Å·²©ÓéÀÖ

Don't miss out

Don't miss out

Don't miss out

ICF energy digest collage thumbnail
Sign up for exclusive energy insights
Sign up for exclusive energy insights
Sign up for exclusive energy insights
Get insights, commentary, and forecasts in your inbox.
Get insights, commentary, and forecasts in your inbox.
Get insights, commentary, and forecasts in your inbox.
Subscribe now

Where's Å·²©ÓéÀÖ value in hosting capacity analysis?

Download
Where's Å·²©ÓéÀÖ value in hosting capacity analysis?
Nov 9, 2017
5 MIN. READ

Use 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

<Å·²©ÓéÀÖad>

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.

The latest Energy news, explained.

Subscribe to get insights, commentary, and forecasts in your inbox.

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.