摘要

The inherent characteristics of renewable energy, such as highly random fluctuation and anti-peak, are essential issues that impede optimal design of a combined cooling, heating and power (CCHP) system. This study presents a novel hybrid CCHP system integrated with compressed air energy storage (CAES). The operation mode of the new system is enriched by the trigeneration characteristic of CAES when compared with a traditional CCHP system. Additionally, an integrated design method based on a tri-level collaborative optimization strategy is proposed for the new scheme. An active storing strategy is introduced to maximize the utility of the superiority of CAES for peak sheaving and efficiency increase. Thus, a novel algorithm based on a hybrid algorithm of Non-Dominated Sorting Genetic Algorithm-II and Multi-Objective Particle Swarm Optimization is employed to solve the multi-objective optimization model with the aim of minimizing the total cost and emissions. A case study shows the effectiveness of the above methods. The implementation of the study fundamentally improves the overall energy utilization degree and the ability for renewable consumption to thereby provide a guiding principle for CCHP system design.

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