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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
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Solar Photovoltaic Systems Research

This CRADA focused on addressing concerns related to the impact of high penetration PV systems and developing simulation models for PV power plants. Technical work encompassed instrumentation, data collection and analysis, and development and validation of industry-standard models for utility planning and interconnection studies. This collaboration also resulted in dissemination of key research findings and advancement of standards. Sandia National Laboratories (Sandia) and SunPower contributed significantly to stakeholder activities such as the North America Electric Reliability Corporation (NERC) Integration of Variable Generation Task Force (IVGTF) and the Western Electricity Coordinating Council(WECC) Modeling and Validation Work Group. This research and collaboration also contributed to the success of Sandia projects sponsored by the DOE PV Solar Energy Technologies Program.

14 SOLAR ENERGY↗
DOE OSTI2018

Using Federal Energy Assistance Funds for PV to Reduce Energy Burden for Low-Income Households

Though the rapid decline in the cost of solar has resulted in unprecedented levels of solar deployment across the country, the majority of residential solar installations have been in middle-to-affluent households. Also, federal energy assistance programs have traditionally focused on weatherization with energy efficiency measures or bill assistance. Coupled with innovative financing mechanisms, solar photovoltaics (PV) now present another attractive option for helping low-income households reduce their energy burden. Seizing this opportunity, several states have undertaken efforts to include solar investments in Department of Health and Human Services' Low-Income Heating and Energy Assistance Program (LIHEAP) and the Department of Energy's Weatherization Assistance Program (WAP) funded projects. To support these state initiatives, DOE's WAP and the Solar Energy Technologies Office (SETO) have been collaborating with the National Renewable Energy Laboratory (NREL) to provide states with additional guidance and technical support to gain approval to use WAP funds for PV. Early examples of states demonstrating cost effectiveness of PV within Colorado and New York state SETO and NREL have also begun exploring how established solar business models could align with the LIHEAP utility assistance model.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Quantifying the Opportunity Limits of Automatic Residential Electric Load Shaping

Electric utility residential demand response programs typically reduce load a few times a year during periods of peak energy use. In the future, utilities and consumers may monetarily and environmentally benefit from continuously shaping load by alternatively encouraging or discouraging the use of electricity. One way to shape load and introduce elasticity is to broadcast forecasts of dynamic electricity prices that orchestrate electricity supply and demand in order to maximize the efficiency of conventional generation and the use of renewable resources including wind and solar energy. A binary control algorithm that influences the on and off states of end uses was developed and applied to empirical time series data to estimate price-based instantaneous opportunities for shedding and adding electric load. To overcome the limitations of traditional stochastic methods in quantifying diverse, non-Gaussian, non-stationary distributions of observed appliance behaviour, recent developments in wavelet-based analysis were applied to capture and simulate time-frequency domain behaviour. The performance of autoregressive and spectral reconstruction methods was compared, with phase reconstruction providing the best simulation ensembles. Results show spatiotemporal differences in the amount of load that can be shed and added, which suggest further investigation is warranted in estimating the benefits anticipated from the wide-scale deployment of continuous automatic residential load shaping. Empirical data and documented software code are included to assist in reproducing and extending this work.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

RODeO (Revenue Operation and Device Optimization Model) [SWR 20-67]

The Revenue, Operation, and Device Optimization (RODeO) model explores optimal system design and operation considering different levels of grid integration, equipment cost, operating limitations, financing, and credits and incentives. RODeO is a price-taker model formulated as a mixed-integer linear programming (MILP) model in the GAMS modeling platform. The objective is to maximizes the net revenue for a collection of equipment at a given site. The equipment includes generators (e.g., gas turbine, steam turbine, solar, wind, hydro, fuel cells, etc.), storage systems (batteries, pumped hydro, gas-fired compressed air energy storage, long-duration systems, hydrogen), and flexible loads (e.g., electric vehicles, electrolyzers, flexible building loads). The input data required by RODeO can be classified into three bins: 1) utility service data, which refers to retail utility rate information (meter cost, energy and demand charges), 2) electricity market data, which include energy and reserve prices, 3) other inputs, which refer to additional electrical demand, product output demand, technological assumptions, financial properties, and operational parameters.

Guerra Fernandez, Omar Jose↗
DOE OSTI2018

Demand Response Operation of Electricity-Intensive Chemical Processes for Reduced Greenhouse Gas Emissions: Application to an Air Separation Unit

A recent push for reduced greenhouse gas (GHG) emissions has led (in part) to the addition of renewable electricity generation sources to the power generation mix. Renewables such as wind and solar are desynchronized from grid demand, requiring the use of fossil fuels to bridge the gap. We propose a novel production scheduling formulation, emissions-minimizing production (EMP), which utilizes time-based information on the nature of the power generation mix to lower GHG emissions related to the transmission and generation of electricity for industrial users. We demonstrate the application of EMP on a single-column air separation unit. The scheduling problem is cast as a mixed integer linear program that can be solved in a practical amount of time. Extensive numerical studies are used to place EMP in the context of other production scheduling methods (such as demand response), and demonstrate its potential for significant reductions in GHG emissions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Distribution Grid Impact Study in Highland Park, Michigan: Understanding Rooftop Solar, Behind-the-Meter Energy Storage, Electric Vehicle Charging, and Building Electrification [Slides]

Through the Communities LEAP (Local Energy Action Program) Pilot, the National Renewable Energy Laboratory (NREL) engaged the Highland Park Stakeholder Coalition to scope four technical assistance work areas to address their energy needs and goals. This slide deck addresses the highlighted tasks under work area "B" related to policy analysis, due diligence, and case studies for removing barriers and providing best practices for local clean energy development. Highland Park community members face frequent, long-duration power interruptions due largely to the aging distribution system serving the area and the legacy design standards used in its construction. While degrading physical infrastructure such as poles, crossarms, and transformers can result in this substandard reliability, another notable characteristic of this legacy system is the lower, 4.8 kV, voltage class. This is a legacy construction standard which many utilities, DTE included, are phasing out in favor of higher, 15 or 25 kV, voltage classes instead. The existing 4.8 kV distribution system serving Highland Park may limit significant adoptions of clean-energy technologies like high percentages of building electrification or electric vehicle adoption. The following analysis seeks to quantify these limitations under a variety of clean-energy technology adoption scenarios. It compares the overall system risks of the present system to those of a hypothetical, upgraded 13.2 kV system, using NREL-developed risk metrics and offers upgrade cost considerations. The legacy 4.8 kV voltage class serving Highland park is not, as we have modeled it, a major limitation to the widespread adoption of cost-optimal rooftop solar and/or behind-the-meter energy storage. Within our modeling framework, these technologies namely impact secondary, low-voltage assets, which may be remedied without the need for a system-wide upgrade to a 13.2 kV voltage class. Our model of the current 4.8kV system indicates it is not capable of supporting community-wide electrification efforts. Widespread building electrification, and the resulting large increase in wintertime load, dramatically increases the prevalence of voltage violations and thermal overloading on the current 4.8 kV distribution system. These impacts illustrate the need for system-wide upgrades to a 13.2 kV voltage class to accommodate these technologies. Low to Moderate DER adoption does not adversely impact the grid but does improve undervoltage and asset overloading issues. However, these benefits are insufficient to defer grid upgrades. Higher DER penetration is shown to increase overvoltage and asset overloading in future electrification scenarios.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Energy Efficiency and Renewable Energy for New Home Construction in Maui

For residential property owners preparing to rebuild homes in Maui, this fact sheet, produced by the National Renewable Energy Laboratory (NREL), a national laboratory of the U.S. Department of Energy (DOE), provides a brief introduction to the topics of renewable energy and energy efficiency for new residential construction, presents a few high-level considerations and key concepts, and provides a sampling of information on rebates, incentives, certification programs, standards, and relevant policies. This fact sheet is not intended to be comprehensive nor to replace local resources.

appliances↗
DOE OSTI2015

Solar, Install, Mount, Production, Labor, Equipment Balance of Systems

The GTRI led project team in partnership with the DOE, universities, and numerous industry leaders, have advanced the mission of the DOE EERE, the Solar Energy Technologies Program, and the SunShot Initiative by accelerating the research, development, and demonstration of solar PV technologies that provide Extreme Balance of Systems Cost Reductions (BOS-X). The research produced 132 design concepts, resulting in 19 invention disclosures, five patent applications, four 90% pre-commercial designs, and three licensed technologies. Technology practice rights were obtained by an industry partner, and a new solar commercial start-up company was launched in Atlanta as a result of this project. Innovations in residential, commercial, and utility scale balance of systems technologies were realized through an unprecedented multi-disciplinary university/industry partnership with over 50 students and 24 faculty members that produced 18 technical publications, a PhD thesis, and two commercially deployed operating prototypes. The technical effectiveness and economic feasibility of the multidisciplinary systems based approach executed by the project team was realized through 1) a comprehensive evaluation of industry, regulatory, and public stakeholder requirements; 2) numerous industry/student/faculty engagements in design studios, technical conferences, and at solar PV installation sites; 3) time and motion studies with domain experts that provided technical data and costs for each phase and component of the solar PV installation processes; 4) extensive wind tunnel and systems engineering modeling; and 5) design, construction, and demonstration of the selected technologies in the field at high profile sites in Atlanta. The SIMPLE BOS project has benefitted the public in the following ways: • Workforce development: The launch of a start-up company to commercialize the DOE funded SIMPLE BoS designs has directly created 9 new jobs in the State of Georgia. As of November 2014, the Georgia solar industry employs 2,890 solar workers, representing a 12.8% growth in employment over 2013 (Solar Jobs Census, 2014). • Growth of the solar industry: The DOE SIMPLE BoS SunShot Award to GTARC accelerated the growth of the solar industry in Georgia, due to the national publicity of the award and the engagement of numerous solar PV manufacturers, designers, and installers on the SIMPLE BoS project. In 2011 less than 50 megawatts of solar PV capacity existed in Georgia; by 2016 Georgia may reach nearly 800 MW of total approved solar capacity with the 2012 Georgia Power Advanced Solar Initiative. • Technical outreach and publications: Georgia Tech has participated in numerous technical symposiums, technology demonstrations, campus solar PV tours, and produced 18 publications for the solar industry and general public. • Cost reductions for consumers: The SIMPLE BoS pre-commercial systems and discoveries enable cost reductions of 50% or more in labor and materials for residential, commercial and utility scale PV installations.

14 SOLAR ENERGY↗
DOE OSTI2021

Assessing the Consistency of Estimated Ground Cover Fractions between the BLM AIM Method and Optical Remote Sensing Method

Since 2012, Argonne National Laboratory (Argonne) has supported the Bureau of Land Management (BLM) in developing remote sensing methodologies for long-term environmental monitoring of Palo Verde Mesa in eastern Riverside County, California, including methods for: detailed mapping of ephemeral streams, estimating fractional cover of desert-land surface components (e.g., trees, shrubs, litters, and bare ground), evaluating erosion risk or land stability, and characterizing vegetation alliances using spatial structure and geostatistical approaches. These studies showed the promise of remote sensing for monitoring changes in desert landscapes by providing information that would be difficult to obtain through field surveys. During this time the BLM has also worked to establish long-term monitoring protocols and compiled field-observation data collected using standardized protocols from the Assessment, Inventory, and Monitoring (AIM) strategy. The AIM data can be compared to data derived from remote sensing methods to evaluate their relative operational utility in monitoring landscape change. If ground cover estimated using remotely sensed imagery is comparable to AIM ground cover estimates, then remote sensing can be used to monitor whether any land cover change in desert landscapes may be related to solar energy development. Therefore, the goal of this study was to determine the consistency in ground cover estimates between AIM data and those derived from publicly- available remotely sensed imagery, such as that available through the U.S. Department of Agriculture, National Agricultural Imagery Program (NAIP), to examine feasibility of a remote sensing method for complementing AIM monitoring. Based on the image analysis in this study, we also provide recommendations for how small unmanned aerial system (sUAS) data may be used to complement BLM’s AIM data and NAIP imagery for future vegetation monitoring. The ground cover types we originally planned to investigate were trees, shrubs, and bare ground. However, the small sample size and a limited range of cover fraction of trees and shrubs in the AIM dataset (e.g., 33 samples with a maximum shrub cover of 18%, 14 samples with a maximum tree cover of 17%) did not allow for performing a meaningful evaluation for the remote sensing approach. Therefore, we conducted the study focusing on bare ground, foliar, and rock cover, all of which are indicators reported in the AIM remote sensing dataset.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Grid Resiliency with a 100% Renewable Microgrid

San Diego Gas & Electric Company (SDG&E) installed America’s first and largest utility-scale microgrid in Borrego Springs in 2013. The first generation Borrego Springs Microgrid utilized diesel generators to form and stabilize the microgrid island, with support from grid-scale batteries and local solar photovoltaic (PV) generation. In this project, SDG&E in partnership with National Renewable Energy Laboratory (NREL) demonstrated through modeling, simulation and utility field testing that blackstart and islanding of the microgrid can be led with 100% renewable, inverter based resources (IBRs), to help reduce community reliance on conventional generation resources. Through equipment upgrades, grid-forming island leader capability was transitioned to a battery IBR instead of the Borrego Springs Microgrid diesel generators. A new microgrid controller was integrated to the microgrid and programmed to control and manage multiple energy storage systems. Synchrophasor and other power quality data verified autonomous, high-speed response of the IBRs through blackstart, islanding, and load step testing. Results of project field evaluations provide distribution systems operators (DSO) with increased confidence that renewable, IBR can replace traditional generators to blackstart and island microgrids and rapidly establish stable island frequency with rapid changes in peak power demand. Importantly, the project validated the integration feasibility of a distributed energy resource management system (DERMS) controller that manages multiple grid-forming and grid-following IBRs, establishing a standard design interface to reduce the complexity of integrating new DERs in the future and supporting replication by the industry. As a result of learnings in this project, SDG&E has implemented the microgrid controller strategy at multiple other microgrid sites, thereby validating the replicability of the solution. Hardware-in-the-loop (HIL) simulations including power and controller HIL hardware — along with electromagnetic transient (EMT) simulations of Borrego Springs Microgrid —informed adjustments to inverter parameters and were important to characterize the performance of the IBRs in relevant operating conditions before deployment. The EMT and HIL simulations of islanding the entire community are important contributions in providing confidence in IBR performance prior to future islanding of the community in the field. High-fidelity EMT and/or HIL simulation of IBRs can de-risk field operations, and its relevance and importance as a tool is increasing as distribution grids and microgrids become more complex and dynamic with an increasing proportion of renewable generation, distributed energy storage, and two-way power and energy flows.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2013

Low-E Retrofit Demonstration and Educational Program

The objective of this project was to demonstrate the capability of low-emissivity (low-E) storm windows / panels and low-E retrofit glazing systems to significantly and cost effectively improve the energy efficiency of both existing residential and commercial buildings. The key outcomes are listed below: RESIDENTIAL CASE STUDIES: (a) A residential case study in two large multifamily apartment buildings in Philadelphia showed a substantial 18-22% reduction in heating energy use and a 9% reduction in cooling energy use by replacing old clear glass storm windows with modern low-E storm windows. Furthermore, the new low-E storm windows reduced the overall apartment air leakage by an average of 10%. (b) Air leakage testing on interior low-E panels installed in a New York City multifamily building over windows with and without AC units showed that the effective leakage area of the windows was reduced by 77-95%. (c) To study the use of low-E storm windows in a warmer mixed climate with a balance of both heating and cooling, 10 older homes near Atlanta with single pane windows were tested with three types of exterior storm windows: clear glass, low-E glass with high solar heat gain, and low-E glass with lower solar heat gain. The storm windows significantly reduced the overall home air leakage by an average of 17%, or 3.7 ACH50. Considerably high variability in the data made it difficult to draw strong conclusions about the overall energy usage, but for heating periods, the low-E storm windows showed approximately 15% heating energy savings, whereas clear storm windows were neutral in performance. For cooling periods, the low-E storm windows showed a wide range of performance from 2% to over 30% cooling energy savings. Overall, the study showed the potential for significantly more energy savings from using low-E glass versus no storm window or clear glass storm windows in warmer mixed climates, but it is difficult to conclusively say whether one type of low-E performed better than the other. COMMERCIAL CASE STUDIES: (a) A 12-story office building in Philadelphia was retrofitted by adding a double-pane low-E insulating glass unit to the existing single pane windows, to create a triple glazed low-E system. A detailed side-by-side comparison in two pairs of perimeter offices facing north and east showed a 39-60% reduction in heating energy use, a 9-36% reduction in cooling energy use, and a 10% reduction in peak electrical cooling demand. An analysis of utility bills estimated the whole building heating and cooling energy use was reduced by over 25%. Additionally, the retrofit window temperatures were commonly 20 degrees warmer on winter days, and 10-20 degrees cooler on summer days, leading to increased occupant comfort. (b) Two large 4-story office buildings in New Jersey were retrofitted with a similar system, but using two low-E coatings in the retrofit system. The energy savings are being monitored by a separate GPIC project; this work quantified the changes in glass surface temperatures, thermal comfort, and potential glass thermal stress. The low-E retrofit panels greatly reduced daily variations in the interior window surface temperatures, lowering the maximum temperature and raising the minimum temperature by over 20F compared to the original single pane windows with window film. The number of hours of potential thermal discomfort, as measured by deviation between mean radiant temperature and ambient air temperature by more than 3F, were reduced by 93 percent on the south orientation and over two-thirds on the west orientation. Overall, the low-E retrofit led to substantially improved occupant comfort with less periods of both overheating and feeling cold. (c) No significant thermal stress was observed in the New Jersey office building test window when using the low-E retrofit system over a variety of weather conditions. The surface temperature difference only exceeded 10F (500 psi thermal stress) for less than 1.5% of the monitored time, and in all cases, the maximum surface temperature difference never exceeded 35F (1,750 psi thermal stress). LOW-E STORM WINDOW OUTREACH AND EDUCATION PROGRAM: (a) The project team assisted the State of Pennsylvania in adding low-E storm windows as a cost effective weatherization measure on its priority list for the state weatherization assistance program. (b) No technical barriers that could hinder widespread application were identified in the case studies. However, educational barriers have been identified, in that weatherization personnel commonly misunderstand how the application of low-E storm windows is very different than much more expensive full window replacement. (c) A package of educational materials was developed to help communicate the benefits of low-E storm windows and retrofits as a cost effective tool for weatherization personnel. (d) Using detailed thermal simulations, more accurate U-factor and solar heat gain coefficient (SHGC) values were determined for low-E storm windows installed over different primary windows. IN SUMMARY, this work confirmed the potential for low-E storm windows, panels, and retrofit systems to provide significant energy savings, reductions in air leakage, and improvements in thermal comfort in both residential and commercial existing buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2015

HEMS: Home Energy Management System [SWR-15-12] - Stochastic Optimal Scheduling of Residential Appliances with Renewable Energy Sources

The HEMS algorithm schedules residential appliance operation to minimize the weighted sum of occupant discomfort, total energy cost, peak electricity consumption and carbon footprint, weighted according to occupant preferences. A centralized mixed integer linear programming (MILP) based optimization approach is taken, with the HEMS managing all appliances directly, following a Model Predictive Control (MPC) methodology which determines the optimal schedule over the user-specified scheduling horizon and repeats the optimization at configurable time intervals. The HEMS is developed on the General Algebraic Modeling System (GAMS) using the MILP solver. This system is able to effectively deal with the stochasticity in the distributed system by utilizing Monte Carlo simulation where uncertainties in future electricity price, outdoor temperature, water usage, solar and wind generation can be accounted for. The HEMS controls the operation of the heating, ventilation and air conditioning (HVAC) system, water heater, refrigerator, residential batteries, electric vehicles, standalone micro combined heat and power (CHP) generator, dishwasher, washer/dryer, pool pumps, and lighting.

Pratt, Annabelle↗
DOE OSTI2014

Greenbuilt Retrofit Test House (Final Report)

The Greenbuilt house is a 1980's era house in the Sacramento area that was a prominent part of Sacramento Municipal Utility District's (SMUD) Energy Efficient Remodel Demonstration Program. The house underwent an extensive remodel, aimed at improving overall energy efficiency with a goal of reducing the home's energy use by 50%. NREL researchers performed a number of tests on the major systems touched by the retrofit to ensure they were working as planned. Additionally, SMUD rented the house from Greenbuilt Construction for a year to allow NREL to perform a number of tests on the cooling system and the water heating system. The goal of the space conditioning tests was to find the best ways to cut cooling loads and shift the summer peak. The water heating system, comprised of an add-on heat pump water heater and an integrated collector-storage solar water heater, was operated with a number of different draw profiles to see how varying hot water draw volume and schedule affected the performance of the system as a whole. All the experiments were performed with the house empty, with a simulated occupancy schedule running in the house to mimic the load imposed by real occupants.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

A Vision for Co-optimized T&D System Interaction with Renewables and Demand Response

The evolution of the power system to the reliable, effi- cient and sustainable system of the future will involve development of both demand- and supply-side technology and operations. The use of demand response to counterbalance the intermittency of re- newable generation brings the consumer into the spotlight. Though individual consumers are interconnected at the low-voltage distri- bution system, these resources are typically modeled as variables at the transmission network level. In this paper, a vision for co- optimized interaction of distribution systems, or microgrids, with the high-voltage transmission system is described. In this frame- work, microgrids encompass consumers, distributed renewables and storage. The energy management system of the microgrid can also sell (buy) excess (necessary) energy from the transmission system. Preliminary work explores price mechanisms to manage the microgrid and its interactions with the transmission system. Wholesale market operations are addressed through the devel- opment of scalable stochastic optimization methods that provide the ability to co-optimize interactions between the transmission and distribution systems. Modeling challenges of the co-optimization are addressed via solution methods for large-scale stochastic op- timization, including decomposition and stochastic dual dynamic programming.

14 SOLAR ENERGY↗
DOE OSTI2020

Accuracy of HVAC Load Predictions: Validation of EnergyPlus and DOE-2 using FLEXLAB Measurements

The aim of the project reported here was to better understand the level of accuracy of three building energy simulation (BES) engines (‘engines’) — EnergyPlus™, DOE-2.1e, and DOE-2.2 — by identifying and investigating significant deviations between the performance predicted by these engines and actual performance as measured in the FLEXLAB® test facility at Lawrence Berkeley National Laboratory (LBNL). The specific test conditions included some of those prescribed in ANSI/ASHRAE Standard 140 - Standard Method of Test for the Evaluation of Building Energy Analysis Computer Programs. Detailed measurements of FLEXLAB performance, including indoor temperatures and heat fluxes and air-flow and water flow rates and temperatures in the Heating, Ventilating and Air Conditioning (HVAC) system, together with hourly weather data, were recorded and used in analyzing the simulation results from EnergyPlus v8.8, DOE-2.2 v3.65 and DOE-2.1e v127. These engines are commonly used in the United States for building energy code compliance, federal, state, and utility incentives programs, as well as energy efficient design of new buildings and energy retrofit of existing buildings. Seven conventional overhead mixing ventilation scenarios were tested and each engine was found to have a similar level of agreement with the measurements of space-level heating and sensible cooling loads. These results provide useful information regarding the accuracy of these engines in predicting the cooling and heating load elements of whole building energy performance. This information is intended for practitioners who are concerned about transitioning between simulation tools with different engines and for managers of utility programs leveraging these tools for evaluating and/or projecting measure savings to be incentivized under their programs. The results of the comparisons of simulated and measured performance indicate that the predictions from all three engines are not significantly different. The 24-hour average value of the absolute mean bias indicates the likely magnitude of the error in any particular case. The average mean bias is reduced by cancelation of overprediction in one case by underprediction in another. The daytime absolute mean biases, which may be more important for both energy performance and occupant comfort, are ~6%, presumably because of the greater complexity involved in simulating in the presence of solar radiation. EnergyPlus typically overpredicts the cooling load and/or underpredicts the heating load by ~1.5% and the DOE-2 engines typically underpredict the cooling load by approximately the same amount. The Root Mean Square Error is relatively more sensitive to shorter term variations in the difference between predicted and measured loads; the three engines have similar values, ~10%, suggesting that the uncertainties in their predictions of peak loads may also be similar in magnitude. The implication of these results is that users, both designers and program analysts, can use EnergyPlus, DOE-2.1e, or DOE-2.2 to model conventional commercial buildings equipped with overhead mixing ventilation with a similar level of confidence. Further work is required to better understand the variability in the level of agreement between the engine predictions and FLEXLAB measurements, where a particular engine will agree well with FLEXLAB in some cases and not so well in others and another engine will agree or disagree in different cases. As the sources of this variability are identified and eliminated or reduced significantly, it is recommended that the experimental capabilities and methods developed in the study reported here should be applied to validating heating and cooling load calculations for spaces with different types of furniture and miscellaneous loads. These methods should then be applied to low energy space conditioning systems in EnergyPlus including, in particular, radiant slab and radiant ceiling panel cooling and heating systems and ‘mixed mode’ systems that combine mechanical cooling and natural ventilation systems, focusing on controls, including control of thermal mass. The work reported here addresses the conventional method of heating and cooling occupied spaces; other methods, such as the use of radiant heating and cooling systems have the potential to provide equivalent occupant comfort, or better, with lower energy consumption. These systems are addressed more explicitly in EnergyPlus but there is a need for empirical validation to give users the same level of confidence in modeling these systems that they have, or should have, in modeling conventional systems, based on the results presented here.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Solving the duck curve in a smart grid environment using a non-cooperative game theory and dynamic pricing profiles

With the intermittency that comes with electricity generation from renewables, utilizing dynamic pricing will encourage the demand-side to respond in a smart way that would minimize the electricity costs and flatten the net electricity demand curve. Determining the optimal dynamic pricing profile that would leverage distributed storage to flatten the curve is a novel idea that needs to be studied. Moreover, the economic feasibility of utilizing distributed electrical energy storage is still not given in the literature. Therefore, in this paper, a novel way of solving a citywide dynamic model using a bilevel programming algorithm is introduced. The problem is developed as a novel non-cooperative Stackelberg game that utilizes air-conditioning systems and electrical storage through the end-users to determine the optimal dynamic pricing profile. The results show that the combined effect of utilizing demand-side air-conditioning systems and distributed storage together can flatten the curve while employing the optimal dynamic pricing profile. An economic study is performed to determine the economic feasibility of 20 different cases with different battery designs and the level of solar penetration. Three metrics were used to evaluate the economic performance of each case: the levelized cost of storage, the levelized cost of energy, and the simple payback period. Most cases had levelized cost of storage values lower than 0.457 $/kWh, which is the lower bound available in the literature. Seven out of 16 cases have a simple payback period shorter than the lifetime of the system (25 years). The case with a 100 MW PV power plant and a battery storage of size 597 MWh, was found to be the most promising case with a simple payback period of 12.71 years for the photovoltaic plant and 19.86 years for the demand-side investments.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Impacts of Renewable Energy and Green Hydrogen Policies on Uttar Pradesh's Power Sector Future

This report is part of a broader program focused on supporting Indian states with long-term power system planning. More information about this program can be found at the National Renewable Energy Laboratory's "Supporting India's States With Renewable Energy Integration" web page at https://www.nrel.gov/international/india-renewable-energy-integration.html. The power sector in Uttar Pradesh, India's most populous state, is poised to transform over the next few decades due to a combination of national and state-level policies impacting both the supply and demand of electricity. The Government of Uttar Pradesh has policies and plans to develop in-state solar PV, pumped storage hydropower, and green hydrogen. Power system policymakers and utilities in Uttar Pradesh are faced with the challenges of planning a system that incorporates increasing amounts of renewable energy and storage resources, meets rising electricity demand due to economic development and green hydrogen production, and satisfies operational and reliability requirements. To support these various objectives, the National Renewable Energy Laboratory (NREL), RMI, and the Uttar Pradesh New and Renewable Energy Development Agency (UPNEDA) evaluated the least-cost pathways for the state's power sector through 2050. NREL developed a capacity expansion model that identifies investment and operational decisions for every year (2024-2050) for all of India, with detailed representation for the state of Uttar Pradesh, which can provide a framework for recurring planning studies. The main insights from this study can also help inform policy development and investment decisions.

08 HYDROGEN↗