AI & ML
Computation of Price Signals for Controlling Flexible Prosumers in Distribution Grids Incorporating Stochasticity and Fairness
arXiv eess.SY0 views
arXiv:2610.18383v1 Announce Type: new Abstract: This paper proposes a method for distribution system operators (DSOs) to design spatially fair dynamic price signals for flexible prosumers, accounting for both distribution grid constraints and the stochastic behavior of prosumers. Since locational pricing can introduce price unfairness when grid constraints are active, the proposed approach includes mechanisms to enforce price fairness across the network. The method involves the DSO solving a scenario-based optimal power flow (OPF) problem to derive, similarly to locational marginal prices in transmission systems, the Lagrange multipliers associated with grid constraints and to compute individualized price signals for each prosumer under various PV generation and demand scenarios. Subsequently, two methods are introduced to aggregate these individualized prices into a single fair price across prosumers. Their performance is evaluated through simulations on a model distribution grid, comparing prosumer revenues, grid constraint violations, and analyzing the impact of fairness on reducing cost variance among prosumers.
Source:https://arxiv.org/abs/2610.18383PreviousAdaptive Handling of Deadline Misses via Stochastic MPCNextImpact of Data Center Load on Co-Optimized Generation and Transmission Expansion Planning with Embedded Unit Commitment
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