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Determining the size of energy storage system to maximize the economic profit for photovoltaic and wind turbine generators in South Korea
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Publication Year
2019-12-01
Publisher
Elsevier Ltd
Citation
Renewable and Sustainable Energy Reviews, Vol.116
Keyword
Economic analysisEnergy storage system (ESS)ESS sizingEstimation modelPhotovoltaic (PV)Wind Turbine (WT)
Mesh Keyword
Economics analysisEnergy storage systemEnergy storage system sizingEstimation modelsPhotovoltaicPhotovoltaicsStorage systemsSystem sizingsWind turbine
All Science Classification Codes (ASJC)
Renewable Energy, Sustainability and the Environment
Abstract
This study identifies the optimal size of an Energy Storage System (ESS) for Photovoltaic (PV) and Wind Turbine (WT) generators under current Korean government policies. The government has pledged to promote the use of ESS with PV and WT generation to reduce the variability and uncertainty of renewable energy generation. The proposed algorithm determines the optimal ESS size required for PV and WT suppliers to maximize economic profit by using their historical generation profiles and compensation price. Net Present Value (NPV) is used as an economic parameter to determine the optimal size of ESS and consequently, the optimization indicates the maximization of NPV in this study. Furthermore, this paper proposes a methodology to estimate the size of ESS when there is insufficient information for future PV and WT suppliers. To verify the proposed algorithms, actual PV and WT generation profiles as well as the compensation price in South Korea are used. The simulation results indicate that the optimal capacity ratio between Renewable Energy Source (RES), ESS battery, and ESS PCS is determined as 1:3.3:0.7 and 1:3:1 for PV and WT respectively. Furthermore, the ESS size estimated by the proposed methodology shows a marginal difference from the optimal size, with an error of less than 3% for PV and 0% for WT.
Language
eng
URI
https://dspace.ajou.ac.kr/dev/handle/2018.oak/30948
DOI
https://doi.org/10.1016/j.rser.2019.109467
Fulltext

Type
Review
Funding
The optimal sizing or economic analysis introduced by the previous studies can be applicable to a different location. For this, however, these methodologies need to be updated by the new profit structure changed by local settlement/compensation rules and the modified operational scheme of ESS adapted by local supporting policies for the integration with RES. In addition, the previous studies require the complete information regarding the RES generation profile, the unit price of electricity in the market, and the supporting policy, such as the REC and FIT. Therefore, it is not able to estimate the size of the ESS if there is insufficient information. Thus, this paper presents a methodology to determine the optimal ESS size for PV and WT suppliers based on an economic analysis under the current government policies and compensation rules in South Korea. Net Present Value (NPV) is used as the factor to determine the optimal size of ESS based on economic analyses. In addition, this methodology is generalized to estimate the size of an ESS with the insufficient information, using the RES nameplate capacity and the Capacity Factor (CF) of the site. The insufficient information means a lack of sufficient historical production data of PV and WT, or these data cannot be generated by using the meteorological dataset. The introduced functions can provide an effective estimate of the ESS size for newly planned PV and WT farms in South Korea.This research was supported by the Ministry of Trade, Industry & Energy (MOTIE), Korea Institute for Advancement of Technology (KIAT) through the Encouragement Program for The Industries of Economic Cooperation Region (No. P0006091).This research was supported by the Ministry of Trade, Industry & Energy (MOTIE) , Korea Institute for Advancement of Technology (KIAT) through the Encouragement Program for The Industries of Economic Cooperation Region (No. P0006091 ).
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Jung, Jaesung  Image
Jung, Jaesung 정재성
Department of Electrical and Computer Engineering
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