Real-Time Building Smart Charging System Based on PV Forecast and Li-ion Battery Degradation

This paper proposes a two-stage smart charging algorithm for future buildings equipped with an electric vehicle, battery energy storage, solar panels, and a heat pump. The first stage is a non-linear programming model that optimizes the charging of electric vehicles and battery energy storage based...

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Main Authors: Wiljan Vermeer, Gautham Ram Chandra Mouli, Pavol Bauer
Format: Article
Language:English
Published: MDPI AG 2020-07-01
Series:Energies
Subjects:
V2G
Online Access:https://www.mdpi.com/1996-1073/13/13/3415
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spelling doaj-537351603dd54bd68408dfafd24bd4652020-11-25T03:48:10ZengMDPI AGEnergies1996-10732020-07-01133415341510.3390/en13133415Real-Time Building Smart Charging System Based on PV Forecast and Li-ion Battery DegradationWiljan Vermeer0Gautham Ram Chandra Mouli1Pavol Bauer2Electrical Sustainable Energy department, Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, 2628CD Delft, The NetherlandsElectrical Sustainable Energy department, Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, 2628CD Delft, The NetherlandsElectrical Sustainable Energy department, Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, 2628CD Delft, The NetherlandsThis paper proposes a two-stage smart charging algorithm for future buildings equipped with an electric vehicle, battery energy storage, solar panels, and a heat pump. The first stage is a non-linear programming model that optimizes the charging of electric vehicles and battery energy storage based on a prediction of photovoltaïc (PV) power, building demand, electricity, and frequency regulation prices. Additionally, a Li-ion degradation model is used to assess the operational costs of the electric vehicle (EV) and battery. The second stage is a real-time control scheme that controls charging within the optimization time steps. Finally, both stages are incorporated in a moving horizon control framework, which is used to minimize and compensate for forecasting errors. It will be shown that the real-time control scheme has a significant influence on the obtained cost reduction. Furthermore, it will be shown that the degradation of an electric vehicle and battery energy storage system are non-negligible parts of the total cost of energy. However, despite relatively high operational costs, V2G can still be cost-effective when controlled optimally. The proposed solution decreases the total cost of energy with 98.6% compared to an uncontrolled case. Additionally, the financial benefits of vehicle-to-grid and operating as primary frequency regulation reserve are assessed.https://www.mdpi.com/1996-1073/13/13/3415smart chargingelectric vehiclevehicle to gridV2Gbattery degradationLi-ion
collection DOAJ
language English
format Article
sources DOAJ
author Wiljan Vermeer
Gautham Ram Chandra Mouli
Pavol Bauer
spellingShingle Wiljan Vermeer
Gautham Ram Chandra Mouli
Pavol Bauer
Real-Time Building Smart Charging System Based on PV Forecast and Li-ion Battery Degradation
Energies
smart charging
electric vehicle
vehicle to grid
V2G
battery degradation
Li-ion
author_facet Wiljan Vermeer
Gautham Ram Chandra Mouli
Pavol Bauer
author_sort Wiljan Vermeer
title Real-Time Building Smart Charging System Based on PV Forecast and Li-ion Battery Degradation
title_short Real-Time Building Smart Charging System Based on PV Forecast and Li-ion Battery Degradation
title_full Real-Time Building Smart Charging System Based on PV Forecast and Li-ion Battery Degradation
title_fullStr Real-Time Building Smart Charging System Based on PV Forecast and Li-ion Battery Degradation
title_full_unstemmed Real-Time Building Smart Charging System Based on PV Forecast and Li-ion Battery Degradation
title_sort real-time building smart charging system based on pv forecast and li-ion battery degradation
publisher MDPI AG
series Energies
issn 1996-1073
publishDate 2020-07-01
description This paper proposes a two-stage smart charging algorithm for future buildings equipped with an electric vehicle, battery energy storage, solar panels, and a heat pump. The first stage is a non-linear programming model that optimizes the charging of electric vehicles and battery energy storage based on a prediction of photovoltaïc (PV) power, building demand, electricity, and frequency regulation prices. Additionally, a Li-ion degradation model is used to assess the operational costs of the electric vehicle (EV) and battery. The second stage is a real-time control scheme that controls charging within the optimization time steps. Finally, both stages are incorporated in a moving horizon control framework, which is used to minimize and compensate for forecasting errors. It will be shown that the real-time control scheme has a significant influence on the obtained cost reduction. Furthermore, it will be shown that the degradation of an electric vehicle and battery energy storage system are non-negligible parts of the total cost of energy. However, despite relatively high operational costs, V2G can still be cost-effective when controlled optimally. The proposed solution decreases the total cost of energy with 98.6% compared to an uncontrolled case. Additionally, the financial benefits of vehicle-to-grid and operating as primary frequency regulation reserve are assessed.
topic smart charging
electric vehicle
vehicle to grid
V2G
battery degradation
Li-ion
url https://www.mdpi.com/1996-1073/13/13/3415
work_keys_str_mv AT wiljanvermeer realtimebuildingsmartchargingsystembasedonpvforecastandliionbatterydegradation
AT gauthamramchandramouli realtimebuildingsmartchargingsystembasedonpvforecastandliionbatterydegradation
AT pavolbauer realtimebuildingsmartchargingsystembasedonpvforecastandliionbatterydegradation
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