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At least 379 records · Page 21

Improving the Power Outage Resilience of Buildings with Solar PV through the Use of Battery Systems and EV Energy Storage

Buildings with solar photovoltaic (PV) generation and a stationary battery energy storage system (BESS) may self-sustain an uninterrupted full-level electricity supply during power outages. The duration of off-grid operation is dependent on the time of the power fault and the capabilities of the home energy management system (HEMS). In this paper, building resilience is quantified by analyzing the self-sustainment duration for all possible power outages throughout an entire year. An evaluation method is proposed and exercised on a reference house in California climate zone 9 for which the detailed electricity usage is simulated using the EnergyPlus software. The influence of factors such as energy use behavioral patterns, energy storage capacity from the BESS, and an electric vehicle (EV) battery on the building resilience is evaluated. Varying combinations of energy storage and controllable loads are studied for optimally improved resilience based on user preferences. It is shown that for the target home and region with a solar PV system of 7.2 kW, a BESS with a capacity of 11 kWh, and an EV with a battery of 80 kWh permanently connected to the home, off-grid self-sustained full operation is guaranteed for at least 72 h.

14 SOLAR ENERGY↗

Integrated Water-Power System Resilience Analysis in a Southeastern Idaho Irrigation District: Minidoka Case Study

This study investigates the joint water–power system resilience of an irrigation district in southeastern Idaho. Irrigation districts face difficulties in the delivery of water to farmers under drought conditions, during equipment failures, or unplanned infrastructure disruptions. The resilience of interconnected water and power systems can be better analyzed and understood through an integrated approach, using a model that connects the dependencies between the two halves of the system. Using a multi-agent system model capturing both water and power system components, as well as their linkages, we capture the interdependencies of these systems and highlight opportunities for improvement when faced with disruptions. Through simulation scenarios, we examine the system resilience using system performance, quantified as the percentage of met demand of the power and water system, when subjected to drought water year, an unforeseen water demand increase, power outage and dam failure. Scenario results indicate that the effects of low flow years are mostly felt in the power system; unexpected increases in water demand marginally impact irrigation system performance; dams and pumps present vulnerabilities of the system, causing substantial unmet demand during disruptions. Noting the interdependencies between the water–power system halves while leveraging an integrated simulation allows for an insightful analysis of the system impacts during disruptions.

13 HYDRO ENERGY↗

Planning for the storm: Considering renewable energy for critical infrastructure resilience

This study uses the renewable energy optimization model to assess three critical facilities in North Carolina. Techno-economic results were then compared to analyses completed for critical facilities in California and New York to assess energy system cost effectiveness. Though solar photovoltaic (PV) arrays are cost-effective across each of the three North Carolina facilities, adopting battery storage to enable PV to operate with existing diesel generators in a hybrid energy system reduces the economic value of the system. This is in contrast to more economically viable systems in California and New York. All of these systems also offer unquantified resilience benefits by extending operation from hours to weeks across the facilities. If decision makers were able to value the resilience benefits offered by each system or utility rate structures were changed to incentivize battery storage during normal operations, it would impact these assessments. Even so, this analysis provides decision makers a key set of cost benchmarks when considering how they might improve resilience at their critical operations.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Advanced-Research-on-Integrated-Energy-Systems-Based Analysis to Support Resilient System Upgrades: Energy to Communities Energyshed In-Depth Partnership with Molokai, Hawaii

The Molokai, Hawaii, Energy to Communities (E2C) Energyshed project represents a collaborative effort between the National Laboratory of the Rockies, Shake Energy Collaborative, the Molokai Clean Energy Hui, Sustainable Molokai, and Ho'ahu Energy Cooperative Molokai to advance Molokai's Community Energy Resilience Action Plan (CERAP). Supported by Hawaiian Electric Company and the Hawaii State Energy Office, the initiative aims to develop a community-defined portfolio of renewable energy solutions that enhance energy resilience while aligning with the Hawaiian Electric Integrated Grid Plan (IGP) and Molokai's energy goals. Phase 1 focused on technical analyses and community engagement to co-design feasible energy scenarios. Challenges such as grid upgrades, storage sizing, and inverter ride-through standards were addressed to align technical and operational requirements with community preferences. The project equips Molokai with actionable data and insights to implement energy initiatives while ensuring resilient and culturally informed solutions. Future efforts aim to finalize project designs, secure interconnection agreements, and deploy energy projects that reflect community priorities and technical feasibility.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Dynamic Distribution System Restoration Strategy for Resilience Enhancement: Preprint

In electric power distribution systems, distributed energy re-sources (DERs) can act as controllable power sources and support utility operators to minimize power outages after ex-treme weather events (e.g., hurricane, earthquake, wildfire) and thus help enhance the grid's resilience. Meanwhile, the influ-ences of extreme events and the capabilities of DERs are dy-namic and difficult to predict. Hence, the desired distribution system restoration strategy should be able to evolve according to real-time fault/disturbance information and the availabil-ity of DERs. In this paper, we propose a new dynamic distribu-tion system restoration strategy to enhance system resilience against potential hazards. An efficient reconfiguration algo-rithm is developed to eliminate the use of integer variables to relieve the computational burden. Model predictive control is implemented to adjust the system topology and DER opera-tion setpoints based on the updated fault information and DER forecasts. The effectiveness of the proposed restoration model in enhancing distribution system resilience is validated through an IEEE 123-bus test system. Simulation results also validate that the proposed restoration model can mitigate the occurrence of unexpected events and the fluctuations of DERs.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Optimal Operation for Resilient and Economic Modes in an Islanded Alaskan Grid: Preprint

Power System is a complex system, with an objective to provide power to the customers. The objective is driven by a complex consideration of the secure, economic and resilient operation of the system. With the growing occurrence of extreme events emphasis has been shifted towards making the grid more resilient. However, an economic operation is still a priority for the utilities as well as its customers. Many utilities especially small isolated micro-grids do not emphasize much on an economic and resilient operation, but more on reliability. In this research we focus on striking a balance between economic and resilientoperation, ensuring reliability.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Options for Resilient and Flexible Power Systems in Select South American Economies

This poster provides highlights from the published report, Options for Resilient and Flexible Power Systems in Select South American Economies, which summarizes opportunities for Argentina, Brazil, Chile, and Colombia to adapt to the new forces buffeting electricity sectors around the globe to ensure reliable, affordable, sustainable, and resilient power systems. Special attention is placed on the potential role for natural gas to help ensure flexible and resilient power.

ENERGY PLANNING, POLICY, AND ECONOMY,NATURAL GAS,P↗

Enhancing Distribution Grid Resilience Through Model Predictive Controller Enabled Prioritized Load Restoration Strategy: Preprint

Effective resilience improvement strategies enable the power grid to cope with disruptive extreme events. Most power grid outages are caused by disruptions in distribution grids. Motivated by the urgent need for power system resilience research, this paper proposes a priority-weighted optimal load restoration technique to enhance the resilience of distribution grids against extreme events. The proposed technique is based on smart distribution technology and framed as sequential multi-step decision process (MDP) and mixed integer linear program (MILP). It is formulated as optimal control problem with a model predictive control (MPC) approach. We applied the devised MILP-MPC-based load restoration technique to a simplified single-bus version of the IEEE 13-bus distribution system with integrated distributed energy resources (DERs) such as wind turbine, photovoltaic array, microturbine, and energy storage device. The technique executes a reducing and rolling horizon optimization in each control step in real-time using the forecasted information of the renewables, the fuel status of the microturbine and the state of charge of the energy storage device. We consider an extreme event which triggered outage of the upstream utility grid and caused islanded operation of the distribution grid. We demonstrated the effectiveness of the proposed MPC approach in restoring the distribution grid loads based on their priority during the main grid outage-caused islanded operation.

61 RADIATION PROTECTION AND DOSIMETRY↗

Enhancing Distribution Grid Resilience Through Model Predictive Controller Enabled Prioritized Load Restoration Strategy

Effective resilience improvement strategies enable the power grid to cope with disruptive extreme events. Most power grid outages are caused by disruptions in distribution grids. Motivated by the urgent need for power system resilience research, this paper proposes a priority-weighted optimal load restoration technique to enhance the resilience of distribution grids against extreme events. The proposed technique is based on smart distribution technology and framed as sequential multi-step decision process (MDP) and mixed integer linear program (MILP). It is formulated as optimal control problem with a model predictive control (MPC) approach. We applied the devised MILP-MPC-based load restoration technique to a simplified single-bus version of the IEEE 13-bus distribution system with integrated distributed energy resources (DERs) such as wind turbine, photovoltaic array, microturbine, and energy storage device. The technique executes a reducing and rolling horizon optimization in each control step in real-time using the forecasted information of the renewables, the fuel status of the microturbine and the state of charge of the energy storage device. We consider an extreme event which triggered outage of the upstream utility grid and caused islanded operation of the distribution grid. We demonstrated the effectiveness of the proposed MPC approach in restoring the distribution grid loads based on their priority during the main grid outage-caused islanded operation.

61 RADIATION PROTECTION AND DOSIMETRY↗

Outage Forecast-Based Preventative Scheduling Model for Distribution System Resilience Enhancement: Preprint

Distribution system resilience enhancement is an important topic to ensure customers have access to the power supply during extreme events. In fact, certain weather-related extreme events can be predicted ahead of time. Therefore, it is important to investigate how to predict grid outages using extreme weather forecasts, and how outage predictions can be incorporated into distribution system resilience enhancement. In this paper, a preventative scheduling model for distribution systems is proposed. The model targets at allocating resources, especially mobile responsive resources such as mobile backup generators and mobile energy storage systems, to prepare for an extreme event in the day-ahead context. To achieve efficient resource allocation and scheduling, a machine learning-based outage prediction module is developed to predict vulnerable or risky segments of the distribution system based on historical operating records and extreme weather event forecasts. By integrating the outage prediction results into the scheduling model, optimal resource allocation can be derived to help distribution systems prepare for an upcoming event and improve resilience performance. A real distribution feeder in North Carolina, U.S. is used in the case study to validate the proposed approach.

distributed energy resources↗

Outage Forecast-Based Preventative Scheduling Model for Distribution System Resilience Enhancement

Distribution system resilience enhancement is an important topic to ensure customers have access to power supply during extreme events. In fact, certain weather-related extreme events can be predicted ahead of time. Therefore, it is important to investigate how to predict grid outages using extreme weather forecasts, and how outage predictions can be incorporated into distribution system resilience enhancement. In this paper, a preventative scheduling model for distribution systems is proposed. The model targets at allocating resources, especially mobile responsive resources such as mobile backup generators and mobile energy storage systems, to prepare for an extreme event in the day-ahead context. To achieve efficient resource allocation and scheduling, a machine learning-based outage prediction module is developed to predict vulnerable or risky segments of the distribution system based on historical operating records and extreme weather event forecast. By integrating the outage prediction results into the scheduling model, optimal resource allocation can be derived to help distribution systems prepare for an upcoming event and improve resilience performance. A real distribution feeder in North Carolina, U.S. is used in the case study to validate the proposed approach.

distributed energy resources↗

Enhancing Resilience of our Nation’s Critical Infrastructure

Due to the ever-changing risk environment that faces the Nation’s critical infrastructure, it is essential that a comprehensive, collaborative approach is taken to enhance the resilience of the infrastructure assets and systems that are relied upon by the American people. To address the gaps that exist in infrastructure resilience research and development, Idaho National Laboratory (INL) created the Resilience Optimization Center (IROC) to bring together multi-disciplinary subject matter experts internally across the laboratory, as well as from public and private entities, other national laboratories, and academia to address some of the Nation’s more challenging infrastructure problems. These experts are working to provide easier access to subject matter experts; providing feasible, optimized solutions that yield observable results; and creating collaborative teams that apply a cyber-physical-dependencies approach. Though a variety of research initiatives, IROC is striving to provide end-to-end solutions, bridging the gap between cyber and physical infrastructure through research, analysis, testing, and validation.

99 GENERAL AND MISCELLANEOUS↗

Power Systems Resilience

As communities take steps toward identifying and achieving their clean energy goals, the topic of resilience will likely emerge. This presentation aims to help inform and empower communities as they explore how their clean energy projects can address evolving power systems reliability and resilience due to climate change and other factors. The training provides a basic introduction to power systems and the resilience challenges this traditional infrastructure faces, as well as strategies for enhancing this important quality of electric service.

communities↗

Best Practices for Resilience in Smart Grid-Interactive Efficient Buildings

The Federal Energy Management Program (FEMP) supports federal agencies' energy decisions with information and guidance on design, funding, and operations to ensure federal buildings are efficient and resilient. The modernization of building infrastructure and the evolution of buildings to support decarbonization involves complex implementation of multiple components across several systems. This includes energy-efficient equipment, on-site energy generation and storage systems, and control systems. These systems have operational modes that can operate more efficiently if they are able to behave responsively to the conditions of the electrical grid. These grid-interactive efficient buildings (GEB) allow facilities to manage power demand according to operational constraints and market signals issued by grid operators. With proper design and planning, these same capabilities have the potential to enable building and facility resilience - coordinating with microgrids, maintaining power on critical circuits to sustain essential operations, and monitoring building health and safety status during an outage. By managing the load of buildings, GEBs can also reduce the cost of backup generation and make better use of renewable power sources on site. This document outlines some of the processes and considerations to guide the design and operation of GEBs in ways that promote facility resilience.

building decarbonization↗

Grid Resilience Analysis on Geothermal District Heating and Cooling Implementation Alongside Four Existing Oil and Gas Wells in Tuttle, Oklahoma: Preprint

This study builds on the existing techno-economic and environmental life cycle assessments performed for a geothermal district heating and cooling system implementation in Tuttle Oklahoma with four existing oil and gas wells. Its resilience in meeting the peak annual heating and cooling loads of the district assuming a temporary disconnection from the electrical grid is assessed both qualitatively and quantitatively. Attributes of resilience and qualitative criteria established by Kolker et al. (2022) for geothermal district heating systems are applied to the proposed case to highlight its vulnerabilities. Results indicate that increasing the redundancy and diversity in the physical configuration of the distributional piping can considerably increase the system’s resilience. A quantitative assessment executed via the REopt tool predicts that the ancillary electricity required to power the geothermal system’s heating and cooling can be met by an onsite emergency diesel generator during times of grid outages for over 28 days.

district heating and cooling↗

Lessons Learned from the Clean Energy to Communities (C2C) Peer-Learning Cohort Enhancing Resilience at Critical Facilities through Solar, Storage, and Microgrids

The National Renewable Energy Laboratory (NREL), with support from World Resources Institute (WRI), designed and led a six-month peer-learning cohort from January through July 2024 on "Enhancing Resilience at Critical Facilities through Solar, Storage, and Microgrids" as part of the U.S Department of Energy's Clean Energy to Communities (nrel.gov/c2c) (C2C) program. Representatives from 15 municipalities, municipal utilities, colleges, and Tribes from across the United States participated in monthly workshops covering best practices for planning and deploying local resilience projects. This document shares key takeaways, lessons learned, and resources from the cohort including considerations for planning, proposing, designing, procuring, and funding microgrid projects for resilience.

C2C↗

Resilient Observer Design for Cyber-Physical Systems with Data-Driven Measurement Pruning

Resilient observer design for Cyber-Physical Systems (CPS) in the presence of adversarial false data injection attacks (FDIA) is an active area of research. The existing state-of-the-art algorithms tend to break down as more and more knowledge of the system is built into the attack model; also as the percentage of attacked nodes increases. From the view of optimization theory, the problem is often cast as a classical error correction problem for which a theoretical limit of has been established as the maximum percentage attacked nodes for which state recovery is guaranteed. Beyond this limit, the performance of -minimization based schemes, for instance, deteriorates rapidly. Similar performance degradation occurs for other types of resilient observers beyond certain percentages of attacked nodes. In order to increase the corresponding percentage of attacked nodes for which state recoveries can be guaranteed, researchers have begun to incorporate prior information into the underlying resilient observer design framework. For the most pragmatic cases, this prior information is often obtained through a data-driven machine learning process. Existing results have shown a strong positive correlation between the maximum attacked percentages that can be tolerated and the accuracy of the data-driven model. Motivated by these results, this chapter examines the case for pruning algorithms designed to improve the Positive Prediction Value (PPV) of the resulting prior information, given stochastic uncertainty characteristics of the underlying machine learning model. Theoretical quantification of the achievable improvement is given. Simulation results show that the pruning algorithm significantly increases the maximum correctable percentage of attacked nodes, even for machine learning model whose prediction power is comparable to the random flip of a coin.

Resilient Observer, Cyber-physical Systems, Data-D↗

Grid Resilience Analysis on Geothermal District Heating and Cooling Implementation Alongside Four Existing Oil and Gas Wells in Tuttle, Oklahoma

This study builds on the existing techno economic and environmental life cycle assessments performed for a geothermal district heating and cooling system implementation in Tuttle Oklahoma with four existing oil and gas wells. Its resilience in meeting the peak annual heating and cooling loads of the district assuming a temporary disconnection from the electrical grid is assessed both qualitatively and quantitatively. Attributes of resilience and qualitative criteria established by Kolker et al. (2022) for geothermal district heating systems are applied to the proposed case to highlight its vulnerabilities. Results indicate that increasing the redundancy and diversity in the physical configuration of the distributional piping can considerably increase the system's resilience. A quantitative assessment executed via the REopt tool predicts that the ancillary electricity required to power the geothermal system's heating and cooling can be met by an onsite emergency diesel generator during times of grid outages for over 28 days.

district heating and cooling↗