Future Peak Loads and DER Adoption Forecasts: Exclusive Interview with Patrick McCoy of Sacramento Municipal Utility District
- Nov 1, 2019 3:22 pm GMT
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A key aspect that decision-makers at utilities must balance is not just matching supply with demand today but also looking ahead to how those figures will change in the coming years and making sure they are making the appropriate investments to match that today. While such needs have always been a challenging exercise, the modern energy landscape that has integrated new grid resources like distributed energy resources and demand response capabilities has thrown a new set of wrenches into this type of forward-looking planning.
This need to look ahead and anticipate how more widespread adoption of DER will adjust the planning from utilities is an area of focus on which Patrick McCoy, Distributed Energy Strategic Business Planner at Sacramento Municipal Utility District (SMUD), will be sharing his insights at next week’s 40th PLMA Conference. If this quickly evolving and inherently critical topic is one that catches your interest, be sure to catch his presentation “Evaluating Future Peak Loads with DER Adoption Forecasting.”
If you can’t wait until next week, though, get a sneak peek by reading through the interview Patrick was kind enough to give me on the topic and his upcoming presentation:
Matt Chester: Before getting to your much-anticipated presentation at the PLMA Conference, I’d love if you could share with the Energy Central audience an overview of your background. How did you find your way into the utility sector and what type of work are you doing these days?
Patrick McCoy: I started in the energy business in 1993 working for the State of California, Department of General Services. I worked in the Office of Energy Services that provided energy-related services to State of California agencies. I actually learned the natural gas business first. We had a natural gas services program that was buying, transporting, and delivering natural gas to state agency clients.
Then, because of the impending electric deregulation that occurred in California at the time in 1996, my role started deviating away from natural gas and more towards distributed generation. Distributed generation became more prominent during the energy crisis, where the goal was to increase generating assets at state facilities.
When Arnold Schwarzenegger was elected Governor in 2003, I was permanently assigned to develop and operate a solar-powered purchase program for the state of California. The goal of the program was to build large-scale solar PV at the systems at state facilities. Typically, these were large state facilities, such as prisons and state hospitals, but I also worked with my counterparts in the California State University system and the University of California system, so that's how I got involved in solar PV as a technology and a generating resource.
I came to SMUD in 2010 to be a planner for the solar incentive programs. California had a solar incentive program that started in 2006, and I was the planner for SMUD's version, so I've been working in solar PV ever since I came to SMUD. The way we became strategists was due to the recognition that distributed energy resources was going to play an increasing role in the utility world and the business of operating utilities. A decision was made that we needed to start developing strategies around distributed energy resources, so a group of us was brought together to form a distributed energy strategy group in 2015. Since then, we've been developing, evaluating, revising and adding to our distributed energy resource strategies and plans.
MC: At SMUD, you’re pursuing DER adoption forecasting via various solutions, but can you preface that by discussing why the ability to forecast DER adoption is critical? How do those forecasts inform SMUD’s overall plans and roadmap?
PM: All electric utilities forecast their load and demand: how much customer demand and how much load do I need to serve next year and for some time horizon looking forward. Utilities need to be able to resource that demand, they need to be able to serve those loads, so forecasting energy demand and supply will increasingly be impacted by the amount of DER technologies that our customers adopt. The adoption of DER technologies impacts the process of load forecasting and has the potential to significantly change the forecasted load on a going forward basis.
Load forecasting is important because a significant part of the overall utility business starts with the load forecast. What's the load going to be? What are the resources that I need to serve that load, what are the revenues I need to collect in order to serve that load both from a resource perspective and from a grid operations perspective? So, load forecasting, at least here at SMUD, is the beginning of a planning business cycle from which we determine our revenue requirements and annual budgets given our current rate structure. Load forecasting also helps us to think about how we might consider changes to those rates and how we should evolve these rate structures and rate design, especially if we are trying to achieve some strategic objective, such as reducing carbon emissions.
Given the way that load forecasting can inform SMUD's overall business plan and strategic roadmap we have commissioned the creation of a distributed resource plan that will play a key role in the implementation of SMUD’s integrated resource plan. The distributed resource plan and the work that goes into its development will be focusing on distributed energy resources connected to the distribution grid, how they get adopted by customers or otherwise deployed, how they are operated over some period of time and the conditions of operation. The development of the plan will also help us start thinking about what we need to consider relative to the continued adoption and/or operation of distributed energy resources. DER adoption forecasting not only provides information that will be incorporated into the distributed resource plan but will become an integral part of the planning process for the distribution planning, distribution operations, resource planning, and energy trading and contracts folks. They will all need to understand the distributed resource plan and the roadmap moving forward so that they can then develop their plans accordingly.
MC: Forecasting tech adoption is traditionally a challenging task, but can you speak about what the unique challenges are when forecasting energy technology and specifically DER forecasting?
PM: The challenge is similar to forecasting technology adoption in that you are primarily trying to forecast customer purchasing behavior. The drivers for purchasing DER technologies are probably different in that the customer is trying to achieve a benefit in the form of lower energy bills and/or contributing to the creation of environmental benefits. This may seem obvious to most everyone in terms of the challenges and importance, but what folks need to be aware of is that there are several approaches to forecasting DER adoption and these approaches may require different data sets and information to run the models and algorithms. There are a number of companies that are involved in the area of forecasting adoption and customer behavior, and it can be comprised of several parts, so in a sense, DER adoption forecasting has a number of moving parts.
For the residential customers, we have to think about their purchasing behavior and propensities relative to how they are characterized on the basis of demographics and psychographics, such as the PRIZM customer segmentation data and information. While the economics of adoption may or may not look promising, we've noticed customers adopting technologies that they probably shouldn't if they were thinking about it rationally from an economic point of view, so they must have done it for some other reason. Environmental reasons as a driver for adoption is certainly a big reason why customers would want to adopt PV, for example. So we have to think about our residential customers differently, we need to think about them in terms of their propensities relative to the particular customer demographic/psychographic segment that they fall into. Otherwise, it can be very challenging, especially when thinking about the temporal aspects of purchasing behavior, as in when will a customer purchase a PV system or EV or battery storage system.
On the commercial side, it's even more challenging because you have a wide variety of commercial customers with differing operational profiles, load profiles, and seasonal variations regarding energy consumption. Ownership of their facilities, local business vs regional vs national companies, energy bill savings vs corporate policy mandates, and other factors can complicate the outlook on adoption. Schools, for example, typically aren't in session during the summer and so their load shapes seasonally look much different than say a commercial strip mall. Schools do want to save money, but they are also price-sensitive and have limited budget flexibility but can accept longer payback horizons. Walmart has a different set of requirements and tolerances when compared to a school. So commercial customers become a real challenge in trying to determine a) whether they would adopt a particular DER technology and b) when would they adopt as well. The propensity for adoption and understanding these propensities is a key challenge because everything else, technically speaking, economically speaking, you can figure out. If rooftop PV was good for everybody, why hasn't everybody adopted ? What's going on there?
MC: I found it interesting that you’re going to discuss in your presentation that DER adoption forecasts can become outdated quickly. How does that tendency affect your approach and what you do with the end results? Does it create an ongoing forecasting need rather than a more periodic check-in?
PM: Currently, DER forecasting is integrated into the load forecast that we generate every year so it has become an annual exercise. Now, we do have more periodic activities to which our DER adoption forecasting effort is also important. I believe that we’ve decided to review our integrated resource plan every three years, which more than likely means we're going to review our distributor resource plan every three years, but the challenge with thinking about it from a frequency or a periodic basis is that things change quickly. Refreshing a DER adoption forecast every three years may not be sufficient.
One story that illustrates how quickly conditions can change refers back to 2015 when the investment tax credits were going to come to an end, and we had just completed our first really deep-dive investigation of DER technology adoptions. In December of that year, Congress decided to extend the investment tax credit to its current form. Within the space of a month or two, meaning late winter of 2015, this decision changed things dramatically and we had to quickly adjust those studies to incorporate this new policy call. And so because things can change quickly as this example demonstrates, you have to think about developing forecasts from a scenario perspective because there are a lot of what-ifs and possible forecast outcomes. If you have a software tool that can iterate rapidly through a number of plausible scenarios, you can start to think about some kind of a distribution of possible future outcomes with regards to where you think things are going, so that notion of not knowing the future and knowing that the future changes really quickly is why you take more of a scenario-based approach. Granted, you are going to have to make some assumptions which should be tested or evaluated through the development of the DER adoption forecasts.
MC: The 40th PLMA Conference will be a great opportunity for you as a presenter, but surely also as an attendee. Outside of the DER forecasting topic you’re discussing, what are some other topics you’re hoping to learn more about at the conference? What are some presentations you’re hoping to catch?
PM: I've been looking at sessions that will discuss DER integration or integration of DR and DER technologies in relation to creating load flexibility. In my opinion, it's interesting how the utility business model has evolved from demand response programs that basically turned off customer’s equipment and/or appliances to implementing less impactful tactics. For example, SMUD had a program, the air conditioning load management program, where we would send out a radio signal, and it would turn off a participating customer’s air conditioning system for an hour or so. We've gone from that on/off perspective to something that's more flexible. Can I change your thermostat settings by a couple few degrees to decrease AC load? Can I shift your battery operation from either storing excess PV energy or discharging during peak demand hours? This notion of load flexibility or flexible loads is one that I'm most interested in, so there are some sessions-- connected devices, bring your own devices, those kinds of discussions that I’m keenly interested in.
The ‘Load Flexibility as a Grid Resource’ workshop is one session that I'm most definitely going to be attending since this is a growing area of interest and my current focus. Something else that I’m interested in are any sessions that talk about rates, the intersection of rates, rates design, and distributed energy resource technology-- because utility rates and rate design are one of the key drivers of the adoption of distributed resource technologies, not only adoption of but also the operation of, and so given that rates are extremely important, any of the sessions that touch upon that intersection between rates, rate design, and distributive energy resource technologies are the sessions that I'm going to be interested in attending.
If you’re interested in hearing more about Partrick’s insights into load forecasting, be sure to find her at the 40th PLMA Conference taking place in St. Petersburg, Florida, from November 4 to 6. You can check out the agenda and register for the conference here.