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At least 91 records · Page 5

Reinforcement Learning-based Output Structured Feedback for Distributed Multi-Area Power System Frequency Control

Load frequency control (LFC) is a key factor to maintain the stable frequency in multi-area power systems. As the modern power systems evolve from centralized to decentralized paradigm, LFC needs to consider the decentralized scheme that considers limited information from the information-exchange graph for the generator control of each interconnected area. This paper aims to solve a data-driven constrained LQR problem with mean-variance risk constraints and output structured feedback, and applies this framework to solve the LFC problem in multi-area power systems. By reformulating the constrained optimization problem into a minimax problem, the stochastic gradient descent max-oracle (SGDmax) algorithm with zero-order policy gradient (ZOPG) is adopted to find the optimal feedback gain from the learning, while guaranteeing the convergence. In addition, to improve the adaptation of the proposed learning method to new or varying models, we construct an emulator grid that approximates the dynamics of a physical grid and performs training based on this model. Once the feedback gain is obtained from the emulator grid, it is applied to the physical grid with a robustness test to check whether the controller from the approximated emulator applies to the actual system. Numerical tests show that the obtained feedback controller can successfully control the frequency of each area, while mitigating the uncertainty from the loads, with reliable robustness that ensures the adaptability of the obtained feedback gain to the actual physical grid.

Kwon, Kyung-bin↗

Efficient learning of power grid voltage control strategies via model-based deep reinforcement learning

Here this article proposes a model-based deep reinforcement learning (DRL) method to design emergency control strategies for short-term voltage stability problems in power systems. Recent advances show promising results for model-free DRL-based methods in power systems control problems. But in power systems applications, these model-free methods have certain issues related to training time (clock time) and sample efficiency; both are critical for making state-of-the-art DRL algorithms practically applicable. DRL-agent learns an optimal policy via a trial-and-error method while interacting with the real-world environment. It is also desirable to minimize the direct interaction of the DRL agent with the real-world power grid due to its safety-critical nature. Additionally, the state-of-the-art DRL-based policies are mostly trained using a physics-based grid simulator where dynamic simulation is computationally intensive, lowering the training efficiency. We propose a novel model-based DRL framework where a deep neural network (DNN)-based dynamic surrogate model (SM), instead of a real-world power grid or physics-based simulation, is utilized within the policy learning framework, making the process faster and more sample efficient. However, having stable training in model-based DRL is challenging because of the complex system dynamics of large-scale power systems. We addressed these issues by incorporating imitation learning to have a warm start in policy learning, reward-shaping, and multi-step loss in surrogate model training. Finally, we achieved 97.5% reduction in samples and 87.7% reduction in training time for an application to the IEEE 300-bus test system.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Autonomous power system intelligent diagnosis and control

The Autonomous Power System (APS) project at NASA Lewis Research Center is designed to demonstrate the abilities of integrated intelligent diagnosis, control, and scheduling techniques to space power distribution hardware. Knowledge-based software provides a robust method of control for highly complex space-based power systems that conventional methods do not allow. The project consists of three elements: the Autonomous Power Expert System (APEX) for fault diagnosis and control, the Autonomous Intelligent Power Scheduler (AIPS) to determine system configuration, and power hardware (Brassboard) to simulate a space based power system. The operation of the Autonomous Power System as a whole is described and the responsibilities of the three elements - APEX, AIPS, and Brassboard - are characterized. A discussion of the methodologies used in each element is provided. Future plans are discussed for the growth of the Autonomous Power System.

Ringer, Mark J.↗

Autonomous Power System intelligent diagnosis and control

The Autonomous Power System (APS) project at NASA Lewis Research Center is designed to demonstrate the abilities of integrated intelligent diagnosis, control, and scheduling techniques to space power distribution hardware. Knowledge-based software provides a robust method of control for highly complex space-based power systems that conventional methods do not allow. The project consists of three elements: the Autonomous Power Expert System (APEX) for fault diagnosis and control, the Autonomous Intelligent Power Scheduler (AIPS) to determine system configuration, and power hardware (Brassboard) to simulate a space based power system. The operation of the Autonomous Power System as a whole is described and the responsibilities of the three elements - APEX, AIPS, and Brassboard - are characterized. A discussion of the methodologies used in each element is provided. Future plans are discussed for the growth of the Autonomous Power System.

Ringer, Mark J.↗

Development of a microprocessor controller for stand-alone photovoltaic power systems

A controller for stand-alone photovoltaic systems has been developed using a low power CMOS microprocessor. It performs battery state of charge estimation, array control, load management, instrumentation, automatic testing, and communications functions. Array control options are sequential subarray switching and maximum power control. A calculator keypad and LCD display provides manual control, fault diagnosis and digital multimeter functions. An RS-232 port provides data logging or remote control capability. A prototype 5 kW unit has been built and tested successfully. The controller is expected to be useful in village photovoltaic power systems, large solar water pumping installations, and other battery management applications.

Millner, A. R.↗

Optimal mitigation and control over power system dynamics for stochastic grid resilience

Optimal mitigation planning for highly disruptive contingencies to a transmission-level power system requires optimization with dynamic power system constraints, due to the key role of dynamics in system stability to major perturbations. We formulate a generalized disjunctive program to determine optimal grid component hardening choices for protecting against major failures, with differential algebraic constraints representing system dynamics (specifically, differential equations representing generator and load behavior and algebraic equations representing instantaneous power balance over the transmission system). We optionally allow stochastic optimal pre-positioning across all considered failure scenarios, and optimal emergency control within each scenario. This novel formulation allows, for the first time, analyzing the resilience interdependencies of mitigation planning, preventive control, and emergency control. Using all three strategies in concert is particularly effective at maintaining robust power system operation under severe contingencies, as we demonstrate on the western system coordinating council 9-bus test system using synthetic multi-device outage scenarios.

30 DIRECT ENERGY CONVERSION↗

Discovery of Signatures, Anomalies, and Precursors in Synchrophasor Data with Matrix Profile and Deep Recurrent Neural Networks (Final Project Report)

The widespread deployment of phasor measurement unit (PMU) across the U.S. together with the burgeoning machine learning technology made it possible to develop data-driven PMU data analytics to improve grid security and reliability in a more insightful and effective manner. Although PMU applications have been explored for over a decade, the representative PMU usage is limited to the bulk power system monitoring mainly due to the data integrity issues associated with PMUs (typically missing, fragmented, and wrongly amplified data). To forge a breakthrough on this stalemate and embrace PMUs for power system control and protection as well, we applied various advanced machine learning and big data analysis technology to the power system event detection and classification as the first step toward the power system control and protection pertaining to grid security enhancement.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Overview of Intelligent Power Controller Development for Human Deep Space Exploration

Intelligent or autonomous control of an entire spacecraft is a major technology that must be developed to enable NASA to meet its human exploration goals. NASA's current long term human space platform, the International Space Station, is in low earth orbit with almost continuous communication with the ground based mission control. This permits the near real-time control by the ground of all of the core systems including power. As NASA moves beyond Low Earth Orbit, the issues of communication time-lag and lack of communication bandwidth beyond geosynchronous orbit does not permit this type of operation. This paper presents the work currently ongoing at NASA to develop an architecture for an autonomous power control system as well as the effort to assemble that controller into the framework of the vehicle mission manager and other subsystem controllers to enable autonomous control of the complete spacecraft. Due to the common problems faced in both space power systems and terrestrial power system, the potential for spin-off applications of this technology for use in micro-grids located at the edge or user end of terrestrial power grids for peak power accommodation and reliability are described.

Space Flight↗

Distribution power system fault control apparatus and method

A method includes detecting a fault in a grid coupled to a distribution power network, the distribution power network comprising a distribution feeder, a plurality of distributed energy resources (DERs) coupled to the distribution feeder and a reference point of applicability (RPA) associated with the plurality of DERs, and in response to detecting the fault, determining an error voltage at the RPA, converting the error voltage into an error signal, broadcasting the error signal to the plurality of DERs, and based on the error signal, reducing the error voltage at the RPA by injecting a plurality of currents from the plurality of DERs to the distribution feeder.

Cintuglu, Mehmet H.↗

Unleashing the Frequency: Multi-Megawatt Demonstration of 100% Renewable Power Systems with Decentralized Communication-Less Control Scheme

Power systems, which range in size from small microgrids to island systems to large regional grids, are typically managed by a central controller that requires complex communication methods and can be unreliable and pose cyber security risks in certain applications, especially when controlling a larger number of nodes. We propose an inherently robust, scalable method of integration using multiple energy storage systems and distributed energy resources, which does not require any means of dedicated communication. This method moves beyond the paradigm of controlling grid frequency at a fixed value (e.g., 60 Hz), instead allowing the frequency to fluctuate within certain limits (e.g., 59.6-60.4 Hz). With a greater operating range, the frequency can carry necessary information from energy storage systems to highly variable distributed energy resources like photovoltaics, wind, hydro, etc.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Monitoring circuit accurately measures movement of solenoid valve

Solenoid operated valve in a control system powered by direct current issued to accurately measure the valve travel. This system is currently in operation with a 28-vdc power system used for control of fluids in liquid rocket motor test facilities.

Gillett, J. D.↗

Preliminary design study of a higher harmonic blade feathering control system

The feasibility to incorporate an active higher harmonic control (HHC) system on an OH-6A rotorcraft was demonstrated. The introduction of continuously modulated low amplitude 4P feathering showed potential for reducing rotor transmitted oscillatory loads. The design implementation of this system on a baseline OH-6A required generation of a hydraulic power system, control actuator placement and design integration of an electronic subsystem comprised of an electronic control unit (ECU) and digital microcomputer. Various placements of the HHC actuators in the primary control system are evaluated. Assembly drawings of the actuator concepts and control rigging are presented. The advantages of generating both hydraulic power and 4F control motions in the nonrotating system is confirmed.

Powers, R. W.↗

Solid state remote power controllers for 120 VDC power systems

Remote Power controllers (RPCs) are devices that combine in one unit the capability to perform all the needed functions of load switching and provide total system protection of equipment and wires. The unique developments of solid-state RPCs for 120 Vdc power distribution systems are reviewed. The discussion covers design guidelines, power switch design concepts, and performance effectiveness. An NPN transistor is used as the the basic switch element. Since the ultimate goal of the 120 Vdc RPC program is to demonstrate technology readiness, the final phase is directed to the design, fabrication, and testing of multi-chip hybrid prototypes in hermetically sealed packages. RPCs have potential application in spacecraft and aircraft electrical systems, in transportation systems, and various industrial applications. The upper voltage limitation on the RPC design is related to the capability and availability of suitable high-voltage power transistors. The merits of solid-state RPCs are noted.

Sundberg, G. R.↗

Bulk Power System Flow Control

On July 28, 2023, the Federal Energy Regulatory Commission (FERC) issued Order Number 2023, targeting an improved generation-interconnection process in the United States. FERC Order No. 2023 requires transmission providers to evaluate transmission technologies, other than network expansion, that could provide system improvements and help expand bulk-power system capacity. Transmission providers must consider technologies that would fall under the category of Grid Enhancing Technologies (GETs), which provide capacity-expansion options other than conventional transmission expansion.

32 - ENERGY CONSERVATION, CONSUMPTION, AND UTILIZA↗