TY - JOUR
T1 - Simultaneous long-term planning of flexible electric vehicle photovoltaic charging stations in terms of load response and technical and economic indicators
AU - Nasab, Morteza Azimi
AU - Zand, Mohammad
AU - Padmanaban, Sanjeevikumar
AU - Dragicevic, Tomislav
AU - Khan, Baseem
N1 - Publisher Copyright:
© 2021 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2021/12
Y1 - 2021/12
N2 - Photovoltaic charging stations (PVCSs) are one of the most important pieces of charging equipment for electric vehicles (EVs). Recently, the process of designing solar charging stations as flexible sources has been growing and developing. This paper presents a relatively complete design of a solar charging station as a flexible economic resource in a 10-year planning horizon based on a genetic algorithm in two scenarios. PVCSs are not considered in the first scenario. This scenario is only to confirm the results, and the proposed method is proposed. However, in the second scenario, the effects of PVCSs and the demand response strategy (DR) on this development are considered. Copula probability distribution functions are used to create appropriate scenarios for vehicles during different planning years. The proposed energy management system shows a stable performance in terms of the annual load growth index and electricity price of each level of demand over the time horizon along with minimizing power losses and costs required, which makes PVCS efficiency higher and gives them a suitable structure and stability. The modeling results in terms of uncertainties in the system indicate that the use of load management along with PVCS design and flexible electric vehicle charge control strategies improves power quality parameters and optimizes system cost over a period of 10 years. Compared to the obtained results with the traditional case, it is observed that long-term planning in terms of DR and PVCSs and the technical specifications of the network have been improved. As a result of this proposed long-term planning, PVCSs are more flexible.
AB - Photovoltaic charging stations (PVCSs) are one of the most important pieces of charging equipment for electric vehicles (EVs). Recently, the process of designing solar charging stations as flexible sources has been growing and developing. This paper presents a relatively complete design of a solar charging station as a flexible economic resource in a 10-year planning horizon based on a genetic algorithm in two scenarios. PVCSs are not considered in the first scenario. This scenario is only to confirm the results, and the proposed method is proposed. However, in the second scenario, the effects of PVCSs and the demand response strategy (DR) on this development are considered. Copula probability distribution functions are used to create appropriate scenarios for vehicles during different planning years. The proposed energy management system shows a stable performance in terms of the annual load growth index and electricity price of each level of demand over the time horizon along with minimizing power losses and costs required, which makes PVCS efficiency higher and gives them a suitable structure and stability. The modeling results in terms of uncertainties in the system indicate that the use of load management along with PVCS design and flexible electric vehicle charge control strategies improves power quality parameters and optimizes system cost over a period of 10 years. Compared to the obtained results with the traditional case, it is observed that long-term planning in terms of DR and PVCSs and the technical specifications of the network have been improved. As a result of this proposed long-term planning, PVCSs are more flexible.
KW - Charging control strategies
KW - Flexible electric vehicles
KW - Load response
KW - Photovoltaic charging stations
UR - https://www.scopus.com/pages/publications/85117949810
U2 - 10.3390/wevj12040190
DO - 10.3390/wevj12040190
M3 - Article
AN - SCOPUS:85117949810
SN - 2032-6653
VL - 12
JO - World Electric Vehicle Journal
JF - World Electric Vehicle Journal
IS - 4
M1 - 190
ER -