Demonstrated Earnings Improvement of More Than 2.3 Times Through the Use of Trading Strategies in Multiple Electricity Markets

-Contributing to the realization of a carbon-neutral society through further development of the renewable energy aggregation business-

  • Renewable Energy
  • R & D / Technology

March 29, 2024

Toshiba Energy Systems & Solutions Corporation
Next Kraftwerke Toshiba Corporation

Toshiba Energy Systems and Solutions Corporation ("Toshiba") and Toshiba Next Kraftwerke Corporation ("TNK") have conducted a Renewable Energy Aggregation Demonstration Project, which was publicly advertised by the Ministry of Economy, Trade and Industry.
In this project the companies conducted a demonstration evaluation to reduce imbalances*1 and improve profitability, which is important for renewable energy aggregators. The results confirm that profitability could be improved by more than 2.3 times using storage batteries with transactions in multiple electricity market (cross market strategies with storage batteries). In addition, Toshiba and TNK improved the accuracy of wind power generation forecasts significantly compared to when they are only used in the conventional wholesale market. Toshiba and TNK carried out the verification and evaluation mainly during the period from December 2023 to January 2024.

The demonstration was conducted by forming a consortium*2 of eight renewable energy aggregators and five demonstration partners, using approximately 100 energy resources across the country in six categories*3 and using the REBSet® system, a renewable energy balancing system jointly developed by Toshiba and the German company Next Kraftwerke.  REBSet® was also used in the last year's demonstration, however for this year some expanded and upgraded functions were developed. In this demonstration, the following four main items were evaluated.

  1. Evaluation of renewable energy generation forecasts
    A new 'integrated method' (Fig. 1) was introduced to improve the forecast accuracy by using multiple power generation forecasting methods with different approaches and combining the methods in an optimal balance according to the forecasting errors in each method. In addition, since the forecast errors for wind were larger than those for photovoltaic (PV) in the last year's demonstration, a new 'power generation forecasting method' (Fig. 2) was included for wind, using the results of local wind speed forecasts calculated by deep learning, and some existing methods were also improved. As a result, the average error* 4 between the power generation forecast in the morning of the previous day and actual power generation was 2.9% for PV power generation and 10.1% for wind power generation. The average error in the last year's demonstration project was 3.5% and 17.3% respectively, and in both cases the accuracy of the forecasts was confirmed to have improved, with wind power generation in particular achieving a significant improvement in forecast accuracy. The demonstration also utilizes power generation forecasting technology developed by Toshiba Corporation's Corporate Research and Development Center.
  2. Reducing imbalances
    The storage battery control method, which was feedback control method while confirming the actual amount of renewable energy generated, was improved, and the imbalance was reduced by an average of 79.1%*5 compared to the amount of imbalance that would occur if storage batteries were not used. The result of last year's demonstration project was 68.4%, and the imbalance reduction effect was demonstrated together with the effect associated with the above-mentioned improvement in the accuracy of power generation forecasts.
  3. Profitability improvement
    To further improve profitability, the Toshiba and TNK has incorporated a 'market trading strategy technology in multiple electricity markets' (Fig.3) to bid at higher prices. Whereas previously, electricity generated was only tendered on the wholesale market, Toshiba and TNK has demonstrated the effect of improved profitability through multiple market transactions using storage batteries, which also assumes tendering on the new supply and demand adjustment market (Replacement Reserve-for FIT)*6. In an evaluation in four areas across the country of general transmission and distribution utilities, the companies confirmed an improvement in earnings of more than 2.3 times, as storage batteries can now be traded more profitably compared to when they are only used in the conventional wholesale market.
  4. Output control measures
    A demonstration using PV was conducted on methods to improve profitability through storage battery control technology that takes output control*7 into account. As a countermeasure against output control, which has recently become a risk factor affecting the earnings for renewable energy power producers and aggregators due to its increasing due to increased frequency of curtailment, the PV generation exceeding the upper limit of the output control value was recharged to storage batteries without wasting any energy (Fig. 4). The system can generate revenue from the amount that would otherwise have been a revenue loss risk, and the system achieved a 32.5% improvement in revenue (revenue equivalent to that without output control) compared to the case with and without storage battery control, confirming that the risk can be controlled.

Toshiba Group will reflect the results of this demonstration in its actual business and contribute to the transition to a carbon-neutral society through the further development of the renewable energy aggregation business.

*1 The difference between the forecasted amount and the actual amount of generation in kWh. Imbalance charges are incurred according to the amount of the difference.

Consortium Members
Consortium leader
Toshiba Energy Systems & Solutions Corporation

Renewable Aggregators (8 companies)
・Urban Energy Corporation
・NTT Anode Energy Corporation
・Nippon Koei Energy Solutions Co., Ltd.
・NEC Corporation
・Hokkaido Electric Power Co., Inc.
・Eurus Green Energy Corporation
・Toshiba Energy Systems & Solutions Corporation

Demonstrating collaborators (5 companies)
・Japan Renewable Energy Corporation
・Japan Weather Association
・PAG Renewables GK
・Next Kraftwerke Toshiba Corporation

*3 Solar power, wind power, hydroelectric power, storage batteries, EVs, EcoCute.

*4 Forecast error is calculated by normalizing the difference between forecast and actual power generation every 30 minutes by the rated capacity of the generator. Average forecast error for all assessment areas in the entire consortium.

*5 Average monthly imbalance reduction rate for all assessment areas in the entire consortium.

*6 A market opened in April 2021 for the procurement of regulating power required by general transmission and distribution utilities for frequency control and supply-demand balance adjustment in electricity supply areas. In Replacement Reserve-for FIT, bids can be submitted when there is a surplus in the supply capacity of the subject power plant as of the day before the electricity is supplied.

*7 The control of the output of a power plant by a power producer at the direction of a general transmission and distribution utility in order to maintain the balance between supply and demand of electricity.

Fig.1: A new integrated method that optimally combines several power generation forecasting methods.
Fig.2: New wind power generation forecasting method incorporated in this year's demonstration.
Fig.3: Market trading strategy technology that also considers the supply and demand adjustment market (Replacement Reserve-for FIT).
Fig. 4: Operational example of storage battery control taking output control into account

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