TY - JOUR
T1 - 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
AU - Saad Suliman, Mohamed
AU - Farzaneh, Hooman
N1 - Publisher Copyright:
© 2024 The Author(s)
PY - 2025/3
Y1 - 2025/3
N2 - 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.
AB - 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.
KW - Demand Elasticity
KW - Electricity Markets
KW - Merit Order Effect
KW - Virtual Power Plant
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U2 - 10.1016/j.ijepes.2024.110433
DO - 10.1016/j.ijepes.2024.110433
M3 - Article
AN - SCOPUS:85212588087
SN - 0142-0615
VL - 164
JO - International Journal of Electrical Power and Energy Systems
JF - International Journal of Electrical Power and Energy Systems
M1 - 110433
ER -