Preprint Article Version 1 This version is not peer-reviewed

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

Version 1 : Received: 19 January 2018 / Approved: 22 January 2018 / Online: 22 January 2018 (04:33:23 CET)

A peer-reviewed article of this Preprint also exists.

Choi, D.G.; Min, D.; Ryu, J.-H. Economic Value Assessment and Optimal Sizing of an Energy Storage System in a Grid-Connected Wind Farm. Energies 2018, 11, 591. Choi, D.G.; Min, D.; Ryu, J.-H. Economic Value Assessment and Optimal Sizing of an Energy Storage System in a Grid-Connected Wind Farm. Energies 2018, 11, 591.

Journal reference: Energies 2018, 11, 591
DOI: 10.3390/en11030591

Abstract

This study identifies the optimal management policy of a given energy storage system (ESS) installed in a grid-connected wind farm for maximizing the monetary benefits and provides guidelines for defining the economic value of the ESS under the optimal management policy and selecting the optimal size of the ESS based on the 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 the management policy, wind electricity variability, and the 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 on how much a subsidy the government should provide for installing ESS in a wind farm.

Subject Areas

wind farm; energy storage system; economic value assessment; optimal sizing; dynamic programming; Markov decision process

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