<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>In this study, for the electricity spot market under the market power suppression scenario, the market power suppression effect of contractual decomposed electricity is quantitatively evaluated by first reconstructing different electricity consumption loads using the combined MLR method and then combining the market power assessment model with the Lerner index. In addition, a contract for difference based on surveillance price is designed to inhibit market members from utilizing market power by adjusting the space of competitive electricity and the space of contracted electricity to avoid the market risk of rising electricity prices. Finally, a dynamic power purchase optimization decision model is constructed with CVaR as the risk metric and the profit of the power selling company and customer satisfaction as the objectives, and the MOSADE algorithm is used to solve the model and explore the optimal power purchase scheme. The analysis results show that the risk of the spot market can be avoided by bilateral contracts, option contracts, and unit power generation, and the price of electricity sales can be reduced. The expected returns of the four combinations are 21.37M$, 20.43M$, 19.24M$, 18.88M$, and 17.49M$ under the five risk coefficients, respectively. The CVaR values are −23.14, 2.84, 8.83, 10.75, 12.58. Higher than all the other cases, and their selling price for electricity is lower than all the different cases.</p>
</abstract>

In this study, for the electricity spot market under the market power suppression scenario, the market power suppression effect of contractual decomposed electricity is quantitatively evaluated by first reconstructing different electricity consumption loads using the combined MLR method and then combining the market power assessment model with the Lerner index. In addition, a contract for difference based on surveillance price is designed to inhibit market members from utilizing market power by adjusting the space of competitive electricity and the space of contracted electricity to avoid the market risk of rising electricity prices. Finally, a dynamic power purchase optimization decision model is constructed with CVaR as the risk metric and the profit of the power selling company and customer satisfaction as the objectives, and the MOSADE algorithm is used to solve the model and explore the optimal power purchase scheme. The analysis results show that the risk of the spot market can be avoided by bilateral contracts, option contracts, and unit power generation, and the price of electricity sales can be reduced. The expected returns of the four combinations are 21.37M$, 20.43M$, 19.24M$, 18.88M$, and 17.49M$ under the five risk coefficients, respectively. The CVaR values are −23.14, 2.84, 8.83, 10.75, 12.58. Higher than all the other cases, and their selling price for electricity is lower than all the different cases.

Research on the decision-making model of power purchase in electricity spot market oriented to market force suppression

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

In this study, for the electricity spot market under the market power suppression scenario, the market power suppression effect of contractual decomposed...

Research on the decision-making model of power purchase in electricity spot market oriented to market force suppression

Pubblicato online: 15 mag 2024

Pagine: -

Ricevuto: 03 feb 2024

Accettato: 14 apr 2024

DOI: https://doi.org/10.2478/amns-2024-1114

Parole chiave
MLR algorithm, Lerner index, MOSADE algorithm, CvaR, Power purchase decision-making

© 2024 Mingshu Song, et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Research on the decision-making model of power purchase in electricity spot market oriented to market force suppression

Pubblicato online: 15 mag 2024

Pagine: -

Ricevuto: 03 feb 2024

Accettato: 14 apr 2024

DOI: https://doi.org/10.2478/amns-2024-1114

Parole chiaveMLR algorithm, Lerner index, MOSADE algorithm, CvaR, Power purchase decision-making

© 2024 Mingshu Song, et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Parole chiave
MLR algorithm, Lerner index, MOSADE algorithm, CvaR, Power purchase decision-making