Characterizing and Visualizing the Impact of Energy Storage on Renewable Energy Curtailment in Bulk Power Systems

Abstract

The uncertain natures of renewable energy lead to its underutilization; energy storage unit (ESU) is expected to be one of the most promising solutions to this issue. This paper evaluates the impact of ESUs on renewable energy curtailment. For any fixed renewable power output, the evaluation model minimizes the total amount of curtailment and is formulated as a mixed integer linear program (MILP) with the complementarity constraints on the charging and discharging behaviors of ESUs; by treating the power and energy capacities of ESUs as parameters, the MILP is transformed into a multi-parametric MILP (mp-MILP), whose optimal value function (OVF) explicitly maps the parameters to the renewable energy curtailment. Further, given the inexactness of uncertainty’s probability distribution, a distributionally robust mp-MILP (DR-mp-MILP) is proposed that considers the worst distribution in a neighborhood of the empirical distribution built by the representative scenarios. The DR-mp-MILP has a max–min form and is reformed as a canonical mp-MILP by duality theory. The proposed method was validated on the modified IEEE nine-bus systems; the parameterized OVFs provide insightful suggestions on storage sizing.

Keywords

• renewable energy curtailment
• energy storage
• distributionally robust optimization
• multi-parametric programming
• optimal value function