{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T06:55:45Z","timestamp":1777704945672,"version":"3.51.4"},"reference-count":37,"publisher":"SAGE Publications","issue":"5","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IFS"],"published-print":{"date-parts":[[2022,9,22]]},"abstract":"<jats:p>Microgrid (MG) systems are growing at a rapid pace since they can accommodate the high amount of renewable energy. Since the MG consists of small distributed generators (DG) with volatile characteristics, an efficient energy management system is the main requisite in MG. In this paper, a chaotic sine cosine algorithm with crossover operator (CSCAC) is proposed for the day-ahead MG optimal energy scheduling problem. CSCAC includes a novel non-linear transition parameter based on the chaos system which can help the algorithm escape from local optima. A chaotic search operator is proposed to enhance the local search ability. Furthermore, a crossover operator is devised to combine the advantages of different search strategies and achieve a comparatively better balance of exploration and exploitation. First, the effectiveness of CSCAC is validated on several benchmark functions. Then, it is applied to the day-ahead energy scheduling in a MG with three wind power plants, two photovoltaic power plants and a combined heat and power plant (CHP). Furthermore, it is implemented in two more cases considering the uncertainty and stochastic nature of the renewable power sources. Experimental results demonstrate the superiority of CSCAC over other comparative algorithms in the optimal MG energy management problem.<\/jats:p>","DOI":"10.3233\/jifs-221178","type":"journal-article","created":{"date-parts":[[2022,6,14]],"date-time":"2022-06-14T11:50:37Z","timestamp":1655207437000},"page":"6805-6819","source":"Crossref","is-referenced-by-count":2,"title":["A chaotic sine cosine algorithm with crossover operator for microgrid energy scheduling considering uncertainty"],"prefix":"10.1177","volume":"43","author":[{"given":"Chenye","family":"Qiu","sequence":"first","affiliation":[{"name":"School of Information Engineering, Huangshan University, Huangshan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Huixing","family":"Fang","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Huangshan University, Huangshan, 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