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At least 307 records · Page 17

A grid-scale study of demand bidding by large industrial users

A demand bidding mechanism for engaging large industrial electricity users in the operation of the power grid is presented. Demand bidding is formulated as an optimization problem based on a modified version of the alternating current optimal power flow problem, and can be interpreted as a tâtonnement process between the grid operator and electricity users. Here, the work provides the first – to the authors’ knowledge – grid-scale case study of demand bidding, using a synthetic grid structure in the footprint of the grid of Texas. Results reveal that the demand bidding lowers overall power generation costs, but economic benefits plateau as the number of participants increases. Transmission line and transformer capacity constraints become the limiting factors, revealing that expanding and fortifying the transmission infrastructure is key to expanding demand-side participation. Demand bidding does not substantially alter the optimal operation of existing bidding entities when the number of bidders increases, thereby supporting existing bidders to stay in the system and encouraging new ones to join.

Chlor-alkali plant↗

Extracting maximal frequency response potential in controllable loads

Methods and apparatus are disclosed for extracting maximal frequency response potential in controllable loads. In one example, a method includes assigning a fitness metric to at least one electrical device coupled to a power grid, assigning a frequency threshold based on the fitness metric, and transmitting the assigned frequency threshold to the at least one electrical device. The fitness metric can be based at least in part on an availability component and a quality component associated with the at least one device and the frequency threshold can cause the at least one electrical device to activate autonomously based on a frequency of the power grid.

Lian, Jianming↗

Predicting Power Outage During Extreme Weather with EAGLE-I and NWS Datasets

Extreme weather events, such as hurricanes, severe thunderstorms, and floods can significantly disrupt power grid systems, leading to electrical outages that result in inconvenience, economic losses, and life-threatening situations. There is a growing need for a robust and precise predictive model to forecast power outages, which will help prioritize emergency response before, during, and after extreme weather events. In this paper, we introduce machine-learning models that predict power outage risk at the state level during and after extreme weather events. We jointly utilized two publicly available datasets: the U.S. historical power outage data collected by the Environment for Analysis of Geo-Located Energy Information (EAGLE-I™) system, and the National Weather Service historical weather alert data sets. We highlight our initial result and discuss future work aimed at enhancing the model's robustness and accuracy for real-world applications.

Lee, Sangkeun (Matt)↗

Explained: Causes of Three Recent Major Blackouts and What Is Being Done in Response

While the power grid is designed to have an adequate supply of electricity generating capacity under hot and cold conditions well above or below average, weather in recent years has approached the bounds of anticipated conditions, in both magnitude and duration. Extreme weather can result in unanticipated levels of electricity demand and correlated power plant outages driven by extreme temperatures. How power system planners account for the changing role of wind and solar also plays an important role in the power grid's ability to supply enough electricity during extreme weather. In response to recent significant outages, power system planners have been focusing on ensuring methods to evaluate reliability during periods of "net peak demand" consider availability of renewable resources and capture the impact of extreme weather on power plants of all types. In particular, there is significant emphasis on the ability of natural gas-fueled power plants to operate during periods of extreme cold temperatures. The impact of extreme weather on the need to change planning processes is demonstrated in this fact sheet that discusses three significant outages that occurred in recent years.

power grid↗

Evaluating grid stress and reliability in future electricity grids across a range of demand, generation mix, and weather trends

The reliability of power grids in the future will depend on how system planners account for the integration of new technologies, extreme weather events, and uncertainties in demand growth from increased electrification and data centers. This study introduces an open-source, multisectoral, multiscale modeling framework that projects grid stress and reliability trends between 2020 and 2055 in the Western Interconnection of the United States. The framework integrates global to national energy-water-land dynamics with power plant siting and hourly grid operations modeling. We analyze future wholesale electricity price shocks and unserved energy events across eight scenarios spanning a range of population growth and economic change, generation mixes, and weather conditions. Our results show future grids with high percentage of non-renewable generation and strong economic growth are characterized by higher reliability and lower wholesale electricity prices than lower growth scenarios because of larger reliance on dispatchable generators and lower fossil fuel extraction costs. Scenarios with high percentage of renewable resources have lower median but more volatile wholesale electricity prices as well as more frequent and severe unserved energy events compared to scenarios relying more on dispatchable generators. These events occur because higher proportion of solar and wind energy causes net demand curves to deepen during midday (duck curves get progressively severe), exacerbating the challenge of meeting demand during summer evening peaks. This study suggests that robust and co-optimized transmission and energy storage planning could help maintain low wholesale electricity prices and high reliability levels in future electricity grids across uncertainties in generation mixes.

Electric grid reliability↗

Total Power Factor Smart Contract with Cyber Grid Guard Using Distributed Ledger Technology for Electrical Utility Grid with Customer-Owned Wind Farm

In modern electrical grids, the numbers of customer-owned distributed energy resources (DERs) have increased, and consequently, so have the numbers of points of common coupling (PCC) between the electrical grid and customer-owned DERs. The disruptive operation of and out-of-tolerance outputs from DERs, especially owned DERs, present a risk to power system operations. A common protective measure is to use relays located at the PCC to isolate poorly behaving or out-of-tolerance DERs from the grid. Ensuring the integrity of the data from these relays at the PCC is vital, and blockchain technology could enhance the security of modern electrical grids by providing an accurate means to translate operational constraints into actions/commands for relays. This study demonstrates an advanced power system application solution using distributed ledger technology (DLT) with smart contracts to manage the relay operation at the PCC. The smart contract defines the allowable total power factor (TPF) of the DER output, and the terms of the smart contract are implemented using DLT with a Cyber Grid Guard (CGG) system for a customer-owned DER (wind farm). This article presents flowcharts for the TPF smart contract implemented by the CGG using DLT. The test scenarios were implemented using a real-time simulator containing a CGG system and relay in-the-loop. The data collected from the CGG system were used to execute the TPF smart contract. The desired TPF limits on the grid-side were between +0.9 and +1.0, and the operation of the breakers in the electrical grid and DER sides was controlled by the relay consistent with the provisions of the smart contract. The events from the real-time simulator, CGG, and relay showed a successful implementation of the TPF smart contract with CGG using DLT, proving the efficacy of this approach in general for implementing electrical grid applications for utilities with connections to customer-owned DERs.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Plug-in Electric Vehicle Charging Response Characterization for Grid Integration: Implications for Smart Charge Management

The rapid expansion of plug-in electric vehicles (PEVs) has created a unique challenge for electrical grids due to their significant power demand. At the same time, PEVs also create a unique opportunity to ease their own burden on the power grid, as they create a growing fleet of distributed energy resources capable of providing grid services such as demand response, frequency regulation, and renewable balancing. For aggregators and grid operators to effectively integrate PEVs into grid management, it is essential to first understand and characterize how they would respond in such situations. This study examines 25 models of PEVs across 25 makes, spanning model years from 2013 to 2025, to characterize their responses to the basic controls used in vehicle-grid integration (VGI): stopping, starting, and modulating the charge rate. Each vehicle was tested in a controlled laboratory setting to evaluate its performance in response to varying the maximum allowable current via the SAE J1772 control pilot signal, as well as its response to wake-up commands outlined in SAE J1772. Results show measurable differences across vehicle makes in the accuracy, latency, and precision with which PEVs respond to changes in ampacity, as well as varying sleep and wake-up behavior. The test results show that all vehicles respond to changes in ampacity, though with varying accuracy, precision, latency, and resolution. Wake-up behavior also differs across makes and models. These findings indicate that effective grid integration strategies must account for these differences. The results provide a foundation for understanding current vehicle behavior and advancing smart-charging methods while also highlighting the need for further testing, broader standardization, and manufacturer collaboration to ensure the successful integration of PEVs into the electrical grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Simplification of the Grid Model and its Impact on the Analysis of Electrical Power Systems

Here, this paper analyzes the impact of the use of Kron reduction on the state variables of a three-phase electrical system, even when it does not meet the necessary conditions for its application. Reduction is applied to a power line model to eliminate the equation corresponding to the neutral conductor of the line. The ATP program is used to model and simulate the behavior of an electrical system considering different degrees of disequilibrium as a reference for the comparison of results. The results show that under certain conditions of disequilibrium the Kron reduction can lead to significant errors in the state variables of the system.

Electric Power Systems↗

A High-Fidelity Electromagnetic Transient Model of Inverter-based Resources Integrated to an IEEE-9 Bus System for Benchmarking Studies

An inverter-based resource (IBR) is a source of electricity that is asynchronously connected to the electrical grid via an electronic power converter. These power sources lack the intrinsic behaviors of the standard power plants, presenting specific challenges to system stability. These power sources lack the intrinsic behaviors of the standards power plants and their features are almost entirely defined by the control strategy used on them, presenting specific challenges to system stability as their penetration increases into the already fragile Bulk Power System (BPS). Utilizing renewable energy has a great upside but the electrical industry needs to understand the requirements like performing electromagnetic transient (EMT) simulation studies in planning and/or in interconnection studies. This paper presents the development of a high-fidelity EMT model based on commercial equipment and field parameters, which at the same time aims to study the increasing penetration of IBRs and their impact on the actual BPS. The open-source EMT model developed will be a benchmarking example that can be used to evaluate algorithms in the power grid (including evaluating grid-forming controls, power system monitoring and operation, etc.).

Martinez Montejano, Misael↗

GridSTIX

SF-25-112 Grid-STIX is a comprehensive extension of the STIX (Structured Threat Information Expression) 2.1 ontology specifically designed for electrical grid cybersecurity applications. This ontology provides a standardized, machine-readable framework for modeling grid assets, operational technology devices, threats, vulnerabilities, supply chain risks, and security relationships in electrical power systems. ## Key Features - **Comprehensive Grid Coverage**: Physical assets, OT devices, grid components, sensors, and energy storage systems - **Zero Trust Architecture**: Policy decision points, enforcement points, trust brokers, and continuous monitoring - **AMI Infrastructure**: Advanced metering networks, head-end systems, mesh gateways, and MDM systems - **Advanced Security Modeling**: Attack patterns, vulnerabilities, mitigations, and supply chain risks - **Critical Grid Relationships**: Power flow, protection, control, and synchronization relationships - **Supply Chain Security**: Supplier modeling, country of origin tracking, and risk assessment - **Protocol Support**: DNP3, Modbus, IEC 61850, IEC 60870-5-104, OPC-UA, and IEEE standards - **Python Code Generation**: Automated STIX-compliant Python class generation from ontologies - **Interactive Visualization**: Enhanced HTML network graphs with grid-specific categorization - **STIX 2.1 Compliance**: Full compatibility with STIX threat intelligence ecosystem

Blakely, Benjamin [Argonne National Laboratory (AN↗

Spatiotemporal Variability of Electric System Reliability Metrics

As urbanization continues to grow, urban density also rises, placing significant stress on critical infrastructure. Cities often face challenges in investing in new infrastructure or upgrading existing ones. One area of infrastructure that has come under strain is the electric grid, leading to prolonged power outages. According to data from the U.S. Energy Information Administration, the average duration of power outages has steadily doubled from 2013 to 2021, primarily due to extreme weather events. The IEEE has developed a series of reliability metrics to assess the reliability of the electric system. However, these metrics are only applied at the utility level, making it challenging to comprehend the variations in these indices at finer spatial resolutions and, consequently, evaluate reliability at the non-utility level. In this study, we leveraged electric outage data collected at 15-minute intervals at the county level to estimate electric system reliability over a six-year period using a novel data analysis approach. Our findings reveal a gradual decline in reliability in the U.S. Southwest compared to national averages. Furthermore, the duration of outages per customer per event has significantly decreased in large portions of California and Florida. These discoveries can be valuable for utility companies as they seek to pinpoint regional anomalies and plan for prioritized remediation efforts.

Singh, Nagendra↗

Deadband Voltage Control and Power Buffering for Extreme Fast Charging Station

Voltage fluctuation is one of the most common challenges that electric vehicle charging station (EVCS) may introduce to the power grid. Local reactive power compensation (Q-compensation) capability of bi-directional electric vehicle (EV) chargers can mitigate the steady-state voltage violations caused by the EV charging itself or changes in the neighboring loads. Power buffering, using energy storage system (ESS), can be utilized to address the voltage transients (sags and swells) as a result of EV charging at the EVCS. To address PI controller’s ‘hunting’ issue, this paper proposes a Q-sign triggered deadband voltage control (V-control) method at the point of common coupling (PCC). In addition, to ensure the ramp rate of EV charging is within the allowable limits set forth by the grid code, a ramp rate control is proposed that uses the ESS as a ‘power buffer’. Lastly, different from most reported work in the literature where no explicit limit of the power electronic converters (PECs) is considered, this work considers a reasonable apparent power capacity limit of the PECs when achieving the V-control. This limit also affects the amount of active power that can be obtained from the grid, and subsequently may require ESS to function as ‘load sharing’ device to provide supplemental active power to satisfy EV load. A case study simulated in MATLAB (interfaced with PLECS) is presented to demonstrate the effectiveness of the proposed approaches for EVCS operation.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Individual and Collective Strategies to Limit the Impacts of Large Power Outages of Long Duration

As modern society becomes ever more dependent on the availability of electric power, the costs that could arise from individual and social vulnerability to large outages of long duration (LLD-outages) increases. During such an outage, even a small amount of power would be very valuable. Here, this article compares individual and collective strategies for providing limited amounts of electric power to residential customers in a hypothetical New England community during a large electric power outage of long duration. We develop estimates of the emergency load required for survival and assess the cost of strategies to address outages that last 5, 10, and 20 days in either winter or summer. We find that the cost of collective solutions could be as much as 10 to 40 times less than individual solutions (less than $2 per month per home). However, collective solutions would require community-wide coordination, and if local distribution system lines are destroyed, only individual back-up systems could provide contingency power until those lines are repaired. Costs might be reduced if more robust distributed generation were employed that could be operated continuously with the ability to sell power back to the grid. Our cost-effectiveness analysis only assesses what could be done, developing estimates of preparedness cost. A decision about what should be done would require additional input from a range of stakeholders as well as some form of analytical deliberative process.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Analyzing at-scale distribution grid response to extreme temperatures

Threats against power grids continue to increase, as extreme weather conditions and natural disasters (extreme events) become more frequent. Hence, there is a need for the simulation and modeling of power grids to reflect realistic conditions during extreme events conditions, especially distribution systems. Herein, this paper presents a modeling and simulation platform for electric distribution grids which can estimate overall power demand during extreme weather conditions. The presented platform's efficacy is shown by demonstrating estimation of electrical demand for 1) Electricity Reliability Council of Texas (ERCOT) during winter storm Uri in 2021, and 2) alternative hypothetical scenarios of integrating Distributed Energy Resources (DERs), weatherization, and load electrification. In comparing to the actual demand served by ERCOT during the winter storm Uri of 2021, the proposed platform estimates approximately 34 GW of peak capacity deficit. These numbers are consistent with state-of-the-art prediction results published in the literature. For the case of the future electrification of heating loads, peak capacity of 78 GW (124% increase) is estimated, which would be reduced to 47 GW (38% increase) with the adoption of efficient heating appliances and improved thermal insulation. Integrating distributed solar PV and storage into the grid causes improvement in the local energy utilization and hence reduces the potential unmet energy by 31% and 40%, respectively.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Caldera Infrastructure Charge Module (ICM)

Caldera ICM is part of Caldera software platform, a suite of collective, open-source tools that was developed to improve the state of the art in modeling the impacts of Electric Vehicle (EV) charging on the grid. The foundation of Caldera ICM is it’s first-of-its-kind library of high-fidelity charging models for a wide variety of vehicles, validated by test data under a range of operating conditions. The charging models are used to accurately model the EV charging on an electric vehicle supply equipment (EVSE) – also known as a charger. ICM uses as inputs, the EV characteristics such as battery size, battery chemistry (i.e. NMC, LTO), watt hour per mile, inverter efficiency and max charge rate; as well as EVSE characteristics such as max current and supply equipment type (i.e. L2 vs XFC). Using these inputs Caldera ICM creates an uncontrolled charging profile curve for each compatible EV-EVSE pair. These charge profiles can be used stand alone to estimate charge duration given start State Of Charge (SOC) and end SOC or charge energy size given start SOC and charge duration. In Caldera Grid, another tool in the Caldera software platform, these charge profiles are used to represent EV charging as a load on the grid using charge event data such as EV type, SE type, start SOC, final SOC, park start time and park end time. ICM currently supports energy shifting Smart Charge Management (SCM) strategies such as "Time Of Use (TOU) immediate”, “TOU random” and “random start” by delaying the charge to start at a preferable time with respect to the strategy and, one voltage support SCM strategy named autonomous voltage control strategy by providing reactive power back to the electric grid.

Sundarrajan, ManojKumar Cebol↗

Conceptual design of an advanced Stirling conversion system for terrestrial power generation

A free piston Stirling engine coupled to an electric generator or alternator with a nominal kWe power output absorbing thermal energy from a nominal 100 square meter parabolic solar collector and supplying electric power to a utility grid was identified. The results of the conceptual design study of an Advanced Stirling Conversion System (ASCS) were documented. The objectives are as follows: define the ASCS configuration; provide a manufacturability and cost evaluation; predict ASCS performance over the range of solar input required to produce power; estimate system and major component weights; define engine and electrical power condidtioning control requirements; and define key technology needs not ready by the late 1980s in meeting efficiency, life, cost, and with goalds for the ASCS.

Source record↗