Distribution Locational Marginal Pricing under Generation and Network Scarcity Conditions

This paper addresses the integration of reserve scarcity pricing into distribution locational marginal prices (DLMPs) by proposing a computationally tractable formulation of reserve deliverability. The primary goal is to understand how network congestion and generation scarcity affect DLMPs and to evaluate the effectiveness of different market design approaches in providing accurate investment signals in distributed energy systems.

Recent research has introduced flexibility platforms and models that attempt to integrate distributed energy resources within market operations. This work builds upon the Caramanis model, and introduces an inscribed-boxes formulation that allows for scalable application to meshed networks. The proposed model is shown to be equivalent to existing approaches on radial networks and offers computational tractability. Furthermore, it enables detailed analysis of DLMP pricing patterns under congestion and various energy and reserve flow scenarios.

The analysis reveals that accounting for reserve deliverability significantly impacts DLMPs and investment incentives. The findings emphasize that without incorporating network constraints and scarcity pricing, investment signals may be distorted, potentially leading to suboptimal infrastructure placement.