Economic Emission Dispatch Considering Renewable Energy Resources—A Multi-Objective Cross Entropy Optimization Approach

Qun Niu, Ming You, Zhile Yang and Yang Zhang
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Qun Niu: School of Mechanical Engineering and Automation, Shanghai University, Shanghai 200444, China
Ming You: School of Mechanical Engineering and Automation, Shanghai University, Shanghai 200444, China
Zhile Yang: Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
Yang Zhang: School of Mechanical Engineering and Automation, Shanghai University, Shanghai 200444, China

Sustainability, 2021, vol. 13, issue 10, 1-33

Abstract: The conventional electrical power system economic dispatch (ED) often only pursues immediate economic benefits but neglects the harmful environment impacts of gas emissions from thermal power plants. To address this shortfall, economic emission dispatch (EED) has drawn a lot of attention in recent years. With the increasing penetration of renewable generation, the intermittence and uncertainty of renewable energy such as solar power and wind power increase the difficulties of power system scheduling. To enhance the dispatch performance with significant penetration of renewable energy, a modified multi-objective cross entropy algorithm (MMOCE) is proposed in this paper. To solve multi-objective optimization problems, a crowding–distance calculation technique and a novel external archive mechanism are introduced into the conventional cross entropy method. Additionally, the population updating process is simplified by introducing a self-adaptive parameter operator that substitutes the smoothing parameters, while the solution diversity and the adaptability in large scale systems are improved by introducing the crossover operator. Finally, a two-stage evolutionary mechanism further enhances the diversity and the rate of convergence. To verify the efficacy of the proposed MMOCE, eight benchmark functions and three different test systems considering different mixes of renewable energy sources are employed. The dispatch results by the proposed MMOCE are compared with other multi-objective cross entropy algorithms and published heuristic methods, confirming the superiority of the proposed MMOCE over other methods in all test systems.

Keywords: economic emission dispatch; renewable energy sources; multi-objective cross entropy algorithm; crossover operator (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
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