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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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 |
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