Optimal Scheduling of Cooling and Power Combined Supply System for Tropical Renewable Microgrids

Abstract

To satisfy the residential cooling demand in tropical large renewable microgrids (MGs), multiple ice-storage air conditionings (IACs) are usually used to supply cold energy. However, these IACs could not directly exchange the cold energy, which seriously limits the combined regulation effect. To address the problem, a novel cooling and power combined supply system (CPCSS) is proposed in this paper, where the trucks are used to distribute the ices among IACs. To evaluate the performance on the multi-time scales, a cooling and power combined supply model is established. On this basis, a two-stage (i.e., day-ahead and real-time stage) scheduling strategy is presented to minimize the MG operation cost. To speed up the solution, this scheduling model is first linearized as a classic mixed-integer second-order cone programming (MISCP) problem, and then is solved by Lagrange solution method. Simulation studies on an IEEE 14-node system indicates that compared with the existing MG operation cost, the annual operational cost of the based-two-truck CPCSS could be reduced by 9868800 yuan (12.6%), while the network loss could be decreased from 5.4 to 3.9 MWh. The results confirm the effectiveness of the proposed strategy.

Keywords

• Renewable microgrid
• ice-storage air conditioning
• multi-time scale
• cooling and power combined supply system
• Lagrange solution