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At least 361 records · Page 20

Deliverable Flexible Ramping Products Considering Spatiotemporal Correlation of Wind Generation and Demand Uncertainties

Flexible ramping products (FRPs) have been implemented by several independent system operators (ISOs) to procure adequate flexible resources. Currently, system operators estimate the system level ramping requirements ignoring the spatiotemporal correlations among various uncertainty sources. This leads to overestimates/underestimates of ramping requirements. In addition, the explicit FRPs model considers only the generation ramping limitation. Other security constraints, such as the transmission limits, are not considered, which leads to deliverability issues of FRPs. To deal with these shortcomings of current FRPs models, this paper proposes a deliverable FRPs based on a distributionally-robust chance constrained multi-interval optimal power flow (DRCC-MIOPF) considering the spatiotemporal correlation of wind power and demand uncertainties endogenously. Furthermore, an asymmetrical affine policy (AAP) is proposed to leverage generation flexibility and mitigate the uncertainty in different directions. The pricing mechanism of the FRPs is proposed using a novel uncertainty-contained locational marginal price (U_LMP) which is derived from the proposed AAP-DRCC-MIOPF model. New components representing the price of FRPs are added into the traditional LMP formulation. Finally, the PJM 5-bus, IEEE 39-bus and IEEE 118-bus systems case studies validate the proposed FRPs approach. The payment of uncertain demand and wind power on FRPs are analyzed.

electricity market↗

dGen™ (Distributed Generation Market Demand Model) [SWR-17-09]

The Distributed Generation Market Demand (dGen™) model is a geospatially rich, bottom-up, market-penetration model that simulates the potential adoption of distributed energy resources (DERs) for residential, commercial, and industrial entities in the continental United States through 2050. The National Renewable Energy Laboratory (NREL) developed dGen to analyze the key factors that will affect future market demand for distributed solar, wind, storage, and other DER technologies in the United States within a single modeling platform. The dGen model builds on, extends, and provides significant advances over NREL’s SolarDS model (Denholm et al. 2009), which is now deprecated. All Authors and Contributors are alphabetized in the Developers section with Authors of Code listed first, followed by Contributors and do not reflect equal contributions.

Sigrin, Benjamin↗

dGen™ (Distributed Generation Market Demand Model) [SWR-17-09]

The Distributed Generation Market Demand (dGen™) model is a geospatially rich, bottom-up, market-penetration model that simulates the potential adoption of distributed energy resources (DERs) for residential, commercial, and industrial entities in the continental United States through 2050. The National Renewable Energy Laboratory (NREL) developed dGen to analyze the key factors that will affect future market demand for distributed solar, wind, storage, and other DER technologies in the United States within a single modeling platform. The dGen model builds on, extends, and provides significant advances over NREL’s SolarDS model (Denholm et al. 2009), which is now deprecated.

Preus, Robert↗

On-demand indistinguishable single photons from an efficient and pure source based on a Rydberg ensemble

Single photons coupled to atomic systems have shown to be a promising platform for developing quantum technologies. Yet a bright on-demand, highly pure, and highly indistinguishable single-photon source compatible with atomic platforms is lacking. In this work, we demonstrate such a source based on a strongly interacting Rydberg system. The large optical nonlinearities in a blockaded Rydberg ensemble convert coherent light into a single collective excitation that can be coherently retrieved as a quantum field. We simultaneously observe a fully single-mode (spectral, temporal, spatial, and polarization) efficiency up to 0.098(2), a detector-background-subtracted g ( 2 ) = 5.0 ( 1.6 ) × <#comment/> 10 − <#comment/> 4 , and indistinguishability of 0.980(7), at an average photon production rate of 1.18 ( 2 ) × <#comment/> 10 4 s − <#comment/> 1 . All of these make this system promising for scalable quantum information applications. Furthermore, we investigate the effects of contaminant Rydberg excitations on the source efficiency and observed single-mode efficiencies up to 0.18(2) for lower photon rates. Finally, recognizing that many quantum information protocols require a single photon in a fully single mode, we introduce metrics that take into account all degrees of freedom to benchmark the performance of on-demand sources.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A Conceptual Framework to Describe Energy Efficiency and Demand Response Interactions

Energy efficiency (EE) and demand response (DR) resources provide important utility system and ratepayer benefits. At the same time, the rapid change in the amount and type of variable renewable energy, like solar and wind, is reshaping the role and economic value of EE and DR, and will likely affect time-dependent valuation of EE and DR measures. Utilities are increasingly interested in integrating EE and DR measures and technologies (as well as other distributed energy resources) as a strategic approach to improve their collective cost-effectiveness and performance. However, the specific EE and DR features that may be best integrated, the interplay between changing EE and DR resource potential, and the resulting utility system impacts, are not well understood. We develop a framework to identify the EE and DR attributes, system conditions, and technological factors that are likely to drive interactions between EE and DR. We apply the framework to example measures with different technology specifics (e.g., presence of controls, building type, and targeted end use) in the context of different system conditions (e.g., peak demand, load-building periods during high renewable generation output). Ultimately, the framework defines EE and DR interactions not only by the change in discretionary load (i.e., DR potential) but also by the change in likelihood of participation in EE and DR programs—as well as the change in system need for, and the overall availability of, EE and DR resources. The framework is intended to improve the integration of EE and DR in utility operational and planning activities.

24 POWER TRANSMISSION AND DISTRIBUTION↗

The Demand-Side Opportunity: The Roles of Distributed Solar and Building Energy Systems in a Decarbonized Grid

Building energy systems represent a significant and largely untapped demand-side grid resource. Buildings use about 75% of electricity in the United States, including around 80% of peak demand, meaning that changes in building energy use have significant implications for grid operations. Building energy technologies-including energy-efficient devices, flexible loads, and energy storage-can be coordinated and aggregated to perform similar functions as centralized grid assets. Recent advances in information and communication (ICT) technologies have significantly improved building energy technology automation, coordination, and aggregation capabilities. With declining costs and technological advances, building energy systems can increasingly compete with conventional grid assets such as natural gas plants. Building energy technologies enable the deployment of distributed solar photovoltaics (DPV). Energy-efficient buildings allow DPV to meet greater shares of building load while flexible loads and energy storage can reshape building load profiles to optimize the on-site use of DPV. Optimized on-site use of DPV increases the value proposition for DPV adoption and can help utilities cost-effectively integrate higher levels of DPV penetration. Together, DPV and building energy technologies could help grids achieve deep decarbonization more quickly and cost-effectively.

14 SOLAR ENERGY↗

The Highly Integrated Vehicle Ecosystem (HIVE): A Platform for Managing the Operations of On-Demand Vehicle Fleets

This paper introduces the Highly Integrated Vehicle Ecosystem (HIVE), a transportation modeling tool developed by within the Center for Integrated Mobility Sciences (CIMS) group at the National Renewable Energy Laboratory (NREL). HIVE is an agent-based supply/demand model for Mobility on Demand (MoD) which mixes agent-based modeling and centralized dispatch for automated and human-driven fleets and ride hail passengers. Research questions using HIVE span multiple categories, including intelligent fleet planning (assessing fleet, battery, and infrastructure investment decisions), intelligent fleet control (charge management, vehicle dispatching) and strategic business model decision-making (depot-based full-time drivers versus gig-based drivers, human-driven versus automated). The components of the HIVE model are explained and then HIVE is demonstrated in a case study using demand data from the New York City Taxi & Limousine Commission data set.

33 ADVANCED PROPULSION SYSTEMS↗

The Demand for a Domestic Offshore Wind Energy Supply Chain

In March of 2021, the Biden-Harris Administration established a National Offshore Wind Target to install 30 GW by 2030. This ambitious goal was not only intended to help reduce dependencies on fossil fuels, but also represents an opportunity to establish a new and sustainable industry in the United States. The announcement referenced the potential benefits of establishing a domestic supply chain, including the opportunity for existing suppliers to produce thousands of components while creating tens of thousands of jobs over the course of the decade. This vision by the Biden-Harris Administration aligns with the perspective of the offshore wind industry. At a Leadership 100 event hosted by the Business Network for Offshore wind in 2019, offshore wind developers and manufacturers identified the need for a roadmap outlining a pathway to a domestic supply chain as the top priority facing the industry. Building up domestic manufacturing capabilities will not only energize local industries but can potentially de-risk individual project by reducing reliance on importing resources from European or Asian markets. Although establishing a domestic supply chain will require significant investment, it has the potential to create substantial benefits throughout the industry and, by extension, on the decarbonization goals of the United States. This study characterizes the challenges and opportunities facing the growth of a domestic supply chain industry and evaluates the potential benefits that could be achieved through the creation of the supply chain. This report is the first of a two-part series which will describe the full supply chain roadmap and the associated benefits; the current report focuses on the high-level deployment, workforce, and component requirements that need to be met to achieve the National Offshore Wind Target. We will present: 1. A deployment pipeline that demonstrates the pathway to 30 GW, the associated demand for major fixed-bottom and floating offshore wind components (turbines, foundations, cables, substations), and the vessel and port requirements to support these installation activities. 2. A series of sensitivity analyses showing how the demand for components, ports, and vessels changes for different technology pathways and availability of the global supply chain. 3. An estimate of the total number of jobs that would be required to support these deployment scenarios under varying levels of assumed domestic content. 4. A comprehensive list of the Tier 1, 2, and 3 components (finished components, subassemblies, and subcomponents) required to construct fixed-bottom and floating offshore wind projects. 5. A discussion of critical path components that represent a significant challenge, bottleneck, or risk for a future domestic supply chain.

17 WIND ENERGY↗

Peak Demand Limiting and Optimization of HVAC Systems for Common Areas in High-Rise Multi-Family Housing (CRADA 518)

This project aims to create an innovative energy saving solution that is affordable and easy to implement. Initially, the proposed solution will fulfill an existing need for HVAC systems that serve multi-family housing. However, the solution can be easily expanded to other markets such as large hospitals, hotels, and commercial buildings. The proposed solution will be creatively packaged so that it can work where peak demand charge is high or where goal is to conserve energy and reduce carbon footprint. Of course, both Peak Demand Limiting (PDL) and Set-point optimization (SPO) can also operate simultaneously.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Assessing the Interactive Impacts of Energy Efficiency and Demand Response on Power System Costs and Emissions

Utilities are increasingly interested in integrating energy efficiency (EE) and demand response (DR) measures and technologies (as well as other distributed energy resources) as a strategic approach to improve their cost-effectiveness and performance. However, the specific EE and DR features that may be best integrated, the interplay between changing EE and DR resource potential, and resulting utility system impacts are not well understood. We quantify the impacts of EE and DR in isolation and in combination on bulk power system costs and emissions based on changes in generation expansion, transmission expansion, and dispatch patterns. The study methodology mimics utility resource planning and uses more novel techniques to select least-cost generation and transmission capacity from supply-and demand-side resources, as compared to more commonly used utility approaches that only consider supply-side resources. The results identify key EE and DR characteristics affecting each other’s power system value and the most valuable technologies and strategies that can be jointly deployed. We discuss implications for EE and DR cost-effectiveness frameworks, program design, and integrated resource planning.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Impact of Mass Wood Walls on Building Energy Use, Peak Demand, and Thermal Comfort

Thermal mass moderates indoor temperatures, allowing the heating, ventilation, and air conditioning (HVAC) system to operate more efficiently during peak hours. Cross-Laminated Timber (CLT) and other mass wood products provide thermal mass to the building envelope in a lighter and more environmentally friendly form than concrete. However, the influence of CLTs on heating and cooling energy, peak energy demand, and the indoor climate is not well-known. This project was formed to find the energy efficiency benefits of mass timber structures. The objectives were to (1) test the thermal performance of insulated mass wall structures in controlled laboratory conditions, (2) validate simulation models to expand performance to natural climatic conditions, (3) isolate the impact of the thermal properties of wood (thermal mass, thermal conductivity, moisture storage) on heating and cooling energy use and peak energy demand, and to optimize the performance. Currently, the designs used for CLT buildings have focused on structural and fire issues, and they do not consider the thermal mass benefits. Therefore, the thermal performance is not necessarily optimized.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

The use of price-based demand response as a resource in electricity system planning

Utilities have conducted IRP for decades to consider both supply- and demand-side resources to meet bulk power system needs. More recently, an increasing number of states are requiring regulated utilities to file plans that identify distribution system needs, including DERs that can avoid or defer certain types of traditional utility investments cost-effectively. Price-based demand response (DR) is an underutilized resource that could substantially contribute to load flexibility. We find that evaluation of price-based DR as a solution to meet identified electricity system needs is uncommon at both planning processes. Where price-based DR is considered as a solution, methodologies are often deficient in the characterization and treatment of this resource. Based on our analysis of utility filings and state requirements, this brief provides recommendations for improving consideration of price-based DR in the context of long-term planning for bulk power and distribution systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Retrofitting Buildings with Solar-Reflective Roofs and Walls and its Impact on Peak Power Demand

Buildings are a major consumer of electricity in the United States and a significant portion of the consumption comes from heating, ventilation, and air-conditioning (HVAC) applications. Passive cooling strategies in the building envelope help to reduce the energy consumption for HVAC as well as peak electricity demand. Although being one of the most cost-effective passive cooling strategies, modern reflective roofing and reflective exterior wall technology is not well documented for its impact on peak demand. This study utilized whole building energy simulations on residential and commercial building prototype models to quantify the impact of cool roofs and cool exterior walls. The analysis was performed in three climate zones with varying insulation levels and solar reflectances for roofs and exterior walls. For both the residential and commercial buildings, the baseline building had a roof solar reflectance value of 0.10 and an exterior wall solar reflectance value of 0.25. The results from the simulations show that roofs and exterior walls with higher reflectance values increase cooling energy savings but can also increase heating energy consumption. The impact of changes in solar reflectances was greater in buildings with low roof/wall insulation levels compared to roofs/walls with higher insulation levels. A baseline for the simulations was set with the roof and exterior wall solar reflectances set at 0.1 and 0.25, respectively and simulations having varying roof and exterior wall thermal resistances were compared to the baselines.

14 SOLAR ENERGY↗

Moving Beyond Direct Load Control: A Maturity Model for Realizing the Promise of Demand Flexibility

This report discusses a new maturity model that regulators and utilities can use to guide and expand demand flexibility programs and enable the resources to provide more grid services. The model has six demand flexibility categories: planning and design; customer engagement; program operations; evaluation, measurement and verification; distributed energy resource orchestration; and data infrastructure. Within each category, capabilities are identified and described on a maturity scale that ranges from performing below expectations to improving on best practices.

24 POWER TRANSMISSION AND DISTRIBUTION↗

ATEAM4Py: An Efficient and Scalable Python-Based Model for Charging Demand

This report details the development and implementation of ATEAM4Py, a Python-based simulation model that projects demand for battery electric vehicle (BEV) charging based on adoption trends and consumer behavior. With Exelon’s support, Argonne National Laboratory converted the original Java-based Agent-based Transportation Energy Analysis Model (ATEAM) into Python, resulting in a faster and more efficient tool for forecasting the timing, location, and scale of charging demand growth. ATEAM4Py tackles key challenges in simulation efficiency and runtime, supporting the strategic development of cost-effective grid capacity expansion strategies and ensuring reliable service for stakeholders.

33 ADVANCED PROPULSION SYSTEMS↗

Dynamic Capacitive Wireless Power Transfer System for Electric Vehicles (CRADA Final Report)

Road transportation accounts for 23% of our nation's total energy consumption, 59% of our petroleum consumption and 22% of our total emissions. Electric vehicles (EVs) have much higher well-to-wheel efficiency compared to gasoline vehicles and can reduce our dependence on oil, minimize emissions, improve local air quality and provide a platform for technological innovation and economic growth. While major progress has been made in the development of electric vehicles, their penetration remains under 1 The main hurdles in their widespread adoption are high cost, limited range and long charging times, due to limitations in battery technology. An approach to overcome these hurdles is to substantially reduce the on-board energy storage and instead deliver power wirelessly to the vehicle while it is in motion dynamic wireless power transfer (WPT). For EV charging applications, researchers have traditionally focused on inductive WPT. An issue with inductive WPT systems is that for magnetic flux guidance and shielding, they require ferrite cores, making them expensive, bulky and difficult to embed in the roadway. Under an ARPA-E IDEAS grant, the CU Boulder team has recently developed an alternative approach to WPT based on capacitive coupling that is much smaller, lighter, less expensive, and easier to embed in the roadway than inductive WPT; and have demonstrated a 1.2-kW 6.78-MHz version of this capacitive WPT system on a stationary platform. Under this seed grant program, preliminary work will be carried out on a dynamic capacitive WPT system to prepare a strong proposal for the ARPA-E OPEN 2018 FOA.

33 ADVANCED PROPULSION SYSTEMS↗

Demand response roadmap for the New Jersey Board of Public Utilities [Slides]

The New Jersey Board of Public Utilities (BPU) requested technical assistance from Berkeley Lab to inform its strategy for advancing demand response through its demand-side program planning process. Berkeley Lab developed this roadmap to delineate milestones for the portfolio's development and to identify the utility investments and BPU actions that achieve those milestones.

24 POWER TRANSMISSION AND DISTRIBUTION↗