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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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At least 253 records · Page 14
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DOE OSTI2012

Sun City Progress Report: Policy Effects on Photovoltaic Adoption for City Planning

This progress report documents the Sun City modeling approach, intended to be an analytic tool for city planners. It is midway in development and this report provides the design basis to provide the mathematics for policy considerations applied to PV market acceleration. It assesses the effects on market diffusion for nine commonly used policies: cash incentives, third party financing, group purchase programs, community solar projects, feed-in-tariffs, property assessed clean energy financing, low interest loans, property and sales tax incentives, and streamlined PV permitting processes. Generic forms of all of these policies are modeled in a system dynamics PowerSim Studio TM model using a concept called the photovoltaic favorability (PVF). PVF is equal to the difference between the ratio of conventional electricity costs to levelized electricity costs of a PV system and four barrier ratios. The barriers are present to model inhibiting influences on human decisions and financial limitations. They include down payment costs, month to month payment costs of financing, time to net profit, and time to lower payments. Each barrier term is divided by a tolerance term which represents the potential that consumers of the region can typically invest. PVF is quantified across a range of limited budget financing and cash incentives options which are then consumed from greatest PVF to least PVF. Finding the overall PVF requires iteration on a variation of the Bass diffusion model. This iterative scheme is tied in a feed-back loop to local and national PV learning curves which in turn quantify reductions in the cost of PV for future time steps based on user input learning rates. The modeling has been wrapped into a graphical user interface which will allow city planners to easily compare and demonstrate multiple scenarios. Data for the DOE sponsored Solar America Cities and for Albuquerque, New Mexico has been entered into the model in order to minimize data collection efforts by city planners.

14 SOLAR ENERGY↗
DOE OSTI2014

Standby Rates for Combined Heat and Power Systems

Improvements in technology, low natural gas prices, and more flexible and positive attitudes in government and utilities are making distributed generation more viable. With more distributed generation, notably combined heat and power, comes an increase in the importance of standby rates, the cost of services utilities provide when customer generation is not operating or is insufficient to meet full load. This work looks at existing utility standby tariffs in five states. It uses these existing rates and terms to showcase practices that demonstrate a sound application of regulatory principles and ones that do not. The paper also addresses areas for improvement in standby rates.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2010

A primer for the statistical analysis of field test data obtained from screening instruments that detect contraband

A variety of federal agencies have continuing development programs whose mission is to advance the technology for monitoring the flow of commerce to detect the presence of contraband. The items of interest can be undeclared goods on which taxes or tariffs are due, or illegal substances such as recreational drugs, or banned weapons or weapon parts such as nuclear material, or nuclear weapons being moved in violation of a nonproliferation treaty. As these technologies continue in development they are assessed periodically in experimental testing either in the laboratory or in the field. The testing programs sometimes may resemble those employed by the pharmaceutical industry and their goal is to determine whether these technologies are efficacious and whether there are unanticipated negative consequences. The goal of the analysis is to determine the most probable value of P and estimate its uncertainty or the confidence that it falls within an acceptable range.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2013

Encouraging Combined Heat and Power in California Buildings

Governor Brown’s research priorities include an additional 6.5 GW of combined heat and power (CHP) by 2030. As of 2009, roughly 0.25 GW of small natural gas and biogas fired CHP is documented by the Self-Generation Incentive Program (SGIP) database. The SGIP is set to expire, and the anticipated grid de-carbonization based on the development of 20 GW of renewable energy will influence the CHP adoption. Thus, an integrated optimization approach for this analysis was chosen that allows optimizing the adoption of distributed energy resources (DER) such as photovoltaics (PV), CHP, storage technologies, etc. in the California commercial sector from the building owners’ perspective. To solve this DER adoption problem the Distributed Energy Resources Customer Adoption Model (DER-CAM), developed by the Lawrence Berkeley National Laboratory and used extensively to address the problem of optimally investing and scheduling DER under multiple settings, has been used. The application of CHP at large industrial sites is well known, and much of its potential is already being realized. Conversely, commercial sector CHP, especially those above 50 to 100 kW peak electricity load, is widely overlooked. In order to analyze the role of DER in CO 2 reduction, 147 representative sites in different climate zones were selected from the California Commercial End Use Survey (CEUS). About 8000 individual optimization runs, with different assumptions for the electric tariffs, natural gas costs, marginal grid CO 2 emissions, and nitrogen oxide treatment costs, SGIP, fuel cell lifetime, fuel cell efficiency, PV installation costs, and payback periods for investments have been performed. The most optimistic CHP potential contribution in this sector in 2020 will be 2.7 GW. However, this result requires a SGIP in 2020, 46% average electric efficiency for fuel cells, a payback period for investments of 10 years, and a CO 2 focused approach of the building owners. In 2030 it will be only 2.5 GW due to the anticipated grid decarbonization. The 2030 result requires a 60% electric efficiency and 20 year life time for fuel cells, a payback period of 10 years, and a CO 2 minimization strategy of building owners. Finally, the possible CHP potential in 2030 shows a significant variance between 0.2 GW and 2.5 GW, demonstrating the complex interactions between technologies, policies, and customer objectives.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2013

A Guidebook on Grid Interconnection and Islanded Operation of Mini-Grid Power Systems Up to 200 kW

A Guidebook on Grid Interconnection and Islanded Operation of Mini-Grid Power Systems Up to 200 kW is intended to help meet the widespread need for guidance, standards, and procedures for interconnecting mini-grids with the central electric grid as rural electrification advances in developing countries, bringing these once separate power systems together. The guidebook aims to help owners and operators of renewable energy mini-grids understand the technical options available, safety and reliability issues, and engineering and administrative costs of different choices for grid interconnection. The guidebook is intentionally brief but includes a number of appendices that point the reader to additional resources for indepth information. Not included in the scope of the guidebook are policy concerns about “who pays for what,” how tariffs should be set, or other financial issues that are also paramount when “the little grid connects to the big grid.”

25 ENERGY STORAGE↗
DOE OSTI2012

Modeling, Analysis, and Control of Demand Response Resources

While the traditional goal of an electric power system has been to control supply to fulfill demand, the demand-side can plan an active role in power systems via Demand Response (DR), defined by the Department of Energy (DOE) as “a tariff or program established to motivate changes in electric use by end-use customers in response to changes in the price of electricity over time, or to give incentive payments designed to induce lower electricity use at times of high market prices or when grid reliability is jeopardized” [29]. DR can provide a variety of benefits including reducing peak electric loads when the power system is stressed and fast timescale energy balancing. Therefore, DR can improve grid reliability and reduce wholesale energy prices and their volatility. This dissertation focuses on analyzing both recent and emerging DR paradigms. Recent DR programs have focused on peak load reduction in commercial buildings and industrial facilities (C&I facilities). We present methods for using 15-minute-interval electric load data, commonly available from C&I facilities, to help building managers understand building energy consumption and ‘ask the right questions’ to discover opportunities for DR. Additionally, we present a regression-based model of whole building electric load, i.e., a baseline model, which allows us to quantify DR performance. We use this baseline model to understand the performance of 38 C&I facilities participating in an automated dynamic pricing DR program in California. In this program, facilities are expected to exhibit the same response each DR event. We find that baseline model error makes it difficult to precisely quantify changes in electricity consumption and understand if C&I facilities exhibit event-to-event variability in their response to DR signals. Therefore, we present a method to compute baseline model error and a metric to determine how much observed DR variability results from baseline model error rather than real variability in response. We find that, in general, baseline model error is large. Though some facilities exhibit real DR variability, most observed variability results from baseline model error. In some cases, however, aggregations of C&I facilities exhibit real DR variability, which could create challenges for power system operation. These results have implications for DR program design and deployment. Emerging DR paradigms focus on faster timescale DR. Here, we investigate methods to coordinate aggregations of residential thermostatically controlled loads (TCLs), including air conditioners and refrigerators, to manage frequency and energy imbalances in power systems. We focus on opportunities to centrally control loads with high accuracy but low requirements for sensing and communications infrastructure. Specifically, we compare cases when measured load state information (e.g., power consumption and temperature) is 1) available in real time; 2) available, but not in real time; and 3) not available. We develop Markov Chain models to describe the temperature state evolution of heterogeneous populations of TCLs, and use Kalman filtering for both state and joint parameter/state estimation. We present a look-ahead proportional controller to broadcast control signals to all TCLs, which always remain in their temperature dead-band. Simulations indicate that it is possible to achieve power tracking RMS errors in the range of 0.26–9.3% of steady state aggregated power consumption. Results depend upon the information available for system identification, state estimation, and control. We find that, depending upon the performance required, TCLs may not need to provide state information to the central controller in real time or at all. We also estimate the size of the TCL potential resource; potential revenue from participation in markets; and break-even costs associated with deploying DR-enabling technologies. We find that current TCL energy storage capacity in California is 8–11 GWh, with refrigerators contributing the most. Annual revenues from participation in regulation vary from $10 to $220 per TCL per year depending upon the type of TCL and climate zone, while load following and arbitrage revenues are more modest at $2 to $35 per TCL per year. These results lead to a number of policy recommendations that will make it easier to engage residential loads in fast timescale DR.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2015

Value of Solar. Program Design and Implementation Considerations

Here, we present an analysis that assesses the potential market type that might form in the United States under a VOS rate, given current national average solar costs and various incentive scenarios, for the most populous city in each state. Three hypothetical VOS tariffs were developed, based on assumptions of avoided fuel costs, avoided capacity, environmental benefits, and line losses, to represent a of range of possible VOS rates. The levelized cost of solar in 50 locations is calculated using NREL’s System Advisor Model (SAM) using input assumptions regarding system size, resource quality, avoided capacity (aka capacity factor) and a variety of incentives. Comparing the solar costs with the hypothetical VOS rates illustrates the various market types that may form under a VOS program, in different locations.

14 SOLAR ENERGY↗
DOE OSTI2014

Demonstration of automated price response in large customers in New York City using Auto-DR and OpenADR

Demand response (DR) – allowing customers to respond to reliability requests and market prices by changing electricity use from their normal consumption pattern – continues to be seen as an attractive means of demand-side management and a fundamental smart-grid improvement that links supply and demand. From October 2011 to December 2013, the Demand Response Research Center at Lawrence Berkeley National Laboratory, the New York State Energy Research and Development Authority, and partners Honeywell and Akuacom, have conducted a demonstration project enabling Automated Demand Response (Auto-DR) in large commercial buildings located in New York City using Open Automated Demand Response (OpenADR) communication protocols. In particular, this project focuses on demonstrating how the OpenADR platform, enabled by Akuacom, can automate and simplify interactions between buildings and various stakeholders in New York State and enable the automation of customers’ price response to yield bill savings under dynamic pricing. In this paper, the cost control opportunities under day-ahead hourly pricing and Auto-DR control strategies are presented for four demonstration buildings; present the breakdown of Auto-DR enablement costs; summarize the field test results and their load impact; and show potential bill savings by enabling automated price response under Consolidated Edison’s Mandatory Hourly Pricing (MHP) tariff. For one of the sites, the potential bill savings at the site’s current retail rate are shown. Facility managers were given granular equipment-level opt-out capability to ensure full control of the sites during the Auto-DR implementation. The expected bill savings ranged from 1.1% to 8.0% of the total MHP bill. The automation and enablement costs ranged from $70 to $725 per kW shed. The results show that OpenADR can facilitate the automation of price response, deliver savings to the customers and opt-out capability of the implementation retains control of the sites by facility managers.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2015

Retrospective North American CFL Experience Curve Analysis and Correlation to Deployment Programs

Retrospective experience curves are a useful tool for understanding historic technology development, and can contribute to investment program analysis and future cost estimation efforts. This work documents our development of an analysis approach for deriving retrospective experience curves with a variable learning rate, and its application to develop an experience curve for compact fluorescent lamps for the global and North American markets over the years 1990-2007. Uncertainties and assumptions involved in interpreting data for our experience curve development are discussed, including the processing and transformation of empirical data, the selection of system boundaries, and the identification of historical changes in the learning rate over the course of 15 years. In the results that follow, we find that that the learning rate has changed at least once from 1990-2007. We also explore if, and to what degree, public deployment programs may have contributed to an increased technology learning rate in North America. We observe correlations between the changes in the learning rate and the initiation of new policies, abrupt technological advances, including improvements to ballast technology, and economic and political events such as trade tariffs and electricity prices. Finally, we discuss how the findings of this work (1) support the use of segmented experience curves for retrospective and prospective analysis and (2) may imply that investments in technological research and development have contributed to a change in market adoption and penetration.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

Wheeling and Banking Strategies for Optimal Renewable Energy Deployment. International Experiences

This paper defines the principles of wheeling (i.e., transmission) tariffs and renewable energy (RE) banking provisions and their role in RE deployment in countries with plans for large-scale RE. It reviews experiences to date in the United States, Mexico, and India and discusses key policy and regulatory considerations for devising more effective wheeling and/or banking provisions for countries with ambitious RE deployment targets. The paper addresses the challenges of competing needs of stakeholders, especially those of RE generators, distribution utilities, and transmission network owners and operators. The importance of wheeling and banking and their effectiveness for financial viability of RE deployment is also explored. This paper aims to benefit policymakers and regulators as well as key renewable energy stakeholders. Key lessons for regulators include: creating long-term wheeling and banking policy certainty, considering incentivizing RE through discounted transmission access, and assessing the cost implications of such discounts, as well as expanding access to renewable energy customers.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2016

Midmarket Solar Policies in the United States: A Guide for Midsized Solar Customers

The midscale market for solar photovoltaics (PV) has not experienced the same high growth rate as residential- or utility-scale market segments in the past five years when solar PV deployment increased rapidly. Midscale solar can be defined as behind-the-meter solar PV between 50 kilowatts and 2 megawatts adopted by multi-housing residential, commercial, industrial, non-profit, and other entities. A number of challenges face the midscale segment, including difficulties in contracting, mismatch between tenant lease and PV financing terms, high transaction costs relative to project sizes, and inefficiencies in matching prospective projects with capital. The changing policy landscape across U.S. states provides both opportunities and challenges to midmarket solar. Some states, such as California, are expanding system capacity limits for policies such as net metering, thus enabling a wider range of customers to benefit from excess generation. A number of states and utilities are making changes to rate design to introduce new or higher user fees for solar customers or reduced tariffs for net metering, which decrease the value of solar generation. An understanding of these policies relative to project feasibility and economics is important for prospective customers to make informed decisions to adopt solar PV. This guide complements existing solar policy resources to help potential customers navigate through the policy landscape in order to make informed decisions for their solar investment. The first part of this guide introduces the key solar policies necessary for policy-based decision-making, which involves using knowledge of a solar policy to improve project economics and efficiency. Policies that could result in policy-based decisions include interconnection standards, net metering, user fees, incentives, and third-party ownership policies. The goal of this section is to equip prospective customers and project developers with the tools necessary to understand and use solar policies in a dynamic policy environment. The second part of this guide provides a complete, state-by-state inventory of midmarket solar policies for potential customers and developers to use as reference when making policy-based decisions. Although solar policies are dynamic, the profiles provide a framework for assessing policies to build the parameters that could be used to determine feasibility and structure of a solar PV system for midmarket customers and developers.

14 SOLAR ENERGY↗
DOE OSTI2017

The Impacts of Changes to Nevada’s Net Metering Policy on the Financial Performance and Adoption of Distributed Photovoltaics

Net energy metering (NEM) is a billing mechanism that has historically compensated owners of distributed generation systems at retail rates for any electricity that they export back to the grid rather than consume on-site. NEM can significantly enhance the financial performance of distributed generation systems from the owner’s perspective. The following analysis was designed to illustrate the potential impact of NEM policy and tariff changes implemented in early 2016 in Nevada.

14 SOLAR ENERGY↗
DOE OSTI2017

Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. I -- National Study

The use of renewable energy (RE) sources, primarily wind and solar generation, is poised to grow significantly within the Indian power system. The Government of India has established a target of 175 gigawatts (GW) of installed RE capacity by 2022, including 60 GW of wind and 100 GW of solar, up from 29 GW wind and 9 GW solar at the beginning of 2017. Thanks to advanced weather and power system modeling made for this project, the study team is able to explore operational impacts of meeting India's RE targets and identify actions that may be favorable for integration. Our primary tool is a detailed production cost model, which simulates optimal scheduling and dispatch of available generation in a future year (2022) by minimizing total production costs subject to physical, operational, and market constraints. Our team comprises a core group from the Power System Operation Corporation, Ltd. (POSOCO), which is the national grid operator (with representation from the National, Southern, and Western Regional Load Dispatch Centers) under Ministry of Power, National Renewable Energy Laboratory (NREL), and Lawrence Berkeley National Laboratory (LBNL), and a broader modeling team that includes Central Electricity Authority (CEA), POWERGRID (the central transmission utility, CTU), and State Load Dispatch Centers in Maharashtra, Gujarat, Tamil Nadu, Karnataka, Rajasthan, and Andhra Pradesh. Our model includes high-resolution wind and solar data (forecasts and actuals), unique properties for each generator, CEA/CTU's anticipated buildout of the power system, and enforced state-to-state transmission flows. Assuming the fulfillment of current efforts to provide better access to the physical flexibility of the power system, we find that power system balancing with 100 GW of solar and 60 GW of wind is achievable at 15-minute operational timescales with minimal RE curtailment. This RE capacity meets 22% of total projected 2022 electricity consumption in India with annual RE curtailment of 1.4%, in line with experiences in other countries with significant RE penetrations (Bird et al. 2016). Changes to operational practice can further reduce the cost of operating the power system and reduce RE curtailment. Coordinating scheduling and dispatch over a broader area is the largest driver to reduce costs, saving INR 6300 crore (USD $920 million) annually when optimized regionally. Lowering minimum operating levels of coal plants (from 70% to 40%) is the biggest driver to reduce RE curtailment - from 3.5% down to 0.76%. In fact, this operating property is more influential than faster thermal generation ramp rates in lowering the projected levels of curtailment. While this study does not answer every question relevant to planning for India's 2022 RE targets, it is an important step toward analyzing operational challenges and cost saving opportunities using state-of-the-art power system planning tools. Further analysis can build upon this basis to explore optimal renewable resource and intrastate transmission siting, system stability during contingencies, and the influence of total power system investment costs on customer tariffs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India’s Electric Grid, Vol. 1. National Study

The use of renewable energy (RE) sources, primarily wind and solar generation, is poised to grow significantly within the Indian power system. The Government of India has established a target of 175 gigawatts (GW) of installed RE capacity by 2022, including 60 GW of wind and 100 GW of solar, up from 29 GW wind and 9 GW solar at the beginning of 2017. Using advanced weather and power system modeling made for this project, the study team is able to explore operational impacts of meeting India’s RE targets and identify actions that may be favorable for integration. Our primary tool is a detailed production cost model, which simulates optimal scheduling and dispatch of available generation in a future year (2022) by minimizing total production costs subject to physical, operational, and market constraints. Our team comprises a core group from the Power System Operation Corporation, Ltd. (POSOCO), which is the national grid operator (with representation from the National, Southern, and Western Regional Load Dispatch Centers) under Ministry of Power, National Renewable Energy Laboratory (NREL), and Lawrence Berkeley National Laboratory (Berkeley Lab), and a broader modeling team that includes Central Electricity Authority (CEA), POWERGRID (the central transmission utility, CTU), and State Load Dispatch Centers in Maharashtra, Gujarat, Tamil Nadu, Karnataka, Rajasthan, and Andhra Pradesh. Our model includes high-resolution wind and solar data (forecasts and actuals), unique properties for each generator, CEA/CTU’s anticipated buildout of the power system, and enforced state-to-state transmission flows. Assuming the fulfillment of current efforts to provide better access to the physical flexibility of the power system, we find that power system balancing with 100 GW of solar and 60 GW of wind is achievable at 15-minute operational timescales with minimal RE curtailment. This RE capacity meets 22% of total projected 2022 electricity consumption in India with annual RE curtailment of 1.4%, in line with experiences in other countries with significant RE penetrations (Bird et al. 2016). Changes to operational practice can further reduce the cost of operating the power system and reduce RE curtailment. Coordinating scheduling and dispatch over a broader area is the largest driver to reduce costs, saving INR 6300 crore (USD 980 million) annually when optimized regionally. Lowering minimum operating levels of coal plants (from 70% to 40%) is the biggest driver to reduce RE curtailment—from 3.5% down to 0.76%. In fact, this operating property is more influential than faster thermal generation ramp rates in lowering the projected levels of curtailment. While this study does not answer every question relevant to planning for India’s 2022 RE targets, it is an important step toward analyzing operational challenges and cost saving opportunities using state-of-the-art power system planning tools. Further analysis can build upon this basis to explore optimal renewable resource and intrastate transmission siting, system stability during contingencies, and the influence of total power system investment costs on customer tariffs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

Solar + Storage Synergies for Managing Commercial-Customer Demand Charges

We study the synergies between behind-the-meter solar and storage in reducing commercial-customer demand charges. This follows two previous studies that examined demand charge savings for stand-alone solar in both the residential and commercial sectors. In this study we show that solar and storage show consistent synergies for demand charge management, that the magnitude of reductions are highly customer-specific, and that the magnitude of savings is influenced by the design of the electricity tariff.

14 SOLAR ENERGY↗
DOE OSTI2018

The Cost of Distribution System Upgrades to Accommodate Increasing Penetrations of Distributed Photovoltaic Systems on Real Feeders in the United States

The increasing deployment of distributed photovoltaic systems (DPV) can impact operations at the distribution level and the transmission level of the electric grid. It is important to develop and implement forward-looking approaches for calculating distribution upgrade costs that can be used to inform system planning, market and tariff design, cost allocation, and other policymaking as penetration levels of DPV increase. Using a bottom-up approach that involves iterative hosting capacity analysis, this report calculates distribution upgrade costs as a function of DPV penetration on three real feeders - two in California and one in the Northeastern United States.

14 SOLAR ENERGY↗
DOE OSTI2018

Distributed Generation Valuation and Compensation

This white paper can help guide a state as it considers issues associated with distributed generation valuation and compensation. States may address a common set of questions and issues in the valuation process, but differences in market expectations, policy priorities, and regulations result in different responses. Key issues include: Context is important. Valuations and compensation strategies will vary based on goals and objectives they are being designed to achieve. Goals and objectives should be made clear up front and will drive the perspective used in performing valuations and how outcomes are applied. Utilities and stakeholders can have different interpretations of how value elements should be calculated. In some states, the objective of standardized calculators and methods is to reduce ambiguity and inconsistencies in how valuations are performed. Certain value elements are difficult or impossible to quantify and most efforts to establish workable value of solar or value of distributed energy resource tariffs are emerging and nascent. Assessing locational and temporal value of distributed generation and applying that in compensation schemes is a new and emerging field of study, being explored by a handful of research organizations and advanced states and utilities. The most advanced states, such as California, are using demonstration projects to test valuation and compensation methodologies or are applying valuation and compensation strategies to a subset of customer projects, such as for community solar projects (e.g., Oregon and New York) before rolling out programs to the full customer base. A variety of states are moving away from full net metering, in many cases substituting avoided cost rates (sometimes with an adder) in lieu of full retail rate compensation, instead of pursuing valuation of distributed energy resource approaches. For example, in Indiana a 25% adder is applied to average wholesale electricity prices and in Mississippi a 2.5 cents/kWh adder is applied to avoided cost rates. These adders appear to have been established through policy directives rather than a comprehensive cost of service valuations.

24 POWER TRANSMISSION AND DISTRIBUTION↗