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Netload Range Cost Curves for a Transmission-Aware Distribution System Planning under DER Growth Uncertainty

Samuel Cordova, Alexandre Moreira, Miguel Heleno

Abstract

In the face of a substantial and uncertain growth of behind-the-meter Distributed Energy Resources (DERs), utilities and regulators are currently in the search for new network planning strategies for facilitating an efficient Transmission & Distribution (T&D) coordination. In this context, here we propose a novel distribution system planning methodology to facilitate coordinated planning exercises with transmission system planners through the management of long-term DER growth uncertainty and its impact on the substation netload. The proposed approach is based on the design of a transmission-aware distribution planning model embedding DER growth uncertainty, which is used to determine a "menu" of secure distribution network upgrade options with different associated costs and peak netload guarantees observed from the transmission-side, referred here as Netload Range Cost Curves (NRCCs). NRCCs can provide a practical approach for coordinating T&D planning exercises, as these curves can be integrated into existing transmission planning workflows, and specify a direct incentive for distribution planners to evaluate peak netload reduction alternatives in their planning process. We perform computational experiments based on a realistic distribution network that demonstrate the benefits and applicability of our proposed planning approach.

Netload Range Cost Curves for a Transmission-Aware Distribution System Planning under DER Growth Uncertainty

Abstract

In the face of a substantial and uncertain growth of behind-the-meter Distributed Energy Resources (DERs), utilities and regulators are currently in the search for new network planning strategies for facilitating an efficient Transmission & Distribution (T&D) coordination. In this context, here we propose a novel distribution system planning methodology to facilitate coordinated planning exercises with transmission system planners through the management of long-term DER growth uncertainty and its impact on the substation netload. The proposed approach is based on the design of a transmission-aware distribution planning model embedding DER growth uncertainty, which is used to determine a "menu" of secure distribution network upgrade options with different associated costs and peak netload guarantees observed from the transmission-side, referred here as Netload Range Cost Curves (NRCCs). NRCCs can provide a practical approach for coordinating T&D planning exercises, as these curves can be integrated into existing transmission planning workflows, and specify a direct incentive for distribution planners to evaluate peak netload reduction alternatives in their planning process. We perform computational experiments based on a realistic distribution network that demonstrate the benefits and applicability of our proposed planning approach.
Paper Structure (16 sections, 5 equations, 12 figures)

This paper contains 16 sections, 5 equations, 12 figures.

Table of Contents

  1. Introduction
  2. Literature Review
  3. Contributions
  4. Conventional Cost Minimization Approaches for Distribution Planning
  5. Deterministic Planning Model
  6. Scenario-Based Planning Model
  7. Proposed Transmission-Aware Distribution Planning Strategy
  8. Transmission-Aware Distribution Planning Model
  9. Netload Range Cost Curves
  10. Computational Experiments
  11. General Settings
  12. DER Growth Scenario Generation
  13. Planning Results:Deterministic Planning Model
  14. Planning Results: Scenario-Based Planning Model
  15. Planning Results: Proposed Transmission-Aware Distribution Planning Strategy
  16. ...and 1 more sections

Figures (12)

  • Figure 1: Workflow for building NRCCs to facilitate T&D planning coordination.
  • Figure 2: Example of application of NRCCs in transmission planning
  • Figure 3: San Francisco distribution network layout, including installed RPV capacity and candidate reinforcements. The size of the circles indicate the RPV capacity installed at each bus, ranging from 36 to 369 kW.
  • Figure 4: Aggregated RPV capacity evolution resulting from 100 agent-based simulations of RPV adoption. Selected representative scenarios are highlighted in black.
  • Figure 5: Minimum, Average, and Maximum RPV adoption scenarios resulting from an agent-based simulation. The size of the circles indicate the installed RPV capacity at each bus, ranging from 36 to 1939 kW. The total resulting installed RPV capacity is indicated in parenthesis for each scenario.
  • ...and 7 more figures