PNNL-CIM-Tools/EASY-CIM
Extracting Attributes in a Simple DictionarY of CIM (EASY-CIM) is a python library to reduce the time and burden of model queries using simplified data representations of CIM power system models.
Anderson, Alex↗
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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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ADMS State of the Industry and Gap Analysis
An Advanced distribution management system (ADMS) is a platform for optimized distribution system operational management. This platform comprises of distribution management system (DMS) applications, supervisory control and data acquisition (SCADA), outage management system (OMS), and distributed energy resource management system (DERMS). One of the primary objectives of this work is to study and analyze several ADMS component and auxiliary systems. All the important component and auxiliary systems, SCADA, GISs, DMSs, AMRs/AMIs, OMSs, and DERMS, are discussed in this report. Their current generation technologies are analyzed, and their integration (or evolution) with an ADMS technology is discussed. An ADMS technology state of the art and gap analysis is also presented. There are two technical gaps observed. The integration challenge between the component operational systems is the single largest challenge for ADMS design and deployment. Another significant challenge noted is concerning essential ADMS applications, for instance, fault location, isolation, and service restoration (FLISR), volt-var optimization (VVO), etc. There are a relatively small number of ADMS application developers as ADMS software platform is not open source. There is another critical gap and while not being technical in nature (when compared the two above) is still important to consider. The data models currently residing in utility GIS systems are either incomplete or inaccurate or both. This data is essential for planning and operations because it is typically one of the primary sources from which power system model are created. To achieve the full potential of ADMS, the ability to execute acute Power Flow solution is an important pre-requisite. These critical gaps are hindering wider Utility adoption of an ADMS technology. The development of an open architecture platform can eliminate many of these barriers and also aid seamless integration of distribution Utility legacy systems with an ADMS.
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Preliminary Findings of the South Africa Power System Capacity Expansion and Operational Modelling Study: Preprint
Wind and solar power contract prices have recently become cheaper than many conventional new-build alternatives in South Africa and trends suggest a continued increase in the share of variable renewable energy (vRE) on South Africa's power system with coal technology seeing the greatest reduction in capacity, see 'Figure 6: Percentage share by Installed Capacity (MW)' in [1]. Hence it is essential to perform a state-of-the-art grid integration study examining the effects of these high penetrations of vRE on South Africa's power system. Under the 21st Century Power Partnership (21CPP), funded by the U.S. Department of Energy, the National Renewable Energy Laboratory (NREL) has significantly augmented existing models of the South African power system to investigate future vRE scenarios. NREL, in collaboration with Eskom's Planning Department, further developed, tested and ran a combined capacity expansion and operational model of the South African power system including spatially disaggregated detail and geographical representation of system resources. New software to visualize and interpret modelling outputs has been developed, and scenario analysis of stepwise vRE build targets reveals new insight into associated planning and operational impacts and costs. The model, built using PLEXOS, is split into two components, firstly a capacity expansion model and secondly a unit commitment and economic dispatch model. The capacity expansion model optimizes new generation decisions to achieve the lowest cost, with a full understanding of capital cost and an approximated understanding of operational costs. The operational model has a greater set of detailed operational constraints and is run at daily resolutions. Both are run from 2017 through 2050. This investigation suggests that running both models in tandem may be the most effective means to plan the least cost South African power system as build plans seen to be more expensive than optimal by the capacity expansion model can produce greater operational cost savings seen only in the operational model.
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1.2.2.404 – Improving the Representation of Hydropower in Production Cost Models
This project's goal is to improve hydropower's representation in power system models by actively coupling river basin (hydrologic) models with grid operations (production cost) models. Near term, this work provides a foundation that allows improved available flexibility and operational constraints representation. Longer term, the work will provide a template that can be used by commercial production cost modeling software vendors to capture the nuances of hydropower operations in their software offerings.
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Guest Editorial High Performance Computing (HPC) Applications for a More Resilient and Efficient Power Grid
The power grid has been evolving over the last 120 years, but it is seeing more changes in this decade and next than it has seen over the past century. In particular, the widespread deployment of intermittent renewable generation, smart loads and devices, hierarchical and distributed control technologies, phasor measurement units, energy storage, and widespread usage of electric vehicles will require fundamental changes in methods and tools for the operation and planning of the power grid. The resulting new dynamic and stochastic behaviors will demand the inclusion of more complexity in modeling the power grid. Solving such complex models in the traditional computing environment will be a major challenge. Along with the increasing complexity of power system models, the increasing complexity of smart grid data further adds to the prevailing challenges. In this environment, the myriad of smart sensors and meters in the power grid increase by multiple orders of magnitude, so do the volume and speed of the data. The information infrastructure will need to drastically change to support the exchange of enormous amounts of data as smart grid applications will need the capability to collect, assimilate, analyze and process the data, to meet real-time grid functions. High performance computing (HPC) holds the promise to enhance these functions, but it is a great resource that has not been fully explored and adopted for the power grid domain.
Huang, Zhenyu Henry↗
Building Highly Detailed Synthetic Electric Grid Data Sets for Combined Transmission and Distribution Systems
Not Available
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Open dynamic simulation dataset of the Texas 2000-bus synthetic power system on ANDES [SWR-25-110]
An open-source power system model (Texas2k), running on an open-source dynamic simulator (ANDES), designed to lower barriers for machine-learning studies of power systems.
Peng, Jiangkai [National Renewable Energy Laborato↗
Transforming the U.S. Market with a New Application of Ternary-Type Pumped-Storage Hydropower Technology: Preprint
As the deployment of wind and solar technologies increases at an unprecedented rate across the United States and in many world markets, the variability of power output from these technologies expands the need for increased power system flexibility. Energy storage can play an important role in the transition to a more flexible power system that can accommodate high penetrations of variable renewable technologies. This project focuses on how ternary pumped storage hydropower (T-PSH) coupled with dynamic transmission can help this transition by defining the system-wide benefits of deploying this technology in specific U.S. markets. T-PSH technology is the fastest responding pumped hydro technology equipment available today for grid services. T-PSH efficiencies are competitive with lithium-ion (Li-ion) batteries, and T-PSH can provide increased storage capacity with minimal degradation during a 50-year lifetime. This project evaluates T-PSH for grid services ranging from fast frequency response (FFR) for power system contingency events and enhanced power system stability to longer time periods for power system flexibility to accommodate ramping from wind and solar variability and energy arbitrage. In summary, this project: Compares power grid services and costs, including ancillary services and essential reliability services, for T-PSH and conventional pumped storage hydropower (PSH) - Evaluates the dynamic response of T-PSH and PSH technologies and their contribution to essential reliability services for grid stability by developing new power system model representations for T-PSH and performing simulations in the Western Interconnection - Evaluates production costs, operational impacts, and energy storage revenue streams for future power system scenarios with T-PSH focusing on time frames of 5 minutes and more - Assesses the electricity market-transforming capabilities of T-PSH technology coupled with transmission monitoring and dynamic control. This paper presents an overview of the methodology and initial, first-year preliminary findings of a 2-year in-depth study into how advanced PSH and dynamic transmission contribute to the transformation and modernization of the U.S. electric grid. This project is part of the HydroNEXT Initiative funded by the U.S. Department of Energy (DOE) that is focused on the development of innovative technologies to advance nonpowered dams and PSH. The project team consists of the National Renewable Energy Laboratory (project lead), Absaroka Energy, LLC (Montana-based PSH project developer), GE Renewable Energy (PSH pump/turbine equipment supplier), Grid Dynamics, and Auburn University (lead for NREL/Auburn dynamic modeling team).
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Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. I -- National Study
The use of renewable energy (RE) sources, primarily wind and solar generation, is poised to grow significantly within the Indian power system. The Government of India has established a target of 175 gigawatts (GW) of installed RE capacity by 2022, including 60 GW of wind and 100 GW of solar, up from 29 GW wind and 9 GW solar at the beginning of 2017. Thanks to advanced weather and power system modeling made for this project, the study team is able to explore operational impacts of meeting India's RE targets and identify actions that may be favorable for integration. Our primary tool is a detailed production cost model, which simulates optimal scheduling and dispatch of available generation in a future year (2022) by minimizing total production costs subject to physical, operational, and market constraints. Our team comprises a core group from the Power System Operation Corporation, Ltd. (POSOCO), which is the national grid operator (with representation from the National, Southern, and Western Regional Load Dispatch Centers) under Ministry of Power, National Renewable Energy Laboratory (NREL), and Lawrence Berkeley National Laboratory (LBNL), and a broader modeling team that includes Central Electricity Authority (CEA), POWERGRID (the central transmission utility, CTU), and State Load Dispatch Centers in Maharashtra, Gujarat, Tamil Nadu, Karnataka, Rajasthan, and Andhra Pradesh. Our model includes high-resolution wind and solar data (forecasts and actuals), unique properties for each generator, CEA/CTU's anticipated buildout of the power system, and enforced state-to-state transmission flows. Assuming the fulfillment of current efforts to provide better access to the physical flexibility of the power system, we find that power system balancing with 100 GW of solar and 60 GW of wind is achievable at 15-minute operational timescales with minimal RE curtailment. This RE capacity meets 22% of total projected 2022 electricity consumption in India with annual RE curtailment of 1.4%, in line with experiences in other countries with significant RE penetrations (Bird et al. 2016). Changes to operational practice can further reduce the cost of operating the power system and reduce RE curtailment. Coordinating scheduling and dispatch over a broader area is the largest driver to reduce costs, saving INR 6300 crore (USD $920 million) annually when optimized regionally. Lowering minimum operating levels of coal plants (from 70% to 40%) is the biggest driver to reduce RE curtailment - from 3.5% down to 0.76%. In fact, this operating property is more influential than faster thermal generation ramp rates in lowering the projected levels of curtailment. While this study does not answer every question relevant to planning for India's 2022 RE targets, it is an important step toward analyzing operational challenges and cost saving opportunities using state-of-the-art power system planning tools. Further analysis can build upon this basis to explore optimal renewable resource and intrastate transmission siting, system stability during contingencies, and the influence of total power system investment costs on customer tariffs.
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Picking the Best from the All-Resources Menu: Advanced Tools for Resource Planning
Introduces the wide range of electric power systems modeling types and associated questions they can help answer. The presentation focusses on modeling needs for high levels of Distributed Energy Resources (DERs), renewables, and inverter-based technologies as alternatives to traditional centralized power systems. Covers Dynamics, Production Cost/QSTS, Metric Assessment, Resource Planning, and Integrated Simulations with examples drawn from NREL's past and on-going projects. Presented at the McKnight Foundation workshop on 'An All-Resources Approach to Planning for a More Dynamic, Low-Carbon Grid' exploring grid modernization options to replace retiring coal plants in Minnesota.
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Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India’s Electric Grid, Vol. 1. National Study
The use of renewable energy (RE) sources, primarily wind and solar generation, is poised to grow significantly within the Indian power system. The Government of India has established a target of 175 gigawatts (GW) of installed RE capacity by 2022, including 60 GW of wind and 100 GW of solar, up from 29 GW wind and 9 GW solar at the beginning of 2017. Using advanced weather and power system modeling made for this project, the study team is able to explore operational impacts of meeting India’s RE targets and identify actions that may be favorable for integration. Our primary tool is a detailed production cost model, which simulates optimal scheduling and dispatch of available generation in a future year (2022) by minimizing total production costs subject to physical, operational, and market constraints. Our team comprises a core group from the Power System Operation Corporation, Ltd. (POSOCO), which is the national grid operator (with representation from the National, Southern, and Western Regional Load Dispatch Centers) under Ministry of Power, National Renewable Energy Laboratory (NREL), and Lawrence Berkeley National Laboratory (Berkeley Lab), and a broader modeling team that includes Central Electricity Authority (CEA), POWERGRID (the central transmission utility, CTU), and State Load Dispatch Centers in Maharashtra, Gujarat, Tamil Nadu, Karnataka, Rajasthan, and Andhra Pradesh. Our model includes high-resolution wind and solar data (forecasts and actuals), unique properties for each generator, CEA/CTU’s anticipated buildout of the power system, and enforced state-to-state transmission flows. Assuming the fulfillment of current efforts to provide better access to the physical flexibility of the power system, we find that power system balancing with 100 GW of solar and 60 GW of wind is achievable at 15-minute operational timescales with minimal RE curtailment. This RE capacity meets 22% of total projected 2022 electricity consumption in India with annual RE curtailment of 1.4%, in line with experiences in other countries with significant RE penetrations (Bird et al. 2016). Changes to operational practice can further reduce the cost of operating the power system and reduce RE curtailment. Coordinating scheduling and dispatch over a broader area is the largest driver to reduce costs, saving INR 6300 crore (USD 980 million) annually when optimized regionally. Lowering minimum operating levels of coal plants (from 70% to 40%) is the biggest driver to reduce RE curtailment—from 3.5% down to 0.76%. In fact, this operating property is more influential than faster thermal generation ramp rates in lowering the projected levels of curtailment. While this study does not answer every question relevant to planning for India’s 2022 RE targets, it is an important step toward analyzing operational challenges and cost saving opportunities using state-of-the-art power system planning tools. Further analysis can build upon this basis to explore optimal renewable resource and intrastate transmission siting, system stability during contingencies, and the influence of total power system investment costs on customer tariffs.
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A Data-Driven Algorithm for Enabling Delay Tolerance in Resilient Microgrid Controls Using Dynamic Mode Decomposition
The increased implementation of smart grid technologies in the power distribution grid presents unique opportunities that enable resiliency, but also brings challenges motivating needs for novel solutions and mitigation techniques. The bi-directional power and data flow allow for the grid to operate with increased resiliency, which is the ability to avoid discontinuity of service to end-use loads during extreme events. However, in applications where control of the distribution grid or microgrid relies on communication networks, the degradation of communication systems in the form of loss or high latency can cause maloperation and result in loss of end-use loads. Here this paper presents a novel framework to enable delay tolerance of centralized microgrid control schemes to mitigate communication system latency impacts and guarantee successful control action. We demonstrate the delay tolerance on a control scheme that operates a battery energy storage system (BESS) to offset the sudden loss of generation and maintain system frequency. During periods of severely degraded communication system performance, the proposed delay-tolerant algorithm compensates for the latency by utilizing a data-driven model generated at the device level using dynamic mode decomposition (DMD) to determine the performance of the communications. The DMD technique predicts the system’s frequency using device-level terminal measurements and provides updated control signals. The HELICS cosimulation platform evaluates the cyber-physical interaction of the power system model in GridLAB-D, the centralized control agent in Python, and the discrete network model in NS-3. The framework is tested and validated on the IEEE-123 node system modified to represent a networked remote microgrid model, and the results show an improvement in the dynamic performance
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Greening the Grid: Advances in Production Cost Modeling for India Renewable Energy Grid Integration Study
The Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid study uses advanced weather and power system modeling to explore the operational impacts of meeting India's 2022 renewable energy targets and identify actions that may be favorable for integrating high levels of renewable energy into the Indian grid. The study relies primarily on a production cost model that simulates optimal scheduling and dispatch of available generation in a future year (2022) by minimizing total production costs subject to physical, operational, and market constraints. This fact sheet provides a detailed look at each of these models, including their common assumptions and the insights provided by each.
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Introducing the 9500 Node Distribution Test System to Support Advanced Power Applications: An Operations-Focused Approach
The 9500 Node Test System is a representative section of distribution power system model developed as a part of the GridAPPS-D™ project, an effort funded by DOE as a part of the Grid Modernization Lab Consortium (GMLC) program. The test system was developed to fulfill a growing need to represent the rapidly evolving state of electric distribution systems by combining elements of legacy infrastructure systems, modern feeder topologies, and an anticipated future with smart grid technologies. It also provides a network model capable of supporting the simulation of operational scenarios such as the ones in a utility distribution control center. This test system allows the evaluation of the performance of advanced power applications in real-time, such as one that simulates the operations of an Advanced Distribution Management Systems (ADMS), Distributed Energy Resource Management Systems (DERMS), etc. in a Distribution control center. This model is an extension of the widely used IEEE 8500 Node Test Feeder and is currently being validated to become an IEEE test case to help increase adoption and widespread usage among both academia and industry. It is a full-size model representative of a section of a utility’s distribution system with multiple feeders fed from different substations. The model includes multiple distribution circuits, a sub-transmission system, multiple substations, behind the meter customer rooftop photovoltaics (PV), and multiple utility-scale distributed energy resources. To enable accurate simulations of operational scenarios, the 9500 Node Test System is designed to support procedure-based operations, with the ability to realistically demonstrate switching operations, feeder reconfiguration, adjustment of volt-var control equipment, dispatch of distributed generation, and response to planned and unplanned outages. The 9500 Node Test System includes three radial distribution feeders with 12.3 MVA of average load, consisting of both medium voltage and low voltage equipment each supplied by a different distribution substation. The three distribution feeders are connected to each other through Normally-Open switches which can be closed when needed to simulate restoration scenarios due to a fault. One feeder represents today’s grid with low penetration of customer-side renewables. The second represents a potential future grid with microgrids and 100% renewable penetration. The third has no customer generation resources, a district steam plant, and a utility-scale solar farm. The three diverse circuits were created to allow the simulation of both today’s situation as well as potential future scenarios. All three feeders have customers connected by low-voltage secondary triplex lines. This test system meets all requirements outlined in the report for creating a simulation environment that would enable discussion between key technical stakeholders as well as having the potential to accelerate operational application development and their subsequent testing and integration. The new model is a possible representation of what we believe the distribution grid may look like in the future: a high penetration of renewables, reconfigurable radial and mesh topology, numerous DERs, islanded microgrids, and significantly increased data and measurement density. The system supports both the solution of existing and newer algorithms but also enables the evaluation of applications in a realistic operational environment defined by task oriented procedural steps that represent the interaction between the control center operator and field personnel.
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Impacts of Alternative Operations and Renewable Energy Deployment on Columbia River Hydropower
The Columbia River Treaty Tribes in the Pacific Northwest - the Nez Perce, Umatilla, Warm Springs, and Yakama - hold treaty-reserved fishing rights for the Columbia River, one of the world's most productive salmon rivers and a critical resource for these tribes. However, the tribes have expressed that current operating regimes of hydropower dams throughout the Columbia River Basin (CRB) do not fully account for tribal fishing rights and have negatively impacted fish populations. Four tribes acting together through the Columbia River Inter-Tribal Fish Commission (CRITFC)'s 2022 Energy Vision stated that current power system models often do not fully account for the many constraints faced by hydropower facilities in the CRB. As the deployment of variable renewable energy (VRE) like solar and wind continues to increase, power system flexibility will become increasingly important. As a result, there is a growing need to better understand the true capabilities of the hydropower generation fleet while accurately accounting for ecological constraints (Northwest Power and Conservation Council 2022). Understanding hydropower's role in a future grid with a higher share of VRE can inform water resources planning to address ecological needs. The goal of this study is to examine the impacts of alternative hydropower operation rules and weather variability on hydropower generation and grid operations in VRE and transmission infrastructure deployment scenarios. The study evaluates how hydropower scheduling practices can reduce ecological impacts to the region's salmon populations. More specifically, the study examines the impact of today's dam water release rules (called "adjusted base water rules" in this study) and new, ecologically informed water release rules (called "ecosystem water rules" in this study) on two VRE scenarios (current renewable energy levels and higher renewable energy levels) using six weather years for each scenario (2008-2013). CRITFC developed the ecosystem water rules, which capture a portion of the changes they recommend for CRB hydropower operations. These analyses use a water resource planning model (OASIS) and a production cost model (PLEXOS) to simulate CRB reservoir cascade and Western Interconnection power grid operation.
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Enabling Data Exchange and Data Integration with the Common Information Model: An Introduction for Power Systems Engineers and Application Developers
The Common Information Model (CIM) is an open-source information model that is used to model an electrical network and the various equipment used on the network. CIM is widely used for data exchange of bulk transmission power systems and is finding increasing use for distribution systems. Use of a non-proprietary information model (such as CIM) that has been agreed upon and adopted by numerous utilities, vendors, and researchers allows significant reduction in the effort and cost of data integration. Likewise, adoption of open data platforms built around the CIM increases available functionalities for managing and optimizing the smart grid of the future. This report is intended as an introduction to CIM for utility engineers, power systems researchers, and application developers, providing a broad view of the CIM and how particular profiles can be adapted for various use cases. Unlike most other CIM introduction documents and the International Electrotechnical Commission (IEC) standards (which are mostly targeted to an audience of data scientists, enterprise database managers, and platform developers), this report is intended for users of traditional power systems analysis software and other readers without any prior experience with canonical information models, data profiles, or UML modeling.
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Verdant Power Gen5 KHPS and TriFrame System Content Models
This submission includes the Component Content Model for Verdant Power TriFrame and the System Content Model for Verdant Power TriFrame + 3 Gen5 KHPS Turbines. The TriFrame is the foundation component of the system, which consists of a TriFrame + 3 Gen5 KHPS Turbines (TF+3T).
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