-In Tariff/Contract Income
[EUR]
267245.4
Intra Day PX Traded Volume [MWh]
[MWh]
4543.4
Intra Day PX Income from Energy Trade
[EUR]
55021.1
Intra Day PX Variable Cost
[EUR]
-15.0
Intra Day Ahead PX Annual Fixed Cost
[EUR]
-3800.0
Total Intra Day PX Financial Balance
[EUR]
51206.1
Final Result
[EUR]
-216039.3
- 33 -
Figure 14. An example of a small (1MW) CHP plant with installed thermal storage facility of 300m3
(approximately 12.5MWhthermal).
The situation changes when we consider provision of balancing services. The Danish tertiary
control (minute reserve) upward and downward options have been considered separately.
The financial results for these two scenarios have been shown in Table 14 and Table 155.
For upward regulation the maximum income may reach the level of 30k€ (when all offers are
accepted) and the minimum level may bring even losses of 30 k€ (no offers have been
accepted). Similarly to the Germany MASSIG test case downward regulation exhibits
significantly less risk with income varying between 2.8k€ and 5.3k€ (no bids have been
accepted).
5
This calculation was done again under the assumption, that 10% of the CHP power are reserved for
Tertiary Control. In the practice the available volume will be often much higher, since heat storage
systems and backup generators (like gas burners) will be mostly available. In some cases even
external coolers exist that allow to produce more heat than could be consumed, so additional upward
regulation can be offered.
- 34 -
Table 14. The results of the participation of a small Danish CHP plant in the ancillary services market.
Tertiary control, upward regulation.
CHP Plant
Feed-In Tariff/Contract Traded Volume
[MWh]
4543
Feed-In Tariff/Contract Income
[EUR]
267245
Day Ahead PX Traded Volume
[MWh]
4089
Day Ahead PX Income from Energy Trade
[EUR]
230886
Day Ahead PX Variable Cost
[EUR]
-13
Day Ahead PX Annual Fixed Cost
[EUR]
-3800
Total Day Ahead PX Financial Balance
[EUR]
22072
Final Result
[EUR]
-40172
Tertiary Control Traded Offer Volume
[MWh]
454
Tertiary Control Income Availability Offers
[EUR]
983
Tertiary Control Income Usage Offers
[EUR]
29274
Lost Opportunity-PX Day Ahead
[EUR]
-25654
Lost Opportunity-RES Support Scheme
[EUR]
0
Max Profits/Losses Offers
[EUR]
30257
Min Profits/Losses Offers
[EUR]
-24670
Table 15. The results of the participation of a small Danish CHP plant in the ancillary services market.
Tertiary control, downward regulation.
CHP Plant
Feed-In Tariff/Contract Traded Volume
[MWh]
4543
Feed-In Tariff/Contract Income
[EUR]
267245
Day Ahead PX Traded Volume
[MWh]
4543
Day Ahead PX Income from Energy Trade
[EUR]
256540
Day Ahead PX Variable Cost
[EUR]
-15
Day Ahead PX Annual Fixed Cost
[EUR]
-3800
Total Day Ahead PX Financial Balance
[EUR]
252725
Final Result
[EUR]
-14520
Tertiary Control Traded Bid Volume
[MWh]
454
Tertiary Control Income Availability Bids
[EUR]
2795
Tertiary Control Income Usage Bids
[EUR]
-23145
Lost Opportunity-PX Day Ahead
[EUR]
25654
Lost Opportunity-RES Support Scheme
[EUR]
0
Max Profits/Losses Offers
[EUR]
2795
Min Profits/Losses Offers
[EUR]
5303
To further mitigate the risk linked with the participation in the tertiary control and maximize
profits a more sophisticated, short-term operation planning tools are required. In Figure 15 an
example of the optimization of the operation strategy in the tertiary control market of the
- 35 -
same small Danish CHP plant is displayed. The operation planning was carried out using
EnergyPro software.
Figure 15. An example of optimisation of the test case plant hourly scheduling and thermal store
facility operation planning using EnergyPro software.
3.6 An example of a single wind farm in Poland
For the second MASSIG project test case in Poland a medium size wind farm of 30MW,
located in the Central Poland has been selected. The decision to include in the MASSIG
project a test case of a medium size wind farm was justified by the lack of metering data of
adequate resolution and credibility collected at smaller size wind plants, as well as, by the
fact that this plant in the past experienced independent operation in the wholesale market in
practice and results yield by the developed tool could be check against real figures.
- 36 -
Figure 16. The Polish wind test case. Single wind farm of 30MW.
The 36 hour forecast used for the calculation of imbalance cost was a professional historical
forecast used for the preparation of the wind plant generation schedule. Because of
complicated terrain the production planning is particularly difficult and it results in the average
forecast error higher than for similar size wind plants in other location.
It was assumed in the analysis that the whole generated energy would be traded in the day
ahead power exchange market.
Results of the analysis presenting two scenarios are shown in Figure 17 and Figure 18. The
first graph presents comparison between profits neglecting the imbalance cost (assuming
perfect forecast). The second graph shows results which include impact of imperfect forecast
and the incurred imbalance cost. In the second case, which assumes independent trading at
the power exchange (full fixed cost of power exchange participation), the influence of the bid
size lower limit (1MWh, bids rejected by the power exchange are then settled through the
balancing market) and the influence of the fixed trading cost (broker services) are accounted
for.
- 37 -
20 000 000.00
13 980 385.70
15 000 000.00
10 000 000.00
4 254 174.60
5 000 000.00
€
47 133.10
0.00
‐50 166.60
‐5 000 000.00
‐10 000 000.00
‐9 721 287.70
‐15 000 000.00
Guaranteed income
DA PX income
DA PX variable cost
BM income
Imbalance cost
Result
Figure 17. The results of the wind farm participation in the day ahead power exchange market. Perfect
forecast, no lower offer volume limit and no broker costs included.
However in both case the final result is positive, in the second case the imbalance cost and
the trading of the part of the plant’s output through the balancing market (power exchange
rejected offers) results in significant reduction of financial benefits (from over 4mln PLZ to
just 700 thousand PLZ).
The results produced by the tool have been confirmed by owners of the plant. After
struggling two years to trade plant’s output in the competitive market, the plant has finally
decided to abandon the idea of independent operation in the wholesale market and returned
to safe must take contracts offered by the local DSO. The decision was also supported by
the fact that with one of the highest “green” certificate price in EU member states, the large
part of the income gained by renewable energy sources in Poland comes from the TGC
system. Due to relatively low electricity prices income gained from energy market is of little
importance.
- 38 -
15 000 000.00
10 072 830.90
10 000 000.00
5 000 000.00
405 722.20
€
719 712.80
0.00
‐35 662.60
‐1 890.00
‐5 000 000.00
‐10 000 000.00
‐9 721 287.70
‐15 000 000.00
Guaranteed income
DA PX income
DA PX variable cost
DA PX fixed cost
BM income
Imbalance cost
Result
Figure 18. The results of the wind farm participation in the day ahead power exchange market.
Imperfect forecast, 1MW offer lower limit and broker cost included.
This last scenario, which is the real one, shows that the structure, settlement rules and
operation mode of the Polish electricity market make entering the wholesale market
complicated and risky even for large DG power producers. Without intraday market an
adjustment of submitted generation schedules is not possible for 36 hours and for DG plants
it results in significant forecast errors and prohibitive imbalance cost. Until the end of 2008
the two-price system settlement (Figure 19) in the Polish balancing market severely
penalized power producers for their deviations from submitted production schedules. The
one-price system put in operation from the beginning of 2009 significantly reduced the
imbalance risk.
- 39 -
one-price system (2008)
two-price system (2009)
15
Cost in €/MWh(wind)
10
5
0
-5
-10
-15
Imbalance cost
Bias component
Covariance component
Figure 19. Comparison of imbalance cost of a single Polish wind farm under a two-price (2008) vs.
one-price (2009) balancing market settlement [3].
3.7 A wind farm cluster in the United Kingdom
This example has been created using forecast and production data from a group of six wind
farms located around Vienna (Austria) and the United Kingdom market data from APX UK,
power exchange continuous market and feed-in tariffs available to smaller RES producers. In
Table 16 the installed capacity and distances between wind farms are shown.
Table 16. Installed capacity and distances between wind plants in the MASSIG wind test case [km].
Wind farm
Capacity
1
2
3
4
5
6
Capacity
[kW]
500
600
225
250
200
200
1
500
24
67
112
96
79
2
600
24
58
100
76
68
3
225
67
58
45
52
13
4
250
112
100
45
52
33
5
200
96
76
52
52
45
6
200
79
68
13
33
45
-
According to the new amendments in the renewable support schemes in the UK, owner of a
small renewable plant can choose between feed-in tariff that varies according to the
- 40 -
technology and installed capacity and the participation in the competitive market facing the
price risk and imbalance risk, but receiving additional RES bonus in the form of ROCs
(Renewable Obligation Certificates).
Table 17. Recently introduced feed-in tariffs in the UK depend on the size of the wind plant
Wind farm
Feed-in tariff [p/kWh]
1
4.5
2
4.5
3
18
4
16
5
18
6
18
To analyse the impact of the intermittency of wind farm outputs the forecasts have been
prepared using weather forecast data (wind speed, wind direction) and generating units’
power curves. In the market option, all generated electricity would be traded through the
power exchange. SSB and SSP have been used for the settlement of imbalances.
The quantitative results of the analysis are shown below in Table 18.
Table 18. The results of the gain-loss evaluation of the wind cluster in the UK.
Cluster
Energy Volume
Feed-In Tariff Income
APX Traded
Volume
APX Rejected
Volume
[MWh]
Wind
Plant1
Wind
Plant2
Wind
Plant3
Wind
Plant4
Wind
Plant5
Wind
Plant6
3058
948
893
440
180
341
254
[GBP] 298406
42662
40203
79357
28810
61494.2
45878
[MWh]
3023.4
955.
880.7
432.1
179.5
327.1
248.5
[MWh]
0.0
0.0
0.0
0.0
0.0
0.0
0.0
APX Income
[GBP]
199465
62918
58698
28305.8
11786
21289
16466
APX Variable Cost
[GBP]
-7
-2
-2
-1.1
-0.4
-0.8
-0.6
[GBP]
-32400
APX Annual
Fixed Cost
Total Day APX
Financial Balance
Imbalance Profits
or Losses
[GBP] 167057
62916
58696
28 304
11785
21289
16465
[GBP]
-16454
-7559
-7426
-3 368
-2087
-2 170
-1977
Final Result
[GBP] -147803
12694
11066
-54421
-19111
-42375
-31390
The last row of the table shows, that however the overall result for the cluster is negative (14k GBP),in the case of the three largest wind farms (Wind Plant 1, Wind Plant 2 and Wind
Plant 3) the market option brings more benefits than ROCs payment, even if the negative
impact of the imbalance cost is included in the calculations. It should be also stressed that
the clustering of wind farms results in the decrease of the total imbalance cost (form 24.6k
GBP to only 16.45k GPB, -33%). This is caused by dramatic reduction of the correlation
between production of farms scattered over large area (see Figure 20). Anyway, for this kind
of RES generating technology the imbalance cost is rather high and may reach 10% of the
- 41 -
income earned in the spot market. Better forecast and/or electricity storage allowing the
reduction or even total elimination of the imbalance cost might revert the final result.
1
0.9
0.8
correlation
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
10
20
30
40
50
60
distance [km]
70
80
90
100
Figure 20. An increase of distances between wind farms decreases correlation and amplifies
clustering effect (reduction of forecast errors and reduction of imbalance costs).
4 Conclusions
During realisation of the MASSIG project work package WP5 Task 5.1 cash flow based
methodology for the gain loss evaluation of the smaller size RES and CHP unit participation
in the wholesale market have been developed and implemented in the form of a calculation
spreadsheet. Using historical market, production and forecast data the tool assesses
economic feasibility of different energy and ancillary service market options for a spectrum of
the most common market structures and operation modes.
The tool has been tested using real and made up test cases examples of single and
clustered RES and CHP distributed generations from Denmark, Germany, Poland and the
United Kingdom. Plants of four different generating technologies (wind, photovoltaic, hydro
power and cogeneration) were included in the gain-loss evaluation and nearly one hundred
different scenarios have been created and tested.
- 42 -
For the most of the mentioned above RES technologies and smaller size generating units,
the results of long term simple participation in the wholesale, competitive markets shows that
at the moment market options do not bring expected profits. High feed-in tariffs and
considerable imbalance risk related to the intermittent output of some DG technologies are
the main reason of this situation.
In the light of the conducted studies small CHP units remain unquestionable leaders among
DG technologies regarding active participation, both in the energy and ancillary service
markets. Degression or cancellation of the CHP support schemes (e.g. KWKG law in
Germany), as well as, new emerging market opportunities at the ancillary service markets
(primary control in Denmark, tertiary control in Germany) create great incentives to leave
feed-in tariff systems or must take contracts.
Electricity market structure, operation and settlement rules have significant impact on the
financial risk embedded in the trading in the competitive wholesale markets. It has been
shown that adjustments to the market’s architecture and market rules, for example
shortening the gate closure time, replacing two-price system with one-price system for
imbalance settlement at the balancing market and marginal pricing versus pay-as-bid pricing
in the tertiary control market might have huge influence on the economic feasibility of small
RES and CHP plants actively participating in different market options.
Rising electricity prices at the wholesale markets and an intelligent participation in the
competitive markets using strategic bidding and optimal application of storage facilities
should further improve the economic feasibility of DG plants.
5 Final remarks
The report presents results of the gain-loss evaluation of several test cases dealing with
small RES and CHP plants participating in competitive wholesale market options. It
combines information which was originally in the MASSIG proposal divided into public
Deliverable 5.1 and confidential Deliverable 5.2, which was intended to deal with sensitive
information. Since all data of the study was public and results are not restricted by owners of
the plants, they can be published in Deliverable 5.1 and there was no necessity to prepare
the confidential Deliverable 5.2.
- 43 -
Instead of Deliverable 5.2 TUL has prepared additional Deliverable 5.3 (Trend analysis for
factors influencing costs and revenues) which was not included in the MASSIG contract and
which extend the gain-loss evaluation into the nearest future taking into consideration
expected changes in the regulatory frameworks, market structures and operations, as well
as, electricity price trends.
6 References
[1]
Carlo Obersteiner, Lukas Weißensteiner, Reinhard Haas et al., Market potentials,
trends and marketing options for Distributed Generation in Europe, MASSIG,
Deliverable D2.1, Energy Economics Group, November 2008.
[2]
Manuel Raimann et al., Pre-conditions for entering „big markets“ by „small DG“,
badenovaWÄRMEPLUS, December 2008.
[3]
C. Obersteiner, T. Siewierski, A. N. Andersen, Drivers of imbalance cost of wind
power: a comparative analysis, European Electricity Market Conference 2010
(EEM2010), Madrid 23-25 June 2010.
[4]
energyPro User’s Guide, EMD International A/S, April 2010, Aalborg Denmark.
- 44 -