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At least 253 records · Page 14

High-resolution climate model datasets for energy infrastructure planning in a renewable-dependent future

Electrification and renewables deployment efforts are amplifying the interdependence of the climate and energy systems. Increases in climate model resolution, which is now approaching that of reanalysis datasets and operational weather forecast models, present a unique opportunity to use future climate projections for energy infrastructure planning. In this Perspective, we review recent developments in high-resolution climate modeling, which have been driven by increased computing power and advanced software tools. We then look ahead to discuss how high-resolution climate data can be used to plan for a renewable-dependent future, and envision a unified climate-energy model framework that captures the two-way feedbacks between these interdependent systems.

climate change↗

Voltage positioning using co-optimization of controllable grid assets in radial networks

With increasing penetration of solar PV, some distribution feeders are experiencing highly variable net-load flows and even reverse flows. To optimize distribution systems under such conditions, the scheduling of mechanical devices, such as OLTCs and capacitor banks, needs to take into account forecasted solar PV and actual grid conditions. However, these legacy switching assets are operated on a daily or hourly timescale, due to the wear and tear associated with mechanical switching, which makes them unsuitable for real-time control. Therefore, there is a natural timescale- separation between these slower mechanical assets and the responsive nature of inverter-based resources. In this paper, we present a network admissible convex formulation for holistically scheduling controllable grid assets to position voltage optimally against solar PV. An optimal hourly schedule is presented that utilizes mechanical resources to position the predicted voltages close to nominal values, while minimizing the use of inverter-based resources (i.e., DERs), making them available for control at a faster time-scale (after the uncertainty reveals itself). A convex, inner approximation of the OPF problem is adapted to a mixed-integer linear program that minimizes voltage deviations from nominal (i.e., maximizes voltage margins). Here, the resulting OPF solution respects all the network constraints and is, hence, robust against modeling simplifications. Simulation based analysis on IEEE distribution feeders validates the approach.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Impact of Transport Electrification Demand and Charging Schedules on Electricity Markets and Nuclear Generators

As the U.S. pursues deep decarbonization targets, electric vehicles (EVs) are likely to become a major driver of demand growth and a major determinant of daily demand patterns. This study analyzes a possible future ERCOT-like electricity grid, and examines the impact of different types of EV charging schedules on grid and market outcomes. This analysis demonstrates the significant impact of EV charging patterns on capacity expansion simulations. Even without EVs, the overall daily demand profile in a market can have significant impacts on prices and grid stability in that system, especially if non-dispatchable renewable generators (e.g. wind and solar) make up a significant fraction of the generation mix. EV demand will not necessarily follow this preexisting demand profile, so its daily trends may significantly change what generation portfolio would optimally serve the system. Furthermore, the effects of EV demand can alter the profitability of different types of units, by altering the frequency of market events like extreme-demand hours or zero-price hours. These effects are explored in this study. The EV demand levels were derived from MARKAL simulations of the West-South-Central North American Electric Reliability Corporation (NERC) region for the year 2050, using a carbon tax of $100/ton. The baseline MARKAL simulation forecasted that 23% of the region’s annual electricity demand in 2050 would be attributable to EVs, and broke out demand projections for EV and non-EV end-use in that year. To model lower EV penetration into the system, an additional case was explored which assumed that EVs only achieved 75% of the demand level projected by MARKAL.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Mir Cooperative Solar Array Flight Performance Data and Computational Analysis

The Mir Cooperative Solar Array (MCSA) was developed jointly by the United States (US) and Russia to provide approximately 6 kW of photovoltaic power to the Russian space station Mir. The MCSA was launched to Mir in November 1995 and installed on the Kvant-1 module in May 1996. Since the MCSA photovoltaic panel modules (PPMs) are nearly identical to those of the International Space Station (ISS) photovoltaic arrays, MCSA operation offered an opportunity to gather multi-year performance data on this technology prior to its implementation on ISS. Two specially designed test sequences were executed in June and December 1996 to measure MCSA performance. Each test period encompassed 3 orbital revolutions whereby the current produced by the MCSA channels was measured. The temperature of MCSA PPMs was also measured. To better interpret the MCSA flight data, a dedicated FORTRAN computer code was developed to predict the detailed thermal-electrical performance of the MCSA. Flight data compared very favorably with computational performance predictions. This indicated that the MCSA electrical performance was fully meeting pre-flight expectations. There were no measurable indications of unexpected or precipitous MCSA performance degradation due to contamination or other causes after 7 months of operation on orbit. Power delivered to the Mir bus was lower than desired as a consequence of the retrofitted power distribution cabling. The strong correlation of experimental and computational results further bolsters the confidence level of performance codes used in critical ISS electric power forecasting. In this paper, MCSA flight performance tests are described as well as the computational modeling behind the performance predictions.

Kerslake, Thomas W.↗

Dynamical Downscaling of Earth System Model Data for Energy System Analysis

Assessing energy resources (e.g., solar, wind, and hydro) under future scenarios requires datasets with sufficient spatial and temporal detail to capture variability and extreme events. While global-scale Earth System Model (ESM) projections are widely used, their coarse resolution limits direct application to regional energy system analyses. Dynamical downscaling offers a robust approach to generate physically consistent, fine-scale datasets that better represent local atmospheric processes impacting energy resources. In this work, we present a two-stage approach for producing high-resolution historical and future projections over the contiguous United States (CONUS). First, we optimize the Weather Research and Forecasting (WRF) model configuration for energy-relevant variables - solar irradiance, wind speed, and precipitation - by conducting ERA5-driven simulations at 8-km and 28-km resolution. Multiple physics schemes and model configurations within the WRF are evaluated against observational datasets including the National Solar Radiation Database (NSRDB), the Parameter-elevation Regressions on Independent Slopes Model (PRISM), and the Stage IV multi-radar/multi-sensor precipitation product for the CONUS domain. Using the best-performing configuration, we dynamically downscale MPI-ESM1-2-HR simulations for 2000-2060 under SSP2-4.5 and SSP5-8.5 scenarios at 4-km spatial and hourly temporal resolution. This presentation will provide a comprehensive analysis of the results from multiple numerical experiments and high-resolution ESM projections. In addition, we will discuss potential applications of our high-resolution datasets within the energy sector and outline future research avenues dedicated to evaluating how extreme weather events influence system performance and resilience.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A Model for Evaluating the Configuration and Dispatch of PV Plus Battery Power Plants

An open-source model was developed to optimize energy storage operation for photovoltaic- (PV-) plus-battery systems with AC-coupled and DC-coupled configurations. It includes the ability to use forecast energy prices to optimize battery charge and discharge on a rolling time horizon. The model allows for exploration of different configurations, including capital costs, inverter performance, dispatch flexibility, and capturing otherwise clipped energy for the DC-coupled system. The model can run 20 full years of hourly data in approximately two seconds, allowing comparison of a large number of configurations. We applied the model in a test case demonstrating reduced inverter clipping for DC-coupled systems and yielded slightly higher overall value than AC-coupled systems, with an approximately 2 percent increase in internal rate of return or benefit/cost ratio. Our results show that at current estimated prices for lithium-ion battery systems, large-scale PV-plus-battery plants are economically viable under the right conditions, with the configuration playing a role in system flexibility and performance. This model provides the ability for project developers, industry professionals, and researchers to use readily available software to quickly evaluate and design these systems.

41 EE - Solar Energy Technologies Office (EE-4S)↗

The Use of Satellite-Measured Aerosol Optical Depth to Constrain Biomass Burning Emissions Source Strength in a Global Model GOCART

Small particles in the atmosphere, called "atmospheric aerosol" have a direct effect on Earth climate through scattering and absorbing sunlight, and also an indirect effect by changing the properties of clouds, as they interact with solar radiation as well. Aerosol typically stays in the atmosphere for several days, and can be transported long distances, affecting air quality, visibility, and human health not only near the source, but also far downwind. Smoke from vegetation fires is one of the main sources of atmospheric aerosol; other sources include anthropogenic pollution, dust, and sea salt. Chemistry transport models (CTMs) are among the major tools for studying the atmospheric and climate effects of aerosol. Due to the considerable variation of aerosol concentrations and properties on many temporal and spatial scales, and the complexity of the processes involved, the uncertainties in aerosol effects on climate are large, as is featured in the latest report of Intergovernmental Panel on Climate Change (IPCC) in 2007. Reducing this uncertainty in the models is very important both for predicting future climate scenarios and for regional air quality forecasting and mitigation. During vegetation fires, also called biomass burning (BB) events, complex mixture of gases and particles is emitted. The amount of BB emissions is usually estimated taking into account the intensity and size of the fire and the properties of burning vegetation. These estimates are input into CTMs to simulate BB aerosol. Unfortunately, due to large variability of fire and vegetation properties, the quantity of BB emissions is very difficult to estimate and BB emission inventories provide numbers that can differ by up to the order of magnitude in some regions. Larger uncertainties in data input make uncertainties in model output larger as well. A powerful way to narrow the range of possible model estimates is to compare model output to observations. We use satellite observations of aerosol properties, specifically aerosol optical depth, which is directly proportional to the amount of aerosol in the atmosphere, and compare it to the model output. Assuming the model represents aerosol transport and particle properties correctly, the amount of BB emissions determines the simulated aerosol optical depth. In this study, we explore the regional performance of 13 commonly used emission estimates. These are each input to global Goddard Chemistry Aerosol Radiation and Transport (GOCART) model. We then evaluate how well each emission estimate reproduces the smoke aerosol optical depth measured by the MODIS instrument. We compared GOCART-simulate aerosol optical depth with that measured from the satellite for 124 fire cases around the world during 2006 and 2007. We summarize the regional performance of each emission inventory and discuss reasons for their differences by considering the assumptions made during their development. We also show that because stronger wind disperses smoke plumes more readily, in cases with stronger wind, a larger increase in emission amount is needed to increase aerosol optical depth. In quiet, low-wind-speed environments, BB emissions produce a more significant increase in aerosol optical depth, other things being equal. Using the region-specific, quantitative relationships derived in our paper, together with the wind speed obtained from another source for a given fire case, we can constrain the amount of emission required in the model to reproduce the observations. The results of this paper are useful to the developers of BB emission inventories, as they show the strengths and weaknesses of individual emission inventories in different regions of the globe, and also for modelers who use these inventories and wish to improve their model results.

Petrenko, Mariya↗

Intermediate-mass Early-type Disk Galaxies in the Virgo Cluster. II. Near-Infrared Spectra and Evidence for Differences in Evolution

We discuss near-infrared (NIR) slit spectra of six early-type disk galaxies in the Virgo Cluster that were examined previously at visible/red wavelengths. Despite having similar intrinsic luminosities, colors, and morphologies, the NIR spectrophotometric properties of these galaxies indicate that they are not a homogeneous ensemble differing only in terms of luminosity-weighted age and metallicity. While the depth of the CO(2,0) band is consistent with the centers of these galaxies having solar or slightly sub-solar luminosity-weighted metallicities, galaxy-to-galaxy variations in the depth of the Na i 2.21 μm doublet are found, with Na i2.21 μm lines in three galaxies (NGC 4491, NGC 4584, and NGC 4620) that are deeper than those predicted for a solar chemical mixture and a solar-neighborhood mass function. In contrast, the Ca i2.26 μm triplet shows good galaxy-to-galaxy agreement but tends to be deeper than the model prediction. Considering the depth of the NaD lines, the deep Na i2.21 μm lines are tentatively attributed to a bottom-heavy mass function. This is counter to observed trends between mass function slope and velocity dispersion, and so the possibility of a super-solar [Na/Fe] is also discussed. Two of the three galaxies with deep Na i 2.21 μm (NGC 4584 and NGC 4620) have Sérsic exponents that are consistent with a classical bulge. As for NGC 4491, its central NIR spectrum contains prominent emission lines. The relative strengths of Brγ and H{sub 2}S(1), the presence of [Fe ii] emission, and the mid-infrared spectral-energy distribution are all consistent with intense recent star formation near the center of that galaxy. The NIR spectrum of NGC 4584 is devoid of line emission in the NIR, suggesting that star formation does not power the emission detected at visible wavelengths from that galaxy. Wavelengths that contain the Ballick–Ramsey C{sub 2} band at 1.76 μm are matched by moderately metal-poor E-MILES model spectra with an age of 2 Gyr. The radial age trends in these galaxies are in the opposite sense to those in late-type disk galaxies, and it is concluded that they have evolved in a cluster environment for at least several Gyr.

79 ASTRONOMY AND ASTROPHYSICS↗

Day-ahead continuous double auction-based peer-to-peer energy trading platform incorporating trading losses and network utilisation fee

Integration of distributed energy resources, such as photovoltaic solar (PV), introduces new opportunities to establish local energy market frameworks to improve renewable energy utilisation in residential sectors. Such peer-to-peer (P2P) energy trading refers to a local market structure where customers (and prosumers) interact to share excess PV generation to enhance the individual and community social welfare. In this work, a day-ahead continuous double auction (CDA)-based P2P market structure considering network losses and network utilisation fees was designed. Day-ahead PV energy is modelled using fractional integral polynomials and the output is forecasted using an autoregressive integrated moving average model for each market interval. Based on the customer load and excess PV energy, the CDA market is cleared using a bid/ask matching mechanism. The performance of the P2P market was evaluated by computing different welfare metrics while analysing the effect of network constraints. The results show that the designed CDA-based P2P market structure increases the social welfare of all participants by an average of 17.75% compared to the baseline for the presented cases. Moreover, the impact of the forecasting error between the day-ahead and real-time market was also quantified.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Technoeconomic Analysis Round Robin of a Retrofit of the Ivanpah Concentrating Solar Plant with a Molten-Salt System with Thermal Energy Storage

While the fidelity of technoeconomic analysis (TEA) models for concentrating solar thermal systems has improved in recent years, there is a lack of consensus on the specific inputs used to forecast performance of a newly built tower system due to a lack of validations and post-mortems available to the public. This effort is a joint initiative between multiple international organizations to validate and compare their TEA models. The specific case study is a proposed retrofit of one unit of the Ivanpah Solar Energy Generating System to include molten-salt storage, replacing the steam generation system with a molten-salt receiver, salt-to-steam heat exchanger train, and new balance of plant while keeping the existing steam turbine, solar field, and interconnection in place, using plant data for calibration. This manuscript discusses several of the agreed-upon assumptions for this study as well as a preliminary analysis from prior work that motivates the study.

14 SOLAR ENERGY↗

AquaPV: Regulatory and Environmental Considerations for Floating Photovoltaic Projects Located on Federally Controlled Reservoirs in the United States

To meet the nation's decarbonization goals, the U.S. Department of Energy's Solar Futures study forecasts that installed solar photovoltaic (PV) capacity must increase nearly tenfold, from 80 gigawatts (GW) in 2020 to approximately 760 GW cumulative installed capacity by 2035. Ground-mounted PV is expected to dominate future solar deployment and will require more than 3.5 million acres of land to meet annual demand projections (of nearly 45 GW) by 2030. However, various competing demands for land (e.g., agricultural production, conservation) and high land acquisition costs in specific locations could be challenges to meeting future PV demand solely with ground-mounted PV deployment. Floating photovoltaics (FPV) may be an alternative in locations where ground-mounted PV is not feasible and aid in reaching the nation's PV deployment and decarbonization goals. FPV is a newer siting approach in which a PV array is affixed to a floating apparatus and sited on a water body like a reservoir behind a dam. FPV systems may be stand-alone or co-located at new or existing hydroelectric facilities or pumped storage hydropower (PSH) facility reservoirs. Co-located FPV systems may or may not be operationally paired and work in tandem with the hydroelectric or PSH facility. This report provides novel analysis to understand the opportunities and challenges associated with developing stand-alone and co-located FPV projects on reservoirs in the United States. Specifically, the report explores potential environmental and energy benefits and environmental impacts associated with the siting, construction, and operation of FPV projects. The report also identifies and analyzes U.S. federal- and state-issued permits and authorizations required by federal laws to understand the licensing pathways and regulatory requirements for FPV projects sited on reservoirs licensed by the Federal Energy Regulatory Commission and on powered and non-powered reservoirs owned by the Bureau of Reclamation or U.S. Army Corps of Engineers.

13 HYDRO ENERGY↗

AquaPV: Regulatory and Environmental Considerations for Floating Photovoltaic Projects Located on Federally Controlled Reservoirs in the United States

To meet the nation's decarbonization goals, the U.S. Department of Energy's Solar Futures study forecasts that installed solar photovoltaic (PV) capacity must increase nearly tenfold, from 80 gigawatts (GW) in 2020 to approximately 760 GW cumulative installed capacity by 2035. Ground-mounted PV is expected to dominate future solar deployment and will require more than 3.5 million acres of land to meet annual demand projections (of nearly 45 GW) by 2030. However, various competing demands for land (e.g., agricultural production, conservation) and high land acquisition costs in specific locations could be challenges to meeting future PV demand solely with ground-mounted PV deployment. Floating photovoltaics (FPV) may be an alternative in locations where ground-mounted PV is not feasible and aid in reaching the nation's PV deployment and decarbonization goals. FPV is a newer siting approach in which a PV array is affixed to a floating apparatus and sited on a water body like a reservoir behind a dam. FPV systems may be stand-alone or co-located at new or existing hydroelectric facilities or pumped storage hydropower (PSH) facility reservoirs. Co-located FPV systems may or may not be operationally paired and work in tandem with the hydroelectric or PSH facility. This report provides novel analysis to understand the opportunities and challenges associated with developing stand-alone and co-located FPV projects on reservoirs in the United States. Specifically, the report explores potential environmental and energy benefits and environmental impacts associated with the siting, construction, and operation of FPV projects. The report also identifies and analyzes U.S. federal- and state-issued permits and authorizations required by federal laws to understand the licensing pathways and regulatory requirements for FPV projects sited on reservoirs licensed by the Federal Energy Regulatory Commission and on powered and non-powered reservoirs owned by the Bureau of Reclamation or U.S. Army Corps of Engineers.

ENERGY PLANNING, POLICY, AND ECONOMY,SOLAR ENERGY↗

AquaPV: Regulatory and Environmental Considerations for Floating Photovoltaic Projects Located on Federally Controlled Reservoirs in the United States

To meet the nation's decarbonization goals, the U.S. Department of Energy's Solar Futures study forecasts that installed solar photovoltaic (PV) capacity must increase nearly tenfold, from 80 gigawatts (GW) in 2020 to approximately 760 GW cumulative installed capacity by 2035. Ground-mounted PV is expected to dominate future solar deployment and will require more than 3.5 million acres of land to meet annual demand projections (of nearly 45 GW) by 2030. However, various competing demands for land (e.g., agricultural production, conservation) and high land acquisition costs in specific locations could be challenges to meeting future PV demand solely with ground-mounted PV deployment. Floating photovoltaics (FPV) may be an alternative in locations where ground-mounted PV is not feasible and aid in reaching the nation's PV deployment and decarbonization goals. FPV is a newer siting approach in which a PV array is affixed to a floating apparatus and sited on a water body like a reservoir behind a dam. FPV systems may be stand-alone or co-located at new or existing hydroelectric facilities or pumped storage hydropower (PSH) facility reservoirs. Co-located FPV systems may or may not be operationally paired and work in tandem with the hydroelectric or PSH facility. This report provides novel analysis to understand the opportunities and challenges associated with developing stand-alone and co-located FPV projects on reservoirs in the United States. Specifically, the report explores potential environmental and energy benefits and environmental impacts associated with the siting, construction, and operation of FPV projects. The report also identifies and analyzes U.S. federal- and state-issued permits and authorizations required by federal laws to understand the licensing pathways and regulatory requirements for FPV projects sited on reservoirs licensed by the Federal Energy Regulatory Commission and on powered and non-powered reservoirs owned by the Bureau of Reclamation or U.S. Army Corps of Engineers.

ENERGY PLANNING, POLICY, AND ECONOMY,SOLAR ENERGY↗

Planning Roadmap for DER Integration in India: Industry Best Practices and Resource Guide

Ensuring safe, reliable, cost-effective DER integration at scale requires holistic planning, broad stakeholder engagement, and should address key development areas such as standards adoption, equipment testing and certification, interoperability and cybersecurity, interconnection procedures, and advanced forecasting and DER management. Each of these areas currently represent significant challenges for utilities, regulators, OEMs, developers, and even consumers worldwide. India has already seen significant growth of DERs and has announced targets for substantial growth yet to come, with the potential for DERs to make up a non-negligible portion of the country's overall generation capacity. As such, it is of critical importance that Indian stakeholders consider the potential impacts of wide-spread adoption of DERs and take preemptive action related to the five development areas listed here, among others. India should consider strategies including the adoption of key DER standards related to interconnection, testing, and cybersecurity; enabling effective and secure communication channels for DER interoperability; testing and certifying DER equipment in accredited testing laboratories; building robust, streamlined interconnection procedures; and revamping legacy system planning structures to incorporate DERs in a holistic planning framework.

24 POWER TRANSMISSION AND DISTRIBUTION↗

High-Resolution ESM Projections for Energy Applications Over the CONUS

Assessing energy resources under future scenarios requires high-resolution meteorological information that is physically consistent and suitable for regional-scale analysis. While Earth system model (ESM) projections provide valuable large-scale information, their coarse resolution and systematic biases limit direct applicability for energy system modeling and planning. In this study, we develop a high-resolution dynamical downscaling framework based on the Weather Research and Forecasting (WRF) model to translate global-scale ESM data into energy-relevant regional projections over the contiguous United States (CONUS). The framework identifies an optimized WRF configuration through numerical experiments and evaluates raw and bias-corrected ESM initial and boundary conditions, with soil moisture (SM) and soil temperature (ST) bias correction implemented as an integral part of the bias-corrected ESM forcing to improve land-atmosphere coupling prior to WRF dynamical downscaling. Using an optimized WRF configuration at 4-km resolution, we show that raw ESM forcing introduces systematic dry and cold soil biases that propagate into pronounced warm biases in near-surface air temperature and positive biases in solar irradiance, particularly during summer. Applying bias-corrected atmospheric forcing together with bias-corrected SM and ST substantially reduces these downstream biases and improves the surface energy balance and near-surface atmospheric fields. These results demonstrate that bias-aware treatment of initial conditions is critical for producing high-resolution downscaled projections suitable for energy system modeling and planning applications.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Modeling Needs to Support the Reconstruction Strategy of Ukraine

Ukraine has been facing difficult times. Russia started a full-scale invasion on February 24, 2022, and has caused huge human and infrastructure losses. As a result of the invasion, more than 8 million people left their homes. The Russian army has targeted Ukrainian energy sources, destroying or damaging over 50% of thermal power generation capacity (coal and gas), 30% of solar generation, and 90% of wind generation. The Russians are also threatening Ukrainian energy security, as they currently control the Zaporizhzhia nuclear power plant – Europe’s largest. In addition, Russia has destroyed 121,000 buildings, including 5,300 multistory buildings - more buildings than Ukraine built during the past five years. The occupiers destroyed or damaged 343 district heat boiler stations (destroyed 12 / damaged 331) and 8 CHPs (destroyed 4/ damaged 4). There is no doubt that Ukraine will be able to protect its sovereignty and restore its territorial integrity; however, this will be a long process. The Government of Ukraine needs to simultaneously focus on many issues, from waging war to the restoration of electricity, water, and heat supply in the territories close to the front line. In addition to these time-sensitive issues, the government also needs to plan a long term multi-sector strategy for the reconstruction of Ukraine’s economy. Ukraine initiated a broad-based political process for recovery at the International Ukraine Recovery Conference (URC 2022) in Lugano, Switzerland. Prior to URC 2022, Ukraine applied for EU membership on February 28 and was granted the status of candidate country by the European Council on June 23, 2022. More than 40 nations are fully committed to supporting Ukraine throughout its path from early to long-term recovery. In addition, these countries link a successful recovery to Ukraine’s European future (URC, 2022a). The reconstruction process will be long. The government also recognizes that it is not enough to build energy infrastructure back – it should be built back better. The government is committed to building a more sustainable and cleaner energy sector. Energy modeling can provide important insights into paths to decarbonize Ukraine’s economy while rebuilding it after the war. Pacific Northwest National Laboratory (PNNL) and the Institute for Economics and Forecasting of the National Academy of Sciences of Ukraine (IEF) work on modeling decarbonization scenarios in the energy sector of Ukraine. The teams focus on the heat sector, which includes district heat, autonomous and individual heating, and energy consumption by final energy consumption sectors, including buildings. Since the teams use world-class integrated assessment models, other sectors will be analyzed as well. The purpose of the document is to describe the needs of key Ukrainian ministries in modeling the reconstruction process. The scope of this document is limited to modeling energy consumption by the power and heat sectors, final energy consumption by buildings, and GHG emissions from these two sectors. The rest of this policy memo is organized as follows. After this introduction, Chapter 2 discusses key provisions of the reconstruction strategy with a focus on energy, buildings, heat supply, environment, and European integration aspirations. Section 3 provides an overview of recent developments and key decisions of the Government of Ukraine in the area of energy efficiency and decarbonization. Finally, Section 4 provides key suggestions on how PNNL and IEF can help the Government of Ukraine in developing strategic documents.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Bias Correction and Statistical Downscaling of Future Solar Irradiance Projections Using the NSRDB

Assessing renewable energy resources under future climate scenarios has been highlighted to understand potential impacts of future climate change in renewable generation on the power sector. Climate model projection has been recognized by the renewable energy community as a useful data set to analyze the impacts of future climate change on renewable resources. However, future climate projections generated from general circulation models (GCMs) contain inherent biases that need to be corrected for accurate analysis of future projections of climate variables. In addition, the coarse spatiotemporal resolution of GCMs needs to be improved for regional climate studies. In this work, we develop statistical methods to downscale future projections of global horizontal irradiance (GHI) in a computationally efficient way. Our approach builds statistical downscaling models that correct bias of climate projection of GHI and downscale the future GHI projection from daily-scale to hourly-scale. The National Solar Radiation Database (NSRDB) is used to calibrate the statistical models and validate the downscaled GHI projections across the contiguous United State (CONUS). Preliminary results show that the statistical approach efficiently downscales climate projections of GHI with a nBIAS of 3%, nMAE of 34 % and nRMSE of 46% calculated against NSRDB for CONUS. This study describes the implemented methodology and initial results as well as future research to create high-resolution climate data sets for solar energy applications.

analytical models↗