Renewable-storage sizing approaches for centralized and distributed renewable energy-A state-of-the-art review

Low-carbon and sustainability transitions necessitate the intermediate bridge of battery for interconnections between renewables and demands. However, the empirical battery sizing approaches for both centralized and distributed energy systems lead to performance overestimation or underestimation, together with material and resource wastes. This study focuses on renewable-storage sizing approaches for centralized and distributed renewable energy systems to avoid battery capacity oversizing or under-sizing and resource waste. Renewable-storage sizing plays significant and dominant roles in techno-economic-environmental performances in long-term sustainability. Energy storages for both centralized and distributed energy systems are comprehensively reviewed, including both thermal and electrical energy systems. Roles of centralized and distributed energy systems are characterized in low-carbon transitions. In terms of renewable-storage sizing approaches, both centralized and distributed renewable-storage systems are characterized by 'U-value' approach and 'M-value' approach, respectively. Lastly, AI-assisted energy storage approach is also prospected with big data training surrogate model and sizing optimization. Research results indicate that distributed energy systems are more flexible in power sharing, transmission and distribution, together with fast load response, recovery and high energy resilience when suffering from natural disasters. Battery outpower stabilization and dynamic energy matching are principles for both centralized and distributed renewable-storage system designs. AI-assisted energy storage sizing approaches mainly include surrogate model development, performance prediction, and optimization. Research results can provide frontier guidelines on renewable-storage sizing approaches for both centralized and distributed energy systems, so as to promote the low-carbon and sustainability transitions.