Renewable Energy, volume 183, pages 903-921

Design and optimal energy management of community microgrids with flexible renewable energy sources

Kozlov Aleksander 1
Kurbatsky Victor 1
Rehtanz C. 2
Lora Electo E S 3
2
 
Institute of Energy Systems, Energy Efficiency and Energy Economics, TU Dortmund University , Dortmund 44227 , Germany
3
 
NEST – Excellence Group in Thermal Power and Distributed Generation, Institute of Mechanical Engineering, Federal University of Itajubá (UNIFEI), Av. BPS 1303, Itajubá, Minas Gerais State, 37500-903, Brazil
Publication typeJournal Article
Publication date2022-01-01
Journal: Renewable Energy
Quartile SCImago
Q1
Quartile WOS
Q1
Impact factor8.7
ISSN09601481
Renewable Energy, Sustainability and the Environment
Abstract
Energy communities is a new, but already successful prosumer model of the local energy systems' construction. It is based on distributed energy sources and the electricity consumers’ flexibility who are the members of the community. In search of the most effective ways to interact within themselves and with the external energy system, local energy communities become platforms for exciting experiments in the field of new energy practices including local markets for flexibility, building cooperative microgrids, achieving energy autonomy, and many others. This work aims to present a unified approach to building and optimally managing the community microgrids with an internal market, given the social, environmental, and economic benefits of a particular location of such a community. A new modeling framework is introduced, based on bilevel programming and reinforcement learning, for structuring and solving the internal local market of a community microgrids, composed of entities that may exchange energy and services among themselves. The overall framework is formulated in the form of a bilevel model, where the lower level problem clears the market, while the upper level problem plays the role of the community microgrid operator (Community EMS). We strengthen the traditional bilevel problem statement by the local energy management system (Local EMS) introduction based on Monte-Carlo tree search algorithm. Our approach makes it possible to enable interaction of the local control systems for microgrids with the community microgrid operator as part bilevel programming problem solution. Numerical results obtained on the real test case of the microgrid community for the settlements located in the Transbaikal National Park (Russia), which include various renewable energy sources (wind, solar power, biomass gasifiers) and storage devices, show reduction of the LCOE index from 20% to 40% and improving the quality of electricity supply to the analyzed settlements. • Methodology for economically optimised design a community microgrids based on RESs. • The concept of building green microgrids communities integrated with biomass gasifiers. • The concept of a fair local electricity market using bi-level optimization.

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Tomin N. V. et al. Design and optimal energy management of community microgrids with flexible renewable energy sources // Renewable Energy. 2022. Vol. 183. pp. 903-921.
GOST all authors (up to 50) Copy
Tomin N. V., Shakirov V., Kozlov A., Sidorov D., Kurbatsky V., Rehtanz C., Lora E. E. S. Design and optimal energy management of community microgrids with flexible renewable energy sources // Renewable Energy. 2022. Vol. 183. pp. 903-921.
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RIS Copy
TY - JOUR
DO - 10.1016/j.renene.2021.11.024
UR - https://doi.org/10.1016%2Fj.renene.2021.11.024
TI - Design and optimal energy management of community microgrids with flexible renewable energy sources
T2 - Renewable Energy
AU - Tomin, Nikita V.
AU - Shakirov, Vladislav
AU - Kozlov, Aleksander
AU - Sidorov, Denis
AU - Kurbatsky, Victor
AU - Rehtanz, C.
AU - Lora, Electo E S
PY - 2022
DA - 2022/01/01 00:00:00
PB - Elsevier
SP - 903-921
VL - 183
SN - 0960-1481
ER -
BibTex
Cite this
BibTex Copy
@article{2022_Tomin
author = {Nikita V. Tomin and Vladislav Shakirov and Aleksander Kozlov and Denis Sidorov and Victor Kurbatsky and C. Rehtanz and Electo E S Lora},
title = {Design and optimal energy management of community microgrids with flexible renewable energy sources},
journal = {Renewable Energy},
year = {2022},
volume = {183},
publisher = {Elsevier},
month = {jan},
url = {https://doi.org/10.1016%2Fj.renene.2021.11.024},
pages = {903--921},
doi = {10.1016/j.renene.2021.11.024}
}
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