{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,27]],"date-time":"2025-11-27T10:48:37Z","timestamp":1764240517205,"version":"3.40.5"},"reference-count":24,"publisher":"Wiley","license":[{"start":{"date-parts":[[2022,1,18]],"date-time":"2022-01-18T00:00:00Z","timestamp":1642464000000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Mobile Information Systems"],"published-print":{"date-parts":[[2022,1,18]]},"abstract":"<jats:p>The optimization of microgrid is an important part of smart grid. The global energy consumption is seriously greater than the energy it has, and the environmental pollution brought by it should not be underestimated. If we want to reduce their impact, introducing the optimization of microgrid is a good solution. Short-term load forecasting is a very important prerequisite for microgrid optimization, which lays a solid foundation for the realization of the development goal of environmental protection and the improvement of the economic benefits of microgrid. In this paper, a Multi-PSO-SVM forecasting model is proposed to forecast the actual load. By simulating four prediction models with three different samples, we can see that the average predicted value and actual load value of Multi-PSO-SVM algorithm in the three different samples are almost less than 10\u2009MV. Compared with the other three algorithms, Multi-PSO-SVM is superior in accurately predicting the load value at each time point, which provides important conditions for the success of microgrid optimization.<\/jats:p>","DOI":"10.1155\/2022\/2051773","type":"journal-article","created":{"date-parts":[[2022,1,18]],"date-time":"2022-01-18T22:50:58Z","timestamp":1642546258000},"page":"1-9","source":"Crossref","is-referenced-by-count":1,"title":["Multiobjective Optimal Dispatching of Smart Grid Based on PSO and SVM"],"prefix":"10.1155","volume":"2022","author":[{"given":"Man","family":"Bao","sequence":"first","affiliation":[{"name":"College of Mechanical and Electrical Engineering, Inner Mongolia Agricultural University, Hohhot 010018, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4367-0808","authenticated-orcid":true,"given":"Hongqi","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Mechanical and Electrical Engineering, Inner Mongolia Agricultural University, Hohhot 010018, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hao","family":"Wu","sequence":"additional","affiliation":[{"name":"College of Mechanical and Electrical Engineering, Inner Mongolia Agricultural University, Hohhot 010018, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chao","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Mechanical and Electrical Engineering, Inner Mongolia Agricultural University, Hohhot 010018, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zixu","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Mechanical and Electrical Engineering, Inner Mongolia Agricultural University, Hohhot 010018, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaohui","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Mechanical and Electrical Engineering, Inner Mongolia Agricultural University, Hohhot 010018, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","reference":[{"issue":"APR","key":"1","first-page":"357","article-title":"Short-term photovoltaic solar power forecasting using a hybrid wavelet-PSO-SVM model based on SCADA and meteorological information","volume":"118","author":"A. 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