{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,21]],"date-time":"2026-04-21T22:45:39Z","timestamp":1776811539783,"version":"3.51.2"},"reference-count":27,"publisher":"European Society of Computational Methods in Sciences and Engineering","issue":"5","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JCM"],"published-print":{"date-parts":[[2022,9,5]]},"abstract":"<jats:p>The power generation industry needs to adopt renewable energy so as to reduce the utilization of fossil energy and pollution emission. In renewable energy power generation, microgrid operation optimization needs to consider multiple objectives such as economy and environmental protection, which is a multi-objective optimization problem. Aiming at the multi-objective optimization problem, based on the Pareto optimal concept, a hybrid crossover multi-agent multi-objective evolutionary algorithm is proposed and applied to the multi-objective optimization problem of microgrid systems, in which the economical cost and environmental protection are considered. The simulation results under three operating conditions show that compared with the classical NSGA-\u00e2\u0085\u00a1 algorithm, the proposed algorithm can obtain higher quality Pareto optimal solution in a shorter time. The efficiency of the proposed algorithm in this problem is higher than that of the classical NSGA-\u00e2\u0085\u00a1 algorithm. It can provide a higher quality solution for the optimal operation of a microgrid.<\/jats:p>","DOI":"10.3233\/jcm-226090","type":"journal-article","created":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T12:24:38Z","timestamp":1652185478000},"page":"1663-1679","source":"Crossref","is-referenced-by-count":1,"title":["A hybrid crossover multi-agent multi-objective evolutionary algorithm and its application in microgrid operation optimization"],"prefix":"10.66113","volume":"22","author":[{"given":"Liheng","family":"Liu","sequence":"first","affiliation":[]},{"given":"Dongliang","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Jinping","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Jin","family":"Yan","sequence":"additional","affiliation":[]}],"member":"55691","reference":[{"key":"10.3233\/JCM-226090_ref2","doi-asserted-by":"crossref","first-page":"411","DOI":"10.1016\/S1876-3804(21)60039-3","article-title":"The role of new energy in carbon Neutral","volume":"48","author":"Zou","year":"2021","journal-title":"Petroleum Exploration and Development."},{"key":"10.3233\/JCM-226090_ref3","doi-asserted-by":"crossref","first-page":"1","DOI":"10.3390\/en14102842","article-title":"A review of optimization of microgrid operation","volume":"14","author":"Gao","year":"2021","journal-title":"Energies."},{"key":"10.3233\/JCM-226090_ref4","doi-asserted-by":"crossref","first-page":"2039","DOI":"10.1016\/j.rser.2017.08.007","article-title":"Hybrid renewable microgrid optimization techniques: A review","volume":"82","author":"Dawoud","year":"2018","journal-title":"Renewable and Sustainable Energy Reviews."},{"key":"10.3233\/JCM-226090_ref5","first-page":"1","article-title":"Resource management optimization for a smart microgrid","volume":"11","author":"Nilgun","year":"2019","journal-title":"Journal of Renewable and Sustainable Energy"},{"key":"10.3233\/JCM-226090_ref6","doi-asserted-by":"crossref","first-page":"785","DOI":"10.1049\/iet-rpg.2018.5795","article-title":"Scenario-based multi-objective optimization with loadability in islanded microgrids considering load and renewable generation uncertainties","volume":"13","author":"Jithendranath","year":"2019","journal-title":"IET Renewable Power Generation."},{"key":"10.3233\/JCM-226090_ref7","first-page":"372","article-title":"Multi-objective coordination optimization of multi-microgrid considering economic and environmental benefits","volume":"37","author":"Zhao","year":"2019","journal-title":"Renewable Energy Resources."},{"key":"10.3233\/JCM-226090_ref8","doi-asserted-by":"crossref","first-page":"1268","DOI":"10.1016\/j.rser.2011.10.002","article-title":"Multi-operation management of a typical micro-grids using Particle swarm optimization: A comparative study","volume":"16","author":"Amjad","year":"2012","journal-title":"Renewable and Sustainable Energy Reviews."},{"key":"10.3233\/JCM-226090_ref9","unstructured":"Zhao ZZ, Wang WQ, Fan XC, Wang HY. 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