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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Powering Data Centers with Clean Energy: A Techno-Economic Case Study of Nuclear and Renewable Energy Dependability

Rising data demands from artificial intelligence (AI) and large language models (LLMs) generating images, videos, and text have prompted increased need for larger and more robust data centers in the United States. Major companies interested in these larger data centers face the choice of linking them to existing regional grids, building stand-alone power supplies onsite, or a combination of both. The request, review, and approval process for new transmission lines to grids in the United States, however, has grown in recent years to times spans rivaling those of new construction for nuclear power plants. Building an islanded power supply for each data center is therefore becoming a prominent option. In this case study, several technologies are modeled in techno-economic simulations for long-term system costs subject to fixed electricity demand from a singular data center. A 250 MWe data center is assumed with additional 50 MWe for resiliency. Techno-economic simulations are conducted using the Holistic Energy Resource Optimization Network (HERON) software, which is a part of the Framework for Optimization of Resources and Economics (FORCE) tool suite. Technologies considered include solar, wind, lithium-ion batteries, and several types of nuclear reactors: large-scale reactors, small modular reactors, and microreactors. A low- and high-cost estimate for each technology is assumed to develop a range of expected economic performance. Low-cost estimates included several clean energy production tax credits. Different combinations of renewable energy generators with nuclear reactors are considered, ranging from a fully renewable-powered data center to a fully nuclear-powered data center. Historic time series of wind and solar availability from the Texas grid are used to train a reduced order model; this model then generates unique time series with similar characteristics of the training dataset. Multiple scenarios of weather and subsequent operations are simulated for each renewable-nuclear combination to determine total costs throughout the project lifetime. Fully renewable-powered configurations required large amounts of installed capacity (GW scale) in the simulations to meet the fixed demand of the data center. This is due to some scenarios in the historical dataset which captured low-wind and low-solar days, requiring over-building of these technologies as well as batteries to compensate for the low amounts of electricity generation. Fully nuclear-powered configurations outperformed the fully renewable and mixed renewable-nuclear configurations in terms of cost, with ranges between $1B and $10B in 2023 USDs compared to $40B+ for fully renewable configurations. Of the nuclear technologies, small modular reactors performed better economically than large-scale nuclear models due to lower projected capital costs, and both performed better than the microreactor models. These results demonstrate the applicability of firm, dispatchable electricity resources from baseload generators like nuclear power plants for operating facilities that run at constant power without daily variability.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Applications of explainable artificial intelligence in renewable energy research

Researchers in renewable energy are applying deep learning (DL) to a variety of problems from diverse renewable energy domains, such as biofuels, wind, solar, power systems, buildings, vehicles, and transportation systems. Improvements in accuracy may be demonstrated using DL in laboratory settings. However, the lack of interpretability of DL models poses a practical limitation to their utility in advancing scientific knowledge and in the deployment of DL models in safety-critical energy systems. In this article, we discuss explainable artificial intelligence (XAI) as one pathway toward more interpretable DL models. We explore a brief timeline of U.S. national laboratory interest in XAI, an overview and taxonomy of methods in the field of XAI, and a selection of applications across renewable energy research domains. We conclude by highlighting pivotal areas where XAI can accelerate innovation in artificial intelligence for renewable energy research and other essential future directions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Renewable Hydrogen to Vehicle (RH2V) – Operation Verification and Risk Mitigation Studies: Original Agreement (Modification 0) (CRADA Final Report)

Toyota has announced plans for commercial fuel cell vehicle deployment in 2015. To fully realize the benefits of fuel cell vehicles (zero emission with no performance loss in terms of vehicle range and capability), hydrogen produced efficiently from renewable sources is necessary. Most of the hydrogen fueling stations today utilize hydrogen reformed from natural gas (produced onsite or delivered). This enables more stations to be deployed cost-effectively within a network. Producing and using cost-effective renewable hydrogen in fuel cell vehicles will enable realization of the full potential. A viable option of green hydrogen that reliably delivers on the full suite of benefits for Toyota fuel cell vehicle drivers is needed. NREL is in a unique position to analyze and optimize renewable hydrogen production scenarios using the Energy Systems Integration Facility (ESIF), a facility that is specifically designed to evaluate renewable energy integration technologies. As the U.S. Department of Energy's (DOE) primary national laboratory for renewable energy and energy efficiency research and development, NREL has extensive knowledge of photovoltaic systems as well as alternative renewable technologies for efficient and reliable production of green hydrogen.

08 HYDROGEN↗
DOE OSTI2022

Optimal design and integration of decentralized electrochemical energy storage with renewables and fossil plants

Increasing renewable energy requires improving the electricity grid flexibility. Existing measures include power plant cycling and grid-level energy storage, but they incur high operational and investment costs. Using a systems modeling and optimization framework, we study the integration of electrochemical energy storage with individual power plants at various renewable penetration levels. Furthermore, our techno-economic analysis includes both Li-ion and NaS batteries to encompass different technology maturity levels. A California case-study indicates localized integration to be cost-effective for greater grid flexibility. Li-ion batteries can mitigate the residual demand fluctuations of small to medium-sized plants, while NaS batteries would be best-suited for larger storage with higher renewable penetration. Overall, the battery-enabled renewable integration could reduce the unmet grid demand by 75%, the renewable curtailment by 58%, and the CO 2 emission intensity by 16% while including the life cycle emissions of the battery and the renewable farm. Our scenario-based analysis also indicates that rather than replacing all fossil power plants, it is more economical to combine batteries and renewables with individual fossil plants to achieve a clean energy grid.

25 ENERGY STORAGE↗
DOE OSTI2018

Solar Street Lighting: Using Renewable Energy for Safety for the Turtle Mountain Band of Chippewa

Renewable energy has grown throughout the years. It is not just something for today. With the United States power electrical grid being 100 plus years old, renewable energy is the future. There are many different types of renewable energy. Solar photovoltaic array units and wind turbines seem to be the most common community scale renewable energy systems. There are new solar and wind farms popping up in more and more places each day. It is said that installing the farms is a fast process as compared to dotting the "i's" and crossing the "t's" (paper work), which is really the most time-consuming part of the entire project. During the internship at Sandia, the Indian Energy interns attended many field visits to various tribal reservations. On these field visits, the interns were able to experience first-hand some amazing renewable energy plans and projects which have now become a reality. With each site visit, the success of tribal projects is seen where hard work and persistence pays off. It brings joy to see these tribes making their dreams a reality. It is heartwarming to hear the stories of why the tribe chose to bring renewable projects to their people. It is also very informative because the tribal hosts encourage as many questions as can be asked. The field visits are what make ideas possible and to dream of what could be pursued. Research is a big part making these goals and dreams a reality. Without the field visits and knowledge shared by the tribal staff and leaders, a relevant research topic would have been difficult to focus on. Returning for a second summer as an intern at Sandia National Laboratories' Indian Energy program, several research topics were considered. Ultimately, this research paper's focus is to incorporate renewable energy specifically to take care of Mother Nature as well as the Turtle Mountain Band of Chippewa Indian people. There have been many deaths on North Dakota Highway 281, which it is the main road of the Turtle Mountain Band of Chippewa reservation. The highway has a high volume of traffic every day, in addition to many people who frequently walk this road. There is no walking or bike path along the road; most people tend to walk the shoulders of the road. This research paper is a way to help protect these pedestrians with an idea of lighting the highway from the west end of Belcourt to one of are housing developments that is 5.34 miles to the west of town. This research paper will look at the various types of street lighting methods and provide recommendations for a suitable and economical project.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Exploring Renewable Energy Opportunities in Select Southeast Asian Countries: A Geospatial Analysis of the Levelized Cost of Energy of Utility-Scale Wind and Solar Photovoltaics

The costs of renewable energy-based electricity generation have fallen precipitously in recent years to levels that are increasingly competitive with traditional generation such as fossil fuel-based generation. As these costs become increasingly competitive, private developers, policymakers, and energy system planners are searching for opportunities to harness high-quality renewable energy resources. Developing economies are setting ambitious targets and exploring how cost-effective, grid-connected renewable energy options can help power economic growth and meet growing electricity demands. This includes the member states of the Association of Southeast Asian Nations (ASEAN) that are determined to reach a target of 23% of renewable energy in the region's total primary energy supply by 2025. A critical gap to identifying opportunities and scaling up renewable energy is the lack of quality data and analyses to support decisions on the investment and deployment of renewables - including wind and solar photovoltaics (PV). This work supports decision making by providing high-quality data and spatial analysis of the cost of utility-scale wind and solar PV generation in select countries of Southeast Asia - specifically, the ASEAN member states. Generation costs are expressed as the levelized cost of energy (LCOE) - a commonly used metric that represents the net present value of the unit cost of electricity during the lifetime of a particular electricity generation technology. This is the first spatial estimate of LCOE for these technologies within the ASEAN member states - providing insights into the roles that renewable energy resource quality and other factors may play in generation costs.

14 SOLAR ENERGY↗
DOE OSTI2021

STOCHASTIC OPTIMAL POWER FLOW FOR REAL-TIME MANAGEMENT OF DISTRIBUTED RENEWABLE GENERATION AND DEMAND RESPONSE (Final Report)

To meet the grand challenge of a sustainable energy future, there has been a surge of interest in renewable energy. Today, the uncertainty associated with renewable resources is handled by using operating reserves. The high penetration of renewable resources, however, introduces difficult-to-control dynamics and challenges for power system operation. Decision support tools are necessary at the bulk system operational level to recognize and efficiently utilize renewable resources and distributed demand response products in concert with traditional grid resources. It is envisaged that responsive load can potentially have very significant cost advantages over either spinning or non-spinning ramping reserve. Critical decisions are made during hour(s)-ahead and real-time power system operation regarding the commitment and dispatch of generators to ensure power delivery is both reliable and economic. These decisions are typically made by a security constrained optimal flow, which determines future generator commitments, dispatches, and ensures adequate reserves are available in the event of a contingency (unexpected outage) or if future system conditions deviate from forecasts. However, security has been always based on a pre-specified subset of contingency constraints whose enforcement does not guarantee security under all possible future possibilities while also giving little or no weight to the likelihood of each contingent event or the severity of its consequences. Existing tools, which are based exclusively on deterministic optimization models, do not yield optimal operational decisions to address these new challenges, in terms of both reliability and cost-effectiveness. This project has focused on developing a stochastic optimal power flow (SOPF) framework, which integrates renewable resource uncertainty, load uncertainty, distributed storage (DS), demand response (DR) products, in a holistic manner to address the uncertainty associated with ever-increasing renewable resources, along with the inclusion of distributed demand response products in future power systems. A proof-of-concept problem was created using the Pennsylvania-Jersey-Maryland (PJM) power system network. Synthetic wind generation was added to the system to simulate 50% wind penetration. A 1-hour test of SOPF operation indicated more than 6% operational cost savings. The project continued by adding the Midwestern Independent System Operator (MISO) as a partner, with focus shifting from SOPF to Stochastic Look-Ahead Unit Commitment (SLAC). Unlike PJM, MISO is faced with significant renewable energy resources within its footprint and is challenged with substantial uncertainty in its operations. The SLAC distinguishes itself from existing tools that operators use. At best, today’s tools solve two to three cases independently, where one or two system parameters, such as forecasted load level (e.g., a low, base, and high forecast), are varied and the resulting scenarios are analyzed independently. The stochastic-based optimization of SLAC leverages statistical information from an ensemble of potential operational scenarios and their respective likelihood. The SLAC output can be translated into valuable information to the operator such as suggested commitments, optimal scheduling and dispatch of resources, reserve requirements at both locational and zonal resolutions, ramping availability and requirements, availability of demand response including operational guidance concerning the near-term and real-time coordination between distributed energy resources, and utilization of distributed storage resources. The developed SOPF/SLAC tool, a stand-alone tool compatible with existing EMSs, will provide system operators with unprecedented visibility, flexibility and predictability to these resources and operational guidance concerning the real-time coordination between DERs and DR/DS products. The game changing and practical impact of this disruptive technology will be dramatic and will usher in a new era in the electric power industry, wherein green energy concepts are fully embraced, and electric power costs are lowered throughout the nation.

42 ENGINEERING↗
DOE OSTI2022

Renewable Energy Guidance for Industry

This document is intended to help Better Plants partners navigate the renewable energy market by providing background on renewable technologies and their benefits as well as a wide range of purchasing options available to organizations. This guidance provides helpful information on adopting renewables by highlighting tools and resources for evaluating renewable energy projects. It also provides information on how renewable energy resources are accounted for by Better Plants reporting requirements. A separate supplemental document to this guidance is available that provides more in-depth information about renewable technologies. This guidance document is applicable to Better Plants partners participating at either the program or challenge level. Although the guidance is primarily intended to assist companies participating in Better Plants, the methodologies and information within are applicable to any organization interested in exploring and adopting renewable energy.

09 BIOMASS FUELS↗
DOE OSTI2025

SmartFlower Renewable Energy Program (Final Technical Report)

The SmartFlower Renewable Energy Programming project brings renewable energy education to K-12 youth in the region. The motivation of the project was to pair an educational curriculum with Girl Scouts of the Colonial Coast’s newly acquired SmartFlower. A SmartFlower is a solar energy device shaped like a flower in which each petal is a solar panel. The ‘stem’ of the SmartFlower rotates throughout the day, so the petal panels follow the sun’s path and maximize sunlight absorption. The goal of the project was to create an educational curriculum for K-12 youth that centered the SmartFlower and other renewable energy related topics. The Girl Scouts of Colonial Coast team created two educational curriculums; each designed for a specific age group (K-5 and 6 th -12 th grade). Both curriculums walk participants through hands-on activities about the sun, renewable energy, and sustainability. The project adds to educational opportunities in the region and for Girl Scouts. As renewable energy becomes more prevalent and essential, youth must be informed on its’ mechanics and application. The project provides an age-appropriate educational tool that welcomes youth to visit the SmartFlower, understand its larger purpose, and consider the importance of renewable energy. The project was achieved on a modest budget of $16,672 and its sustainability beyond the project period has low to no cost for participants. The curriculum is free and accessible on our website and can be used as an evergreen educational tool. The SmartFlower Renewable Energy Programming project benefits the public as it provides a free, easily accessible education tool to children, families, caregivers, and local educators that is scientifically based and relevant to our energy landscape.

14 SOLAR ENERGY↗
NASA NTRS2003

Student Outreach With Renewable Energy Technology

The Student Outreach with Renewable Energy Technology (SORET) program is a joint grant that involves a collaboration between three HBCU's (Central State University, Savannah State University, and Wilberforce University) and NASA John H. Glenn Research Center at Lewis Field. The overall goal of the grant is to increase the interest of minority students in the technical disciplines, to encourage participating minority students to continue their undergraduate study in these disciplines, and to promote graduate school to these students. As a part of SORET, Central State University has developed an undergraduate research associates program over the past two years. As part of this program, students are required to take special laboratory courses offered at Wilberforce University that involve the application of renewable energy systems. The course requires the students to design, construct, and install a renewable energy project. In addition to the applied renewable energy course, Central State University provided four undergraduate research associates the opportunity to participate in summer internships at Texas Southern University (Renewable Energy Environmental Protection Program) and the Cleveland African-American Museum (Renewable Energy Summer Camp for High School Students) an activity co sponsored by NASA and the Cleveland African-American Museum. Savannah State University held a high school summer program with a theme of the Direct Impact of Science on Our Every Day Lives. The purpose of the institute was to whet the interest of students in science, mathematics, engineering, and technology (SMET) by demonstrating the effectiveness of science to address real world problems. The 2001 institute involved the design and installation of a PV water pumping system at the Center for Advanced Water Technology and Energy Systems at Savannah State. Both high school students and undergraduates contributed to this project. Wilberforce University has used NASA support to provide resources for an Applied Renewable Energy Laboratory offered to both Central State and Wilberforce students. In addition, research endeavors for high school and undergraduates were funded during the summer. The research involved attempts to layer photovoltaic materials on a conducting polymer (polypyrrole) substrate. Two undergraduate students who were interested in polymer research originated this concept. Finally, the university was able to purchase a meteorological station to assist in the analysis of the solar/wind hybrid power system operating at the university.

Clark, Eric B.↗
DOE OSTI2019

China’s Trajectories beyond Efficiency: CO 2 Implications of Maximizing Electrification and Renewable Resources through 2050

In support of the Paris Agreement, China committed to peak its CO 2 emissions by 2030 or earlier and to reduce its CO 2 intensity by 60-65% from 2005 levels by 2030. While energy efficiency will continue to play a major role, other significant actions in China beyond efficiency are needed to help limit the average global temperature increase to 1.5°C. This study uses a bottom-up national end-use model to evaluate even lower CO 2 emissions pathways for China beyond cost-effective efficiency by maximizing end-use electrification and adoption of new renewable resources. Unlike most recent modelling studies that only focus on renewable electricity generation with simplified projections for future electricity demand growth, this study evaluates maximum electrification for specific end-use sectors and non-conventional renewable resources on the demand-side. We use scenario analysis to evaluate the potential CO 2 reductions if China is able to rapidly decarbonize its power sector while maximizing electrification across all sectors and the additional opportunity from maximizing biomass and low temperature renewable heat use in industry and solar heating, cooling and water heating technologies use in buildings. While already widely used in some European countries, large-scale adoption of these non-conventional technologies have not yet been considered in China. We find that maximizing non-conventional electric and renewable technologies can help China peak its national CO 2 emissions as early as 2023, with significant additional CO 2 emission reductions through 2050. The greatest additional CO 2 reduction potential beyond efficiency lies in fossil fuel displaced by renewable heat in industry. These results suggest accelerating the utilization of non-conventional electric and renewable technologies present additional CO 2 reduction opportunities for China, but new policies and strategies are needed to change technology choice in the demand sectors.

Khanna, Nina↗
DOE OSTI2021

A hub and spoke approach to optimizing energy wheeling of renewable resources

The deployment of zero carbon renewable energy sources needs to increase significantly to support the goal of net zero greenhouse gas emissions by 2050. At the same time energy end use needs to decarbonize. This will change both energy supply and energy demand patterns, requiring the energy delivery infrastructure (grid-based transmission circuits) to become increasingly flexible to maintain security of supply everywhere and always. The integration of zero carbon renewable energy requires cross-border and cross energy system coupling and a fit-for-purpose design. Nowadays, energy systems are planned, designed and operated in silos with a strong national focus. However, large-scale offshore wind production needs to be transported to deep inland locations, across country borders. The increased peak generation capacity of renewable energy sources will, at times, significantly exceed demand (Matthew Langholtz, 2020). The traditional solution of continuously reinforcing and extending the electricity grid is not sustainable from a cost and societal perspective. This paper will, however, propose a deterministic approach on how networked (interconnected grid) Points of receipt (POR) to Points of Delivery (POD) can be optimized for wheeling renewable energy resources while minimizing energy cost with a hub and spoke approach. The statistical approach will be done via using existing daily energy market clearing prices, available transmission capacity and firm daily transmission prices in open access energy markets. Renewable energy targets, including specific offshore wind targets, need to be in line with the ramp-up as implied by the Paris Agreement. These targets are required to provide industry with a secure market outlook that allows them to build up supply chains accordingly. Optimizing wheeled energy paths from carbon neutral resources such as renewables make them not only cost competitive on the unit commitment stack, but also more accessible on the dispatch stack to other carbon heavy forms of generation such as coal and natural gas turbines (Matthew Langholtz, 2020). This correlates to maximizing renewable resource inertia (wind, solar, biomass) within an interconnected grid without having to consider additional expansion of resources via land purchases and de-forestation.

Mukherjee, Srijib↗
DOE OSTI2020

Improving operational flexibility of integrated energy system with uncertain renewable generations considering thermal inertia of buildings

Insufficient flexibility in system operation caused by traditional "heat-set" operating modes of combined heat and power (CHP) units in winter heating periods is a key issue that limits renewable energy consumption. In order to reduce the curtailment of renewable energy resources through improving the operational flexibility, a novel optimal scheduling model based on chance-constrained programming (CCP), aiming at minimizing the lowest generation cost, is proposed for a small-scale integrated energy system (IES) with CHP units, thermal power units, renewable generations and representative auxiliary equipments. In this model, due to the uncertainties of renewable generations including wind turbines and photovoltaic units, the probabilistic spinning reserves are supplied in the form of chance-constrained; from the perspective of user experience, a heating load model is built with consideration of heat comfort and inertia in buildings. To solve the model, a solution approach based on sequence operation theory (SOT) is developed, where the original CCP-based scheduling model is tackled into a solvable mixed-integer linear programming (MILP) formulation by converting a chance constraint into its deterministic equivalence class, and thereby is solved via the CPLEX solver. We report the simulation results on the modified IEEE 30-bus system demonstrate that the presented method manages to improve operational flexibility of the IES with uncertain renewable generations by comprehensively leveraging thermal inertia of buildings and different kinds of auxiliary equipments, which provides a fundamental way for promoting renewable energy consumption.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2021

Optimal energy storage portfolio for high and ultrahigh carbon-free and renewable power systems

Achieving 100% carbon-free or renewable power systems can be facilitated by the deployment of energy storage technologies at all timescales, including short-duration, long-duration, and seasonal scales; however, most current literature focuses on cost assessments of energy storage for a given timescale or type of technology. In this work, we use an optimization framework with high spatial and temporal resolution to simultaneously assess the variable renewable power deployment and the optimal storage portfolio for seven independent system operators in the United States. Results indicate that achieving high (75–90%) and ultrahigh (>90%) energy mixes requires combining several flexibility options, including renewable curtailment, short-duration, long-duration, and seasonal storage. For instance, carbon-free and renewable energy mix targets of up to 80% are achieved with economic curtailment and a combination of short- and long-duration energy storage for the performance and cost assumptions used. After that, there is a point between 80% and 95% where seasonal storage becomes cost-competitive, depending on the specific power system. Moreover, our results indicate that storage-to-storage operation—one storage device used to charge another storage device—and the decoupling of charging and discharging storage power capacity are cost-effective options for the integration of high and ultrahigh shares of carbon-free or renewable power sources. Additionally, the results from this study show that an 85% carbon-free or renewable energy mix can be achieved at a cost of avoided CO 2 emissions of US$66.0 per tonne or less, regardless of the power system.

25 ENERGY STORAGE↗
DOE OSTI2016

A Prospective Analysis of the Costs, Benefits, and Impacts of U.S. Renewable Portfolio Standards

This report evaluates the future costs, benefits, and other impacts of renewable energy used to meet current state renewable portfolio standards (RPSs). It also examines a future scenario where RPSs are expanded. The analysis examines changes in electric system costs and retail electricity prices, which include all fixed and operating costs, including capital costs for all renewable, non-renewable, and supporting (e.g., transmission and storage) electric sector infrastructure; fossil fuel, uranium, and biomass fuel costs; and plant operations and maintenance expenditures. The analysis evaluates three specific benefits: air pollution, greenhouse gas emissions, and water use. It also analyzes two other impacts, renewable energy workforce and economic development, and natural gas price suppression. This analysis finds that the benefits or renewable energy used to meet RPS polices exceed the costs, even when considering the highest cost and lowest benefit outcomes.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2018

Prospective Costs, Benefits, and Impacts of U.S. Renewable Portfolio Standards

These slides were presented at a webinar on January 9, 2017. The slides overview a report that evaluates the future costs, benefits, and other impacts of renewable energy used to meet current state renewable portfolio standards (RPSs). It also examines a future scenario where RPSs are expanded. The analysis examines changes in electric system costs and retail electricity prices, which include all fixed and operating costs, including capital costs for all renewable, non-renewable, and supporting (e.g., transmission and storage) electric sector infrastructure; fossil fuel, uranium, and biomass fuel costs; and plant operations and maintenance expenditures. The analysis evaluates three specific benefits: air pollution, greenhouse gas emissions, and water use. It also analyzes two other impacts, renewable energy workforce and economic development, and natural gas price suppression. The analysis finds that the benefits or renewable energy used to meet RPS polices exceed the costs, even when considering the highest cost and lowest benefit outcomes.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2019

International Best Practices for Implementing and Designing Renewable Portfolio Standard (RPS) Policies

Renewable energy (RE) targets have been around since the 1970s and have taken a number of forms, such as renewable energy action plans, government announcements, renewable portfolio standards and others. In this report, we focus on one subset of renewable energy targets: renewable portfolio standards (RPS). In the electricity sector, an RPS is a public policy tool in which a required amount of renewable energy relative to the entire energy mix is used to generate electricity connected to the electrical grid. RPSs are an enforceable form of RE targets; if the compliance entity does not perform, a penalty is assessed. In order to ensure successful implementation of RPS and other policies, the Government of Vietnam requested this policy study examining effective RPS policies globally. The purpose of this document is to provide an overview of RPSs internationally, highlighting key design elements and best practices. The paper includes a discussion of the other polices that can support RPS fulfillment. The paper draws on case examples from the U.S., Mexico, China, Korea, Australia, and the Philippines.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Local Power: Comparing County-Level Renewable Energy Potential to Consumption Using the SLOPE Platform

Wide-scale deployment of renewable energy technologies has the potential to significantly reduce greenhouse gas emissions and mitigate the effects of climate change. Many communities have ambitious clean energy goals with targets for locally generated renewable energy. To inform state and local clean energy planning, analysts from the Joint Institute for Strategic Energy Analysis (JISEA) and National Renewable Energy Laboratory (NREL) used data from NREL's State and Local Planning for Energy (SLOPE) platform to compare annual technical generation potential of renewable energy technologies to modeled electricity consumption in every county of the contiguous United States. Annual costs were calculated to produce a 20% share of electricity consumed annually from each technology to examine localized cost effectiveness of a diversified mix of generation sources. For example, combining distributed and utility-scale wind and solar generation can offset the need for storage and nonintermittent fossil resources to achieve high deployment of renewables. This county-level analysis provides insight into where localized renewable energy generation could cost-effectively match annual electricity consumption.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗