{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,29]],"date-time":"2026-01-29T16:31:11Z","timestamp":1769704271828,"version":"3.49.0"},"reference-count":30,"publisher":"SAGE Publications","issue":"3","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IFS"],"published-print":{"date-parts":[[2023,3,9]]},"abstract":"<jats:p>The high power generation growth by photovoltaic systems needs to forecast the power generation profile during a day. It is also required to evolve the high-efficient and optimal on-grid\/off-grid photovoltaic power generation units. Furthermore, some advantages can be achieved by integrating photovoltaic systems with storage devices such as battery energy storage systems. Thus, optimizing the hybrid systems comprising photovoltaic and battery energy storage systems is needed to evaluate the best capacity. In the present work, a novel control and sizing scheme is proposed for the battery energy storage system in a photovoltaic power generation plant in one-hour ahead and one-day ahead during the dispatching phase. Then, the proposed prediction strategy is recommended for solar irradiation and power utilization. The control approach comprises a predictive control method concerning a Radial Basis Function network optimized by Levenberg-Marquardt back-propagation learning algorithm. Using the RBF network for simulation leads to a WAPE%\u00a0=1.68\u00a0%.<\/jats:p>","DOI":"10.3233\/jifs-221123","type":"journal-article","created":{"date-parts":[[2022,9,6]],"date-time":"2022-09-06T11:50:08Z","timestamp":1662465008000},"page":"3667-3680","source":"Crossref","is-referenced-by-count":0,"title":["A novel prediction and control method for solar energy dispatch based on the battery energy storage system using an experimental dataset"],"prefix":"10.1177","volume":"44","author":[{"given":"Yongguo","family":"Wang","sequence":"first","affiliation":[{"name":"Department of Control Engineering, Jilin Institute of Chemical Technology, Jilin, China"}]},{"given":"Xuewen","family":"Bi","sequence":"additional","affiliation":[{"name":"Calcium Carbide Factory of Jilin Petrochemical Company, Jilin, China"}]},{"given":"Xinxin","family":"Zhang","sequence":"additional","affiliation":[{"name":"Acrylonitrile Plant, Jilin Petrochemical Company, Jilin, China"}]}],"member":"179","reference":[{"key":"10.3233\/JIFS-221123_ref1","unstructured":"Sobhani B. and Afzal S. , Combinatorial price offer for a wind turbine with flexible load considering the uncertainty to increase the benefit of wind turbine, Adv Eng Intell Syst 1(01) (2022)."},{"issue":"2","key":"10.3233\/JIFS-221123_ref2","doi-asserted-by":"crossref","first-page":"84","DOI":"10.1109\/MPE.2014.2321704","article-title":"Integrated solutions for photovoltaic grid connection: Increasing the reliability of solar power","volume":"12","author":"Yan","year":"2014","journal-title":"IEEE Power Energy Mag"},{"key":"10.3233\/JIFS-221123_ref4","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1016\/j.renene.2013.05.011","article-title":"Solar radiation forecast based on fuzzy logic and neural networks","volume":"60","author":"Chen","year":"2013","journal-title":"Renew Energy"},{"issue":"3","key":"10.3233\/JIFS-221123_ref5","doi-asserted-by":"crossref","first-page":"117","DOI":"10.1109\/TSTE.2010.2061880","article-title":"Rule-based control of battery energy storage for dispatching intermittent renewable sources","volume":"1","author":"Teleke","year":"2010","journal-title":"IEEE Trans Sustain Energy"},{"key":"10.3233\/JIFS-221123_ref7","unstructured":"Hammad Saeed M. , Iqbal S. and Kalwar B.A. , Electricity market management through optimum installation of distributed generation sources and optimum placement based on LMP and ISC, Adv Eng Intell Syst 1(01) (2022)."},{"issue":"4","key":"10.3233\/JIFS-221123_ref9","doi-asserted-by":"crossref","first-page":"3","DOI":"10.17775\/CSEEJPES.2015.00042","article-title":"Aggregator service for PV and battery energy storage systems of residential building","volume":"1","author":"Li","year":"2015","journal-title":"CSEE J Power Energy Syst"},{"key":"10.3233\/JIFS-221123_ref12","doi-asserted-by":"crossref","first-page":"627","DOI":"10.1016\/j.apenergy.2019.01.102","article-title":", Smart energy management algorithm for load smoothing and peak shaving based on load forecasting of an island\u2019s power system","volume":"238","author":"Chapaloglou","year":"2019","journal-title":"Appl Energy"},{"key":"10.3233\/JIFS-221123_ref13","doi-asserted-by":"crossref","first-page":"3001","DOI":"10.1051\/e3sconf\/201911303001","article-title":", Advanced energy management system based on PV and load forecasting for load smoothing and optimized peak shaving of islanded power systems, in","volume":"113","author":"Iliadis","year":"2019","journal-title":"E3S Web of Conferences"},{"key":"10.3233\/JIFS-221123_ref18","doi-asserted-by":"crossref","first-page":"324","DOI":"10.1016\/j.apenergy.2015.01.004","article-title":"Operational optimization and demand response of hybrid renewable energy systems","volume":"143","author":"Wang","year":"2015","journal-title":"Appl Energy"},{"issue":"4","key":"10.3233\/JIFS-221123_ref19","doi-asserted-by":"crossref","first-page":"1426","DOI":"10.1109\/TSTE.2013.2294194","article-title":"Testing of a predictive control strategy for balancing renewable sources in a microgrid","volume":"5","author":"Marinelli","year":"2014","journal-title":"IEEE Trans Sustain Energy"},{"issue":"1","key":"10.3233\/JIFS-221123_ref20","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1145\/3508467.3508477","article-title":"Automated generation of models for demand side flexibility using machine learning: an overview","volume":"1","author":"F\u00f6rderer","year":"2021","journal-title":"ACM SIGENERGY Energy Informatics Rev"},{"key":"10.3233\/JIFS-221123_ref21","doi-asserted-by":"crossref","first-page":"103","DOI":"10.1016\/j.apenergy.2014.03.045","article-title":"Improving photovoltaics grid integration through short time forecasting and self-consumption","volume":"125","author":"Masa-Bote","year":"2014","journal-title":"Appl Energy"},{"key":"10.3233\/JIFS-221123_ref22","doi-asserted-by":"crossref","first-page":"230","DOI":"10.1016\/j.renene.2012.12.036","article-title":"Energy dispatch schedule optimization and cost benefit analysis for grid-connected, photovoltaic-battery storage systems","volume":"55","author":"Nottrott","year":"2013","journal-title":"Renew Energy"},{"issue":"4","key":"10.3233\/JIFS-221123_ref23","doi-asserted-by":"crossref","first-page":"1914","DOI":"10.1109\/TSG.2015.2392081","article-title":"Distributed and decentralized control of residential energy systems incorporating battery storage","volume":"6","author":"Worthmann","year":"2015","journal-title":"IEEE Trans Smart Grid"},{"key":"10.3233\/JIFS-221123_ref24","doi-asserted-by":"crossref","first-page":"123","DOI":"10.1016\/j.renene.2014.09.008","article-title":"An optimization-based approach to scheduling residential battery storage with solar PV: Assessing customer benefit","volume":"75","author":"Ratnam","year":"2015","journal-title":"Renew Energy"},{"issue":"1","key":"10.3233\/JIFS-221123_ref25","doi-asserted-by":"crossref","first-page":"68","DOI":"10.1109\/TSTE.2012.2199339","article-title":"Storage size determination for grid-connected photovoltaic systems","volume":"4","author":"Ru","year":"2012","journal-title":"IEEE Trans Sustain Energy"},{"issue":"39","key":"10.3233\/JIFS-221123_ref26","doi-asserted-by":"crossref","first-page":"13820","DOI":"10.1016\/j.ijhydene.2015.04.013","article-title":"Study of hybrid photovoltaic\/fuel cell system for stand-alone applications","volume":"40","author":"Bensmail","year":"2015","journal-title":"Int J Hydrogen Energy"},{"key":"10.3233\/JIFS-221123_ref27","doi-asserted-by":"crossref","first-page":"743","DOI":"10.1016\/j.energy.2018.04.073","article-title":"Salah, D. Rekioua and M.F. Mimouni, Sizing methodology for hybrid photovoltaic\/wind\/hydrogen\/battery integrated to energy management strategy for pumping system","volume":"153","author":"Khiareddine","year":"2018","journal-title":"Energy"},{"issue":"45","key":"10.3233\/JIFS-221123_ref29","doi-asserted-by":"crossref","first-page":"20914","DOI":"10.1016\/j.ijhydene.2016.06.243","article-title":"Overview of energy storage in renewable energy systems","volume":"41","author":"Amrouche","year":"2016","journal-title":"Int J Hydrogen Energy"},{"key":"10.3233\/JIFS-221123_ref31","first-page":"239","article-title":"Decentralized energy equalizer for a balancing aggregation of production and consumption of energy in scalable units, in","volume":"1","author":"Henneboehle","year":"2013","journal-title":"2013 IEEE 7th International Conference on Intelligent Data Acquisition and Advanced Computing Systems (IDAACS)"},{"key":"10.3233\/JIFS-221123_ref37","unstructured":"Kleissl J. , Solar energy forecasting and resource assessment, Academic Press, 2013."},{"key":"10.3233\/JIFS-221123_ref39","first-page":"1","article-title":"Brabandere, Photovoltaic and solar forecasting: state of the art","volume":"14","author":"Pelland","year":"2013","journal-title":"IEA PVPS Task"},{"issue":"4","key":"10.3233\/JIFS-221123_ref41","doi-asserted-by":"crossref","first-page":"1234","DOI":"10.1109\/TSTE.2014.2341954","article-title":"Urban scale photovoltaic charging stations for electric vehicles","volume":"5","author":"Brenna","year":"2014","journal-title":"IEEE Trans Sustain Energy"},{"issue":"7\u20139","key":"10.3233\/JIFS-221123_ref42","doi-asserted-by":"crossref","first-page":"1388","DOI":"10.1016\/j.neucom.2007.06.004","article-title":"Time series prediction using evolving radial basis function networks with new encoding scheme","volume":"71","author":"Du","year":"2008","journal-title":"Neurocomputing"},{"issue":"2","key":"10.3233\/JIFS-221123_ref43","doi-asserted-by":"crossref","first-page":"174","DOI":"10.1109\/78.978374","article-title":"A tutorial on particle filters for online nonlinear\/non-Gaussian Bayesian tracking","volume":"50","author":"Arulampalam","year":"2002","journal-title":"IEEE Trans signal Process"},{"key":"10.3233\/JIFS-221123_ref44","unstructured":"Nurlan Z. , A novel hybrid radial basis function method for predicting the fresh and hardened properties of self-compacting concrete, Adv Eng Intell Syst 1(01) (2022)."},{"issue":"3","key":"10.3233\/JIFS-221123_ref45","doi-asserted-by":"crossref","first-page":"853","DOI":"10.1109\/TPWRS.2008.922249","article-title":"RBF neural network and ANFIS-based short-term load forecasting approach in real-time price environment","volume":"23","author":"Yun","year":"2008","journal-title":"IEEE Trans Power Syst"},{"issue":"2","key":"10.3233\/JIFS-221123_ref46","doi-asserted-by":"crossref","first-page":"1138","DOI":"10.3390\/en8021138","article-title":"A physical hybrid artificial neural network for short term forecasting of PV plant power output","volume":"8","author":"Dolara","year":"2015","journal-title":"Energies"},{"key":"10.3233\/JIFS-221123_ref47","doi-asserted-by":"crossref","unstructured":"Barcellona S. , Brenna M. , Foiadelli F. , Longo M. and Piegari L. , Analysis of ageing effect on Li-polymer batteries, Sci World J 2015 (2015).","DOI":"10.1155\/2015\/979321"},{"key":"10.3233\/JIFS-221123_ref49","doi-asserted-by":"crossref","first-page":"322","DOI":"10.1109\/PCC.2002.998568","article-title":"Study on maximum power point tracking of wind turbine generator using a flywheel, in","volume":"1","author":"Koyanagi","year":"2002","journal-title":"Proceedings of the Power Conversion Conference-Osaka 2002 (Cat. No. 02TH8579)"}],"container-title":["Journal of Intelligent &amp; Fuzzy Systems"],"original-title":[],"link":[{"URL":"https:\/\/content.iospress.com\/download?id=10.3233\/JIFS-221123","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,29]],"date-time":"2026-01-29T06:48:06Z","timestamp":1769669286000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/full\/10.3233\/JIFS-221123"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,3,9]]},"references-count":30,"journal-issue":{"issue":"3"},"URL":"https:\/\/doi.org\/10.3233\/jifs-221123","relation":{},"ISSN":["1064-1246","1875-8967"],"issn-type":[{"value":"1064-1246","type":"print"},{"value":"1875-8967","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,3,9]]}}}