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

Yujia Li, Alexandre Moreira, Miguel Heleno

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.

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

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.

Paper Structure

This paper contains 22 sections, 10 equations, 2 figures, 2 tables, 1 algorithm.

Table of Contents

  1. Introduction
  2. Temporal Interface Products
  3. Baseline Models in the Original NRCC Framework
  4. Model 1: Scenario-Based Least-Cost Distribution Network Planning (LCDNP)
  5. Model 2: Transmission-Aware Distribution Network Planning (TADNP) (P0)
  6. Temporal NRCC Extension: Service-Window Products and Rebound Management
  7. Service-Window Call Set
  8. Model 3: Temporal NRCC Product Design (P1)
  9. Model 4: Rebound-Aware Refinement (P2)
  10. Solution Method and Workflow
  11. Stress-Call Screening Set
  12. Product Construction Procedure
  13. Baseline and P0 (Models 1--2)
  14. P1 Construction (Model 3)
  15. P2 Construction (Model 4)
  16. ...and 7 more sections

Figures (2)

  • Figure 1: P0 peak netload reduction, P1 service capability, and P2 rebound metric across budget tiers.
  • Figure 2: Substation netload profiles under sustained down-call for P2 variants at reference tier. Shaded regions mark service window $\mathcal{T}(\nu)$ and variant-specific recovery windows.

Theorems & Definitions (2)

  • Remark 1
  • Remark 2