Risk Evaluation of Distribution Networks Considering Residential Load Forecasting with Stochastic Modeling of Electric Vehicles

Abstract

Large‐scale integration of electric vehicles (EVs) into residential distribution networks (RDNs) is an evolving issue of paramount significance for utility operators. Similarly, electric load forecasting is an operational process permitting the utilities to manage demand issues for optimal energy utilization. Unbalanced voltages prevent the effective and reliable operation of RDNs. This study implements a novel framework to examine risks associated with RDNs by applying a residential forecasting model with a stochastic model of EVs charging pattern. Diversified EV loads require a stochastic approach to predict EVs charging demand; consequently, a probabilistic model is developed to account for several realistic aspects comprising charging time, battery capacity, driving mileage, state‐of‐charge, travelling frequency, charging power, and time‐of‐use mechanism under peak and off‐peak charging strategies. Peak‐day forecast of various households is obtained in summer and winter by implementing an optimum nonlinear auto‐regressive neural‐network (NN) with time‐varying external input vectors (NARX). Outputs of the EV stochastic model and residential forecasting model obtained from Monte‐Carlo simulations and the NARX‐NN model, respectively, are utilized to evaluate power quality parameters of RDNs. Performance specifications of RDNs including voltage unbalance factor (VUF) and voltage behavior are assessed in context to EV charging scenarios with various charging power levels under different penetration levels.

Real-time Locally Optimal Schedule for Electric Vehicle Load via Diversity-maximization NSGA-II

“…In Section III, the users' charging costs and battery degradations are merged to account for the total charging costs of EV users. In this sub-section, the power load profile in (1), EV charging cost in (5), and the battery degradation in (8) are separated to discuss their contradictions. Figure 9 illustrates the Pareto frontier with the proposed DM-NSGA-II.…”

“…The increase in charging demand from the extensive EVs poses new challenges to the existing distribution system [2]- [4]. References [5] and [6] illustrate that the integration of unordered EV into the power system can damage the grid operation. However, vehicle-to-grid (V2G) technology has been proposed as a cost-effective solution to make full use of the existing network.…”

An Enhanced Distributed Voltage Regulation Scheme for Radial Feeder in Islanded Microgrid

“…A three-phase AC network can be further be classified as a balanced or unbalanced system: a balanced network contains the positive phase sequence components with equal magnitude and phase shift, while the unbalanced network has either a positive or negative sequence with irregular magnitude and phase shift. Unequal loading, fault, single-phasing, outrages, etc., are considered as the main causes of disturbances in the distribution system voltages and currents [8,9].…”

An Optimal Control Scheme for Load Bus Voltage Regulation and Reactive Power-Sharing in an Islanded Microgrid

“…One of the important factors of autonomous MG is to drive the electrical network with high security and reliability at various operating conditions. Control of voltage and reactive power is a salient step in order to obtain a reliable smart network [1][2][3]. Such issues have been investigated by many researchers as it is considered one of the leading cause for voltage collapse, which may drive the power system blackout [4].…”