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The emerging “Utility of the Future” (UoF) paradigm underscores the importance of integrated approaches to utility planning. Regulators and utilities are rethinking the traditional utility business model in response to increasing penetration of distributed energy resources (DERs), decarbonization goals, essentially flat or even declining sales, new market participants, and end-use technology developments. The interactions of these factors with each other and with the utility are new and complex, and thus not well-suited for modeling exclusively with conventional planning tools.

Brattle has developed a new application of System Dynamics modeling to address the challenges of understanding and planning for a UoF environment. Our System Dynamics utility planning platform simulates the complex and interdependent aspects of DER technology improvements and adoption, regulatory policies, utility participation in new services, enhanced pricing, and resulting financial performance.

System Dynamics Modeling for the Utility Industry

Growing Need for Dynamic Planning Tools

The supply-driven, hierarchical structure of the electric industry of the past is being replaced with a bi-directional, network-interactive architecture featuring new participants.

New DERs and energy use management technologies are rapidly emerging at the “grid-edge,” the seam at the distribution (delivery-side) and retail (customer-side) business sectors of electric utilities. While DERs have the potential to provide substantial benefits, these innovative technologies also add complexity to system engineering, risk to financial planning, and they require innovations in resource planning, service design, and pricing.

To date, it has been customer decisions that have driven DER adoption, rather than electricity system planners using avoidable system marginal costs or aggregate resource requirements to find the best application of these technologies. Customer-driven adoption can result in DER development in locations and/or quantities that are not well correlated with system needs; it may even create new infrastructure needs if concentrated in areas with limited “hosting capacity.” Of course, DERs may provide system benefits if well-located, but in most jurisdictions the price signals or connection incentives are not yet in place to indicate those preferred locations.

This increase in customer-based energy management means that demand will become much more elastic (price-sensitive), and it also creates the dynamic behind the putative “death spiral:” DER adoption drives further DER adoption because customers are increasingly likely to self-supply as the utility spreads its fixed costs over a shrinking sales base, and rates rise. This draconian vision is almost certainly overstated, but it is nonetheless true that such feedback makes system planning and pricing for distribution assets and services (and in the long run, for bulk market generation) more difficult. It also shortens the potential useful life of conventional utility assets, making investments riskier.

A dynamic modeling framework is essential for understanding the interdependent aspects of DER technology adoption, utility system planning, and eventually the utility’s bottom line.

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Utilities are beginning to build more comprehensive UoF strategies in response to the changing nature of the electric industry. As a foundation for these strategies, they must develop insight into the economics and potential impacts of DERs on utility system needs, cost recovery, and appropriate service design.

Unfortunately, many aspects of the ongoing developments in technology and customer behavior are not yet well-understood. This can create a great deal of uncertainty and potentially conflicting opinions about the significance of UoF strategies. Even within the same organization, management may have differing viewpoints on the UoF outlook:

– Some may be concerned that the transition to the UoF will be mostly painful, in which the “death spiral” effect is strong and virtually inevitable.

– Another group may foresee exciting opportunities, either because they expect to expand the system considerably to support these DERs, or because they expect that the utility will participate directly in the new value processes.

– Others may believe the UoF concept is overblown and that utilities will continue to function mostly similar to the way they have for decades.

A key first step for organizational response is to reach consensus around the utility’s outlook and perceived need for new strategies. Understanding the range of possible outcomes and, as importantly, the paths that could lead there, will help utilities to sort out opinions and evaluate possible paths forward to find what approach is most promising for long-term growth and financial health.

Brattle uses System Dynamics modeling to facilitate a behavioral and managerial approach to the inherent complexity of the emerging UoF environment.

The Traditional Approach

Traditionally, utility strategic analysis has relied on scenario modeling, a largely linear approach that projects key events and models using known relationships. A familiar example is evaluating how changes in load growth or fuel prices could affect future plant needs, utilization, or system costs. In the UoF context, a scenario could involve modeling hypothetical renewable penetration levels (e.g., comparing 5%, 10%, or 20% rooftop solar photovoltaic (PV) penetration by a future date-certain) to assess the impacts on distribution equipment and on utility financials.

These kinds of scenario-based analyses can provide informative snapshots of possible future outcomes, but they ignore important dynamics of exactly how or why a utility might end up in a particular situation. They are about “what-if,” not “why” or “how,” and so they may overlook important feedbacks and interactions that would make higher or lower DER penetration more likely than the assumed conditions.

The scenario modeling approach falls short in UoF-related planning, where the path forward is not yet specified, but of pivotal importance and amenable to proactive management.

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System Dynamics Modeling for the Utility Industry

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There is little empirical history to extrapolate when projecting a UoF scenario. Simulating what could make a particular scenario occur is therefore as useful as studying what condition the utility would be in if it were to find itself in that scenario. Utility managers should consider not only their viability under possible end-states (e.g., under alternative DER penetration assumptions) but also the risks and opportunities, contingencies, and milestones along the paths that could result in those end-states, and whether there are ways of influencing the current path towards better outcomes. There are many ways to end up with “x%” renewables by a given date, so it is important to understand how to get there in the most effective fashion.

System Dynamics captures feedback effects and non-linear interactions to ensure that organizations are focused on anticipating and managing a path, and not just an end-state.

What is System Dynamics Modeling?

Dynamic simulations can reveal why a scenario could occur, not just what it would look like if it did.

At a high level, System Dynamics modeling can be thought of as creating detailed influence diagrams of what factors influence each other in a problem, and then animating these with variables that reflect the strength and timing of their interactions. This is an intuitive way of thinking about problems that can be developed iteratively from a fairly simple framework to a very sophisticated one. It is particularly useful for analyzing complex processes where multiple participants are involved and there are recognized feedbacks among their behaviors. Decision-makers often apply this modeling approach in situations where it is important to understand how an entire system changes over time, for example in the context of ecosystem management, business strategy development, or public policy decisions that affect various constituents. The emerging UoF environment has many of these characteristics: new participants and technologies, new kinds of behaviors motivated by a broader range of factors than just utility system economics, and many interactions.

How System Dynamics Works

– Causal loop diagrams represent relationships in a system– Stocks and flows are used to track movement of quantities or information through the system

– Stocks could be anything from balance sheet items, to MWs of a DER, to number of customers– Flows could include changes to exogenous factors (e.g., technology costs), growth or changing

classification of customers (e.g., solar PV adopters), etc.– Intuitive equations back-up the causal loop diagrams and stocks/flows

System Dynamics Modeling for the Utility Industry

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Brattle experts develop customized System Dynamics models, mapping out relationships among participants and the impacts of their decisions on the utility system:

– Typically start with one or a few issues that are particularly pressing for the utility or jurisdiction in question, such as rooftop solar penetration or electric vehicle (EV) adoption, then expand the model to accommodate additional, complementary issues (such as other DERs).

– Assign mathematical relationships and ranges around key variables so that they can be manipulated based on different worldviews. This allows managers to compare and contrast beliefs and to test alternative path-influencing strategies.

– Build time- or state-sensitive parameters into the model for behavioral and technology change feedbacks, such as learning curves that reflect adaptation to outcomes in prior periods.

We define the scope of a UoF System Dynamics model such that the closed system under study is comprehensive and detailed enough to explore the utility’s business decisions and policy concerns in the context of other factors outside its control. All key variables and behaviors that are codependent evolve together, in response to the strength of the connections between them and the prevailing external conditions (e.g., technology costs or wholesale market power prices).

System Dynamics starts with simple, intuitive, and straightforward relationships and uses those relationships to create a robust model of a complex social and economic system.

Brattle’s Modeling Approach and Industry Expertise

Brattle’s application of System Dynamics modeling to utilities and UoF issues is unique because we inform our models with deep understanding of the full panoply of analytic tools, regulatory practices, and market conditions facing the utility industry. Our experts understand the complementary relationship between System Dynamics modeling and traditional planning tools, and we design our models to be integrated with other standard industry analytical tools, such as load forecasting, production cost models of generation and transmission, revenue requirement and financial models, rate design frameworks, and resource benefit-cost analysis.

System Dynamics Modeling for the Utility Industry

System Dynamics Capabilities

– Provides insight into path dependencies– Tests robustness of investment and policy strategies across sensitivities– Identifies tipping points– Estimates the value of a portfolio of proposed investments over time

Brattle’s System Dynamics modeling can be run in real time with utility planners to inform strategic discussions and identify areas that warrant closer examination.

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This example illustrates a System Dynamics model of a distribution utility that is evaluating the potential impacts of a proliferation of customers adopting rooftop PV technology. The overall model is comprised of modules that capture customer segments, consumption patterns, drivers for PV adoption, rate design, and utility financials.

The component modules are fairly simple, but together they create a sophisticated interconnected system offering insights that none of them could provide alone. In Module 1, some customers choose to adopt PV. This leads to greater PV generation and lower net utility-supplied consumption in Module 2. Rates are then adjusted so that the utility meets its revenue requirement in Modules 4 and 5, under alternative rate designs that may be set as a tactical policy options to explore. As rates increase, PV becomes more attractive in Module 3, not only because of its economic benefits, but also because of a strengthening “social contagion” factor which drives further PV adoption in Module 1. Module 6 tracks how these shifts in growth, required or desired rates, and budgets for CapEx interact to affect profits and bond covenants, or similar metrics.

The model can be run to analyze impacts over long timeframes while capturing interactions between these modules continuously. Managers can explore the effects of “path-dependent” decisions through variation in the timing, type, or extent of utility’s role in DER development, shifting towards new rate designs, or altering decoupling and cost reallocation mechanisms. The model can produce standard financial outputs in spreadsheet format to help isolate and compare effects of decisions on the utility bottom line.

Example: Modeling PV Adoption Impacts on a Distribution Utility

System Dynamics Modeling for the Utility Industry

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Building a System Dynamics model encourages sharing of information and viewpoints across utility planning groups, and leads to new insights about the planning issues.

A System Dynamics model often starts with a fairly simple architecture and set of influences. However, it provides insight into the underlying complexities of the issue and requires gathering or sharing information across utility planning groups. For example, in regard to the PV adoption example, we have seen the planning analysis evolve to consider the following types of new questions:

Load forecasting:– What is the base case load forecast? What has it already assumed about DERs?– Is there a need for customer segmentation below the customer class? For instance, by income or type of housing?

Distribution planning:– Is there locational value of PV, requiring more insight into customers?– Is there a level of DER penetration at which the distribution system itself must be modified or reinforced?– What is the outlook for energy and capacity prices? When do DERs alter that?

Finance:– What are the short- and long-term impacts of DER adoption on key financial indicators (earnings, interest

coverage, ROE)?– Does DER adoption drive a different mix of assets (e.g., shorter-life assets)?

We typically facilitate discussion through a dashboard view of the model that allows decision-makers to adjust utility policy and customer behavior variables in real-time and react to outputs.

The screenshot that follows is an example model dashboard view illustrating how alternative rate designs can alter PV penetration. The dashboard focuses on a few graphs of important variables along with a tactical assortment of “sliders” that allow the driving factors to be varied up or down while the performance graphs change instantly.

In particular, this view demonstrates how sliding the Fixed Charge rate design control (1) towards more fixed charges creates a lower avoidable variable energy rate (2), leading to a longer payback for solar adopters (3) and resulting in reduced adoption (4). Several such views showing impacts on the system (such as what is happening to financials or to rates for non-participating customers) can be created very quickly once the model’s relationships are established and calibrated, and they respond in parallel to the changes studied in this view.

System Dynamics Modeling for the Utility Industry

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Utilities are currently facing many issues that are well-suited to System Dynamics modeling, which would also capture synergistic and other interdependent effects.

The above example illustrated a model built to investigate key relationships and drivers of PV adoption. Below is a list of other key issues and topics that utilities are currently facing and that Brattle’s System Dynamics model can provide new insights on:

Opportunities and risks driven by growth in DERs:– Modeling growth in Combined Heat and Power (CHP) or microturbine use for C&I customers– Testing the potential for PV Community Choice Aggregations– Understanding the integration of storage into solar deployments – Modeling energy efficiency potential and its impact on the utility’s business – Examining potential for EVs or electrification of heating loads– Changes in wholesale power markets as DERs affect load growth and load shape

Evolving business models and strategies:– Modeling participation by an unregulated subsidiary in DER development – Alternative approaches to Community Choice– Understanding the impacts on a utility of entering the EV charging station business

Regulatory and policy impacts:– Modeling of utility incentives for DERs and opportunities for utilities to improve finances by developing DERs – Evaluating whether proposed legislative or regulatory policies are internally consistent and likely to produce

attractive vs. imbalanced results, and how alternative implementation plans could improve results– Testing impacts of potential new rate designs – such as Time of Use (TOU) rates, demand charges, or Performance

Based Rates (PBR) – on participating vs. nonparticipating customers, utility finances, and attainment of policy goals

System Dynamics Modeling for the Utility Industry

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As new issues become relevant, the System Dynamics model platform can be expanded through the integration of new modules and variables.

One appealing aspect of incorporating System Dynamics modeling into your utility toolkit is that it can be expanded readily as new issues become relevant. Modules specific to those new areas can be developed and then used in isolation or grafted on to a larger integrated platform where they share variables. For example, the question of EV adoption and its resulting effect on utility sales is a good application, because many of its development factors involve strong feedbacks and lie outside of the electric utility business (arising in the automotive sector first). That industry is developing EVs for their own sake, but there are development feedbacks there that could strongly alter the pace of adoption, such as cost reductions and technology learning curves, consumer acceptance, growth in the variety of models, and public incentives.

The figure below provides a sketch of a module which begins to capture the inherent feedbacks behind understanding electric vehicle adoption. It mostly depicts the EVs from the automotive side, but there are many “chicken or the egg” questions with regard to vehicle charging that link the problem to electric utility planning: If more charging stations are built, will that spur more EV adoption? Or is the natural growth in EV adoption instead going to be the precursor to more charging stations? How will the patterns of charging affect utility costs, either for energy supply or for distribution system reinforcement? How much could TOU pricing for charging smooth out the potential spikes in load? When might there be enough EV growth to offset the load losses from rooftop PVs? Are the same customers likely to have both? These kinds of questions benefit from the systems dynamics approach, because of their tight interdependencies and feedbacks on each other.

System Dynamics Modeling for the Utility Industry

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Brattle’s System Dynamics approach can provide utility managers an invaluable framework for understanding how to navigate the road ahead.

We expect the UoF environment will develop in a manner that makes these kinds of cross-product, cross-market, and cross-customer interdependencies and feedbacks more prominent and more consequential. As a complement to existing utility planning tools, Brattle’s System Dynamics approach produces an integrated view without requiring brute force integration of vastly more detailed conventional models. In so doing, it provokes new understanding of elements of the problem that need to be better understood or need to be proactively managed early in the process in order to create a better chance of better long-run outcomes.

Contact

For more information on Brattle’s utility planning platform, please contact:

William P. Zarakas Principal, Boston

+1.617.864.7900

Bill.Zarakas@brattle.com

Brattle’s Retail Energy Practice

Brattle’s Retail Energy team has extensive experience developing benefit-cost analyses for next generation investments in smart grid, system reliability and resilience, and overall grid modernization, as well as for investments at the distribution system edge, such as electrification opportunities. We have also worked extensively on assessing business and financial models applicable to the evolving electricity market ecosystem, and are at the forefront of marginal cost and benefit analyses that are becoming increasingly important in determining efficient and equitable pricing constructs and incentives for DER compensation.

Our expertise is grounded in foundational principles of economics and finance, in order to better align load forecasting, rate design, and risk management with industry trends and developments.

For more information, please visit brattle.com.

System Dynamics Modeling for the Utility Industry