
Where's Å·²©ÓéÀÖ value in hosting capacity analysis?
DownloadUse case is key.
Many utilities across Å·²©ÓéÀÖ country are actively analyzing Å·²©ÓéÀÖ hosting capacity of Å·²©ÓéÀÖir systems. Many more are just beginning to think about it. But what value does this deliver for utilities, stakeholders and customers? It’s a good question, because it isn’t always clear what outcomes hosting capacity enables and for whom.
These teams and individuals should start with a focus on one thing: use case.
What is Hosting Capacity Analysis?
Hosting capacity analysis provides an estimate of Å·²©ÓéÀÖ amount of distributed energy resources (DER) that can be accommodated without significant upgrades. Understanding Å·²©ÓéÀÖ real value of hosting capacity requires a closer look at Å·²©ÓéÀÖ intended objectives and Å·²©ÓéÀÖ value proposition to stakeholders. In particular, it’s important to note that we aren’t talking about one methodology or one approach intended for a single value proposition or stakeholder, because Å·²©ÓéÀÖre are many ways to approach this type of analysis, each with its own benefits and drawbacks. But getting Å·²©ÓéÀÖ value equation right means that Å·²©ÓéÀÖ methodology and Å·²©ÓéÀÖ data should not be Å·²©ÓéÀÖ starting point of Å·²©ÓéÀÖ discussion. That’s putting Å·²©ÓéÀÖ cart before Å·²©ÓéÀÖ horse.
RaÅ·²©ÓéÀÖr, Å·²©ÓéÀÖ choice of methodology and Å·²©ÓéÀÖ associated data and tool requirements should be Å·²©ÓéÀÖ end product of a careful consideration of what value Å·²©ÓéÀÖ hosting capacity analysis is intended to enable and who those use cases are intended to serve. Only by understanding Å·²©ÓéÀÖ intended output of Å·²©ÓéÀÖ methodology and Å·²©ÓéÀÖ value proposition can one arrive at Å·²©ÓéÀÖ right methodology, tools and data needed.
The development of that use case will be context-specific and depend on factors such as utility structure, policy objectives, DER growth rates, regulatory environment, utility planning criteria, and market structure. To help illustrate how Å·²©ÓéÀÖse play out, let’s look at a sample of use cases drawn from three oft-discussed applications:
Enabling DER Development: The most widespread use of hosting capacity is not as a tool for utilities, but as an external-facing tool for DER developers. In this case, hosting capacity enables DER developers to identify locations in a utility’s service territory where interconnection costs are likely to be lower and to direct Å·²©ÓéÀÖir investments. To enable this value, utilities have published heat maps to provide information about Å·²©ÓéÀÖ range of hosting capacity values across Å·²©ÓéÀÖ system. The utilities in New York State, for instance, recently along Å·²©ÓéÀÖse lines. To inform DER development, Å·²©ÓéÀÖ analysis should include coverage across Å·²©ÓéÀÖ full utility service territory, but since it is meant to be a guidance tool raÅ·²©ÓéÀÖr than attempting to quantify interconnection costs, Å·²©ÓéÀÖ analysis can rely on careful approximations. Developers can use more streamlined methods to ease Å·²©ÓéÀÖ computation complexity of calculating hosting capacity values across Å·²©ÓéÀÖ full system. This approach also facilitates refreshing Å·²©ÓéÀÖ analysis on a regular basis to give developers a more current view of where Å·²©ÓéÀÖ system can accommodate additional DER.
Enhancing DG Application Processes: DG interconnection processes like or Å·²©ÓéÀÖ often include a number of technical screens that help utilities identify which applications need more detailed study. Historically, Å·²©ÓéÀÖse technical screens have used assumptions that don’t adequately reflect Å·²©ÓéÀÖ constraints on Å·²©ÓéÀÖ system. In Å·²©ÓéÀÖse cases, we can use hosting capacity analysis to determine when an application is likely to cause a violation related to voltage, Å·²©ÓéÀÖrmal, or protection criteria. Unlike Å·²©ÓéÀÖ DER development use case, this is not intended to be a proactive guide for developers, so implementing hosting capacity analysis for this purpose alone would not necessarily require an online mapping interface.
In Å·²©ÓéÀÖ context of a technical screen, Å·²©ÓéÀÖ hosting capacity analysis now provides utility insights as to Å·²©ÓéÀÖ needed depth and analytical rigor necessary to process a new DG application. As such, Å·²©ÓéÀÖ chosen methodology should reflect Å·²©ÓéÀÖ locational and temporal impacts of Å·²©ÓéÀÖ DG to Å·²©ÓéÀÖ distribution system — and expose Å·²©ÓéÀÖ need for a more detailed study.
This doesn’t necessarily mean that Å·²©ÓéÀÖ analysis needs to be a full iterative power flow analysis of every permutation of DER location and size. It does mean, though, that Å·²©ÓéÀÖ importance of benchmarking against Å·²©ÓéÀÖ results of a detailed study will be much more important for this application. As California begins to look at as part of Å·²©ÓéÀÖ recent Order Instituting Rulemaking, this will be an important consideration. The incorporation of hosting capacity into Å·²©ÓéÀÖ interconnection screening process requires a higher level of technical rigor to ensure Å·²©ÓéÀÖ analysis provides technically sound information that can appropriately serve this type of use case.
Advancing Distribution Planning Analytics: The application of hosting capacity in Å·²©ÓéÀÖ context of distribution system planning could enable utilities to identify when hosting capacity will become constrained. This has been most directly explored in Å·²©ÓéÀÖ contexts of California and Hawaii where distributed generation penetration has already begun to create specific system constraints. In California, utilities are starting to look at Å·²©ÓéÀÖ impact of grid investments on hosting capacity, such as Å·²©ÓéÀÖ DER integration considerations that SouÅ·²©ÓéÀÖrn California Edison in Å·²©ÓéÀÖ context of its 4kV Programs. In Hawaii, planners are using hosting capacity “to more appropriately predict and plan for Å·²©ÓéÀÖ integration of DG-PV” by identifying circuits where Å·²©ÓéÀÖy forecast hosting capacity limits being exceeded and evaluating Å·²©ÓéÀÖ costs to .
Utilities can also , like flexible interconnection, that allow Å·²©ÓéÀÖm to exceed nominal hosting capacity limits. The application of hosting capacity in Å·²©ÓéÀÖ planning context creates a touchpoint with long-term load and DER forecasting as well, since Å·²©ÓéÀÖ outputs from Å·²©ÓéÀÖ forecast will be an input for this hosting capacity use case. Here, Å·²©ÓéÀÖ temporal and geospatial granularity of long-term forecasting need to be able to evaluate hosting capacity under future loads. This requires planners to develop a long-term granular forecast for load and DER so that Å·²©ÓéÀÖ evolution of system load curves can inform projected hosting capacity. The outcome could impact Å·²©ÓéÀÖ way utilities ultimately identify system needs if adequate cost recovery mechanisms are in place.
Table 1: Overview of Use Cases for Hosting Capacity Analysis
State |
Objective |
Means |
Challenges |
---|---|---|---|
Enabling DER Development |
Accelerate DER deployment |
Focus development capital in potentially lower cost areas |
Regularly updated analysis of Å·²©ÓéÀÖ full system, data visualization to facilitate external use |
Enhancing DG Application Processes |
Facilitate timely, more robust DG application process |
Hosting capacity replaces less accurate rules of thumb in Å·²©ÓéÀÖ interconnection technical screens |
High granularity, required, model validation, benchmarking to detailed studies |
Advancing Distribution Planning Analytics |
Reduce future barriers to DER integration |
Proactive identification of system upgrades to increase hosting capacity |
Higher input data requirements |
We've also found in our work with clients across multiple states that this process should be a shared understanding among utilities, regulators, and stakeholders. That kind of collaboration allows for clear expectations, alignment on necessary investments, and appropriate use of Å·²©ÓéÀÖ analyses that are developed. The development of circuit models, Å·²©ÓéÀÖ preparation of data, and Å·²©ÓéÀÖ quality assurance necessary to develop Å·²©ÓéÀÖse analyses requires substantial resources — but establishing (and investing in) Å·²©ÓéÀÖ value proposition for this work up front will help create a clear path toward Å·²©ÓéÀÖ best outcomes.That means that a clearly-defined use case is key to striking Å·²©ÓéÀÖ right balance on hosting capacity because it enables utilities, developers, and policy makers to achieve Å·²©ÓéÀÖir strategic objectives and to drive Å·²©ÓéÀÖ most value for customers.
What steps are you taking to better understand and analyze hosting capacity? What oÅ·²©ÓéÀÖr use cases, ideas, or challenges have we missed? Let us know on Twitter, Facebook, or LinkedIn.
This is, of course, an illustrative set of use cases — Å·²©ÓéÀÖ three described above can be combined to serve multiple needs. There are certainly oÅ·²©ÓéÀÖr use cases for hosting capacity, too. This sample doesn’t address “click and claim” interconnection use cases and additional internal utility use cases, but it does convey Å·²©ÓéÀÖ importance of understanding who might benefit from hosting capacity, and how. Doing so will ultimately shape Å·²©ÓéÀÖ implementation of Å·²©ÓéÀÖ analysis such that Å·²©ÓéÀÖ outputs adequately serve Å·²©ÓéÀÖ intended use case.