Risk-Averse Multiobjective Optimization for Integrated Electricity and Heating System: An Augment Epsilon-Constraint Approach

Uncertainties including demand and environmental factors would increase the operational risk of the energy supply networks. It significantly affects the technical and financial aspects of the integrated electricity and heating system (IEHS). This article presents a risk-averse multiobjective optimiz...

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Bibliographic Details
Published in:IEEE systems journal Vol. 16; no. 4; pp. 5142 - 5153
Main Authors: Si, Fangyuan, Wang, Jinkuan, Han, Yinghua, Zhao, Qiang
Format: Journal Article
Language:English
Published: New York IEEE 01.12.2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithms
Cogeneration
Costs
Decision making
Electricity
Epsilon-constraint method
Heating
integrated electricity and heating system (IEHS)
Integrated energy systems
multiobjective optimization
Multiple objective analysis
Optimization methods
Pareto front
Pareto optimization
Probability distribution
Resistance heating
Risk levels
Uncertainty
Waste heat
Wind power generation
ISSN:1932-8184, 1937-9234
Online Access:Get full text
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Summary:Uncertainties including demand and environmental factors would increase the operational risk of the energy supply networks. It significantly affects the technical and financial aspects of the integrated electricity and heating system (IEHS). This article presents a risk-averse multiobjective optimization strategy for short-term decision-making. The objective is to optimize the total cost and the technical dissatisfaction in a way that the economy of system operation and energy supply quality for the risk-averse scheme is guaranteed simultaneously. Based on the trapezoidal fuzzy membership function, the fuzzy constraint is constructed to quantify the technical dissatisfaction of the nodal voltage and supply temperature. Then, a multiobjective min-max-min problem is formulated to hedge the IEHS against risk imposed by the uncertain variables. Since the formulated two objectives compete with each other, a risk-averse multiobjective solution procedure based on the augmented epsilon-constraint algorithm is developed to recast the multiobjective problem into its equivalent single objective problem. And the accurate Pareto fronts under different risk levels are obtained with several iterations. Numerical case studies are conducted to evaluate the effectiveness and applicability of the proposed method. It provides benefits in the aspect of balancing the economy and energy supply quality under network constraints and uncertainties.
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ISSN:1932-8184
1937-9234
DOI:10.1109/JSYST.2021.3135295