{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,21]],"date-time":"2026-09-21T21:43:48Z","timestamp":1790027028893,"version":"4.0.1"},"reference-count":21,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T00:00:00Z","timestamp":1777334400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T00:00:00Z","timestamp":1777334400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100003789","name":"Helwan University","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100003789","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Sci Rep"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Active power distribution networks are evolving with the integration of distributed energy resources (DERs) and advanced optimization techniques to enhance grid flexibility and efficiency. However, radial distribution networks suffer from significant voltage drops and high-power losses due to their inherent topology and unidirectional power flow.This study proposes a novel Classification-based Global Optimization (CGO) approach that integrates electrical engineering principles with a structured optimization framework\u2014a departure from conventional metaheuristic methods. Unlike black-box algorithms, CGO classifies distribution buses based on voltage sensitivity and power flow characteristics before applying a deterministic global optimization function for optimal placement and sizing of distributed generation (DG) and capacitor banks (CBs). The methodology is validated on IEEE 33-bus and IEEE 69-bus test systems. For the IEEE 33-bus system, simultaneous DG and CB integration achieved a 94.75% reduction in active power losses, while for the IEEE 69-bus system, losses were reduced by 98.061%. Voltage stability was significantly improved, with the voltage stability index (VSI) increasing to 0.9740 and 0.9773 for the 33-bus and 69-bus systems, respectively. The proposed CGO approach demonstrates superior computational efficiency, with average simulation times of 18.62\u00a0s (33-bus) and 21.45\u00a0s (69-bus) for combined DG and CB optimization. By enhancing energy efficiency and renewable integration, the method directly supports Sustainable Development Goals (SDGs) 7, 9, 11, and 13, offering a scalable and interpretable solution for modern active distribution networks.<\/jats:p>","DOI":"10.1038\/s41598-026-48973-7","type":"journal-article","created":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T20:44:02Z","timestamp":1777409042000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["New classification-based global optimization approach for sustainable active power distribution networks"],"prefix":"10.1038","volume":"16","author":[{"given":"Rasha","family":"Elazab","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Abdelazim","family":"Salem","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,4,28]]},"reference":[{"key":"48973_CR1","doi-asserted-by":"publisher","first-page":"27341","DOI":"10.1038\/s41598-024-78569-y","volume":"14","author":"T Muthusamy","year":"2024","unstructured":"Muthusamy, T. et al. Enhancing distribution system performance by optimizing electric vehicle charging station integration in smart grids using the honey badger algorithm. Sci. Rep. 14, 27341. https:\/\/doi.org\/10.1038\/s41598-024-78569-y (2024).","journal-title":"Sci. Rep."},{"key":"48973_CR2","doi-asserted-by":"publisher","first-page":"1450986","DOI":"10.3389\/fenrg.2024.1450986","volume":"12","author":"C Gong","year":"2024","unstructured":"Gong, C. et al. Active power optimisation scheduling method for large-scale urban distribution networks with distributed photovoltaics considering the regulating capacity of the main network. Front. Energy Res. 12, 1450986. https:\/\/doi.org\/10.3389\/fenrg.2024.1450986 (2024).","journal-title":"Front. Energy Res."},{"issue":"5","key":"48973_CR3","doi-asserted-by":"publisher","first-page":"6113","DOI":"10.1007\/s00202-024-02348-1","volume":"5","author":"S Anbuchandran","year":"2024","unstructured":"Anbuchandran, S., Kalarathi, M., Suresh, S. & Bhuvanesh, A. Multi-objective optimal distributed generators integration using firefly algorithm with Fuzzy decision making. Electr. Eng. 5 (5), 6113\u20136130. https:\/\/doi.org\/10.1007\/s00202-024-02348-1 (2024).","journal-title":"Electr. Eng."},{"issue":"6","key":"48973_CR4","doi-asserted-by":"publisher","first-page":"7803","DOI":"10.1007\/s00202-024-02469-7","volume":"6","author":"S Anbuchandran","year":"2024","unstructured":"Anbuchandran, S., Jaya Christa, S. T., Suresh, S. & Bhuvanesh, A. Enhancing grid resilience and efficiency with distributed generators through fuzzified firefly optimization. Electr. Eng. 6 (6), 7803\u20137818. https:\/\/doi.org\/10.1007\/s00202-024-02469-7 (2024).","journal-title":"Electr. Eng."},{"issue":"1","key":"48973_CR5","doi-asserted-by":"publisher","first-page":"115","DOI":"10.1007\/s42835-024-02010-7","volume":"1","author":"S Anbuchandran","year":"2024","unstructured":"Anbuchandran, S., Jaya Christa, S. T., Kannan, S. & Bhuvanesh, A. Enhancing Distribution System Pliability and Planning with Distributed Generators Using Fuzzy Firefly Optimization. J. Electr. Eng. Technol. 1 (1), 115\u2013129. https:\/\/doi.org\/10.1007\/s42835-024-02010-7 (2024).","journal-title":"J. Electr. Eng. Technol."},{"key":"48973_CR6","doi-asserted-by":"publisher","unstructured":"Anbuchandran, S., Jaya Christa, S. T., Suresh, S. & Bhuvanesh, A. Enhancing grid voltage stability and reliability by harnessing off-grid power sources with multi-objective fuzzy spark firefly optimization algorithm. J. Chin. Inst. Eng. 48 (1). https:\/\/doi.org\/10.1080\/02533839.2024.2420096 (2024).","DOI":"10.1080\/02533839.2024.2420096"},{"key":"48973_CR7","doi-asserted-by":"crossref","unstructured":"Kowsalya, M. & Mohamed Imran, A. January. Optimal distributed generation and capacitor placement in power distribution networks for power loss minimization. In Proceedings of the 2014 International Conference on Advances in Electrical Engineering (ICAEE), Vellore, India, 9\u201311 ; pp. 1\u20136. (2014).","DOI":"10.1109\/ICAEE.2014.6838519"},{"key":"48973_CR8","doi-asserted-by":"publisher","first-page":"223","DOI":"10.1049\/iet-gtd.2013.0290","volume":"8","author":"AA El-Fergany","year":"2014","unstructured":"El-Fergany, A. A. & Abdelaziz, A. Y. Capacitor allocations in radial distribution networks using cuckoo search algorithm. IET Gener Transm Distrib. 8, 223\u2013232 (2014).","journal-title":"IET Gener Transm Distrib."},{"issue":"2","key":"48973_CR9","doi-asserted-by":"publisher","first-page":"831","DOI":"10.3390\/app14020831","volume":"14","author":"N Pamuk","year":"2024","unstructured":"Pamuk, N. & Uzun, U. E. Optimal Allocation of Distributed Generations and Capacitor Banks in Distribution Systems Using Arithmetic Optimization Algorithm. Appl. Sci. 14 (2), 831 (2024).","journal-title":"Appl. Sci."},{"key":"48973_CR10","doi-asserted-by":"publisher","first-page":"15639","DOI":"10.1007\/s00521-021-06185-2","volume":"33","author":"K Balu","year":"2021","unstructured":"Balu, K. & Mukherjee, V. Optimal siting and sizing of distributed generation in radial distribution system using a novel student psychology-based optimization algorithm. Neural Comput. Appl. 33, 15639\u201315667 (2021).","journal-title":"Neural Comput. Appl."},{"issue":"4","key":"48973_CR11","doi-asserted-by":"publisher","first-page":"68","DOI":"10.11648\/j.epes.20231204.12","volume":"12","author":"M Mustapha","year":"2023","unstructured":"Mustapha, M. et al. Impact Assessment of Optimal Integration of Combined DG and D-STATCOM Allocation for Active Distribution System Enhancement with Loading Variations. Am. J. Electr. Power Energy Syst. 12 (4), 68\u201376. https:\/\/doi.org\/10.11648\/j.epes.20231204.12 (2023).","journal-title":"Am. J. Electr. Power Energy Syst."},{"key":"48973_CR12","doi-asserted-by":"publisher","first-page":"e2322","DOI":"10.1002\/etep.2322","volume":"27","author":"P Kayal","year":"2017","unstructured":"Kayal, P., Chanda, S. & Chanda, C. K. An analytical approach for allocation and sizing of distributed generations in radial distribution network. Int. Trans. Electr. Energy Syst. 27, e2322 (2017).","journal-title":"Int. Trans. Electr. Energy Syst."},{"key":"48973_CR13","doi-asserted-by":"publisher","first-page":"461","DOI":"10.1016\/j.ijepes.2014.06.011","volume":"63","author":"AM Imran","year":"2014","unstructured":"Imran, A. M., Kowsalya, M. & Kothari, D. A novel integration technique for optimal network reconfiguration and distributed generation placement in power distribution networks. Int. J. Electr. Power Energy Syst. 63, 461\u2013472 (2014).","journal-title":"Int. J. Electr. Power Energy Syst."},{"key":"48973_CR14","doi-asserted-by":"publisher","first-page":"106234","DOI":"10.1016\/j.asoc.2020.106234","volume":"92","author":"S Nagaballi","year":"2020","unstructured":"Nagaballi, S. & Kale, V. S. Pareto optimality and game theory approach for optimal deployment of dg in radial distribution system to improve techno-economic benefits. Appl. Soft Comput. 92, 106234 (2020).","journal-title":"Appl. Soft Comput."},{"key":"48973_CR15","doi-asserted-by":"publisher","first-page":"4343","DOI":"10.1007\/s00521-020-05239-1","volume":"33","author":"TD Pham","year":"2021","unstructured":"Pham, T. D., Nguyen, T. T. & Dinh, B. H. Find optimal capacity and location of distributed generation units in radial distribution networks by using enhanced coyote optimization algorithm. Neural Comput. Appl. 33, 4343\u20134371 (2021).","journal-title":"Neural Comput. Appl."},{"key":"48973_CR16","doi-asserted-by":"publisher","first-page":"348","DOI":"10.1016\/j.ijepes.2015.07.034","volume":"74","author":"S Sharma","year":"2016","unstructured":"Sharma, S., Bhattacharjee, S. & Bhattacharya, A. Quasi-oppositional swine influenza model-based optimization with quarantine for optimal allocation of dg in radial distribution network. Int. J. Electr. Power Energy Syst. 74, 348\u2013373 (2016).","journal-title":"Int. J. Electr. Power Energy Syst."},{"key":"48973_CR17","doi-asserted-by":"publisher","first-page":"15639","DOI":"10.1007\/s00521-021-06185-2","volume":"33","author":"K Balu","year":"2021","unstructured":"Balu, K. & Mukherjee, V. Optimal siting and sizing of distributed generation in radial distribution system using a novel student psychology-based optimization algorithm. Neural Comput. Appl. 33, 15639\u201315667 (2021).","journal-title":"Neural Comput. Appl."},{"key":"48973_CR18","doi-asserted-by":"publisher","first-page":"384","DOI":"10.1016\/j.ijepes.2014.07.041","volume":"64","author":"YM Shuaib","year":"2015","unstructured":"Shuaib, Y. M., Kalavathi, M. S. & Rajan, C. C. A. Optimal capacitor placement in radial distribution system using gravitational search algorithm. Int. J. Electr. Power Energy Syst. 64, 384\u2013397 (2015).","journal-title":"Int. J. Electr. Power Energy Syst."},{"issue":"1","key":"48973_CR19","doi-asserted-by":"publisher","first-page":"273","DOI":"10.1049\/gtd2.12683","volume":"17","author":"M Ehsanbakhsh","year":"2023","unstructured":"Ehsanbakhsh, M. & Sepasian, M. S. Simultaneous siting and sizing of Soft Open Points and the allocation of tie switches in active distribution network considering network reconfiguration. IET Gener Transm Distrib. 17 (1), 273\u2013280. https:\/\/doi.org\/10.1049\/gtd2.12683 (2023).","journal-title":"IET Gener Transm Distrib."},{"issue":"18","key":"48973_CR20","doi-asserted-by":"publisher","first-page":"1","DOI":"10.3390\/en13184914","volume":"13","author":"W Gil-Gonz\u00e1lez","year":"2020","unstructured":"Gil-Gonz\u00e1lez, W., Montoya, O. D., Rajagopalan, A., Grisales-Nore\u00f1a, L. F. & Hern\u00e1ndez, J. C. Optimal selection and location of fixed-step capacitor banks in distribution networks using a discrete version of the vortex search algorithm. Energies 13 (18), 1\u201321. https:\/\/doi.org\/10.3390\/en13184914 (2020).","journal-title":"Energies"},{"key":"48973_CR21","doi-asserted-by":"publisher","unstructured":"Saw, B. K., Bohre, A. K., Jobanputra, J. H. & Kolhe, M. L. Solar-DG and DSTATCOM Concurrent Planning in Reconfigured Distribution System Using APSO and GWO-PSO Based on Novel Objective Function, 16, 1. (2023). https:\/\/doi.org\/10.3390\/en16010263","DOI":"10.3390\/en16010263"}],"container-title":["Scientific Reports"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.nature.com\/articles\/s41598-026-48973-7","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41598-026-48973-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41598-026-48973-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T20:58:38Z","timestamp":1777409918000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/s41598-026-48973-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4,28]]},"references-count":21,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,12]]}},"alternative-id":["48973"],"URL":"https:\/\/doi.org\/10.1038\/s41598-026-48973-7","relation":{},"ISSN":["2045-2322"],"issn-type":[{"value":"2045-2322","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,4,28]]},"assertion":[{"value":"13 March 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 April 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"28 April 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}},{"value":"This study did not involve human participants, animals, or any form of biological material, and therefore, ethical approval was not required. The research conducted is based on engineering simulations and theoretical models. All data used in this study are publicly available or generated through validated computational methods, and no ethical concerns arose in the course of the work.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}}],"article-number":"13648"}}