Cost-aware renewable energy management: Centralized vs. distributed generation

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Cost-aware renewable energy management: Centralized vs. distributed generation. / Leithon, Johann; Werner, Stefan; Koivunen, Visa.

In: Renewable Energy, Vol. 147, 03.2020, p. 1164-1179.

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@article{5b2545e3f8df42ea85f439a34980ea3d,
title = "Cost-aware renewable energy management: Centralized vs. distributed generation",
abstract = "We propose optimization strategies for cooperating households equipped with renewable energy assets and storage devices. We consider two system configurations: In the first configuration, households share access to an energy farm, where electricity is generated from renewable sources and stored in battery banks. In the second configuration, households are equipped with their own renewable energy sources and storage devices, and are allowed to share energy through the grid. The developed optimization model takes into account location and time-varying energy prices as well as energy transfer fees. To design our strategies, we first establish performance bounds, and compare the two configurations in terms of achievable savings and usability of renewable energy. Then, we devise real-time energy management algorithms by incorporating forecasting techniques in the proposed framework. Simulation results show that the proposed strategies outperform existing solutions by up to 10{\%}. It is also shown that cooperative strategies outperform greedy approaches by up to 6.8{\%}.",
keywords = "Energy storage, Energy allocation, Cooperative strategies, Non-convex optimization",
author = "Johann Leithon and Stefan Werner and Visa Koivunen",
year = "2020",
month = "3",
doi = "10.1016/j.renene.2019.09.077",
language = "English",
volume = "147",
pages = "1164--1179",
journal = "Renewable Energy",
issn = "0960-1481",

}

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TY - JOUR

T1 - Cost-aware renewable energy management: Centralized vs. distributed generation

AU - Leithon, Johann

AU - Werner, Stefan

AU - Koivunen, Visa

PY - 2020/3

Y1 - 2020/3

N2 - We propose optimization strategies for cooperating households equipped with renewable energy assets and storage devices. We consider two system configurations: In the first configuration, households share access to an energy farm, where electricity is generated from renewable sources and stored in battery banks. In the second configuration, households are equipped with their own renewable energy sources and storage devices, and are allowed to share energy through the grid. The developed optimization model takes into account location and time-varying energy prices as well as energy transfer fees. To design our strategies, we first establish performance bounds, and compare the two configurations in terms of achievable savings and usability of renewable energy. Then, we devise real-time energy management algorithms by incorporating forecasting techniques in the proposed framework. Simulation results show that the proposed strategies outperform existing solutions by up to 10%. It is also shown that cooperative strategies outperform greedy approaches by up to 6.8%.

AB - We propose optimization strategies for cooperating households equipped with renewable energy assets and storage devices. We consider two system configurations: In the first configuration, households share access to an energy farm, where electricity is generated from renewable sources and stored in battery banks. In the second configuration, households are equipped with their own renewable energy sources and storage devices, and are allowed to share energy through the grid. The developed optimization model takes into account location and time-varying energy prices as well as energy transfer fees. To design our strategies, we first establish performance bounds, and compare the two configurations in terms of achievable savings and usability of renewable energy. Then, we devise real-time energy management algorithms by incorporating forecasting techniques in the proposed framework. Simulation results show that the proposed strategies outperform existing solutions by up to 10%. It is also shown that cooperative strategies outperform greedy approaches by up to 6.8%.

KW - Energy storage

KW - Energy allocation

KW - Cooperative strategies

KW - Non-convex optimization

U2 - 10.1016/j.renene.2019.09.077

DO - 10.1016/j.renene.2019.09.077

M3 - Article

VL - 147

SP - 1164

EP - 1179

JO - Renewable Energy

JF - Renewable Energy

SN - 0960-1481

ER -

ID: 37043092