{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,1]],"date-time":"2025-12-01T11:24:43Z","timestamp":1764588283515,"version":"build-2065373602"},"reference-count":42,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2022,3,31]],"date-time":"2022-03-31T00:00:00Z","timestamp":1648684800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Computers"],"abstract":"<jats:p>The problem of optimal siting and dimensioning of photovoltaic (PV) generators in medium-voltage distribution networks is addressed in this research from the perspective of combinatorial optimization. The exact mixed-integer programming (MINLP) model is solved using a master\u2013slave (MS) optimization approach. In the master stage, the generalized normal distribution optimization (GNDO) with a discrete\u2013continuous codification is used to represent the locations and sizes of the PV generators. In the slave stage, the generalization of the backward\/forward power method, known as the successive approximation power flow method, is adopted. Numerical simulations in the IEEE 33-bus and 69-bus systems demonstrated that the GNDO approach is the most efficient method for solving the exact MINLP model, as it obtained better results than the genetic algorithm, vortex-search algorithm, Newton-metaheuristic optimizer, and exact solution using the General Algebraic Modeling System (GAMS) software with the BONMIN solver. Simulations showed that, on average, the proposed MS optimizer reduced the total annual operative costs by approximately 27% for both test feeders when compared with the reference case. In addition, variations in renewable generation availability showed that from 30% ahead, positive reductions with respect to the reference case were obtained.<\/jats:p>","DOI":"10.3390\/computers11040053","type":"journal-article","created":{"date-parts":[[2022,3,31]],"date-time":"2022-03-31T21:33:03Z","timestamp":1648762383000},"page":"53","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Optimal Allocation and Sizing of PV Generation Units in Distribution Networks via the Generalized Normal Distribution Optimization Approach"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6051-4925","authenticated-orcid":false,"given":"Oscar Danilo","family":"Montoya","sequence":"first","affiliation":[{"name":"Grupo de Compatibilidad e Interferencia Electromagn\u00e9tica, Facultad de Ingenier\u00eda, Universidad Distrital Francisco Jos\u00e9 de Caldas, Bogot\u00e1 110231, Colombia"},{"name":"Laboratorio Inteligente de Energ\u00eda, Facultad de Ingenier\u00eda, Universidad Tecnol\u00f3gica de Bol\u00edvar, Cartagena 131001, Colombia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1409-9756","authenticated-orcid":false,"given":"Luis Fernando","family":"Grisales-Nore\u00f1a","sequence":"additional","affiliation":[{"name":"Facultad de Ingenier\u00eda, Campus Robledo, Instituci\u00f3n Universitaria Pascual Bravo, Medell\u00edn 050036, Colombia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2231-4177","authenticated-orcid":false,"given":"Carlos Andres","family":"Ramos-Paja","sequence":"additional","affiliation":[{"name":"Facultad de Minas, Universidad Nacional de Colombia, Medell\u00edn 050041, Colombia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,3,31]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"241","DOI":"10.1007\/s42452-019-1612-z","article-title":"Urban and rural medium voltage networks reliability assessment","volume":"2","author":"Ridzuan","year":"2020","journal-title":"SN Appl. 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