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This paper presents a comprehensive reliability framework for incorporating different plug-in electric vehicle (PEV) charging load models into the evaluation of generation adequacy. The proposed framework comprises special treatment and innovative models to achieve an accurate determination of the impact of PEV load models on reliability. First, a goodness-of-fit statistical model determines the probability distribution functions (PDFs) that best reflect the main characteristics of driver behavior. Second, robust and detailed stochastic methods are developed for modeling different charging scenarios (uncontrolled charging and charging based on time-of-use (TOU) pricing). These models are based on the use of a Monte Carlo simulation in conjunction with the fitted PDFs to generate and assess a large number of possible scenarios, while handling the uncertainties associated with driver behavior, penetration levels, charging levels, battery capacities, and customer response to TOU pricing. A novel reliability-based framework for the application of dynamic critical event call programs for use with PEV charging loads is also proposed. The effectiveness of the proposed framework with respect to improving system reliability is demonstrated using several case studies applied on the IEEE Reliability Test System. [ABSTRACT FROM AUTHOR]

This paper proposes a novel stochastic planning model for AC-DC hybrid distribution systems (DSs). Taking into account the possibility of each line/bus being AC or DC, the model finds the optimal AC-DC hybrid configuration of buses and lines in the DS. It incorporates consideration of the stochastic behavior of load demands and renewable-based distributed generators (DGs). The stochastic variations are addressed using a Monte-Carlo simulation technique. The objective of the planning model is the minimization of DS installation and operation costs. The optimal planning solution is obtained by dividing the hybrid planning problem into two nested optimization problems: 1) the main problem is formulated using a genetic algorithm (GA) to search for the optimal AC-DC configuration and 2) the subproblem is used for determining the optimal power flow solution for each configuration generated by the GA. The proposed model has been employed for finding the optimal configuration for a suggested case study that included photovoltaic panels, wind-based DG, and electric vehicle charging stations. The same case study was also solved using a traditional AC planning technique in order to evaluate the effectiveness of the proposed model and the associated cost-savings. The results demonstrate the advantages offered by the proposed model. The proposed framework represents an effective technique that can be used by DS operators to identify the optimal AC-DC network configuration of future DSs. [ABSTRACT FROM PUBLISHER]

Recent years have seen increased interest in green technologies such as photovoltaic (PV) electricity and plug-in hybrid electric vehicles (PHEVs). Such technologies, however, have been found to be detrimental to distribution networks. This paper introduces a novel distribution system architecture that can better accommodate the expected growth in PV electricity and PHEVs. In the proposed architecture, the distribution system becomes a bilayer system composed of the traditional ac layer that serves existing system loads, plus an embedded dc layer that interfaces with PV arrays and PHEVs. A bidirectional converter interconnects the two layers and controls the power flows between them. This paper presents the key design and operational aspects of the proposed architecture, with consideration of different uncertainties inherent in the system. To this end, a probabilistic benchmark has been developed for modeling these uncertainties and for use with the sizing and scheduling of different system components. Monte Carlo (MC) simulations confirmed the technical and economic merit of the proposed design methodology. [ABSTRACT FROM PUBLISHER]

The recent deployment of distributed generation has led to a revolution in the use of distribution systems and the emergence of “smart grid” concepts. Smart grids are intended primarily as a means of facilitating the integration of renewable energy sources and of achieving greater system reliability and efficiency. Energy storage systems (ESSs) offer a number of benefits that can help utilities move toward those goals. One of those benefits is the capacity to improve the utilization of network infrastructure by means of proper load management. This paper proposes a methodology for allocating ESSs in distribution systems in order to defer system upgrades, minimize system losses, and take advantage of the arbitrage benefit. The cost and arbitrage benefit of energy storage installation are optimized with respect to system upgrade and energy losses costs. The primary goal of this research is to determine the optimal size and location of storage units to be installed, in addition to their optimal operation, so that total system costs are minimized, while system benefits are maximized. In this paper, a probabilistic load model is adopted instead of utilizing time-series based models, which provide an optimal solution that is valid only for the time-series pattern that is applied. [ABSTRACT FROM PUBLISHER]

The recent deployment of distributed generation has led to a revolution in the use of distribution systems and the emergence of smart-grid concepts. Smart grids are intended primarily as a means of facilitating the integration of renewable energy sources and of achieving greater system reliability and efficiency. Energy storage systems offer a number of benefits that can help utilities move toward those goals. One of those benefits is the capacity to improve system reliability through successful islanding operation. This paper proposes a methodology for the cost-effective improvement of system reliability through the allocation of distributed storage units in distribution systems. The costs of energy storage installation are optimized with respect to reliability value expressed as customers' willingness to pay in order to avoid power interruptions. The primary goal of this research was thus to determine the optimal combination of storage units to be installed and the loads to be shed so that all possible contingencies can be effectively addressed. A probabilistic approach is therefore adopted that includes consideration of the stochastic nature of system components. [ABSTRACT FROM PUBLISHER]

This paper presents a novel probabilistic distribution load flow (PDLF) algorithm to study the effect of connecting a wind turbine (WT) to a distribution system. This probabilistic approach is used to capture the stochastic behavior of the generation of WTs. Three different models of WTs are developed to be embedded in the PDLF. Consequently, a probabilistic approach to evaluate the impact of wind penetration into distribution systems is developed. Futhermore, the effect of WT penetration on feeder losses, voltage profile and substation powers is presented. [ABSTRACT FROM PUBLISHER]

Analyzing the impacts of large on-grid photovoltaic (PV) systems on the performance of the electric network is an essential task prior to the installation of these systems. To quantify these impacts, a method based on chronological simulations can be used. The main advantage of this method is its ability to provide information about the impacts of the fluctuation of the power generated from the PV systems. However, this method requires performing extensive analysis and simulations, making it impractical for utility studies, especially if long historical data with subhourly time resolution is used. In this paper, a new method that utilizes the data efficiently while preserving the temporal information of the generated PV power is proposed. The method takes advantage of the clustering techniques to group together segments of the output PV power having similar features. Hence, a representative segment for each group can be chosen and used in the analysis and simulations. This representative segment can provide information about the expected performance of other segments of the group. The validity and usefulness of the proposed method are demonstrated by identifying the suitable size and site of a large PV system. [ABSTRACT FROM PUBLISHER]

In this paper, a new method is proposed for the control of voltage regulators that enables the regulation of multiple feeders having diversified loads using only one regulator. The selection of the tap position of the regulator is chosen based on the solution of an integer linear optimization problem. The main advantage of the method is that it has a closed-form solution for the optimal tap; a merit which is very valuable in real-time operation. The constraints for having the voltage of the regulating points within the range of permissible values were ensured. Also, the necessary condition for feasible solutions was examined. A simulation study was carried out to validate the proposed method. [ABSTRACT FROM PUBLISHER]