Energy Trading System in Microgrids With Future Forecasting and Forecasting Errors

In this paper, we propose a periodic energy trading system model in microgrids with future forecasting and forecasting errors. In the proposed model, retailers in a microgrid can purchase (sell) energy periodically from (to) other retailers in the same microgrid. In this regard, our proposed model u...

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Main Authors: Gyohun Jeong, Sangdon Park, Joohyung Lee, Ganguk Hwang
Format: Article
Language:English
Published: IEEE 2018-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/8424153/
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spelling doaj-298a632a00e64093aef7bd829ede722e2021-03-29T20:51:39ZengIEEEIEEE Access2169-35362018-01-016440944410610.1109/ACCESS.2018.28619938424153Energy Trading System in Microgrids With Future Forecasting and Forecasting ErrorsGyohun Jeong0Sangdon Park1https://orcid.org/0000-0001-5392-749XJoohyung Lee2https://orcid.org/0000-0003-1102-3905Ganguk Hwang3https://orcid.org/0000-0002-9481-0607Department of Mathematical Sciences, Korea Advanced Institute of Science and Technology, Daejeon, South KoreaInformation and Electronics Research Institute, Korea Advanced Institute of Science and Technology, Daejeon, South KoreaDepartment of Software, Gachon University, Seongnam, South KoreaDepartment of Mathematical Sciences, Korea Advanced Institute of Science and Technology, Daejeon, South KoreaIn this paper, we propose a periodic energy trading system model in microgrids with future forecasting and forecasting errors. In the proposed model, retailers in a microgrid can purchase (sell) energy periodically from (to) other retailers in the same microgrid. In this regard, our proposed model uses stochastic processes that capture the series of forecasted energy generation/consumption over time and the forecasting errors as transitions among states. We show with the proposed model that it is enough to consider only one time period to maximize revenues of retailers over the whole time period. We further design a hierarchical algorithm that provides an equilibrium price of energy among retailers to balance between energy demand and supply in the microgrid. Some numerical examples show that our proposed model and algorithm outperform traditional ones by efficiently managing forecasting errors.https://ieeexplore.ieee.org/document/8424153/Microgridenergy trading systemfuture forecastingforecasting error
collection DOAJ
language English
format Article
sources DOAJ
author Gyohun Jeong
Sangdon Park
Joohyung Lee
Ganguk Hwang
spellingShingle Gyohun Jeong
Sangdon Park
Joohyung Lee
Ganguk Hwang
Energy Trading System in Microgrids With Future Forecasting and Forecasting Errors
IEEE Access
Microgrid
energy trading system
future forecasting
forecasting error
author_facet Gyohun Jeong
Sangdon Park
Joohyung Lee
Ganguk Hwang
author_sort Gyohun Jeong
title Energy Trading System in Microgrids With Future Forecasting and Forecasting Errors
title_short Energy Trading System in Microgrids With Future Forecasting and Forecasting Errors
title_full Energy Trading System in Microgrids With Future Forecasting and Forecasting Errors
title_fullStr Energy Trading System in Microgrids With Future Forecasting and Forecasting Errors
title_full_unstemmed Energy Trading System in Microgrids With Future Forecasting and Forecasting Errors
title_sort energy trading system in microgrids with future forecasting and forecasting errors
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2018-01-01
description In this paper, we propose a periodic energy trading system model in microgrids with future forecasting and forecasting errors. In the proposed model, retailers in a microgrid can purchase (sell) energy periodically from (to) other retailers in the same microgrid. In this regard, our proposed model uses stochastic processes that capture the series of forecasted energy generation/consumption over time and the forecasting errors as transitions among states. We show with the proposed model that it is enough to consider only one time period to maximize revenues of retailers over the whole time period. We further design a hierarchical algorithm that provides an equilibrium price of energy among retailers to balance between energy demand and supply in the microgrid. Some numerical examples show that our proposed model and algorithm outperform traditional ones by efficiently managing forecasting errors.
topic Microgrid
energy trading system
future forecasting
forecasting error
url https://ieeexplore.ieee.org/document/8424153/
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AT sangdonpark energytradingsysteminmicrogridswithfutureforecastingandforecastingerrors
AT joohyunglee energytradingsysteminmicrogridswithfutureforecastingandforecastingerrors
AT gangukhwang energytradingsysteminmicrogridswithfutureforecastingandforecastingerrors
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