Search

Battery energy storage systems (BESSs) can be very beneficial to power systems and microgrids for various applications. With increasing sales of electric vehicles (EV), the availability of used electric vehicle batteries (EVBs) is on the rise, which has received significant attention in recent years. The retired EVBs, after repurposing, can serve as an alternative option to new batteries in a BESS. In addition, when a microgrid operator desires to install a BESS, the optimal decisions such as installation year, energy and power size, replacement year, and the number of cycles to failure, that are normally overlooked, have to be determined. Therefore, this paper proposes a comprehensive and novel framework for planning and operation of the BESS based on repurposed EVBs. A novel linearized BESS sizing model is proposed that obtains the BESS optimal decisions regarding design and operation. Various new, modified, and linearized relationships for the BESS have been included in the planning model to ensure that the replacement year of the BESS is optimally determined. Several classes of EVs with multiple drive cycles are clustered and integrated within the proposed framework. [ABSTRACT FROM AUTHOR]

Given the expected impact of electric vehicle (EV) charging on power grids, this paper presents a novel two-step approach for the smart operation of EVs with four-quadrant chargers in a primary distribution feeder, accounting for the uncertainties associated with EVs, and considering the perspectives of both the utility and the EV owners. In the first step of the proposed approach, the mean daily feeder peak demand and corresponding hourly feeder control schedules, such as taps and switched capacitor setpoints, considering the bidirectional active and reactive power transactions between EVs and the grid, are determined. A nonparametric bootstrap technique is used, in conjunction with a genetic algorithm-based optimization model, to account for EV uncertainties and discrete variables. In the second step, the maximum possible power that can be given to connected EVs at each node, while providing active and/or reactive power to maintain the peak demand value and corresponding feeder dispatch schedules defined in the first step, is computed every few minutes in a way which is fair to the EVs. The proposed approach is validated using the distribution feeder model of a real primary feeder in Ontario, Canada, considering significant EV penetration levels. The results show that the proposed approach could be implemented in practice to properly operate EVs, satisfying feeder, and peak demand constraints, which would be better than the business-as-usual practice or a popular heuristic method in terms of number of tap operations, system peak demand, and voltage regulation. [ABSTRACT FROM AUTHOR]

With the increased penetration of electric vehicle (EV) chargers in distribution systems, there is a need to understand and minimize their impact on medium-voltage (MV) and low-voltage (LV) networks. Thus, this paper proposes a three-stage algorithm to coordinate the operation of four-quadrant EV chargers with other volt/var control devices in MV and LV distribution feeders. The first stage operates on a day-ahead basis and defines the load tap changer and capacitor schedules while minimizing the peak load associated with EVs in the distribution system. The second and third stages update their operation every five minutes, to fairly allocate the aggregated and individual EV loads in the MV an LV feeders, respectively, while minimizing active power losses and voltage deviations. The proposed technique is applied to CIGRE’s North-American MV and LV benchmark systems to demonstrate its ability to properly allocate EV loads, and improve distribution system performance in terms of losses and voltage deviations. [ABSTRACT FROM AUTHOR]

This paper proposes a model of a single-phase bidirectional electric vehicle (EV) charger with capability of operating in all four quadrants of the P – Q plane. The steady-state and step responses of the proposed model are used to validate it based on the actual responses of a bidirectional charger prototype for different P – Q requests. The model can be used efficiently in time-domain simulations that require models of a number of EV chargers, such as EV integration studies in low-voltage (LV) distribution networks. A practical case study is presented to demonstrate and test the proposed smart charger and model, investigating the provision of vehicle-to-grid (V2G) for active and reactive power in an LV residential distribution network. These results demonstrate the advantages of the presented charger model for developing V2G strategies in distribution networks. [ABSTRACT FROM PUBLISHER]

This paper provides a detailed comparative analysis of optimal sizing of battery-only, ultracapacitor-only, and battery–ultracapacitor hybrid energy storage systems (ESSs) for a plug-in electric city bus (PECB). It is shown how the configuration affects the optimal size of the ESS. The problem of optimal sizing of the storage system for the PECB is formulated and solved for a specific set of vehicle parameters, battery, and ultracapacitor cell data, as well as a specific daily drive cycle. A modified particle swarm optimization algorithm is used to solve the optimal sizing problem. The optimization platform developed by the authors and used for this study is highly flexible and accepts different component data, vehicle parameters, and drive cycles as the input for determining the optimal sizes of the storage system. [ABSTRACT FROM PUBLISHER]

Batteries are the most commonly used electrical energy storage devices. The cost and performance of an electric vehicle (EV) are strongly affected by the proper selection of technology, number, and arrangement of the battery cells used. This paper formulates the problem of optimal sizing of the battery unit (BU) for a plug-in EV (PEV), given the specifications of the vehicle, battery cell data, and drive cycle. This paper employs a metaheuristic optimization algorithm to find the optimal size of the BU with the objective of minimizing the overall cost. Feasibility of the optimization results in terms of respecting the constraints is verified via simulation. The developed optimization platform is highly flexible and allows use of different vehicle designs, component data, and drive cycles. [ABSTRACT FROM PUBLISHER]

Fuel-celI vehicles have the potential to revolutionize transportation. In particular, a fuel-cell vehicle using a combined battery-ultracapacitor energy storage system can provide excellent fuel economy and performance while extending the battery life due to more frequent use of the ultracapacitor. This paper first presents a new fuel cell-battery-ultracapacitor (FC-B-UC) vehicle topology. Then, a vehicle simulator is used to show that the new topology is superior to a promising FC-B-UC topology from the literature. Finally, an analytical optimization method is developed to determine the optimal battery and ultracapacitor sizes for two different options of the novel FC-B-UC topology. The optimization method seeks to maximize efficiency and minimize mass and cost of the overall system. Numerical examples are provided to validate the analytical optimization method. [ABSTRACT FROM AUTHOR]

Although many researchers have investigated the use of different powertrain topologies, component sizes, and control strategies in fuel-cell vehicles, a detailed parametric study of the vehicle types must be conducted before a fair comparison of fuel-cell vehicle types can be performed. This paper compares the near-optimal configurations for three topologies of vehicles: fuel-cell-battery, fuel-cell--ultracapacitor, and fuel-cell-battery--ultracapacitor. The objective function includes performance, fuel economy, and powertrain cost. The vehicle models, including detailed dc/dc converter models, are programmed in MATLAB/Simulink for the customized parametric study. A controller variable for each vehicle type is varied in the optimization. [ABSTRACT FROM AUTHOR]