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Wang, Shaobu

Publications and source records attributed to Wang, Shaobu.

At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

5G Energy FRAME Report on 5G for Grid Use Case (Year 3 Final Report)

This report provides an extensive overview of the interrelationships among energy, communication, and computing—especially in the context of decarbonization goals, challenges, and opportunities. Technical examples enabled by 5G technologies and their performance are presented, discussed, based on the experiment performed at Pacific Northwest National Laboratory. This is the first use case focused on using 5G for the U.S. power grid and will be referred to as the 5G for Grid Use Case from here on. Specifically, this use case looks at the workflow, which integrates the performance data of a real-world 5G communication testbed and a grid transmission and distribution co-simulation platform. The cross-domain information flow and logic design are illustrated with a combination of power grid contingencies and events. Lastly, a summary of the project achievement and outcome is provided, along with a technology roadmap envisioned by the project team.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Model Gap Quantification and Evaluation

In the real world, model gaps always exist because models cannot perfectly match the objective physical plants. Model gaps reflect the integrity of models, which is vital for model validation and calibration. This letter proposes a novel approach for model gap quantification and evaluation. First, a comprehensive metric is developed to quantify dynamic model gaps. Next, the model gaps are evaluated from a panoramic view of the probability distribution of the comprehensive metric for multiple scenarios. Finally, we demonstrate the proposed quantification and evaluation approach through synchronous machine models.

Wang, Shaobu↗
DOE OSTI2024

Topology property analysis and application of stable time-delay regions for linear multiple time-delay systems

This study examines the relationship between the topology of stable time-delay regions and the stability analysis of an linear multiple time delay system. To analyze the topology of stable time-delay regions, we construct a function with a value equal to zero for the time-delay points on the boundaries of stable time-delay regions. The function is continuous and differentiable in the whole defining field with a global minimum of zero so that we can locate the boundaries by minimizing the value of the function. Based on the topology analysis, we proposed a performance validation approach for controllers that are designed to stabilize the system using feedback signals with time delays. The method based on the topology analysis is simple and reliable so that can deal with a linear time-invariant system with high order and multiple time delays (more than 3). The example case study shows that the above method is reliable and enables ultra-low latency coordination and control for the future power grid with ubiquitous power electronics.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Robust Disturbance Rejection Rotor Current Control of Doubly-Fed Induction Generators

This article proposes a robust transient disturbance rejection current controller (TDRCC) to improve the transient performance of doubly-fed induction generators (DFIGs) in wind turbines during grid disturbances, such as short circuits. Here, the proposed robust TDRCC replaces the proportional-integral-derivative (PID) current controllers conventionally used in the vector control scheme of the DFIG rotor side converter (RSC). The TDRCC estimates the transient disturbances caused by grid faults or other external disturbances and provides compensation to the DFIG rotor voltage in the current control loops of the RSC to improve the robustness of the controller to disturbance. A sliding-mode current controller (SMCC) is also designed to highlight the transient performance improvement of the DFIG using the TDRCC over the state-of-the-art control methods during grid short circuit faults. Simulation studies are conducted in PSCAD/EMTDC for a 3.6-MW DFIG wind turbine with the proposed TDRCC, the conventional PI controller, and the SMCC, respectively during the most severe balanced three-phase grid short circuit fault specified by the U.S. grid code as well as an unbalance single-phase grid short circuit fault. Hardware experiments are conducted on a 200-W DFIG wind turbine emulator with the three different controllers for the same three-phase short circuit fault. Simulation and hardware experiment results show that the TDRCC reduces the peak rotor current significantly when compared with the PI and SMCC controlled DFIG system and, therefore, would help prolong the lifespan of the DFIG's power electronics and reduce maintenance costs.

42 ENGINEERING↗
DOE OSTI2023

Fast Frequency Response using Reinforcement Learning-Controlled Wind Turbines

To fulfill the auxiliary grid services such as load regulation, spin and non-spin reserve, and frequency support during emergencies, power system operators often require certain wind farms to operate in de-loaded modes. By leveraging the fast response capability of wind farms, the reserved power in deloaded modes can significantly enhance the stability and reliability of power grids. This paper presents a novel methodology that incorporates wind turbines into reinforcement learning-based solutions for frequency response. The proposed approach employs the state-of-the-art reinforcement learning algorithm, surrogategradient- based evolution strategy (GSES), for continuous control of the wind farm output. Our methodology is tested on a modified IEEE-39 bus system, and simulation outcomes demonstrate that the proposed approach can reliably support the frequency of the power system and prevent unnecessary load shedding.

Gao, Wei↗
DOE OSTI2023

Multifold Insights for Power System Dynamics From Data Assimilation: Meeting Current Challenges

The world’s electric power grids have evolved over the last 120 years from a single power line to today’s large networks. The evolution will continue at an accelerated rate with extensive smart grid development worldwide. Here for example, the U.S. government has set a goal of reaching 100 percent carbon pollution-free electricity by 2035, while the Department of Energy (DOE) shared a goal to deploy 30 GW and 110 GW of offshore wind by 2030 and 2050, respectively. To meet such ambitious goals, in the years to come, a significant percentage of electricity will come from intermittent renewable sources, electric vehicles (EVs), and be supplied to a vast number of loads that will actively respond to grid conditions and incentive signals. This development is largely driven by environmental and economic factors, such as reducing carbon emissions and saving electricity cost for consumers. These energy resources lead to new uncertain behaviors and dynamics which the grid has never seen and were not considered in its design. Operating such a dynamic grid with sufficient reliability and efficiency is a monumental challenge.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

WECC Wide-Area Oscillation Assessment and Trending Study Report

This project, Wide-area Oscillation Analysis and Trending Study, is sponsored by the Office of Electricity (OE) of the Department of Energy (DOE) who tasked Northwest National Laboratory (PNNL) to conduct this research. Staff of Federal Energy Regulatory Commission (FERC) have been involved in the project as observers and have provided advisory comments and suggestions. The primary objective of this study is to assess whether there are significant trends in the wide-area oscillatory behavior with respect to the significant generation-mix changes brought by the increased penetration of RES in the WECC system. The work performed in this project is considered to be complimentary to previous work by NERC/industry and covers the aspects that have not been studied or trended before. The trending analysis presented in this report can serve as reference for future grid planning and operation of the WECC system. In this report, how the changes in the generation mix can impact the frequency and damping ratio (DR) of WECC wide-area oscillation modes has been studied. Thorough data-based and model-based analyses have been carried out to analyze the current trends and then extended to evaluate the oscillation behaviors of the future WECC system.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Wavelet and Deep-Learning-Based Approach for Generation System Problematic Parameters Identification and Calibration

Accurate models of generation systems are critical for maintaining reliable and secure grid operations. In this paper, a novel and systematic approach is proposed to identify and calibrate the generation system problematic parameters using continuous wavelet transform (CWT) and advanced deep-learning technology. The phasor measurement unit (PMU) data are used through “event playback” to check whether the parameter calibration is required, and if yes, a group of suspicious parameters will be identified as the primary problematic parameter candidates (PPCs). These primary PPCs are randomly perturbed to generate the event playback simulation data, which are used by the CWT and convolutional neural networks (CNNs) to further narrow down the primary PPCs into a smaller set of candidates. Then, the identified candidates are perturbed again to generate massive event playback simulation data for training a parameter calibration neural network. Here, we designed a multi-output neural network structure to find the mappings between the perturbed parameters and the simulation data using both CNN and long short-term memory (LSTM) models. Finally, the well-trained and tested CNN-LSTM model is used to estimate the accurate value of the suspicious parameters with actual PMU measurements. The proposed CNN-LSTM network can accurately and reliably estimate the generation-system problematic parameters, and has better performance when compared to other machine-learning methods, such as the multilayer perceptron network and the conditional variational autoencoder method. The accuracy and effectiveness of the proposed approach have been validated through simulation and real-world data.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Improving DFIG performance under fault scenarios through evolutionary reinforcement learning based control

The double-fed induction generator (DFIG) usually experiences high rotor current and DC capacitor link voltage during system fault events. In this paper, a novel data-driven approach is proposed to enhance the DFIG performance under fault scenarios. An advanced reinforcement learning (RL) algorithm called guided surrogate-gradient-based evolution strategy (GSES) is used to control the DFIG power and capacitor DClink voltage by adjusting the optional reference signals. This controller is able to prevent the rotor of DFIG from overcurrent risk and maintain the grid-connected operation. The proposed GSES-based control algorithm was evaluated through simulations on a 3.6-MW DFIG in PSCAD/EMTDC software. Results have validated the effectiveness of the proposed GSESbased control algorithm in improving the DFIG performance under fault scenarios.

42 ENGINEERING↗
DOE OSTI2022

Bounds of linear time‐varying systems with applications to quantify model gap of synchronous generators

Abstract Linear time‐varying (LTV) systems play a key role in many engineering problems, for example, trajectory sensitivity analysis of power systems. Because LTV systems do not generally have closed‐form solutions, estimates of their bounds are crucial to their analysis. In this paper, bounds for LTV systems with known inputs and unknown but bounded inputs are obtained via Grönwall's inequality. The estimated bounds are then used to quantify the gap between synchronous generators and their models in different scenarios through simulation.

42 ENGINEERING↗
DOE OSTI2021

Roles of Dynamic State Estimation in Power System Modeling, Monitoring and Operation

—Power system dynamic state estimation (DSE) remains an active research area. This is driven by the absence of accurate models, the increasing availability of fast-sampled, time synchronized measurements, and the advances in the capability, scalability, and affordability of computing and communications. This paper discusses the advantages of DSE as compared to static state estimation, and the implementation differences between the two, including the measurement configuration, modeling framework and support software features. The important roles of DSE are discussed from modeling, monitoring and operation aspects for today’s synchronous machine dominated systems and the future power electronics-interfaced generation systems. Several examples are presented to demonstrate the benefits of DSE on enhancing the operational robustness and resilience of 21st century power system through time critical applications. Future research directions are identified and discussed, paving the way for developing the next generation of energy management systems.

Zhao, Junbo↗
DOE OSTI2020

Robust Adaptive Decentralized Dynamic State Estimation with Unknown Control Inputs using Field PMU Measurements

This paper proposes a robust adaptive decentralized dynamic state estimation method for power system with unknown inputs of the highly detailed synchronous machine model. The temporal and spatial correlations among the unknown inputs are used to derive a vector auto-regressive model. The latter is further integrated together with state transition and measurement models for joint state and unknown inputs estimation. Thanks to the consideration of implicit cross-correlations between the states and the unknown inputs, only generator terminal voltage and current phasors are needed. Test results on the US WECC system using the field PMU measurements show that the proposed method is able to track both the system dynamic states and unknown controller inputs. These information could significantly benefit the validation and calibration of generator controller parameters.

Zhao, Junbo↗
DOE OSTI2020

A robust dynamic state estimation approach against model errors caused by load changes

Dynamic state estimation (DSE) plays an important role in power system security monitoring and online control. In practice, there are two approaches to implementing DSE. The first approach is distributed DSE, which is based on the assumption that the terminal bus of each generator can be measured by PMUs (phasor measurement units). The assumption cannot be satisfied currently, however, because PMUs usually are installed at important high-voltage buses such as 500-kV buses installed in portions of the grid overseen by the Western Electricity Coordinating Council. Another issue of this approach is that performance of DSE is vulnerable to bad measurement data. The reason for this vulnerability is that DSE is performed separately through measurements at each terminal bus, and measurements at terminal buses are the only measurement upon which DSE can rely. Therefore, important redundant measurements are not included in this approach. The second approach is centralized DSE. This approach does not have the requirement for PMU location, and redundant measurements can be considered fully. However, load changes and grid topology changes impact centralized DSE. In this paper, we propose a new approach for handling the impact of load changes on DSE. We have developed a new algorithm that includes two sequential steps. In the first step, errors caused by load changes are detected by analyzing the difference between prediction results and measured results. In the second step, once model error is detected, a model optimization procedure is run to correct the error so the state estimation error can be mitigated. Simulation results from the IEEE 68 bus system show that the proposed approach can effectively handle model errors caused by load changes.

robust dynamic state estimation, load change, powe↗
DOE OSTI2020

Application of Detectability Analysis for Power System Dynamic State Estimation

To guide the measurement placement and selection for dynamic state estimation in power systems, it is important to determine the existence of an observer that can estimate the dynamic states. Past studies have been focused on observability analysis, which determines whether the initial states can be uniquely determined. In this paper, detectability analysis is proposed to determine whether the current states can be estimated as time involving. Through the proposed detectability analysis, the states of an unobservable system can be categorized into the detectable states and undetectable states. It is shown that if the eigenvalues corresponding to the unobservable states are stable, the states are detectable and their estimates will converge to the true ones asymptotically. The study can be used to guide measurement placement and selection.

Detectability, dynamic state estimation↗
DOE OSTI2020

Correlation-Aided Robust Decentralized Dynamic State Estimation of Power Systems with Unknown Control Inputs

This paper proposes a correlation-aided robust adaptive unscented Kalman filter for power system decentralized dynamic state estimation with unknown inputs, termed as robust AUKF-UI. The temporal and spatial correlations among the unknown inputs are used to derive a vector auto-regressive (VAR) model in an adaptive manner. This VAR model is further integrated together with state transition and measurement models for joint state and unknown inputs estimation. This allows taking into account the implicit cross-correlations between the states and the unknown inputs. As a result, the rank requirement for unknown input vector estimation is relaxed and the local generator frequency measurement is not required. The temporal correlations of time series innovation vectors, predicted state and input vectors are also leveraged by the robust AUKFUI to detect, identify and process bad data. Without these correlations, it is very challenging to address bad data with unknown inputs. Simulation results carried out on the IEEE 39-bus system demonstrate that the proposed robust AUKF-UI achieves much better results than other methods in the presence of low measurement redundancy, strong nonlinearity, and bad data.

Zhao, Junbo↗
DOE OSTI2020

Risk-Oriented PMU Placement Approach in Electric Power Systems

The objective of traditional PMU placement approaches is to use the minimal number of PMUs to cover system complete observability. Very few consider the probability and the consequence severity of observability loss. For example, following line trip, grid topology changes, which may results in observability loss and overloaded lines. As long as the overloaded lines are still observable, then we can take action in time to correct the system; and the consequence of the observability loss is not severe, although some parts of the system is not observable. Otherwise, if the overloaded lines become unobservable, then we lose the situation awareness of the system and the consequence of the observability loss is severe. To address the above points in PMU placement, this paper proposes a risk-oriented PMU placement approach. The proposed approach uses two indices, namely the probability of observability loss and its corresponding consequence of severity to design the optimal PMU placement strategy. We show that our proposed approach is able to capture the critical events while the traditional approaches fail to do so. Extensive simulation results carried out on the IEEE 39-bus and 118-bus systems demonstrate its effectiveness.

observability, risk of observability loss, PMUs pl↗
DOE OSTI2020

Wide-Area Measurement-Based Modal Decoupling for Power System Oscillation Damping

Inter-area oscillation modes usually fall within the same frequency range of 0.1 to 1.0 Hz; thus, power oscillation damping (POD) control methods should avoid unnecessary excitation of weakly damped modes. This paper presents a decoupled control strategy to damp inter-area oscillations in the power grid. Pure oscillation mode signals are extracted from wide-area measurements and used as feedback input for POD actuators such as power system stabilizers or high-voltage direct current transmission. The decoupled control strategy is able to increase the damping of the concerned oscillation modes without deteriorating others. This proposed strategy could be implemented independently, or serve as a complement and work along with conventional POD controllers to damp concerned inter-area modes. The proposed method has been tested on a modied MinniWECC system. Extensive results indicate that inter-area oscillations can be successfully and precisely damped using the proposed decoupled strategy.

Fan, Rui↗