Engineering topics

Xia, Qianxue

Publications and source records attributed to Xia, Qianxue.

12 records

DOE OSTI2024

EMT data generation

The integration of inverter-based resources (IBRs) in power systems is accelerating, bringing with it significant benefits such as reduced greenhouse gas emissions, improved grid resilience, and increased energy independence. Despite these advantages, the widespread adoption of IBRs introduces several challenges, including issues related to grid stability, increased operational complexity, and the need for updated regulatory frameworks. To address these challenges, IEEE released Standard 2800 in 2022, which sets forth the necessary interconnection capabilities and performance criteria for IBRs connected to transmission and sub-transmission systems. This standard outlines the performance requirements to ensure the reliable integration of IBRs into the bulk power system. Furthermore, in 2023, the North American Electric Reliability Corporation (NERC) published a reliability guideline for electromagnetic transient (EMT) modeling of BPS-connected IBRs. This guideline provides recommendations for developing EMT model requirements, performing model quality checks, and implementing verification practices specifically for EMT models representing BPS-connected inverter-based resources in reliability studies conducted by transmission planners and planning coordinators. These standards and guidelines have a profound impact on EMT studies for transmission networks, influencing system stability analyses, grid recovery and resynchronization processes, fault ride-through evaluations, protection and coordination strategies, advanced control methodologies, and the inclusion of IBRs in transient models of transmission networks. As a result, the generation of EMT data is crucial for conducting various transient-based studies to understand the impact of IBRs. EMT data generation use cases serve as the basis for scenarios in event detection and identification use cases, providing comprehensive details about EMT data generation for transmission grids with inverter-based resources. These use cases supply sufficient training and validation datasets for subsequent EMT analysis algorithms.

Xia, Qianxue↗

DOE OSTI2024

Reinforcement Learning-Based Approach for EMT Automation of Large-Scale PV Plants

In the pursuit of efficient and precise modeling of large-scale power systems, particularly utility-scale photovoltaic (PV) plants, Electromagnetic Transient (EMT) simulations play a crucial role. As utility-scale PV plants increase in size and complexity, traditional computational methods become inadequate, necessitating more advanced techniques. This paper highlights the progressive efforts made to accelerate EMT simulations. A novel continuous reinforcement learning (RL) strategy is explored to automate the differentiation and categorization of stiff and non-stiff differential algebraic equations (DAEs). The use of stiff and non-stiff integration methods applied to relevant parts of the DAEs assists with the speed-up of the simulations. The paper details the data acquisition, development and offline training of the RL model, leading to its validation that demonstrates a high precision in optimizing simulation methods. The proposed RL promises to significantly enhance the efficacy of EMT simulations, offering a robust framework for the future of power system analysis.

Xia, Qianxue↗

DOE OSTI2024

Assessing the Feasibility of Bordered Block Diagonal Reordering in Power System Matrices using Fully Convolutional Network

In electromagnetic transient (EMT) simulations for power systems and inverter-based resources (IBRs), the arrangement of states within the system's linear equations, represented by matrix A in Ax=b, is critical. The state ordering in matrix A can highlight distinct characteristics of the system's graph, and identifying an optimal state ordering is crucial for efficient computation. The choice of state ordering, however, is dependent on the solver used, as each solver may perform optimally with different matrix patterns. With a wide array of matrix reordering algorithms available, selecting the most suitable one becomes challenging without insights into the matrix's ideal configuration. To address this, the paper proposes a fully convolutional network (FCN) to evaluate the reordering potential of the A matrix into a bordered block diagonal (BBD) pattern, which is commonly observed in power system and IBR modeling. The FCN's assessment aims to streamline the solver's operation, which in turn could substantially reduce the computational time required to find a solution.

Xia, Qianxue↗

DOE OSTI2024

Machine Learning-Assisted Stability Boundary Determination of Multiport Autonomous Reconfigurable Solar Power Plants

The multiport autonomous reconfigurable solar (MARS) power plant is a promising solution to integrate renewable resources and energy storage systems into the alternating current (ac) power grid and an high-voltage direct current (HVdc) link. In the MARS system, various input power sources are connected to the individual submodules (SMs) through direct current (dc)–dc converters. However, the presence of external power sources can result in unbalanced capacitor voltages of SMs, thereby violating stability constraints under multiple/diverse operating conditions. This article aims to address the gap by accurately determining the stability boundary of the MARS system. As such, a novel machine learning (ML)-assisted energy balancing control (EBC) criterion is proposed. Further, in conjunction with a refined EBC, this approach ensures balanced capacitor voltages across various types of SMs, significantly enhancing the overall system efficiency. The proposed EBC criterion effectively controls EBC activation and deactivation, achieving remarkable accuracy. Both power systems computer aided design (PSCAD)/electromagnetic transients including direct current (EMTDC) simulations and control hardware-in-the-loop (cHIL) tests are conducted to validate the feasibility and efficiency of the proposed method. By combining the EBC and ML-assisted EBC criterion, efficient energy management is achieved for systems featuring multiple input power sources, such as MARS. This approach enables the system to fully exploit its potential across an expanded operational range while upholding high-efficiency standards.

14 SOLAR ENERGY↗

DOE OSTI2023

Control System of Multi-Port Autonomous Reconfigurable Solar Power Plant (MARS) & HIL Platforms for Design

Multi-port autonomous reconfigurable solar power plant (MARS) provides an attractive alternative to connect photovoltaic (PV) and energy storage systems (ESSs) to high-voltage direct current (HVdc) links and high-voltage alternating current (ac) grids. In this paper, a unique hierarchical control system of MARS is proposed and evaluated. To evaluate the control system and associated algorithms in early-stage research of complex architectures like MARS, it is important to develop unique suitable hardware-in-the-loop (HIL) platforms. In this paper, the HIL platforms for MARS to evaluate the performance of the hierarchical control system and the control algorithms implemented are presented. Further, they help with the design process of control systems. The real-time simulation models and algorithms that are utilized for MARS in the HIL platforms are also discussed in the paper. The HIL experiments of the control system of MARS showcase the capability to provide continuity of operation under faults and frequency support to the power grid during loss of generation. They also showcase the stability of the proposed hierarchical control system of MARS.

14 SOLAR ENERGY↗

DOE OSTI2023

AI & Physics-Based Bad Command/Data Detection in Large Power Electronics Systems: Multi-Port Autonomous Reconfigurable Solar Power Plant (MARS)

Detection of bad data from measurement sensors and bad commands from control centers need to be carried out to avoid instabilities within large power electronics systems. Towards the same, in this paper, model and data driven methods are proposed to identify anomalies in measured data and commands received by large power electronics systems. The large power electronics system considered in this paper is a multi-port autonomous reconfigurable solar power plant (MARS), which consists of photovoltaic (PV) and energy storage systems (ESSs) that connect to high-voltage direct current (HVdc) system and transmission ac power grid. The proposed algorithms in the MARS power plant to detect bad data from measurements and bad commands from control centers are evaluated in simulations and hardware-in-the-loop (HIL) tests. Furthermore, it has been observed that the proposed algorithms are able to detect bad measurements and commands in all the use cases evaluated.

14 SOLAR ENERGY↗

DOE OSTI2023

Multi-Port Autonomous Reconfigurable Solar Power Plant

As the penetration level of power electronics increases and remote photovoltaic (PV) generation is integrated into the alternating current (ac) grid, the short-circuit ratio (SCR) at the point of interconnection of a hybrid PV–energy storage system (ESS) plant may be low. Additionally, the inertia of the alternating current (ac) grid may be low. The low SCRs and inertias can lead to reliability challenges in the power grid. These operating conditions require additional reinforcements, such as synchronous condensers, static var compensators, static synchronous compensators, and high-voltage direct current (HVdc) links/grids. HVdc links or grids may also provide the additional capability of connecting the plant to asynchronous grids and/or connecting asynchronous grids, among others. This scenario leads to discrete development of solar inverters, energy storage inverters, HVdc converters, and several transformers. Some of the problems associated with this discrete development and inverter-based generation include increased cost, lower reliability, and reduced efficiency associated with duplication of power electronics (PEs); competing controls of several individual discrete inverter-based generators due to the presence of multiple PEs, which leads to derating of the system; and transient stability problems arising from inverter-based generation, such as voltage/frequency events leading inverter shutdowns, voltage instability and control interactions in the formed weak grid, and harmonics caused by resonances of multiple inverters.

14 SOLAR ENERGY↗

DOE OSTI2022

Power Electronic Hardware-in-the-Loop (PE-HIL): Testing Individual Controllers in Large-Scale Power Electronics Systems

Large power electronics systems like multi-port autonomous reconfigurable solar power plant (MARS) are increasingly being researched upon to integrate emerging energy sources. MARS connects photovoltaic (PV) systems and energy storage systems (ESSs) to high-voltage direct current (HVdc) links/grids and high-voltage alternating current (ac) transmission grids. As these large power electronics systems incorporate complex hierarchical control systems that are close-by and communicate fast, the control systems require an unique power electronic hardware-in-the-loop (PE-HIL) real-time architecture to evaluate individual controllers. In this paper, a PE-HIL real-time architecture is proposed to evaluate one of the hundreds to thousands of digital signal processors (DSPs) that are a part of the complex hierarchical control system. The DSP connects to a central processing unit (CPU) and a field programmable gate array (FPGA) that form a part of the upper levels of the control system. The DSP is part of the lower level of the control system. The proposed PE-HIL architecture is tested and evaluated. Preliminary test results are presented to showcase the concept.

Debnath, Suman↗

DOE OSTI2022

Virtual Synchronous Generator Control of Multi-port Autonomous Reconfigurable Solar Plants (MARS)

Multi-port autonomous reconfigurable solar power plant (MARS) is an integrated concept for integration of solar photovoltaic (PV) and energy storage systems (ESS) to transmission alternating current (ac) grid and high-voltage direct current (HVdc) links. The integrated development incorporates advanced control methods to provide enhanced grid ancillary services such as fast frequency responses and dynamic voltage support. In this paper, the virtual synchronous generator (VSG) control algorithm of MARS is discussed. The proposed VSG-based control enables enhanced synthetic inertial response and flexible frequency response characteristics of hybrid PV and ESS power plants in accordance with grid ancillary service requirements. Multi-port power electronics interface allows controlled emergency power support from MARS to local transmission ac grid and remote grid through the HVdc link. The performance of VSG control is validated using a reduced-order model of MARS in Simulink. Methods for estimating grid ancillary service capabilities of MARS are also discussed.

Pan, Jiuping↗

DOE OSTI2021

Real-time Simulation Framework for Hardware-in-the-Loop Testing of Multi-port Autonomous Reconfigurable Solar Power Plant (MARS)

Multiport autonomous reconfigurable solar power plant (MARS) has been proposed for integrated development of photovoltaic (PV) and energy storage system (ESS) that can connect to high-voltage direct current (HVdc) and alternating current (ac) transmission grid. To de-risk the development of this complex integrated system that consists of hundreds to thousands of power electronics modules, a controller hardware-in-the-loop (cHIL) test setup will be extremely beneficial. The cHIL testing can be used for evaluation of modules as well as the hierarchical control system in MARS. With the unique configuration of power electronics modules in MARS, it becomes necessary to develop custom-designed real-time simulation models in the cHIL setup in absence of off-the-shelf models. In this paper, high-fidelity dynamic model of MARS, control algorithms at the lower level, and required communication algorithms are developed and optimized for real-time performance in the cHIL setup. Real-time experimental results from the cHIL are provided.

Dong, Zerui↗

DOE OSTI2020

Renewable Integration in Hybrid ac-dc Systems using Multi-port Autonomous Reconfigurable Solar power plant (MARS)

To increase inertia and improve primary frequency response of future grids, grid-forming inverters connecting PV to grid and energy storage systems (ESSs) are likely to play an important role. Moreover, high-voltage direct current (HVdc) links will also be an enabler to transfer remote PV generation and for improved grid stability. That is, with increased penetration of PV, discrete development of PV and ESS connecting to transmission ac grid and HVdc links is one of the solutions for stable operation of grid. Here, an integrated concept for integration of PV and ESS to transmission ac grid and HVdc links is proposed that is named as multi-port autonomous reconfigurable solar power plant (MARS). The proposed integrated development reduces the cost associated with respect to discrete development of PV-ESS systems connecting to transmission ac grid and HVdc links. The integrated development incorporates advanced control methods to provide inertial and primary frequency response, reactive power support, and transient stability to manage PV and ESS resources. In this paper, high-fidelity switched system model of the integrated system and grids are developed and detailed simulation results are provided to showcase the stable operation of the integrated system and provision of grid support functions.

14 SOLAR ENERGY↗

DOE OSTI2019

Advanced High-Fidelity Lumped EMT Grid Modelling & Comparison

There is increased interest in performing electromagnetic transient (EMT) studies of large power grids for stability purposes. The large power grids may not represent the entire grid, but portions of interest. For example, studies are being performed to identify the impact of extreme events on solar power plants in California that requires the EMT model of the grid in California, but not the complete western interconnection (WI) grid model to which the grid in California is connected. The EMT models of grids are necessary to perform integration studies of large power electronics systems like utility-scale photovoltaic (PV) systems, high-voltage direct current (HVdc) systems, flexible alternating current transmission systems (FACTs), and others. Traditionally, models of grids available to utilities are the transient stability (TS) models. Hence, it assumes significance to identify methods of developing high-fidelity EMT models for portions of the grid (of interest) from the information available in the existing TS models of the entire grid. In this paper, a conversion mechanism along with upgradation based on data-driven methods is applied to develop EMT models of grids. The conversion mechanism utilizes information from TS models of grids to generate EMT models of grids. These models can be extracted for the required portion of the grid. While these models adequately represent the local voltage behaviour of the grid, they are inadequate in representing the frequency behaviour of the grid. The data-driven methods are applied to identify frequency dynamics of the grid, and the EMT models are upgraded with the data-driven methods. The resulting upgraded EMT models of grids can perform the studies mentioned above. These models are tested under contingencies of interest to validate the developed models.

Debnath, Suman↗