{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T01:29:33Z","timestamp":1780536573745,"version":"3.54.1"},"reference-count":54,"publisher":"Wiley","license":[{"start":{"date-parts":[[2022,6,25]],"date-time":"2022-06-25T00:00:00Z","timestamp":1656115200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Pan African University Institute for Basic Sciences, Technology and Innovation"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Journal of Electrical and Computer Engineering"],"published-print":{"date-parts":[[2022,6,25]]},"abstract":"<jats:p>This paper investigates the utilization of a STATCOM to enhance the LVRT capability of wind power plants (WPPs) during grid faults. The STATCOM under investigation is tuned using the Water Cycle Algorithm (WCA), Particle Swarm Optimization (PSO), and a hybrid algorithm of both WCA and PSO. Simulations are conducted in MATLAB programming software, using the SimScape power system toolbox, where two test systems are investigated: a 9\u2009MW WPP and the IEEE 39 bus test system. Performance analysis is done by investigating the ability of the WPPs to ride through grid voltage sags, with the incorporation of the STATCOM, independently tuned using WCA, PSO, and further with the hybrid WCA-PSO algorithm. To confirm the effectiveness of the proposed algorithm, simulation results for the three scenarios are compared. Results show that the LVRT capability of the German power system was met for L-G faults, for the 9\u2009MW test system, whereas during LLL-G faults, the WPP only remained online for WCA and WCA-PSO tuned STATCOM. For the IEEE 39 bus system, the WPPs were able to ride through the LLL-G fault. In all scenarios, the WCA-PSO tuned STATCOM resulted in the least voltage, active, and reactive power overshoots.<\/jats:p>","DOI":"10.1155\/2022\/2873053","type":"journal-article","created":{"date-parts":[[2022,6,25]],"date-time":"2022-06-25T18:50:34Z","timestamp":1656183034000},"page":"1-26","source":"Crossref","is-referenced-by-count":10,"title":["STATCOM Controller Tuning to Enhance LVRT Capability of Grid-Connected Wind Power Generating Plants"],"prefix":"10.1155","volume":"2022","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2913-2157","authenticated-orcid":true,"given":"Irene Ndunge","family":"Muisyo","sequence":"first","affiliation":[{"name":"Pan African University Institute for Basic Sciences,Technology and Innovation (PAUSTI), Juja, Kenya"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christopher Maina","family":"Muriithi","sequence":"additional","affiliation":[{"name":"Murang\u2019a University of Technology (MUT), Murang\u2019a, Kenya"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stanley Irungu","family":"Kamau","sequence":"additional","affiliation":[{"name":"Jomo Kenyatta University of Agriculture and Technology (JKUAT), Juja, Kenya"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","reference":[{"key":"1","doi-asserted-by":"publisher","DOI":"10.1080\/15325008.2020.1854375"},{"key":"2","volume-title":"Renewable Capacity Statistics","author":"Irena","year":"2020"},{"key":"3","doi-asserted-by":"publisher","DOI":"10.1109\/access.2019.2946141"},{"issue":"11","key":"4","first-page":"119","article-title":"Designing of advanced crowbar protection system for DFIG coupled wind energy conversion system at different fault conditions","volume":"4","author":"D. 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