Bi-level optimal configuration of microgrid in data center considering load characteristics

The problem that the early capacity planning of microgrid in data center is unreasonable and cannot adapt to the operation characteristics of data center has not been solved. At the same time, in order to improve the power supply economy and renewable energy consumption capacity of the microgrid in data center, a bi-level optimal configuration model of the microgrid capacity in data center taking into account the load characteristics is proposed in this paper. Scenario reduction-based selection method is used to deal with the uncertainty of renewable energy and the computational complexity caused by a large number of scenarios. The corresponding load scheduling strategies are proposed according to the characteristics of different loads together with their flexibility. The problem of capacity planning for different microgrid resources, including energy storage system, photovoltaic and wind turbine, is solved by using non-dominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ) and Gurobi. Finally, the conpromise optimal soulation is obtained by the fuzzy multi-attribute decision-making approach. The simulation results show that the proposed approach can reduce the construction costs, operation costs and carbon emissions of data center microgrids. Besides, the satisfaction of data center operators is improved.