{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T13:04:01Z","timestamp":1740143041243,"version":"3.37.3"},"reference-count":59,"publisher":"Springer Science and Business Media LLC","issue":"28","license":[{"start":{"date-parts":[[2021,9,1]],"date-time":"2021-09-01T00:00:00Z","timestamp":1630454400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2021,9,1]],"date-time":"2021-09-01T00:00:00Z","timestamp":1630454400000},"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":["Environ Sci Pollut Res"],"DOI":"10.1007\/s11356-021-16072-x","type":"journal-article","created":{"date-parts":[[2021,9,1]],"date-time":"2021-09-01T19:02:57Z","timestamp":1630522977000},"page":"71726-71740","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["New modified algorithm: \u03b8-turbulent flow of water-based optimization"],"prefix":"10.1007","volume":"30","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1466-1702","authenticated-orcid":false,"given":"Amirreza","family":"Naderipour","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Iraj Faraji","family":"Davoudkhani","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zulkurnain","family":"Abdul-Malek","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,9,1]]},"reference":[{"key":"16072_CR1","first-page":"65","volume":"17","author":"N Bakhshinezhad","year":"2020","unstructured":"Bakhshinezhad N, Mir Mohammad Sadeghi SA, Fathi AR, Mohammadi Daniali HR (2020) Adaptive particularly tunable fuzzy particle swarm optimization algorithm. Iran J Fuzzy Syst 17:65\u201375","journal-title":"Iran J Fuzzy Syst"},{"key":"16072_CR2","doi-asserted-by":"crossref","first-page":"213","DOI":"10.1016\/j.ijepes.2016.03.024","volume":"82","author":"M Basu","year":"2016","unstructured":"Basu M (2016) Multi-objective optimal reactive power dispatch using multi-objective differential evolution. Int J Electr Power Energy Syst 82:213\u2013224","journal-title":"Int J Electr Power Energy Syst"},{"key":"16072_CR3","doi-asserted-by":"crossref","first-page":"396","DOI":"10.1016\/j.ijepes.2015.07.037","volume":"74","author":"B Bhattacharyya","year":"2016","unstructured":"Bhattacharyya B, Raj S (2016) PSO based bio inspired algorithms for reactive power planning. Int J Electr Power Energy Syst 74:396\u2013402","journal-title":"Int J Electr Power Energy Syst"},{"key":"16072_CR4","doi-asserted-by":"crossref","first-page":"616","DOI":"10.1016\/j.asoc.2018.11.042","volume":"75","author":"PP Biswas","year":"2019","unstructured":"Biswas PP, Suganthan PN, Mallipeddi R, Amaratunga GAJ (2019) Optimal reactive power dispatch with uncertainties in load demand and renewable energy sources adopting scenario-based approach. Appl Soft Comput 75:616\u2013632","journal-title":"Appl Soft Comput"},{"key":"16072_CR5","doi-asserted-by":"crossref","first-page":"1218","DOI":"10.1109\/TPWRS.2009.2021226","volume":"24","author":"C Dai","year":"2009","unstructured":"Dai C, Chen W, Zhu Y, Zhang X (2009) Seeker optimization algorithm for optimal reactive power dispatch. IEEE Trans power Syst 24:1218\u20131231","journal-title":"IEEE Trans power Syst"},{"key":"16072_CR6","doi-asserted-by":"crossref","first-page":"1151","DOI":"10.1016\/j.ijepes.2010.06.014","volume":"32","author":"D Devaraj","year":"2010","unstructured":"Devaraj D, Roselyn JP (2010) Genetic algorithm based reactive power dispatch for voltage stability improvement. Int J Electr Power Energy Syst 32:1151\u20131156","journal-title":"Int J Electr Power Energy Syst"},{"key":"16072_CR7","doi-asserted-by":"crossref","first-page":"231","DOI":"10.1016\/j.ins.2014.03.050","volume":"278","author":"M Ghasemi","year":"2014","unstructured":"Ghasemi M, Ghanbarian MM, Ghavidel S, Rahmani S, Mahboubi Moghaddam E (2014a) Modified teaching learning algorithm and double differential evolution algorithm for optimal reactive power dispatch problem: a comparative study. Inf Sci (Ny) 278:231\u2013249","journal-title":"Inf Sci (Ny)"},{"key":"16072_CR8","doi-asserted-by":"crossref","first-page":"126","DOI":"10.1016\/j.asoc.2014.05.006","volume":"22","author":"M Ghasemi","year":"2014","unstructured":"Ghasemi M, Ghavidel S, Ghanbarian MM, Habibi A (2014b) A new hybrid algorithm for optimal reactive power dispatch problem with discrete and continuous control variables. Appl Soft Comput 22:126\u2013140","journal-title":"Appl Soft Comput"},{"key":"16072_CR9","doi-asserted-by":"crossref","first-page":"103666","DOI":"10.1016\/j.engappai.2020.103666","volume":"92","author":"M Ghasemi","year":"2020","unstructured":"Ghasemi M, Davoudkhani IF, Akbari E, Rahimnejad A, Ghavidel S, Li L (2020) A novel and effective optimization algorithm for global optimization and its engineering applications: turbulent flow of water-based optimization (TFWO). Eng Appl Artif Intell 92:103666","journal-title":"Eng Appl Artif Intell"},{"key":"16072_CR10","doi-asserted-by":"crossref","first-page":"103963","DOI":"10.1016\/j.engappai.2020.103963","volume":"96","author":"MN Gilvaei","year":"2020","unstructured":"Gilvaei MN, Jafari H, Ghadi MJ, Li L (2020) A novel hybrid optimization approach for reactive power dispatch problem considering voltage stability index. Eng Appl Artif Intell 96:103963","journal-title":"Eng Appl Artif Intell"},{"key":"16072_CR11","doi-asserted-by":"crossref","first-page":"657","DOI":"10.1016\/j.asoc.2017.04.048","volume":"57","author":"AA Heidari","year":"2017","unstructured":"Heidari AA, Abbaspour RA, Jordehi AR (2017) Gaussian bare-bones water cycle algorithm for optimal reactive power dispatch in electrical power systems. Appl Soft Comput 57:657\u2013671","journal-title":"Appl Soft Comput"},{"key":"16072_CR12","doi-asserted-by":"crossref","first-page":"780","DOI":"10.1002\/etep.1730","volume":"24","author":"L Hongxin","year":"2014","unstructured":"Hongxin L, Yinhong L, Jinfu C (2014) Adaptive multiple evolutionary algorithms search for multi-objective optimal reactive power dispatch. Int Trans Electr Energy Syst 24:780\u2013795","journal-title":"Int Trans Electr Energy Syst"},{"key":"16072_CR13","doi-asserted-by":"crossref","unstructured":"Jafar-Nowdeh A, Babanezhad M, Arabi-Nowdeh S et al (2020) Meta-heuristic matrix moth-flame algorithm for optimal reconfiguration of distribution networks and placement of solar and wind renewable sources considering reliability. Environ Technol Innov 101118","DOI":"10.1016\/j.eti.2020.101118"},{"key":"16072_CR14","doi-asserted-by":"crossref","first-page":"7854","DOI":"10.1007\/s11356-020-11089-0","volume":"28","author":"MN Jahromi","year":"2021","unstructured":"Jahromi MN, Gomeh Z, Busico G, Barzegar R, Samany NN, Aalami MT, Tedesco D, Mastrocicco M, Kazakis N (2021) Developing a SINTACS-based method to map groundwater multi-pollutant vulnerability using evolutionary algorithms. Environ Sci Pollut Res 28:7854\u20137869","journal-title":"Environ Sci Pollut Res"},{"key":"16072_CR15","doi-asserted-by":"crossref","first-page":"232","DOI":"10.1016\/j.ijepes.2015.01.021","volume":"69","author":"B Kanna","year":"2015","unstructured":"Kanna B, Singh SN (2015) Towards reactive power dispatch within a wind farm using hybrid PSO. Int J Electr Power Energy Syst 69:232\u2013240","journal-title":"Int J Electr Power Energy Syst"},{"key":"16072_CR16","doi-asserted-by":"crossref","first-page":"684","DOI":"10.1016\/j.ijepes.2010.11.018","volume":"33","author":"AH Khazali","year":"2011","unstructured":"Khazali AH, Kalantar M (2011) Optimal reactive power dispatch based on harmony search algorithm. Int J Electr Power Energy Syst 33:684\u2013692","journal-title":"Int J Electr Power Energy Syst"},{"key":"16072_CR17","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1049\/iet-gtd.2010.0256","volume":"5","author":"A Khorsandi","year":"2011","unstructured":"Khorsandi A, Alimardani A, Vahidi B, Hosseinian SH (2011) Hybrid shuffled frog leaping algorithm and Nelder\u2013Mead simplex search for optimal reactive power dispatch. IET Gener Transm Distrib 5:249\u2013256","journal-title":"IET Gener Transm Distrib"},{"key":"16072_CR18","doi-asserted-by":"crossref","first-page":"980","DOI":"10.1080\/15325008.2017.1311387","volume":"45","author":"Y Li","year":"2017","unstructured":"Li Y, Li X, Li Z (2017) Reactive power optimization using hybrid CABC-DE algorithm. Electr power components Syst 45:980\u2013989","journal-title":"Electr power components Syst"},{"key":"16072_CR19","doi-asserted-by":"crossref","first-page":"641","DOI":"10.1016\/j.asoc.2009.08.038","volume":"10","author":"K Mahadevan","year":"2010","unstructured":"Mahadevan K, Kannan PS (2010) Comprehensive learning particle swarm optimization for reactive power dispatch. Appl Soft Comput 10:641\u2013652","journal-title":"Appl Soft Comput"},{"key":"16072_CR20","doi-asserted-by":"crossref","first-page":"334","DOI":"10.1049\/iet-sen.2009.0079","volume":"4","author":"DJ Mala","year":"2010","unstructured":"Mala DJ, Mohan V, Kamalapriya M (2010) Automated software test optimisation framework\u2013an artificial bee colony optimisation-based approach. IET Softw 4:334\u2013348","journal-title":"IET Softw"},{"key":"16072_CR21","doi-asserted-by":"crossref","first-page":"104","DOI":"10.1016\/j.ijepes.2016.03.039","volume":"83","author":"M Mehdinejad","year":"2016","unstructured":"Mehdinejad M, Mohammadi-Ivatloo B, Dadashzadeh-Bonab R, Zare K (2016) Solution of optimal reactive power dispatch of power systems using hybrid particle swarm optimization and imperialist competitive algorithms. Int J Electr Power Energy Syst 83:104\u2013116","journal-title":"Int J Electr Power Energy Syst"},{"key":"16072_CR22","doi-asserted-by":"crossref","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","journal-title":"Adv Eng Softw"},{"key":"16072_CR23","doi-asserted-by":"crossref","first-page":"598","DOI":"10.1016\/j.renene.2015.07.021","volume":"85","author":"SM Mohseni-Bonab","year":"2016","unstructured":"Mohseni-Bonab SM, Rabiee A, Mohammadi-Ivatloo B (2016) Voltage stability constrained multi-objective optimal reactive power dispatch under load and wind power uncertainties: a stochastic approach. Renew Energy 85:598\u2013609","journal-title":"Renew Energy"},{"key":"16072_CR24","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1016\/j.ijepes.2016.02.039","volume":"82","author":"A Mukherjee","year":"2016","unstructured":"Mukherjee A, Mukherjee V (2016) Chaos embedded krill herd algorithm for optimal VAR dispatch problem of power system. Int J Electr Power Energy Syst 82:37\u201348","journal-title":"Int J Electr Power Energy Syst"},{"key":"16072_CR25","doi-asserted-by":"crossref","first-page":"441","DOI":"10.1016\/j.asoc.2017.01.012","volume":"53","author":"E Naderi","year":"2017","unstructured":"Naderi E, Narimani H, Fathi M, Narimani MR (2017) A novel fuzzy adaptive configuration of particle swarm optimization to solve large-scale optimal reactive power dispatch. Appl Soft Comput 53:441\u2013456","journal-title":"Appl Soft Comput"},{"key":"16072_CR26","doi-asserted-by":"publisher","first-page":"182611","DOI":"10.1109\/ACCESS.2019.2958964","volume":"7","author":"A Naderipour","year":"2019","unstructured":"Naderipour A, Abdul-Malek Z, Zahedi Vahid M, Mirzaei Seifabad Z, Hajivand M, Arabi-Nowdeh S (2019) Optimal, reliable and cost-effective framework of photovoltaic-wind-battery energy system design considering outage concept using grey wolf optimizer algorithm - case study for Iran. IEEE Access 7:182611\u2013182623. https:\/\/doi.org\/10.1109\/ACCESS.2019.2958964","journal-title":"IEEE Access"},{"key":"16072_CR27","doi-asserted-by":"publisher","first-page":"124207","DOI":"10.1016\/j.jclepro.2020.124207","volume":"283","author":"A Naderipour","year":"2021","unstructured":"Naderipour A, Abdul-Malek Z, Nowdeh SA, Kamyab H, Ramtin AR, Shahrokhi S, Kleme\u0161 JJ (2021) Comparative evaluation of hybrid photovoltaic, wind, tidal and fuel cell clean system design for different regions with remote application considering cost. J Clean Prod 283:124207. https:\/\/doi.org\/10.1016\/j.jclepro.2020.124207","journal-title":"J Clean Prod"},{"key":"16072_CR28","doi-asserted-by":"crossref","unstructured":"Nakawiro W, Erlich I, Rueda JL (2011) A novel optimization algorithm for optimal reactive power dispatch: a comparative study. In: 2011 4th International Conference on Electric Utility Deregulation and Restructuring and Power Technologies (DRPT). IEEE, pp 1555\u20131561","DOI":"10.1109\/DRPT.2011.5994144"},{"key":"16072_CR29","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1016\/j.enconman.2012.08.016","volume":"66","author":"T Niknam","year":"2013","unstructured":"Niknam T, Bornapour M, Gheisari A (2013a) Combined heat, power and hydrogen production optimal planning of fuel cell power plants in distribution networks. Energy Convers Manag 66:11\u201325","journal-title":"Energy Convers Manag"},{"key":"16072_CR30","doi-asserted-by":"crossref","first-page":"742","DOI":"10.1109\/JSYST.2012.2227217","volume":"7","author":"T Niknam","year":"2013","unstructured":"Niknam T, Narimani MR, Azizipanah-Abarghooee R, Bahmani-Firouzi B (2013b) Multiobjective optimal reactive power dispatch and voltage control: a new opposition-based self-adaptive modified gravitational search algorithm. IEEE Syst J 7:742\u2013753","journal-title":"IEEE Syst J"},{"key":"16072_CR31","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1016\/j.knosys.2019.01.018","volume":"171","author":"P Niu","year":"2019","unstructured":"Niu P, Niu S, Chang L (2019) The defect of the grey wolf optimization algorithm and its verification method. Knowledge-Based Syst 171:37\u201343","journal-title":"Knowledge-Based Syst"},{"key":"16072_CR32","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1016\/j.eswa.2017.06.009","volume":"87","author":"K Nuaekaew","year":"2017","unstructured":"Nuaekaew K, Artrit P, Pholdee N, Bureerat S (2017) Optimal reactive power dispatch problem using a two-archive multi-objective grey wolf optimizer. Expert Syst Appl 87:79\u201389","journal-title":"Expert Syst Appl"},{"key":"16072_CR33","doi-asserted-by":"crossref","first-page":"116644","DOI":"10.1016\/j.energy.2019.116644","volume":"192","author":"A Parizad","year":"2020","unstructured":"Parizad A, Hatziadoniu K (2020) Security\/stability-based Pareto optimal solution for distribution networks planning implementing NSGAII\/FDMT. Energy 192:116644","journal-title":"Energy"},{"key":"16072_CR34","doi-asserted-by":"crossref","first-page":"106915","DOI":"10.1016\/j.ijepes.2021.106915","volume":"130","author":"A Parizad","year":"2021","unstructured":"Parizad A, Hatziadoniu C (2021) Employing load and irradiance profiles for the allocation of PV arrays with inverter reactive power and battery storage in distribution networks\u2013a fast comprehensive QSTS technique. Int J Electr Power Energy Syst 130:106915","journal-title":"Int J Electr Power Energy Syst"},{"key":"16072_CR35","doi-asserted-by":"crossref","first-page":"889","DOI":"10.1109\/TII.2018.2837079","volume":"15","author":"A Parizad","year":"2018","unstructured":"Parizad A, Mohamadian S, Iranian ME, Guerrero JM (2018) Power system real-time emulation: a practical virtual instrumentation to complete electric power system modeling. IEEE Trans Ind Informatics 15:889\u2013900","journal-title":"IEEE Trans Ind Informatics"},{"key":"16072_CR36","doi-asserted-by":"crossref","first-page":"518","DOI":"10.1080\/15325008.2015.1112449","volume":"44","author":"J Polprasert","year":"2016","unstructured":"Polprasert J, Ongsakul W, Dieu VN (2016) Optimal reactive power dispatch using improved pseudo-gradient search particle swarm optimization. Electr Power Components Syst 44:518\u2013532","journal-title":"Electr Power Components Syst"},{"key":"16072_CR37","doi-asserted-by":"crossref","first-page":"99","DOI":"10.1049\/iet-cta.2012.0343","volume":"7","author":"R-E Precup","year":"2013","unstructured":"Precup R-E, David R-C, Petriu EM, Preitl S, R\u0103dac MB (2013) Fuzzy logic-based adaptive gravitational search algorithm for optimal tuning of fuzzy-controlled servo systems. IET Control Theory Appl 7:99\u2013107","journal-title":"IET Control Theory Appl"},{"key":"16072_CR38","doi-asserted-by":"crossref","first-page":"253","DOI":"10.1007\/s00202-016-0503-1","volume":"100","author":"J Radosavljevi\u0107","year":"2018","unstructured":"Radosavljevi\u0107 J, Jevti\u0107 M, Milovanovi\u0107 M (2018) A solution to the ORPD problem and critical analysis of the results. Electr Eng 100:253\u2013265","journal-title":"Electr Eng"},{"key":"16072_CR39","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1016\/j.ijepes.2014.10.041","volume":"66","author":"A Rajan","year":"2015","unstructured":"Rajan A, Malakar T (2015) Optimal reactive power dispatch using hybrid Nelder\u2013Mead simplex based firefly algorithm. Int J Electr Power Energy Syst 66:9\u201324","journal-title":"Int J Electr Power Energy Syst"},{"key":"16072_CR40","doi-asserted-by":"crossref","first-page":"320","DOI":"10.1016\/j.asoc.2016.02.041","volume":"43","author":"A Rajan","year":"2016","unstructured":"Rajan A, Malakar T (2016) Exchange market algorithm based optimum reactive power dispatch. Appl Soft Comput 43:320\u2013336","journal-title":"Appl Soft Comput"},{"key":"16072_CR41","doi-asserted-by":"crossref","first-page":"733","DOI":"10.1080\/15325008.2010.541410","volume":"39","author":"PK Roy","year":"2011","unstructured":"Roy PK, Ghoshal SP, Thakur SS (2011) Optimal reactive power dispatch considering flexible AC transmission system devices using biogeography-based optimization. Electr Power Components Syst 39:733\u2013750","journal-title":"Electr Power Components Syst"},{"key":"16072_CR42","doi-asserted-by":"crossref","first-page":"106031","DOI":"10.1016\/j.epsr.2019.106031","volume":"178","author":"MS Saddique","year":"2020","unstructured":"Saddique MS, Bhatti AR, Haroon SS, Sattar MK, Amin S, Sajjad IA, ul Haq SS, Awan AB, Rasheed N (2020) Solution to optimal reactive power dispatch in transmission system using meta-heuristic techniques\u2015status and technological review. Electr Power Syst Res 178:106031","journal-title":"Electr Power Syst Res"},{"key":"16072_CR43","doi-asserted-by":"crossref","first-page":"3844","DOI":"10.1049\/iet-gtd.2016.0362","volume":"10","author":"WS Sakr","year":"2016","unstructured":"Sakr WS, El-Sehiemy RA, Azmy AM (2016) Optimal allocation of TCSCs by adaptive DE algorithm. IET Gener Transm Distrib 10:3844\u20133854","journal-title":"IET Gener Transm Distrib"},{"key":"16072_CR44","doi-asserted-by":"crossref","first-page":"897","DOI":"10.1016\/j.ijepes.2015.12.004","volume":"78","author":"AM Shaheen","year":"2016","unstructured":"Shaheen AM, El-Sehiemy RA, Farrag SM (2016a) A novel adequate bi-level reactive power planning strategy. Int J Electr Power Energy Syst 78:897\u2013909","journal-title":"Int J Electr Power Energy Syst"},{"key":"16072_CR45","doi-asserted-by":"crossref","first-page":"424","DOI":"10.1109\/JSYST.2016.2573799","volume":"12","author":"AM Shaheen","year":"2016","unstructured":"Shaheen AM, El-Sehiemy RA, Farrag SM (2016b) Integrated strategies of backtracking search optimizer for solving reactive power dispatch problem. IEEE Syst J 12:424\u2013433","journal-title":"IEEE Syst J"},{"key":"16072_CR46","doi-asserted-by":"crossref","first-page":"998","DOI":"10.1049\/iet-ipr.2018.6150","volume":"13","author":"D Shao","year":"2019","unstructured":"Shao D, Xu C, Xiang Y, Gui P, Zhu X, Zhang C, Yu Z (2019) Ultrasound image segmentation with multilevel threshold based on differential search algorithm. IET Image Process 13:998\u20131005","journal-title":"IET Image Process"},{"key":"16072_CR47","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1016\/j.ijepes.2013.08.010","volume":"55","author":"B Shaw","year":"2014","unstructured":"Shaw B, Mukherjee V, Ghoshal SP (2014) Solution of reactive power dispatch of power systems by an opposition-based gravitational search algorithm. Int J Electr Power Energy Syst 55:29\u201340","journal-title":"Int J Electr Power Energy Syst"},{"key":"16072_CR48","doi-asserted-by":"crossref","first-page":"374","DOI":"10.1016\/j.epsr.2008.07.008","volume":"79","author":"P Subbaraj","year":"2009","unstructured":"Subbaraj P, Rajnarayanan PN (2009) Optimal reactive power dispatch using self-adaptive real coded genetic algorithm. Electr Power Syst Res 79:374\u2013381","journal-title":"Electr Power Syst Res"},{"key":"16072_CR49","doi-asserted-by":"crossref","first-page":"286","DOI":"10.1016\/j.asoc.2015.03.041","volume":"32","author":"MH Sulaiman","year":"2015","unstructured":"Sulaiman MH, Mustaffa Z, Mohamed MR, Aliman O (2015) Using the gray wolf optimizer for solving optimal reactive power dispatch problem. Appl Soft Comput 32:286\u2013292","journal-title":"Appl Soft Comput"},{"key":"16072_CR50","doi-asserted-by":"crossref","first-page":"609","DOI":"10.1002\/etep.1717","volume":"24","author":"X Tang","year":"2014","unstructured":"Tang X, Zhang H, Cui Y, Gu L, Deng YY (2014) A novel reactive power optimization solution using improved chaos PSO based on multi-agent architecture. Int Trans Electr Energy Syst 24:609\u2013622","journal-title":"Int Trans Electr Energy Syst"},{"key":"16072_CR51","doi-asserted-by":"crossref","first-page":"588","DOI":"10.1016\/j.ijepes.2014.05.078","volume":"63","author":"LS Titare","year":"2014","unstructured":"Titare LS, Singh P, Arya LD, Choube SC (2014) Optimal reactive power rescheduling based on EPSDE algorithm to enhance static voltage stability. Int J Electr Power Energy Syst 63:588\u2013599","journal-title":"Int J Electr Power Energy Syst"},{"key":"16072_CR52","doi-asserted-by":"crossref","first-page":"2548","DOI":"10.1049\/iet-gtd.2015.1555","volume":"10","author":"S Verma","year":"2016","unstructured":"Verma S, Mukherjee V (2016) Optimal real power rescheduling of generators for congestion management using a novel ant lion optimiser. IET Gener Transm Distrib 10:2548\u20132561","journal-title":"IET Gener Transm Distrib"},{"key":"16072_CR53","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1016\/j.engappai.2014.02.018","volume":"32","author":"C Wang","year":"2014","unstructured":"Wang C, Liu Y, Zhao Y, Chen Y (2014) A hybrid topology scale-free Gaussian-dynamic particle swarm optimization algorithm applied to real power loss minimization. Eng Appl Artif Intell 32:63\u201375","journal-title":"Eng Appl Artif Intell"},{"key":"16072_CR54","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1109\/4235.585893","volume":"1","author":"DH Wolpert","year":"1997","unstructured":"Wolpert DH, Macready WG (1997) No free lunch theorems for optimization. IEEE Trans Evol Comput 1:67\u201382","journal-title":"IEEE Trans Evol Comput"},{"key":"16072_CR55","doi-asserted-by":"crossref","first-page":"1742","DOI":"10.1109\/TSMCC.2012.2218596","volume":"42","author":"Y Xu","year":"2012","unstructured":"Xu Y, Zhang W, Liu W, Ferrese F (2012) Multiagent-based reinforcement learning for optimal reactive power dispatch. IEEE Trans Syst Man, Cybern Part C Applications Rev 42:1742\u20131751","journal-title":"IEEE Trans Syst Man, Cybern Part C Applications Rev"},{"key":"16072_CR56","doi-asserted-by":"crossref","unstructured":"Yapici H (2020) Solution of optimal reactive power dispatch problem using pathfinder algorithm. Eng Optim:1\u201318","DOI":"10.1080\/0305215X.2020.1839443"},{"key":"16072_CR57","doi-asserted-by":"crossref","first-page":"351","DOI":"10.1016\/j.ijepes.2009.11.009","volume":"32","author":"X Zhang","year":"2010","unstructured":"Zhang X, Chen W, Dai C, Cai W (2010) Dynamic multi-group self-adaptive differential evolution algorithm for reactive power optimization. Int J Electr Power Energy Syst 32:351\u2013357","journal-title":"Int J Electr Power Energy Syst"},{"key":"16072_CR58","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1016\/j.knosys.2016.10.024","volume":"116","author":"X Zhang","year":"2017","unstructured":"Zhang X, Yu T, Yang B, Cheng L (2017) Accelerating bio-inspired optimizer with transfer reinforcement learning for reactive power optimization. Knowledge-Based Syst 116:26\u201338","journal-title":"Knowledge-Based Syst"},{"key":"16072_CR59","doi-asserted-by":"crossref","first-page":"1070","DOI":"10.1109\/TPWRS.2005.846064","volume":"20","author":"B Zhao","year":"2005","unstructured":"Zhao B, Guo CX, Cao YJ (2005) A multiagent-based particle swarm optimization approach for optimal reactive power dispatch. IEEE Trans power Syst 20:1070\u20131078","journal-title":"IEEE Trans power Syst"}],"container-title":["Environmental Science and Pollution Research"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11356-021-16072-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11356-021-16072-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11356-021-16072-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,6,10]],"date-time":"2023-06-10T08:18:56Z","timestamp":1686385136000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11356-021-16072-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,9,1]]},"references-count":59,"journal-issue":{"issue":"28","published-online":{"date-parts":[[2023,6]]}},"alternative-id":["16072"],"URL":"https:\/\/doi.org\/10.1007\/s11356-021-16072-x","relation":{},"ISSN":["1614-7499"],"issn-type":[{"type":"electronic","value":"1614-7499"}],"subject":[],"published":{"date-parts":[[2021,9,1]]},"assertion":[{"value":"26 March 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"17 August 2021","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"1 September 2021","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Not applicable","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare that no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}]}}