Integrated Systems with Data Centers Based on Chance Constrained Goal Programming

Data centers (DCs) are energy consumers with high electricity demand. Due to their Spatio-Temporal demand response (DR) capabilities, DCs are crucial DR participants. This paper presents a scheduling model for wind power integrated systems with DCs. To maximize the total social welfare, it is considered that the reserve capacity can be flexibly adjusted based on its reference value. Accordingly, a coordinated optimization model based on the chance-constrained goal programming (CCGP) is proposed. To overcome the solving difficulty of the probabilistic chance constraints, a conversion method is adopted in this paper to convert the probabilistic constraints into deterministic forms. Finally, the proposed model is verified on an IEEE 30-bus power system with wind farms. Simulation results prove that DCs' participation in DR has a positive effect on reducing wind power curtailment and increasing social welfare.