Trust but Verify: Report Supports Advanced Practices for Assessing Demand Flexibility Performance; Performance Assessments of Demand Flexibility from Grid-Interactive Efficient Buildings: Issues and Considerations
Steven R Schiller, Lisa C Schwartz, Sean Murphy, July 2020 (Lawrence Berkeley National Laboratory)
Abstract
This SEE Action Network report explains basic concepts and fundamental considerations for assessing the actual demand flexibility performance of buildings participating in demand flexibility programs and responding to time-varying retail rates. Demand flexibility is the capability of distributed energy resources (DERs) to adjust a building’s load profile across different timescales. Assessments determine the timing, location, quantity, and quality of grid services provided.
The results can be used for financial settlements and to improve performance of demand flexibility, support its consideration in resource potential studies and electricity system planning, and contribute to cost-effectiveness evaluations.
While practitioners and regulators regularly find opportunities to improve performance assessments of demand-related services, to a large degree current best practices are sufficient for basic service offerings as demand flexibility is implemented today.
However, advances in assessment practices will be required in a future with grid-interactive efficient buildings (GEBs) that provide continuous demand flexibility by integrating multiple DERs and flexibility modes (load shed, load shift, modulate, and generate). Example practices include using new baseline constructs—including whether baselines are even required for certain building flexibility modes or configurations, deploying more advanced metering and analytics, further developing cybersecurity standards, improving communication standards for increased interoperability, and establishing performance metrics and assessment procedures for load modulation as it is more fully defined and implemented.
This report provides information on prioritizing and designing performance assessment elements for demand flexibility programs and time-varying retail rates, assessment protocols, and research and development needs. Additional research sponsored by DOE’s Building Technologies Office1(link is external) offers more detailed technical information on assessing performance of demand flexibility, including definition of performance metrics.
• The Summary section provides major findings and recommendations.
• Section 1 describes GEBs and their characteristics, defines the concepts and purposes of demand flexibility assessments, summarizes current demand flexibility practices, and describes expected advancements both in capabilities of buildings to provide demand flexibility and in assessment practices.
• Section 2 presents five fundamental considerations associated with performance assessments of demand flexibility: (1) assessment objectives, (2) assessment boundaries, (3) performance metrics (both number and quality of metrics), (4) analysis methods (including baselines), and (5) assessment implementation requirements (for example, for data collection and privacy).
• Section 3 builds on these five fundamental considerations to describe development needs for assessments in a future with buildings providing more complex grid services.
The three areas of focus are: (1) developing new baseline constructs; (2) implementing assessments, with attention to additional metering needs, interoperability and communication standards, privacy, cybersecurity, and independent evaluators; and (3) assessing modulation as a demand flexibility service.
• Section 4 summarizes ways state and local governments and others can support implementing, standardizing, and enhancing assessments to support cost-effective services from demand flexibility.
• Appendix A summarizes our interviews with experts. Other appendices provide references and additional information on select topics—GEB characteristics, industry-standard measurement and verification approaches, and demand-side management strategies and grid services
Summary
Demand flexibility in buildings supports electricity system reliability and resilience, energy affordability, integration of new generating resources and loads, and other state and local energy goals. By contributing grid services needed for these purposes, demand flexibility can help advance a jurisdiction’s energy-related policies such as integrating energy efficiency with other distributed energy resources (DERs), hardening critical energy infrastructure, reducing peak demand, mitigating climate change, achieving renewable energy targets, and electrifying transportation and targeted building loads.
Performance assessments of demand flexibility determine the timing, location, quantity, and quality of grid services provided. Such assessments are common for financial settlements and have other important applications (Figure S-1). For utilities, regional grid operators, and utility regulators, assessments provide confirmation that buildings can reliably and consistently provide demand flexibility, critical to its broad acceptance as a grid resource. For building owners, operators, and occupants, assessments help optimize building performance, provide confidence in the benefits they will receive from demand flexibility (e.g., lower energy costs, payments for performance), and demonstrate acceptable non-energy impacts (e.g., building maintains comfort standards). Assessments also can reveal positive non-energy impacts, such as improved equipment performance through better building monitoring and controls and higher building resale value through lower net energy costs. In addition, comprehensive assessments provide state and local governments data they need to advance demand flexibility in support of their broader energy goals. In these ways, all stakeholders benefit from information that assessments provide for planning, designing, and implementing demand flexibility cost-efficiently.
DEMAND FLEXIBILITY
Demand flexibility is the capability of DERs to adjust a building’s load profile across different timescales. Demand flexibility (or load flexibility), integrated with energy efficiency, is the core characteristic of grid-interactive efficient buildings. The potential impacts are significant. Buildings account for 75% of U.S. electricity consumption and a comparable share of peak power demand. Source: U.S. Energy Information Administration 2019
This report synthesizes basic concepts and fundamental considerations and identifies development needs associated with assessing performance of individual buildings (residential, commercial, institutional) participating in dispatchable demand flexibility programs. Individual buildings are the building blocks for assessing multiple buildings aggregated for programs. Dispatchable demand flexibility programs provide financial incentives to consumers that change electricity demand in response to events called by a utility, regional grid operator, or DER aggregator for reliability or economic reasons.
The report includes some discussion of assessment methods for multiple buildings, known as impact evaluations, in the context of assessing time-varying retail rates that also encourage demand flexibility. In addition, performance assessments may be conducted for voluntary demand flexibility efforts encouraged by government entities or utilities during times of electricity system stress. While not the subject of this report, market evaluation—another type of assessment—can be a valuable tool for increasing adoption of demand flexibility, to assess progress toward market transformation and other market-related objectives.
In addition, the report identifies ways that state and local governments and other stakeholders can support meeting assessment needs in order to advance demand flexibility for reliable grid services. Government agencies, utilities, regional grid operators, DER aggregators, energy service providers, building system designers, and building owners, operators, and occupants can use the information in this report to improve their understanding of the role of assessments and as a starting point for defining assessment procedures and requirements, such as those associated with data collection and analysis.
Grid-interactive efficient buildings (GEBs) use smart technologies, including advanced controls3 and sensors, to actively manage DERs—energy efficiency, demand response, distributed generation and storage, and managed electric vehicle (EV) charging—to optimize energy use for grid services, occupant needs and preferences, cost reductions, and other purposes in a continuous and integrated way. In addition to providing ongoing reductions in energy use through energy efficiency, a building’s load profile can be adjusted across different timescales using four demand flexibility modes, individually or in combination (see Section 1.1 for definitions):
• Load shed
• Load shift
• Modulate
• Generate.
In the future, buildings will use multiple DERs and demand flexibility modes to respond to grid needs quickly, even within seconds or sub-seconds, potentially providing continuous demand flexibility. These changes will enable buildings to provide additional grid services, but will require advances in demand flexibility performance assessments.
Effective performance assessments use data to quantify the amount and quality of demand flexibility provided by a building with respect to predefined performance metrics. For example, assessments can indicate the average amount of load shed or shifted, in kilowatts (kW), over a given time period and how quickly a building’s shedding or shifting of load ramped up to provide a sustained change in demand. Beyond short-term uses of such information, such as for financial settlements, assessments support resource potential studies and electricity system planning, including evaluating cost-effectiveness of demand flexibility compared to other options for meeting generation and transmission and distribution (T&D) needs.4 Demand flexibility assessments also can adopt integrated or holistic approaches that take into account a jurisdiction’s related energy programs and policy goals.
Five fundamental considerations define a demand flexibility (and energy efficiency) assessment:
1. Assessment objectives–What information is the assessment intended to provide and how will the information be used?
2. Assessment boundary–At what level will performance be assessed—whole (individual) building or building system or equipment level, by DER, and/or by demand flexibility mode (e.g., load shed, load shift, modulate, or generate)? Or will the assessment boundary encompass multiple buildings, perhaps defined by their location (e.g., all buildings served by a single substation on the electric grid)?
3. Performance metrics–What metrics will be assessed and how will be they defined? What data will be required and at what temporal granularity (e.g., sub-seconds to hours for data measurement frequency) to calculate metric values?
4. Analysis methods–How will metrics be calculated and with what expectations for certainty? Will baselines be used and, if so, how will they be defined?
5. Assessment implementation requirements–What are the requirements with respect to data collection, privacy, cybersecurity, and reporting—particularly timing of reporting (e.g., in real time, within hours or days)? What entities will conduct the assessments? What is the duration of assessments (performance period covered)?
The most critical step in designing an assessment is determining appropriate performance metrics. Metrics are numbers, or other forms of information (e.g., categorical values), describing a process in a manner that indicates how well it is performing. Metrics provide a basis for making process improvements. For assessing demand flexibility performance in individual buildings, metrics may encompass four dimensions:
• Quantity and timing of demand flexibility provided (e.g., amount of demand reduction during defined period in kW or kilowatt-hours (kWh), the most common metric for demand flexibility today)
• Quality of demand flexibility provided (e.g., speed of achieving desired demand change or persistence of desired demand flexibility over long periods of time)
• Attribution of impacts to equipment, DER, flexibility mode, and/or building location (performance assessment boundary)5
o Individual equipment (e.g., chillers) and systems (e.g., lighting)
o Individual DERs
o Individual flexibility modes o Location of impacts on the electricity grid
• Impacts on owners and occupants, including energy cost savings and non-energy impacts such as comfort, health, and productivity.
For some demand flexibility modes and grid services provided, performance metrics may simply be based on direct measurements, such as the amount of electricity provided to the grid from a building with on-site generation. Alternatively, performance metrics may be based on whether the building’s demand for electricity is within desired parameters, such as a desired load shape (e.g., lower demand during certain hours and higher demand during other hours).
But for most types of demand flexibility and grid services provided, direct measurements must be compared to other quantities—typically a counterfactual scenario (commonly referred to as the baseline)—to understand the quantity of grid services provided. For example, the amount of load shed during a specific time period is equal to the difference between the actual load of the building and a counterfactual scenario, defined as the load that would have occurred in the absence of the subject utility demand flexibility program or time-varying retail rate. Defining and determining counterfactual scenarios for most metrics is a major component of assessment analytics, particularly for dispatchable demand flexibility programs which typically rely on historical data for building electricity demand to define baselines. In contrast, the counterfactual scenario for time-varying retail rates, such as time-of-use (TOU) pricing, can be defined by a control group6 without attribution for individual building performance, because no settlement process is involved for individual participants. Figure S-2 presents a hierarchy of analysis methods for demand flexibility assessments.
Impacts such as demand (kW) change and energy (kWh) savings, and thus metrics, are quantified in the same manner regardless of the state’s electricity market structure—vertically integrated utilities or centrally organized wholesale electricity markets (or a combination). Conceptually, all performance metrics may be assessed at the whole building or individual system or equipment level, or for all buildings participating in a demand flexibility program or time-varying retail rate. Performance metrics may differentiate between impacts associated with energy efficiency or the four modes of demand flexibility (load shed, load shift, modulate, and generate) and which DERs are providing such flexibility. Still, metrics of greatest interest are associated with demand flexibility performance of a whole building or an aggregation of buildings.
Demand flexibility assessments can build on existing approaches for performance verification, such as demand response measurement and verification (M&V) protocols for utility programs and wholesale electricity markets. The fundamentals of assessing demand reductions from energy efficiency, load shed, and generation have been in place for decades, are well-established, and can serve as the basis for load shifting and modulation assessments. Particularly applicable are advanced M&V practices that have adopted the use of smart meter data and automated analytics. For example, demand flexibility assessments can adapt existing practices related to metering and data quality standards, measurement protocols, counterfactual scenario definitions, and use of independent third parties. Further, at least as a starting point, assessments can take advantage of approaches to data privacy and cybersecurity, as well as installation of building automation systems (BAS) and advanced metering infrastructure (AMI). Where deployed, BAS and AMI support data collection and sharing and may significantly ease implementation and assessment of demand flexibility.
Advanced M&V (also called M&V 2.0) can help realize the promise of buildings as grid assets in two important ways. First, it leverages standardized data formats and the finer timescale of smart meter data. Second, automated analytics enable processing of larger volumes of data at high speeds to support fast-response modulation implementation and assessments. Combined with conventional impact evaluations, used regularly to assess load shedding associated with time-varying rates, a strong base of existing practices can be drawn upon to assess demand flexibility as currently implemented.
In order to meet the full potential of GEBs to integrate multiple DERs and flexibility modes, however, existing assessment approaches will need to be modified or new approaches will need to be developed to assess demand flexibility performance—for example, in the context of:
• Buildings providing continuous or near-continuous demand flexibility
• Engagement of multiple demand flexibility modes in an integrated manner
• Load modulation in sub-seconds to seconds, autonomously providing grid stability and balancing services
• Increased use of combinations of DERs, such as on-site generation to charge batteries in concert with load shed and shift
• Integrated whole-building system approaches to providing grid services, as well as demand flexibility at the individual end-use level or individual device level
• Managed EV charging
• Reducing complexity associated with multiple DERs, demand flexibility modes, and program and rate designs by providing simplified approaches for consumers and other market participants.
These examples imply more sophisticated assessments of demand flexibility.
8
Table S-1 summarizes five drivers of development needs for future demand flexibility assessments and three priority development needs with respect to baseline constructs, implementation practices and infrastructure, and modulation.
New assessment approaches may best take the form of standardized protocols that can reduce costs and increase consistency and credibility of assessment findings. Such approaches likely will be based on frameworks that emphasize reasonable costs for assessing performance by considering meter-based analyses as an integral element of program implementation and resource planning. Inevitably, methods will emphasize consistent, simplified tracking and reporting that enables continuous and rapid feedback and opportunities for improvement in demand flexibility performance.
Research, development, and demonstration (RD&D) is required to address these needs. State and local governments can support such RD&D in several ways:
• Lead by example by conducting assessments of demand flexibility in their own public buildings.
• Encourage or require performance assessments for buildings participating in demand flexibility programs they operate or regulate, and for buildings on time-varying retail rates.
• Catalog and consider adopting best assessment practices, consistent with the jurisdiction’s policies and regulations.
• Share and support advances in assessment practices related to performance metrics, analysis methods, baselines, and implementation approaches for determining demand flexibility impacts.
• Disseminate assessment results and the metrics, data, analysis methods, and implementation strategies used. Leveraging and sharing data results in increased understanding and continuous improvement of demand flexibility performance, informs DER potential studies and electricity system planning based on verified performance, and secures confidence in performance assessment practices and thus demand flexibility as a grid resource, all in the most cost-effective manner.
Public utility commissions (PUCs) and state energy offices also can play an important role by providing guidance on performance metrics and standardized protocols for verifying buildings’ demand flexibility in response to grid signals in real time, as well as over longer time periods. Standardization can reduce costs and increase consistency and credibility of assessment findings. States can take these actions in collaboration with utilities and regional grid operators, which write the assessment rules for verifying demand flexibility performance of program participants.
Other opportunities, including those for PUCs and state energy offices, include updating assessment strategies, such as baselines and qualifications criteria for entities that conduct and report assessment results, and encouraging development and adoption of standard, cost-efficient protocols for communication, data privacy, and cybersecurity. Additional actions include improving access to data necessary to conduct assessments. That may include facilitating investments in metering infrastructure, such as AMI and BAS with real-time measurement capability and built-in, two-way communication capability consistent with established standards and protocols for interoperability, cybersecurity, and data privacy.
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