Measurement-Based Locational Marginal Prices for Real-Time Markets in Distribution Systems

This paper presents a measurement-based method to calculate distribution locational marginal prices (DLMPs) toward establishing real-time electricity markets that help to support reliable and efficient operation of distribution systems. The calculation of DLMPs typically relies on an accurate and up-to-date distribution network model, but this may not be available in practice. Instead, central to the proposed method is the online estimation of linear sensitivity models that map bus voltages to power injections and to line power flows using only synchrophasor measurements collected at buses interfacing market participants and in lines of interest. The estimated linear models replace the nonlinear power flow constraints in a multi-period look-ahead optimal power flow (OPF) problem, thus obviating the need for an offline distribution network model in obtaining DLMPs as the optimal Lagrange multipliers of the linear sensitivity constraints. Moreover, the modified OPF problem with linear constraints is a convex quadratic programming problem, for which computationally efficient solvers are readily available. The resulting DLMPs also embed costs due to potential congestion in certain lines monitored by synchrophasor measurements. Numerical simulations demonstrate the effectiveness, adaptability, and scalability of the proposed measurement-based method to establish a real-time market for distributed generation, energy storage devices, and flexible loads.