Data-driven modeling of the aggregator-based price-maker virtual power plant (VPP) in the day-ahead wholesale electricity markets; evidence from the Japan Electric power Exchange (JEPX) market

• Data-driven aggregation of the complete set of supply resources into a unified VPP. • Control and schedule the regional supply and demand patterns based on market equilibrium. • Hybridizing unit commitment, market clearing, LSTM, and econometric models. • Implemented in the Japan Electric Power Exchange (JEPX) Market. This study hypothesizes that many regulated electricity markets in developing countries are not prepared to undertake major and long-term reforms to deregulate their electricity sectors. Thus, it proposes a comprehensive modeling framework based on aggregating the complete set of energy supply and demand resources into a unified virtual power plant (VPP) to dynamically price electricity based on market equilibrium. Data-driven modeling is structured using mixed integer linear programming (MILP) and based on hybridizing several concepts, including conventional unit commitment, hydropower scheduling, pumping storage dispatch, market clearing mechanism, variable renewable energy forecasts, price elasticity of demand, and shadow prices of production technologies. The developed model is then applied to the Japan Electric Power Exchange (JEPX) Market, collecting the set of strategic supply resources of the Kyushu region. The research findings indicate that the generated electricity prices are determined by the merit order effect of energy production technologies rather than by market participants. The results are validated against the JEPX market, showing an annual root mean squared error and mean absolute error of 5.14 and 3.55 ¥/kWh, respectively. The VPP prices are responsive to fuel price fluctuations, which increased by 48% from October to November 2021, driven by a 20% increase in coal prices and an 18% rise in gas prices. Comparing the fixed electricity pricing mechanism in regulated markets with dynamic VPP prices shows a 49% superiority of VPP, generating a consolidated annual profit of 142.3 billion Japanese yen.

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Publication Details

Journal
International Journal of Electrical Power & Energy Systems
Published
2024-12-23
DOI
https://doi.org/10.1016/j.ijepes.2024.110433
Citations
5
Primary Topic
Electric Power System Optimization
Type
article
Field-Weighted Citation Impact
1.04
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article

Data-driven modeling of the aggregator-based price-maker virtual power plant (VPP) in the day-ahead wholesale electricity markets; evidence from the Japan Electric power Exchange (JEPX) market

Mohamed Saad Suliman, Hooman Farzaneh
5 citations
International Journal of Electrical Power & Energy Systems
Electric Power System Optimization
1.04
article

Data-driven modeling of the aggregator-based price-maker virtual power plant (VPP) in the day-ahead wholesale electricity markets; evidence from the Japan Electric power Exchange (JEPX) market

Mohamed Saad Suliman, Hooman Farzaneh
article en
5 citations

Abstract

• Data-driven aggregation of the complete set of supply resources into a unified VPP. • Control and schedule the regional supply and demand patterns based on market equilibrium. • Hybridizing unit commitment, market clearing, LSTM, and econometric models. • Implemented in the Japan Electric Power Exchange (JEPX) Market. This study hypothesizes that many regulated electricity markets in developing countries are not prepared to undertake major and long-term reforms to deregulate their electricity sectors. Thus, it proposes a comprehensive modeling framework based on aggregating the complete set of energy supply and demand resources into a unified virtual power plant (VPP) to dynamically price electricity based on market equilibrium. Data-driven modeling is structured using mixed integer linear programming (MILP) and based on hybridizing several concepts, including conventional unit commitment, hydropower scheduling, pumping storage dispatch, market clearing mechanism, variable renewable energy forecasts, price elasticity of demand, and shadow prices of production technologies. The developed model is then applied to the Japan Electric Power Exchange (JEPX) Market, collecting the set of strategic supply resources of the Kyushu region. The research findings indicate that the generated electricity prices are determined by the merit order effect of energy production technologies rather than by market participants. The results are validated against the JEPX market, showing an annual root mean squared error and mean absolute error of 5.14 and 3.55 ¥/kWh, respectively. The VPP prices are responsive to fuel price fluctuations, which increased by 48% from October to November 2021, driven by a 20% increase in coal prices and an 18% rise in gas prices. Comparing the fixed electricity pricing mechanism in regulated markets with dynamic VPP prices shows a 49% superiority of VPP, generating a consolidated annual profit of 142.3 billion Japanese yen.

International Journal of Electrical Power & Energy SystemsVol. 164
Kyushu University (JP)
Affordable and clean energy
Openalex Percentile: Top 22%
Electric Power System Optimization
1.04
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