Distribution Electricity Pricing under Uncertainty
This work addresses the need for pricing mechanisms in distribution systems with high renewable penetration, offering a theoretically grounded approach for market design.
The paper proposes a method to incorporate renewable energy uncertainty and operator risk tolerance into distribution locational marginal prices (DLMPs) using chance-constrained AC optimal power flow and conic duality, resulting in itemized prices for active/reactive power, balancing, and voltage support, while proving competitive equilibrium and showing that voltage chance constraints distort it.
Distribution locational marginal prices (DLMPs) facilitate the efficient operation of low-voltage electric power distribution systems. We propose an approach to internalize the stochasticity of renewable distributed energy resources (DERs) and risk tolerance of the distribution system operator in DLMP computations. This is achieved by means of applying conic duality to a chance-constrained AC optimal power flow. We show that the resulting DLMPs consist of the terms that allow to itemize the prices for the active and reactive power production, balancing regulation, and voltage support provided. Finally, we prove the proposed DLMPs constitute a competitive equilibrium, which can be leveraged for designing a distribution electricity market, and show that imposing chance constraints on voltage limits distorts the equilibrium.