Multi-objective optimization of combined cooling, heating and power system considering the collaboration of thermal energy storage with load uncertainties

A thermoelectric coupling limitation imposes the combined cooling, heating, and power (CCHP) systems low performance under dynamic uncertainty. Energy storage is an effective way to address the problem. This paper integrates an energy storage device into the CCHP system to decouple the limitation and proposes a multiobjective optimization model considering load uncertainty for the optimal capacity of energy storage. The design space is a set of all feasible configuration schemes that meet the requirements of the system's confidence level. A chance-constrained method is employed to address the load uncertainty and transform the uncertain optimization into deterministic optimization. Load uncertainty is closely related to the given confidence level. Therefore, the indicator loss of load expectation is used to evaluate the reliability of the CCHP system. The economic and environmental performance of the CCHP system is assessed by using the annual total cost and carbon dioxide emission, respectively. A hotel example validates the feasibility of the proposed methodology. The results show that increasing the confidence level from 0.5 to 0.99 results in the capacity increase of the waste heat boiler from 326.8 kW to 408.2 kW in the heating mode. The increased change reduces the loss of load expectation by 108.4% and increases the annual operation cost by 110.14%.

Automated summary

This paper discusses the integration of an energy storage device into a CCHP system to address thermoelectric coupling limitations under dynamic uncertainty. It proposes a multiobjective optimization model for determining the optimal energy storage capacity and uses a probability-constrained method to handle load uncertainty. The economic and environmental performance of the CCHP system is evaluated through total annual cost and carbon dioxide emission assessment.