Credibility Copula-Based Robust Multistage Plan for Industrial Parks Under Exogenous and Endogenous Uncertainties

Zehao Shi; Jiajia Chen; Yanxin Wang; Yanlei Zhao; Bingyin Xu

doi:10.17775/CSEEJPES.2024.09120

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Credibility Copula-Based Robust Multistage Plan for Industrial Parks Under Exogenous and Endogenous Uncertainties

更新时间：2026-02-06

- Credibility Copula-Based Robust Multistage Plan for Industrial Parks Under Exogenous and Endogenous Uncertainties
- CSEE Journal of Power and Energy Systems Vol. 11, Issue 3, Pages: 987-998(2025)
- 作者机构：
  
  School of Electrical and Electronic Engineering, Shandong University of Technology,Zibo,China
- 作者简介：
- 基金信息：
- DOI：10.17775/CSEEJPES.2024.09120
  CLC：
- Published：2025
- 稿件说明：
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Zehao Shi, Jiajia Chen, Yanxin Wang, et al. Credibility Copula-Based Robust Multistage Plan for Industrial Parks Under Exogenous and Endogenous Uncertainties[J]. CSEE Journal of Power and Energy Systems, 2025, 11(3): 987-998.
DOI：

Zehao Shi, Jiajia Chen, Yanxin Wang, et al. Credibility Copula-Based Robust Multistage Plan for Industrial Parks Under Exogenous and Endogenous Uncertainties[J]. CSEE Journal of Power and Energy Systems, 2025, 11(3): 987-998. DOI： 10.17775/CSEEJPES.2024.09120.

摘要

Abstract

The integration of photovoltaic and energy storage in industrial parks enhances economic benefits. However

uncertainties in photovoltaic output and future electricity prices pose challenges to optimal configuration. To address these issues

this paper develops a credibility copula-based robust multistage plan. Firstly

it addresses endogenous uncertainties in electricity pricing and exogenous uncertainties in photovoltaic output. Meanwhile

the copula function is used to couple endogenous uncertainties of the time-of-use

on-grid and demand power prices. Secondly

based on credibility theory

a fuzzy chance constraint model of endogenous uncertainties of future electricity prices and exogenous uncertainties of the PV output is derived. Finally

the method transforms fuzzy chance constraints into deterministic robust optimization through clear equivalence classes. Simulation analyses using data from an industrial park validate the applicability and effectiveness of the proposed approach.

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