Probabilistic Network Pricing Considering Demand Uncertainty in Distribution Systems

The distribution system has become highly uncertain due to the changing landscape. This paper proposes a novel probabilistic network pricing method based on the Long-Run-Incremental Pricing (LRIC) method considering demand uncertainty. The probability distributions of annual peak demand and its coincidence peak demand are represented by random variables following certain probability distributions. Probabilistic power flow is formulated by the convolution of nodal demand probability density function (PDF). The LRIC is then applied to calculate network charges by combining the Tail value at risk (TVaR) and Shapley value (SV). TVaR is used to determine the expected network utilization at a given level of risk and SV is employed to evaluate the impact of individual demand uncertainty. The proposed pricing method distinguishes network users based on their uncertainty levels and incentives lower uncertain users by economic signals. The proposed method can help both network owners and operators to potentially save investment costs and network charges at certain levels of risk.