Journal Article10.1016/j.ijepes.2022.108652
Information gap-based coordination scheme for active distribution network considering charging/discharging optimization for electric vehicles and demand response
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TL;DR: In this paper , a demand response model based on a logistic function is introduced, and the dynamic charging/discharging electricity price of electric vehicles based on the comprehensive load is considered in order to incentivize electric vehicle users to charge/discharge orderly.
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About: This article is published in International Journal of Electrical Power & Energy Systems. The article was published on 01 Feb 2023. The article focuses on the topics: Demand response & Scheme (mathematics).
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References
A fast and elitist multiobjective genetic algorithm: NSGA-II
TL;DR: This paper suggests a non-dominated sorting-based MOEA, called NSGA-II (Non-dominated Sorting Genetic Algorithm II), which alleviates all of the above three difficulties, and modify the definition of dominance in order to solve constrained multi-objective problems efficiently.
Handling multiple objectives with particle swarm optimization
TL;DR: An approach in which Pareto dominance is incorporated into particle swarm optimization (PSO) in order to allow this heuristic to handle problems with several objective functions and indicates that the approach is highly competitive and that can be considered a viable alternative to solve multiobjective optimization problems.
4.2K
PlatEMO: A MATLAB Platform for Evolutionary Multi-Objective Optimization [Educational Forum]
TL;DR: PlatEMO as discussed by the authors is a MATLAB platform for evolutionary multi-objective optimization, which includes more than 50 multiobjective evolutionary algorithms and more than 100 multobjective test problems, along with several widely used performance indicators.
1.7K
A Decision Variable Clustering-Based Evolutionary Algorithm for Large-Scale Many-Objective Optimization
TL;DR: The experimental results demonstrate that the proposed algorithm has significant advantages over several state-of-the-art evolutionary algorithms in terms of the scalability to decision variables on MaOPs.
565
An Efficient Approach to Nondominated Sorting for Evolutionary Multiobjective Optimization
TL;DR: In this paper, a novel, computationally efficient approach to nondominated sorting is proposed, termed efficient nondominated sort (ENS), where a solution to be assigned to a front needs to be compared only with those that have already been assigned toA front, thereby avoiding many unnecessary dominance comparisons.
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