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At least 199 records · Page 11

High-Resolution Synthetic Solar Irradiance Sequence Generation: An LSTM-Based Generative Adversarial Network

The rapid growth of renewable energy resources penetration is bringing more challenges to power system planning and operation. Relevant renewable energy integration studies, such as the capability and dynamic performance of inverter-based resources' primary frequency response and fast frequency response, require high-resolution renewable generation output data that are representative of renewable energy resources. This paper focuses on creating synthetic but realistic solar irradiance data and proposes a long short-term memory-based generative adversarial network to generate high-resolution (second-level) solar irradiance sequences from low-resolution (minute-level) measurements. Combined with a classifier to recognize the solar irradiance patterns, the proposed model is trained using multi-loss functions to accurately capture the temporal correlations among both high-resolution and low-resolution sequences. Verification of the proposed approach is performed on the data set of the Oahu Solar Measurement Grid collected through the National Renewable Energy Laboratory. The results of the case studies demonstrate the proposed approach's capability to capture the statistical characteristics of different solar irradiance patterns and to generate high-quality synthetic solar irradiance sequences in high resolution.

dynamic scheduling↗

Guest Editorial: Special issue on flexible and resilient urban energy systems

This guest editorial summarizes the topics and the papers selected for the Special Issue on Flexible and Resilient Urban Energy Systems. After rigorous reviewing process, 21 papers are accepted for publication. These 21 accepted papers cover various aspects of urban energy systems and are distributed as following: situational awareness of urban energy systems (2 papers), quantification metrics of flexibility and resilience of urban energy systems (3 papers), vulnerability modeling of urban energy systems under various extreme events (3 papers), planning of flexible and resilient urban energy systems (4 papers), robust and resilient operation and control of urban energy systems (4 papers), recovery and restoration strategy of urban energy systems (2 papers), and coordination and interoperability of interconnected energy systems (3 papers). The Guest Editorial Board hopes this Special Issue can provide a valuable information for future research and advancements in the field of flexible and resilient urban energy systems.

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Joint Planning of Electricity Transmission and Hydrogen Transportation Networks

The abundance and uneven distribution of renewable energy might cause congestion and curtailment in electric power systems. Transmission expansions can potentially alleviate transmission congestion and reduce renewable energy curtailment. On the other hand, with the substantial cost reduction of electrolyzer technology and the continuing rise of hydrogen demand, converting surplus renewable energy to hydrogen provides synergistic benefits to power and hydrogen systems, but consequently requires joint planning of the two systems. To this end, we propose a joint planning approach for power transmission and hydrogen transportation networks to coordinately optimize the investment and operation of power and hydrogen infrastructure. In our proposed model, detailed truck routing, pipeline, and hydrogen storage are formulated to quantify the flexibility of hydrogen transportation system. A robust joint planning approach is also proposed to address various uncertainties from renewable energy, electric load, and hydrogen demand. Furthermore, our numerical simulations show that the proposed joint planning model can save the total system cost, reduce renewable energy curtailment, and increase the utilization level of transmission lines.

08 HYDROGEN↗

Connecting Minds: AI Use Cases to Bridge Power Systems and Large Language Models for Practical Applications

Recent advances in artificial intelligence (AI) and development of large language models (LLMs) present the opportunity to develop a new generation of power systems applications. In contrast with early power system AI applications based on structured numerical data, LLMs offer unique capabilities to perform logical reasoning using text documents, unstructured data, and application programming interface (API) calls to computational software. This paper seeks to bridge the knowledge gap between power systems engineers and LLM developers through a crosscutting explanation of use cases, characteristics, requirements, practical considerations from the perspectives of both LLM capabilities and industry needs. Specific focus is given to applications that can be realistically deployed by electric utilities. After introducing the architecture of LLMs and unique challenges of the power systems domain, this paper proposes twenty representative LLM applications grouped into categories of 1) power system operations, 2) asset management, 3) system planning and analytics, and 4) energy management and protection systems. Five use cases are presented within each category with descriptions of the motivation, objectives, approaches, example inputs / outputs, and benefits of each use case.

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Transmission Planning with Renewable Energy Zones (REZ): Overview, Select Case Studies, and Key Enablers

The renewable energy zone (REZ) transmission planning process is a proactive method to plan, approve, and build transmission infrastructure that connects high-quality and large-scale renewable resources to the power system. This presentation was developed for a technical side event focused on transmission systems to facilitate the rapid decarbonization of power systems at the Clean Energy Ministerial Senior Officials Meeting in March 2023. This document contains a synthesis of key REZ case studies throughout the world and is intended as a resource for policymakers and energy planners.

Australia↗

IRES Microgrid Energy Integration Report Version 1.0

This report presents technical information and guidance for the planned Integrated Renewable Energy System (IRES) microgrid project. This deployment of the microgrid and its associated assets was initiated in the beginning of 2022 at the Marine and Coastal Research Laboratory (MCRL) facility of Pacific Northwest National Laboratory (PNNL)-Sequim, Washington. The information in the report is organized under two main focus areas: electrical power interface, or interconnection, information of planned IRES assets; and communication and control interface, or interoperability, information of the planned IRES assets. The information will provide technical input for the development of the IRES microgrid controller technical specification, and also provide input for PNNL’s evaluation of adequacy of the electrical service infrastructure at MCRL to support the IRES project and help identify any gaps that will require facility-based upgrades. From an R&D aspect, this study and report will build on PNNL’s research and development work relating to energy storage (ES) codes and standards (C&Ss), including hybrid systems, performed on behalf of the Department of Energy (DOE) Office of Electricity (OE) ES. The current state of C&Ss for advanced technologies and their application, including microgrid-based technology is limited. For cases where formal standards issued by recognized Standards Developing Organizations do not yet exist, guidance is provided based on emerging best practices, including industry-group references that can be leveraged for microgrid technology which is in its early stages of development and use.

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Hybrid Electric Transit Bus

A government, industry, and university cooperative is developing an advanced hybrid electric city transit bus. Goals of this effort include doubling the fuel economy compared to current buses and reducing emissions to one-tenth of current EPA standards. Unique aspects of the vehicle's power system include the use of ultra-capacitors as an energy storage system, and a planned natural gas fueled turbogenerator developed from a small jet engine. Power from both the generator and energy storage system is provided to a variable speed electric motor attached to the rear axle. At over 15000 kg gross weight, this is the largest vehicle of its kind ever built using ultra-capacitor energy storage. This paper describes the overall power system architecture, the evolution of the control strategy, and its performance over industry standard drive cycles.

Viterna, Larry A.↗

Hydrogen Transportation and Distributed Energy Systems Risk and Feasibility Assessment for Airport Facilities - CRADA 555 (Abstract)

This CRADA presents the strategy that Pacific Northwest National Laboratory (PNNL) and Sandia National Laboratories (SNL) will take to support PDX in performing a risk assessment for several hydrogen deployment scenarios. It is intended that the deployment of hydrogen at PDX could serve several roles, including decarbonizing its bus fleet and building out a distributed energy system which could also be used to facilitate emergency operations. PDX’s initial plans concern replacing their current fleet of 28 busses with FCEBs. To do so, PDX will need to deploy the hydrogen systems needed to support the buses. This includes hydrogen storage, production, delivery, filling, compression, and maintenance. PDX also has long range plans to build a distributed energy system to support normal and resilient operations. This study will investigate the risks of each plan individually, and a combined plan which serves both. Additionally, PDX is in an area with the potential for high seismic activity, as such this work will also include a seismic risk assessment. A detailed risk assessment using PDX as a test case is necessary to ensure the deployment of large-scale hydrogen is successful and to understand the benefits or drawbacks in contrast to electric only technologies. Many technologies have been proposed that claim to utilize hydrogen for both transportation and distributed energy systems; however, these technologies need to be analyzed as they apply to an actual site. The physical infrastructure and hydrogen use cases for PDX will be analyzed, a risk assessment will be performed on the hydrogen infrastructure and distributed energy system. These assessments will be useful for understanding how each of these technologies would perform as applied to a large public facility and public safety. The results of this CRADA, and an impact of the DOE funding, will evaluate hydrogen as a key fuel for PDX and will accelerate by several years availability of hydrogen, fuel cells, and other low-carbon technologies.

08 HYDROGEN↗

Using Time Series Data Products to Support ASHRAE’s Historic and Future Climate Data Needs through NASA’s POWER Web Services

To address the data needs for resilience and sustainability of building systems within ASHRAE, the NASA Prediction of Worldwide Energy Resource (POWER) project facilitates the use of NASA Earth Science data on a long-term, global scale. Solar data from several NASA projects and meteorological data from NASA assimilation models have been reformatted and disseminated to the public via a user friendly web GIS-enabled based data portal (https://power.larc.nasa.gov) in selectable data formats, immediately amenable to key industry wide decision support tools such as EnergyPlus. Time series of potential climate conditions from downscaled climate simulations are being made available for similar statistics and formats. An emphasis is placed upon obtaining and utilizing time series data to conduct analysis of building system performance for current and planning building systems for energy savings and greenhouse gas emissions. This presentation has the learning following learning objectives for the ASHRAE community: 1) Learn how NASA POWER’s web service suite can provide supplementary solar and surface meteorological data parameters, including a discussion of uncertainty. 2) Learn how downscaled climate scenario information can be provided to evaluate potential future requirements. The presentation is part of a forum entitled, "Weather Data for Large-Scale Building Energy Modeling".

time series↗

Capacity Density Considerations for Floating Offshore Wind Farms in Ultradeep Waters

Capacity density describes the concentration of wind energy development in an area and is often specified in terms of megawatts-per-square-kilometer (MW/km2). Understanding capacity density trends in wind energy projects helps to inform both energy system and spatial planning efforts. Borrman et al. (2018) and Mulas Hernando et al. (2023) analyze capacity density trends for fixed-bottom offshore wind farms in Europe and the United States, respectively, and Cooperman et al. (2022) explores how floating offshore wind mooring technology choices may impact wind plant layout through setbacks from lease area boundaries in waters up to 1,300 m deep. Technical challenges facing floating offshore wind development in ultradeep waters (beyond 1,300 m) could impact achievable capacity densities, with potential implications to marine spatial planning and project economics. When compared to fixed-bottom commercial-scale wind farms, mooring system footprints from floating offshore wind systems can constrain capacity density in some circumstances. In this study, we conduct an initial investigation of how taut mooring configurations may constrain floating offshore wind turbine placement and estimate capacity density for representative floating wind plants in generic lease areas. In addition, we explore floating wind plant capacity density drivers in ultradeep waters by characterizing area utilization for a range of lease area characteristics. This analysis highlights the primary challenges that floating offshore wind systems may encounter in achieving capacity densities comparable to commercial-scale fixed-bottom projects at ultradeep water depths, from a technical standpoint.

capacity density↗

North American Renewables Integration Study (NARIS): Cooperative Research and Development Final Report, CRADA Number CRD-16-00633

The goal of the study is to help inform and assist power system planning entities, electricity system operators, government energy agencies, legislators and regulators to better understand the planning, engineering, operational, and economic implications of integrating large amounts of wind, solar and hydro energy into the Canadian, US and Mexican electrical systems.

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Improving Transparency in Electric Distribution System Planning to Support Affordability [Slides]

This resource identifies opportunities for communities to participate in the distribution system planning process to achieve their energy goals, including affordability. It begins with background information on the distribution system and distribution system planning, and then focuses on topical areas where communities could focus their engagement (e.g., non-wires alternatives, DER forecast, scenario analysis). The report concludes with illustrative examples of how communities have engaged in distribution system planning. The appendix provides procedural guidance on engagement in utility planning processes.

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A novel approach for large-scale wind energy potential assessment

Increasing wind energy generation is central to grid decarbonization, yet methods to estimate wind energy potential are not standardized, leading to inconsistencies and even skewed results. This study aims to improve the fidelity of wind energy potential estimates through an approach that integrates geospatial analysis and machine learning (i.e., Gaussian process regression). We demonstrate this approach to assess the spatial distribution of wind energy capacity potential in the Contiguous United States (CONUS). We find that the capacity-based power density ranges from 1.70 MW/km2 (25th percentile) to 3.88 MW/km2 (75th percentile) for existing wind farms in the CONUS. The value is lower in agricultural areas (2.73 ± 0.02 MW/km2, mean ± 95 % confidence interval) and higher in other land cover types (3.30 ± 0.03 MW/km2). Notably, advancements in turbine manufacturing could reduce power density in areas with lower wind speeds by adopting low specific-power turbines, but improve power density in areas with higher wind speeds (>8.35 m/s at 120m above the ground), highlighting opportunities for repowering existing wind farms. Wind energy potential is shaped by wind resource quality and is regionally characterized by land cover and physical conditions, revealing significant capacity potential in the Great Plains and Upper Texas. The results indicate that areas previously identified as hot spots using existing approaches (e.g., the west of the Rocky Mountains) may have a limited capacity potential due to low wind resource quality. Improvements in methodology and capacity potential estimates in this study could serve as a new basis for future energy systems analysis and planning.

Dai, Tao↗

Grid Resilience to Extreme Events (ResiliEX 2.0)

The Grid Resilience to Extreme Events (ResiliEX) 2.0 workshop, co-hosted by Pacific Northwest National Laboratory and Seattle City Light, was held at the Seattle City Hall April 23–25, 2024. This is the second workshop of its kind, with the first one having occurred in Seattle in November 2022. Participants from the second workshop hailed from research organizations, utilities, professional associations, consultants, government organizations, and communities. The purpose of the workshop was to Connect scientists, energy professionals, and policy experts to build knowledge and partnerships Advance the understanding of the science of extreme events and application to the energy system Promote grid planning and engineering that addresses the increasingly complex interdependencies as society combats the climate crisis Understand the role of different decision-makers and policymakers in increasing and accelerating grid resilience Identify new approaches, processes, and structures that should be pursued to increase grid resilience to extreme events.

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High-Resolution WRF-Based Downscaling of Earth System Model Projections for Energy Applications across CONUS

Evaluating energy resources under future scenarios requires meteorological information that adequately resolves regional-scale variability and is suitable for regional energy system studies. Although Earth system model (ESM) outputs provide essential large-scale context, their coarse resolution and inherent biases limit direct use in energy system applications. This work presents a high-resolution dynamical downscaling framework using the Weather Research and Forecasting (WRF) model to generate energy-relevant regional fields for future scenarios over the contiguous United States (CONUS). The framework first identifies an optimal WRF configuration through sensitivity experiments, then evaluates raw and bias-corrected ESM initial and boundary conditions, with soil moisture and soil temperature bias correction implemented as an integral component of the bias-corrected ESM atmospheric forcing prior to WRF dynamical downscaling to improve land-atmosphere interactions. Simulations performed at 4-km resolution show that uncorrected ESM forcing leads to systematically dry and cold soil states, which propagate into elevated near-surface air temperature and solar irradiance biases, particularly during summer for the period 2000-2014. Incorporating bias-corrected atmospheric forcing together with soil state bias correction substantially reduces these errors and improves the representation of surface energy processes in WRF simulations. The results highlight the importance of bias-aware initialization strategies in high-resolution dynamical downscaling for future energy system analysis and planning.

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