Optimal scheduling of wind–photovoltaic power-generation system based on a copula-based conditional value-at-risk model. Issue 4 (7th July 2022)

• Record Type: Journal Article
• Authors: Ju, Xin; Liu, Xiaomin; Liu, Shangke; Xiao, Yangli
• Is Part Of: Clean energy. Volume 6:Issue 4(2022)
• Page Start: 550
• Page End: 556
• Publication Date: 2022-07-07
• Subjects: renewable energy -- 'Dual Carbon' targets -- copula–CVaR -- particle swarm optimization algorithm -- optimized scheduling; Clean energy -- Periodicals; Energy industries -- Periodicals; Renewable energy sources -- Periodicals; Carbon dioxide mitigation -- Periodicals; Green technology -- Periodicals; Carbon dioxide mitigation; Clean energy; Energy industries; Green technology; Renewable energy sources; Electronic journals; Periodicals
• DOI: 10.1093/ce/zkac029
• Languages: English
• ISSNs: 2515-396X

Abstract

Abstract: Increasing the application of renewable energy in the power system is an effective way to achieve the goal of 'Dual Carbon'. At the same time, the high proportion of renewable energy connected to the grid endangers the safe operation of the power system. To solve this problem, this paper proposes the application of a copula function to describe the correlation between wind power and photovoltaic power, and reduce the uncertainty of power-system operation with a high proportion of renewable energy. In order to increase the robustness of the model, this paper proposes the application of the conditional value-at-risk theory to construct the objective function of the model and effectively control the tail risk of power-system operation costs. Through case analysis, it is found that the model proposed in this paper has strong practicality and economy. Abstract : To reduce the uncertainty of power-system operation with a high proportion of renewable energy in an industrial park, a copula function is combined with conditional value-at-risk theory to create a model for optimal scheduling of multiple energy generation sources. Graphical Abstract: