Learning the price response of active distribution networks for TSO-DSO coordination

TL;DR

This paper introduces a data-driven method for TSO-DSO coordination that learns the price response of active distribution networks using limited observations, enabling efficient and near-optimal decision-making without proprietary data or real-time communication.

Contribution

It proposes a novel, computationally efficient learning approach to model distribution network responses using only price and power observations, avoiding proprietary data and complex communication.

Findings

The method accurately predicts distribution network responses.

Results show near-centralized coordination performance.

The approach is adaptable to different contextual information.

Abstract

The increase in distributed energy resources and flexible electricity consumers has turned TSO-DSO coordination strategies into a challenging problem. Existing decomposition/decentralized methods apply divide-and-conquer strategies to trim down the computational burden of this complex problem, but rely on access to proprietary information or fail-safe real-time communication infrastructures. To overcome these drawbacks, we propose in this paper a TSO-DSO coordination strategy that only needs a series of observations of the nodal price and the power intake at the substations connecting the transmission and distribution networks. Using this information, we learn the price response of active distribution networks (DN) using a decreasing step-wise function that can also adapt to some contextual information. The learning task can be carried out in a computationally efficient manner and the curve it produces can be interpreted as a market bid, thus averting the need to revise the current operational procedures for the transmission network. Inaccuracies derived from the learning task may lead to suboptimal decisions. However, results from a realistic case study show that the proposed methodology yields operating decisions very close to those obtained by a fully centralized coordination of transmission and distribution.