Planning alignment implies new interdependencies between processes and bidirectional information flows between processes. On the one hand, distribution planning informs IRP by providing granular information about local resources and their impact on planning reserve requirements. On the other hand, DER sourcing outcomes stemming from resource plans could inform the need for distribution system upgrades to ensure resource deliverability. These interdependencies create the need for more robust alignment between the two processes. Alignment points related to planning objectives, information flows, and solution evaluation illustrate how this alignment works in practice.
Articulating planning objectives
The first element of the alignment between IRP and distribution system planning is the articulation of objectives. With states, cities, and utilities adopting increasingly ambitious goals for clean energy adoption, energy storage procurement, and electric system resilience, the adoption of congruent planning objectives is becoming increasingly important.
This adoption will be increasingly important in the context of resilience, where the electric sector is only one facet of a broader statewide approach (as in North Carolina). This kind of alignment applies to both objective setting at the outset of the planning process as well as the development of associated planning criteria that reflect those objectives.
Ultimately, planning objectives and criteria help tie the planning process to specific outcomes against which utilities can evaluate the solutions in each process.
Data flows and information sharing
The second point of alignment between planning processes is in the data flows, and information sharing that ensures models used in each process are internally consistent.
This doesn’t mean that IRP capacity expansion models need to make use of distribution system interval meter data, nor that distribution planning forecasts need to match IRP zonal forecasts. The sum of bottom-up forecasts doesn’t match top-down forecasts because local peaks are often non-coincident and because different forecasting approaches will reflect the risk management approaches appropriate for each study. For example, planning studies might call for different types of forecasts (e.g., 90/10 vs 50/50 forecasts). This also doesn’t imply the need for uber-models that can co-optimize across transmission, distribution, generation, and customer solutions.
What it does mean is that models should reflect common assumptions and a consistent set of inputs. Approaches like hierarchical models can reconcile top-down and bottom-up forecasts to help facilitate this alignment. More importantly, information flow and information sharing between planning departments can ensure that load forecasts and other model inputs remain internally consistent and accurately reflect the objectives, criteria, and constraints at each level of the system.
Solution identification and evaluation
Finally, the identification and evaluation of distributed resource solutions can contribute to the development of a composite supply curve that can, in turn, inform IRP solution identification and evaluation.
For example, the distribution system plan could provide information about the availability of DER and its resource adequacy contribution or effective load carrying capability (ELCC). To the extent that utilities are increasingly planning for emerging needs on the system, this kind of a supply curve can comprehensively address not only traditional planning metrics (such as resource adequacy and generation output) but also contribute to system flexibility needs and system resilience.
IRP solicitation outputs similarly inform forecasts by reflecting sourced DER to inform distribution system planning. This two-way flow of information, between resource planning and distribution system planning, ensures that IRP holistically considers all possible resources to meet system needs and that all planning processes reflect the value of DER.
Enabling a holistic view of resource value
The promise of more integrated distribution planning is predicated on the ability to reflect the full set of values that all resources can provide. This requires capabilities that enable not just DER integration and utilization, but also alignment with resource planning and transmission planning to reflect the value of those resources to all parts of the system.
Aligned objectives help promote congruent outcomes across planning processes, and new information flows to promote internal consistency between models and studies. This kind of aligned planning also requires a holistic view of the value that resources can provide—not just for energy and capacity but for emerging attributes like flexibility and local resilience that are increasingly important to meeting system needs and achieving state goals.