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At least 1,621 records · Page 90

Structure-Informed Graph Learning of Networked Dependencies for Online Prediction of Power System Transient Dynamics

Online transient analysis plays an increasingly important role in dynamic power grids as the renewable generation continues growing. Traditional numerical methods for transient analysis not only are computationally intensive but also require precise contingency information as input, and therefore, are not suitable for online applications. Existing online transient assessment studies focus on the determination of post-contingency system stability or stability margin. Here, this paper develops a novel graph-learning framework, Deep-learning Neural Representation or DNR, for online prediction, of the time-series trajectories of the system states using initial system responses that can be measured by phasor measurement units (PMUs). The proposed DNR framework consists of two sequential modules: a Network Constructor that captures network dependencies among generators, and a Dynamics Predictor that predicts the system trajectories. The key to improved prediction performance is the introduction of the spatio-temporal message-passing operations into graph neural networks with structural knowledge. Its effectiveness and scalability are validated through comparative studies, demonstrating the prediction performance under different contingency scenarios for systems of different sizes. This framework provides a solution to online predicting post-fault system dynamics based on real-time PMU measurements. Additionally, it can also be applied to facilitate the offline transient simulation without simulating the entire trajectories.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Co-optimized trading of hybrid wind power plant with retired EV batteries in energy and reserve markets under uncertainties

To be competitive in the electricity markets, various technologies have been reported to increase profits of wind farm owners. Combining battery storage system, wind farms can be operated as conventional power plants which promotes the integration of wind power into the power grid. However, high expenses on batteries keep investors away. Retired EV batteries, fortunately, still have enough capacity to be reused and could be obtained at a low price. In this work, a two-stage optimization of a wind energy retired EV battery-storage system is proposed. The economic performance of the proposed system is examined concerning its participation in the frequency containment normal operation reserve (FCR-N) market and the spot market simultaneously. To account uncertainties in the wind farm output, various electricity market prices, and up/down regulation status, a scenario-based stochastic programming method is used. The sizing of the equipment is optimized on top of daily operations of the hybrid system which formulates a mixed-integer linear programming (MILP) problem. Scenarios are generated with the Monte Carlo simulation (MCS) and Roulette Wheel Mechanism (RWM), which are further reduced with the simultaneous backward method (SBM) to increase computational efficiency. A 21 MW wind farm is selected as a case study. Here, the optimization results show that by integrating with a retired EV battery-storage system (RESS) and a bi-directional inverter, the wind farm can increase its profits significantly when forwarding bids in both of the aforementioned electricity markets.

17 WIND ENERGY↗

Transactive Emergency Power Allocation

The devastating impacts of extreme weather events, many of which are climate-change related, are increasingly evident through the frequency and duration of outages on power grids, especially the distribution systems. One of the major modern-day concerns of utilities is dealing with such extreme supply outages where operators have used rolling blackouts as a contingency plan balance supply and demand while serving critical loads. Such events have significant repercussions social and economic costs. Such blackouts practices are a blunt instrument, depriving customers with low-capacity high-priority loads (i.e. refrigeration, water, telecommunication, etc.) that provide high marginal amenity. Our contribution presented in this work is a transactive emergency allocation mechanism that would provide some minimum level of service to all of the customers while enabling preference-based trading of this initial allocation. This is in contrast to the state-of-art TE mechanisms that allocate resources to customers solely based on their willingness-to-pay. The effectiveness of the proposed mechanism is demonstrated through simulation-based evaluation on a prototypical distribution system experiencing 12-hour scarcity-based emergency event due to extreme operating conditions. Simulation results clearly demonstrate the capability of the proposed transactive emergency allocation mechanism in effectively utilizing the available energy and providing some level of service to all customers to operate their high-priority loads throughout the extreme scarcity event while being economically efficient in allowing trading of allocation based on customer preferences.

transactive energy, power system economics, emerge↗

Flexible Intelligent Real-time dc-ac grid Emulator (FIRE): Power Electronic Hardware-in-the-Loop (PE-HIL) Amplifier

Grid modernization efforts are leading to increased penetration of power electronics in the existing alternating current (ac) bulk power systems (BPS). Some examples of power electronics based applications that are being developed in BPS include high-voltage direct current (HVdc) systems, renewable generation systems, energy storage systems, and others. One of the requirements to succeed in the goals of grid modernization (like increased efficiency and reliability) is to setup a platform that can evaluate basic building blocks of such systems. For example, the basic building block of a modular multilevel converter (MMC)-based HVdc system is a submodule (SM). The evaluation platform will provide means to innovate new SM circuit architectures, new semiconductor devices in the SM, new gate-drivers, new controllers, and others. The flexible intelligent real-time dc-ac grid emulator (FIRE) platform incorporates the evaluation capability to evaluate the basic building blocks. The FIRE platform incorporates this evaluation capability through the power electronic hardware-in-the-loop (PE-HIL) concept. The PE-HIL for MMC-HVdc system can evaluate SMs in the MMC. In this paper, the design of amplifier required to perform PE-HIL simulation is presented. Experimental results of the amplifier and the simulation results of the PE-HIL concept utilizing the amplifier are presented.

Debnath, Suman↗

Use of Grid-Forming Medium-Voltage Power Electronics Hub in a Microgrid Setting

This paper presents the application of a new design of a multiport, modular, medium-voltage power electronics hub (M3PE-HUB) in a microgrid setting. The M3PE-HUB system was modeled in a digital real-time simulator (DRTS) and integrated into the Banshee microgrid test system. This paper presents the preliminary DRTS simulation-based results of the M3PE-HUB system connected in a test microgrid system. Verification and validation of the M3PE-HUB architecture and controls in the test microgrid setting are the primary contributions of this work. The results of the operation during the islanding and resynchronization process indicate the feasibility of the proposed architecture in a microgrid setting. This paper also presents results for a system reconfiguration use case where the M3PE-HUB was used to reconfigure the system under a fault condition.

grid forming↗

Satellite-based Investigation of Power-Line Vegetation Encroachment in the US (SILVANUS)

Rapid wide-area assessments of vegetation encroachment on transmission and distribution line rights-of-way (ROW) is a highly desirable capability for understanding risks to the power grid during severe weather and wildfire events. Conventional assessments are time-consuming and expensive due to the need for in-situ inspections and the use of aerial assets. Performing conventional assessments on a wide area would require immense resources and time that might not be available within the horizon of an expected adverse event. Developing a capability to accurately assess vegetation encroachment into ROWs will enable faster analysis of potential grid vulnerabilities in NAERM. This project sought to develop a prototype capability for rapid ROW vegetation encroachment assessments by using Puerto Rico as a test case. Puerto Rico is a heavily forested island territory frequently impacted by tropical cyclones that threaten the electric grid by downing trees across transmission and distribution lines. Multispectral satellite imagery (MSI) enable very high resolution (i.e., 0.5 - 2 meter) assessment of vegetation conditions at scale and with revisit times appropriate for regular monitoring (e.g., weekly to quarterly, depending on cloud cover) of the entire island. Synthetic aperture radar (SAR) data from satellites was also investigated as solution to the cloud-cover issue as they are active sensors that emit and receive a microwave signal rather than relying on solar illumination, and are therefore unaffected by cloud cover and can collect data during day or night. Finally, MSI-derived digital surface models (DSMs) map the height of objects relative to sea level, and were assessed for their ability to estimate the height of forest canopies relative to coincident transmission lines. The results of the mapping investigation are described in this report.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Public perceptions of wave energy development on the west coast of North America: Risks, benefits, and coastal attachment

While solar and wind energy continue to grow as significant sources of renewable energy, a global energy transition away from fossil fuels will require an expanding portfolio of generating resources. Marine renewable energy has the potential to contribute greatly in the coming decades, as the more predictable nature of wave energy can support the resiliency of the power grid and complement solar and inland wind generation. Yet, the broad deployment of marine energy technologies like wave energy will depend on public support, making it critical to identify the relevant factors associated with public attitudes and risk/benefit perceptions. This paper draws on social representations theory to specifically examine perceptions of wave energy on the west coast of North America, a site chosen because of the high suitability for wave energy generation and the fact that one of only three wave energy test sites in the world is under development off the coast of Oregon. Using an online survey in June 2020, we recruited a sample of 2000 respondents from California, Oregon, Washington, and British Columbia. We found a majority of respondents held positive attitudes to wave energy, but respondents also had low familiarity – with a quarter of respondents lacking sufficient information to form an opinion. We used logistic regression to identify factors correlated with wave energy attitudes, finding that respondents who were more supportive of wind and solar energy, more optimistic about new technology, and reported more familiarity with wave energy were significantly more likely to have a positive impression of wave energy. Respondents with higher levels of place attachment to coastal areas were more split, as they perceived higher benefits of wave energy – but also higher risks. Our results indicate broad appeal of wave energy on the west coast, but we caution policymakers and developers to not take initial siting processes for granted. As experience has shown for offshore wind, broad appeal does not guarantee a smooth siting process in a local context. Furthermore, the role of place attachment to coastal areas must be taken seriously or risk alienating local communities.

16 TIDAL AND WAVE POWER↗

A Comparison of Forecast Error Generators for Modeling Wind and Load Uncertainty

This paper presents four algorithms to generate random forecast error time series, including a truncated-normal distribution model, a state-space based Markov model, a seasonal autoregressive moving average (ARMA) model, and a stochastic-optimization based model. The error time series are used to create real-time (RT), hour-ahead (HA), and day-ahead (DA) wind and load forecast time series that statistically match historically observed forecasting data sets, used for variable generation integration studies. A comparison is made using historical DA load forecast and actual load values to generate new sets of DA forecasts with similar stoical forecast error characteristics. This paper discusses and compares the capabilities of each algorithm to preserve the characteristics of the historical forecast data sets.

Lu, Ning↗

Project Boeing SGS (Final Report)

Boeing and its partner, PJM Interconnection, teamed to bring advanced “defense-grade” technologies for cyber security to the US regional power grid through demonstration in PJM’s energy management environment. Under this cooperative project with the Department of Energy, Boeing and PJM have developed and demonstrated a host of technologies specifically tailored to the needs of PJM and the electric sector as a whole. The team has demonstrated to the energy industry a combination of processes, techniques and technologies that have been successfully implemented in the commercial, defense, and intelligence communities to identify, mitigate and continuously monitor the cyber security of critical systems. Guided by the results of a Cyber Security Risk-Based Assessment completed in Phase I, the Boeing-PJM team has completed multiple iterations through the Phase II Development and Phase III Deployment phases. Multiple cyber security solutions have been completed across a variety of controls including: Application Security, Enhanced Malware Detection, Security Incident and Event Management (SIEM) Optimization, Continuous Vulnerability Monitoring, SCADA Monitoring/Intrusion Detection, Operational Resiliency, Cyber Range simulations and hands on cyber security personnel training. All of the developed and demonstrated solutions are suitable for replication across the electric sector and/or the energy sector as a whole. Benefits identified include; Improved malware and intrusion detection capability on critical SCADA networks including behavioral-based alerts resulting in improved zero-day threat protection; Improved Security Incident and Event Management system resulting in better threat visibility, thus increasing the likelihood of detecting a serious event; Improved malware detection and zero-day threat response capability; Improved ability to systematically evaluate and secure in house and vendor sourced software applications; Improved ability to continuously monitor and maintain secure configuration of network devices resulting in reduced vulnerabilities for potential exploitation; Improved overall cyber security situational awareness through the integration of multiple discrete security technologies into a single cyber security reporting console; Improved ability to maintain the resiliency of critical systems in the face of a targeted cyber attack of other significant event; Improved ability to model complex networks for penetration testing and advanced training of cyber security personnel

24 POWER TRANSMISSION AND DISTRIBUTION↗

Electric Utility Distribution Costs: Scoping Study on Trends, Drivers, and Possible Response Strategies [Slides]

This scoping study synthesizes information that will help stakeholders understand the scope, scale, and drivers of recent increases in investor-owned utility (IOU) expenditures on local distribution power grids, while providing regulators and other decision-makers with potential strategies to keep electricity bills down. The study includes five distinct components. Drawing first on data from FERC Form 1, it summarizes key trends in past and recent IOU distribution costs. Next, through a review of a sample of distribution-system plans, it characterizes material drivers of planned distribution expenditures. Ultimately, regulators must approve cost recovery for IOU expenditures, including those for the distribution system. The study therefore also: examines trends in utility requests and regulatory approvals related to changes in retail rates and return on equity; identifies areas where utility shareholder and customer incentives may be misaligned; and develops a menu of options that state regulators might consider to optimize distribution system expenditures. Some of the key findings include: - IOU distribution spending at a national level has grown by 6%/yr since 2014 in real dollar terms, 4x faster than in the prior 20 years and consisting mostly of capital (not operating) expenditure. - On a per-kWh basis, increases in IOU distribution costs since 2014 represent over 30% of the overall national-average increase in retail electricity rates. - Regional spending growth has ranged from 2-8%/yr, with larger estimated rate impacts in CAISO, then NYISO & ISO-NE, and then the Southeast, MISO & PJM (see figure). - Some utilities are planning for significantly increased distribution system spending. Planned spending on managing the existing system (asset replacement, safety & reliability, and resilience are all important drivers) exceeds that for capacity expansion. - IOU rate increase requests ($18 billion in 2025) and public utility commission (PUC) approval levels (average of 64% of requested amounts from 2021-2025) have recently hit multi-decadal highs. - PUCs in New England and the Southeast have recently approved a greater fraction of rate requests (>75%, on average) than in ther regions, while PUCs in California and the Southeast have generally authorized higher equity returns than in other regions. - Regulators have many tools to tackle potential misalignments between utility and customer interests and, more specifically, to optimize and reduce distribution costs. Shorter-term options include those related to return on equity, capital structure, depreciation, trackers, construction work in progress, and securitization. Longer-term options include performance-based regulation and a wide variety of planning-related requirements. All options embed important tradeoffs.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Assurance by Design for Cyber Physical Data-Driven Systems

Currently, Cyber Physical Data-Driven Systems (CPDDS) employ machine learning for the classification, data fusion, and control of our nation’s infrastructure, such as the power grid, transportation networks (e.g., fuel distribution, air traffic control), and DoD long-duration collaborative autonomous platforms including unmanned underwater, ground, surface, space, and aerial systems. Many CPDDSs are system-of-systems that should be designed to communicate over disadvantaged networks. It is important to assure that the CPDDSs are resilient against physical and cyber threats by design. Additionally, their design should tolerate misclassification errors resulting from natural and/or adversarial distribution shifts within their data driven components. The all-domain nature of the problem of assuring the design of CPDDSs requires a multi-disciplinary perspective as outlined in this chapter.

Chikkagoudar, Satish↗

Multiple Functional Bonds Integrated Interphases for Long Cycle Sodium-Ion Batteries

Sodium-ion batteries (SIBs) have garnered significant interest as one of the most promising energy suppliers for power grid energy storage. However, the poor electrode/electrolyte interfacial stability leads to continual electrolyte decomposition and transition metal dissolution, resulting in rapid performance degradation of SIBs. In this work, we propose a strategy integrating multiple functional bonds to regulate electrode/electrolyte interphase by triple-coupling of succinonitrile (SN), sodium hexafluorophosphate (NaPF 6 ) and fluorinated ethylene carbonate (FEC). Theoretical calculation and experiment results show that the solvation structure of Na + and ClO 4 – is effectively reconfigured by the solvated FEC, SN and PF 6 – in PC-based carbonate electrolyte. The newly developed electrolyte demonstrates increased Na + -FEC coordination, weakened interaction of Na + -PC and participation of SN and PF 6 – anions in solvation, resulting in the formation of a conformal interfacial layer comprising of sodium oxynitrides (NaN x O y ), sodium fluoride (NaF) and phosphorus oxide compounds (NaP x O y ). Consequently, a 3 Ah pouch full cell of hard carbon//NaNi 1/3 Fe 1/3 Mn 1/3 O 2 exhibits an excellent capacity retention of 90.4 % after 1000 cycles. Detailed postmortem analysis of interface chemistry is further illustrated by multiple characterization methods. Finally, this study provides a new avenue for developing electrolyte formulations with multiple functional bonds integrated interphases to significantly improve the long-term cycling stability of SIBs.

25 ENERGY STORAGE↗

Overshadow PLC to Detect Remote Control-Logic Injection Attacks

Programmable logic controllers (PLCs) in industrial control systems (ICS) are vulnerable to remote control logic injection attacks. Attackers target the control logic of a PLC to manipulate the behavior of a physical process such as nuclear plants, power grids, and gas pipelines. Control logic attacks have been studied extensively in the literature, including hiding the transfer of a control logic over the network from both packet header-based signatures, and deep packet inspection. For instance, these attacks transfer a control logic code as data, into small fragments (one-byte per packet), that are further padded with noise data. To detect control logic in ICS network traffic, this paper presents Shade, a novel shadow memory technique that observes the network traffic to maintain a local copy of the current state of a PLC memory. To analyze the memory contents, Shade employs a classification algorithm with 42 unique features categorized into five types at different semantic levels of a control logic code, such as number of rungs, number of consecutive decompiled instructions, and n-grams. We then evaluate Shade against control logic injection attacks on two PLCs, Modicon M221 and MicroLogix 1400 from two ICS vendors, Schneider electric and Allen-Bradley, respectively. The evaluation results show that Shade can detect an attack instance (i.e., identifying at least one attack packet during the transfer of a malicious control logic) accurately without any false alarms.

Yoo, Hyunguk↗

Manufacture and Tests of a Bi2223/YBCO Coil for a 1-MJ/0.5-MVA Fault Current Limiter-Magnetic Energy Storage System

With the increasing of wind energy, it is necessary to develop an energy storage system to level the wave of wind power, and to develop a fault current limiter for improvement of the LVRT capability of the wind farm. An innovative idea to deal with the above problem is to develop a superconducting fault current limiter-magnetic energy storage system (SFCL-MES). In this paper, we report the progress of the superconducting coil for a 1-MJ/0.5-MVA FCL-SMES system. The coil consisted of 46 double pancakes, in which 8 pancakes were made of YBCO tapes and the others were made of Bi2223 tapes; the inductance of the coil was 13.3 H, and its rated current was 388 A while the maximum magnetic field was 3.5 T. This coil had been used for a FCL-SMES system, which was installed and tested at a wind farm connected to the live power grid.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Fabrication and Tests of a Resistive-Type Superconducting Fault Current Limiter Module Based on Coated Conductors

The resistivetype superconducting fault current limiter (R-SFCL) is simple in structure, near zero impedance at normal state and can be quickly triggered by the fault current. Thus, it is a possible solution to limit the fault current in the power grid. In this paper, we report the fabrication and test for an R-SFCL module The R-SFCL module consists of seven bifilar coils connected in parallel, which were wound with two parallel 2G tapes. A 5mm spacer was co-wound between adjacent turns to act as the highvoltage insulation. In the tests, we test the current distribution among the bifilar coils, and then simulated short-circuit tests were conducted on the module to obtain its performance under fault current surge.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Building simulation: Ten challenges

Buildings consume more than one-third of the world’s primary energy. Reducing energy use and greenhouse-gas emissions in the buildings sector through energy conservation and efficiency improvements constitutes a key strategy for achieving global energy and environmental goals. Building performance simulation has been increasingly used as a tool for designing, operating and retrofitting buildings to save energy and utility costs. However, opportunities remain for researchers, software developers, practitioners and policymakers to maximize the value of building performance simulation in the design and operation of low energy buildings and communities that leverage interdisciplinary approaches to integrate humans, buildings, and the power grid at a large scale. This paper presents ten challenges that highlight some of the most important issues in building performance simulation, covering the full building life cycle and a wide range of modeling scales. In conclusion, the formulation and discussion of each challenge aims to provide insights into the state-of-the-art and future research opportunities for each topic, and to inspire new questions from young researchers in this field.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Integration of a grey-box refrigerated case model in EnergyPlus via Python plugin

Commercial buildings, in particular grocery stores (due mainly to their large refrigeration load), provide opportunities for energy cost reductions. Grocery stores could offer substantial load flexibility to the power grid through participation in demand response programs because of their usage patterns and relatively high energy intensity. This load flexibility could come from modifying the control of heating, ventilation, and air conditioning (HVAC) systems, refrigeration systems, or both. Although estimation of the HVAC system’s load flexibility potential is relatively targeted in the literature, estimating load flexibility of refrigeration systems is nascent and has been a challenge, in part because of the lack of proper simulation tools that capture the dynamics in the refrigeration cases. The existing refrigerated case model within EnergyPlus, a whole building energy simulation program, assumes a constant case temperature throughout the simulation period and does not explicitly model the cycling of the compressor serving the refrigerated case. In addition, it does not encompass modeling of temperatures of the product inside the refrigerated case. This difference between modeled and actual operation can be a barrier to the development of demand control algorithm and accurate analysis of load flexibility potential. In this paper, we present a grey-box model for modeling refrigerated cases in grocery stores, which include medium temperature and low temperature. Four cases are modeled; two are low-temperature closed cases and two are medium-temperature cases with one closed and one open. Data from an experimental facility are used to train and test the models. Results demonstrate the efficacy of the grey-box models in predicting the temperatures. This model is integrated into EnergyPlus to capture the dynamic effects of case temperature on the environment and enhance the calculation of sensible and latent heat exchange with the environment (case credits). These enhancements can be leveraged more broadly to model advanced refrigeration controls such as defrost, develop and test unique algorithms that could affect refrigeration interactions with HVAC, and refine store design for any commercial building with refrigeration.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗