Providing the Spark: Impact of financial incentives on battery electric vehicle adoption
Not Available
Clinton, Bentley C.↗
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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Incentive-Based Voltage Regulation in Distribution Networks
This paper considers distribution networks fea- turing distributed energy resources, and designs incentive-based mechanisms that allow the network operator and end-customers to pursue given operational and economic objectives, while concurrently ensuring that voltages are within prescribed limits. Two different network-customer coordination mechanisms that require different amounts of information shared between the network operator and end-customers are developed to identify a solution of a well-defined social-welfare maximization prob- lem. Notably, the signals broadcast by the network operator assume the connotation of prices/incentives that induce the end- customers to adjust the generated/consumed powers in order to avoid the violation of the voltage constraints. Stability of the proposed schemes is analytically established and numerically corroborated.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Financial incentives for reducing proliferation risks
This article submitted for publication to the Bulletin of Atomic Scientists explains the possible financial incentives for financial institutions and large integrators to reduce nuclear proliferation risks by including anti-proliferation measures in their due diligence and requiring their suppliers to meet heightened compliance standards. Because manufacturers of dual-use nuclear goods are diverse and numerous outreach is difficult. However, financial institutions and large integrators work with nearly all dual-use manufacturers, making financial institutions and integrators well-positioned to increase awareness of proliferation and trafficking risks throughout the nuclear supply chain
anti-proliferation↗
Leveraging Mixed-Strategy Gaming to Realize Incentive-Driven VNF Service Chain Provisioning in Broker-Based Elastic Optical Inter-Datacenter Networks
Not Available
Chen, Xiaoliang (ORCID:0000000278056237)↗
Game Theory Approaches for System-level Incentive Design
This report presents a generalized Stackelberg game framework for designing and evaluating financial incentives that enhance power system resilience through strategic deployment of distributed energy resources(DERs) under various contingencies. The proposed approach addresses the challenge of coordinating individual community investment decisions to meet system-wide resilience objectives. The framework is demonstrated in a three-community test system subjected to two transmission contingency scenarios: inter-community line failure (Case 1) and complete main grid disconnection (Case 2). In both cases, three incentive levels are compared: a Base case with no financial incentives, and low and high incentive cases. In Case 1, the Base case (no incentives) results in a total installed DER capacity of 217.2 MW, with no load shedding due to alternative routing, but community costs remain high. Increasing incentives raises DER deployment to 286.9 MW, lowers aggregate community costs by $22M annually, and completely avoids the need for costly new transmission line construction. In Case 2, the Base case results in 24.3 MWh of unserved load; introducing incentives eliminates all load shedding and ensures up to 89 MWh of battery storage is available for emergency reserve. These results demonstrate that targeted incentives can dramatically improve grid resilience and cost-effectiveness. The framework thus offers policymakers and system planners a robust tool to quantify and compare the effectiveness of incentive programs for multi-community transmission networks behavior, system resilience, and economic efficiency.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Dynamically Learning Incentives for Load Control
As electrical generation becomes more distributed and volatile, and loads become more uncertain, controllability of distributed energy resources (DERs), regardless of their ownership status, will be necessary for grid reliability. Grid operators lack direct control over end-users' grid interactions, such as energy usage, but incentives can influence behavior -- for example, an end-user that receives a grid-driven incentive may adjust their consumption or expose relevant control variables in response. A key challenge in studying such incentives is the lack of data about human behavior, which usually motivates strong assumptions, such as distributional assumptions on compliance or rational utility-maximization. In this paper, we propose a general incentive mechanism in the form of a constrained optimization problem -- our approach is distinguished from prior work by modeling human behavior (e.g., reactions to an incentive) as an arbitrary unknown function. We propose feedback-based optimization algorithms to solve this problem that each leverage different amounts of information and/or measurements. We show that each converges to an asymptotically stable incentive with (near)-optimality guarantees given mild assumptions on the problem. Finally, we evaluate our proposed techniques in voltage regulation simulations on standard test beds. We test a variety of settings, including those that break assumptions required for theoretical convergence (e.g., convexity, smoothness) to capture realistic settings. In this evaluation, our proposed algorithms are able to find near-optimal incentives even when the reaction to an incentive is modeled by a theoretically difficult (yet realistic) function.
demand response↗
Analyzing The Impacts of the Biogas-to-Electricity Purchase Incentives on Electric Vehicle Deployment with the MA3T Vehicle Choice Model
This analysis represents the biogas-to-electricity pathway under the Renewable Fuel Standard (RFS) as a point of purchase incentive and tests the impact of this incentive on EV deployment using a vehicle consumer choice model. The credit value generated under this policy was calculated in a number of scenarios based on electricity use of each power train choice on a yearly basis over the 15 year vehicle lifetime, accounting for the average electric vehicle miles travelled and vehicle efficiency, competition for biogas-derived electricity among electric vehicles (EVs), the RIN equivalence value and the time value of money. The credit value calculation in each of these scenarios is offered upfront as a point of purchase incentive for EVs using the Market Acceptance of Advanced Automotive Technologies (MA3T) vehicle choice model, which tracks sales, fleet size and energy use over time. The majority of the scenarios use a proposed RIN equivalence value, which increases the credit value as a way to explore the analysis space. Additional model runs show the relative impact of the equivalence value on EV deployment. The MA3T model output shows that a consumer incentive accelerates the deployment of EVs for all scenarios relative to the baseline (no policy) case. In the scenario modeled to represent the current biogas-to-electricity generation capacity (15 TWh/year) with a 5.24kWh/RIN equivalence value, the policy leads to an additional 1.4 million plug-in hybrid electric vehicles (PHEVs) and 3.5 million battery electric vehicles (BEVs) in 2025 beyond the no-policy case of 1.3 million PHEVs and 2.1 million BEVs when the full value of the credit is passed on to the consumer. In 2030, this increases to 2.4 million PHEVs and 7.3 million BEVs beyond the baseline. This larger impact on BEVs relative to PHEVs is due in part to the larger credit that BEVs receive in the model based on the greater percentage of electric vehicle miles traveled by BEVs relative to PHEVs. In this scenario 2025 also represents the last year in which biogas-derived electricity is able to fully supply the transportation electricity demand in the model. After 2025, the credit value declines on a per vehicle basis. At the same time a larger fraction of the credit may shift towards biogas producers in order to incent additional biogas production. The expanded 41 TWh/year biogas availability scenarios represent an increase beyond today s generation capacity and allow greater eRIN generation. With a 5.24kWh/RIN equivalence value, when all of the credit is directed towards reducing vehicle purchase prices, the 41 TWh/year biogas scenario results in 4.1 million additional PHEVs and 12.2 million additional BEVs on the road in 2030 beyond the baseline of 2.5 million PHEVs and 6.1 million BEVs. Under this expanded biogas capacity, biogas-derived electricity generation is able to fully supply electricity for a fleet of over 21 million EVs (15.6 million BEVs and 5.8 million PHEVs) on a yearly basis. In addition to assessing the full value credit scenarios described above, multiple scenarios were analyzed to determine the impact if only a fraction of the credit value was passed on to the consumer. In all of these cases, the EV deployment was scaled back as the fraction of the credit that was passed on to the consumer was reduced. These scenarios can be used to estimate the impact if the credit value is reduced in other ways as well, as demonstrated by the scenarios where the current (22.6 kWh/RIN) equivalence value was used. The EV deployment that results from an equivalence value of 22.6 kWh/RIN equivalence value is roughly equivalent to the EV deployment observed in the 25% case using the 5.24 kWh/RIN equivalence value. A higher equivalence value means that a smaller number of credits, and therefore value, is created for each kWh, and therefore the impact on EV deployment is reduced. This analysis shows several of the drivers that will impact eRIN generation and credit value, and tests the impact of an eRIN point of purchase incentive on EV deployment. This additional incentive can accelerate the deployment of EVs when it is used to reduce vehicle purchase prices. However, the ultimate impact of this policy, as modeled here, will be determined by future RIN prices, the extent to which eRIN credit value can be passed on to the consumer as a point of purchase incentive and the equivalence value.
09 BIOMASS FUELS↗
Rooftop solar incentives remain effective for low- and moderate-income adoption
Financial incentives for rooftop solar photovoltaic (PV) adoption have declined in the United States over time by policy design. Incentive phase-down can efficiently promote early adoption and avoid ineffective payments to late adopters. Furthermore, incentive phase-down may exclude low- and moderate-income (LMI) households from realizing the same financial benefits from PV adoption as high-income early adopters. Here, data from two state-level LMI PV incentive programs are analyzed to test whether incentives still drive PV adoption among LMI households. As a first order approximation, the analysis suggests that incentives drove adoption that would not otherwise have happened in about 80% of cases. To the extent that policymakers prioritize PV adoption equity as part of the emerging energy justice policy agenda, the results suggest that ongoing incentive support for LMI adoption may be merited.
14 SOLAR ENERGY↗
Regulatory Incentives and Disincentives for Utility Investments in Grid Modernization
Electric power is America's most capital-intensive industry, with more than $100 billion invested each year in energy infrastructure. Investment needs are likely to grow as electric utilities make power systems more reliable and resilient, deploy advanced digital technologies, and facilitate new services to meet some consumers' expectations for greater choice and control. But do current regulatory approaches provide the appropriate incentives for grid modernization investments? This report presents three perspectives: -Financial analyst Steve Kihm begins by explaining that any major investor-owned electric utility that wants to raise capital today can do so at a reasonable cost. The question is whether utility managers want to raise capital for grid modernization. Specifically, they look for investments that create the most value for their existing shareholders. In cases where grid modernization investments are not the best choice in terms of shareholder value, Kihm describes shareholder incentive mechanisms that regulators could consider to encourage such investments when they are in the public interest. -From an institutional perspective, Dr. Janice Beecher finds that the traditional rate-base/rate of return regulatory model provides powerful incentives for utilities to pursue investments, cost control, efficiency and even innovation, and it is well suited to the policy objectives of grid modernization. Prudence of grid modernization investments (fair returns) depends on careful evaluation of the specific asset, and any special incentives (bonus returns) should be used only if they promote economic efficiency consistent with the core goals of economic regulation. According to Beecher, realizing the promises of grid modernization depends on effective implementation of the traditional regulatory model and ratemaking tools to serve the public interest. -Conversely, former commissioner and clean energy consultant Ron Lehr says that rapid electric industry changes require a better alignment of utility investment incentives with changes challenging the electricity sector, emerging grid modernization options and benefits, and public policies. For example, investor-owned utilities typically have an incentive to make capital investments, but rarely to employ expense-based solutions, since utilities do not earn profits on expenses. Further, Lehr cites a variety of factors that stand in the way of creating well targeted and well aligned utility incentives, including litigated regulatory processes. These may be a poor choice for finding the right balance among competing interests, establishing rules of prospective application, justifying demonstrations of new technologies and approaches to meeting emerging consumer demands, and keeping pace with rapid change.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Beyond Widgets: Validated Systems Energy Savings and Utility Custom Incentive Program Systems Trends
Energy efficiency upgrades to buildings to date through avenues such as utility incentive programs have been largely limited to component-based products (e.g., lamps, RTUs). While some utilities do provide ‘custom’ incentive programs with whole building and system level technical assistance, these programs require deeper levels of analysis, resulting in higher program costs. This results in custom programs being restricted to utilities with greater resources, and are typically applied mainly to large or energy-intensive facilities, leaving much of the market without cost effective access and incentives for these solutions. In addition, with increasingly stringent energy codes, cost effective component-based solutions that achieve significant savings are dwindling. Integrated building systems (e.g., integrated façade, HVAC and/or lighting solutions) can deliver higher savings (Regnier et al. 2017) that translate into large sector-wide savings if deployed at the scale of these programs. However, systems application poses a number of challenges – energy savings assessments are inherently more complex and are not easily suited to the deemed measure model, and implementation of systems can be more disruptive. This paper presents the outcomes of a project to develop validated utility incentive program packages for three specific integrated building systems, in collaboration with ComEd, a consortium of California Public Owned Utilities (CA POUs) (Northern California Power Agency(NCPA) and the Southern California Public Power Authority(SCPPA)), and Xcel Energy (CO, MN). Previous work described the potential for energy savings of these systems at the individual and market level, early test findings for the task-ambient lighting system, and described the work products to develop utility incentive programs (Regnier et al. 2016). This paper presents validated end use energy savings of all three systems showing energy savings of ~20% for automated shading combined with daylight dimming (does not include light fixture retrofit savings); 30-46% for task-ambient lighting systems combined with plug load occupancy controls, depending on technology package and office building size (no daylight dimming impacts); and ~94% in the south-façade daylit zone for workstation specific lighting systems with daylight dimming (including lighting retrofit and task tuning). Using a U.S. Department of Energy (DOE) reference building model (DOE 2018), this translates to whole building savings of 2-5% (large-medium commercial), 12-23% (large-small commercial), and 13-15% (medium-large commercial) for these systems respectively. Early findings from the utilities in deploying these systems through their incentive programs indicate that deployment methods such as direct install programs might be best suited for these integrated systems. Further, early findings from a scoping study across custom utility programs and federal retrofit programs indicate that component level retrofits are still prevalent even in these programs, pointing towards an opportunity for deeper energy savings deployment. High performance retrofit case studies demonstrate that deeper energy savings is possible through integrated approaches. Market stakeholder interviews indicate however that there is generally a low level of awareness of the potential for energy savings of these three integrated systems.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Financial Incentives to Enable Clean Energy Deployment: Policy Overview and Good Practices
Financial incentives have been widely implemented by governments around the world to support scaled up deployment of renewable energy and energy efficiency technologies and practices. As of 2015, at least 48 countries have adopted financial incentives to support renewable energy and energy efficiency deployment. Broader clean energy strategies and plans provide a crucial foundation for financial incentives that often complement regulatory policies such as renewable energy targets, standards, and other mandates. This policy brief provides a primer on key financial incentive design elements, lessons from different country experiences, and curated support resources for more detailed and country-specific financial incentive design information.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Driving Investment in Wind Energy: An Introduction to Incentives and the Inflation Reduction Act [Slides]
In a webinar hosted by the U.S. Department of Energy's WINDExchange initiative, experts from the North Carolina Clean Energy Technology Center and the National Renewable Energy Laboratory introduce attendees to the key incentives supporting investment in wind energy deployment and manufacturing in the United States, as well as the role that the Inflation Reduction Act (IRA) plays in shaping those investments. Over the past few decades, incentives like the production tax credit and investment tax credit have supported the growth of wind energy deployment, while manufacturing-related incentives have helped scale up domestic manufacturing of wind energy components. With its passage in 2022, the IRA ushered in a new wave of investment in wind energy and other renewable technologies, as well as introducing new workforce requirements and equity provisions. This presentation explores the history and impact of major incentives, unpacks some of the complex provisions of the IRA, and highlights the ways federal incentives and policies will continue to shape the wind energy industry.
17 WIND ENERGY↗
Analysis of Manufacturer Plug-In Electric Vehicle Incentives
Vehicle manufacturers offer incentives in an attempt to encourage consumers to purchase or lease new vehicles. Similarly federal and local governments offer incentives to help build and maintain a market for plug-in electric vehicles. This paper analyzes manufacturer cash rebates and special lease offers and presents a comparison of plug-in electric vehicle incentives by manufacturer, technology, geographic area, and time period. How these manufacturer plug-in electric vehicle incentives relate to vehicle sales as well as state and federal government incentives is also investigated in this study.
33 ADVANCED PROPULSION SYSTEMS↗
Calculating Behind-the-Meter Energy Storage Incentives on an Avoided Cost Basis
Behind-the-meter (BTM) energy storage offers the potential for shared investment by utilities and their customers, in which both parties share in the costs and benefits of battery investment. Several utilities and a handful of states have begun providing incentives to help customers purchase BTM energy storage, and in exchange, operate that battery on behalf of the customer to realize grid benefits such as meeting peak capacity needs. But there is wide variation in the value and structure of these incentives, suggesting a lack of clarity on the value of BTM storage to the grid and to non-participating customers who fund the incentives for participating customers. This paper provides an objective framework for establishing BTM energy storage incentives based on the avoided cost of generation from a marginal, gas-fired peaking plant. It also conducts several sensitivity analyses to see how those avoided costs vary with emissions pricing, gas prices, plant heat rates, and utility capital structures. This work may be of use to utilities, regulators, and energy system stakeholders in providing a value-based framework for BTM incentive programs that can be used in the absence of policy guidance.
Twitchell, Jeremy B.↗
Portfolio-Scale Optimization of Customer Energy Efficiency Incentive and Marketing: Cooperative Research and Development Final Report, CRADA Number CRD-13-535
North East utility National Grid (NGrid) is developing a portfolio-scale application of OpenStudio designed to optimize incentive and marketing expenditures for their energy efficiency (EE) programs. NGrid wishes to leverage a combination of geographic information systems (GIS), public records, customer data, and content from the Building Component Library (BCL) to form a JavaScript Object Notation (JSON) input file that is consumed by an OpenStudio-based expert system for automated model generation. A baseline model for each customer building will be automatically tuned using electricity and gas consumption data, and a set of energy conservation measures (ECMs) associated with each NGrid incentive program will be applied to the model. The simulated energy performance and return on investment (ROI) will be compared with customer hurdle rates and available incentives to A) optimize the incentive required to overcome the customer hurdle rate and B) determine if marketing activity associated with the specific ECM is warranted for that particular customer. Repeated across their portfolio, this process will enable NGrid to substantially optimize their marketing and incentive expenditures, targeting those customers that will likely adopt and benefit from specific EE programs.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗