Grid Constraints and Equitable DER Adoption

Grid Constraints and Equitable DER Adoption

Introduction

• Exploring the integration of equitable targets and incentives while maintaining a safe and reliable grid.
• Focus on how policies can achieve deployment and equity goals in distributed energy resource (DER) adoption.

Granularity of Grid Constraints

• Grid constraints are granular, often at the feeder level.
• Hosting capacities are used to identify these constraints.
• Policies are typically set at a broader level (state, utility jurisdiction, census track, or county).
• Potential tension: Policies may not consider feeder-level constraints when designed.

The Question

• How to ensure policies accomplish goals related to overall DER deployment and equity.

The Challenge of "First Come, First Served"

• Utilities or regulators may aim to incentivize a percentage of DER adoption in vulnerable communities or desire more equitable adoption policies.
• "First come, first served" can hinder DER adoption because:
  • Affluent customers are often early adopters.
  • They can quickly use up hosting capacity.
  • This leaves lower-income customers potentially responsible for grid upgrades to deploy DER.
  • If upgrades are too costly, low-income customers may not participate in clean energy or receive bill relief.

Equity Policy vs. Technical Constraints

• Equity policy is generally applied broadly, while technical constraints are granular.
• Demonstrating real-world scenarios to highlight how hosting capacity allocations occur.
• Modeling scenarios to show how desired allocation patterns depend on organizational goals.
• Looking at potential policy solutions to balance deployment and meet utility/regulatory objectives.

Example Feeder Analysis

• Initial State: Feeder before any DER deployment.
  • Features: Older, lower-income neighborhood; new, more affluent construction; a school; community businesses.
  • Peak load: 6 megawatts.
  • Minimum load: 1.2 megawatts.
  • 600 residences and 10 commercial loads.
  • Sufficient hosting capacity for some DER.
• Deployment Over Time:
  • One business (blue marker) and several residential deployments (tan/orange markers).
  • Limited remaining hosting capacity for other customers.

Scenarios for Hosting Capacity Allocation

• Evaluating scenarios to use remaining hosting capacity before grid upgrades are needed.
• Illustrating feeder-level challenges in allocating hosting capacity.
• Working through pros and cons of various approaches for utilities to distribute hosting capacity.

Scenario 1: Commercial DER (School)

• A 600 kilowatt system is added at a school.
• This single commercial customer uses up the remaining hosting capacity on the entire feeder.
• Potential Outcome: Residential customers are unhappy due to a lack of DER access and potential upgrade costs under a "first come, first served" system.
• DER capacity deployment: 230% of minimum load, 47% of peak load.

Scenario 2: Residential DER

• Remaining hosting capacity is used by residential customers.
• Comparison of total DER deployment and the number of customers deploying DER.
• Consideration of lower-income DER customers:
  • Affluent customers are typically early adopters.
  • Low-income customers may become "cost causers" due to grid upgrade requirements.
  • Economic hurdles may prevent low-income customers from deploying DER, leading to lower aggregate DER.
• Outcome:
  • 50 customers added.
  • Total DER: 2.7 megawatts (slightly lower than the commercial scenario's 2.8 megawatts).
  • More customers on the feeder.

Key Takeaways from Scenarios

• Vastly different outcomes in DER deployment can occur.
• Varying solutions to hosting capacity allocation can help achieve utility and regulatory goals.
• Goal-Dependent Policies:
  • Maximizing DER capacity deployment might favor policies supporting school deployment.
  • Social equity might prioritize reserving capacity for lower-income customers who might otherwise face economic barriers.

Potential Solutions and Policies for Hosting Capacity Allocation

• Each option has trade-offs but allows compromises between technical constraints and policy.
• The suitability of options depends on the objectives of utilities and regulators.

Quick Analysis of Selected Solutions

1. Access to Community Solar

Pros:

• Provides all customers with the option to participate, addressing equity and access to clean energy.
• Enables DER access for all customers.
• Provides bill benefits to low-income customers without upfront economic hurdles (like roof upgrades).
• Potentially higher total DER deployment across the system.

Cons:

• Potential challenges with siting large community solar projects.
• May require building system upgrades, incurring costs.
• If located on a shared feeder, it may limit DER deployment for other customers without grid upgrades.

2. Preserving a Portion of Capacity by Customer Class

Pros:

• No billing system or grid upgrades are required, saving costs for rate payers.
• Saves hosting capacity for customers in each class (commercial, residential, industrial, vulnerable/low-income).
• Addresses the issue of certain customer classes deploying DER more quickly and using all available hosting capacity.
• Saves capacity for late adopters.

Cons:

• Requires system knowledge to determine how much capacity should be saved for each class.
• If a customer class doesn't use its full capacity, total DER deployment may dip compared to a first-come, first-served policy.

Overall Outcomes of the Work

• An article was crafted for a non-technical audience.
• The goal was to bridge the gap between policy and technical personnel.
• The aim was that they understand how local grid constraints can be integrated with policy to achieve organizational goals.