III. Resultados
3.1. Descripción de los resultados
The rapid development of fluctuating renewable electricity generation has increased public interest in load management as an important option to deal with fluctuating generation in or-der to manage the electricity grid. This case study takes a different perspective by analysing the potential income that can be generated by load management on the different electricity markets in Germany. The potential income represents the upper boundary for the cost of the implementation of load management such as communication infrastructure and management.
7.2.1
Characteristics of the load management potential
The technical characteristics of the analysed load management options in this study are based on data published by Klobasa et al. (Klobasa et al., 2007; Klobasa and Ragwitz, 2005b). The applied data set focuses on the industry and the household sector. Important characteristics for the assessment of load management options are the unit size and the maximum number of hours the load of the application can be moved. Since the minimum time horizon on the spot market is one hour, adjustments are necessary in cases where the application can only be moved for less than one hour. In these cases it is assumed that a pool of the electric devices can reach a movement of one hour by sequential load reduction of parts of the pool. But in these cases the average available unit size of a technology is reduced correspondingly. Exam-ples are cooking devices where it cannot be assumed that the load can be moved for one hour.
Other important assumptions are the efficiency of the load management measures in terms of energy losses and the maximum number of times per year a given application can be utilized for load management. This is especially important for industrial applications where the main purpose is the production of a good. An overview of the key characteristics of the analysed load management options is given in Table 7-2.
Table 7-2: Key characteristics of the analysed load management potential
Branch Technolgy Capacity (MW) Chemicals Chlorine
Electrolysis
Households Washing machine 487 0.000033 24 8,760 100 Households Dish washer 427 0.000031 24 8,760 100 Households Dryer 538 0.000374 24 8,760 100 Households Refrigerator 353 0.000027 1 8,760 90 Households Refrigerator &
Freezer 194 0.000033 1 8,760 90 Households Freezer 358 0.000033 1 8,760 90 Households Cooking 191 0.000032 1 8,760 90
* Unit size for households: average available unit size = Capacity multiplied by the utilization in % of time
** Efficiency: Electricitity consumption without one movement divided by electricity consumption with one move-ment
Source: Based on Klobasa et al., 2007; Klobasa and Ragwitz, 2005b
7.2.2
Methodology
This case study assesses the potential income of load management options on the spot market and on the reserve market. In order to assess the potential income on the spot market a modi-fied version of the pump storage algorithm presented in Chapter 5 is applied. The data on the load management options is transferred to the characteristics of pump storage plants and stored in an additional database. The main modification is the calculation of the "storage vol-ume" by multiplying the available capacity with the maximum hours of delay. In order to as-sess the broad range of the potential income two scenarios are developed which represent the upper and the lower range of the potential income. The Max.-Scenario represents the upper range of the potential income. The scenario utilizes the algorithm for the bid price of pump storage plants on the secondary reserve market. The price prognosis is based on the real mar-ket prices of the German spot marmar-ket in the year 2005. The utilization of pump storage plants takes place with perfect knowledge of the market price of the entire year. In addition it is as-sumed that market prices are not affected if load management is activated. Both assumptions of perfect market knowledge and stable price which do not react to the activation of up to 4.5 GW load management potential are very optimistic. Therefore it can be stated that this sce-nario represents the very upper end of the possible income on the spot market. The second scenario is the Min.-Scenario. This scenario uses model based prices as input data. As
de-scribed in Chapter 5, these prices are less volatile, which leads to lower income for load man-agement. The utilization of load management measures takes place on a cost based price prognosis. In the household sector the dispatch takes place on the time horizon of 24 hours and prices are simulated dynamically which means that prices are influenced by the utilization of load management, thus reducing the potential income. In case of the industry sector the limited number of activations for load management needs to be integrated into the simulation.
Therefore the dispatch takes place on the time horizon of an entire year and a cost based price prognosis. Especially the dispatch on the basis of a cost based price prognosis which is far less volatile than the real market leads to a comparatively low income for load management.
Therefore the scenario can be considered to represent the lower end of the possible income.
An overview of the main characteristics of the developed scenarios is given in Table 7-3.
Table 7-3: Description of the selected scenarios
Max.-Scenario Industry-Households
Min.-Scenario Industry
Min.-Scenario Households Prices Real Market Prices 2005 Model-based prices Model-based prices Market prices Static Static dynamic
Dispatch of load
mana-gement Optimized dispatch for 365 days, perfect knowl-edge of market prices
Optimized dispatch for 365 days, cost based price prognosis
Optimized dispatch for 24 hours, simulation for 365 days, cost based price prognosis
7.2.3
Results
The potential income that can be generated by load management is calculated as average daily income in Euro/MW and as annual income per unit. The results for the industry sector show an average daily income between 1.3 Euro/MW and 27.5 Euro/MW depending on the sce-nario and technology. If the income is compared to an estimation of the daily cost for load management with a limited number of movements of ca 10 Euro/MW (Klobasa et al., 2007), it is likely that some big industrial application can create profits by spot market trades based on load management. In terms of annual income per unit the income varies between several hundred and ca. 190 thousand Euro. The figures indicate that the communication infrastruc-ture and management of the load can be feasible in some big industrial applications. The re-sults of the household sector are different. While in most cases the calculated average daily income in Euro/MW is higher than in the industry sector, the actual income per unit is rather small. Even in the Max.-Scenario the annual income per unit reaches values between 0.40 and 3.76 Euro. An exception is the dryer which can reach a higher income due to the higher avail-able capacity.
Other opportunities to create income by the utilization of the existing load management po-tential are the reserve markets (also see Chapter 5.4.2 for more details). The primary reserve market is not very attractive for load management due to technical requirements and the ne-cessity to be able to change the load in both directions, which may not be the case for most load management options. But the secondary reserve market and the minute reserve market could be attractive for load management since positive and negative reserve are purchased by
a separate tender. In order to estimate the possible income on the reserve markets the average positive capacity prices for the year 2005 are multiplied by the unit size and the number of days per year.
Table 7-4: Model results: Possible income on the spot market
Min.
Daily income Annual income Branch Technolgy
MW MW €/MW € per unit
Chemicals Chlorine
Electrolysis 260 14 1.91 16.05 9,760 82,020
Paper Paper-
Households Dish washer 427 0.000031 54.99 303.05 0.62 3.43
Households Dryer 538 0.000374 54.5 244.09 7.44 33.32
Households Refrigerator 353 0.000027 0 40.2 0 0.40
Households Refrigerator &
Freezer
194 0.000033 0 40.3 0 0.49
Households Freezer 358 0,000033 0 40.2 0 0.48
Households Cooking 191 0.000032 0 35.62 0 0.42
* Unit size for households: average available unit size = Capacity multiplied by the utilization in % of time
The results are presented in Table 7-5. Especially the load management in the industry sector can generate considerable incomes between 78 thousand and more than two million Euro per unit and year. Additional income could be generated by the work prices. But due to the lack of data on the work prices and the actual utilization of the reserve capacity they are difficult to estimate. Even without this additional income the figures show that the reserve markets are far more attractive for industrial load management than the spot market. Especially the minute reserve market seems to be very attractive as it is characterized by a daily tender and low utilization of the reserve itself. The size of the expected income seems to be high enough to deal with the qualification procedures and the technical issues. There are already players on the market who bid load management potential into the reserve market. Again, the results for the household sector are different. Apart from dryers the possible income per unit reaches not more than ca. 3 Euro per year and unit. These figures show that the cost of the communication infrastructure and the management of the applications need to be very cheap in order to be
profitable. This is mainly caused by the low available capacity per unit. Bigger applications in the service sector could be more attractive.
Table 7-5: Estimated income on the reserve markets
Minute
Capacity price Annual income Branch Technolgy
Paper Preparation 250 1 215 250 78,475 91,250
Non-ferrous
Households Refrigerator 353 0.000027 215 250 2.12 2.46
Households Refrigerator
& Freezer 194 0.000033 215 250 2.59 3.01
Households Freezer 358 0.000033 215 250 2.59 3.01
Households Cooking 191 0.000032 215 250 2.51 2.92
* Unit size for households: average available unit size = Capacity multiplied by the utilization in % of time
Source: Own calculations based on: RWE Transportnetz Strom, 2006; E.ON Netz, 2006;EnBW Transport-netze AG, 2006;Vattenfall Europe Transmission, 2006)
7.2.4
Summary and outlook
This case study presents an estimation of the potential income of load management options based on the market situation in year 2005. The estimation of the spot market income by means of the developed simulation platform PowerACE and its pump storage algorithm shows the flexibility of the developed model. The analysis shows that the industry sector is the most attractive sector for load management while the potential income in the household sector is rather low. A comparison between the expected income on spot and reserve markets shows that the reserve markets are far more attractive for industrial load management. An interesting extension of this case study could be the analysis of load management options in the service sector. If prices tend to become more volatile, it could also be useful to repeat this
case study for other years since higher volatility is likely to lead to higher income for storage options or load management.