Improved triangle splitting based bi-objective optimization for community integrated energy systems with correlated uncertainties

•An improved triangle splitting algorithm (ITSA) was proposed for the bi-objective optimization of CIES.•The ITSA-based optimization method was designed for the optimal operation of CIES under uncertainties.•Correlations in uncertainties were considered for effective scenario generation. Economic an...

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Vydáno v:Sustainable energy technologies and assessments Ročník 49; s. 101682
Hlavní autoři: Yu, Hao, Tian, Weikun, Yan, Jinyue, Li, Peng, Zhao, Kunpeng, Wallin, Fredrik, Wang, Chengshan
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier Ltd 01.02.2022
Témata:
algorithm
alternative energy
Bi-objective optimization
China
Community integrated energy system
Decision making
economic development
electricity generation
energy market
Improved triangle splitting algorithm
integrated approach
Integrated energy systems
Operation strategy
optimization
Pareto principle
Probability functions
Solution probability function
Splitting algorithms
Splittings
Uncertainty
uncertainty analysis
Bi-objective optimization
Uncertainty
Improved triangle splitting algorithm
Community integrated energy system
Solution probability function
ISSN:2213-1388, 2213-1396
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Shrnutí:•An improved triangle splitting algorithm (ITSA) was proposed for the bi-objective optimization of CIES.•The ITSA-based optimization method was designed for the optimal operation of CIES under uncertainties.•Correlations in uncertainties were considered for effective scenario generation. Economic and environmental benefits are the most important in the operation of community integrated energy systems (CIES), modeled as a bi-objective optimization problem. In the case of the uncertainties from loads and renewable energy generators, the effectiveness of the operation strategies may be degraded in the practical applications of CIES. In this paper, an improved triangle splitting based bi-objective optimization method is proposed to search for the Pareto optimal solution of the CIES operation. The general preference of decision-makers in practical applications is utilized in the search process to reduce the detailed search interval and consequently improve the optimization efficiency. In addition, a bi-objective uncertain optimization framework is established for the economic-environmental operation of the CIES under uncertainties. The correlation between uncertainties is considered to generate the operation scenarios, in which the solution probability function is employed to determine the final operation strategy with robustness. A comprehensive case study is conducted based on a practical CIES in China, proving the feasibility and effectiveness of the proposed methods.
ISSN:2213-1388
2213-1396
DOI:10.1016/j.seta.2021.101682