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
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 d...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-03-01
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| Series: | International Journal of Electrical Power & Energy Systems |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S0142061524006574 |
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| author | Mohamed Saad Suliman Hooman Farzaneh |
| author_facet | Mohamed Saad Suliman Hooman Farzaneh |
| author_sort | Mohamed Saad Suliman |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-c7422078eda94eaeab54d90b2b4533a3 |
| institution | Kabale University |
| issn | 0142-0615 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | International Journal of Electrical Power & Energy Systems |
| spelling | doaj-art-c7422078eda94eaeab54d90b2b4533a32025-01-19T06:24:02ZengElsevierInternational Journal of Electrical Power & Energy Systems0142-06152025-03-01164110433Data-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) marketMohamed Saad Suliman0Hooman Farzaneh1Interdisciplinary Graduate School of Engineering Sciences, Kyushu University, Fukuoka, JapanInterdisciplinary Graduate School of Engineering Sciences, Kyushu University, Fukuoka, Japan; Transdisciplinary Research and Education Center for Green Technologies, Kyushu University, Fukuoka, Japan; Corresponding author at: Interdisciplinary Graduate School of Engineering Sciences, Kyushu University, Fukuoka, Japan.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.http://www.sciencedirect.com/science/article/pii/S0142061524006574Virtual Power PlantElectricity MarketsDemand ElasticityMerit Order Effect |
| spellingShingle | Mohamed Saad Suliman Hooman Farzaneh 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 International Journal of Electrical Power & Energy Systems Virtual Power Plant Electricity Markets Demand Elasticity Merit Order Effect |
| title | 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 |
| title_full | 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 |
| title_fullStr | 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 |
| title_full_unstemmed | 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 |
| title_short | 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 |
| title_sort | 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 |
| topic | Virtual Power Plant Electricity Markets Demand Elasticity Merit Order Effect |
| url | http://www.sciencedirect.com/science/article/pii/S0142061524006574 |
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