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| High-Dimensional Multiobjective Optimization for Multi-Energy Coupled System Planning with Consideration of Economic, Environmental and Social Factors |
| Zeng Bo1, Xu Fuqiang1, Liu Yixian1, Liu Yu1, Gong Dunwei2 |
1. State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power University Beijing 102206 China;
2. School of Information and Control Engineering China University of Mining and Technology Xuzhou 221116 China |
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Abstract Improving economic performance, reducing pollution emission, and improving energy efficiency are important goals for future energy system development. However, due to the complex correlations between different goals, it tends to be difficult to achieve the above aim when the system planning goals is over three. In order to resolve this challenge, this paper proposes a high-dimensional multi-objective optimization analysis framework for multi-energy system planning. First, based on an in-depth analysis of the source-load coupling characteristics, a multi-objective planning model for an integrated energy system is proposed, which comprehensively considers the impacts of economy, environmental, and social factors. In view of the contradictions between different goals and the inherent uncertainties associated with supply and demand-side behaviors, the model is constructed under the objectives of economic cost, energy efficiency, carbon emissions and consumption comfort. This model comprehensively considers the system component capacity configuration and demand-side management schemes, and uses an interval-based method to allow for the impact of potential uncertainties in the system. The objective functions and constraints are processed by using the fuzzy preference function method and reformulated into a deterministic optimization problem first, and then the non-dominated sorting genetic algorithm-II with dimensionality reduction decomposition is employed as the solution approach for the problem. Finally, the effectiveness of the proposed method is verified and demonstrated through numerical studies.
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Received: 27 June 2020
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2021, Vol. 36 
