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At least 307 records · Page 17

An Integrated Framework for Effective Management of Delivery Risk in Electricity Markets: From Batteries to Insurance and Beyond

Net load imbalances due to imperfect day-ahead forecasts can cause variability in real-time electricity prices and higher system operations costs. We propose a novel market product called Flexibility Options that allow participants to hedge uncertainty by buying flexibility from flexible resources. Simulations show that flexibility options can reduce total system operating costs by up to 15% and can reduce variability in market participant revenues. To better quantify the flexibility that DER aggregators can provide, we develop DER flexibility scores that account for asset flexibility and uncertainty from occupant behavior and weather. Preliminary results show that realistic sets of DERs have significant variability in flexibility and uncertainty metrics.

delivery risk↗

Residential Home Decarbonization Using Advanced Micro-CHP

An efficient micro-combined heat and power (CHP) prototype was developed to provide heat and electricity for single-family homes and light commercial buildings. The unit can be installed independently at the point of energy consumption. Consequently, it enables cost-effectively and flexibly matching heat and electrical loads, simplifying distribution and installation processes, and recovering and storing waste heat as hot water. The analyzed results show that the micro-CHP using natural gas as fuel achieves 10.68%–32.80% CO2 reduction in the selected five home applications. The potential effect of H2 on decarbonization of these home was also evaluated, finding that the micro-CHP using a blended fuel with H2 and natural gas can further reduce CO2 emissions. However, the 50% CO2 reduction in the micro-CHP requires at least 70%–90% of H2 in the blend with natural gas. Overall, the micro-CHP technology demonstrates a solid potential to accelerate micro-CHP adoption in residential and light commercial markets, thereby promoting broader micro-CHP acceptance and use in the future for building decarbonization.

Gao, Zhiming [ORNL] (ORCID:0000000271397995)↗

EV Charging Infrastructure Energization An Overview of Approaches for Simplifying and Accelerating Timelines to Processing EV Charging Load Service Requests

The United States has seen significant growth in electric vehicle (EV) adoption, leading to increased demand for EV charging infrastructure. Over the past decade, EV charging infrastructure site developers, site hosts, and electric distribution utilities have navigated the process to integrate chargers onto the electric grid. Site developers and site hosts have raised the alarm that the integration process for high-powered EV charging projects does not meet the needs of the EV market for timeliness or cost. High-powered charging stations typically require a load service request or an agreement with the local utility to connect to the grid. The process of energizing a new high-powered charging site can be complex and time-consuming, often taking up to 2 years. This timeline is the result of current utility energization processes having been designed for construction projects that take longer to build (i.e., buildings). The specific challenges stem from various factors, including compartmentalization in application processes, the integration of EV charging process approvals with other distributed energy resources (DERs), and the need to ensure grid reliability. The energization process needs to evolve to meet the growing demand for high-powered EV charging. This white paper compiles information gathered through various conversations with key stakeholders, including utilities, utility regulators, EV charging operators, site developers, and authorities having jurisdiction (AHJ) as well as through an extensive literature review. This document identifies the challenges and provides potential solutions to streamline the process of connecting EV charging infrastructure to the power grid in the United States, serving as a starting point for future conversations around these solutions. The solutions noted in this white paper require collaborative efforts among utilities, regulators, and EV charging infrastructure developers to streamline the grid connection process for EV charging infrastructure. They are broadly organized into four areas: 1. Increase data access and transparency: Develop automated load service request tools, integrate hosting capacity and load service request analyses, incorporate EV adoption forecasts, and provide transparency on the processing queue. 2. Improve energization processes and timing: Create fast-track options based on prescreening criteria, provide flexibility or phased approvals in the load service request/interconnection process, build internal knowledge within utilities about EV charging technologies, and provide standardized workforce training. 3. Promote economic efficiency: Right size distribution components to accurately reflect the load requirements of EV charging infrastructure, make proactive investments in grid infrastructure based on EV adoption forecasts and growth projections, and consider energy equity and environmental justice factors such as equitable access to EV charging when planning infrastructure. 4. Improve grid reliability and resilience: Use load management/power control systems (PCS) at EV charging stations, adopt and implement harmonized standards for communication protocols and information models between the EV charging and grid control infrastructure, and address cybersecurity considerations by implementing robust security measures and standards for EV charging infrastructure—with particular emphasis on clarifying the security requirements for the interface to the grid. The objective of the solutions proposed in this white paper is to accelerate the timeline and decrease costs associated with connecting EV charging infrastructure to the grid. Electric utilities, utility regulators, EV charging infrastructure developers, and site hosts will first need to understand which solutions are available in their service territory, and if warranted, which combination of solutions would support their specific needs. Through the successful implementations of solutions at scale detailed here, industry will demonstrate a new and innovative ecosystem where timely deployment and energization of EV charging infrastructure with greater grid resiliency and reliability is a reality.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Large-Scale Simulation of Regional Demand Flexibility Implementation and Customer Economic Impact

The Distribution System Operator with Transactive (DSO+T) study conducted a large-scale simulation of over 60,000 customers in a region the size of Texas to demonstrate the effective coordination of distributed energy resources (DERs) in commercial and residential buildings. The integrated simulation included both the bulk (wholesale generation and transmission) and distribution systems. The DERs (including batteries, electric vehicles, air conditioning, and water heaters) participated in a transactive energy retail market that was integrated into an existing competitive wholesale market. The engineering and economic performance of the resulting demand flexibility was evaluated over annual simulations for both moderate and high renewable generation scenarios. A detailed parametric cost model was developed to enable detailed economic analysis of key stakeholders. In addition, fixed and dynamic customer tariffs were designed and applied to the customer population. This allowed the impact on annual customer bills to be analyzed for various building types (residential versus commercial; single- versus multi-family). This paper presents results showing the relative flexibility of batteries, electric vehicles, and building loads throughout the year and under different renewable scenarios. This feeds a detailed breakdown of the impact this flexibility has on the operating costs of the grid and the resulting net economic benefit. Finally, the study showed that practically all customer classes (including non-participating customers) save money under the proposed demand flexibility scheme. The study found overall net annual economic savings of $3.3-5.0B for a region the size of Texas equating to average customer bill savings of 10-16%.

Reeve, Hayden M.↗

End-Use Savings Shapes Measure Documentation: Dispatch Schedule Generation for Demand Flexibility Measures

This supplemental document describes the methodology used for determining the dispatch timing of various EUSS demand flexibility measures. Demand flexibility measures are designed to reduce/dispatch electricity demand in buildings during especially beneficial/critical times. The method used in this work utilizes predictions of building loads to generate a schedule that reflects the periods when the building's daily peak load occurs to support decision making in demand flexibility measures. The dispatch schedule generation method described in this document creates an hourly schedule that includes a load dispatch (peak) window for each day for a whole year based on load prediction, with options using different prediction methods: perfect prediction, bin-sampling method, fixed schedule, and outdoor air temperature (OAT)-based prediction method. The perfect prediction method performs a simulation to obtain the annual load profile as predicted load, representing the scenario of perfect load prediction. The bin-sampling method (1) categorizes days into representative bins by temperature characteristics, (2) performs simulations on sample days from each of those bins to create representative (or predicted) load, and (3) assigns representative loads for all days in a year based on the bin categorization. The fixed schedule method defines uniform start and end time of peak window with assumed fixed daily peak time, for all days in a season or a year. The OAT-based prediction method uses the statistics of OAT (minimum and maximum) as the indicators of peak load, with specified delay response time from building loads to temperature. Given the load prediction, daily peak periods are determined as a time window with specified length in each day that include the predicted daily peak load and with a secondary rule such as maximizing energy saving potential. The dispatch schedule generation method is not a standalone measure and is intended to be combined with other demand flexibility measures that could leverage the peak schedule and apply demand controls on specific systems or devices for demand response, such as measures described in "Measure Documentation - Thermostat Control for Load Shedding" and "Measure Documentation - Thermostat Control for Load Shifting".

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

The value of hydropower flexibility for electricity system decarbonization

Hydropower is an abundant, dispatchable, clean energy resource that will play an important role in supporting the clean energy transition. In particular, dispatchable hydropower can provide the operational flexibility that will be required in future systems with high variable renewable energy penetrations. However, the theoretical operational flexibility of hydropower can be restricted in practice by various non-power constraints. In this paper, we quantify how increasing the operational flexibility of dispatchable hydropower resources with reservoirs impacts least-cost generation portfolios and supports power system decarbonization. Specifically, we conduct a capacity expansion analysis of a two-zone system: a hydro-dominated region and a neighboring region with aggressive decarbonization targets that are represented by the United States Pacific Northwest and California respectively. We then introduce a quantifiable index for characterizing the operational flexibility of reservoir hydropower and assess how changes in this metric impact the system-optimal generation portfolio. We find that increasing hydropower flexibility leads to more investment in wind generation, less investment in natural gas generation, lower system costs, and lower system emissions. We further demonstrate a substitution effect between the grid services provided by flexible hydropower operation, increased transmission capacity on a congested line, and energy storage resources. Finally, we show that increasing the operational flexibility of hydropower increases the effective load carrying capability of both hydropower and wind resources. This research supports a more nuanced understanding of how hydropower can support electricity system decarbonization and may motivate reassessing the cost-benefit tradeoffs of non-power constraints that restrict operational flexibility.

Capacity expansion modeling↗

Real-World Distribution System Modeling Framework for Transmission-and-Distribution Cosimulation: Preprint

This paper presents a modeling methodology for realistic distribution system simulation and analysis. The methodology involves three major approaches: utility model conversion, feeder load modeling, and feeder model validation. The feeder models obtained from the utility are converted to the format that is more flexible for analysis and algorithm development. The load profiles down to each node are modeled in detail using advanced metering infrastructure data and supervisory control and data acquisition (SCADA) system measured load data. Then the distribution system models are validated by comparing the simulated feeder-head voltage results and SCADA measured voltage data. To better understand the bulk system operations and the interactions between transmission and distribution systems, the modeled realistic distribution systems are integrated into a transmission-and-distribution cosimulation framework to perform the system simulation from the bulk system down to each node in the distribution system.

load modeling↗

High-Frequency, Multiclass Nonintrusive Load Monitoring for Grid-Interactive Residential Buildings

Smart buildings with net-load metering and control capabilities can provide valuable flexibility to grid operators. This article develops a novel approach for high-frequency, multiclass nonintrusive load monitoring (NILM) that enables effective net-load monitoring capabilities with minimal additional equipment and cost. Relative to existing NILM work, the proposed solution operates at a faster timescale, providing accurate multiclass state predictions for each 60-Hz ac cycle without relying on event-detection techniques. The approach is validated using a test bed with residential appliances and shown to have high accuracy, good generalization properties, and sufficient response time to support building grid-interactive control at fast timescales relevant to the provision of grid frequency support services.

27 ARPA - Advanced Research Projects Agency-Energy↗

Waste Glass Property Database and Data Qualification Plan

The U.S. Department of Energy vitrification facilities currently employ glass property-composition models to ensure processability of waste streams and acceptability of the final glass products. The efficiency (e.g., process flexibility, reduced down time, and reduced cost) of waste vitrification is directly tied to the size of the waste processing envelope. To increase the size of the processing envelope, a larger database was developed. The database will improve the prediction accuracy of glass properties, leading to higher waste loadings, higher waste throughput, broader process flexibility, and reduced mission life. Some of the data in this expanded database has insufficient quality assurance (QA) rigor for use in nuclear facility operation and glass qualification. A plan was developed to qualify high-value data under the appropriate QA rigor for use at the Hanford Waste Treatment and Immobilization Plant’s High-Level Waste (HLW) Facility. This qualification plan first compares the data coverage over the composition region of interest to Hanford HLW by property. Those studies that significantly improve the data coverage in the Hanford HLW glass composition region were prioritized for qualification activities. Qualification methods including QA equivalence, peer review, data corroboration, and confirmatory testing have been assigned to each high-priority study.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

High-Frequency, Multiclass Nonintrusive Load Monitoring for Grid-Interactive Residential Buildings

Smart buildings with net-load metering and control capabilities can provide valuable flexibility to grid operators. This article develops a novel approach for high-frequency, multiclass nonintrusive load monitoring (NILM) that enables effective net-load monitoring capabilities with minimal additional equipment and cost. Relative to existing NILM work, the proposed solution operates at a faster timescale, providing accurate multiclass state predictions for each 60-Hz ac cycle without relying on event-detection techniques. The approach is validated using a test bed with residential appliances and shown to have high accuracy, good generalization properties, and sufficient response time to support building grid-interactive control at fast timescales relevant to the provision of grid frequency support services.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Predictive modeling of a subcritical pulverized-coal power plant for optimization: Parameter estimation, validation, and application

As renewable power generation deployment increases, fossil fuel plants are increasingly required to operate more flexibly. Many coal-fired power plants were originally designed to operate at base load and do not operate optimally at partial load. Predictive first-principles plant-wide models can be employed to identify opportunities for flexibility improvements and diagnose low-load operating issues. This paper describes the application of the Institute for the Design of Advanced Energy Systems Integrated Platform (IDAES) to model and optimize flexible power plant operations. The key benefits of using IDAES are that it provides an open-source, fully equation-oriented modeling framework for efficient modular model construction, reuse, and customization, together with a mathematical optimization framework leveraging powerful, state-of-the-art solvers. The process systems engineering workflow from predictive process simulation to parameter estimation, model validation, and plant optimization is applicable to a variety of existing and next-generation energy systems as well as other chemical and environmental processes. Here, to demonstrate this capability, a physics-based, steady-state model was developed to improve full- and part-load performance of the Escalante Generating Station, a 245 MWe (net) subcritical pulverized coal-fired power plant owned and operated by Tri-State Generation and Transmission Association. Specifically, sixty-nine model parameters were simultaneously estimated from several months of operating data enabling prediction of flow rates, temperatures, pressures, and steam quality throughout the plant. The validated model was leveraged by Escalante to reduce the minimum operating load from 90 MW to 50 MW by diagnosing a low-load water-hammer issue, enabling coal usage and emissions reductions during periods of low power demand. Additionally, opportunities for heat rate reduction (i.e., efficiency improvement) through a steeper sliding-pressure approach to load-following and optimization of other boiler operating variables were also identified and quantified. For example, a potential efficiency improvement of 0.7 percentage points was observed at half-load operation.

01 COAL, LIGNITE, AND PEAT↗

A Simulation and Optimization Framework for Managing Wind-Driven Loading on PV Systems

As PV modules continue to trend toward larger, thinner, and more flexible forms they grow more susceptible to damage from dynamic wind loading. As a result, understanding the impact of wind on PV systems, particularly when mounted on solar-tracking hardware, and identifying robust, stable array layouts and stow strategies is becoming increasingly important for the PV community. We are developing an open-source software package, PVade (PV aerodynamic design engineering), to simulate the cascading fluid-structure interaction that occurs within solar-tracking arrays to enable researchers to test hardware, layout, and tracker control changes, leading to enhanced stability and a reduction in wind-driven damage. We will give an overview of the PVade software and present the latest outcomes from our ongoing validation campaign in which we compare statistical structural responses with field data. From there, we will present simulated results from a larger, multi-row array and highlight the effect of varying tracker angles on stability as measured by both acceleration and deformation, focusing on the stability differences between positive and negative tilt angles.

fluid structure interaction↗

Simulating Wind-Driven Loading on PV Systems

As PV modules continue to trend toward larger, thinner, and more flexible forms they grow more susceptible to damage from dynamic wind loading. As a result, understanding the impact of wind on PV systems, particularly when mounted on compliant solar-tracking hardware, and identifying robust, stable array layouts and stow strategies is becoming increasingly important for the PV community. We are developing an open-source software package, PVade (PV aerodynamic design engineering), to simulate the cascading fluid-structure interaction that occurs within single-axis, solar-tracking arrays to enable researchers to test hardware, layout, and tracker control changes, leading to enhanced stability and a reduction in wind-driven damage. We will give an overview of the PVade software and present the latest outcomes from our ongoing validation campaign in which we compare time series and statistical structural responses with field data. From there, we will present simulated results from a larger, multi-row array and highlight the effect of varying tracker angles on stability and the differences between positive and negative tilt angles.

fluid↗

Demand Response in Bangalore: Implications for Electricity System Operations

Recent Greening the Grid studies for India highlight the benefits of flexible resources for integrating variable renewable energy onto India’s electricity system. India’s ambitious renewable energy targets, which are particularly focused on renewable resource states such as Karnataka, will face fewer challenges when combined with new planning and operational strategies and technologies. This report explores one such strategy - demand response - by which the system operator shifts load throughout a day to minimize system wide production costs. To explore this strategy, we added demand response resources to Karnataka’s electricity system in a production cost model of India, using load shifting potential analyzed by Lawrence Berkeley National Labs. We then investigated the impacts of increasing demand response capacity under several renewable resource scenarios. Our results show the addition of demand response enables fuel shifting from high-marginal-cost and emissions-intensive subcritical coal and diesel generation to zero-marginal-cost and emissions-free renewable generation. Accordingly, the value that demand response provides to the system increases as the renewable penetration increases. In addition to reducing production costs and emissions, demand response reduces the time that thermal generators spend at their minimum output levels, which typically represents a less efficient and costlier operational state. Agricultural load shifting provides greater value to the system than residential, commercial, or industrial loads. Agricultural demand response is more flexible than other sectors because it is not exposed to subdaily operational constraints and it can operate for more hours per day without impacting customer satisfaction. Further, the first increment of demand response that is added to a system provides the greatest value; further additions provide additional benefits but have a decreasing impact. The insights we discuss could be leveraged by system planners and operators in other jurisdictions, particularly those facing significant renewable energy penetrations, to develop their own demand response programs.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Performance and flexibility improvements of Staged Pressurized Oxy-Combustion

Staged Pressurized Oxy-Combustion (SPOC) is a low-carbon coal combustion power technology being developed by Washington University in St. Louis (WUSTL). Oxy-combustion plants enable straightforward capture of carbon dioxide (CO 2 ) by removing most of the nitrogen in the combustion air prior to use, thereby burning fuel in near-pure oxygen instead of air, producing a flue gas containing primarily CO 2 and water. CO 2 capture at amounts > 90% is possible, often using cryogenic air separation. Oxy-combustion typically relies on flue gas recycle (FGR) to reduce the peak temperature and radiation that would otherwise occur in a fuel/oxygen only flame. SPOC reduces the peak temperatures of combustion by utilizing two or more pressurized boiler modules connected in series to produce fuel staging; hence, only a portion of the fuel is combusted in any given furnace module. This means that the thermal energy released at each stage can be captured and removed from the gases prior to subsequent stages, when more fuel is introduced. This allows the SPOC process to operate with minimal FGR, avoiding the associated efficiency losses and additional costs. Also, the process operates at an elevated gas-side pressure, reducing boiler size, enhancing heat transfer to achieve a compact boiler configuration as compared to an atmospheric-pressure boiler design, and allowing for recovery of the latent heat of the water from the flue gas at a temperature useful to the steam cycle. The resultant net efficiency of the system is over 3 percentage points greater than traditional atmospheric-pressure oxy-combustion, and 7 percentage points greater than the post combustion variant, representing a step-change improvement over first-generation capture technologies. To further develop the concept, WUSTL and the Electric Power Research Institute, Inc., organized a project with American Air Liquide, Inc., Doosan Babcock Limited, and the U.S. Department of Energy to investigate a practicable and workable boiler design. The team has identified the potential for enhanced process flexibility for controlling power generation over a wider load range than is normally available to conventional coal-fired power plants due to the staged nature of the heat release. With increasing intermittent renewable generator contribution, on-demand generators need to be highly flexible to participate in the future energy market, requiring extensive operation at reduced load. Conventional coal-fired steam generators typically face challenges in maintaining temperature control of the reheat steam and main steam at reduced loads. This results in inefficient operation, both in terms of the boiler efficiency and steam turbine heat rate. The results of this project show the SPOC process is capable of exceptional turndown, both on a stage basis and with the ability to bypass entire stages. Oxygen-supply flexibility was also investigated, as this is also a key consideration for the overall flexibility of the SPOC process given the operating constraints of conventional air separation units. A boiler design concept assessment was conducted and was focused on delivering compact and constructible design. The assessment checked appropriate tube operating metal temperatures at full load and at lower operating loads, balanced against the needs of efficient coal combustion, and the resultant slagging and ash environments. Combustion testing in the 100-kWth pressurized combustion test rig at WUSTL was carried out to validate the combustion, heat flux profiles and burnout at multiple loads. Combustion parameters investigated were flame stability, fuel burnout, ash composition, radiative heat flux, and temperature profiles. The results of these tests formed the basis of a full-scale boiler design that will encompass improvements in both efficiency and flexibility over conventional oxy-combustion processes. The air separation unit flexibility was investigated, and associated cost implications were addressed. Detailed economic assessment results for a 550 MWe net power block are also provided, allowing for a comparison against the baseline NETL oxy-combustion and post combustion capture cases.

20 FOSSIL-FUELED POWER PLANTS↗

Factors Influencing Grid-connected Heat Pump Water Heater Performance in the Southeast U.S.

Grid-connected heat pump water heaters (HPWH) can shift electrical load while minimizing impacts to hot water availability for occupants. This capability provides a flexible grid resource to utilities seeking to manage peak loads Such load control also can feasibly improve renewable utilization within the utility electric production mix, for instance using off-peak generation during periods with high renewable energy generation. It also offers lower electric bills to customers through increased energy efficiency of HPWH and cuts greenhouse gas emissions. In particular, the Southeast U.S. due to its high penetration of electric water heating presents a promising opportunity for grid-connected HPWHs. This paper builds upon the results of an extensive HPWH load shifting field study conducted in 51 occupied homes in Florida using EcoPort technology (Butzbaugh et al, 2022). In 2022, only an initial evaluation was available. Here, long term load results are available as well as examination of various control strategies and influences. Analysis is conducted for HPWH energy use and load shifting performance based on home occupancy (i.e., low and high) and water heater location (i.e., conditioned and unconditioned) across different temperature profiles. An unexpected outcome of this analysis was the poor performance of HPWHs located in conditioned spaces, possibly because of inadequate air volume from improper installation. We did find higher demand reductions from 2-hour load ups and slightly improved for critical peak signals in the afternoon control periods. As expected, higher occupancy households showed great load reductions.

Fenaughty, Karen↗

Graph Neural Networks for Surrogate Modeling of Offshore Floating Platforms

Floating offshore wind turbines (FOWTs) present an significant opportunity to increase renewable energy generation. However, significant challenges remain before FOWTs can be widely commercialized and deployed. In particular, hydrodynamic loading on the platforms can stress the overall structure, damage the mooring systems, and impact power generation. Studying these loads is difficult and often relies on computationally expensive models or experiments. In this work, we explore the use of graph neural networks (GNNs) to construct flexible, data-driven surrogates for hydrodynamic loads on platforms. We leverage the natural graph-like structure of offshore wind platform designs to enable the GNN model to learn to approximate the loads for different wave conditions and structural designs. We demonstrate potential uses for the surrogate by performing parameter sweeps and ridge analysis on the trained model to identify the impacts of different wave and structural features on the loads.

floating offshore wind turbines↗

Field tests of a highly flexible downwind ultralight rotor to mimic a 13-MW turbine rotor

Offshore extreme-scale turbines of 20–25 MW in size may offer reduced energy costs. The technical barriers at these extreme scales include escalating blade masses with increased flexibility as well as high gravity loads and tower-strike issues. These barriers may be addressed with a load-aligning downwind turbine. To investigate this type of design, a field test campaign was conducted with an aeroelastically scaled rotor, termed the Segmented Ultralight Morphing Rotor Demonstrator (SUMR-D). The tests were conducted on the Controls Advanced Research Turbine at the National Renewable Energy Laboratory. The paper gives an overview of the experimental diagnostics, blade design, and results of the field campaign, as well as makes conclusions and recommendations regarding extreme-scale highly flexible downwind rotors.

17 WIND ENERGY↗