Distributed Energy Resource Optimization: Page 2 of 5
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Brad Heavner, the policy director for the California Solar and Storage Association (CALSSA, formerly the California Solar Energy Industries Association), notes, “If the ICA is successful in making project development go smoother, it will avoid the many cases where customers are paying financing costs while interconnection delays keep them from achieving bill savings. Happier customers should lead to more business for solar developers.” He adds, “The ICA will not lead to an overall increase in hosting capacity throughout the state. Rather, we will know ahead of time what the available interconnection capacity is in any location.”
It is tempting to draw parallels between the ICA and the Renewable Auction Mechanism (RAM) program maps the CPUC has made available for several years now. However, there are several key differences. RAM maps are not connected to the Rule 21 tariff in any meaningful way, so there is no guarantee that the hosting capacity indicated in a RAM map will hold true when a project enters the Rule 21 process. In addition, the RAM maps are very broad and only illustrate capacity at the feeder level based on very conservative rules of thumb. Having run into these limitations on several occasions, I and many other stakeholders have abandoned using the RAM maps altogether.
The ICA approach is different. Because IOUs will use ICA results to fast-track existing Rule 21 tariff screening procedures, the hosting capacity values will be much more accurate. In addition, the ICA methodology is far more comprehensive than that used to produce RAM maps.
Heavner explains, “While the theory behind RAM maps is good—showing circuits as red, yellow or green depending on their hosting capacity—the maps have been so inaccurate and out of date in practice that they are barely useful. The ICA takes the theory behind RAM maps and does a much better job in practice by conducting a functional analysis with monthly updates. The analysis will not only be baked into the interconnection application process, but also the maps will include downloadable data on hourly and seasonal constraints.”
Demo A. The Distribution Resource Plan working group mandated that all three IOUs in California test and demonstrate two methodologies—a streamlined method and an iterative method—for development of the ICA tool. On the one hand, the streamlined approach uses complex computer algorithms to draw conclusions on DER hosting capacity at specific points within the IOU’s system. On the other, the iterative approach simulates power flows based on different DER levels at each node on the distribution system. As the CPUC mandates, the IOUs executed Demonstration Project A, or simply Demo A, with the goal of developing a common ICA methodology that works across all utilities.
The IOUs concluded that while the streamlined method uses simpler equations and enables faster computations, the results lack the level of granularity needed to replace major choke points in the Rule 21 review process. Though the streamlined method provides a reasonably good measure of hosting capacity, its results still require confirmation by a standard review process. In comparison, the iterative approach provides a more accurate and thorough assessment of DER hosting capacity but requires much longer processing times. This is because this approach must accommodate millions of iterations to model the almost infinite combinations of DER and load power flows that can arise throughout the system.
For industry stakeholders, a high level of accuracy is necessary to instill confidence in the process and to encourage active use of the ICA. In the end, the ICA working group settled on having all three IOUs utilize the iterative method for development of the ICA tool. The IOUs published the results of their first Demo A test cases on their graphical information system mapping tools in 2017. Stakeholders now have an opportunity to use Demo A and play an active role in its refinement prior to computing the ICA for entire service areas.
As shown in Figure 2, the ICA tool operates based on relatively easy-to-read heat maps that graphically illustrate optimal DER locations by overlaying ICA analysis data on a graphical information system map, accessible to the public via a web portal. The ICA tool assigns a green color to any distribution-line segment that can support a relatively large amount of DER; orange and red line sections represent locations with a decreased ability to support DER capacity. By selecting a line segment, users can access additional data-defining limits for different types of DERs. These specified limits do not rule out interconnections that exceed these limits, but rather set the expectation that larger systems should prepare for longer interconnection review timelines and substantial upgrade costs.