An Interval Optimization-Based Approach for Electric–Heat–Gas Coupled Energy System Planning Considering the Correlation between Uncertainties

Wenshi Wang, Houqi Dong, Yangfan Luo, Changhao Zhang, Bo Zeng, Fuqiang Xu and Ming Zeng
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Wenshi Wang: State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China
Houqi Dong: State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China
Yangfan Luo: State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China
Changhao Zhang: State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China
Bo Zeng: State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China
Fuqiang Xu: State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China
Ming Zeng: State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China

Energies, 2021, vol. 14, issue 9, 1-24

Abstract: In this paper, a novel methodological framework for energy hub (EH) planning, considering the correlation between renewable energy source (RES) and demand response (DR) uncertainties, is proposed. Unlike other existing works, our study explicitly considers the potential correlation between the uncertainty of integrated energy system operations (i.e., wind speed, light intensity, and demand response). Firstly, an EH single-objective interval optimization model is established, which aims at minimizing investment and operation costs. The model fully considers the correlation between various uncertain parameters. Secondly, the correlation between uncertainties is dealt with by the interval models of multidimensional parallelism and affine coordinate transformation, which are transformed into a deterministic optimization problem by the interval order relationship and probability algorithm, and then solved by a genetic algorithm. Finally, an experimental case is analyzed, and the results show that the research method in this paper has good engineering practicability. At the same time, different correlations among uncertainties have different influences on integrated energy system planning. Correlation and influence are positively correlated.

Keywords: EH multi-objective interval optimization; correlations model; uncertainties; affine coordinate transformation; genetic algorithm (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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