A Multi-Objective Stochastic Optimization Approach for Planning a Multi-Energy Microgrid Considering Unscheduled Islanded Operation
Yan Cao, Yunfei Mu, Hongjie Jia, Xiaodan Yu, Kai Hou, Hui–Yuan Wang
Abstract
The multi-energy microgrid (MEMG) improves the energy supply economy through a multi-energy coupling operation. However, due to faults or maintenance, outages may occur in the main grid, forcing the MEMG switch to the islanded mode, which heavily impacts the energy supply reliability. To solve this problem, a multi-objective stochastic optimization approach for planning the MEMG considering unscheduled islanded operation is proposed in this paper. This method aims to optimize the planning decision, improve the operation economy in the grid-connected mode and enhance the energy supply reliability in the islanded mode. A planning-operation co-optimization model is established with two objective functions: the minimum total planning cost and the minimum expected economic loss caused by islanded operation. The model incorporates equipment capacity allocation constraints, operation constraints in two operation modes and load curtailment constraints in the islanded mode. In addition to considering the uncertainties of load and renewable energy, the model of the uncertain islanded mode is established using four correlated random variables, and the scenario tree is used for islanded scenario generation. The adaptive weighted sum (AWS) method is used to solve the multi-objective model and obtain an optimal and evenly distributed Pareto frontier. On this basis, the technique for order preference by similarity to an ideal solution (TOPSIS) is employed to determine the final planning scheme. Numerical results illustrate the effectiveness of the proposed method, which makes a trade-off between planning economy and energy supply reliability.