This white paper is the culmination utility interviews coordinated over five months by the National Renewable Energy Laboratory (NREL) and Kevala, Inc. (Kevala) to better understand distribution capacity planning challenges. The interviews covered all aspects of capacity planning including load and DER forecasting, criteria for assessing system constraints, solution types, and organizational and decision-making structures. This report provides insight into distribution capacity planning decision support needs for utilities and the increasing number of stakeholders involved, from state and regulatory agencies, to communities and solution providers with interest in increasing their understanding in the distribution capacity planning process.

Executive Summary

Distribution system planning (DSP) is experiencing monumental shifts in consumer needs and expectations. Opening DSP to stakeholders is a challenging but critical endeavor, and innovative solutions are needed for utilities to effectively communicate the costs and risks of planning decisions and facilitate meaningful stakeholder engagements and education around DSP. This white paper is the culmination of interviews with utility representatives coordinated over 5months by the National Renewable Energy Laboratory (NREL) and Kevala, Inc. (Kevala) to better understand the current state, challenges, and opportunities in distribution capacity planning.

For this study, common features of current DSP were observed among the utilities interviewed and are illustrated in Figure ES-1.

Capacity constraints are typically predicted using a deterministic load and distributed energy resource (DER) forecasting process looking at 3- to 10-year time horizons, and at the“substation” or circuit-level spatial resolution. The most common concern raised by the utilities for this study was low geospatial resolution forecasts. These “peanut-butter spread” forecasts result from a top-down forecast for load and DER technologies with disaggregation methods that may not accurately capture locational adoption trends and differences in the underlying building stock and customer characteristics. This lack of granularity greatly reduces a planner’s ability to anticipate relative grid needs and target solutions in areas with expected future rapid load and/or DER growth.

Low-cost solutions and new infrastructure replacements are typically used to address capacity constraints, while non-wires alternative (NWA) solutions are limited by technical criteria, timing, project size and economics based on the deferral value of capital investments. Fixed annual capital budgets, along with competition for these limited funds between departments(e.g., between planning and operations), or within departments (e.g., capacity projects indifferent utility planning zones) for project priority can make it difficult to provide transparency in the project selection process.

The current planning process has several gaps and opportunities as illustrated in the future distribution capacity planning framework in Figure ES-1, which are primarily in the following areas:

  • Longer-term (>15 years) capacity planning horizons that align with policy goals
  • Customer-driven, time-series and geospatially granular load and DER adoption forecast methods
  • Use of scenario and probabilistic methods to better capture uncertainty and manage risk
  • Use and integration of data and technologies across utility departments
  • A more holistic view of objectives and metrics for evaluating distribution planning solutions that include not only reliability and economics but also address resiliency, equity, and carbon emissions

Forward-looking decision support methods for DSP could be developed that align with the forward-looking nature of IRP and IGP frameworks. For example, IGP with decision support tools could be used to proactively assess how long-term distribution capacity costs would change with and without managed electric vehicle charging, DERs, and other load management options. IGP could also help entities undertaking DSP to equitably allocate DER or electric vehicle interconnection costs.

Objective metrics and decision-making frameworks to weigh the importance of each planning criteria should be clearly defined to align corporate utility goals with external stakeholders and regulatory bodies. New holistic and technology-agnostic metrics or planning criteria (e.g., for hosting capacity, resilience, equity, energy justice, energy efficiency, and distribution resource adequacy) are needed that can be applied with confidence to utility investments and non-wires solutions.

Ultimately, the industry would benefit from having a distribution planning guide that can serve as a reference and can describe best practices on conducting distribution planning activities, without prescribing a “one-size fits all” approach to distribution planning, since distribution grids across country have significant differences in their structure and operations.