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At least 1,387 records · Page 77

A hybrid architecture for volt-var control in active distribution grids

Modern active distribution grids are characterized by the increasing penetration of distributed energy resources (DERs). The proper coordination and scheduling of a large numbers of these small-scale and spatially distributed DERs is necessary, and warrants the use of novel distributed approaches. In this paper, we propose a hybrid volt-var control architecture for the distribution grid, which leverages existing centralized and local approaches to planning, decision making, and control, and augments it with distributed optimization and distributed control for DER management. First, we propose a convex model to describe the power physics of distribution grids of meshed topology and unbalanced structure, based on current injection and McCormick Envelopes. Second, we employ the distributed proximal atomic coordination (PAC) algorithm to coordinate DERs to provide voltage support. We implement volt-var optimization by optimally coordinating DERs including PV smart inverters and demand response. We present results using the IEEE-34 bus network, using real data from a distribution feeder in Hawaii, to model load and PV generation. Different levels of DER penetration and objective functions are simulated. Finally, our results show the need for the coordination of DERs to improve voltage profiles, even in networks with existing voltage control devices. Further, we show the need for flexible reactive power capabilities to achieve desired grid performance.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Analysis of operating reserve demand curves in power system operations in the presence of variable generation

The electric power industry landscape is continually evolving. As emerging technologies such as wind and solar generating systems become more cost effective, traditional power system operating strategies will need to be re-evaluated. The presence of wind and solar generation (commonly referred to as variable generation or VG) can increase variability and uncertainty in the net-load profile. One mechanism to mitigate this issue is to schedule and dispatch additional operating reserves. These operating reserves aim to ensure that there is enough capacity online in the system to account for the increased variability and uncertainty occurring at finer temporal resolutions. A new operating reserve strategy, referred to as flexibility reserve, has been introduced in some regions. A similar implementation is explored in this study, and its implications on power system operations are analyzed. Results show that flexibility reserve products can improve economic metrics, particularly in significantly reducing the number of scarcity pricing events, with minimal impacts on reliability metrics and production costs. Furthermore, the production costs increased due to increased VG curtailment - i.e. including the flexible ramping product in the commitment of excess thermal capacity that needed to remain online at the expense of VG output.

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Power System Modeling for the Study of High Penetration of Distributed Photovoltaic Energy

Many conventional power systems are evolving due to the growth of renewable energy and distributed energy resources (DERs). Modeling the interplay of transmission and distribution systems is critical to analyze how DERs impact a system’s conventional operation and which electric infrastructure improvements are needed to achieve a balance between centralized generation and DERs. This article describes the process, tools, and resources used to model electric power systems with a centralized infrastructure in an isolated context and limited access to actual utility data. Photovoltaic systems installed on residential rooftops were the main design option. This work broadened the typical power system modeling to include planning and social considerations. This integrative engineering-social method allows for interdisciplinary teams to work in the development of a model as part of broader design goals for a renewable-dominant energy system. The Puerto Rico electric power system was used as a case study to demonstrate the process. The integrative engineering-social perspective in developing the model and the actions to manage data limitations are aspects that could be followed in other locations with aggressive renewable energy goals and where utility data are not readily available.

Cuello-Polo, Gustavo↗

Communication enabled fast-acting imbalance reserve

A system and method for control of dispatchable resources on an electrical power distribution grid is disclosed. The disclosed method provides improved response to power imbalance based on a communications signal independent of system frequency. The communication signal provides a feed-forward control of dispatchable power resources. A communications network is employed to generate a signal to dispatchable resources that a power imbalance has occurred. Due to fast response power transmission network interfaces associated with the dispatchable resources, the respective resources respond in significantly less time than feedback controlled conventional generators which depend on line frequency sensing. The rapid response mitigates the impact of power imbalances and enables greater penetrations of converter-interfaced power generation units such as renewable energy sources to be connected to the grid.

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Stability Assessment of a System Comprising a Single Machine and Inverter with Scalable Ratings

Synchronous machines have traditionally acted as the foundation of large-scale electrical infrastructures and their physical properties have formed the cornerstone of system operations. However, with the increased integration of distributed renewable resources and energy-storage technologies, there is a need to systematically acknowledge the dynamics of power-electronics inverters - the primary energy-conversion interface in such systems - in all aspects of modeling, analysis, and control of the bulk power network. In this paper, we assess the properties of coupled machine-inverter systems by studying an elementary system comprised of a synchronous generator, three-phase inverter, and a load. The inverter model is formulated such that its power rating can be scaled continuously across power levels while preserving its closed-loop response. Accordingly, the properties of the machine-inverter system can be assessed for varying ratios of machine-to-inverter power ratings. After linearizing the model and assessing its eigenvalues, we show that system stability is highly dependent on the inverter current controller and machine exciter, thus uncovering a key concern with mixed machine-inverter systems and motivating the need for next-generation grid-stabilizing inverter controls.

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THE VMC SURVEY. XVIII. RADIAL DEPENDENCE OF THE LOW-MASS, 0.55–0.82 M{sub ⊙} STELLAR MASS FUNCTION IN THE GALACTIC GLOBULAR CLUSTER 47 TUCANAE

We use near-infrared observations obtained as part of the Visible and Infrared Survey Telescope for Astronomy (VISTA) Survey of the Magellanic Clouds (VMC), as well as two complementary Hubble Space Telescope (HST) data sets, to study the luminosity and mass functions (MFs) as a function of clustercentric radius of the main-sequence stars in the Galactic globular cluster 47 Tucanae. The HST observations indicate a relative deficit in the numbers of faint stars in the central region of the cluster compared with its periphery, for 18.75 ≤ m{sub F606W} ≤ 20.9 mag (corresponding to a stellar mass range of 0.55 < m{sub *}/M{sub ⊙} < 0.73). The stellar number counts at 6.′7 from the cluster core show a deficit for 17.62 ≤ m{sub F606W} ≤ 19.7 mag (i.e., 0.65 < m{sub *}/M{sub ⊙} < 0.82), which is consistent with expectations from mass segregation. The VMC-based stellar MFs exhibit power-law shapes for masses in the range 0.55 < m{sub *}/M{sub ⊙} < 0.82. These power laws are characterized by an almost constant slope, α. The radial distribution of the power-law slopes α thus shows evidence of the importance of both mass segregation and tidal stripping, for both the first- and second-generation stars in 47 Tuc.

79 ASTRONOMY AND ASTROPHYSICS↗

Impedance Scan of Inverter-Based Resources and Diesel Generator for Stability Analysis

Impedance-based methods are widely used for power system stability analysis with inverter-based resources (IBRs), e.g., assessing dynamic interactions between the power grid and an IBR, control interactions between multiple IBRs, and the sub-synchronous oscillation and damping phenomenon. Since it is difficult to get a numerical model 100% matching with the hardware IBR, using the hardware inverter directly to obtain its output impedance has become a prominent approach nowadays. Therefore, this article presents the impedance scan using hardware IBRs, and also a hardware diesel generator as it still stays with the grid before the grid completely goes to renewable. The devices under test (DuTs) for the impedance scan includes two 3-..phi.., 480 V, 60 Hz commercial grid-forming IBRs (one of 250 kVA and another of 125 kVA rating) in series with ..delta..-Y transformers, one 3-..phi.., 480 V, 60 Hz commercial grid-following IBR (of 125 kVA rating), and a 3-..phi.., 480 V, 60 Hz commercial diesel generator (of 187.5 kVA rating). Using voltage signals perturbed with sub-, inter-, and higher harmonic components, and measuring the current response, the positive-sequence impedances are computed via an offline-based post-analysis. Moreover, best-fit transfer functions are estimated that closely resemble the measured data points of the positive-sequence impedances. Based on the observations from various outcomes of the hardware experiments, this article also provides some fundamental insights on the equivalent positive-sequence impedance of a combination of multiple hardware components by comparing the estimated and the empirically computed impedances. A comparative insight on the damping capability of the DuTs using the positive-sequence impedances of the hardware is also discussed.

current measurement↗

Adaptive Deep Reinforcement Learning Algorithm for Distribution System Cyber Attack Defense With High Penetration of DERs

With grid modernization, smart inverters are increasingly used to execute advanced controls for distribution network reliability. However, this also increases the cyber-attack space. Here this paper focuses on the defense approaches to restore the system to normal operation circumstances in the presence of cyber-attacks. A unique deep reinforcement learning (DRL) method is developed to minimize voltage violations and reduce power losses for impacted feeders. The defense problem is reformulated as a Markov decision-making process to dynamically control DERs while minimizing load shedding. This is achieved via an improved soft actor-critic (SAC)-based DRL algorithm, which can govern DER set points and load-shedding scenarios in discrete and continuous modes via the auto-tune entropy and Gaussian policy features. Numerical comparison results on the modified IEEE 123-node system with other control approaches, such as Volt-VAR (VV), Volt-Watt (VW), and model predictive control (MPC) show that the proposed method can eliminate voltage violations and provide feasible control actions that perform complete mitigation of cyber-threats.

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Residential PV-Energy Storage Testing Collaboration with SunPower: Cooperative Research and Development Final Report, CRADA Number CRD-14-569

Residential scale energy storage devices have shown great promise to add value and improve the ability to integrate distributed and variable generation into the distribution grid. Battery energy storage systems combined with PV and advanced inverters can provide many services. These include extended backup power in case of grid failure, reductions in feeder and system level peak load, system level net load ramp reduction, grid management services both locally (e.g., voltage management) and bulk system (e.g., reserves) level, and improved grid reliability through grid voltage and frequency support. Even though the cost of the energy storage systems are decreasing, one of the main challenges related to the widespread deployment of energy storage, as found by the U.S. Department of Energy (DOE), is utility acceptance of storage technologies. Various interconnection challenges exist when connecting distributed PV-energy storage into the electrical distribution grid in terms of safety, reliability and stability of the electric power systems. Some of the urgent challenges, as seen by the manufacturers and installers are: safety of the battery cells and the packs, performance of the power conversion systems, effect of bidirectional power flow on existing utility equipment and qualification of solutions such as volt-ampere reactive (VAR) support and frequency regulation. Under this project, National Renewable Energy Laboratory (NREL) researchers will work with SunPower to address these challenges by research, testing and analysis at Energy System Integration Facility (ESIF) and energy storage testing laboratory at NREL. NREL's unique power hardware-in-the-loop (PHIL) capability will be utilized to evaluate system-level issues such as reverse power flow and VAR support (if available) for these PV-energy storage systems. Through the analysis of test results, the proposed project will demonstrate use of ESIF capabilities in a way that advances both the DOE and SunPower's goals of moving clean, renewable energy technologies onto the electrical grid.

14 SOLAR ENERGY↗

2023 Standard Scenarios Report: A U.S. Electricity Sector Outlook

This report, originally published in December 2023, has been revised in January 2024. There were three changes in the revision. First, Anthony Lopez was added as a contributing author, as he had been erroneously omitted in the original publication. Second, in appendix section A.1 the cost of upgrading a hydrogen combustion turbine from a natural gas turbine was erroneously reported as 20% when it should have been 33%. Lastly, appendix Figure A-8 was erroneously a duplication of the same figure from the Standard Scenarios 2022, it has now been updated to reflect this year’s data.

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Electron and Proton Acceleration in Trans-relativistic Magnetic Reconnection: Dependence on Plasma Beta and Magnetization

Nonthermal electron acceleration via magnetic reconnection is thought to play an important role in powering the variable X-ray emission from radiatively inefficient accretion flows around black holes. The trans-relativistic regime of magnetic reconnection—where the magnetization σ, defined as the ratio of magnetic energy density to enthalpy density, is ~1—is frequently encountered in such flows. By means of a large suite of two-dimensional particle-in-cell simulations, we investigate electron and proton acceleration in the trans-relativistic regime. Additionally, we focus on the dependence of the electron energy spectrum on σ and the proton β (the ratio of proton thermal pressure to magnetic pressure). We find that the electron spectrum in the reconnection region is nonthermal and can be modeled as a power law. At low β, the slope, p, is independent of β and hardens with increasing σ as $p\simeq 1.8+0.7/\sqrt{\sigma }$. Electrons are primarily accelerated by the nonideal electric field at X-points, either in the initial current layer or in current sheets generated between merging magnetic islands. At higher values of β, the electron power law steepens, and the electron spectrum eventually approaches a Maxwellian distribution for all values of σ. At values of β near β max ≈ 1/4σ, when both electrons and protons are relativistically hot prior to reconnection, the spectra of both species display an additional component at high energies, containing a few percent of particles. Finally, these particles are accelerated via a Fermi-like process by bouncing between the reconnection outflow and a stationary magnetic island

43 PARTICLE ACCELERATORS↗

Experiments on neural network architectures for fuzzy logic

The use of fuzzy logic to model and manage uncertainty in a rule-based system places high computational demands on an inference engine. In an earlier paper, the authors introduced a trainable neural network structure for fuzzy logic. These networks can learn and extrapolate complex relationships between possibility distributions for the antecedents and consequents in the rules. Here, the power of these networks is further explored. The insensitivity of the output to noisy input distributions (which are likely if the clauses are generated from real data) is demonstrated as well as the ability of the networks to internalize multiple conjunctive clause and disjunctive clause rules. Since different rules with the same variables can be encoded in a single network, this approach to fuzzy logic inference provides a natural mechanism for rule conflict resolution.

Keller, James M.↗

Far Noise Field of Air Jets and Jet Engines

An experimental investigation was conducted to study and compare the acoustic radiation of air jets and jet engines. A number of different nozzle-exit shapes were studied with air jets to determine the effect of exit shape on noise generation. Circular, square, rectangular, and elliptical convergent nozzles and convergent-divergent and plug nozzles were investigated. The spectral distributions of the sound power for the engine and the air jet were in good agreement for the case where the engine data were not greatly affected by reflection or jet interference effects. Such power spectra for a subsonic or slightly choked engine or air jet show that the peaks of the spectra occur at a Strouhal number of 0.3.

Callaghan, Edmund E↗

Lunar Microgrid Trade Studies to Define Interface Converter Requirements

The National Aeronautics and Space Administration (NASA) is interested in developing an incremental lunar power grid to support continuous human/robotic operations under the Artemis missions and can scale to global power utilization and industrial power levels. The initial lunar surface power system will be composed primarily of assets that contain their own power generation and energy storage. These assets can be connected to form a grid, which allows power to be shared between the system’s distributed energy resources. This grid can provide backup power to existing assets as well as primary power to future assets. A trade study was conducted for an Artemis scale grid, which has identified 3 kVAC as an ideal transmission voltage. This paper documents the analysis and findings from these trade studies. These studies were used to define the operating voltage and develop a common interface for connecting lunar surface assets to the power grid. The Universal Modular Interface Converter (UMIC) connects lunar surface assets to the high voltage grid. Products from this grid definition and UMIC development work will enable highly reliable and available power for Artemis and future planetary surface missions, which is key to achieving NASA’s long-term vision of space exploration.

Planetary surface power↗

An improved synthetic signal injection routine for the Haloscope At Yale Sensitive To Axion Cold dark matter (HAYSTAC)

Microwave cavity haloscopes are among the most sensitive direct detection experiments searching for dark matter axions via their coupling to photons. When the power of the expected microwave signal due to axion–photon conversion is on the order of 10 −24 W, having the ability to validate the detector response and analysis procedure by injecting realistic synthetic axion signals becomes helpful. Here, we present a method based on frequency hopping spread spectrum for synthesizing axion signals in a microwave cavity haloscope experiment. It allows us to generate a narrow and asymmetric shape in frequency space that mimics an axion’s spectral distribution, which is derived from a Maxwell–Boltzmann distribution. In addition, we show that the synthetic axion’s power can be calibrated with reference to the system noise. Further, compared to the synthetic axion injection in the Haloscope At Yale Sensitive to Axion Cold dark matter (HAYSTAC) Phase I, we demonstrated synthetic signal injection with a more realistic line shape and calibrated power.

47 OTHER INSTRUMENTATION↗

Peer-to-peer communication control for resilient operations of networked cyberphysical systems

This report includes two main accomplishments of the peer-to-peer communication control for resilient operation of networked microgrids project in FY24, which include a scheme for cyberattack-aware coordination of networked microgrids for supporting voltages of bulk power systems and a scheme for price signal-based operations of EV-rich networked microgrids with mixed ownership. First, the cyberattack-aware scheme enables networked microgrids to distributedly determine the amount of reactive power injection to support the voltage of bulk power system (BPS) in a fair manner. In this scheme, a risk-informed algorithm is presented to generate the peer-to- peer (P2P) communication graph with minimal risk of attack on communication links. To deal with cyberattacks on MG controllers, the resilient consensus algorithm (CA) is utilized for MG controllers to robustly estimate the total reactive power headroom, from which the MGs can accurately provide the needed amount of reactive power injection for supporting the voltage of BPS. The CA implementation and performance within the P2P communication framework are demonstrated on the IEEE 39-bus system with 6 microgrids contained in the distribution feeder under different cyberattack scenarios. Second, the price-based scheme enables the usage of the real-time price signal for the operations of electric vehicle (EV)-rich networked-microgrids with mixed ownership, in which not all the microgrids can communicate with the distribution system operator (DSO). In this scheme, a max consensus is introduced to enable the real-time price signal to be propagated from the DSO to all the microgrids, from which each microgrid controller will manage the DERs to balance the load demand and the power injection from the EV charging stations within its microgrid. Numerical results over one day with 288 slots of 5-minute intervals on the modified 123-node test feeder including 3 microgrids with high penetration of EV are presented to evaluate how the price signal affects the operations of networked microgrids under different charging strategies of the EV charging stations. The result indicates that our proposed EVCS (dis)charging strategy, which leverages the flexibility of EVs to support the grid through discharging during peak demand, proves to be a cost-effective solution that reduces operational costs while improving the social welfare of EV charging.

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Chance-Constrained AC Optimal Power Flow for Distribution Systems With Renewables

This paper focuses on distribution systems featuring renewable energy sources (RESs) and energy storage systems, and presents an AC optimal power flow (OPF) approach to optimize system-level performance objectives while coping with uncertainty in both RES generation and loads. The proposed method hinges on a chance-constrained AC OPF formulation where probabilistic constraints are utilized to enforce voltage regulation with prescribed probability. A computationally more affordable convex reformulation is developed by resorting to suitable linear approximations of the AC power-flow equations as well as convex approximations of the chance constraints. The approximate chance constraints provide conservative bounds that hold for arbitrary distributions of the forecasting errors. An adaptive strategy is then obtained by embedding the proposed AC OPF task into a model predictive control framework. Finally, a distributed solver is developed to strategically distribute the solution of the optimization problems across utility and customers.

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