A Hybrid Multi-Objective Crisscross Optimization for Dynamic Economic/Emission Dispatch Considering Plug-In Electric Vehicles Penetration

Panpan Mei, Lianghong Wu, Hongqiang Zhang and Zhenzu Liu
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Panpan Mei: School of Information and Electrical Engineering, Hunan University of Science and Technology, Xiangtan 411201, China
Lianghong Wu: School of Information and Electrical Engineering, Hunan University of Science and Technology, Xiangtan 411201, China
Hongqiang Zhang: School of Information and Electrical Engineering, Hunan University of Science and Technology, Xiangtan 411201, China
Zhenzu Liu: School of Information and Electrical Engineering, Hunan University of Science and Technology, Xiangtan 411201, China

Energies, 2019, vol. 12, issue 20, 1-21

Abstract: Due to the significant uncertainty of charging time and charging power consumption, the large increase in plug-in electric vehicles (PEVs) may create a major influences on the power system: According to people’s living habits, PEVs are basically charged during peak load periods (after work). Once PEVs continue the random charging behavior, there will be a higher difference of peak-valley and bigger burden on the grid. A new strategy is put forward for dynamic economic/emission dispatch (DEED) with the consideration of PEVs for the purpose to shave the peak and fill the valley in this paper, and the influences brought from different loads of grid-to-vehicle (G2V) and vehicle-to-grid (V2G) on DEED problem are discussed. The problem to be solved is a challenging multi-objective non-linear problem. By taking advantage of the differential evolution (DE) algorithms and a newly developed crisscross optimization algorithm, a new multi-objective hybrid optimization algorithm is put forward to deal with the problem including effectively dealing with the inequality and equality constraints. A case study is presented to show the feasibility and effectiveness of the put forward method. The analysis results demonstrate that the put forward algorithm could effectively solve DEED problem, showing that the resulting approach of peak shaving and valley filling could significantly save economic costs and reduce emissions under the same load.

Keywords: dynamic economic/emission dispatch (DEED); multi-objective optimization; differential evolution; crisscross optimization; plug-in electric vehicles (PEVs) (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: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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