{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,11,26]],"date-time":"2024-11-26T20:40:21Z","timestamp":1732653621355,"version":"3.28.2"},"reference-count":66,"publisher":"Springer Science and Business Media LLC","issue":"36","license":[{"start":{"date-parts":[[2024,10,1]],"date-time":"2024-10-01T00:00:00Z","timestamp":1727740800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,10,1]],"date-time":"2024-10-01T00:00:00Z","timestamp":1727740800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput &amp; Applic"],"published-print":{"date-parts":[[2024,12]]},"DOI":"10.1007\/s00521-024-10301-3","type":"journal-article","created":{"date-parts":[[2024,10,1]],"date-time":"2024-10-01T02:01:53Z","timestamp":1727748113000},"page":"22999-23030","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Optimal renewable distributed generation planning in radial distribution systems: a probabilistic and multi-objective approach with enhanced Young\u2019s double-slit experiment optimizer"],"prefix":"10.1007","volume":"36","author":[{"given":"Ali","family":"Tarraq","sequence":"first","affiliation":[]},{"given":"Fatma A.","family":"Hashim","sequence":"additional","affiliation":[]},{"given":"Anas","family":"Bouaouda","sequence":"additional","affiliation":[]},{"given":"Faissal","family":"El Mariami","sequence":"additional","affiliation":[]},{"given":"Salah","family":"Kamel","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,10,1]]},"reference":[{"key":"10301_CR1","unstructured":"M. Wiatros-Motyka (2023) Global electricity review: global trends. Available: https:\/\/ember-climate.org\/app\/uploads\/2021\/03\/Global-Electricity-Review-2021.pdf. Accessed 13 Apr 2024"},{"issue":"1","key":"10301_CR2","doi-asserted-by":"publisher","first-page":"142","DOI":"10.1109\/TITS.2019.2955359","volume":"22","author":"H Wang","year":"2021","unstructured":"Wang H, Fang YP, Zio E (2021) Risk assessment of an electrical power system considering the influence of traffic congestion on a hypothetical scenario of electrified transportation system in New York state. IEEE Trans Intell Transp Syst 22(1):142\u2013155. https:\/\/doi.org\/10.1109\/TITS.2019.2955359","journal-title":"IEEE Trans Intell Transp Syst"},{"key":"10301_CR3","doi-asserted-by":"publisher","first-page":"119605","DOI":"10.1016\/j.apenergy.2022.119605","volume":"323","author":"A Fathy","year":"2022","unstructured":"Fathy A (2022) A novel artificial hummingbird algorithm for integrating renewable based biomass distributed generators in radial distribution systems. Appl Energy 323:119605. https:\/\/doi.org\/10.1016\/j.apenergy.2022.119605","journal-title":"Appl Energy"},{"key":"10301_CR4","doi-asserted-by":"publisher","first-page":"104154","DOI":"10.1016\/j.est.2022.104154","volume":"49","author":"H Abdel-mawgoud","year":"2022","unstructured":"Abdel-mawgoud H, Fathy A, Kamel S (2022) An effective hybrid approach based on arithmetic optimization algorithm and sine cosine algorithm for integrating battery energy storage system into distribution networks. J Energy Storage 49:104154. https:\/\/doi.org\/10.1016\/j.est.2022.104154","journal-title":"J Energy Storage"},{"issue":"4\/5","key":"10301_CR5","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1504\/ijgei.2023.10054664","volume":"45","author":"A Tarraq","year":"2023","unstructured":"Tarraq A, El Mariami F, Belfqih A, Haidi T (2023) Optimal renewable distributed generation planning: an up-to-date state-of-the-art review. Int J Glob Energy Issue 45(4\/5):1. https:\/\/doi.org\/10.1504\/ijgei.2023.10054664","journal-title":"Int J Glob Energy Issue"},{"key":"10301_CR6","doi-asserted-by":"publisher","first-page":"41588","DOI":"10.1109\/ACCESS.2020.2973670","volume":"8","author":"Q Xu","year":"2020","unstructured":"Xu Q, Xu Z, Ma T (2020) A survey of multiobjective evolutionary algorithms based on decomposition: variants, challenges and future directions. IEEE Access 8:41588\u201341614. https:\/\/doi.org\/10.1109\/ACCESS.2020.2973670","journal-title":"IEEE Access"},{"issue":"17","key":"10301_CR7","doi-asserted-by":"publisher","first-page":"10841","DOI":"10.1007\/s00521-021-06216-y","volume":"33","author":"HT Rauf","year":"2021","unstructured":"Rauf HT, Bangyal WHK, Lali MI (2021) An adaptive hybrid differential evolution algorithm for continuous optimization and classification problems. Neural Comput Appl 33(17):10841\u201310867. https:\/\/doi.org\/10.1007\/s00521-021-06216-y","journal-title":"Neural Comput Appl"},{"key":"10301_CR8","doi-asserted-by":"publisher","first-page":"44","DOI":"10.1016\/j.apenergy.2017.10.106","volume":"210","author":"A Ehsan","year":"2017","unstructured":"Ehsan A, Yang Q (2017) Optimal integration and planning of renewable distributed generation in the power distribution networks: a review of analytical techniques. Appl Energy 210:44\u201359. https:\/\/doi.org\/10.1016\/j.apenergy.2017.10.106","journal-title":"Appl Energy"},{"key":"10301_CR9","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-023-08623-9","author":"M Ebeed","year":"2023","unstructured":"Ebeed M, Ahmed D, Kamel S, Jurado F, Ali A, Refai A (2023) Optimal energy planning of multi-microgrids at stochastic nature of load demand and renewable energy resources using a modified Capuchin search Algorithm. Neural Comput Appl. https:\/\/doi.org\/10.1007\/s00521-023-08623-9","journal-title":"Neural Comput Appl"},{"issue":"24","key":"10301_CR10","doi-asserted-by":"publisher","first-page":"3400","DOI":"10.1049\/gtd2.12230","volume":"15","author":"M Khasanov","year":"2021","unstructured":"Khasanov M, Kamel S, Rahmann C, Hasanien HM, Al-Durra A (2021) Optimal distributed generation and battery energy storage units integration in distribution systems considering power generation uncertainty. IET Gener Transm Distrib 15(24):3400\u20133422. https:\/\/doi.org\/10.1049\/gtd2.12230","journal-title":"IET Gener Transm Distrib"},{"key":"10301_CR11","doi-asserted-by":"publisher","first-page":"108276","DOI":"10.1016\/j.est.2023.108276","volume":"72","author":"MS Abid","year":"2023","unstructured":"Abid MS, Apon HJ, Nafi IM, Ahmed A, Ahshan R (2023) Multi-objective architecture for strategic integration of distributed energy resources and battery storage system in microgrids\u201d. J. Energy Storage 72:108276. https:\/\/doi.org\/10.1016\/j.est.2023.108276","journal-title":"J. Energy Storage"},{"key":"10301_CR12","doi-asserted-by":"publisher","first-page":"9","DOI":"10.1016\/j.epsr.2018.10.015","volume":"167","author":"JM Lujano-Rojas","year":"2019","unstructured":"Lujano-Rojas JM, Dufo-L\u00f3pez R, Bernal-Agust\u00edn JL, Dom\u00ednguez-Navarro JA, Catal\u00e3o JPS (2019) Probabilistic perspective of the optimal distributed generation integration on a distribution system. Electr Power Syst Res 167:9\u201320. https:\/\/doi.org\/10.1016\/j.epsr.2018.10.015","journal-title":"Electr Power Syst Res"},{"issue":"4","key":"10301_CR13","doi-asserted-by":"publisher","first-page":"670","DOI":"10.1166\/jmihi.2019.2654","volume":"9","author":"WH Bangyal","year":"2019","unstructured":"Bangyal WH, Ahmad J, Rauf HT (2019) Optimization of neural network using improved bat algorithm for data classification. J Med Imaging Heal Inform 9(4):670\u2013681. https:\/\/doi.org\/10.1166\/jmihi.2019.2654","journal-title":"J Med Imaging Heal Inform"},{"key":"10301_CR14","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-11593-7","volume-title":"Metaheuristics algorithms in power systems","author":"E Cuevas","year":"2019","unstructured":"Cuevas E, Barocio Espejo E, Enr\u00edquez AC (2019) Metaheuristics algorithms in power systems. Springer Nature, Switzerland"},{"key":"10301_CR15","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1155\/2021\/5990999","volume":"2021","author":"S Pervaiz","year":"2021","unstructured":"Pervaiz S, Ul-Qayyum Z, Bangyal WH, Gao L, Ahmad J (2021) A systematic literature review on particle swarm optimization techniques for medical diseases detection. Comput Math Methods Med 2021:1\u201310. https:\/\/doi.org\/10.1155\/2021\/5990999","journal-title":"Comput Math Methods Med"},{"key":"10301_CR16","doi-asserted-by":"publisher","first-page":"54465","DOI":"10.1109\/ACCESS.2020.2981406","volume":"8","author":"EA Almabsout","year":"2020","unstructured":"Almabsout EA, El-Sehiemy RA, An ONU, Bayat O (2020) A hybrid local search-genetic algorithm for simultaneous placement of DG units and shunt capacitors in radial distribution systems. IEEE Access 8:54465\u201354481. https:\/\/doi.org\/10.1109\/ACCESS.2020.2981406","journal-title":"IEEE Access"},{"key":"10301_CR17","doi-asserted-by":"publisher","first-page":"46","DOI":"10.1016\/j.advengsoft.2013.12.007","volume":"69","author":"S Mirjalili","year":"2014","unstructured":"Mirjalili S, Mirjalili SM, Lewis A (2014) Grey wolf optimizer. Adv Eng Softw 69:46\u201361. https:\/\/doi.org\/10.1016\/j.advengsoft.2013.12.007","journal-title":"Adv Eng Softw"},{"key":"10301_CR18","doi-asserted-by":"publisher","first-page":"1595","DOI":"10.3390\/en16041595","volume":"16","author":"N Belbachir","year":"2023","unstructured":"Belbachir N, Zellagui M, Settoul S, El-Bayeh CZ, El-Sehiemy RA (2023) Multi dimension-based optimal allocation of uncertain renewable distributed generation outputs with seasonal source-load power uncertainties in electrical distribution network using marine predator algorithm. Energies 16:1595. https:\/\/doi.org\/10.3390\/en16041595","journal-title":"Energies"},{"key":"10301_CR19","doi-asserted-by":"publisher","first-page":"115652","DOI":"10.1016\/j.cma.2022.115652","volume":"403","author":"M Abdel-Basset","year":"2023","unstructured":"Abdel-Basset M, El-Shahat D, Jameel M, Abouhawwash M (2023) Young\u2019s double-slit experiment optimizer: a novel metaheuristic optimization algorithm for global and constraint optimization problems. Comput Methods Appl Mech Eng 403:115652. https:\/\/doi.org\/10.1016\/j.cma.2022.115652","journal-title":"Comput Methods Appl Mech Eng"},{"key":"10301_CR20","doi-asserted-by":"publisher","first-page":"80","DOI":"10.1016\/j.advengsoft.2015.01.010","volume":"83","author":"S Mirjalili","year":"2015","unstructured":"Mirjalili S (2015) The ant lion optimizer. Adv Eng Softw 83:80\u201398. https:\/\/doi.org\/10.1016\/j.advengsoft.2015.01.010","journal-title":"Adv Eng Softw"},{"issue":"5","key":"10301_CR21","doi-asserted-by":"publisher","first-page":"4810","DOI":"10.11591\/ijece.v13i5.pp4810-4823","volume":"13","author":"A Tarraq","year":"2023","unstructured":"Tarraq A, El Mariami F, Belfqih A (2023) Multi-objective distributed generation integration in radial distribution system using modified neural network algorithm. Int J Electr Comput Eng 13(5):4810\u20134823. https:\/\/doi.org\/10.11591\/ijece.v13i5.pp4810-4823","journal-title":"Int J Electr Comput Eng"},{"issue":"10","key":"10301_CR22","doi-asserted-by":"publisher","first-page":"5887","DOI":"10.1002\/int.22535","volume":"36","author":"B Abdollahzadeh","year":"2021","unstructured":"Abdollahzadeh B, Soleimanian Gharehchopogh F, Mirjalili S (2021) Artificial gorilla troops optimizer: a new nature-inspired metaheuristic algorithm for global optimization problems. Int J Intell Syst 36(10):5887\u20135958. https:\/\/doi.org\/10.1002\/int.22535","journal-title":"Int J Intell Syst"},{"key":"10301_CR23","doi-asserted-by":"publisher","first-page":"300","DOI":"10.1016\/j.future.2020.03.055","volume":"111","author":"S Li","year":"2020","unstructured":"Li S, Chen H, Wang M, Heidari AA, Mirjalili S (2020) Slime mould algorithm: a new method for stochastic optimization. Futur Gener Comput Syst 111:300\u2013323. https:\/\/doi.org\/10.1016\/j.future.2020.03.055","journal-title":"Futur Gener Comput Syst"},{"key":"10301_CR24","doi-asserted-by":"publisher","first-page":"114194","DOI":"10.1016\/j.cma.2021.114194","volume":"388","author":"W Zhao","year":"2022","unstructured":"Zhao W, Wang L, Mirjalili S (2022) Artificial hummingbird algorithm: a new bio-inspired optimizer with its engineering applications. Comput Methods Appl Mech Eng 388:114194. https:\/\/doi.org\/10.1016\/j.cma.2021.114194","journal-title":"Comput Methods Appl Mech Eng"},{"key":"10301_CR25","doi-asserted-by":"publisher","first-page":"153","DOI":"10.1049\/rpg2.12013","volume":"15","author":"ML Merlin Sajini","year":"2021","unstructured":"Merlin Sajini ML, Suja S, S. Merlin Gilbert Raj, (2021) Impact analysis of time-varying voltage-dependent load models on hybrid DG planning in a radial distribution system using analytical approach. IET Renew Power Gener 15:153\u2013172. https:\/\/doi.org\/10.1049\/rpg2.12013","journal-title":"IET Renew Power Gener"},{"key":"10301_CR26","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/JSYST.2018.2875177","volume":"2","author":"S Roy Ghatak","year":"2018","unstructured":"Roy Ghatak S, Sannigrahi S, Acharjee P (2018) Multi-objective approach for strategic incorporation of solar energy source, battery storage system, and DSTATCOM in a smart grid environment. IEEE Syst J 2:1\u201312. https:\/\/doi.org\/10.1109\/JSYST.2018.2875177","journal-title":"IEEE Syst J"},{"key":"10301_CR27","doi-asserted-by":"publisher","first-page":"164887","DOI":"10.1109\/ACCESS.2019.2947308","volume":"7","author":"MR Elkadeem","year":"2019","unstructured":"Elkadeem MR, Abd Elaziz M, Ullah Z, Wang S, Sharshir SW (2019) Optimal planning of renewable energy-integrated distribution system considering uncertainties. IEEE Access 7:164887\u2013164907. https:\/\/doi.org\/10.1109\/ACCESS.2019.2947308","journal-title":"IEEE Access"},{"issue":"13","key":"10301_CR28","doi-asserted-by":"publisher","first-page":"2418","DOI":"10.1049\/iet-rpg.2018.6060","volume":"13","author":"S Sannigrahi","year":"2019","unstructured":"Sannigrahi S, Ghatak SR, Acharjee P (2019) Multi-objective optimisation-based active distribution system planning with reconfiguration, intermittent RES, and DSTATCOM. IET Renew Power Gener 13(13):2418\u20132429. https:\/\/doi.org\/10.1049\/iet-rpg.2018.6060","journal-title":"IET Renew Power Gener"},{"key":"10301_CR29","doi-asserted-by":"publisher","first-page":"179","DOI":"10.1016\/j.ijepes.2013.09.007","volume":"55","author":"DQ Hung","year":"2014","unstructured":"Hung DQ, Mithulananthan N, Lee KY (2014) Electrical power and energy systems optimal placement of dispatchable and nondispatchable renewable DG units in distribution networks for minimizing energy loss. Int J Electr Power Energy Syst 55:179\u2013186. https:\/\/doi.org\/10.1016\/j.ijepes.2013.09.007","journal-title":"Int J Electr Power Energy Syst"},{"issue":"3","key":"10301_CR30","doi-asserted-by":"publisher","first-page":"3068","DOI":"10.1109\/TIA.2020.2968046","volume":"56","author":"S Roy Ghatak","year":"2020","unstructured":"Roy Ghatak S, Sannigrahi S, Acharjee P (2020) Multiobjective framework for optimal integration of solar energy source in three-phase unbalanced distribution network. IEEE Trans Ind Appl 56(3):3068\u20133078. https:\/\/doi.org\/10.1109\/TIA.2020.2968046","journal-title":"IEEE Trans Ind Appl"},{"issue":"1","key":"10301_CR31","doi-asserted-by":"publisher","first-page":"850","DOI":"10.1109\/TIA.2019.2951118","volume":"56","author":"S Sannigrahi","year":"2020","unstructured":"Sannigrahi S, Ghatak SR, Acharjee P (2020) Multi-scenario based Bi-level coordinated planning of active distribution system under uncertain environment. IEEE Trans Ind Appl 56(1):850\u2013863. https:\/\/doi.org\/10.1109\/TIA.2019.2951118","journal-title":"IEEE Trans Ind Appl"},{"key":"10301_CR32","doi-asserted-by":"publisher","first-page":"118097","DOI":"10.1016\/j.apenergy.2021.118097","volume":"307","author":"LDL Pereira","year":"2021","unstructured":"Pereira LDL et al (2021) Optimal allocation of distributed generation and capacitor banks using probabilistic generation models with correlations. Appl Energy 307:118097. https:\/\/doi.org\/10.1016\/j.apenergy.2021.118097","journal-title":"Appl Energy"},{"key":"10301_CR33","doi-asserted-by":"publisher","first-page":"91062","DOI":"10.1109\/ACCESS.2021.3092145","volume":"9","author":"H Abdel-Mawgoud","year":"2021","unstructured":"Abdel-Mawgoud H, Ali A, Kamel S, Rahmann C, Abdel-Moamen MA (2021) A modified manta ray foraging optimizer for planning inverter-based photovoltaic with battery energy storage system and wind turbine in distribution networks. IEEE Access 9:91062\u201391079. https:\/\/doi.org\/10.1109\/ACCESS.2021.3092145","journal-title":"IEEE Access"},{"key":"10301_CR34","doi-asserted-by":"publisher","first-page":"107387","DOI":"10.1016\/j.knosys.2021.107387","volume":"231","author":"TP Nguyen","year":"2021","unstructured":"Nguyen TP, Nguyen TA, Phan TVH, Vo DN (2021) A comprehensive analysis for multi-objective distributed generations and capacitor banks placement in radial distribution networks using hybrid neural network algorithm. Knowl Based Syst 231:107387. https:\/\/doi.org\/10.1016\/j.knosys.2021.107387","journal-title":"Knowl Based Syst"},{"key":"10301_CR35","doi-asserted-by":"publisher","first-page":"103288","DOI":"10.1109\/access.2023.3316725","volume":"1","author":"THB Huy","year":"2023","unstructured":"Huy THB, Vo DN, Truong KH, Van Tran T (2023) Optimal distributed generation placement in radial distribution networks using enhanced search group algorithm. IEEE Access 1:103288\u2013103305. https:\/\/doi.org\/10.1109\/access.2023.3316725","journal-title":"IEEE Access"},{"issue":"5","key":"10301_CR36","doi-asserted-by":"publisher","first-page":"4909","DOI":"10.11591\/ijece.v13i5.pp4909-4918","volume":"13","author":"A Tarraq","year":"2023","unstructured":"Tarraq A, El Mariami F, Belfqih A (2023) New typical power curves generation approach for accurate renewable distributed generation placement in the radial distribution system. Int J Electr Comput Eng 13(5):4909\u20134918. https:\/\/doi.org\/10.11591\/ijece.v13i5.pp4909-4918","journal-title":"Int J Electr Comput Eng"},{"issue":"2","key":"10301_CR37","doi-asserted-by":"publisher","first-page":"1425","DOI":"10.1109\/TPWRS.2012.2230276","volume":"28","author":"JH Teng","year":"2013","unstructured":"Teng JH, Luan SW, Lee DJ, Huang YQ (2013) Optimal charging\/discharging scheduling of battery storage systems for distribution systems interconnected with sizeable PV generation systems. IEEE Trans Power Syst 28(2):1425\u20131433. https:\/\/doi.org\/10.1109\/TPWRS.2012.2230276","journal-title":"IEEE Trans Power Syst"},{"key":"10301_CR38","doi-asserted-by":"publisher","first-page":"42","DOI":"10.1016\/j.enconman.2017.10.090","volume":"155","author":"HZ Al Garni","year":"2018","unstructured":"Al Garni HZ, Awasthi A, Ramli MAM (2018) Optimal design and analysis of grid-connected photovoltaic under different tracking systems using HOMER. Energy Convers Manag 155:42\u201357. https:\/\/doi.org\/10.1016\/j.enconman.2017.10.090","journal-title":"Energy Convers Manag"},{"key":"10301_CR39","volume-title":"Renewable and efficient electric power systems","author":"GM Masters","year":"2013","unstructured":"Masters GM (2013) Renewable and efficient electric power systems, 2nd edn. Wiley-IEEE Press, Hoboken","edition":"2"},{"issue":"2","key":"10301_CR40","doi-asserted-by":"publisher","first-page":"101872","DOI":"10.1016\/j.asej.2022.101872","volume":"14","author":"A Ramadan","year":"2023","unstructured":"Ramadan A, Ebeed M, Kamel S, Ahmed EM, Tostado-v\u00e9liz M (2023) Optimal allocation of renewable DGs using artificial hummingbird algorithm under uncertainty conditions optimal allocation of renewable DGs using artificial hummingbird algorithm under uncertainty conditions. Ain Shams Eng J 14(2):101872. https:\/\/doi.org\/10.1016\/j.asej.2022.101872","journal-title":"Ain Shams Eng J"},{"key":"10301_CR41","doi-asserted-by":"publisher","first-page":"11342","DOI":"10.1109\/ACCESS.2021.3050307","volume":"9","author":"A Ahmed","year":"2021","unstructured":"Ahmed A, Nadeem MF, Khan I, Alquhayz H, Khan MA, Kiani AT (2021) A novel framework to determine the impact of time varying load models on wind DG planning. IEEE Access 9:11342\u201311357. https:\/\/doi.org\/10.1109\/ACCESS.2021.3050307","journal-title":"IEEE Access"},{"key":"10301_CR42","unstructured":"Meteoblue (2023) Historical weather data for Basel https:\/\/www.meteoblue.com\/en\/weather\/archive\/export. Accessed 13 Apr 2024"},{"key":"10301_CR43","doi-asserted-by":"publisher","first-page":"102723","DOI":"10.1016\/j.scs.2021.102723","volume":"67","author":"GK Suman","year":"2021","unstructured":"Suman GK, Guerrero JM, Roy OP (2021) Optimisation of solar\/wind\/bio-generator\/diesel\/battery based microgrids for rural areas: a PSO-GWO approach. Sustain Cities Soc 67:102723. https:\/\/doi.org\/10.1016\/j.scs.2021.102723","journal-title":"Sustain Cities Soc"},{"key":"10301_CR44","unstructured":"ENERCON E30\/200 https:\/\/www.thewindpower.net\/turbine_en_1109_enercon_e30-200.php .Accessed 13 Apr 2024"},{"key":"10301_CR45","unstructured":"Datasheet, EMMVEE ES 275\u2013295 P72, Photovolta\u00efque module https:\/\/cdn.enfsolar.com\/z\/pp\/dlo60ef67b3db000\/53aa88b5bbe94.pdf. Accessed 13 Apr 2024"},{"issue":"3","key":"10301_CR46","doi-asserted-by":"publisher","first-page":"882","DOI":"10.1109\/TPWRD.2003.813818","volume":"18","author":"J-H Teng","year":"2003","unstructured":"Teng J-H (2003) A direct approach for distribution system load flow solutions. IEEE Trans Power Deliv 18(3):882\u2013887. https:\/\/doi.org\/10.1109\/TPWRD.2003.813818","journal-title":"IEEE Trans Power Deliv"},{"issue":"11","key":"10301_CR47","doi-asserted-by":"publisher","first-page":"2606","DOI":"10.1049\/iet-gtd.2015.1034","volume":"10","author":"AK Bohre","year":"2016","unstructured":"Bohre AK, Agnihotri G, Dubey M (2016) Optimal sizing and sitting of DG with load models using soft computing techniques in practical distribution system. IET Gener Transm Distrib 10(11):2606\u20132621. https:\/\/doi.org\/10.1049\/iet-gtd.2015.1034","journal-title":"IET Gener Transm Distrib"},{"issue":"3","key":"10301_CR48","doi-asserted-by":"publisher","first-page":"3038","DOI":"10.1109\/JSYST.2018.2875177","volume":"13","author":"S Roy Ghatak","year":"2019","unstructured":"Roy Ghatak S, Sannigrahi S, Acharjee P (2019) Multi-objective approach for strategic incorporation of solar energy source, battery storage system, and DSTATCOM in a smart grid environment. IEEE Syst J 13(3):3038\u20133049. https:\/\/doi.org\/10.1109\/JSYST.2018.2875177","journal-title":"IEEE Syst J"},{"key":"10301_CR49","doi-asserted-by":"publisher","DOI":"10.1007\/s13369-020-04808-9","author":"U Raut","year":"2020","unstructured":"Raut U, Mishra S (2020) Enhanced sine-cosine algorithm for optimal planning of distribution network by incorporating network reconfiguration and distributed generation. Arab J Sci Eng. https:\/\/doi.org\/10.1007\/s13369-020-04808-9","journal-title":"Arab J Sci Eng"},{"issue":"5","key":"10301_CR50","doi-asserted-by":"publisher","first-page":"621","DOI":"10.1049\/iet-gtd:20070515","volume":"2","author":"AH Etemadi","year":"2008","unstructured":"Etemadi AH, Fotuhi-Firuzabad M (2008) Distribution system reliability enhancement using optimal capacitor placement. IET Gener Transm Distrib 2(5):621\u2013631. https:\/\/doi.org\/10.1049\/iet-gtd:20070515","journal-title":"IET Gener Transm Distrib"},{"issue":"3","key":"10301_CR51","doi-asserted-by":"publisher","first-page":"4411","DOI":"10.1109\/JSYST.2021.3132300","volume":"16","author":"S Pemmada","year":"2021","unstructured":"Pemmada S, Patne N, Ajay Kumar T, Manchalwar A (2021) Optimal planning of power distribution network by a novel modified jaya algorithm in multiobjective perspective. IEEE Syst J 16(3):4411\u20134422. https:\/\/doi.org\/10.1109\/JSYST.2021.3132300","journal-title":"IEEE Syst J"},{"key":"10301_CR52","unstructured":"IEA Electricity Market Report (2023). Available: https:\/\/www.iea.org\/reports\/electricity-market-report-2023. Accessed 13 Apr 2024"},{"issue":"6","key":"10301_CR53","doi-asserted-by":"publisher","first-page":"3308","DOI":"10.3390\/su13063308","volume":"13","author":"C Venkatesan","year":"2021","unstructured":"Venkatesan C, Kannadasan R, Alsharif MH, Kim MK, Nebhen J (2021) A novel multiobjective hybrid technique for siting and sizing of distributed generation and capacitor banks in radial distribution systems. Sustain 13(6):3308. https:\/\/doi.org\/10.3390\/su13063308","journal-title":"Sustain"},{"issue":"23","key":"10301_CR54","doi-asserted-by":"publisher","first-page":"6185","DOI":"10.3390\/en13236185","volume":"13","author":"E Karunarathne","year":"2020","unstructured":"Karunarathne E, Pasupuleti J, Ekanayake J, Almeida D (2020) Optimal placement and sizing of dgs in distribution networks using mlpso algorithm. Energies 13(23):6185. https:\/\/doi.org\/10.3390\/en13236185","journal-title":"Energies"},{"issue":"3","key":"10301_CR55","doi-asserted-by":"publisher","first-page":"96","DOI":"10.18178\/ijeetc.7.3.96-102","volume":"7","author":"S Ikeda","year":"2018","unstructured":"Ikeda S, Ohmori H (2018) Evaluation for maximum hosting capacity of distributed generation considering active network management. Int J Electr Electron Eng Telecommun 7(3):96\u2013102. https:\/\/doi.org\/10.18178\/ijeetc.7.3.96-102","journal-title":"Int J Electr Electron Eng Telecommun"},{"key":"10301_CR56","volume-title":"Hybrid meta-heuristic algorithms for optimal sizing of hybrid renewable energy system: a review of the state-of-the-art","author":"A Bouaouda","year":"2022","unstructured":"Bouaouda A, Sayouti Y (2022) Hybrid meta-heuristic algorithms for optimal sizing of hybrid renewable energy system: a review of the state-of-the-art, vol 29. Springer, Netherlands"},{"key":"10301_CR57","doi-asserted-by":"publisher","first-page":"106894","DOI":"10.1016\/j.asoc.2020.106894","volume":"99","author":"X li Lu","year":"2021","unstructured":"li Lu X, He G (2021) QPSO algorithm based on L\u00e9vy flight and its application in fuzzy portfolio. Appl Soft Comput 99:106894. https:\/\/doi.org\/10.1016\/j.asoc.2020.106894","journal-title":"Appl Soft Comput"},{"key":"10301_CR58","doi-asserted-by":"publisher","first-page":"695","DOI":"10.1109\/cimca.2005.1631345","volume":"1","author":"HR Tizhoosh","year":"2005","unstructured":"Tizhoosh HR (2005) Opposition-based learning: a new scheme for machine intelligence. Proc Int Conf Comput Intell Model Control Autom CIMCA 2005 Int Conf Intell Agents Web Technol Internet 1:695\u2013701. https:\/\/doi.org\/10.1109\/cimca.2005.1631345","journal-title":"Proc Int Conf Comput Intell Model Control Autom CIMCA 2005 Int Conf Intell Agents Web Technol Internet"},{"key":"10301_CR59","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.swevo.2017.09.010","volume":"39","author":"S Mahdavi","year":"2018","unstructured":"Mahdavi S, Rahnamayan S, Deb K (2018) Opposition based learning: a literature review. Swarm Evol Comput 39:1\u201323. https:\/\/doi.org\/10.1016\/j.swevo.2017.09.010","journal-title":"Swarm Evol Comput"},{"key":"10301_CR60","doi-asserted-by":"publisher","unstructured":"AW Mohamed, AA Hadi, AK Mohamed, NH Awad (2020) Evaluating the performance of adaptive gainingsharing knowledge based algorithm on CEC 2020 benchmark problems. In: 2020 IEEE congress evolutionary computation CEC 2020 conference proceeding, pp 1\u20138. https:\/\/doi.org\/10.1109\/CEC48606.2020.9185901","DOI":"10.1109\/CEC48606.2020.9185901"},{"key":"10301_CR61","doi-asserted-by":"publisher","first-page":"151","DOI":"10.1016\/j.compstruc.2012.07.010","volume":"110\u2013111","author":"H Eskandar","year":"2012","unstructured":"Eskandar H, Sadollah A, Bahreininejad A, Hamdi M (2012) Water cycle algorithm\u2014a novel metaheuristic optimization method for solving constrained engineering optimization problems. Comput Struct 110\u2013111:151\u2013166. https:\/\/doi.org\/10.1016\/j.compstruc.2012.07.010","journal-title":"Comput Struct"},{"issue":"15","key":"10301_CR62","doi-asserted-by":"publisher","first-page":"10733","DOI":"10.1007\/s00521-023-08261-1","volume":"35","author":"HA Shehadeh","year":"2023","unstructured":"Shehadeh HA (2023) Chernobyl disaster optimizer (CDO): a novel meta-heuristic method for global optimization. Neural Comput Appl 35(15):10733\u201310749. https:\/\/doi.org\/10.1007\/s00521-023-08261-1","journal-title":"Neural Comput Appl"},{"issue":"24","key":"10301_CR63","doi-asserted-by":"publisher","first-page":"22465","DOI":"10.1007\/s00521-022-07639-x","volume":"34","author":"AM Khalid","year":"2022","unstructured":"Khalid AM, Hosny KM, Mirjalili S (2022) COVIDOA: a novel evolutionary optimization algorithm based on coronavirus disease replication lifecycle. Neural Comput Appl 34(24):22465\u201322492. https:\/\/doi.org\/10.1007\/s00521-022-07639-x","journal-title":"Neural Comput Appl"},{"issue":"1","key":"10301_CR64","doi-asserted-by":"publisher","first-page":"1030","DOI":"10.1007\/s10489-022-03533-0","volume":"53","author":"H Mohammed","year":"2023","unstructured":"Mohammed H, Rashid T (2023) FOX: a FOX-inspired optimization algorithm. Appl Intell 53(1):1030\u20131050. https:\/\/doi.org\/10.1007\/s10489-022-03533-0","journal-title":"Appl Intell"},{"issue":"1","key":"10301_CR65","doi-asserted-by":"publisher","first-page":"725","DOI":"10.1109\/61.19265","volume":"4","author":"ME Baran","year":"1989","unstructured":"Baran ME, Wu FF (1989) Optimal capacitor placement on radial distribution systems. IEEE Trans Power Deliv 4(1):725\u2013734. https:\/\/doi.org\/10.1109\/61.19265","journal-title":"IEEE Trans Power Deliv"},{"key":"10301_CR66","doi-asserted-by":"publisher","first-page":"34","DOI":"10.1016\/j.ijepes.2014.02.020","volume":"60","author":"SA Taher","year":"2014","unstructured":"Taher SA, Afsari SA (2014) Optimal location and sizing of DSTATCOM in distribution systems by immune algorithm. Int J Electr Power Energy Syst 60:34\u201344. https:\/\/doi.org\/10.1016\/j.ijepes.2014.02.020","journal-title":"Int J Electr Power Energy Syst"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-024-10301-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00521-024-10301-3\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-024-10301-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,26]],"date-time":"2024-11-26T20:05:30Z","timestamp":1732651530000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00521-024-10301-3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,10,1]]},"references-count":66,"journal-issue":{"issue":"36","published-print":{"date-parts":[[2024,12]]}},"alternative-id":["10301"],"URL":"https:\/\/doi.org\/10.1007\/s00521-024-10301-3","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"type":"print","value":"0941-0643"},{"type":"electronic","value":"1433-3058"}],"subject":[],"published":{"date-parts":[[2024,10,1]]},"assertion":[{"value":"6 February 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 July 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"1 October 2024","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 that there is no conflict of interest regarding the publication of this manuscript.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"This article does not contain any studies with human participants or animals performed by any of the authors.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}},{"value":"Not applicable.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Informed Consent"}}]}}