Adequacy assessment methodologies have historically focused on assessing generation outages during peak demand across various economic load growth projections. However, growth in renewables, energy limited resources, end-use electrification, and the increasing adoption of distributed resources has increased the variability and uncertainty of future operating conditions, driven by weather and behavioral factors. Hence, assessments need to systematically account for the range of variability and uncertainty of each factor in determining system adequacy which is typically achieved by the construction of appropriate scenarios.
While the approach to selecting scenarios for analysis comprises both traditional adequacy and stress testing scenarios, this overview covers scenario generation specifically for traditional resource adequacy assessments (not stress testing) and provides guidelines across a wide range of adequacy components. This overview focuses on the development of a structured, repeatable, and transparent approach to making choices in the design of adequacy assessments.
Even though scenario generation approaches are disaggregated by component in this overview, it is necessary for planners to ensure that selected modeling approaches by component are aligned and consistent within in the global RA framework applied. Further details on scenario selection guidance, and scenario development for stress tests can be found in the Scenario Generation for Adequacy Studies document.
For each component impacting scenario generation, approaches are summarized by level of fidelity as summarized below.
LEVEL I
Basic: These scenario selection approaches are generally the least extensive, often limited to a single view of how the future emerges. Level I approaches are generally acceptable for studies with a limited scope, when the influencing factor is relatively certain and has low materiality on study outcomes, when the influencing factor is subject to external guidance, or when factors are determined exogenously.
LEVEL II
Intermediate: These factors are important to consider because of the level of impact that a change in foreseen conditions would have on the outcome of the adequacy assessment. A more detailed treatment may be warranted including the assessment of alternate parameterizations of a model or to represent a specific factor with a higher level of detail than would be otherwise warranted.
LEVEL III
Advanced: these modeling approaches systematically ensure the highest fidelity representation of factors influencing scenario generation. Level III models may be required for systems when a given factor’s influence is significantly material to adequacy outcomes. These approaches are generally the most data intensive and may not always be needed or justified, depending on a specific system’s characteristics.
SCOPE AND RESOLUTION
Geographical scope and resolution refer to the geographical area and granularity captured in adequacy studies, as well as considerations relating to the temporal horizon and resolution. In reality, these two choices are interrelated; smaller scope allows the potential for higher resolution and vice versa.
The geographical scope covered by adequacy studies may be set up in a variety of ways, depending on the decision being informed. Selection of an appropriate geography may be informed by the risks related to dependence on exchange of power with neighboring entities. In self-contained regions or entities, a smaller scope may be envisaged. In cases with significant trade and those vulnerable to co-incident peak demand or wide area weather fronts exerting stress on the system, a wider area may be warranted.
Studies that model larger geographical areas can capture in greater detail inter-area exchanges. Advanced models include the widest geographical scope, often conducting continental-scale modeling, paired with state or country level resolution.
Level I:
Level I approaches focus on capturing the geographical scope covered by a utility, balancing area, or a country. Inter-area exchanges are not, or not fully, accounted for in Level I approaches.
Level II:
Level II approaches model reliability regions. regions and the trade within the sub regions. Examples of this include ISO-wide adequacy assessments for regions such as PJM in the US.
Level III:
Advanced models include the widest geographical scope comprising multiple countries or regions, often conducting continental-scale modeling. The European Resource Adequacy Assessment conducted by ENTSO-E models most countries in Europe (as well as other non-European interconnected regions) and is an example of an RA model employing a Level III approach in the Geographical Scope category. Overall, advanced approaches enable planners to capture the impact of wide area climate events on adequacy.
The choice of geographical resolution in resource adequacy studies is directly related to the level of representation of intra-area transmission constraints and geographical scope. Decisions regarding geographical resolution do not require differentiation for different study timeframes.
Level I:
These studies represent each region as a copper plate, where it is assumed that intra-region flows are never constrained. Regions may represent a country, a state, or a balancing authority. Depending on the specific process requirements, these may be suitable for long range integrated resource plans or where downstream activities are responsible for assuring deliverability, or where no trade is modelled.
Level II:
These approaches recognize transmission constraints between zones, which are transmission constrained areas within regions, with a copper plate assumption made for intra-zone flows. Examples of this are the zonal approach taken by New York ISO in their adequacy assessments related to the NY capacity market.
Level III:
The highest fidelity approach to capturing geographical resolution in adequacy studies is to use a nodal representation of the area under study. This approach is rarely a requirement but should be considered in systems that anticipate significant congestion and consequently, generation curtailment
Study horizons should align with the information required to take a consequent decision. Long lead time investment needs studies that have further horizon, often stretching decades into the future. Meanwhile immediate decisions relating to outage timing or fuel purchases may only require a horizon of several days ahead.
When the choice of study horizon does not compromise modeling detail, studies with longer lookaheads (wider horizons) can capture more information regarding new unit interconnection, as well as decommissioning, along with associated adequacy challenges.
Short Term
Level I:
In the short term, Level I models examine seasons up to 1 year ahead, informing the need for fuel procurement, maintenance scheduling, conservation and trade.
Level II:
Level II models consider one to three years ahead and is used to inform the same decisions as Level 1, but on a longer timeframe, as well as the need to secure emergency generation and the design of demand side tariffs.
Level III:
Most Level III approaches look from 1 to 5 years ahead and are used to inform systems related to the same as the previous two levels as well as the delivery risk associated with investment and retirement decisions taken.
Mid & Long Term
Level I:
Considers a 5-to-10-year horizon and is most suitable for mothballing, retirement decisions, demand flexibility product design and investment decisions in assets not longer than 5 years (e.g. CCGTs).
Level II:
10-to-20-year time frame and is most suitable for investments in longer lead time resources such as inter-ties, pumped hydro storage and nuclear power plant.
Level III:
These approaches consider a longer term 10 – 20-year horizon and are suitable to inform and characterize the need to develop new technologies and to understand long term and structural changes in demand over the lifetime of an existing fleet.
Assessments face a choice of how granular a time step to represent in a model. Higher fidelity models capture more hours in the year, while lower fidelity models focus on those hours where loss of load risk has been highest historically.
As generation mixes change to incorporate increasing levels of wind and solar power, as well as energy storage, there has been a growing need to move from Level I towards Level III approaches.
Level I:
Level I approaches focus only model seasonal peaks. These are more suitable for systems facing little to no variable generation, energy limited resources or extreme weather.
Level II:
Level II Approaches model daily peaks hours and while an improvement on L1, are similarly only suitable for systems with immaterial wind, solar PV and batteries. This approach has a greater chance of identifying risk associated with extreme weather than L1, but not as good as L3.
Level III:
Level III approaches represent a full year at an hourly resolution. This enables a higher fidelity representation of units that have time-dependent constraints, such as energy storage.
ENERGY AND GHG POLICY AND CLIMATE
Climate and policy scenarios refer to the variability in public policy and climate pathways that may affect the bulk power system during the period under assessment.
Energy and GHG emission policy can impact adequacy by setting an environment that is favorable to the operation of certain types of generation assets, and unfavorable to others. Methodologies for accounting for energy and GHG policy differ depending on whether studies are long, or mid and short term.
In the case of energy and emissions policies, unless significant change is foreseen across the horizon, prevailing or business as usual policies are sufficient. However, in cases where such policies are likely to result in potentially different outcomes in terms of demand, supply, storage, fuel or interconnection, these alternatives should be represented to the extent that they are likely foreseeable and material.
Short & Mid Term
Level I:
In the mid- and short-term horizon, Level I considers business-as-usual approaches if significant change is not foreseen across the horizon.
Level II & III:
These approaches account for policy changes that are committed to that impact the study horizon.
Long Term
Level I:
Basic scenario generation approaches assume that existing policy prevails over the study horizon.
Level II & III:
These approaches account for multiple plausible policies in the developed scenarios.
Climate can have multiple impacts on resource adequacy; it not only directly impacts outputs from hydro, wind, and solar units, but also (strongly) impacts customer load, as well as generator outages and fuel delivery. Methodologies for accounting for climate differ depending on whether studies are long, or mid and short term.
Level I:
A basic approach for systems that do not expect to experience any significant deviation in climate from the historical record over the assessment period is to consider historical weather years without adjustment for climate.
Level II:
Intermediate models consider historical weather years without adjustment for climate. The climate adjusted scenario may be adjusted to a single ‘most plausible’ trajectory.
Level III:
Advanced approaches include the impact of a range of scenarios following alternate emissions pathways. One such approach is to follow the Shared Socioeconomic Pathways (SSPs) defined through the most recent Intergovernmental Panel on Climate Change assessment report.
CUSTOMER CHOICES
Electricity end use factors represent the influence of load consumption patterns on scenario generation.
Decisions regarding load growth representations do not require differentiation for different study timeframes.
Level I:
Level I approaches for representing load growth rely on a single load (timeseries) forecast. This is suitable in cases where no structural change and there is little feasible uncertainty in the demand.
Level II:
Level II approaches expand on Level I by scaling load up and down, while maintaining existing load shapes, by a given set of positive or negative percentage points to represent the influence of economic factors on load growth. This is suitable in cases where there is no structural change in demand but some uncertainty relating to demand growth exists.
Level III:
Level III approaches are required when structural changes in demand are anticipated. In this case, a bottom-up approach to constructing a load forecast may be required for major demand categories. Examples of the constituent categories which may require individual treatment are heating and cooling, electric transportation and industrial end use.
Decisions regarding electric heating and cooling load representations do not require differentiation for different study timeframes.
Level I:
As for global load growth, Level I approaches rely on a single profile representing heating and cooling loads.
Level II & III:
Level II approaches build on Level I by considering multiple electrified heating and cooling adoption profiles. These approaches may also discern between how end use tariffs, such as time-of-use, demand charge, or adoption of real-time-price-correlated tariffs, can impact heating and cooling load profiles
Decisions regarding electric transportation representations do not require differentiation for different study timeframes.
Level I:
Level I approaches rely on a single electric transportation adoption profile.
Level II & III:
Level II approaches rely on multiple electric transportation adoption profiles. These approaches may also consider the impact of customer tariffs incentivizing electric vehicle charging shifting (such as time-of-use tariffs) on global vehicle load shapes.
Decisions regarding industrial end use representations do not require differentiation for different study timeframes.
Level I:
Industrial electric demand is not explicitly considered in Level I assumptions, rather as part of the main load forecast. This is partly driven by the fact that it has not been necessary to do so in the past (and still may not be needed) in many systems.
Level II & III:
Level II assumptions may consider a single industrial electrification trajectory and the resulting distinct load profile. These approaches may consider multiple possible industrial electrification trajectories and flexibilities driven by a set of different decarbonization pathways – e.g. hydrogen electrolysis with hourly additionality rules.
Decisions regarding DER representations do not require differentiation for different study timeframes.
Level I:
A basic approach to DER adoption is to forecast one level of adoption, a related production profile (perhaps cognizant of incentives) and to net it from demand. This is suitable in cases where DER adoption uncertainty is low.
Level II & III:
Level II approaches treat DER similarly to bulk system resource adoptions, considering DERs in the same manner as supply-side assets. In this level multiple adoption trajectories may be considered.
Decisions regarding energy efficiency representations do not require differentiation for different study timeframes.
Level I:
Basic consideration of energy efficiency in scenario generation (Level I approaches) involves a single profile capturing the forecasted impact of energy efficiency schemes on load profiles.
Level II & III:
These approaches consider a range of profiles forecasting the influence of energy efficiency schemes on demand, instead of one, based on the potential for multiple trajectories to appear over the assessment period (e.g. building heat retention forecasts).
ELECTRICITY SUPPLY
Electricity supply factors represent the influence of supply-side generation assets on scenario generation. After demand, variations in the availability and performance of supply and storage resources are the next most material impact on adequacy outcomes. Representations of electricity supply factors can vary depending on the timeframe of the resource adequacy study. The following set of factors relating to supply-side units must be considered in scenario generation.
Electricity supply factors represent the influence of supply-side generation assets on scenario generation. Representations of electricity supply factors can vary depending on the timeframe of the resource adequacy study.
Short Term
Level I:
Level I methods generate installed capacity scenarios based on a single profile of available capacity values. This is suitable when short term uncertainty is low, which is a large number of cases.
Level II:
Level II scenario selection reflects the inclusion of a range of maintenance profiles that may be expected across the operating horizon.
Level III:
In cases where supply assets are anticipated to be in a mothballed state, advanced analysis to consider the return or exclusion of those resources to service is recommended.
Mid &Long Term
Level I:
The basic scenario selection approaches for accounting for installed capacity consider declared or intended future capacity additions and retirements in forecasts. This is suitable in cases, where no deviation from the set of forecasted supply resources is possible, with high certainty
Level II:
These approaches evaluate alternate sets of scenarios considering the potential for accelerated retirement of aging plant or delayed completion of assets under development. This approach is recommended for systems undergoing significant transition in the generation fleet over the assessment period.
Level III:
Advanced approaches iterate between adequacy studies and economic viability assessments for generating plant, removing plant in each iteration that appear to be at high risk of mothballing or retirement. This approach is suitable in cases where the risk of uneconomic operating conditions for marginal assets is likely.
ELECTRICITY NETWORKS
When it comes to scenario selection, the dominant factor in adequacy assessments is the degree to which external trade is considered. For self-contained systems or systems with fixed trade, this is more straight forward. For systems interconnected with many other systems upon who there is interdependence, representation of those links becomes a question of scenario selection. The table below gives an overview of the options to represent electricity networks in scenarios.
Decisions regarding electricity network representations do not need to be differentiated as a function of study timeframes.
Level I:
Level I methods account for external transmission through the inclusion of a single set of (projected) inter-area sales and purchases or a single set of interties.
Level II:
Level II scenario selection evaluates adequacy under a range of intertie capacities, typically based on anticipated build outs of new connections. This is suitable for systems where the interconnection capacity is anticipated to change over time.
Level III:
Level III requires the definition of a stress test scenario which may focus on the performance of a system during a period of elevated stress due to high demand or low supply, as well as variations based on available inter-area transmission capacity.
FUELS
Two key fuel-related aspects are relevant at the resource adequacy level: fuel availability and fuel prices. The table below gives an overview of the consideration of fuel-related aspects in the different approaches.
The assumption that fuel is never constrained has been acceptable in many regions in the past and may still be in certain regions. However, more and more regions, particularly importing regions, have seen fuel constraints over the past years (often related to fossil gas delivery). As such, Level II and III methods are increasingly necessary to appropriately capture fuel availability in resource adequacy scenarios.
Decisions regarding fuel availability representations do not require differentiation depending on study timeframes.
Level I:
Basic scenario generation methods do not consider the impact of fuel availability.
Level II:
Level II approaches include fuel import constraints.
Level III:
Level III approaches not only include fuel import constraints, but also scenarios where pipeline infrastructure (or other delivery infrastructure) is lost.
While fuel prices may appear to be more of a matter of economic performance, in systems with significant penetrations of energy limited storage, such as batteries, economic factors may influence the state of charge of such units. As a result, this factor may be material in certain systems and to varying degrees.
Decisions regarding fuel price representations do not require differentiation depending on study timeframes.
Level I:
Basic methods for accounting for fuel prices in resource adequacy scenarios consider a single, static (often annual) price per fuel. This assumption may not be acceptable in regions seeing (or expecting) sufficiently significant fuel price fluctuations to impact generator outputs.
Level II:
A more advanced approach may be required in regions seeing (or expecting) sufficiently significant fuel price fluctuations to impact mothballing or storage dispatch in a material manner. Such approaches may consider alternative seasonal fuel scenarios, annual fuel profiles or fuel price shocks price fluctuations.
Level III:
Advanced methods consider multiple price forecasts at, at least, a seasonal resolution.
Deliverables under EPRI’s Resource Adequacy for a Decarbonized Future initiative
Reports
Metrics and Criteria for Resource Adequacy (3002023230)
Resource Adequacy Scenario Selection Guide (3002027829)
Modeling New and Existing Technologies and System Components in Resource Adequacy (3002027830)
Data Collection Guide (3002027831)
Resource Adequacy Assessment Tool Guide (3002027832)
Resource Adequacy Gap Assessment (3002027833)
Tools
Resource Adequacy Viewer Tool (RAVT) (3002026144)
Resource Adequacy Fuel Insufficiency Screening Tool (RAFIST) (3002028168)
Case Studies
EPRI Resource Adequacy for a Decarbonized Future Case Study: Western US (3002027834)
EPRI Resource Adequacy for a Decarbonized Future Case Study: Northeastern US and Canada (3002027835)
EPRI Resource Adequacy for a Decarbonized Future Case Study: Southwest Power Pool (3002027836)
EPRI Resource Adequacy for a Decarbonized Future Case Study: Midcontinent (3002027837)
EPRI Resource Adequacy for a Decarbonized Future Case Study: Texas (3002027838)
EPRI Resource Adequacy for a Decarbonized Future Case Study: Southeastern US (3002027839)