A Bi-Objective Optimization Strategy of a Distribution Network Including a Distributed Energy System Using Stepper Search
Source abstract
Abstract
The optimal scheduling of DES is to solve a multi-objective optimization problem (MOP) with complex constraints. However, the potential contradiction between multiple optimization objectives leads to the diversity of feasible solutions, which has a serious impact on the selection of optimal scheduling strategies. Therefore, a stepper search optimization (SSO) method has been proposed for a bi-objective optimization problem (BiOP). Firstly, a constrained single-objective optimization problem (CSiOP) has been established to transform a BiOP and describe an accurate pareto front curve. Then, based on the characteristics of pareto front, the rate of the pareto front is analyzed by the SSO, and the best recommended solution of the BiOP is obtained. Finally, in the IEEE 33 with a DES simulation, by comparing other methods, the SSO method can better control the bi-objective optimization results to be 1–2.5 times as much as the optimal result under each single optimization objective and avoid the imbalance between the two optimization objectives. Additionally, the optimization speed of the SSO method is more than 10 times faster than that of the non-dominated sorting genetic algorithm (NSGA). Further, the SSO method will provide a novel idea for solving MOP.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Integrated Energy Systems Optimization · Smart Grid Energy Management · Optimal Power Flow Distribution
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Electrical and Control Engineering, North China University of Technology, Shijingshan District, Beijing 100144, China
Shandong Electric Power Company Haiyang Power Supply Company, Haiyang 265100, China
Distribution Technology Center, China Electric Power Research Institute, Haidian District, Beijing 100192, China
Funding
Beijing Nova Program
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