Time Window-Based Netload Range Cost Curves for Coordinated Transmission and Distribution Planning Under Uncertainty

TL;DR

This paper extends Netload Range Cost Curves to include temporal aspects, enabling better coordination of transmission and distribution planning under uncertainty without invasive data sharing.

Contribution

It introduces a hierarchy of certified temporal interface products that quantify distribution network flexibility for T&D planning, improving upon static approaches.

Findings

Proposed products outperform static bounds in valuing storage flexibility.

Numerical results show improved coordination and investment efficiency.

Time-window-based products better capture temporal flexibility benefits.

Abstract

Mechanisms to coordinate transmission and distribution planning should be regulatory compliant and keep the spheres of DSO and TSO decisions separate, without requiring disclosure of proprietary data or unrealistic computationally expensive T&D co-simulations. The concept of Netload Range Cost Curves (NRCC) has been recently proposed as simple non-invasive form of coordinating T&D investments under distribution netload uncertainty. This paper extends the NRCC concept to accommodate the temporal dimension of the T&D planning process. We propose to compute a hierarchy of certified temporal interface products that represent the different levels of flexibility that distribution networks can provide transmission grids with at the planning stage. The first product (P1) maps distribution investment into scenario-robust, per-window service envelopes within which any TSO service call (to modify load within specified bounds) is guaranteed distribution-network-feasible. The second product (P2) adds lexicographic rebound minimization, preserving P1-optimal service capacity while certifying post-service recovery under three governance variants with qualitatively distinct rebound-budget responses. In our numerical results, based on a real distribution feeder, we compare the performance of our proposed time-window-based flexibility products to an atemporal product (P0) that offers a static bound on the aggregate distribution grid netload across all time periods. Our results demonstrate the superiority of our proposed products in properly valuing the benefits of incremental investments in storage to allow for temporal flexibility.