Lifecycle Optimization of Grid-connected Photovoltaic Energy Storage Systems

Lifecycle Optimization of Grid-connected Photovoltaic Energy Storage Systems | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Lifecycle Optimization of Grid-connected Photovoltaic Energy Storage Systems Raphael Ibukun Areola, Abayomi A. Adebiyi, Dwayne Jensen Reddy This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8694962/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 13 You are reading this latest preprint version Abstract The increasing penetration of photovoltaic (PV) generation and battery energy storage systems (ESS) in grid-connected applications has intensified the need for design and operational strategies that simultaneously address technical performance, economic viability, and long-term system sustainability. Conventional multi-objective optimization frameworks for PV–ESS systems typically neglect component degradation or treat it as an exogenous post-processing factor, leading to solutions that are suboptimal over the system lifetime. This paper embeds physics-informed battery aging and grid constraints inside the NSGA-II optimization loop to co-optimize Net Present Cost (NPC), reliability (Energy Not Supplied and Loss of Power Supply Probability), curtailment, and battery State-of-Health. Across three regions (Nigeria, South Africa, India), the lifecycle-aware design reduces NPC by 12–15% and slows degradation by 38–41%, extending replacement intervals to 10–12 years while maintaining grid-code compliance. The framework integrates realistic battery aging models, energy balance constraints, and grid interaction limits, ensuring physical feasibility and long-term performance consistency. Validation across Nigeria, South Africa, and India under different climatic and tariff conditions demonstrates that integrating degradation awareness fundamentally alters optimal sizing and dispatch decisions, yielding solutions with improved lifecycle reliability and reduced total cost of ownership compared to conventional approaches. The results confirm that lifecycle-aware optimization is essential for the sustainable deployment of grid-connected PV–ESS systems and provide practical findings for system planners, utilities, and policymakers seeking to improve long-term grid resilience. Lifecycle-aware optimization photovoltaic systems battery energy storage multi-objective optimization grid-connected PV systems NSGA-II Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 10 Mar, 2026 Reviews received at journal 10 Mar, 2026 Reviews received at journal 08 Mar, 2026 Reviews received at journal 06 Mar, 2026 Reviews received at journal 26 Feb, 2026 Reviewers agreed at journal 23 Feb, 2026 Reviewers agreed at journal 20 Feb, 2026 Reviewers agreed at journal 19 Feb, 2026 Reviewers agreed at journal 17 Feb, 2026 Reviewers invited by journal 17 Feb, 2026 Editor assigned by journal 11 Feb, 2026 Submission checks completed at journal 08 Feb, 2026 First submitted to journal 08 Feb, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8694962","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":593009151,"identity":"7aa75ce7-1bfc-401b-9621-4e7baad419a1","order_by":0,"name":"Raphael Ibukun Areola","email":"","orcid":"","institution":"Durban University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Raphael","middleName":"Ibukun","lastName":"Areola","suffix":""},{"id":593009155,"identity":"710125aa-7236-4f22-9e97-18387e96ce8a","order_by":1,"name":"Abayomi A. 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Conventional multi-objective optimization frameworks for PV\u0026ndash;ESS systems typically neglect component degradation or treat it as an exogenous post-processing factor, leading to solutions that are suboptimal over the system lifetime.\u003c/p\u003e \u003cp\u003eThis paper embeds physics-informed battery aging and grid constraints inside the NSGA-II optimization loop to co-optimize Net Present Cost (NPC), reliability (Energy Not Supplied and Loss of Power Supply Probability), curtailment, and battery State-of-Health. Across three regions (Nigeria, South Africa, India), the lifecycle-aware design reduces NPC by 12\u0026ndash;15% and slows degradation by 38\u0026ndash;41%, extending replacement intervals to 10\u0026ndash;12 years while maintaining grid-code compliance. The framework integrates realistic battery aging models, energy balance constraints, and grid interaction limits, ensuring physical feasibility and long-term performance consistency.\u003c/p\u003e \u003cp\u003eValidation across Nigeria, South Africa, and India under different climatic and tariff conditions demonstrates that integrating degradation awareness fundamentally alters optimal sizing and dispatch decisions, yielding solutions with improved lifecycle reliability and reduced total cost of ownership compared to conventional approaches. 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