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

Junyu Liang,Xingyu Yuan,Min Dong,Yinghao Dai,Jialu Geng,Hongzhi Liu,Zhao Luo,Jiaquan Yang

doi:10.1109/access.2021.3071121

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.

Highlights

Energy crisis and environmental awareness stimulate the large-scale renewable energy connected to grid [1], [2]
Research shows that multi-energy systems could mitigate the bad impact of the renewable generation while developing complementary advantage [5]
It is of great practical significance to study the optimal scheduling of the integrated heat, cooling and power system

Summary

INTRODUCTION

Energy crisis and environmental awareness stimulate the large-scale renewable energy connected to grid [1], [2]. To ensure the cooling and power combined supply performance, a two-stage (i.e., day-ahead stage and real-time stage) MG scheduling strategy is formulated On this basis, linear techniques are first used to convert this MG scheduling model into a classic mixed-integer second-order cone programming problem (MISCP), followed by Lagrange solution method. 2) A novel cooling and power combined supply model on multi-time scales is established On this basis, a two-stage scheduling strategy is designed to carry out consumption shifting and power smoothing simultaneously. CPCSS MODEL ON THE COOLING SIDE Multiple IACs with trucks are combined to satisfy the cooling demands They are operated with the time-space network constraints and time-energy limits. TWO-STAGE SCHEDULING STRATEGY To ensure the cooling and power combined supply performance on multi-time scales, a two-stage scheduling strategy is proposed, where the day-ahead stage optimizes ice transportation routes, and the real-time stage determines the optimal unit operation power

DAY-AHEAD SCHEDULING STAGE

SOLUTION ALGORITHM

LAGRANGE SOLUTION STAGE

RESULTS AND DISCUSSION

CONCLUSION