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The Role of Flexible Connection in Accelerating Load Interconnection in Distribution Networks

Nan Gu, Ge Chen, Junjie Qin

TL;DR

This work addresses accelerating load interconnection in distribution grids amid rising demand by introducing flexible connection, where new loads can be curtailed or delayed under utility-controlled interventions. It develops a flexibility-aware hosting capacity analysis FA-HCA that explicitly limits interventions and provides efficient solution methods for both curtailment and delay models. Theoretical and empirical results show that a small number of infrequent interventions can unlock significant hosting capacity, with a formal link between curtailment and delay and a robust extension from copperplate to general radial networks validated on the IEEE 123-bus feeder. The findings offer a practical pathway to avoid costly grid upgrades and speed interconnection for data centers, EVs, and other flexible loads while maintaining reliability and service continuity.

Abstract

This paper investigates the role of flexible connection in accelerating the interconnection of large loads amid rising electricity demand from data centers and electrification. Flexible connection allows new loads to defer or curtail consumption during rare, grid-constrained periods, enabling faster access without major infrastructure upgrades. To quantify how flexible connection unlocks load hosting capacity, we formulate a flexibility-aware hosting capacity analysis problem that explicitly limits the number of utility-controlled interventions per year, ensuring infrequent disruption. Efficient solution methods are developed for this nonconvex problem and applied to real load data and test feeders. Empirical results reveal that modest flexibility, i.e., few interventions with small curtailments or delays, can unlock substantial hosting capacity. Theoretical analysis further explains and generalizes these findings, highlighting the broad potential of flexible connection.

The Role of Flexible Connection in Accelerating Load Interconnection in Distribution Networks

TL;DR

This work addresses accelerating load interconnection in distribution grids amid rising demand by introducing flexible connection, where new loads can be curtailed or delayed under utility-controlled interventions. It develops a flexibility-aware hosting capacity analysis FA-HCA that explicitly limits interventions and provides efficient solution methods for both curtailment and delay models. Theoretical and empirical results show that a small number of infrequent interventions can unlock significant hosting capacity, with a formal link between curtailment and delay and a robust extension from copperplate to general radial networks validated on the IEEE 123-bus feeder. The findings offer a practical pathway to avoid costly grid upgrades and speed interconnection for data centers, EVs, and other flexible loads while maintaining reliability and service continuity.

Abstract

This paper investigates the role of flexible connection in accelerating the interconnection of large loads amid rising electricity demand from data centers and electrification. Flexible connection allows new loads to defer or curtail consumption during rare, grid-constrained periods, enabling faster access without major infrastructure upgrades. To quantify how flexible connection unlocks load hosting capacity, we formulate a flexibility-aware hosting capacity analysis problem that explicitly limits the number of utility-controlled interventions per year, ensuring infrequent disruption. Efficient solution methods are developed for this nonconvex problem and applied to real load data and test feeders. Empirical results reveal that modest flexibility, i.e., few interventions with small curtailments or delays, can unlock substantial hosting capacity. Theoretical analysis further explains and generalizes these findings, highlighting the broad potential of flexible connection.

Paper Structure

This paper contains 17 sections, 6 theorems, 21 equations, 5 figures.

Table of Contents

  1. Introduction
  2. Formulation
  3. Flexibility Models
  4. Power Flow Constraints
  5. Flexibility-Aware Hosting Capacity Analysis
  6. Copperplate Case with Curtailment Flexibility
  7. Methods for FA-HCA
  8. Empirical Observations
  9. Probabilistic Modeling and Universality
  10. Copperplate Case with Delay Flexibility
  11. Methods for FA-HCA
  12. Empirical Observations
  13. Theory: Connecting DF and CF
  14. General Radial Networks
  15. Theory: Bridging General and Copperplate Cases
  16. ...and 2 more sections

Key Result

Proposition 1

The optimal value of opt:hca is The optimal load modification is

Figures (5)

  • Figure 1: Hosting capacity gain for CF (left) and depth of curtailment requirement distribution with $K/T=1\%$ (right).
  • Figure 2: Distribution of the existing load.
  • Figure 3: Expected hosting capacity (left) and depth of curtailment distribution for $K=350$ (right).
  • Figure 4: Hosting capacity gain for DF (left) and delay requirement distribution with $K/T=1\%$ (right).
  • Figure 5: Results for the IEEE 123-bus test feeder.

Theorems & Definitions (9)

  • Definition 1: Dynamic Hosting Capacity and Order Statistics
  • Proposition 1: Solving FA-HCA: Copperplate with CF
  • Theorem 1: Distribution of $C^\star_K$
  • Theorem 2: Marginal Gain & Depth of Curtailment
  • Proposition 2: Solving FA-HCA: Copperplate with DF
  • Remark 1: Dynamic Minimal Delay Requirement
  • Theorem 3: Connecting DF and CF
  • Definition 2: Dynamic Hosting Capacity, Network Case
  • Theorem 4: FA-HCA, General Network