Economic Value Assessment and Optimal Sizing of an Energy Storage System in a Grid-Connected Wind Farm

• Published in: Energies (Basel) Vol. 11; no. 3; p. 591
• Main Authors: Choi, Dong, Min, Daiki, Ryu, Jong-hyun
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.03.2018
• Subjects: dynamic programming; economic value assessment; Electricity; Electricity pricing; Energy management; Energy storage; energy storage system; Farm management; Markov chains; Markov decision process; optimal sizing; Optimization; Stochastic models; Stochasticity; Storage capacity; Variability; wind farm; Wind farms; Wind power
• ISSN: 1996-1073; 1996-1073
• DOI: 10.3390/en11030591

This study identifies the optimal management policy of a given energy storage system (ESS) installed in a grid-connected wind farm in terms of maximizing the monetary benefits and provides guidelines for defining the economic value of the ESS under optimal management policy and selecting the optimal size of the ESS based on economic value. Considering stochastic models for wind power and electricity price, we develop a finite-horizon periodic-review Markov decision process (MDP) model to seek the optimal management policy. We also use a simple optimization model to find the optimal storage capacity and charging/discharging capacity of the ESS. By applying our analytic approach to a real-world grid-connected wind farm located in South Korea, we verify the usefulness of this study. Our numerical study shows that the economic value of the ESS is highly dependent on management policy, wind electricity variability, and electricity price variability. Thus, the optimal size of ESS should be carefully determined based on the locational characteristics and management policy even with limited investments. Furthermore, this study provides a meaningful policy implication regarding how much of a subsidy the government should provide for installing ESS in a wind farm.