SEARCH · Search NASA

Results for “utilities policy”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 55 records · Page 3

All sources NASA NTRS DOE OSTI

DOE OSTI2023

A game-theoretic approach to nuclear fuel cycle transition analysis under uncertainty

We present a novel methodology for optimizing nuclear fuel cycle transitions that incorporates a game-theoretic approach and captures interactions among multiple decision makers. The methodology is demonstrated using a two-person sequential game with uncertainty, where the two players represent a policy maker and an electric utility company, though the method generalizes to any number and type of individual decision making entities. Coupled with a sophisticated nuclear fuel cycle simulator, rich transition scenarios may be analyzed to identify robust transition strategies. These strategies explicitly treat uncertainties using a stochastic programming approach, devising optimal near-term hedging strategies that simultaneously consider all possible states of the world, maintaining flexibility to allow for intelligent recourse decisions once uncertainties are resolved. In the demonstration game, reactor technology and fuel cycle scheme adopted by the electric utility are shown to depend on both the policy maker’s decisions and the distributions over uncertain technological and economic outcomes.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2022

The Policy Mullet: Good Intentions in the Front, Bad Policy in the Back

To achieve important policy goals like decarbonization, energy efficiency, and social justice, it is important to translate high-level policy into operational practice. Establishing sustainable purchasing goals has been one important part of this translation. However, not all sustainable purchasing policies are equally effective for organizations. In this study, we analyze sustainable purchasing policies collected from 30 public-sector organizations. We discuss a theoretical framework of optimal policy language and use that framework to evaluate the policies we collected. We believe that an ideal sustainable purchasing policy can increase the likelihood of implementation success by providing more product-specific guidance, giving authority to procurement staff, setting performance targets, and requiring reporting to account for progress. In our review of public sector sustainable purchasing policies, we found that policy language is less than ideal when measured against the framework. Based on our findings, we highlight the best practice language organizations can use in their sustainable purchasing policies to meet sustainability goals. While there is more work needed to inform best practices with sustainable purchasing policies, we recommend that organizations utilize existing frameworks when developing a sustainable purchasing policy to encourage better implementation.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2021

Next-Cycle Optimal Fuel Control for Cycle-to-Cycle Variability Reduction in EGR-Diluted Combustion

In this simulation study, cycle-to-cycle fuel control was used to reduce CCV by injecting additional fuel in operating conditions with sporadic misfires and partial burns. An optimal control policy was proposed that utilizes 1) a physics-based model that tracks in-cylinder gas composition and 2) a one-step-ahead prediction of the combustion efficiency based on a kernel density estimator. The optimal solution, however, presents a tradeoff between the reduction in combustion CCV and the increase in fuel injection quantity required to stabilize the charge. Such a tradeoff can be ad- just by a single parameter embedded in the cost function.

Maldonado, BryanP. [Oak Ridge National Lab. (ORNL)↗

DOE OSTI2025

Decentralized Distributed Proximal Policy Optimization (DD-PPO) for High Performance Computing Scheduling on Multi-User Systems

Resource allocation in High Performance Computing (HPC) environments presents a complex and multifaceted challenge for job scheduling algorithms. Beyond the efficient allocation of system resources, schedulers must account for and optimize multiple performance metrics, including job wait time and system throughput. Traditional heuristic-based scheduling algorithms increasingly struggle and lack the efficiency needed to meet the demands and address the complexity and scale of modern HPC systems. Consequently, recent research efforts have focused on leveraging advancements in Artificial Intelligence (AI) and Deep Learning (DL), particularly Reinforcement Learning (RL), to develop more adaptable and intelligent scheduling strategies. Previous RL-based scheduling approaches have explored a range of algorithms, from Deep Q-Networks (DQN) to Proximal Policy Optimization (PPO), and more recently, hybrid methods that integrate Graph Neural Networks (GNNs) with RL techniques. However, a common limitation across these methods is their reliance on relatively small datasets, with few methods being evaluated using large-scale, multi-million-job trace datasets representative of real-world HPC workloads. Moreover, existing RL schedulers face scalability issues due to centralized policy updates, which hinder training efficiency and performance when applied to large datasets. This study introduces a novel RL-based scheduler utilizing Decentralized Distributed Proximal Policy Optimization (DD-PPO) algorithm, which supports large-scale distributed training across multiple workers without requiring parameter synchronization at every step. By eliminating reliance on centralized updates to a shared policy, the DD-PPO scheduler enhances scalability, training efficiency, and sample utilization. Experimental validation using a large real-world dataset containing over 11.5 million job traces collected from petascale HPC systems over six years assesses the influence of dataset scale on training effectiveness and compares DD-PPO performance to traditional and advanced scheduling approaches. The experimental results demonstrate improved scheduling performance in comparison to both heuristic-based schedulers and existing RL-based scheduling algorithms.

AI↗

DOE OSTI2025

Rooftop Solar Deployment, Potential Electricity Rate Impacts, and the Timing of Revisions to State Net Metering Policy

Most U.S. states require utilities to credit residential solar photovoltaic (PV) output at the retail electricity rate, a structure known as net metering. However, 12 states have replaced net metering with alternative rate structures that reduce PV adopter bill savings. The share of households living in states that require net metering fell from around 84% in 2014 to around 57% by the end of 2023. Proponents of net metering revisions have argued that net metering can affect the electricity rates of customers without PV. This report analyzes the relationships between state PV deployment levels, potential electricity rate impacts on PV nonadopters, and the timing of revisions to net metering policy.

14 SOLAR ENERGY↗

DOE OSTI2023

Renewable Thermal Energy Systems: Systemic Challenges and Transformational Policies (Report 2)

Two important challenges for RTES are the need for significant further innovation and deployment, particularly in the United States. In the face of continued success of other renewable energy technologies, such as solar photovoltaics (PV) and land-based wind energy for electricity, it is worthwhile to evaluate the current state of select RTES technologies in the context of technology innovation systems and energy transitions. This report marks a departure from the existing body of research we are aware of and have contributed to relating to RTES applications for industrial process heat in the United States. Our objectives for this report are fourfold: 1) Begin considering the challenges of RTES deployment in the United States through application of socio-technical and transitions frameworks; 2) Begin applying the theory of RTES as configurational technology innovation systems in the United States and for industrial process heat specifically; 3) Review RTES innovation, policies, and market formation activities in the contexts of Objectives 1 and 2; 4) Identify future paths for RTES research. Ultimately, the challenges associated with scaling the deployment of RTES in the United States are related to the need to develop a well-functioning innovation system that can overcome resistance from a highly stable socio-technical regime within a shrinking window of time to address the climate crisis, U.S. industrial competitiveness, and volatile energy commodity price shocks. Current efforts toward scaling for RTES applications in industry and buildings emphasize the need for further cost reductions, but not for interventions that support actors and their interactions and that increase the legitimacy of the technologies. As a result, there are significant opportunities to analyze the social contexts of RTES that can then be used to inform the design of effective, transformational policy portfolios.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

An OpenStreetMaps based tool to study the energy demand and emissions impact of electrification of medium and heavy-duty freight trucks

In this paper, we present the mathematical formulation of an OpenStreetMaps (OSM) based tool that compares the costs and emissions of long-haul medium and heavy-duty (M&HD) electric and diesel freight trucks, and determines the spatial distribution of added energy demand due to M&HD EVs. The optimization utilizes a combination of information on routes from OSM, utility rate design data across the United States, and freight volume data, to determine these values. In order to deal with the computational complexity of this problem, we formulate the problem as a convex optimization problem that is scalable to a large geographic area. In our analysis, we further evaluate various scenarios of utility rate design (energy charges) and EV penetration rate across different geographic regions and their impact on the operating cost and emissions of the freight trucks. Our approach determines the net emissions reduction benefits of freight electrification by considering the primary energy source in different regions. Such analysis will provide insights to policy makers in designing utility rates for electric vehicle supply equipment (EVSE) operators depending upon the specific geographic region and to electric utilities in deciding infrastructure upgrades based on the spatial distribution of the added energy demand of M&HD EVs. To showcase the results, a case study for the U.S. state of Texas is conducted.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

Alternative Ratemaking in the US: A Prerequisite for Grid Modernization or an Unwarranted Shift of Risk to Customers?

With increasing frequency, investor-owned electric utilities are requesting preferred cost recovery for "grid modernization" in multiple forms, from multi-year rate plans to riders. Utilities' claims that massive grid investment is necessary, and that exceptional investment requires exceptional cost recovery, are typically accepted by policymakers with little challenge. It is difficult for policymakers to resist the siren call of grid modernization's perceived outcomes, from improved reliability and resilience to reduced risks to safety and new customer technology adoption (electric vehicles, distributed energy resources, and more). This paper provides a contrarian viewpoint that is virtually absent as policymakers consider alternative ratemaking practices. It introduces the possibility that excess grid investment in the name of modernization is not only possible, and economically harmful, but has already occurred, encouraged by alternative ratemaking. It provides examples of common grid modernization expenditures the authors have identified as cost-ineffective in the course of their work. It also describes traditional grid planning practices with proven ability to address changing requirements over time, calling into question the need for exceptional grid modernization investment plans. Most important, the paper explains the moral hazard inherent in alternative ratemaking, and the fundamental shift in ratemaking risks and responsibilities from utilities to customers that results. The perspectives this paper presents are critical for policymakers to understand before adopting, extending, or expanding alternative ratemaking practices in their respective jurisdictions.

ENERGY PLANNING, POLICY, AND ECONOMY,POWER TRANSMI↗

DOE OSTI2021

Energy Efficiency: What Has Research Delivered in the Last 40 Years?

This article presents a critical assessment of 40 years of research that may be brought under the umbrella of energy efficiency, spanning different aggregations and domains—from individual producing and consuming agents to economy-wide effects to the role of innovation to the influence of policy. After 40 years of research, energy efficiency initiatives are generally perceived as highly effective. Innovation has contributed to lowering energy technology costs and increasing energy productivity. Energy efficiency programs in many cases have reduced energy use per unit of economic output and have been associated with net improvements in welfare, emission reductions, or both. Rebound effects at the macro level still warrant careful policy attention, as they may be nontrivial. Complexity of energy efficiency dynamics calls for further methodological and empirical advances, multidisciplinary approaches, and granular data at the service level for research in this field to be of greatest societal benefit.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

Optimal Electric Vehicle Charging and Discharging Strategies Under DER Compensation Programs: Preprint

The adoption of electric vehicles (EVs) is becoming increasingly popular because of environmental concerns, the greater availability of models, and increased cost-competitiveness with gas vehicles. Because EVs have both charging and discharging capabilities, they provide great potential to help electric utilities with grid operation. When the grid demand is high, EVs can discharge to the grid to reduce the peak load, and vice versa; therefore, electric utilities have designed different policies to encourage EV charging station operators to charge or discharge at certain time periods. The New York State Public Service Commission established the Value of Distributed Energy Resources (VDER), or the Value Stack, to compensate for energy created by distributed energy resources, including EVs. This paper presents an optimization-based approach to identify the "golden hours" and "golden spots," i.e., the effective time periods and geographic locations for EV charging station operators to charge or discharge under the VDER program that can provide them the highest benefit. The proposed methodology can be applied to other compensation mechanisms and distribution systems as well. By working with industry partner NineDot Energy, realistic charging station information is used in this study, and the proposed approach is tested on a distribution feeder. The results from this study can help electric utilities and EV charging station operators determine the ideal charging/discharging time and the ideal locations for the charging station(s) in their distribution systems to achieve maximized benefit.

electric vehicle↗

DOE OSTI2025

Unlocking load growth at the grid edge: Practices for managing, recovering, and allocating distribution system investments

Utilities and utility regulators are preparing to make significant investments in the electricity distribution system driven by expected load growth in coming years and decades. Regulators will be tasked with vetting investment proposals and implementing cost recovery and allocation mechanisms. In particular, state regulators are anticipating the need to make proactive distribution system investments, building the capability to serve new load in advance of demand. This report focuses on load growth from homes and businesses that adopt electric vehicles and heat pump heating technologies. Through a review of legislation and regulatory dockets in a subset of states, we provide insights into emerging utility and regulatory practices to recover and allocate costs of electrification-driven distribution system investments necessary to accommodate these technologies. Our review focused on utility electrification programs, line extension policies, and proactive investments. Our report is largely descriptive, offering detailed information about approaches different state commissions and utilities have implemented to inform future decision-making.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

pnnl/MBDRL

Model-based Deep Reinforcement Learning for Real-time Grid Emergency Voltage Control. A model-based Deep Reinforcement Learning (DRL) framework where a deep neural network (DNN)-based surrogate model is utilized within the control policy learning framework, making the learning process faster and more sample efficient

Yin, Tim↗

DOE OSTI2021

The Value of Distributed Wind: A Valuation Framework

While there has been an increase in distributed energy resource (DER) adoption, particularly for solar photovoltaic (PV) DERs, distributed wind deployment is still relatively low. However, distributed wind has significant growth potential for behind-the-meter applications and can provide improved resource diversity and resilience in high-DER grid systems. In order to make optimized decisions about distributed wind deployment, it is important to identify and characterize the value streams of distributed wind in a way that will help policy makers, microgrid developers, utilities, project developers, and others understand the potential value of distributed wind. In our paper, we develop a framework to provide a consistent and comprehensive approach to finding the net benefits of distributed wind to various stakeholders in different scenarios. We do this by considering the main use cases for distributed wind, and then developing a framework which is flexible for these various use cases and the relevant stakeholders while maintaining the same overall structure for analysis. Ongoing work includes applying this framework to valuing two distributed wind power systems, one in a remote village in Alaska and one in a front-of-the-meter deployment in Iowa. Our analysis aims to understand the full value that distributed wind is providing in these systems, including the resilience benefits it is contributing. As a better understanding of distributed wind valuation is gained, it will be easier for stakeholders to make informed decisions in order to have resilient renewable energy systems.

17 WIND ENERGY↗

DOE OSTI2024

Driving Affordable Decarbonization: Inclusive Utility Program Designs for Disadvantaged Communities

Our research team worked with 17 utility partners from various U.S. regions to study current utility program practices. We identified the key characteristics of these programs and the challenges and opportunities in implementing them. Through our research, we provide a pragmatic, design-oriented, and customer-centered perspective for effective program design and implementation. We identify 13 successful characteristics of program design that may be considered by utility partners.

disadvantaged communities↗

DOE OSTI2021

ESPC ESA Training Series: Photovoltaic (PV) Project Considerations

This training covers technical, economic and other photovoltaic (PV) project considerations. Technical topics include cost-effectiveness, resilience, cybersecurity, and electrical considerations. In addition, other topics, such as compatibility with agency mission, site plans, coordination with the serving utility, the National Environmental Policy Act, and agency approval requirements. Considerations specific to third-party owned/third-party financed PV projects are also covered, as well as available resources and templates for project development. The training also includes a recap of the first session in the Energy Savings Performance Contracts Energy Sales Agreements (ESPC ESA) Webinar Series.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

National Community Solar Partnership Multifamily Affordable Housing Portfolio Screening Approach

Community solar offers multiple benefits to providers and residents of multifamily affordable housing (MFAH), including access to affordable renewable energy for low- and moderate-income households, tax credits and other financial benefits for property owners, and increased community resilience when paired with energy storage. Even so, MFAH providers interested in realizing these benefits may need support to identify where to start or how to expand and accelerate solar deployment across their property portfolios once they have completed their first few installations. This fact sheet describes a portfolio screening approach for MFAH providers to evaluate their multi-state building portfolios for community solar project viability. The approach was developed by the National Renewable Energy Laboratory as part of its support for the National Community Solar Partnership (NCSP) MFAH Collaborative. By utilizing NREL's companion Policy Screening Workbook in conjunction with the web-based tools PVWatts® Calculator and REopt™ (Renewable Energy Integration and Optimization), MFAH providers can take a data-informed approach to identifying and prioritizing buildings in their portfolios that are most amenable to community solar development.

community solar↗

DOE OSTI2026

State-Tribal Collaboration: Utility Programs

This is one of 6 fact sheets for the State/Tribal Collaboration project for Office of Policy. This fact sheets discusses low-income utility programs that can benefit Tribes.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2024

Industrial Assessment Center

Established in 1990, San Diego State University’s (SDSU) Industrial Assessment Center (IAC) is proud of its years of service. During this period, it has served over 620 small and medium-sized manufacturing plants in Southern California. SDSU/IAC’s efforts to transfer state-of-the-art technologies to industry have increased revenues, cultivated creativity, improved energy efficiencies, and benefited the environment. The Center has contributed to the region's economic growth and stability by assisting small and medium size companies to better compete in the global market. It has helped mitigate climate change by reducing greenhouse gas emissions. IAC activities have fostered productive relationships between the University and local industry, assisted industrial sectors to improve their energy efficiency and enhance their manufacturing productivity, in turn impacting the material and working conditions of their employees. In addition to financial savings and environmental benefits, we have trained tens of students who became energy specialists in various companies. Thus, a substantial benefit of the IAC has been the ongoing training of engineering faculty and students. All IAC graduates were offered jobs before or within weeks of their graduation. The activities of the SDSU/IAC have expanded the institutional expertise of the College and improved the knowledge base of the faculties involved leading to several related publications, master’s theses, and senior student projects. Significant number of peer-reviewed publications of the IAC director at SDSU have greatly benefitted from the experience of the Center. As a result of this extensive exposure to manufacturing processes, the SDSU/IAC has grown to be an integral component of SDSU’s engineering research and training. We have successfully built upon these established achievements and academic excellence. IAC service to industry is particularly vital in Southern California, a region with one of the highest manufacturing concentrations in the country. SDSU/IAC has understood and implemented the overall objectives of DOE’s IAC program and guidelines except for the pandemic years when the country’s manufacturing sector was put in dire stress. In addition to student training and service to industry, IAC’s contribution to state and local governments as well as utility companies to assess energy policies and design rebate and incentive strategies cannot be undermined.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗