Distribution planning has traditionally relied on snapshot studies, where planners model feeder peak demand under normal conditions (N – 0) and contingency conditions (N – 1) to identify thermal overloads and voltage violations. Based on these assessments, utilities typically pursue conventional infrastructure upgrades such as reconductoring, load transfers, feeder additions, or substation expansion [1]. This approach was effective when demand growth was predictable and power flowed primarily in one direction.
Today’s distribution grid presents a different challenge. The rapid adoption of Distributed Energy Resources (DERs), electrification, and energy storage has introduced bidirectional power flows, changing load profiles, and greater operational uncertainty. As a result, planners are increasingly considering Non-Wires Alternatives (NWAs), including battery energy storage, demand response, and other DER based solutions, as alternatives or complements to traditional infrastructure investments [2, 3].
Unlike conventional wires solutions, NWAs depend on operational factors such as weather, customer behavior, and dispatch strategies. Evaluating whether an NWA can defer a feeder upgrade requires planning approaches beyond a single peak hour analysis. Modern distribution planning therefore uses multiyear simulation, time series analysis, optimization techniques, and scenario-based methods to evaluate how load growth, DER adoption, and network constraints evolve over time [1, 4]. These methods allow planners to compare technical feasibility, economic value, and uncertainty across different investment strategies.
Several planning frameworks and software tools have been developed to support this analysis. These include research tools, utility specific platforms, and commercial solutions that combine power system simulation with automated evaluation of traditional infrastructure upgrades and NWA. By assessing wires and non-wires options within the same framework, these approaches enable more practical distribution investment decisions [1, 3].
One example is EPRI’s Automated Distribution Assessment and Planning Tools (ADAPT), which represents one implementation of this broader planning approach. Built on EPRI’s open-source OpenDSS simulation engine, ADAPT evaluates distribution feeders over multiple planning years rather than a single operating snapshot. It identifies evolving thermal and voltage constraints and compares conventional upgrades with NWA options across a user defined planning horizon.
These capabilities are increasingly important as utilities face growing expectations to demonstrate that non wires alternatives have been considered before committing to major infrastructure investments. Effective NWA evaluation requires accounting for uncertainties related to location, operation, and long-term performance that traditional planning workflows were not designed to capture [3].
Overall, modern planning frameworks do not eliminate uncertainty in DER adoption, regulation, or cost recovery. However, they provide utilities with a more consistent and technically rigorous basis for comparing wires and non-wires solutions as distribution systems continue to evolve.
References
[1] D. Montenegro, C. McEntee, M. Hernandez, and R. Dugan, “Modern planning framework based on non-wires alternatives for advancing distribution planning,” in 2023 IEEE Rural Electric Power Conference (REPC), 2023.
[2] J. E. Contreras-Ocana, U. Siddiqi, and B. Zhang, “Non-wire alternatives to capacity expansion,” in 2018 IEEE Power & Energy Society General Meeting (PESGM), 2018.
[3] Electric Power Research Institute (EPRI), “Guidance on DER as non-wires alternatives (NWAs): Technical and economic considerations for assessing NWA projects,” Technical Update, Palo Alto, CA, USA, Rep. 3002013327, Dec. 2018. [Online]. Available: https://www.epri.com/research/products/3002013327
[4] P. Andrianesis, M. Caramanis, R. D. Masiello, R. D. Tabors, and S. Bahramirad, “Locational marginal value of distributed energy resources as non-wires alternatives,” IEEE Transactions on Smart Grid, vol. 11, no. 1, 2020.
