Pennsylvania Transmission and Distribution (T&D) Avoided Cost Study

Demand Side Analytics (DSA) conducted a transmission and distribution (T&D) avoided cost study in Pennsylvania. The focus of the study is on quantifying the change in T&D costs associated with an increase or decrease of kW coincident with location-specific peaks. It employs methodologies that are novel for Pennsylvania but have been applied and approved in New York and California for load forecasting and distributed energy resource (DER) valuation. The full study is available online here.

A vital role of the Electric Distribution Company (EDC) is to ensure that regional electricity supply makes its way to homes and businesses safely, reliably, and cost-effectively. By projecting future demand and reinforcing the local transmission and distribution network so that sufficient capacity is available to meet local needs as they change over time, costly outages are avoided.

What are the objectives of the study?

The study was designed to meet the following objectives:

• Analyze load patterns, excess capacity, load growth rates, and the magnitude of expected infrastructure investments at a local level
• Model location-specific forecasts of growth with uncertainty
• Quantify the probability of potential need for infrastructure upgrades at specific locations
• Calculate local avoided distribution costs by year and location
• Identify beneficial locations for demand reductions

Which methods did we use?

The deferral value approach focuses on quantifying the value of load relief on ratepayer costs (i.e. revenue requirements). It effectively compares revenue requirements with and without load relief. While infrastructure upgrades can be temporarily avoided or deferred via load relief, they cannot be avoided indefinitely because equipment eventually ages and needs to be replaced. The marginal cost of service study approach quantifies the supply cost of additional distribution or transmission capacity on the system. At the simplest level, it involves classifying infrastructure investments as growth related or not and dividing the costs of those investments by the incremental transmission or distribution capacity added. The approach uses the cost of adding additional transmission capacity to the system as a proxy for the cost avoided by reducing peak demand.

Figure 1: T&D Avoided Costs Methods Considered

What did we do?

Figure 2 describes the main steps in developing location-specific avoided distribution costs using probabilistic methods. These steps help identify the magnitude of reductions at the right location at the right time and right season to delay upgrades. The process was implemented for each feeder and substation (transformers or terminals if applicable) that had a valid growth rate and operating limit, then layered two levels to get the distribution avoided cost for each site. For system-wide values, the estimates consider the likelihood that reductions would be in locations with or without value due to random chance. We emphasize that system-wide value is a load-weighted average of areas where reductions do or do not lead to deferral of distribution investments.

Figure 2: Key Steps in Estimating Location Specific Avoided Costs

What are the results?

Based on the analysis, Table 1 summarizes the territory-wide average T&D avoided cost by EDC and season. The avoided cost of transmission capacity estimates simply increases with inflation and escalation. The avoided cost of distribution capacity values changes at varying rates based on the outcomes of the probabilistic deferral analysis methodology.

Table 1: T&D Avoided Cost ($2026)

While the final study outputs are territory-wide average values for each EDC, the granular forecasts are useful for identifying locations and timing when demand reductions or injections of distributed generation are beneficial. Figure 3 shows the total deferral value by local systems. Shades of blue indicate relatively low deferral value while orange and red tones indicate high deferral value. The values range from a lower bound of $100 to a maximum of $200 in 2026 nominal dollar. To calculate the total deferral value, we aggregated the deferral value at feeder and substation levels, then incorporated the deferral value of transmission. A key outcome of the study was to highlight the fact that the avoided T&D costs associated with peak load relief vary widely within each EDC territory.

The value of avoided T&D costs associated with an increment or decrement of peak load is a key component of benefit-cost analyses. In practice, T&D capital costs resources are concentrated in pockets that are experiencing growth but lack the capacity to accommodate additional growth. Most utilities have a mix of areas where loads are growing and areas where loads are declining, which may or may not overlap with highly loaded components. In locations with excess distribution capacity or where local peak demand is declining, the potential to avoid T&D costs is minimal. In areas where a large, growth‐related investment is imminent, the avoided T&D costs from reducing peak demand are much higher.

Figure 3: Heat Map of Total Deferral Value ($2026/kW-year)

What did we find?

    Load growth varies by location. Some pockets are experiencing load growth, and some are experiencing load decreases. We received granular growth rates for PECO, PPL, and FirstEnergy. In each EDC territory, growth trends varied by location. As a result, growth-related T&D investments are required even when overall EDC loads are flat or declining.

    The T&D avoided costs are concentrated in locations that are more heavily loaded. A key component of distribution planning is the loading factor: the weather-normalized peak demand divided by the operating limit. Not surprisingly, avoided costs are concentrated in more highly loaded locations. Conversely, locations with ample capacity to accommodate additional loads had lower avoided T&D costs.

    Individual locations are generally winter or summer peaking, not both. Most distribution locations – feeders, transformers, substations – can be classified as winter or summer peaking. Few feeders are dual peaking. The implication is that the avoidable T&D cost for a specific location is concentrated in the summer or winter, but not both.

    Resources that deliver load relief at the right location, in the right season, and at the right hours are more valuable. The same energy efficiency resource can deliver different T&D benefits at two locations based on how well it coincides with the local peak load. To illustrate, a more efficient air conditioner does not provide T&D load relief on a winter-peaking substation but does so on a summer-peaking substation. Likewise, measures with load shapes that better coincide with the need for load relief are more valuable.

    Lump loads are a key driver of distribution upgrades. Lump loads are simply new, large loads. They vary widely in size, and it can be difficult to predict in advance when and where they will show up. When they are built, they often trigger distribution and even transmission upgrades. Reducing demand via EE&C program efforts can create room for additional loads and help avoid upgrades due to smaller lump-load projects.

The Pennsylvania PUC leveraged the results of the study for its 2026 TRC Test Tentative Order. The TRC Test Order provides utilities with directions for calculating avoided costs and performing benefit-cost analysis when planning for Phase V of Act 129 programs. The avoided T&D values will play an important role in the Phase V DR Potential Study, which DSA is currently working on.