Issue |
E3S Web Conf.
Volume 218, 2020
2020 International Symposium on Energy, Environmental Science and Engineering (ISEESE 2020)
|
|
---|---|---|
Article Number | 02024 | |
Number of page(s) | 6 | |
Section | New Energy Development and Energy Sustainable Development Optimization | |
DOI | https://doi.org/10.1051/e3sconf/202021802024 | |
Published online | 11 December 2020 |
Analysis of Market Equilibrium Based on Co-evolution in Electricity Spot Market
1
State Grid Jiangxi Electric Power Co., LTD., Nanchang 330077, Jiangxi Province, China
2
Jiangxi Electric Power Trading Centre Co., LTD, Nanchang 330077, Jiangxi Province, China
3
School of Electric Power, South China University of Technology, Guangzhou 510641, Guangdong Province, China
* Corresponding author: eehychen@scut.edu.cn
By solving the Nash equilibrium of the electricity market, it is possible to observe the game process of market entities under different boundary conditions and predict the future trend of the market. In order to study the state of market equilibrium in the power spot market, firstly we constructed a bi-level equilibrium model. The upper layer is the problem of maximizing the profit of power generation enterprises under the bidding constraint, and the lower layer is the security constraint economic dispatch with the goal of maximizing social welfare. The traditional solution transforms the bi-level model into MPEC or EPEC through optimal conditions, but they are generally non-convex and difficult to solve. In this regard, the coevolution algorithm is used to solve the bi-level model, and it is proved that the result of co-evolution under a limited strategy set is equivalent to the Nash equilibrium. Finally, an example of PJM 5 machine with 5 nodes is used to analyse the power market equilibrium in the spot market.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.