With the growing adoption of both residential and commercial electric vehicles (EV) and the rapid deployment of EV charging stations, it is of paramount importance to assess the potential overloading impact of intensive EV charging on the operation and planning of power distribution systems. Targeting at the west Kentucky rural area, this research leverages the Distribution Resource Integration and Value Estimation (DRIVE) and HotSpotter software tools to investigate the potential impact of EV charging on the operation of regional distribution systems and the lifetime degradation of power transformers. The research outcome helps identify possible distribution system overload risks and mitigation solutions to meet future intensive EV charging necessity under assumed EV adoption scenarios. Possible overloading in the distribution systems and undervoltage violations are examined. In addition, the overload impact of EV charging is investigated by conducting a multi-physics reliability analysis of a distribution transformer.

This study demonstrates a dispatching scheme of wind-solar hybrid power system (WSHPS) for a one-hour dispatching period for an entire day utilizing battery and supercapacitor hybrid energy storage subsystem (HESS). A frequency management approach is deployed to extend the longevity of the batteries through extensively utilizing the high energy density property of batteries and the high power density property of supercapacitors in the HESS framework. A low-pass filter (LPF) is employed to decouple the power between a battery and a supercapacitor (SC). The cost optimization of the HESS is computed based on the time constant of the LPF through extensive simulations in MATLAB/SIMULINK platform. The curve fitting and Particle Swarm Optimization approaches are applied to seek the optimum value of the LPF time constant. Several control algorithms as a function of the battery state of charge are developed to achieve accurate estimation of the grid reference power for each one-hour dispatching period. This estimation helps to minimize the energy storage cost, in addition to ensuring that the HESS has sufficient capacity for next-day operation. The optimum value of depth of discharge for HESS considering both cycling and calendar expenses has also been investigated for the best competitive energy storage cost for hourly dispatching the power of the WSHPS. This research also presents an economic comparison to investigate the significance of using different types of energy storage for hourly dispatching the WSHPS. The simulation results show that the presented HESS is superior to battery or SC-only operation.

This study demonstrates an effective dispatching scheme of utility-scale wind power at one-hour increments for an entire day with a hybrid energy storage system consisting of a battery and a supercapacitor (SC). Accurate forecasting of wind power is crucial for generation scheduling and economic operation. Here, wind speed is predicted by one hour ahead of time using a multilayer perceptron Artificial Neural Network, which exhibits satisfactory performance with good convergence mapping between input and target output data. Furthermore, an adaptive neuro-fuzzy inference system is employed to devise a state of charge (SOC) controller to accurately estimate the grid reference power (P _Grid,ref ) for each one-hour dispatching period. This type of desired P _Grid,ref estimation is critical to ensure the energy storage system (ESS) completes each dispatching period with its starting SOC and has adequate capacity available for next-day operation. Also, the particle swarm optimization technique is implemented to optimize the life cycle cost of the ESS based on its depth of discharge usage, which is vital for minimizing the cost of a dispatchable wind power scheme. The actual wind speed data of four different days as a representative of each season recorded at Oak Ridge National Laboratory are utilized in the simulations to provide a realistic economic assessment for dispatching the wind power.

Electric power grids are critical infrastructure for delivering energy from generation stations to load centers. To maximize utilization of assets, it is desirable to increase the power transferred over transmission systems. Reliable protection of transmission systems is essential for safeguarding the integrity and reliability of the power grid. Distance protection is the most widely used scheme for protecting transmission lines. Most existing protection systems use local measurements to make a decision while pilot protection is used in some circumstances. Distance protection may fail under stressed operating conditions, which could lead to cascading faults. This paper proposes a system integrity protection scheme by utilizing wide area measurements. The scheme partitions the system into subnetworks or protection zones and employs current measurements to derive a fault identification vector indicating the faulted zone. Then the fault location is pinpointed based on wide area measurements and network data. The proposed method is able to deal with multiple, simultaneous faults, and is applicable to both transposed and untransposed lines. Evaluation studies based on simulation studies are presented.

Significant opportunity for savings in energy and investment through improved performance of power distribution systems exists in the optimal placement and rating of capacitors, a conventionally cost-effective and popular reactive power compensating technology. A novel optimal capacitor planning (OCP) procedure is proposed for large-scale utility power distribution systems, which is exemplified on an existing utility circuit of approximately 4,000 buses. An initial sensitivity analysis is employed to intelligently reduce OCP computation time and maintain quality of optimal configurations. Three optimization objectives are considered, including the minimization of total system active power losses, standard deviation of node voltages, and investment in total capacitor power rating. Eight multi-objective optimization methods that employ the non-dominated sorting algorithm III (NSGA-III) concept are compared to determine individual merits. Differences between the methods include the incorporation of a penalty constraint for voltage violations and the automatic readjustment of load-tap-changing (LTC) transformer tap settings for proposed capacitor re-configurations concurrently within the optimizer, which ensures peak system performance and fair comparison to the reference case. A multi-step model conversion process was developed with OpenDSS to enable the OCP procedure to be generally applicable to real large-scale utility circuits. OCP is performed for three example sub-circuits served by a substation with a 48MW, 9Mvar peak load, which represents the most extreme case and offers the best opportunity for savings. Example configurations from the resulting Pareto sets through a pseudo-weight vector approach are also analyzed through a systematic procedure of comparison between the most extreme configuration types to inform configuration selection.