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.
Highlights
The consumption of fuel fossils has considerably soared in the past few decades due to the industrialization and economic development worldwide, resulting in the issues of energy shortage and environmental pollution
With the aim to reduce the renewable energy curtailment, researchers pin their hopes on the energy storage unit (ESU), which can store the excessive renewable energy and discharge it when needed, cutting down the spillage
Dui X. et al proposes a two-stage method to determine the optimal capacity of battery energy storage to decrease wind power curtailment in grid-connected wind farms [6]; the first stage schedules the unit commitment of thermal generators and the wind farm output, and the second stage optimizes the operational strategies of battery energy storage while penalizing the curtailment in the objective function
Summary
The consumption of fuel fossils has considerably soared in the past few decades due to the industrialization and economic development worldwide, resulting in the issues of energy shortage and environmental pollution. In Reference [15], the stochastic capacity expansion planning of remote microgrids with wind farms and energy storage is explored; the scenarios are generated by Monte Carlo simulations Another method is robust optimization, which describes the uncertainty with an uncertainty set that encloses all the possible candidates of uncertain realizations [16]. Sci. 2021, 11, 1135 multi-parametric programming, which is a systematic theory and technique that subdivides the parameter set into characteristic regions where the optimal values are given as explicit functions of the parameters [27]; if we treat the power and energy capacities as parameters, such functions provide the decision-maker with insightful information about the impact of ESU on renewable energy curtailment.
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