{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,12]],"date-time":"2025-07-12T01:18:49Z","timestamp":1752283129208,"version":"3.37.3"},"reference-count":60,"publisher":"Springer Science and Business Media LLC","issue":"15","license":[{"start":{"date-parts":[[2023,5,2]],"date-time":"2023-05-02T00:00:00Z","timestamp":1682985600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2023,5,2]],"date-time":"2023-05-02T00:00:00Z","timestamp":1682985600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"name":"N\/a"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Soft Comput"],"published-print":{"date-parts":[[2023,8]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Resolving the power crises requires the combination of different individual renewable energy sources so that one source can compensate for another. Unfortunately, renewable energy sources are not always available at certain times making their use problematic. To solve this uncertainty, it is important to combine independent renewable energy sources and determine the right set of the renewable energy mix that is economical and reliable. The sources of renewable energy data are solar PV, wind, battery, and biomass. Different scenarios of renewable energy mix or combination considered are wind\u2013biomass\u2013battery, solar PV\u2013wind\u2013biomass, PV\u2013biomass\u2013battery, and solar PV\u2013wind\u2013biomass\u2013battery. Knowing the economic and reliable impact of these combinations helps to make the best investment decision. The nature-inspired optimization is utilized as the methodology to determine the feasible dimension, economic, and reliability of the energy mix. Historical energy-related data for one year were obtained from the National Renewable Energy Laboratory and was used to evaluate the hybrid renewable energy systems. The result shows that SSP guaranteed optimal economic costs and satisfied the reliability constraints for wind\u2013biomass\u2013battery system, solar PV\u2013wind\u2013biomass system, PV\u2013biomass\u2013battery, and PV\u2013wind\u2013biomass\u2013battery. The outcomes suggests that SSP can provide optimal result and therefore calls for researchers to further explore the potential of integrating this algorithm in their optimization approach for solar PV\u2013wind\u2013biomass\u2013battery hybrid system.\n<\/jats:p>","DOI":"10.1007\/s00500-023-08231-8","type":"journal-article","created":{"date-parts":[[2023,5,2]],"date-time":"2023-05-02T19:03:04Z","timestamp":1683054184000},"page":"10687-10718","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Economic and reliability determination of sustainable renewable energy mix based on social spider prey optimization algorithm"],"prefix":"10.1007","volume":"27","author":[{"given":"Samuel Ofori","family":"Frimpong","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5718-4494","authenticated-orcid":false,"given":"Israel Edem","family":"Agbehadji","sequence":"additional","affiliation":[]},{"given":"Abdultaofeek","family":"Abayomi","sequence":"additional","affiliation":[]},{"given":"Richard C.","family":"Millham","sequence":"additional","affiliation":[]},{"given":"Emmanuel","family":"Freeman","sequence":"additional","affiliation":[]},{"given":"Martin Mabeifam","family":"Ujakpa","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,5,2]]},"reference":[{"issue":"12","key":"8231_CR1","doi-asserted-by":"publisher","first-page":"3351","DOI":"10.3390\/en11123351","volume":"11","author":"M Abd El-salam","year":"2018","unstructured":"Abd El-salam M, Beshr E, Eteiba M (2018) A new hybrid technique for minimizing power losses in a distribution system by optimal sizing and siting of distributed generators with network reconfiguration. Energies (Basel) 11(12):3351. https:\/\/doi.org\/10.3390\/en11123351","journal-title":"Energies (Basel)"},{"issue":"11\u201321","key":"8231_CR2","doi-asserted-by":"publisher","first-page":"2018","DOI":"10.1007\/978-3-319-64795-1_2","volume":"121","author":"M Abdelaziz Mohamed","year":"2017","unstructured":"Abdelaziz Mohamed M, Eltamaly AM (2017) \u201cModeling of hybrid renewable energy system. Stud Syst Decis Control 121(11\u201321):2018. https:\/\/doi.org\/10.1007\/978-3-319-64795-1_2","journal-title":"Stud Syst Decis Control"},{"key":"8231_CR3","doi-asserted-by":"publisher","first-page":"107113","DOI":"10.1016\/j.asoc.2021.107113","volume":"102","author":"BH Abed-Alguni","year":"2021","unstructured":"Abed-Alguni BH, Alawad NA (2021) Distributed Grey Wolf Optimizer for scheduling of workflow applications in cloud environments. Appl Soft Comput 102:107113","journal-title":"Appl Soft Comput"},{"issue":"15","key":"8231_CR4","doi-asserted-by":"publisher","first-page":"10167","DOI":"10.1007\/s00500-021-05939-3","volume":"25","author":"BH Abed-alguni","year":"2021","unstructured":"Abed-alguni BH, Alawad NA, Barhoush M, Hammad R (2021) Exploratory cuckoo search for solving single-objective optimization problems. Soft Comput 25(15):10167\u201310180","journal-title":"Soft Comput"},{"key":"8231_CR5","doi-asserted-by":"publisher","first-page":"113609","DOI":"10.1016\/j.cma.2020.113609","volume":"376","author":"L Abualigah","year":"2021","unstructured":"Abualigah L, Diabat A, Mirjalili S, Abd Elaziz M, Gandomi AH (2021) The arithmetic optimization algorithm. Comput Methods Appl Mech Eng 376:113609. https:\/\/doi.org\/10.1016\/j.cma.2020.113609","journal-title":"Comput Methods Appl Mech Eng"},{"issue":"23","key":"8231_CR6","doi-asserted-by":"publisher","first-page":"4509","DOI":"10.3390\/math10234509","volume":"10","author":"L Abualigah","year":"2022","unstructured":"Abualigah L, Diabat A, Zitar RA (2022) Orthogonal learning Rosenbrock\u2019s direct rotation with the gazelle optimization algorithm for global optimization. Mathematics 10(23):4509","journal-title":"Mathematics"},{"key":"8231_CR7","doi-asserted-by":"publisher","unstructured":"Aggarwal CC, Hinneburg A, Keim DA (2001) On the surprising behavior of distance metrics in high dimensional space. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics),1973:420\u2013434. DOI: https:\/\/doi.org\/10.1007\/3-540-44503-x_27","DOI":"10.1007\/3-540-44503-x_27"},{"issue":"11","key":"8231_CR8","doi-asserted-by":"publisher","first-page":"e0275346","DOI":"10.1371\/journal.pone.0275346","volume":"17","author":"JO Agushaka","year":"2022","unstructured":"Agushaka JO, Akinola O, Ezugwu AE, Oyelade ON, Saha AK (2022) Advanced dwarf mongoose optimization for solving CEC 2011 and CEC 2017 benchmark problems. PLoS ONE 17(11):e0275346","journal-title":"PLoS ONE"},{"key":"8231_CR9","doi-asserted-by":"publisher","first-page":"252","DOI":"10.1016\/j.enconman.2017.04.019","volume":"143","author":"MDA Al-falahi","year":"2017","unstructured":"Al-falahi MDA, Jayasinghe SDG, Enshaei H (2017) A review on recent size optimization methodologies for standalone solar and wind hybrid renewable energy system. Energy Convers Manag 143:252\u2013274. https:\/\/doi.org\/10.1016\/j.enconman.2017.04.019","journal-title":"Energy Convers Manag"},{"issue":"June","key":"8231_CR10","doi-asserted-by":"publisher","first-page":"2502","DOI":"10.1016\/j.rser.2017.06.055","volume":"81","author":"AK Aliyu","year":"2018","unstructured":"Aliyu AK, Modu B, Tan CW (2018) A review of renewable energy development in Africa: a focus in South Africa, Egypt and Nigeria. Renew Sustain Energy Rev 81(June):2502\u20132518. https:\/\/doi.org\/10.1016\/j.rser.2017.06.055","journal-title":"Renew Sustain Energy Rev"},{"key":"8231_CR11","doi-asserted-by":"publisher","DOI":"10.3390\/en13133423","author":"TM Aljohani","year":"2020","unstructured":"Aljohani TM, Ebrahim AF, Mohammed O (2020) Hybrid microgrid energy management and control based on metaheuristic-driven vector-decoupled algorithm considering intermittent renewable sources and electric vehicles charging lot. Energies (Basel). https:\/\/doi.org\/10.3390\/en13133423","journal-title":"Energies (Basel)"},{"key":"8231_CR12","doi-asserted-by":"publisher","DOI":"10.3390\/en13215648","author":"O Approach","year":"2020","unstructured":"Approach O, Torres-madro\u00f1ero JL, Nieto-londo\u00f1o C (2020) Hybrid energy systems sizing for the Colombian context: a genetic algorithm and particle swarm. Energies. https:\/\/doi.org\/10.3390\/en13215648","journal-title":"Energies"},{"key":"8231_CR13","doi-asserted-by":"publisher","first-page":"122467","DOI":"10.1016\/j.jclepro.2020.122467","volume":"270","author":"MA Ashraf","year":"2020","unstructured":"Ashraf MA, Liu Z, Alizadeh A, Nojavan S, Jermsittiparsert K, Zhang D (2020) Designing an optimized configuration for a hybrid PV\/Diesel\/Battery Energy System based on metaheuristics: a case study on Gobi Desert. J Clean Prod 270:122467. https:\/\/doi.org\/10.1016\/j.jclepro.2020.122467","journal-title":"J Clean Prod"},{"issue":"1","key":"8231_CR14","doi-asserted-by":"publisher","first-page":"152","DOI":"10.1049\/iet-rpg.2016.0194","volume":"11","author":"A Askarzadeh","year":"2017","unstructured":"Askarzadeh A (2017) Electrical power generation by an optimised autonomous PV\/wind\/tidal\/battery system. IET Renew Power Gener 11(1):152\u2013164. https:\/\/doi.org\/10.1049\/iet-rpg.2016.0194","journal-title":"IET Renew Power Gener"},{"key":"8231_CR15","doi-asserted-by":"publisher","first-page":"226","DOI":"10.1016\/j.rser.2015.11.053","volume":"56","author":"TR Ayodele","year":"2016","unstructured":"Ayodele TR, Ogunjuyigbe ASO (2016) Wind energy potential of Vesleskarvet and the feasibility of meeting the South Africans SANAE IV energy demand. Renew Sustain Energy Rev 56:226\u2013234. https:\/\/doi.org\/10.1016\/j.rser.2015.11.053","journal-title":"Renew Sustain Energy Rev"},{"key":"8231_CR16","doi-asserted-by":"crossref","unstructured":"Chakraborty S, Saha AK, Ezugwu AE, Agushaka JO, Zitar RA, Abualigah L (2022) Differential evolution and its applications in image processing problems: a comprehensive review. Arch Comput Methods Eng. pp. 1\u201356","DOI":"10.1007\/s11831-022-09825-5"},{"issue":"10","key":"8231_CR17","doi-asserted-by":"publisher","first-page":"1552","DOI":"10.4236\/am.2012.330215","volume":"03","author":"JM Dieterich","year":"2012","unstructured":"Dieterich JM, Hartke B (2012) Empirical review of standard benchmark functions using evolutionary global optimization. Appl Math (irvine) 03(10):1552\u20131564. https:\/\/doi.org\/10.4236\/am.2012.330215","journal-title":"Appl Math (irvine)"},{"issue":"8","key":"8231_CR18","doi-asserted-by":"publisher","first-page":"775","DOI":"10.1080\/15435075.2021.1880911","volume":"18","author":"A Ebrahimi","year":"2021","unstructured":"Ebrahimi A, Attar S, Farhang-Moghaddam B (2021) A multi-objective decision model for residential building energy optimization based on hybrid renewable energy systems. Int J Green Energy 18(8):775\u2013792. https:\/\/doi.org\/10.1080\/15435075.2021.1880911","journal-title":"Int J Green Energy"},{"issue":"4","key":"8231_CR19","doi-asserted-by":"publisher","first-page":"591","DOI":"10.1007\/s11708-018-0567-x","volume":"12","author":"M Faccio","year":"2018","unstructured":"Faccio M, Gamberi M, Bortolini M, Nedaei M (2018) State-of-art review of the optimization methods to design the configuration of hybrid renewable energy systems (HRESs). Front Energy 12(4):591\u2013622. https:\/\/doi.org\/10.1007\/s11708-018-0567-x","journal-title":"Front Energy"},{"issue":"6","key":"8231_CR20","first-page":"72","volume":"3","author":"M Fran","year":"2017","unstructured":"Fran M, Anitha S, Mohan RR (2017) IoT based wind turbine monitoring, fault diagnosis and control using UART. Int J Adv Res Manag Arch Technol Eng 3(6):72\u201376","journal-title":"Int J Adv Res Manag Arch Technol Eng"},{"key":"8231_CR21","doi-asserted-by":"crossref","unstructured":"Frimpong SO, Agbehadji IE, Millham R, Jung JJ (2020) Nature-inspired search method for cost optimization of hybrid renewable energy generation at the edge. In: 2020 International conference on artificial intelligence, big data, computing and data communication systems (icABCD), 2020, pp. 1\u20136","DOI":"10.1109\/icABCD49160.2020.9183811"},{"key":"8231_CR22","doi-asserted-by":"crossref","unstructured":"Frimpong SO, Millham RC, Agbehadji IE (2021) A comprehensive review of nature-inspired search techniques used in estimating optimal configuration size, cost, and reliability of a mini-grid HRES: A systemic review. In: International Conference on Computational Science and Its Applications, pp. 492\u2013507","DOI":"10.1007\/978-3-030-87013-3_37"},{"key":"8231_CR23","doi-asserted-by":"publisher","DOI":"10.1007\/s40305-021-00341-0","author":"DK Geleta","year":"2021","unstructured":"Geleta DK, Manshahia MS (2021) A hybrid of grey wolf optimization and genetic algorithm for optimization of hybrid wind and solar renewable energy system. J Oper Res Soc China. https:\/\/doi.org\/10.1007\/s40305-021-00341-0","journal-title":"J Oper Res Soc China"},{"key":"8231_CR24","doi-asserted-by":"publisher","first-page":"116754","DOI":"10.1016\/j.energy.2019.116754","volume":"193","author":"A Ghaffari","year":"2020","unstructured":"Ghaffari A, Askarzadeh A (2020) Design optimization of a hybrid system subject to reliability level and renewable energy penetration. Energy 193:116754. https:\/\/doi.org\/10.1016\/j.energy.2019.116754","journal-title":"Energy"},{"key":"8231_CR25","doi-asserted-by":"publisher","DOI":"10.5772\/65971","author":"M Ghofrani","year":"2016","unstructured":"Ghofrani M, Hosseini NN (2016) Optimizing hybrid renewable energy systems: a review. Sustain Energy Technol Issues Appl Case Stud. https:\/\/doi.org\/10.5772\/65971","journal-title":"Sustain Energy Technol Issues Appl Case Stud"},{"key":"8231_CR26","unstructured":"Hassas MA, Pourhossein K, Azad VT (2017) A comprehensive review of optimal sizing methods for hybrid renewable energy systems. In: 3rd international conference of IEA technology and energy management, pp. 1\u20139"},{"key":"8231_CR27","doi-asserted-by":"publisher","unstructured":"Husain S, Shrivastava NA (2020) A comparative analysis of multi-objective optimization algorithms for stand-alone hybrid renewable energy system. In: 2nd International Conference on Innovative Mechanisms for Industry Applications, ICIMIA 2020 - Conference Proceedings, 2020, no. Icimia, pp. 255\u2013260. DOI: https:\/\/doi.org\/10.1109\/ICIMIA48430.2020.9074903","DOI":"10.1109\/ICIMIA48430.2020.9074903"},{"key":"8231_CR28","doi-asserted-by":"publisher","first-page":"100740","DOI":"10.1016\/j.esr.2021.100740","volume":"38","author":"ID Ibrahim","year":"2021","unstructured":"Ibrahim ID et al (2021) A review on Africa energy supply through renewable energy production: Nigeria, Cameroon, Ghana and South Africa as a case study. Energy Strategy Rev 38:100740. https:\/\/doi.org\/10.1016\/j.esr.2021.100740","journal-title":"Energy Strategy Rev"},{"key":"8231_CR29","doi-asserted-by":"publisher","first-page":"727","DOI":"10.1016\/j.solener.2017.06.070","volume":"155","author":"A Kaabeche","year":"2017","unstructured":"Kaabeche A, Diaf S, Ibtiouen R (2017) Firefly-inspired algorithm for optimal sizing of renewable hybrid system considering reliability criteria. Sol Energy 155:727\u2013738. https:\/\/doi.org\/10.1016\/j.solener.2017.06.070","journal-title":"Sol Energy"},{"key":"8231_CR30","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-15-9968-2","author":"VKRA Kalananda","year":"2021","unstructured":"Kalananda VKRA, Komanapalli VLN (2021) Nature-inspired optimization algorithms for renewable energy generation, distribution and management\u2014a comprehensive review. Intell Paradig Smart Grid Renew Energy Syst. https:\/\/doi.org\/10.1007\/978-981-15-9968-2","journal-title":"Intell Paradig Smart Grid Renew Energy Syst"},{"issue":"11","key":"8231_CR31","first-page":"174","volume":"2","author":"B Kalappan","year":"2013","unstructured":"Kalappan B, Ponnudsamy V (2013) Modeling, simulation and optimization of hybrid renewable power system for daily load demand of metropolitan cities in India. Am J Eng Res 2(11):174\u2013184","journal-title":"Am J Eng Res"},{"key":"8231_CR32","doi-asserted-by":"publisher","first-page":"13655","DOI":"10.1109\/ACCESS.2021.3051573","volume":"9","author":"M Kharrich","year":"2021","unstructured":"Kharrich M et al (2021) Developed approach based on equilibrium optimizer for optimal design of hybrid PV\/Wind\/Diesel\/Battery Microgrid in Dakhla, Morocco. IEEE Access 9:13655\u201313670. https:\/\/doi.org\/10.1109\/ACCESS.2021.3051573","journal-title":"IEEE Access"},{"issue":"20","key":"8231_CR33","doi-asserted-by":"publisher","first-page":"4285","DOI":"10.1049\/iet-gtd.2020.0453","volume":"14","author":"R Khezri","year":"2020","unstructured":"Khezri R, Mahmoudi A (2020) Review on the state-of-the-art multi-objective optimisation of hybrid standalone\/gridconnected energy systems. IET Gener Transm Distrib 14(20):4285\u20134300. https:\/\/doi.org\/10.1049\/iet-gtd.2020.0453","journal-title":"IET Gener Transm Distrib"},{"key":"8231_CR34","doi-asserted-by":"publisher","first-page":"24925","DOI":"10.1109\/ACCESS.2018.2832460","volume":"6","author":"A Kumar","year":"2018","unstructured":"Kumar A, Member GS, Singh AR, Deng YAN (2018) A Novel Methodological framework for the design of sustainable rural microgrid for developing nations. IEEE Access 6:24925\u201324951. https:\/\/doi.org\/10.1109\/ACCESS.2018.2832460","journal-title":"IEEE Access"},{"key":"8231_CR35","doi-asserted-by":"publisher","first-page":"514","DOI":"10.1016\/j.ijepes.2016.04.008","volume":"83","author":"A Maleki","year":"2016","unstructured":"Maleki A, Khajeh MG, Ameri M (2016) Optimal sizing of a grid independent hybrid renewable energy system incorporating resource uncertainty, and load uncertainty. Int J Electr Power Energy Syst 83:514\u2013524. https:\/\/doi.org\/10.1016\/j.ijepes.2016.04.008","journal-title":"Int J Electr Power Energy Syst"},{"issue":"6","key":"8231_CR36","doi-asserted-by":"publisher","first-page":"436","DOI":"10.1080\/02286203.2019.1650488","volume":"40","author":"S Mandal","year":"2020","unstructured":"Mandal S (2020) Modeling of photovoltaic systems using Modified Elephant Swarm Water Search Algorithm Modeling of photovoltaic systems using Modified Elephant Swarm Water Search. Int J Model Simul 40(6):436\u2013455. https:\/\/doi.org\/10.1080\/02286203.2019.1650488","journal-title":"Int J Model Simul"},{"issue":"February","key":"8231_CR37","doi-asserted-by":"publisher","first-page":"515","DOI":"10.1016\/j.rser.2017.04.048","volume":"77","author":"MA Mohamed","year":"2017","unstructured":"Mohamed MA, Eltamaly AM, Alolah AI (2017) Swarm intelligence-based optimization of grid-dependent hybrid renewable energy systems. Renew Sustain Energy Rev 77(February):515\u2013524. https:\/\/doi.org\/10.1016\/j.rser.2017.04.048","journal-title":"Renew Sustain Energy Rev"},{"key":"8231_CR38","doi-asserted-by":"publisher","first-page":"114224","DOI":"10.1016\/j.apenergy.2019.114224","volume":"259","author":"S Mohseni","year":"2020","unstructured":"Mohseni S, Brent AC, Burmester D (2020) A comparison of metaheuristics for the optimal capacity planning of an. Appl Energy 259:114224. https:\/\/doi.org\/10.1016\/j.apenergy.2019.114224","journal-title":"Appl Energy"},{"key":"8231_CR39","doi-asserted-by":"publisher","first-page":"119605","DOI":"10.1016\/j.energy.2020.119605","volume":"219","author":"C Mokhtara","year":"2021","unstructured":"Mokhtara C, Negrou B, Settou N, Settou B, Samy MM (2021) Design optimization of off-grid Hybrid Renewable Energy Systems considering the effects of building energy performance and climate change: case study of Algeria. Energy 219:119605. https:\/\/doi.org\/10.1016\/j.energy.2020.119605","journal-title":"Energy"},{"issue":"7","key":"8231_CR40","doi-asserted-by":"publisher","first-page":"2383","DOI":"10.1007\/s12649-017-9923-z","volume":"8","author":"K Mugodo","year":"2017","unstructured":"Mugodo K, Magama PP, Dhavu K (2017) Biogas production potential from agricultural and agro-processing waste in South Africa. Waste Biomass Valoriz 8(7):2383\u20132392. https:\/\/doi.org\/10.1007\/s12649-017-9923-z","journal-title":"Waste Biomass Valoriz"},{"issue":"1","key":"8231_CR41","doi-asserted-by":"publisher","first-page":"25","DOI":"10.1080\/15435075.2010.529407","volume":"8","author":"AESA Nafeh","year":"2011","unstructured":"Nafeh AESA (2011) Optimal economical sizing of a PV-wind hybrid energy system using genetic algorithm. Int J Green Energy 8(1):25\u201343. https:\/\/doi.org\/10.1080\/15435075.2010.529407","journal-title":"Int J Green Energy"},{"issue":"12","key":"8231_CR42","first-page":"9382","volume":"3","author":"R Nagalakshmi","year":"2014","unstructured":"Nagalakshmi R, Babu BK, Prashanth D (2014) Design and development of a remote monitoring and maintenance of solar plant supervisory system. Int J Eng Comput Sci 3(12):9382\u20139385","journal-title":"Int J Eng Comput Sci"},{"issue":"5","key":"8231_CR43","doi-asserted-by":"publisher","first-page":"723","DOI":"10.1080\/0952813X.2018.1550814","volume":"31","author":"M Nazari-Heris","year":"2019","unstructured":"Nazari-Heris M, Mohammadi-Ivatloo B, Asadi S, Kim JH, Geem ZW (2019) Harmony search algorithm for energy system applications: an updated review and analysis. J Exp Theor Artif Intell 31(5):723\u2013749. https:\/\/doi.org\/10.1080\/0952813X.2018.1550814","journal-title":"J Exp Theor Artif Intell"},{"issue":"20","key":"8231_CR44","doi-asserted-by":"publisher","first-page":"8495","DOI":"10.3390\/su12208495","volume":"12","author":"T-H Nguyen","year":"2020","unstructured":"Nguyen T-H, Nguyen LV, Jung JJ, Agbehadji IE, Frimpong SO, Millham RC (2020) Bio-inspired approaches for smart energy management: state of the art and challenges. Sustainability 12(20):8495","journal-title":"Sustainability"},{"key":"8231_CR45","unstructured":"Power Africa in South Africa | Power Africa | U.S. Agency for International Development (2022) https:\/\/www.usaid.gov\/powerafrica\/south-africa. Accessed Sep 30, 2022"},{"key":"8231_CR46","unstructured":"PVWatts Calculator (2023) https:\/\/pvwatts.nrel.gov\/pvwatts.php. Accessed Jan 07 2023"},{"issue":"14","key":"8231_CR47","first-page":"121","volume":"9","author":"RM Rasli","year":"2019","unstructured":"Rasli RM, Aziz NAA, Razali FM, Norwawi NM, Basir N (2019) A preliminary survey on artificial immune systems (AIS): a review on their techniques, strengths and drawbacks. Int J Acad Res Bus Soc Sci 9(14):121\u2013144","journal-title":"Int J Acad Res Bus Soc Sci"},{"issue":"1","key":"8231_CR48","doi-asserted-by":"publisher","first-page":"433","DOI":"10.1007\/s42835-019-00184-z","volume":"15","author":"SR Sandeep","year":"2020","unstructured":"Sandeep SR, Nandihalli R (2020) Optimal sizing in hybrid renewable energy system with the aid of opposition based social spider optimization. J Electr Eng Technol 15(1):433\u2013440. https:\/\/doi.org\/10.1007\/s42835-019-00184-z","journal-title":"J Electr Eng Technol"},{"key":"8231_CR49","doi-asserted-by":"publisher","first-page":"178","DOI":"10.1016\/j.enconman.2016.09.046","volume":"128","author":"S Singh","year":"2016","unstructured":"Singh S, Singh M, Kaushik SC, Chandra S (2016) Feasibility study of an islanded microgrid in rural area consisting of PV, wind, biomass and battery energy storage system. Energy Convers Manag 128:178\u2013190. https:\/\/doi.org\/10.1016\/j.enconman.2016.09.046","journal-title":"Energy Convers Manag"},{"key":"8231_CR50","doi-asserted-by":"publisher","first-page":"755","DOI":"10.1016\/j.rser.2015.05.040","volume":"50","author":"S Sinha","year":"2015","unstructured":"Sinha S, Chandel SS (2015) Review of recent trends in optimization techniques for solar photovoltaic-wind based hybrid energy systems. Renew Sustain Energy Rev 50:755\u2013769. https:\/\/doi.org\/10.1016\/j.rser.2015.05.040","journal-title":"Renew Sustain Energy Rev"},{"key":"8231_CR51","unstructured":"Stage 4 loadshedding will continue to be implemented throughout Thursday and Friday, with a possibility of lower stages from Saturday morning. \u2013 Eskom (2022) https:\/\/www.eskom.co.za\/stage-4-loadshedding-will-continue-to-be-implemented-throughout-thursday-and-friday-with-a-possibility-of-lower-stages-from-saturday-morning\/. Accessed Sep 30, 2022"},{"issue":"1","key":"8231_CR52","doi-asserted-by":"publisher","first-page":"1001","DOI":"10.1016\/j.aej.2020.10.027","volume":"60","author":"HM Sultan","year":"2021","unstructured":"Sultan HM, Menesy AS, Kamel S, Korashy A, Almohaimeed SA, Abdel-Akher M (2021) An improved artificial ecosystem optimization algorithm for optimal configuration of a hybrid PV\/WT\/FC energy system. Alex Eng J 60(1):1001\u20131025. https:\/\/doi.org\/10.1016\/j.aej.2020.10.027","journal-title":"Alex Eng J"},{"key":"8231_CR53","doi-asserted-by":"publisher","first-page":"594","DOI":"10.1016\/j.egyr.2020.01.013","volume":"6","author":"V Suresh","year":"2020","unstructured":"Suresh V, Muralidhar M, Kiranmayi R (2020) Modelling and optimization of an off-grid hybrid renewable energy system for electrification in a rural areas. Energy Rep 6:594\u2013604. https:\/\/doi.org\/10.1016\/j.egyr.2020.01.013","journal-title":"Energy Rep"},{"key":"8231_CR54","doi-asserted-by":"publisher","first-page":"840","DOI":"10.1016\/j.rser.2017.01.118","volume":"73","author":"T Tezer","year":"2017","unstructured":"Tezer T, Yaman R, Yaman G (2017) Evaluation of approaches used for optimization of stand-alone hybrid renewable energy systems. Renew Sustain Energy Rev 73:840\u2013853. https:\/\/doi.org\/10.1016\/j.rser.2017.01.118","journal-title":"Renew Sustain Energy Rev"},{"issue":"21","key":"8231_CR55","doi-asserted-by":"publisher","first-page":"1","DOI":"10.3390\/en13215648","volume":"13","author":"JL Torres-madro\u00f1ero","year":"2020","unstructured":"Torres-madro\u00f1ero JL, Nieto-Londo\u00f1o C, Sierra-P\u00e9rez J, Approach O, Torres-madro\u00f1ero JL, Nieto-Londo\u00f1o C (2020) Hybrid energy systems sizing for the colombian context: a genetic algorithm and particle swarm optimization approach. Energies (basel) 13(21):1\u201330. https:\/\/doi.org\/10.3390\/en13215648","journal-title":"Energies (basel)"},{"issue":"April","key":"8231_CR56","doi-asserted-by":"publisher","first-page":"320","DOI":"10.1016\/j.scs.2018.05.027","volume":"41","author":"S Twaha","year":"2018","unstructured":"Twaha S, Ramli MAM (2018) A review of optimization approaches for hybrid distributed energy generation systems : Off -grid and grid-connected systems. Sustain Cities Soc 41(April):320\u2013331. https:\/\/doi.org\/10.1016\/j.scs.2018.05.027","journal-title":"Sustain Cities Soc"},{"issue":"2","key":"8231_CR57","doi-asserted-by":"publisher","first-page":"170","DOI":"10.3102\/10769986023002170","volume":"23","author":"A Vargha","year":"1998","unstructured":"Vargha A, Delaney HD (1998) The Kruskal-Wallis test and stochastic homogeneity. J Educ Behav Stat 23(2):170\u2013192. https:\/\/doi.org\/10.3102\/10769986023002170","journal-title":"J Educ Behav Stat"},{"key":"8231_CR58","doi-asserted-by":"publisher","DOI":"10.3390\/en11010085","author":"H Xiao","year":"2018","unstructured":"Xiao H, Pei W, Dong Z, Kong L, Wang D (2018) Application and comparison of metaheuristic and new metamodel based global optimization. Energies. https:\/\/doi.org\/10.3390\/en11010085","journal-title":"Energies"},{"key":"8231_CR59","doi-asserted-by":"publisher","first-page":"614","DOI":"10.1016\/j.asoc.2015.02.014","volume":"30","author":"JJQ Yu","year":"2015","unstructured":"Yu JJQ, Li VOK (2015) A social spider algorithm for global optimization. Appl Soft Comput J 30:614\u2013627. https:\/\/doi.org\/10.1016\/j.asoc.2015.02.014","journal-title":"Appl Soft Comput J"},{"issue":"1","key":"8231_CR60","doi-asserted-by":"publisher","first-page":"462","DOI":"10.1016\/j.rser.2009.07.025","volume":"14","author":"I Y\u00fcksel","year":"2010","unstructured":"Y\u00fcksel I (2010) Hydropower for sustainable water and energy development. Renew Sustain Energy Rev 14(1):462\u2013469. https:\/\/doi.org\/10.1016\/j.rser.2009.07.025","journal-title":"Renew Sustain Energy Rev"}],"container-title":["Soft Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00500-023-08231-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00500-023-08231-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00500-023-08231-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,6,16]],"date-time":"2023-06-16T16:09:33Z","timestamp":1686931773000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00500-023-08231-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,5,2]]},"references-count":60,"journal-issue":{"issue":"15","published-print":{"date-parts":[[2023,8]]}},"alternative-id":["8231"],"URL":"https:\/\/doi.org\/10.1007\/s00500-023-08231-8","relation":{},"ISSN":["1432-7643","1433-7479"],"issn-type":[{"type":"print","value":"1432-7643"},{"type":"electronic","value":"1433-7479"}],"subject":[],"published":{"date-parts":[[2023,5,2]]},"assertion":[{"value":"8 April 2023","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 May 2023","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Authors declare that there is no conflict of interest issues.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflicts 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"}}]}}