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At least 559 records · Page 31

The Development of a Highly Reliable Power Management and Distribution System for Civil Transport Aircraft

NASA is pursuing a program in Advanced Subsonic Transport (AST) to develop the technology for a highly reliable Fly-By-Light/Power-By-WIre aircraft. One of the primary objectives of the program is to develop the technology base for confident application of integrated PBW components and systems to transport aircraft to improve operating reliability and efficiency. Technology will be developed so that the present hydraulic and pneumatic systems of the aircraft can be systematically eliminated and replaced by electrical systems. These motor driven actuators would move the aircraft wing surfaces as well as the rudder to provide steering controls for the pilot. Existing aircraft electrical systems are not flight critical and are prone to failure due to Electromagnetic Interference (EMI) (1), ground faults and component failures. In order to successfully implement electromechanical flight control actuation, a Power Management and Distribution (PMAD) System must be designed having a reliability of 1 failure in 10(exp +9) hours, EMI hardening and a fault tolerance architecture to ensure uninterrupted power to all aircraft flight critical systems. The focus of this paper is to analyze, define, and describe technically challenging areas associated with the development of a Power By Wire Aircraft and typical requirements to be established at the box level. The authors will attempt to propose areas of investigation, citing specific military standards and requirements that need to be revised to accommodate the 'More Electric Aircraft Systems'.

Coleman, Anthony S.↗

Energy Scheduling-based Operating Envelopes including a Distribution System Branch Screening Algorithm

This paper presents an energy scheduling-based formulation for computing operating envelopes including a distribution branch screening algorithm, termed DBS-ES. The contribution of the paper is two-fold: firstly, it presents an innovative methodology for calculating operating envelopes using energy scheduling (baseline), and secondly, it enhances this methodology by incorporating a custom distribution branch screening algorithm (DBS-ES). The custom algorithm leverages power system knowledge to reduce both model build time and total processing time while maintaining the same scheduling results as the baseline. The effectiveness of the proposed approach is demonstrated through experiments on the IEEE13, IEEE123, and EPRI Secondary test feeders. Results highlight a 24.5% decrease in model build time and an 8.17% decrease in total processing time when using DBS-ES compared to the baseline, specifically for the IEEE123 test feeder. Additionally, the paper briefly discusses the influence of utility-controlled storage on computing operating envelopes, noting a general incre

24 POWER TRANSMISSION AND DISTRIBUTION↗

Computer modeling and simulation of a 20kHz ac distribution system for Space Station

A computer model of a 20 kHz, ac distribution testbed for Space Station is presented. The system consists of six resonant inverters, a one-hundred-meter transmission line, and three load receivers: a dc receiver, a bidirectional receiver, and an ac receiver. A model library is generated characterizing all system components. The system's local and global behaviors are investigated using the EASY5 dynamic analysis program.

Tsai, Fu-Sheng↗

Advanced Semi-Supervised Learning with Uncertainty Estimation for Phase Identification in Distribution Systems

The integration of advanced metering infrastructure (AMI) into power distribution networks generates valuable data for tasks such as phase identification; however, the limited and unreliable availability of labeled data in the form of customer phase connectivity presents challenges. To address this issue, we propose a semi-supervised learning (SSL) framework that effectively leverages labeled and unlabeled data. Our approach incorporates self-training, label spreading, and Bayesian neural networks (BNNs) to enhance phase identification with AMI data. Our method uses an ensemble of multilayer perceptron classifiers in a self-training setup, iteratively adding high-confidence pseudo-labels to improve robustness. We also apply label spread to propagate labels based on data similarity, which enhances generalization across diverse distributions. In addition, we employ a BNNs with uncertainty estimation, boosting confidence in predictions and reducing phase identification errors. In our case study, we achieved approximately 98% +/- 0.08 accuracy with uncertainty using minimal and unreliable labeled data from a real U.S. utility, Duquesne Light Company. Our SSL approach, combined with uncertainty estimation, provides an efficient solution for phase identification in AMI data, ultimately improving the reliability of smart grid applications.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Advanced Semi-Supervised Learning With Uncertainty Estimation for Phase Identification in Distribution Systems

The integration of advanced metering infrastructure (AMI) into power distribution networks generates valuable data for tasks such as phase identification; however, the limited and unreliable availability of labeled data in the form of customer phase connectivity presents challenges. To address this issue, we propose a semi-supervised learning (SSL) framework that effectively leverages labeled and unlabeled data. Our approach incorporates self-training, label spreading, and Bayesian neural networks (BNNs) to enhance phase identification with AMI data. Our method uses an ensemble of multilayer perceptron classifiers in a self-training setup, iteratively adding high-confidence pseudo-labels to improve robustness. We also apply label spread to propagate labels based on data similarity, which enhances generalization across diverse distributions. In addition, we employ a BNNs with uncertainty estimation, boosting confidence in predictions and reducing phase identification errors. In our case study, we achieved approximately 98% +/- 0.08 accuracy with uncertainty using minimal and unreliable labeled data from a real U.S. utility, Duquesne Light Company. Our SSL approach, combined with uncertainty estimation, provides an efficient solution for phase identification in AMI data, ultimately improving the reliability of smart grid applications.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Power Management and Distribution System Developed for Thermionic Power Converters

A spacecraft solar, bimodal system combines propulsion and power generation into a single integrated system. An Integrated Solar Upper Stage (ISUS) provides orbital transfer capabilities, power generation for payloads, and onboard propulsion to the spacecraft. A key benefit of a bimodal system is a greater payload-to-spacecraft mass ratio resulting in lower launch vehicle requirements. Scaling down to smaller launch vehicles increases space access by reducing overall mission cost. NASA has joined efforts with the Air Force Phillips Laboratory to develop enabling technologies for such a system. The NASA/Air Force bimodal concept uses solar concentrators to focus energy into an integrated power plant. This power plant consists of a graphite core that stores thermal energy within a cavity. An array of thermionic converters encircles the graphite cavity and provides electrical energy conversion functions. During the power generation phase of the bimodal system, the thermionic converters are exposed to the heated cavity and convert the thermal energy to electricity. Near-term efforts of the ISUS bimodal program are focused on a ground demonstration of key technologies in order to proceed to a full space flight test. Thermionic power generation is one key technology of the bimodal concept. Thermionic power converters impose unique operating requirements upon a power management and distribution (PMAD) system design. Single thermionic converters supply large currents at very low voltages. Operating voltages can vary over a range of up to 3 to 1 as a function of operating temperature. Most spacecraft loads require regulated 28-volts direct-current (Vdc) power. A combination of series-connected converters and powerprocessing boosters is required to deliver power to the spacecraft's payloads at this level.

Baez, Anastacio N.↗

A data-driven network optimisation approach to coordinated control of distributed photovoltaic systems and smart buildings in distribution systems

The increasing integration of distributed energy resources, including demand-side resources and distributed photovoltaics (PVs), into distribution systems has resulted in more complicated power system operation. A data-driven network optimisation approach is proposed to coordinate the control of distributed PVs and smart buildings in distribution networks considering the uncertainties of solar power, outdoor temperature and heat gain associated with building thermal dynamics. These uncertain parameters have a significant impact on the operation and control of distributed PVs and smart buildings, bringing challenges to the distribution system operation. In the proposed data-driven distributionally robust optimisation (DRO) approach, the Wasserstein ball is used to construct an ambiguity set for the uncertain parameters, which does not require the probability distributions to be known. Furthermore, a conditional value-at-risk is incorporated into the Wasserstein-based DRO model and converted into a computationally tractable mixed-integer convex optimisation problem. Benchmarked with robust optimisation and chance-constrained programming, the proposed data-driven model can give a less conservative robust solution.

24 POWER TRANSMISSION AND DISTRIBUTION↗

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.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Sampling Rate Comparison for Distribution System Voltage Measurements

Measurement of the voltage delivered by an electric distribution is a relatively straight forward task. When determining the harmonic distortion in the voltage, matters associated with what orders of the 50/60 Hz harmonics to be analyzed dictate the sampling rate. A study addressing this matter is presented.

42 ENGINEERING↗

Valuing Resilience Benefits of Microgrids for an Interconnected Island Distribution System

Extreme climate-driven events such as hurricanes, floods, and wildfires are becoming more intense in areas exposed to these threats, requiring approaches to improve the resilience of the electrical infrastructure serving these communities. Long-duration outages caused by such high impact events propagate to economic, health, and social consequences for communities. As essential service providers, electric utilities are mandated to provide safe, economical and reliable electricity to their customers. The public is becoming less tolerant to these more frequent disruptions, especially in view of technological advances that are intended to improve power quality, reliability and resilience. One promising solution is state-of-the-art microgrids and the advanced controls employed therein. This paper presents and demonstrates an approach to technoeconomic analysis that can be used to value the avoided economic consequences of grid resilience investments, as applied to the islands of Vieques and Culebra in Puerto Rico. This valuation methodology can support policies to incorporate resilience value into any investment decision-making process, especially those which serve the public interest.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Thermal Energy Distribution System (TEDS) Operating Modes and Control Strategies

A Thermal Energy Delivery System was constructed at the Idaho National Laboratory for demonstrating distribution of thermal energy to and from co-located systems sited in the INL Dynamic Energy Transport and Integration Laboratory (DETAIL). DETAIL includes a flow loop simulating a pressurized water reactor, a high-temperature steam electrolysis unit and a thermal energy storage system. This report discusses the various operating modes and control strategies for enabling simultaneous, flexible and efficient transfer of heat from thermal energy sources to end users.

25 ENERGY STORAGE↗

Simulation and analysis of an intermediate frequency (IF) distribution system with applications for Space Station

Simulation and analysis results are described for a wideband fiber optic intermediate frequency distribution channel for a frequency division multiple access (FDMA) system where antenna equipment is remotely located from the signal processing equipment. The fiber optic distribution channel accommodates multiple signals received from a single antenna with differing power levels. Performance parameters addressed are intermodulation degradations, laser noise, and adjacent channel interference, as they impact the overall system design. Simulation results showed that the laser diode modulation level can be allowed to reach 100 percent without considerable degradation. The laser noise must be controlled as to provide a noise floor of less than -90 dBW/Hz. The fiber optic link increases the degradation due to power imbalance yet diminishes the effects of the transmit amplifier nonlinearity. Overall, optimal operation conditions can be found to yield a degradation level of about .1 dB caused by the fiber optic link.

Costello, Thomas A.↗

A Fairness-based Distributed Energy Coordination for Voltage Regulation in Distribution Systems

The rapid adoption of photovoltaic (PV) systems combined with falling prices of energy storage is paving the way for a future in which customers could locally supply their energy needs and export surplus power to the grid. However, reverse power flow from multiple sites in a network can cause overvoltage that decreases system reliability and the utilization level of PV system. In this paper, we present a two-stage approach to solve the energy coordination problem in distribution networks. In the first stage, a household with PV and energy storage is optimized to allow customers to adopt different control strategies such as load following and tariff arbitrage. We show that such customer-led control strategies can cause reverse power flows during peak PV generation periods, thus resulting in overvoltage. In such cases, the second stage of the proposed approach is called upon to solve a fairness-based energy coordination problem that can maintain voltages within limits while maximizing the PV generation while fairly distributing the actions among all the PV systems. As a result, each of the resources in the network has equal opportunity to export power and shares the responsibility of voltage regulation. Simulation studies have been carried out on the IEEE 13-bus test feeder to verify the effectiveness of the proposed approach.

Distributed energy resources, fairness, overvoltag↗