Abstract
Distribution locational marginal pricing (DLMP) is an increasingly popular pricing signal that can be used to incentivize grid-friendly behavior of distributed energy resources (DER) to optimize economic efficiency in distribution grids. In this paper, a lossy direct-current optimal power flow (DCOPF) is utilized to obtain the iterative calculation framework for DLMPs. The two-stage algorithm iterates between the transmission system optimal power flow (OPF) and the distribution system OPF until no significant changes in DLMPs are observed. Real power losses are estimated using a static piecewise linear approximation technique. A sampling algorithm is proposed to minimize the possible convergence issues associated with the proposed mathematical model. DLMPs are calculated for the i) contemporary, ii) enhanced, and iii) meshed distribution grids using an IEEE 34-bus test feeder. The test transmission system is modeled using an IEEE 30-bus system. Finally, the calculated DLMPs in the enhanced grid are compared against three existing pricing mechanisms via three case studies to prove its validity and superiority, especially in congested systems with high penetration of price-responsive loads (PRLs).
Highlights
Green-energy policies and innovative technological advancements have collectively led to a rapid growth of interest for grid-integration of distributed energy resources (DER) over the last decade
This paper aims to investigate an extension of Locational marginal pricing (LMP) concept to various types of distribution systems in order to encourage grid-friendly behavior from DER to benefit system operations at both the distribution and transmission levels
We develop an iterative framework to calculate distribution locational marginal pricing (DLMP) based on solving a lossy direct-current optimal power flow (DCOPF) problem
Summary
Green-energy policies and innovative technological advancements have collectively led to a rapid growth of interest for grid-integration of distributed energy resources (DER) over the last decade. As a result of these advancements, the structure and the control procedures of the future distribution grid is predicted to change. Development of smart grids and the increase in penetration levels of DER such as battery energy storage systems (BESSs) and price-responsive loads (PRLs), bring about new challenges to the centralized distribution infrastructure and distribution system operators (DSOs). The future distribution grid is likely to experience significantly higher levels of congestion at. Generating appropriate pricing signals is crucial for efficient DER management, to ensure efficient congestion management and efficacy in overall grid operation [4]
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