Risk Assessment Of Distribution Network Research Articles

A framework for stochastic estimation of electric vehicle charging behavior for risk assessment of distribution networks

Power systems are being transformed to enhance the sustainability. This paper contributes to the knowledge regarding the operational process of future power networks by developing a realistic and stochastic charging model of electric vehicles (EVs). Large-scale integration of EVs into residential distribution networks (RDNs) is an evolving issue of paramount significance for utility operators. Unbalanced voltages prevent effective and reliable operation of RDNs. Diversified EV loads require a stochastic approach to predict EVs charging demand, consequently, a probabilistic model is developed to account several realistic aspects comprising charging time, battery capacity, driving mileage, state-of-charge, traveling frequency, charging power, and time-of-use mechanism under peak and off-peak charging strategies. An attempt is made to examine risks associated with RDNs by applying a stochastic model of EVs charging pattern. The output of EV stochastic model obtained from Monte-Carlo simulations is utilized to evaluate the power quality parameters of RDNs. The equipment capability of RDNs must be evaluated to determine the potential overloads. Performance specifications of RDNs including voltage unbalance factor, voltage behavior, domestic transformer limits and feeder losses are assessed in context to EV charging scenarios with various charging power levels at different penetration levels. Moreover, the impact assessment of EVs on RDNs is found to majorly rely on the type and location of a power network.

Risk Assessment of Distribution Networks Integrating Large-Scale Distributed Photovoltaics

Risk impacts on the operation of electric power distribution networks, when large amounts of distributed photovoltaics (PVs) are included, are gradually increasing to become a critical consideration for distribution networks' operations. In this paper, a risk assessment method is proposed which considers large-scale distributed PV feeding into distribution networks. Cluster partitioning is used to group large-scale distributed PV, to more accurately calculate the operational risk indicators for distribution networks with large-scale distributed PV compared to traditional risk assessment methods. A copula function is used to describe the correlation between the PV output and the load, in order to more accurately calculate power flow information compared to the traditional independent model of output and load. Node voltages over-limits and branch power flows outside boundaries are selected as the risk indicators, and a comprehensive risk indicator is introduced to more comprehensively and meaningfully evaluate the risk of distribution networks' operation. Also, the effects on the operational risk of the distribution network of load fluctuations, and, PV quantity, capacity, and location are analyzed and discussed. Finally, the IEEE34-bus system was simulated, and the results for different scenarios were calculated and analyzed. The simulation results demonstrate the effectiveness of the proposed method.

Assessment and Countermeasures of the Operation Risk of Distribution Network with High Penetration of Distributed PV

Due to the severe intermittence, volatility and uncertainty of the output power, the integration of large scale photovoltaics (PVs) will inevitably impact the power flow and node voltage of a distribution network, and confront the network with higher operation risk. This paper carries out the operation risk assessment of distribution networks with high penetration of PV units, and develops measures to offset the risk. A probabilistic power flow calculation based on Monte Carlo method is proposed in this paper at first, then the operation risk assessment model for a distribution network is established based on the risk assessment indexes of node voltage and line power flow limit violation. The specific implementation of the risk assessment method is presented. Based on these works, specific risk countermeasures are proposed. The validity of the risk assessment method and effectiveness of the risk countermeasures are verified by simulation results.

Risk Assessment of Distribution Network Based on Random set Theory and Sensitivity Analysis

Considering the complexity and uncertainty of operating information in distribution network, this paper introduces the use of random set for risk assessment. The proposed method is based on the operating conditions defined in the random set framework to obtain the upper and lower cumulative probability functions of risk indices. Moreover, the sensitivity of risk indices can effectually reflect information about system reliability and operating conditions, and by use of these information the bottlenecks that suppress system reliability can be found. The analysis about a typical radial distribution network shows that the proposed method is reasonable and effective.

Operation risk assessment of distribution network considering time dependence correlation coefficient

Operation risk assessment of distribution network considering time dependence correlation coefficient

Risk Assessment of Distribution Networks Considering the Charging-Discharging Behaviors of Electric Vehicles

Electric vehicles (EVs) have received wide attention due to their higher energy efficiency and lower emissions. However, the random charging and discharging behaviors of substantial numbers of EVs may lead to safety risk problems in a distribution network. Reasonable price incentives can guide EVs through orderly charging and discharging, and further provide a feasible solution to reduce the operational risk of the distribution network. Considering three typical electricity prices, EV charging/discharging load models are built. Then, a Probabilistic Load Flow (PLF) method using cumulants and Gram-Charlier series is proposed to obtain the power flow of the distribution network including massive numbers of EVs. In terms of the risk indexes of node voltage and line flow, the operational risk of the distribution network can be estimated in detail. From the simulations of an IEEE-33 bus system and an IEEE 69-bus system, the demonstrated results show that reasonable charging and discharging prices are conducive to reducing the peak-valley difference, and consequently the risks of the distribution network can be decreased to a certain extent.