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At least 577 records · Page 32

Disruptive Photovoltaic Technologies Can Accelerate Global Decarbonization

This contribution explores PV manufacturing capacity expansion trajectories needed to achieve the goal of global decarbonization assuming that investors make financially rational decisions avoiding stranded production assets while still effectively exploiting experience curve benefits in both manufacturing process and product design. Substantial production cost savings and timely decarbonization risk mitigation could accrue by adoption and scaling of high efficiency multijunction device architectures and thin film direct bandgap semiconductor technologies that provide lower manufacturing capital intensity. We demonstrate that there is a $1-2 trillion market opportunity for such disruptive technologies while also providing hundreds of billions of dollars of cost savings to reach total decarbonization.

decarbonization↗

The Effect of Clean Energy Generation Targets on the Portfolio of Electric Grid Generation Technologies

A least-cost generation and transmission expansion planning model is used to optimize the U.S. generation portfolio in 2030 under a range of Clean Energy Generation Target (CEGT) policy goals. As reference cases for comparison, the model is used to optimize the generation portfolio for the future electric grid with and without the Investment and Production Tax Credits (ITC and PTC). Next, the model is used to optimize the generation portfolio with a CEGT ranging from 10% to 70%. The results show that due to the ITC and PTC extensions by the 2022 Inflation Reduction Act, there is little additional investment in renewable energy generation assets at low CEGT levels. Significant additional installations of both renewable energy generation and energy storage systems – both batteries and pumped storage hydro – become important at CEGT levels above approximately 30%.

Aldeman, Matthew↗

High-Penetration Microgrids Providing Grid Stability Using Frequency Watt Control

The U.S. grid is rapidly transitioning towards utilizing inverter-based renewable energy resources such as solar, wind, and batteries, reducing the carbon emission footprint. Inverter-based microgrid control architectures remain a critical focus to address power system stability issues in future high penetration markets lacking spinning generation assets. Idaho National Laboratory (INL) is researching an active layered inverter based frequency-Watt control scheme that provides distribution level stability in high-penetration markets where grid inertia is lacking. Hardware in the loop case study was implemented using INL’s Microgrid Testbed to combat scalable frequency deviations ranging from 60 Hz down to 50 Hz initialized by a hydropower model implementing step loads using a 540-kW grid emulator. Our research findings demonstrate the importance of distribution level, inverter-based active frequency-Watt controls utilizing a battery energy storage system (BESS) to provide adequate frequency support at the point of common coupling without major power infrastructure upgrades.

14 SOLAR ENERGY↗

Experiments and Project-Based Enhancements for STEM Learning

Motivating K-12 students to pursue careers in science, technology, engineering, and mathematics (STEM) is an effort that requires consistent engagement. Throughout the K-12 student timeline, STEM educators need to continuously pivot their teaching and update their educational materials to motivate the next generation of students. Once students begin their undergraduate education, university professors need to encourage them to consider pursuing graduate studies to ensure that a qualified future workforce can be developed for research and teaching. In this paper, we present our work on developing STEM materials for K-12 student engagement. Our K-12 materials target the grid integration of hydrogen assets that are suitable to engage students in the classroom. Our undergraduate materials target hands-on projects and collaboration with industry to connect classroom learning with real-world applications and needs in renewable energy. Our work leverages available open-source models and tools to create projects for undergraduate students and motivate their interest in pursuing research topics in graduate-level education.

ENERGY PLANNING, POLICY, AND ECONOMY↗

Scalable Wind Turbine Generator Bearing Fault Prediction Using Machine Learning: A Case Study

Operation and maintenance (O&M) costs for wind turbines pose a risk to competitiveness and asset owners. With machine-learning technologies and digitalization rapidly maturing, the wind industry is actively investigating these new technologies to optimize O&M practices and reduce costs. This paper reviews recent work on machine-learning approaches to generator bearing failure prediction and presents a relevant real-world case study through a collaboration between the National Renewable Energy Laboratory and Envision Digital Corporation. In the case study, we evaluate the performance of representative machine-learning algorithms for predicting wind turbine generator bearing failures. Operational supervisory control and data acquisition data from one wind power plant was used to train and test the machine-learning models. The investigated data channels are chosen based on whether physically they reflect the failed generator bearing conditions and the component historical usage, including both environmental and operational conditions. Benefits and drawbacks of different methods are identified.

generator bearing failures↗

An Alternative Timing and Synchronization Approach for Situational Awareness and Predictive Analytics

Accurate and synchronized timing information is required by power system operators for controlling the grid infrastructure (relays, Phasor Measurement Units (PMUs), etc.) and determining asset positions. Satellite-based global positioning system (GPS) is the primary source of timing information. However, GPS disruptions today (both intentional and unintentional) can significantly compromise the reliability and security of our electric grids. A robust alternate source for accurate timing is critical to serve both as a deterrent against malicious attacks and as a redundant system in enhancing the resilience against extreme events that could disrupt the GPS network. To achieve this, we rely on the highly accurate, terrestrial atomic clock-based network for alternative timing and synchronization. In this paper, we discuss an experimental setup for an alternative timing approach. The data obtained from this experimental setup is continuously monitored and analyzed using various time deviation metrics. We also use these metrics to compute deviations of our clock with respect to the National Institute of Standards and Technologys (NIST) GPS data. The results obtained from these metric computations are elaborately discussed. Finally, we discuss the integration of the procedures involved, like real-time data ingestion, metric computation, and result visualization, in a novel microservices-based architecture for situational awareness.

Chinthavali, Supriya↗

Experimental Test Bed to Enable Realistic Evaluations for Direct Transfer Trip Relaying via Private Wireless LTE Communications

Increasing penetration levels of inverter-based distributed energy resources (DERs) in distribution systems are creating challenges in system operation. Currently, wired or proprietary wireless communications are used by advanced distribution management systems (ADMS) to detect the state of the system and control the DERs for optimal operation. Wireless communications are an alternative solution that can enable connectivity between the dispersed assets used in distribution system applications. This paper demonstrates an experimental test bed to enable the realistic evaluation of communications system characteristics for direct transfer trip (DTT) relaying of a photovoltaic inverter system using a private 900-MHz spectrum wireless LTE network. Private LTE network communications can be deployed to many remote DERs and other grid-edge devices to prevent costly infrastructure upgrades across distribution systems. In addition, this paper provides a framework for evaluating the impact of signal strength and network traffic in communications systems. The results shown develop a better understanding of the best practices for using LTE communications systems across multiple utility applications, such as protective relaying, voltage regulation, and supervisory control and data acquisition system messages.

900-MHz LTE network↗

Monte Carlo-based Transmission and Subtransmission Recovery Simulation of Hurricanes

High-impact low-probability (HILP) events can wreak havoc on electric power systems without appropriate preparedness. In this paper, the recent development of a tool, named Recovery Simulator and Analysis (RSA), is described and demonstrated. While there are many issues to consider when recovering electric power systems, the focus of RSA is on the coordination of transmission and subtransmission recovery with generation dispatch to minimize unserved energy. RSA focuses on recovery simulation to evaluate resilience as part of a planning process. RSA is demonstrated on an approximately 1400-bus Puerto Rican power system for 100 simulated instances of Hurricane Maria. Analysis of the recovery determines how many lines are critical to the recovery and which loads may experience delayed recovery. The results demonstrate the potential uses of RSA for identifying recovery decisions with low unserved energy and for identifying assets critical to recovery which can then be hardened prior to a HILP event.

Maloney, Patrick R.↗

Smart Data Mapping for Connecting Power System Model and Geospatial Data

Knowing the geospatial locations of power system model elements is the foundation for analyzing system vulnerability to natural hazards and connecting loads with end users and their communities. However, power system models and geospatial data for power grid assets may have been developed asynchronously without close coordination. Creating a direct mapping between the two may be a challenging task, considering heterogeneous data structures, target uses, historical legacies, and human errors. This work aims to build an automatic data mapping workflow to connect power system model elements and geospatial data for transmission network, and to support energy grid resilience studies for Puerto Rico. The primary steps in this workflow include constructing graphs using geospatial data, and aligning them to the transmission networks defined in the power system data. The results have been evaluated against existing manual mapping practices for part of the Puerto Rico Power Grid model to illustrate the performance of such auto-mapping solutions.

Resilience, geospatial data, grid transmission net↗

Understanding Impacts of Data Integrity Attacks on Transactive Control Systems

With the rapid growth of internet-connected smart devices capable of exchanging energy price information and adaptively controlling energy consumption of connected loads, the role of transactive control is expected to become more prominent in the modern grid. Transactive control systems integrate the wholesale and retail energy markets, and enable active participation of end users, thereby playing a key role in managing the rising number of distributed assets in the smart grid. The use of internet for the communication of data between the controllers at the building, distribution, and transmission levels makes the system susceptible to cyber-attacks. A skilled adversary can potentially manipulate the exchanged data with the intention of inflicting damage to the system. In this paper, four categories of metrics are put forth for evaluating the performance of the system when under data integrity attacks. A model for scaling-based data integrity attack has been described, and co-simulations have been performed on a 240 bus WECC transmission system model with detailed modeling of distribution systems at specific buses. Our results show that scaling-based data integrity attacks can have non-trivial impacts on the operational, financial, and comfort aspects of the transactive control system.

Smart grid, transactive control system, Buildings-↗

Hierarchical Model-Free Transactive Control of Residential Building Loads: An Actual Deployment

The transformation of electricity systems into more sustainable configurations brought some new challenges. The uncertain, intermittent, and variable nature of renewable energy sources require a significant amount of load demand flexibility, in which grid-interactive buildings (GEBs) are important flexible assets for electricity systems. In this regard, many demand response (DR) tools have been developed to harness this demand flexibility. However, such tools are mostly simulation-based or deal with a single load, which may not be sufficient to demonstrate their effectiveness. Towards this end, this paper presents a real-world field implementation and testing of a hierarchical model-free transactive DR control approach on actual GEBs. The control implementation incorporates elements of virtual battery, game theory, and model-free control mechanisms. The proposed approach was tested using a total of five GEBs, each having three zones. The results show that the proposed approach can mostly achieve all intended objectives, including flexibility estimation, peak load reduction, power tracking, and controlling GEBs while maintaining occupants’ comfort.

Amasyali, Kadir↗

Flexibility Requirements for Energy Systems with Renewable Generation under Forecast Uncertainties

Energy systems with high fractions of renewable energy-based resources require adequate assets providing flexibility in electricity usage to maximize the benefits of renewable energy. In this paper, we provide an analytical approach to estimate the flexibility requirements of such energy systems, with forecast uncertainties in both demand and generation. Our analytical results show that even with forecast errors, the expected system operating cost decreases with an increase in the amount of flexibility capacity -- however, there is an inflection point, beyond which addition of further flexibility capacity does not reduce expected system cost any further. Additionally, an enumeration-based approach is presented to estimate the maximum flexibility capacity needed to optimize the operating cost. Numerical experiments conducted on a network-abstracted modified IEEE 30-bus system are used for empirical validation and gaining additional insights on the effect of prosumers' willingness to offer flexibility on the dispatch performance.

Bhattacharya, Saptarshi↗

SMARTER Rules-Based Distributed Deconfliction of ADMS Applications

A conceptual numerical methodology derived from Grid Architecture principles is introduced for deconflicting setpoints issued by multiple advanced distribution management system applications. The methodology applies technical, economic, environmental, and social rules to eliminate non-viable combinations. The concept of temporal equipment controls budgets is introduced to preserve the health of physical assets and avoid equipment damage through repeated controls cycling. The rules are combined with a multi-criteria decision-making framework to select a near-optimal set of deconflicted setpoints using a set of qualitative and quantitative decision criteria selected by the distribution system operator. Numerical results are demonstrated on the IEEE 123-bus test feeder for three competing applications. Three alternative distributed schemes are used to decompose the problem: by topological area, by phase, and fully decentralized. The fully decentralized implementation is shown to yield near-optimal deconfliction results with significantly reduced computational time.

Anderson, Alexander A.↗

Medium-Duty Delivery Truck Integrated Bidirectional Wireless Power Transfer System With Grid and Stationary Energy Storage System Connectivity

Electric vehicles (EVs) can provide power to the grid or buildings similar to distributed energy resources (DER) for energy balancing applications or optimizing the operation of the microgrids in harmony with the other DER assets. This article presents the operating modes of a bidirectional wireless power transfer (WPT) system designed for a medium-duty package delivery vehicle. The WPT system designed for this study can transfer 20 kW of power across 11 in of air gap using custom-designed double-D (DD) couplers with LCC–LCC tuning networks. The proposed system utilizes a 480-V three-phase grid connection, a plug-in hybrid delivery truck with bidirectional WPT, and a stationary energy storage system (SESS) that can be connected to the primary-side dc link. Due to the differences in primary and secondary dc bus voltages, and considering the voltage of the SESS, asymmetric voltage gains were used in the system. Sensitivity analyses of this system with respect to these voltage levels are presented. Five different operating modes of the grid, SESS, and the EV battery are investigated with experimental results. Control algorithms are described for grid-to-vehicle (G2V) and vehicle-to-grid (V2G) operating modes. A bidirectional WPT system is operated with a power factor of 0.99 on the grid side in every operating mode. The EV battery was charged with 20.3 kW with an overall efficiency of 93.02% in the G2V operating mode. Finally, in the V2G operating mode, the WPT system provided 12.82 kW of power back to the grid with an overall efficiency of 89.08%.

25 ENERGY STORAGE↗

Verifying Deep Reductions in the Nuclear Arsenals: Development and Demonstration of a Motion-detection Subsystem for a “Buddy Tag” Using Non-export Controlled Accelerometers

Future nuclear arms-control agreements may place numerical limits on items that are difficult to monitor with national technical means, even when complemented with onsite inspections. Such items could include small objects and mobile assets, such as non-deployed nuclear warheads and mobile missile launchers. Typically, this verification task can be addressed with unique identifiers, but standard tagging techniques may be unacceptable in this case due to host concerns about safety and intrusiveness. First proposed in the late 1980s and partially developed by Sandia National Laboratories in the early 1990s, the “Proximity Tag” or “Buddy Tag” concept seeks to overcome these concerns by separating the tag from the treaty accountable item itself. A buddy tag has two key elements: a tamper-indicating enclosure and a motion-detection system designed to detect illicit movements in a stand-down period. As part of this project, we have built a buddy-tag prototype for demonstration and evaluation purposes. This paper reviews the design choices and functionalities of the tag’s motion-detection subsystem.We pursue a modular approach for the tag’s hardware, built around an Arduino-class microcontroller and a non-export-controlled low-noise accelerometer, and use open-source algorithms for the motion-detection software. Finally, we discuss the results of an extensive experimental campaign involving both indoor and outdoor measurements assessing the performance of the tag under real-world environmental conditions.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

The Effect of Prosumer Duality on Power Market: The Effect of Market Regulation

Electricity prosumers are energy subsystems that not only consume, but also produce electricity. They are present in distribution level networks as traditional utility customers who have installed distributed energy resources. They are also present in transmission level networks as large conglomerates own both generation assets and large industrial loads. Previous work on the economics of prosumers has demonstrated that prosumers in a market have incentives to behave more competitively compared to producers and consumers in traditional markets. This paper further explores the behavior of prosumers and their response to market policies including the allocation of network losses and the impact of net metering. We extend a Cournot model of a dual prosumer and find that prosumers respond with higher supply quantities if network losses are allocated to demand base. They respond with lower supply quantities if network losses are allocated to supply base. Allocating network losses to demand base also causes equilibrium prices to decline. Markets where prosumers first satisfy their own load and then sell the balance of electricity to the grid have lower quantities and higher prices compared to markets where prosumers buy and sell at locational marginal price.

Tsybina, Eve↗

Reduced-Order Models of Static Power Grids based on Spectral Clustering

For large-scale interconnected power systems that cover large geographical areas, certain electrical studies are required so that appropriate decisions ensure system reliability and low cost. For such studies, it is often neither practical nor necessary to model in detail the entire power system, which is increasingly complex due to a more diverse range of grid assets to choose from in both short and long-term planning. The goal of this paper is to present a methodology to reduce the order of large-scale power networks based on spectral graph theory given that current methods for static network reduction are not scalable. A brief analysis of some spectral clustering properties to determine which graph Laplacian matrix should be used and why is included. The analysis shows that the utilization of the normalized graph Laplacian is more advantageous for clustering purposes. Techniques are proposed to approximate cost functions for the aggregated generators. This is done via linear regression. The reduced-order model obtained with the proposed methodology has an accuracy above 94% and solves the scalability issue commonly present in other reduction methods. If the utilization of the reduced-order model is either constrained to load levels above mid-peak demand, or cost functions of aggregated units are approximated via a piecewise quadratic approach, then the error distribution is in the order of 10^-3. .

Baquedano-Aguilar, Mario D.↗

Optimal Energy Dispatch of Distributed PVs for the Next Generation of Distribution Management Systems

Advanced Distribution Management Systems (ADMS) are being widely adopted by electric utilities for managing and optimizing the operations of their distribution systems. Distributed photovoltaic (DPV) systems with smart inverters can be controlled to adjust active power and reactive power outputs, and they are envisioned to become a part of (centrally or distributed) controllable assets managed by the ADMS for optimizing grid operations. This paper proposes an optimal energy dispatch strategy controlling DPV systems for regulating distribution voltages and achieving conservation voltage reduction. A convex optimization model is proposed with the use of linearized power flow, and the gradient projection algorithm is used to solve the optimal active power and reactive power outputs of smart inverters. The proposed optimal energy dispatch is implemented using an open-source ADMS platform, and simulation results have demonstrated the effectiveness of the proposed approach on improving distribution grid operations.

42 ENGINEERING↗