SYSYOCMar 28

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

arXiv:2603.2716186.9h-index: 6
AI Analysis

For TSOs and DSOs, it provides a non-invasive, regulatory-compliant coordination mechanism that improves investment valuation for temporal flexibility, though it is an incremental extension of the existing NRCC framework.

This paper extends the Netload Range Cost Curves (NRCC) concept to include temporal coordination in transmission and distribution planning under uncertainty, proposing two new flexibility products (P1 and P2) that outperform an atemporal baseline (P0) by properly valuing storage investments for temporal flexibility.

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.

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