Grid integration of solar photovoltaic (PV) systems and electric vehicles (EVs) has been increasing in recent years, mainly with two motivations: reducing energy cost, and reducing emission. Several research studies focuses on the individual impact of grid integration of PVs and EVs. However, it is worth noting that with the increasing penetration of PVs and EVs, the power grid will be experiencing the combined impact of PV–EV integration. To present a thorough understanding, this study first presents a detailed study on the impact of grid integration of PVs and EVs individually, followed by combined impact of PV and EV, on the aspects of grid stability, power quality and energy economics. It has been identified from the literature review that individually PVs and EVs can negatively affect the grid stability and power quality due to the intermittent nature of PV energy and uncertainty of EV load. However, several research works have reported that coordinated operation of the PVs and EVs can negate the issues arising due to individual integration of PVs and EVs. Furthermore, large‐scale penetration of PVs and EVs are expected in future energy market, and coordinated operation of them can potentially help lowering energy costs and carbon footprint.
The global warming problem together with the environmental issues has already pushed the governments to replace the conventional fossil-fuel vehicles with electric vehicles (EVs) having less emission. This replacement has led to adding a huge number of EVs with the capability of connecting to the grid. It is noted that the presence of such vehicles may introduce several challenges to the electrical grid due to their grid-to-vehicle and vehicle-to-grid capabilities. In between, the power quality issues would be the main items in electrical grids highly impacted by such vehicles. Thus, this study is devoted to investigating and reviewing the challenges brought to the electrical networks by EVs. In this regard, the current and future conditions of EVs along with the recent research works made into the issue of EVs have been discussed in this study. Accordingly, the problems due to the connection of EVs to the electrical grid have been discussed, and some solutions have been proposed to deal with these challenges.
This paper proposes a novel approach to energy exchange between electric vehicle (EV) load and wind generation utilities participating in the day-ahead energy, balancing, and regulation markets. An optimal bidding/offering strategy model is developed to mitigate wind energy and EV imbalance threats, and optimize EV charging profiles. A new strategy model is based on optimizing decision making of a wind generating company (WGenCO) in selecting the best option among the use of the balancing or regulation services, the use of the energy storage system (ESS) and the use of all of them to compensate wind power deviation. Energy imbalance is discussed using conventional systems, ESS, and EV-Wind coordination; results are compared and analyzed. Stochastic intra-hour optimization is solved by mixed-integer linear programming (MILP). Uncertainties associated with wind forecasting, energy price, and behavior of EV owners based on their driving patterns, are considered in the proposed stochastic method and validated through several case studies. Abstract-This paper proposes a novel approach to energy exchange between electric vehicle (EV) load and wind generation utilities participating in the day-ahead energy, balancing, and regulation markets. An optimal bidding/offering strategy model is developed to mitigate wind energy and EV imbalance threats, and optimize EV charging profiles. A new strategy model is based on optimizing decision making of a wind generating company (WGenCO) in selecting the best option among the use of the balancing or regulation services, the use of the energy storage system (ESS) and the use of all of them to compensate wind power deviation. Energy imbalance is discussed using conventional systems, ESS, and EV-Wind coordination; results are compared and analyzed. Stochastic intra-hour optimization is solved by mixed-integer linear programming (MILP). Uncertainties associated with wind forecasting, energy price, and behavior of EV owners based on their driving patterns, are considered in the proposed stochastic method and validated through several case studies.Index Terms-Electricity market, energy exchange, electric vehicles, energy storage, stochastic optimization.
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