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.
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Centralized renewable-storage systems Battery capacity of a centralized renewable energy system is optimized using the U-value method . Table 3 summarizes the capacity sizing on centralized electrical energy systems. Generally, capacity sizing approaches mainly include parametrical analysis, single-objective and multi-objective optimizations.
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.
Techno-economic and life cycle assessment on energy storage technologies is critical for capacity sizing. Multiple assessment criteria mainly include renewable penetration, battery capacity degradation and service life, levelized costs of electricity and heat, and so on.
Subsequently, based on the optimal strategy for joint operation, with the maximization of economic benefits for energy storage system as the objective, a capacity optimization model is established. The NSGA-II algorithm is employed to determine the optimal capacity of the BESS, thereby achieving revenue maximization.
Summary of optimization and assessment criteria of renewable-storage systems. Battery energy storage (BES) capacity degradation affects BES performance and microgrid total costs. Coordinated battery deployment can improve economic performances. High renewable penetration through the sized capacity. RES sizing is dependent on V2G operation.
The optimal configuration for power and maximum continuous energy storage duration is determined to be 30.99 MW and 4.52 h, respectively. At this configuration, the average daily return is 2.362 × 10 5 yuan and the initial investment cost is 1.45 × 10 9 yuan. Fig. 20. Optimal solution selected by TOPSIS. Table 4. Optimal solution data.
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