Distribution Locational Marginal Pricing (DLMP) for Congestion Management and Voltage Support

TLDR

Distributed energy resources such as storage, generators, microgrids, and load aggregators can bid into a day‑ahead distribution‑level electricity market. The paper proposes a day‑ahead market‑clearing model for smart distribution systems. The model optimizes day‑ahead market clearing with Volt/VAR control, network reconfiguration, and wholesale market interactions, producing DLMPs for active and reactive power that are decomposed into marginal costs for active power, reactive power, congestion, voltage support, and loss. Case studies confirm the effectiveness of the proposed method.

Abstract

In this paper, a day-ahead market-clearing model for smart distribution systems is proposed. Various types of distributed energy resources (DERs), such as distributed energy storage, distributed generators, microgrids, and load aggregators, can bid into the day-ahead distribution-level electricity market. Considering system Volt/VAR control, network reconfiguration, and interactions with the wholesale market, an optimization model is built to clear the day-ahead market, through which the distribution locational marginal pricing (DLMPs) for both active power and reactive power are determined. Through derivations of the Lagrangian function and sensitivity factors, DLMPs are decomposed to five components (i.e., marginal costs for active power, reactive power, congestion, voltage support, and loss), which provide price signals to motivate DERs to contribute to congestion management and voltage support. Finally, case studies demonstrate the effectiveness of the proposed method.