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Development of 24-hour optimal scheduling algorithm for energy storage system using load forecasting and renewable energy forecasting
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Publication Year
2018-01-29
Journal
IEEE Power and Energy Society General Meeting
Publisher
IEEE Computer Society
Citation
IEEE Power and Energy Society General Meeting, Vol.2018-January, pp.1-5
Keyword
Energy Storage System (ESS)ESS SchedulingKorea Electricity Tariff StructureLoad ForecastingRenewable Forecasting
Mesh Keyword
Charging/dischargingElectricity tariffEnergy storage systemsLoad forecastingMultivariate forecastingOptimal scheduling algorithmRenewable energiesShort-term forecasting
All Science Classification Codes (ASJC)
Energy Engineering and Power TechnologyNuclear Energy and EngineeringRenewable Energy, Sustainability and the EnvironmentElectrical and Electronic Engineering
Abstract
This paper presents the 24-hour optimal scheduling algorithm for Energy Storage System (ESS) using load forecasting and renewable energy forecasting in South Korea electricity tariff structure. For load forecasting and renewable energy forecasting, 24-hour multivariate forecasting model combining very-short-term and short-term forecasting models is developed. Then, load and renewable forecasts are input to the optimal ESS scheduling algorithm. The objective of this algorithm is to maximize the customer's profit by energy arbitrage, minimize the peak load to reduce the contract power, and minimize the charging/discharging cycles to lengthen the expected life of ESS. The effectiveness of this algorithm is validated in case study.
Language
eng
URI
https://aurora.ajou.ac.kr/handle/2018.oak/36308
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85046362832&origin=inward
DOI
https://doi.org/10.1109/pesgm.2017.8273907
Journal URL
http://ieeexplore.ieee.org/xpl/conferences.jsp
Type
Conference
Funding
This work was supported by the Korea Institute of Energy Technology Evaluation and Planning (KETEP) and the Ministry of Trade, Industry and Energy (MOTIE) of the Republic of Korea (No. 20162010103780).
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Jung, Jaesung  Image
Jung, Jaesung 정재성
Department of Electrical and Computer Engineering
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