Real-Time Resilience of Energy Systems [Slides]
This presentation summarizes the real-time resilience of energy systems (FY20-FY22) LDRD project.
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This presentation summarizes the real-time resilience of energy systems (FY20-FY22) LDRD project.
The energy sector is undergoing digital transformation which is to say more and more power generation assets have become automated and connected to the internet. The connected sensors can tap into plants to monitor the health of assets and manage fleets remotely. These are just some of the benefits digitalization is bringing to the power industry. Within a power plant, control systems are no longer concerned with one system or one piece of equipment, but rather whole fleet of assets inter-connected with smart sensors which have the function of continuously monitoring and transmitting real-time operational data to operators. These connected systems will form a part of the industrial internet of things (IIoT). The big data scenarios provide benefits of performing system prognostics and optimization which is a key selling point of power plant digitalization.
A method for auto-commissioning of multiple device control modules on a power line during the power up of the system. Device control modules associated with the peripheral devices are powered up sequentially and a unique address is assigned to each device controller when it is powered up.
The estimation (and control) of the output variables is often challenging for wireless power transfer (WPT) systems. This paper presents a secondary side sensor-less closed loop estimation technique to estimate the output current in a primary side LCC and secondary side series compensated WPT system. Using information of primary side variables, the proposed estimation can estimate the output current over a wide range of load current variations. Results are presented to verify the efficacy of the proposed estimation.
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This paper proposes a control architecture for frequency, current, and voltage control that facilitates using battery storage to improve the response of standalone small hydropower plants. The frequency controller uses rate-of-change of frequency and frequency-Watt-based generations to produce active power commands. The distinctive feature of the controller design is that it nicely integrates response to frequency change with constraints on frequency and state of battery to enable power injections. The current and voltage control scheme allows incorporating the frequency controller. The distinctive feature of this controller is that it incorporates a bounded integral control strategy that guarantees stability. Results on the stability of the hydropower plant with proposed scheme are presented and robust ways to choose the controller gains are investigated via root locus analysis. In conclusion, simulations performed show that: the hydropower plant response is significantly improved with battery storage using the proposed scheme; the load carrying capability of the hydropower plant is significantly improved with battery storage; the proposed scheme has the capability to recharge the battery; and the proposed control scheme gives improved performance.
This paper examines the impact of inverter-based resource (IBR) momentary cessation timing on transmission system protection relays. IEEE Std. 2800 mandates voltage ride-through, requiring IBRs to remain online during voltage disturbances. However, for severe voltage dips (|V| = 0.1 p.u.), the standard permits current blocking. In practice, vendors implement momentary cessation with varying delays, potentially affecting relay operation if IBRs cease too early. This article studies the impact of the time IBRs enter momentary cessation on transmission line protective relays. Using an electromagnetic transient (EMT) simulation, this study models IBR momentary cessation with tunable delays in a realistic transmission network. COMTRADE files generated from EMT simulations are analyzed in MATLAB using detailed protective relay models. Results indicate that IBRs must sustain operation for at least one cycle to ensure proper relay response; otherwise, relays may fail to oper- ate. These findings guide IBR vendors in optimizing momentary cessation settings to enhance transmission line protection.
Through support of the US Department of Energy's Office of Basic Energy Sciences, Oak Ridge National Laboratory has begun applying machine learning methods to improve accelerator and target performance of the Spallation Neutron Source (SNS). These methods are being applied to the control optimization and power upgrade of the SNS Cryogenic Moderator System (CMS). A numerical model of the CMS has been developed to study these optimizations and system modifications using EcosimPro. This paper compares steady-state and transient numerical results with experimental data. Control optimization studies focused on dampening mass flow, temperature, and pressure fluctuations during sudden losses of accelerator beam power. This analysis was conducted by adjusting five proportional-integral-derivative controllers connected to four flow control valves and one heater. Future efforts include power uprate studies focused on increasing the CMS cooling capacity. The current accelerator power is 1.4 MW; the first target station is being upgraded to 2.0 MW as part of the Proton Power Upgrade effort. The CMS cooling capacity is sufficient for 2.0 MW operation.
Synchrophasor measurement devices (SMDs) have been widely deployed to support real-time monitoring and control of power systems. In the meantime, data spoofing has emerged in recent years. Therefore, it is of great importance to study data authentication algorithms for detecting and defending the data spoofing effectively. Here, a one-dimensional convolutional neural network (1D-CNN) is utilized to extract temporal signatures hidden in frequency, voltage angle and amplitude data; then the gated recurrent unit (GRU) employs these temporal signatures for data source authentication. In case studies, the performances of different algorithms are tested in large-scale power systems with numerous SMDs for the first time, and comparisons among different algorithms show that the proposed algorithm can achieve a higher accuracy of data source authentication with a shorter time window.
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Driven by the1.4 GW generator, the 60T Controlled Waveform (60 TCW) magnet was the most powerful controlled waveform system in the world and had always been one of most important magnets to the National High Magnetic Field (NHMFL) and high-field research community because of its following unique features: (1) quasi-static field up to 60 T with 100 ms flat-top and total pulse-length of about 2000 ms, (2) variable magnetic field waveforms such as staircase and triangle with flat-top (3) relative large bore (32 mm) and (4) very fast cooling time (20 minutes) between pulses [Boebinger, 2001], [Crooker et al. 2001]. The magnet is composed of nine concentric coils, with each coil consisting of several conductor winding layers reinforced by a high-strength metallic shell. The magnet underwent a catastrophic failure in 2000 and all the coils had to be rebuilt. In late 2014 the second magnet version failed near the mid-plane of coil 7. The simulations afterward that incident indicated that the overall strength of the coil would be increased by replacing a section of the reinforcing shell with Zylon fiber-epoxy composite. This reduces the stress and thus significantly lowers the level of plastic deformation in the windings. The role of the metal and Zylon fiber reinforcing layers in bearing the axial and radial Lorentz forces has been studied to optimize the magnet design. Here, the results of the optimization will be discussed as well as challenges that have been presented in rebuilding the individual coils of the magnet.
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This HADREC GUI is designed to visualize power system emergency control time-series data and facilitate the comparison of the newly developed meta strategy optimization algorithm-based emergency control with existing out-of-step-based emergency control approach, and a no-action case for reference.
Prior efforts have shown that deep reinforcement learning (DRL) may provide a new method for controlling networked power systems. Though successful, prior approaches have not yet demonstrated their behavior on systems of realistic scale. This effort examined multiple theoretical and technical approaches to allow a DRL model to operate over a system of 2,000 buses or more. We find that allowing the DRL models to run training episodes in parallel provides near limitless efficiency gains, allowing us to train successful agents to behave on our Kuramoto transmission model of up to 4,000 buses. We further show that we can expand our PowerWorld DRL implementation to systems of up to 25 buses but struggle to go beyond this limit due to PowerWorld’s inability to run multiple instances at once. Finally, we examine a multi-agent approach and find that it performs as well if not better than our existing centralized approach.
This project is intended to model wind power plant based on monitored data at the wind power plant. This project will promote the university research in Renewable Energy area and trains the future highly qualified engineers. The dynamic model will be based on neural net model with the input from the two met towers (12 inputs), and the number of turbines in operation (one input). The overall input will be 13 inputs to drive the simulations. The output power at the point of interconnection will be used to tune the neural net weight coefficients. Two neural net concepts will be investigated (the back propagation neural net and the dynamic recurrent neural net with feedback).
Here, in this work we propose a novel data-driven, real-time power system voltage stability control method based on the physics-informed guided meta evolutionary strategy (ES). The main objective is to quickly provide an adaptive control strategy to secure system voltage stability. The problem is challenging due to the high-dimensional feature of the power system model and the fast-changing and uncertain nature of power system operation scenarios. To this end, a model-free and derivative-free guided ES method is applied. The method is further combined with a meta-learning strategy to make the learnt control policy automatically adapted to unseen operation conditions and fault scenarios, which is highly desired for real-time emergency control. Last but not least, physical knowledge is embedded in the above method through a trainable action mask technique to rule out unnecessary load shedding actions for better learning and control performance. Case studies on the IEEE 300-bus system and comparisons with other state-of-the-art benchmark methods verify the superiority of the proposed physics-informed guided meta ES method in realizing fast and adaptive power system voltage stability control.
The Holos-Quad micro-reactor concept, developed by HolosGen LLC, is equipped with a 22 MWt (Mega-Watt thermal) core and an integral power conversion system converting the core thermal energy into approximately 10 MWe (Mega-Watt electric). This design can be configured to support a wide range of applications. It is a very innovative high-temperature gas-cooled reactor concept using TRI-structural ISOtropic particle fuel (TRISO) distributed in graphite hexagonal blocks, cooled with helium in a direct Brayton cycle independently executed by four Subcritical Power Modules (SPMs) fitted into a hardened 40-foot container whose dimensions are in compliance with ISO shipping containers requirements. In FY2019 HolosGen LLC was awarded by the Department of Energy Advanced Research Project Agency-Energy (DOE ARPA-E) under the MEITNER funding program. As part of the MEITNER award, the Argonne National Laboratory (ANL) contributed expertise through two specialized teams: The “Design Team” and the “Resource Team”. The Design Team was dedicated to validate feasibility of the Holos-Quad core and to optimize its core design through neutronics analyses. The Resource Team was dedicated to feasibility verification via high-fidelity codes of Holos-Quad thermal-hydraulic, heat transfer, shielding, and structural aspects. This report summarizes the activities conducted by ANL Design Team. A rigorous design approach based on multi-criteria optimization and code-to-code comparison involving stochastic and high-fidelity deterministic solutions was developed and employed at several evolutionary stages of the Holos-Quad design. Several generations of the Holos-Quad core were designed within this project before converging to the current full-scale Gen 2+ design that is detailed in this report. Figure EA-1 illustrates a cross-sectional view of Gen 2+ Holos-Quad core configuration, and Figure EA-2 provides a simplified perspective view of 1-of-4 SPMs. The Holos-Quad uses four thermal-hydraulically independent SPMs locked into stationary positions during power operation, surrounded by BeO reflector and structural component fully comprised within the dimensional constraints represented by traditional ISO containers. One of the benefits of this approach is to enable transportation of each SPM promptly after irradiation in shielded containers. The core is designed to operate for approximately 8 full-power years while the reactivity controls and power conversion system enable load-following operations. The reactivity controls are represented by independent, diversified, and redundant reactivity control systems based on control drums and redundant sets of shutdown rods. The high-fidelity simulation tools were used to assess detailed power and flux distributions of the three-dimensional full-core or quarter-core of the Gen 2+ configuration. Single-physics and multi-physics simulations of the neutronics code PROTEUS and the thermal-hydraulic code System Analysis Module (SAM) were performed to analyze the Holos design configurations with detailed high-fidelity solutions. The design work performed confirmed feasibility of the Holos-Quad concept, provided realistic design description for detailed design of the operational system, and identified several core design improvements to be further considered for future reactor development activities.