Energy Storage for Renewable-Dominant Power Systems: Grid Flexibility, Long-Duration Storage, Safety, Degradation, and Circularity Pathways

Peter O Ohiero

Abstract


Renewable-dominant power systems require storage portfolios that deliver flexibility, adequacy, resilience, affordability, safety, and responsible resource use across timescales. This review synthesises electrical, mechanical, electrochemical, thermal, and chemical storage using a transparent evidence architecture comprising a 572-record citation reservoir, a 549-study bibliometric corpus, and 100 method-verified references for critical analysis. Technology suitability is shown to depend on response time, discharge duration, cycling duty, location, climate exposure, grid constraints, and revenue design; consequently, no universal option dominates. Batteries and power devices support rapid regulation and daily balancing, whereas pumped hydro, compressed-air, thermal, flow-battery, hydrogen, and hybrid systems address longer scarcity periods with distinct efficiency, siting, safety, and cost trade-offs. The synthesis treats degradation, operational safety, digital control, circularity, and bankability as coupled lifecycle considerations rather than isolated topics. It proposes a Storage-to-System Evidence Matrix linking duration, eligible services, risk, degradation, digital readiness, circularity, resilience, maturity, and finance. Priority actions include duration-aware valuation, representative demonstrations, harmonised safety standards, degradation-linked warranties, interoperable digital architectures, and closed-loop supply chains. Storage planning should therefore optimise service-matched portfolios against verified system needs and lifecycle constraints, strengthening reliable and equitable net-zero electricity transitions. 

Citation: Ohiero, P. (2026). Energy Storage for Renewable-Dominant Power Systems: Grid Flexibility, Long-Duration Storage, Safety, Degradation, and Circularity Pathways. Trends in Renewable Energy, 12(2), 288-335. doi:http://dx.doi.org/10.17737/tre.2026.12.2.00206

 

Keywords


Energy Storage; Renewable-Dominant Grids; Grid Flexibility; Long-Duration Energy Storage; Safety; Degradation

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References


Nwokolo, S. C., Eyime, E. E., Obiwulu, A. U., Meyer, E. L., Ahia, C. C., Ogbulezie, J. C., & Proutsos, N. (2024). A multi-model approach based on CARIMA-SARIMA-GPM for assessing the impacts of climate change on concentrated photovoltaic (CPV) potential. Physics and Chemistry of the Earth, 134, 103560. doi: 10.1016/j.pce.2024.103560.

Okonkwo, P. C., Nwokolo, S. C., Meyer, E. L., Ahia, C. C., & Mansir, I. B. (2025). Techno-economic optimization of renewable hydrogen infrastructure via AI-based dynamic pricing. Scientific Reports, 15 (1), 31529. doi: 10.1038/s41598-025-17506-z.

Hassan, M. A., Bailek, N., Bouchouicha, K., & Nwokolo, S. C. (2021). Ultra-short-term exogenous forecasting of photovoltaic power production using genetically optimized non-linear auto-regressive recurrent neural networks. Renewable Energy, 171, 191-209. doi: 10.1016/j.renene.2021.02.103.

Nwokolo, S. C., Ogbulezie, J. C., & Ushie, O. J. (2023). A multi-model ensemble-based CMIP6 assessment of future solar radiation and PV potential under various climate warming scenarios. Optik, 285, 170956. doi: 10.1016/j.ijleo.2023.170956.

Eyime, E. E., Nwokolo, S. C., Alhousni, F. K., Meyer, E. L., & Ahia, C. C. (2026). Machine learning from renewables to green hydrogen production optimization: A PM-CFL-OPT framework addressing uncertainty, safety constraints, and interpretability. Chemical Engineering Journal Advances, 27, 101292. doi: 10.1016/j.ceja.2026.101292.

Alhousni, F. K., Nwokolo, S. C., Meyer, E. L., Alsenani, T. R., Alhinai, H. A., Ahia, C. C., Okonkwo, P. C., & Ahmed, Y. E. (2025). Multi-scale computational fluid dynamics and machine learning integration for hydrodynamic optimization of floating photovoltaic systems. Energy Informatics, 8 (1), 103. doi: 10.1186/s42162-025-00567-9.

Yao, H., Wang, B., Xia, H., Yu, J., Yu, X., & Miao, Y. (2025). Power system operational reliability assessment considering battery energy storage system failures. Chongqing Daxue Xuebao/Journal of Chongqing University, 48 (11), 1-13. doi: 10.11835/j.issn.1000-582X.2024.225.

Beitelmal, W. H., Nwokolo, S. C., Meyer, E. L., & Ahia, C. C. (2024). Exploring Adaptation Strategies to Mitigate Climate Threats to Transportation Infrastructure in Nigeria: Lagos City, as a Case Study. Climate, 12 (8), 117. doi: 10.3390/cli12080117.

A'amar, K., Sajid, M. U., Bicer, Y., & Al-Ansari, T. (2025). Thermal assessment of pole-integrated LiFePO4energy storage system for arid and non-maintainable locations - A case study in Qatar. Journal of Power Sources, 660, 238444. doi: 10.1016/j.jpowsour.2025.238444.

Ji, W., Fu, Y., Zhang, H., & Zhou, C. (2025). Machine learning-enhanced multiscale modeling of high-rate sodium-ion batteries integrating electrochemical dynamics and thermal safety analysis. Journal of Energy Storage, 130, 117445. doi: 10.1016/j.est.2025.117445.

Emrani, A., & Berrada, A. (2023). Structural behavior and flow characteristics assessment of gravity energy storage system: Modeling and experimental validation. Journal of Energy Storage, 72, 108277. doi: 10.1016/j.est.2023.108277.

Nwokolo, S. C. (2025). Assessing the role of material substitution in cost reduction and demand mitigation for sustainable wind energy infrastructure. Cleaner Chemical Engineering, 11, 100203. doi: 10.1016/j.clce.2025.100203.

Eyime, E. E., Ojobe, O.-S. O., Nwokolo, S. C., Meyer, E. L., & Ahia, C. C. (2026). Degradation of components in lithium-ion batteries: from active-material failure pathways to degradation-aware diagnostics, regeneration, and circular management. Results in Chemistry, 29, 103670. doi: 10.1016/j.rechem.2026.103670.

Obiwulu, A. U., Erusiafe, N., Olopade, M. A., & Nwokolo, S. C. (2022). Modeling and estimation of the optimal tilt angle, maximum incident solar radiation, and global radiation index of the photovoltaic system. Heliyon, 8 (6), e09598. doi: 10.1016/j.heliyon.2022.e09598.

Obiwulu, A. U., Chendo, M. A. C., Erusiafe, N., & Nwokolo, S. C. (2020). Implicit meteorological parameter-based empirical models for estimating back temperature solar modules under varying tilt-angles in Lagos, Nigeria. Renewable Energy, 145, 442-457. doi: 10.1016/j.renene.2019.05.136.

Yin, W., Zhuang, K., Kong, P., Fan, P., Ye, J., Wu, Y., & Dou, X. (2025). Quantifying the energy imbalance in hydrogen energy storage-assisted power systems under heat waves. International Journal of Electrical Power and Energy Systems, 164, 110434. doi: 10.1016/j.ijepes.2024.110434.

Liu, L., Li, K., Liu, H., & Sun, Z. (2025). A DFT-based kinetic equation for Co3O4 decomposition reaction in high-temperature thermochemical energy storage. Applied Thermal Engineering, 260, 125064. doi: 10.1016/j.applthermaleng.2024.125064.

Ghilardi, A., Baccioli, A., Frate, G. F., & Ferrari, L. (2025). Investigation of the thermodynamic and economic feasibility of cold Pumped Thermal Energy Storage using Oceanic Temperature Difference. Energy, 338, 138810. doi: 10.1016/j.energy.2025.138810.

Guo, W., Li, X., Song, S., Xu, G., Lan, J., & Jia, Z. (2025). Novel multimodular power conditioning system for battery energy storage system. Journal of Energy Storage, 120, 116406. doi: 10.1016/j.est.2025.116406.

Migliari, L., Micheletto, D., & Cocco, D. (2025). Green hydrogen generation for mitigating the impact of curtailment in floating photovoltaic - pumped hydro energy storage (FPV-PHES) systems. Journal of Energy Storage, 132, 117997. doi: 10.1016/j.est.2025.117997.

Zhang, L., Wu, Z., Wang, Y., Zhang, C., Li, S., & Zhang, W. (2025). Two-tier anomaly detection for real-world data of energy storage battery pack with machine learning and sensitivity-aware feature analysis. Journal of Energy Storage, 139, 118905. doi: 10.1016/j.est.2025.118905.

McTigue, J., & Ma, Z. (2025). Analysis of pumped thermal energy storage using particle media integrated with concentrating solar power. Solar Energy, 292, 113436. doi: 10.1016/j.solener.2025.113436.

Shamsi, S. S. M., Barberis, S., Burlando, A., Maccarini, S., & Traverso, A. (2025). A Novel Thermally Integrated CO2-Carnot Battery (TI-PTES) Utilizing Cold Thermal Storage. Journal of Engineering for Gas Turbines and Power, 147 (2), 21017. doi: 10.1115/1.4066353.

Gifford, J., Wang, X., Ma, Z., & Braun, R. (2024). Modeling electrical particle thermal energy storage systems for long-duration, grid-electricity storage applications. Applied Energy, 371, 123521. doi: 10.1016/j.apenergy.2024.123521.

Shiraishi, K., Park, W. Y., & Kammen, D. M. (2024). The role of hydrogen as long-duration energy storage and as an international energy carrier for electricity sector decarbonization. Environmental Research Letters, 19 (8), 84011. doi: 10.1088/1748-9326/ad5856.

Le, T. S., Nguyen, T. N., Bui, D.-K., & Ngo, T. D. (2023). Optimal sizing of renewable energy storage: A techno-economic analysis of hydrogen, battery and hybrid systems considering degradation and seasonal storage. Applied Energy, 336, 120817. doi: 10.1016/j.apenergy.2023.120817.

Shayeghi, H., Davoudkhani, I. F., & Bizon, N. (2024). Robust self-adaptive fuzzy controller for load-frequency control of islanded airport microgrids considering electric aircraft energy storage and demand response. IET Renewable Power Generation, 18 (4), 616-653. doi: 10.1049/rpg2.12926.

Zhang, X., Liu, Y., Zeng, Y., Wu, G., & Liu, J. (2022). Prosumer-centric energy storage system and high voltage distribution network topology Co-optimisation for urban grid congestion management. IET Smart Grid, 5 (4), 297-307. doi: 10.1049/stg2.12061.

Li, Z., & Lu, Y.-C. (2022). Advanced aqueous redox flow batteries design: Ready for long-duration energy storage applications?. MRS Energy and Sustainability, 9 (2), 171-182. doi: 10.1557/s43581-022-00027-x.

Habibifar, R., Awad, A. S. A., & Azzouz, M. A. (2025). Planning energy hubs with hydrogen and battery storage for flexible ramping market participation. Journal of Energy Storage, 140, 119012. doi: 10.1016/j.est.2025.119012.

Klasing, F., Prenzel, M., & Bauer, T. (2025). Repurposing of supercritical coal plants into highly flexible grid storage with adapted 620 °C nitrate salt technology. Applied Energy, 377, 124524. doi: 10.1016/j.apenergy.2024.124524.

Liu, Q., Liu, H., Meng, K., Hai, R., Zhou, R., Wang, T., & Meng, X. (2025). Research on multi-time scale power decomposition and predictive control methods for hybrid flywheel energy storage systems. International Journal of Electrical Power and Energy Systems, 173, 111218. doi: 10.1016/j.ijepes.2025.111218.

Xia, S., Wang, Z., Wang, Y., Ban, M., Tian, Y., Terzić, J. S., & Lu, X. (2025). Collaborative Energy Schedule of Highway Cluster Microgrids Considering SPEV and Portable Battery Packs Operation Flexibility. IET Renewable Power Generation, 19 (1), e70080. doi: 10.1049/rpg2.70080.

Witharama, W. M. N., Bandara, K. M. D. P., Azeez, M. I., Logeeshan, V., & Wanigasekara, C. (2024). Advanced Genetic Algorithm for Optimal Microgrid Scheduling Considering Solar and Load Forecasting, Battery Degradation, and Demand Response Dynamics. IEEE Access, 12, 83269-83284. doi: 10.1109/ACCESS.2024.3412914.

Leippi, A., Fleschutz, M., Davis, K., Klingler, A.-L., & Murphy, M. D. (2024). Optimizing electric vehicle fleet integration in industrial demand response: Maximizing vehicle-to-grid benefits while compensating vehicle owners for battery degradation. Applied Energy, 374, 123995. doi: 10.1016/j.apenergy.2024.123995.

Liu, T., Li, J., Yang, Z., & Duan, Y. (2024). Evaluation of the short- and long-duration energy storage requirements in solar-wind hybrid systems. Energy Conversion and Management, 314, 118635. doi: 10.1016/j.enconman.2024.118635.

Zhang, K., Prakash, A., Paul, L., Blum, D., Alstone, P., Zoellick, J., Brown, R., & Pritoni, M. (2022). Model predictive control for demand flexibility: Real-world operation of a commercial building with photovoltaic and battery systems. Advances in Applied Energy, 7, 100099. doi: 10.1016/j.adapen.2022.100099.

Yin, W., Yang, Q., Kong, P., Yang, J., & Ye, J. (2025). Renewable target constrained co-expansion planning of wind power generation and long-duration energy storage considering wind draughts. Journal of Energy Storage, 125, 116713. doi: 10.1016/j.est.2025.116713.

Yu, T., Wei, S., Lu, T., Zhang, Z., & Sun, N. (2025). Distributed energy storage hierarchical partition dispatch control of virtual power plant based on SaDE-BBO algorithm. EAI Endorsed Transactions on Energy Web, 12, 1-11. doi: 10.4108/EW.9072.

Yu, Y., Zhong, M., He, L., Liu, Y., Xu, Z., & Li, Z. (2025). Data-driven optimization of flow field design for redox flow batteries: A statistical framework. Journal of Energy Storage, 138, 118714. doi: 10.1016/j.est.2025.118714.

Gifford, J., Davenport, P., Wang, X., & Ma, Z. (2024). Fabrication, Modeling, and Testing of a Prototype Thermal Energy Storage Containment. Journal of Solar Energy Engineering, 146 (5), 51009. doi: 10.1115/1.4065869.

Jokar, M. R., Shahmoradi, S., Mohammed, A. H., Foong, L. K., Le, B. N., & Pirouzi, S. (2023). Stationary and mobile storages-based renewable off-grid system planning considering storage degradation cost based on information-gap decision theory optimization. Journal of Energy Storage, 58, 106389. doi: 10.1016/j.est.2022.106389.

Yin, Y., Gao, Z., Huang, Y., & Liu, Q. (2025). PLT-GRU: physics-informed lightweight Transformer-GRU algorithm for few-shot battery state-of-health estimation. Measurement Science and Technology, 36 (9), 96216. doi: 10.1088/1361-6501/ae0495.

Ding, X., Mao, C., Guo, P., Xiong, J., Xu, Z., Sun, W., & Harrison, G. P. (2025). Dual-module coupled rolling optimization for hydro-wind-PV-battery complementary system: Considering battery capacity degradation. Journal of Energy Storage, 134, 118104. doi: 10.1016/j.est.2025.118104.

Wang, Z., Zhou, L., Xiong, L., Zhou, Q., Huang, W., Yang, H., Gao, F., & Chen, Y. (2025). Voltage-Source Control for Green-Hydrogen Hybrid Energy Storage System With Operational Constraints and Current Rate Limiter. IEEE Transactions on Smart Grid, 16 (4), 2871-2883. doi: 10.1109/TSG.2025.3556988.

Rezaei, M. A., Fathollahi, A., Akbari, E., Saki, M., Khorgami, E., Teimouri, A. R., Chronopoulos, A. T., & Mosavi, A. (2024). Reliability Calculation Improvement of Electrolytic Capacitor Banks Used in Energy Storage Applications Based on Internal Capacitor Faults and Degradation. IEEE Access, 12, 13146-13164. doi: 10.1109/ACCESS.2024.3351604.

Han, D., Kwon, S., Kim, J., Yoo, K., & Lee, S.-E. (2022). Integration of long-short term memory network and fuzzy logic for high-safety in a FR-ESS with degradation and failure. Sustainable Energy Technologies and Assessments, 49, 101790. doi: 10.1016/j.seta.2021.101790.

Barelli, L., Pelosi, D., Ciupageanu, D. A., Ottaviano, P. A., Longo, M., & Zaninelli, D. (2021). Hess in a wind turbine generator: Assessment of electric performances at point of common coupling with the grid. Journal of Marine Science and Engineering, 9 (12), 1413. doi: 10.3390/jmse9121413.

Haoxin, D., Qiyuan, D., Chaojie, L., Nian, L., Zhang, W., Hu, M., & Xu, C. (2025). A comprehensive review on renewable power-to-green hydrogen-to-power systems: Green hydrogen production, transportation, storage, re-electrification and safety. Applied Energy, 390, 125821. doi: 10.1016/j.apenergy.2025.125821.

Eyime,, Eyime Echeng, Nwokolo,, Samuel Chukwujindu, Alhousni,, Fadhil Khadoum, Meyer,, Edson L, & Ahia,, Chinedu Christian (2026). Hybrid AI Architectures for Solar–Wind–Battery Systems: Machine-Learning Control, Fuzzy Energy Management, Robust MPC, and Automated Source-Switching Hardware. Results in Engineering, 112150. doi: 10.1016/j.rineng.2026.112150.

Jain, V. K., & Arora, R. K. (2025). Fundamental of Battery Energy Storage Systems (BESS) & its Growth and Safety Regulations. Water and Energy International, 68r (8), 35-40.

Gao, Y., Zhang, Z., Meng, K., Liu, W., & Gao, R. (2025). Graph reinforcement learning for real-time dynamic reconfiguration and fault management in energy storage networks. Journal of Energy Storage, 125, 116833. doi: 10.1016/j.est.2025.116833.

Haghjoo-Haghighi, M., Gholami, M., Mahdavi, H., & Khodsuz, M. (2025). Operational Planning of Hydrogen Energy Storage Systems Using Risk-Averse Stochastic Programming. IET Renewable Power Generation, 19 (1), e70147. doi: 10.1049/rpg2.70147.

Yang, Y., Ma, M., Li, F., Zhao, W., Zhang, R., & Chen, Y. (2025). Comprehensive reliability evaluation and enhancement of distributed energy systems: Unlocking risk-resistant potential of building virtual thermal storage with uncertainty in renewable resources and equipment failures. Journal of Building Engineering, 106, 112568. doi: 10.1016/j.jobe.2025.112568.

Buscemi, G., Cuomo, F. P., Razzano, G., Cappiello, F. L., & Brandi, S. (2025). Deep reinforcement learning-based control of thermal energy storage for university classrooms: Co-Simulation with TRNSYS-Python and transfer learning across operational scenarios. Energy Reports, 14, 1349-1367. doi: 10.1016/j.egyr.2025.07.003.

Sage, M., Al, Handawi K., & Zhao, Y. F. (2025). Deep reinforcement learning for joint dispatch of battery storage and gas turbines in renewable-powered microgrids. Energy and AI, 22, 100653. doi: 10.1016/j.egyai.2025.100653.

Ma, Z., Wang, X., Davenport, P., Gifford, J., Cook, K., Martinek, J., Schirck, J., Morris, A., Lambert, M., & Zhang, R. (2022). System and component development for long-duration energy storage using particle thermal energy storage. Applied Thermal Engineering, 216, 119078. doi: 10.1016/j.applthermaleng.2022.119078.

Cheng, L., Wan, Y., Zhou, Y., & Gao, D. W. (2022). Operational Reliability Modeling and Assessment of Battery Energy Storage Based on Lithium-ion Battery Lifetime Degradation. Journal of Modern Power Systems and Clean Energy, 10 (6), 1738-1749. doi: 10.35833/MPCE.2021.000197.

Bellache, K., Camara, M. B., Dakyo, B., & Ramasamy, S. (2021). Aging characterization of lithium iron phosphate batteries considering temperature and direct current undulations as degrading factors. IEEE Transactions on Industrial Electronics, 68, 9696-9706. doi: 10.1109/TIE.2020.3020021.

Pelosi, D., Brunori, E., & Barelli, L. (2025). Assessment of additional aging on electric vehicles batteries in the framework of vehicle to building services. Journal of Energy Storage, 132, 117691. doi: 10.1016/j.est.2025.117691.

Zhen, M., Chen, Z., Lu, B., Chen, Z., & Pan, E. (2025). Net benefit-oriented condition-based maintenance for lithium-ion battery packs in SGLS systems: Combining degradation updating and decision-making. Computers and Industrial Engineering, 200, 110850. doi: 10.1016/j.cie.2024.110850.

Kulikovskaya, I. S., Karlina, Y. I., Gladkikh, V. A., & Kondratiev, V. V. (2025). Comprehensive Assessment of Energy Balance and Battery Degradation in Autonomous Power Systems with Renewable Sources. Tikrit Journal of Engineering Sciences, 32 (SP1), 2675. doi: 10.25130/tjes.sp1.2025.49.

Safavi, V., Vaniar, A. M., Bazmohammadi, N., Vasquez, J. C., Keysan, O., & Guerrero, J. M. (2025). A battery degradation-aware energy management system for agricultural microgrids. Journal of Energy Storage, 108, 115059. doi: 10.1016/j.est.2024.115059.

Superchi, F., Moustakis, A., Pechlivanoglou, G., & Bianchini, A. (2025). On the importance of degradation modeling for the robust design of hybrid energy systems including renewables and storage. Applied Energy, 377, 124645. doi: 10.1016/j.apenergy.2024.124645.

Grimaldi, A., Minuto, F. D., Perol, A., Casagrande, S., & Lanzini, A. (2025). Techno-economic optimization of utility-scale battery storage integration with a wind farm for wholesale energy arbitrage considering wind curtailment and battery degradation. Journal of Energy Storage, 112, 115500. doi: 10.1016/j.est.2025.115500.

Montalà, Palau M., Cheah, Mañé M., & Gomis-Bellmunt, O. (2025). Techno-economic optimization for BESS sizing and operation considering degradation and ramp rate limit requirement. Journal of Energy Storage, 105, 114631. doi: 10.1016/j.est.2024.114631.

Valedsaravi, S., Vegelin, R., & Olveira, A. (2025). Operational Framework for Large-Scale Power-to-X Plants Fed by Renewable Energies Incorporating BESS and Electrolyzer Degradation. IEEE Access, 13, 215994-216012. doi: 10.1109/ACCESS.2025.3645141.

Dias, de Lima T., Faria, P., & Vale, Z. (2025). Optimizing home energy management systems: A mixed integer linear programming model considering battery cycle degradation. Energy and Buildings, 329, 115251. doi: 10.1016/j.enbuild.2024.115251.

Beriwal, N., Vishnu, K., & Verma, A. (2025). Shunt current associated bipolar plate degradation in a multi-cell vanadium redox flow battery. Journal of Energy Storage, 131, 117607. doi: 10.1016/j.est.2025.117607.

Hassanin, K. M., Mansour, D.-E. A., Kato, T., & Megahed, T. F. (2025). A New IoT-based Adaptive Optimization for Multi-Objective Energy Management in Microgrids Considering Battery Degradation Cost and Emissions Minimization. Smart Grids and Sustainable Energy, 10 (3), 66. doi: 10.1007/s40866-025-00296-8.

Zhang, L., Yu, Y., Li, B., Qian, X., Zhang, S., Wang, X., Zhang, X., & Chen, M. (2022). Improved Cycle Aging Cost Model for Battery Energy Storage Systems Considering More Accurate Battery Life Degradation. IEEE Access, 10, 297-307. doi: 10.1109/ACCESS.2021.3139075.

Kostenko, G., & Zaporozhets, A. (2025). Trigger-Based PDCA Framework for Sustainable Grid Integration of Second-Life EV Batteries. World Electric Vehicle Journal, 16 (10), 584. doi: 10.3390/wevj16100584.

Terkes, M., Demirci, A., & Gokalp, E. (2023). An evaluation of optimal sized second-life electric vehicle batteries improving technical, economic, and environmental effects of hybrid power systems. Energy Conversion and Management, 291, 117272. doi: 10.1016/j.enconman.2023.117272.

Jurasz, J., Ceran, B., & Orłowska, A. (2020). Component degradation in small-scale off-grid PV-battery systems operation in terms of reliability, environmental impact and economic performance. Sustainable Energy Technologies and Assessments, 38, 100647. doi: 10.1016/j.seta.2020.100647.

Liang, Y., Zhou, M., Bai, X., Liu, H., Xu, M., & Wu, Z. (2025). Capacity Compensation Mechanism Design for Energy Storage Sharing in New Energy Base. IET Renewable Power Generation, 19 (1), e70059. doi: 10.1049/rpg2.70059.

Nordström, H., Söder, L., & Hesamzadeh, M. R. (2025). System cost-minimizing scheduling of battery energy storage systems providing energy and balancing services. Sustainable Energy, Grids and Networks, 43, 101820. doi: 10.1016/j.segan.2025.101820.

Chu, A. K., Baik, E., & Benson, S. M. (2025). Long-duration energy storage in transmission-constrained variable renewable energy systems. Cell Reports Sustainability, 2 (1), 100285. doi: 10.1016/j.crsus.2024.100285.

Gupta, D., Liu, S., Zhang, R., & Guo, Z. (2025). Future Long Cycling Life Cathodes for Aqueous Zinc-Ion Batteries in Grid-Scale Energy Storage. Advanced Energy Materials, 15 (18), 2500171. doi: 10.1002/aenm.202500171.

Shonnard, D. R., Zolghadr, A., & Kulas, D. G. (2025). Carbon Footprint and Energy Analysis of a Mixed Metal Oxide Thermochemical Energy Storage Technology. ACS Sustainable Chemistry and Engineering, 13 (16), 5864-5871. doi: 10.1021/acssuschemeng.4c09254.

Nirbheram, J. S., Mahesh, A., & Bhimaraju, A. (2024). Techno-economic optimization of standalone photovoltaic-wind turbine-battery energy storage system hybrid energy system considering the degradation of the components. Renewable Energy, 222, 119918. doi: 10.1016/j.renene.2023.119918.

Guinot, B., Champel, B., Montignac, F., Lemaire, E., Vannucci, D., Sailler, S., & Bultel, Y. (2015). Techno-economic study of a PV-hydrogen-battery hybrid system for off-grid power supply: Impact of performances' ageing on optimal system sizing and competitiveness. International Journal of Hydrogen Energy, 40 (1), 623-632. doi: 10.1016/j.ijhydene.2014.11.007.

Zhuang, W., Zhou, S., Gu, W., Ding, S., Lu, S., Zhang, T., Ding, Y., Chan, C. C., & Zhang, S. (2024). Optimal planning of electricity-gas coupled coordination hub considering large-scale energy storage. Energy Conversion and Management, 300, 117917. doi: 10.1016/j.enconman.2023.117917.

Kyrimlidou, P. T., Simoglou, C. K., & Biskas, P. N. (2024). Optimal sizing and long-term operation of a hybrid RES-BESS station in a competitive electricity market. Sustainable Energy, Grids and Networks, 39, 101450. doi: 10.1016/j.segan.2024.101450.

Poli, N., Bonaldo, C., Moretto, M., & Guarnieri, M. (2024). Techno-economic assessment of future vanadium flow batteries based on real device/market parameters. Applied Energy, 362, 122954. doi: 10.1016/j.apenergy.2024.122954.

Leon, J. P. M., Habbou, H., Friis-Møller, M., Gupta, M., Zhu, R., & Das, K. (2024). HyDesign: A tool for sizing optimization of grid-connected hybrid power plants including wind, solar photovoltaic, and lithium-ion batteries. Wind Energy Science, 9 (4), 759-776. doi: 10.5194/wes-9-759-2024.

Ba-Alawi, A. H., Nguyen, H.-T., Aamer, H., & Yoo, C. (2024). Techno-economic risk-constrained optimization for sustainable green hydrogen energy storage in solar/wind-powered reverse osmosis systems. Journal of Energy Storage, 90, 111849. doi: 10.1016/j.est.2024.111849.

Gbadegesin, A. O., Sun, Y., & Nwulu, N. I. (2023). Operational Optimisation of Grid-Connected Microgrids Incorporating Hybrid Energy Storage and Demand Response. Energy Exploration and Exploitation, 41 (6), 1869-1883. doi: 10.1177/01445987231174907.

Chen, S., Chen, L., Cui, S., Liu, H., Wei, W., & Mei, S. (2025). Electromechanical modeling of advanced adiabatic compressed air energy storage system compressed charging unit: Incorporating compressor dynamical performance under variable operating conditions. Applied Energy, 389, 125739. doi: 10.1016/j.apenergy.2025.125739.

Okonkwo, P. C., Nwokolo, S. C., Barhoumi, E. M., Mansir, I. B., Taura, U. H., Das, B. K., Radwan, A. B., Emori, W., Agyekum, E. B., & Kaaf, K. A. (2025). Technical and economic feasibility assessment for hybrid energy system electricity and hydrogen generation: A case study. Global Energy Interconnection, 8 (1), 62-81. doi: 10.1016/j.gloei.2025.01.001.

Gu, Z., Pan, G., Gu, W., Qiu, H., & Lu, S. (2024). Robust Optimization of Scale and Revenue for Integrated Power-to-Hydrogen Systems Within Energy, Ancillary Services, and Hydrogen Markets. IEEE Transactions on Power Systems, 39 (3), 5008-5023. doi: 10.1109/TPWRS.2023.3323660.

De, Carne G., Maroufi, S. M., Beiranvand, H., De, Angelis V., D'Arco, S., Gevorgian, V., Waczowicz, S., Mather, B., Liserre, M., & Hagenmeyer, V. (2024). The role of energy storage systems for a secure energy supply: A comprehensive review of system needs and technology solutions. Electric Power Systems Research, 236, 110963. doi: 10.1016/j.epsr.2024.110963.

Liu, H., Shuai, W., Yao, Z., Xuan, J., Ni, M., Xiao, G., & Xu, H. (2025). Optimization of solid oxide electrolysis cells using concentrated solar-thermal energy storage: A hybrid deep learning approach. Applied Energy, 377, 124610. doi: 10.1016/j.apenergy.2024.124610.

Sun, W., Liu, W., Zhang, J., & Tian, K. (2022). Bi-level Optimal Operation Model of Mobile Energy Storage System in Coupled Transportation-power Networks. Journal of Modern Power Systems and Clean Energy, 10 (6), 1725-1737. doi: 10.35833/MPCE.2020.000730.

Liu, X., Li, T., Yuan, Z., & Li, X. (2022). Low-cost all-iron flow battery with high performance towards long-duration energy storage. Journal of Energy Chemistry, 73, 445-451. doi: 10.1016/j.jechem.2022.06.041.

Saleem, M. I., Saha, S., Izhar, U., & Ang, L. (2024). Optimized energy management of a solar battery microgrid: An economic approach towards voltage stability. Journal of Energy Storage, 90, 111876. doi: 10.1016/j.est.2024.111876.

Shaikh, R. A., Vowles, D. J., Allison, A., & Abbott, D. (2023). Evaluation of Australia's Generation-Storage Requirements in a Fully Renewable Grid with Intermittent and Flexible Generation. IEEE Access, 11, 64201-64218. doi: 10.1109/ACCESS.2023.3286037.

Li, H., Sun, D., Li, B., Wang, X., Zhao, Y., Wei, M., & Dang, X. (2023). Collaborative optimization of VRB-PS hybrid energy storage system for large-scale wind power grid integration. Energy, 265, 126292. doi: 10.1016/j.energy.2022.126292.

Jain, T., & Verma, K. (2025). Reliability enhancement with coordinated operation of wind power and battery energy storage using machine learning based unit commitment decision. Journal of Energy Storage, 111, 115455. doi: 10.1016/j.est.2025.115455.

Eyime, E. E., Ojobe, O.-S. O., Nwokolo, S. C., Meyer, E. L., & Ahia, C. C. (2026). A hybrid CARIMA-SARIMA-Logistic model for Energy-CO2 transition in Africa: Evaluating five paths to Net-Zero by 2050 under scenario conditions. Energy Conversion and Management: X, 30, 101934. doi: 10.1016/j.ecmx.2026.101934.

Abdelghany, M. B., Al-Durra, A., Zeineldin, H., & Gao, F. (2023). Integrating scenario-based stochastic-model predictive control and load forecasting for energy management of grid-connected hybrid energy storage systems. International Journal of Hydrogen Energy, 48 (91), 35624-35638. doi: 10.1016/j.ijhydene.2023.05.249.

Sun, X., He, Y., Yang, J., Zhao, Z., Yang, Y., Li, M., Zhang, M., Chen, D., & Bai, Z. (2025). Optimization and comparative analysis of hydrogen energy storage and pumped hydro storage capacity configuration for enhancing power system flexibility in clean energy bases. Energy Conversion and Management, 342, 120144. doi: 10.1016/j.enconman.2025.120144.

Santosuosso, L., Camal, S., Liberati, F., Di, Giorgio A., Michiorri, A., & Kariniotakis, G. (2024). Stochastic economic model predictive control for renewable energy and ancillary services trading with storage. Sustainable Energy, Grids and Networks, 38, 101373. doi: 10.1016/j.segan.2024.101373.

Yang, Y., Wang, Y., Lu, Q., Ruan, G., Lin, Y., Wang, X., Xie, P., & Zhong, H. (2023). System value assessment method of energy storage system for multi-services of power system considering battery degradation. IET Energy Systems Integration, 5 (3), 355-364. doi: 10.1049/esi2.12109.

Okonkwo, P. C., Nwokolo, S. C., Udo, S. O., Obiwulu, A. U., Onnoghen, U. N., Alarifi, S. S., Eldosouky, A. M., Ekwok, S. E., Andráš, P., & Akpan, A. E. (2025). Solar PV systems under weather extremes: Case studies, classification, vulnerability assessment, and adaptation pathways. Energy Reports, 13, 929-959. doi: 10.1016/j.egyr.2024.12.067.

Nwokolo, S. C., Udo, S. O., Ebong, E. D., Orji, C., Meyer, E. L., & Ahia, C. C. (2026). Hydrogen storage materials and performance-conditioning technologies bridging gravimetric capacity, usable performance, and deployment readiness: A review. Results in Chemistry, 26, 103341. doi: 10.1016/j.rechem.2026.103341.

Hassan, M. A., Bailek, N., Bouchouicha, K., Ibrahim, A., Jamil, B., Kuriqi, A., Nwokolo, S. C., & El-Kenawy, E.-S. M. (2022). Evaluation of energy extraction of PV systems affected by environmental factors under real outdoor conditions. Theoretical and Applied Climatology, 150 (1-2), 715-729. doi: 10.1007/s00704-022-04166-6.

Agbor, M. E., Udo, S. O., Ewona, I. O., Nwokolo, S. C., Ogbulezie, J. C., & Amadi, S. O. (2023). Potential impacts of climate change on global solar radiation and PV output using the CMIP6 model in West Africa. Cleaner Engineering and Technology, 13, 100630. doi: 10.1016/j.clet.2023.100630.

Nwokolo, S. C., Alsenani, T. R., Okonkwo, P. C., Meyer, E. L., & Ahia, C. C. (2026). Hybridized forecasting and climate change impact analysis of six solar PV technologies under CMIP6-SSP scenarios. Energy Reports, 15, 108972. doi: 10.1016/j.egyr.2025.108972.

Nwokolo, S. C., Udo, S. O., Ebong, E. D., Meyer, E. L., & Ahia, C. C. (2025). Machine learning and analytical hybridization models for evaluating climate change impacts on solar agrivoltaic systems and photosynthetically active radiation in Nigeria. Energy Reports, 14, 4015-4055. doi: 10.1016/j.egyr.2025.11.026.

Obiwulu, A. U., Erusiafe, N., Olopade, M. A., & Nwokolo, S. C. (2020). Modeling and optimization of back temperature models of mono-crystalline silicon modules with special focus on the effect of meteorological and geographical parameters on PV performance. Renewable Energy, 154, 404-431. doi: 10.1016/j.renene.2020.02.103.

Nwokolo, S. C., Udo, S. O., Ebong, E. D., Okonkwo, P. C., Orji, R., Orji, C., Meyer, E. L., & Ahia, C. C. (2026). Hydrogen storage and enabling materials beyond capacity: Digital MRV, safety-by-design, climate resilience, and thermal management demand. Energy Conversion and Management: X, 31, 102039. doi: 10.1016/j.ecmx.2026.102039.

Okonkwo, P. C., Nwokolo, S. C., Alsenani, T. R., Meyer, E. L., & Ahia, C. C. (2026). A hybrid CARIMA-SARIMA-logistic model for multi-scenario hydrogen demand forecasting: Insights from global economies. Energy Reports, 15, 108982. doi: 10.1016/j.egyr.2025.108982.

Nwokolo, S. C., Obiwulu, A. U., & Ogbulezie, J. C. (2023). Machine learning and analytical model hybridization to assess the impact of climate change on solar PV energy production. Physics and Chemistry of the Earth, 130, 103389. doi: 10.1016/j.pce.2023.103389.

Nwokolo, S. C., Obiwulu, A. U., Okonkwo, P. C., Orji, R., Alsenani, T. R., Mansir, I. B., & Orji, C. (2025). Machine learning and physics-based model hybridization to assess the impact of climate change on single- and dual-axis tracking solar-concentrated photovoltaic systems. Physics and Chemistry of the Earth, 138, 103881. doi: 10.1016/j.pce.2025.103881.

Okonkwo, P. C., Nwokolo, S. C., Meyer, E. L., Ahia, C. C., & Mansir, I. B. (2026). Reinforcement learning-driven stochastic optimization and blockchain-enabled demand response to determine the techno-economic feasibility of hydrogen fueling stations in Australia. Energy Reports, 15, 108949. doi: 10.1016/j.egyr.2025.108949.

Nwokolo, S. C., Alsenani, T. R., Okonkwo, P. C., Meyer, E. L., & Ahia, C. C. (2026). Rare earth and non-rare earth critical minerals for the manufacturing of renewable energy technologies. Energy Reports, 16, 109423. doi: 10.1016/j.egyr.2026.109423.

Okonkwo, P. C., Nwokolo, S. C., Alarifi, S. S., Ekwok, S. E., Orji, R., Udo, S. O., Eldosouky, A. M., Barhoumi, E. M., Das, B. K., Gomez-Ortiz, D., Abdelrahman, K., & Akpan, A. E. (2025). Bio-inspired computational intelligence metaheuristic-based optimization and sensitivity analysis approach to determine techno-economic feasibility of hydrogen refueling stations for fuel cell vehicles. Scientific Reports, 15 (1), 12451. doi: 10.1038/s41598-025-97088-y.

Nwokolo, S. C., Meyer, E. L., & Ahia, C. C. (2023). Credible pathways to catching up with climate goals in Nigeria. Climate, 11 (9), 196. doi: 10.3390/cli11090196.

Mansir, I. B., Nwokolo, S. C., El-Hout, S. I., & Babiker, S. G. (2026). Techno-economic evaluation of a hybrid renewable energy system for a sustainable health clinic. Natural Resources Forum, 1-15. doi: 10.1111/1477-8947.70057.




DOI: http://dx.doi.org/10.17737/tre.2026.12.2.00206

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