{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T13:12:27Z","timestamp":1772111547234,"version":"3.50.1"},"reference-count":33,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2023,5,27]],"date-time":"2023-05-27T00:00:00Z","timestamp":1685145600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JSAN"],"abstract":"<jats:p>The microgrid is a group of smaller renewable energy sources (REs), which act in a coordinated manner to provide the required amount of active power and additional services when required. This article proposes coordinated power management for a microgrid with the integration of solar PV plants with maximum power point tracking (MPPT) to enhance power generation and conversion using a hybrid MPPT method based on particle swarm optimization-adaptive neuro-fuzzy inference system (PSO-ANFIS) to acquire rapid and maximum PV power along with battery energy storage control to maintain the stable voltage and frequency (V-f) of an isolated microgrid. In addition, it is proposed to provide active and reactive power (P-Q) regulation for the grid connected. The approach used provides more regulation due to the least root mean square error (RMSE), which improves photovoltaic (PV) potential extraction. The comparison results of the PSO-ANFIS and P&amp;O controllers of the MPPT and the controller of the energy storage devices combined with the V-f (or P-Q) controller of the inverter all show effective coordination between the control systems. This is the most important need for contemporary microgrids, considering the potential of changing irradiance in the grid following mode, the grid forming mode under an island scenario, and back-to-grid synchronization. With the test model, the islanded and grid-islanded-grid connected modes are investigated separately. The results demonstrate conclusively that the proposed strategies are effective. To run the simulations, MATLAB and SimPowerSystems are utilized.<\/jats:p>","DOI":"10.3390\/jsan12030045","type":"journal-article","created":{"date-parts":[[2023,5,27]],"date-time":"2023-05-27T16:17:33Z","timestamp":1685204253000},"page":"45","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Coordinated PSO-ANFIS-Based 2 MPPT Control of Microgrid with Solar Photovoltaic and Battery Energy Storage System"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0389-3388","authenticated-orcid":false,"given":"Siddaraj","family":"SIddaraj","sequence":"first","affiliation":[{"name":"Department of Electrical and Electronics Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal 576104, India"}]},{"given":"Udaykumar R.","family":"Yaragatti","sequence":"additional","affiliation":[{"name":"Department of Electrical and Electronics Engineering, National Institute of Technology Karnataka, Mangalore 575025, India"}]},{"given":"Nagendrappa","family":"Harischandrappa","sequence":"additional","affiliation":[{"name":"Department of Electrical and Electronics Engineering, National Institute of Technology Karnataka, Mangalore 575025, India"}]}],"member":"1968","published-online":{"date-parts":[[2023,5,27]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1109\/MIE.2013.2279306","article-title":"Microgrids: Hierarchical control and an overview of the control and reserve management strategies","volume":"7","author":"Vandoorn","year":"2013","journal-title":"IEEE Ind. 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