Keywords
electricity retailer, power purchasing and selling strategy, conditional value at risk, risk analysis
Abstract
The phenomenon of resigning annual contracts in China medium-term and long-term electricity market highlights the theoretical and policy issues of optimal power combination decision making by multiple investors considering risk factors in 2021. Based on the independent decision making for power purchase in wholesale market and tariff packages in retail market, the decision making model of optimal power ratio of power salez business based on conditional value at risk (CVaR) is constructed for power companies, numerical calculation and analysis are carried out. According to the typical power purchase and sales business scenario for power companies based on the current provincial power market, this paper proposes a corresponding revenue or cost calculation method; uses CVaR as the risk assessment index, and takes the purchase ratio of different trading varieties in the wholesale market and the sales ratio of different tariff packages in the retail market as the decision variables. The optimal revenue-risk decision model aims to maximize the revenues. The impact of typical power transaction combinations and different confidence levels on the structure, revenue and risks of power transactions by power companies is calculated by combining the actual data of Guangdong power market. The paper analyzes the reasons for resigning contracts based on the objective models and simulation, and provides a basis for investors, including power companies, to make decisions on power purchase and sales considering risk management and the government's annual market trading scheme.
DOI
10.19781/j.issn.1673-9140.2022.04.001
First Page
3
Last Page
12
Recommended Citation
Tang, Yang; Liu, Yifeng; Wang, Jing; Gao, Xiong; Ye, Ze; Chen, Lei; and Liu, Chang
(2022)
"Optimal decision model and application of electricity purchasing and selling ofelectricity retailer in electricity market,"
Journal of Electric Power Science and Technology: Vol. 37:
Iss.
4, Article 1.
DOI: 10.19781/j.issn.1673-9140.2022.04.001
Available at:
https://jepst.researchcommons.org/journal/vol37/iss4/1