Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6729070 | Energy and Buildings | 2018 | 26 Pages |
Abstract
This paper proposes a novel Pareto tribe evolution (PTE) with equilibrium-based decision for multi-objective optimization of multiple home energy management systems (HEMS). The multiple HEMS are divided into three types according to their electrical appliances, thus the curse of dimension resulted from massive controllable electrical appliances can be effectively addressed. Three objective functions including maximization of consumer satisfaction, minimization of energy cost, and minimization of peak-to-average ratio of the load profile are simultaneously optimized by PTE, in which the best compromise solution is determined through Nash equilibrium based decision making according to the obtained Pareto front (PF). In order to obtain a uniform and widespread PF, the efficient search mechanism for tribe division, reproduction and migration are presented to achieve an exact local search and a synergistic search among all the individuals. The performance of PTE for multi-objective optimization of multiple HEMS has been evaluated with 100-HEMS.
Keywords
TOUSDLCADNNSGA-IIPVSPTEHEMSPVDMOPSONon-dominated Sorting Genetic AlgorithmMulti-objective particle swarm optimizationMulti-objective optimizationNash equilibriumDistributed generationmodeElectric VehicleTime of usePhotovoltaic systemHome energy management systemActive distribution networkPareto frontDemand response
Related Topics
Physical Sciences and Engineering
Energy
Renewable Energy, Sustainability and the Environment
Authors
Dezhi Wang, Xiaoshun Zhang, Kaiping Qu, Tao Yu, Zhenning Pan, Qianjin Liu,