Lin Guan

Preventive Dynamic Security Control of Power Systems Based on Pattern Discovery Technique

This paper presents a statistical learning-based method for preventive dynamic security control of power systems. Critical operating variables regarding system dynamic security are first selected via a distance-based feature estimation process. An unsupervised learning procedure called pattern discovery (PD) is then performed in the space of the critical variables to extract the subtle structure knowledge called patterns. The patterns are geometrically non-overlapped hyper-rectangles, representing the system dynamic secure/insecure regions and can be explicitly presented to provide decision support for real-time security monitoring and situational awareness. By formulating the secure patterns into a standard optimal power flow (OPF) model, the preventive control against dynamic insecurities can be efficiently and transparently attained. The proposed method is validated on the New England 39-bus system considering both single- and multi-contingency conditions.

Transient stability assessment on China Southern Power Grid system with an improved pattern discovery-based method

Intelligent systems (IS) have been widely adopted to facilitate very fast transient stability assessment (TSA) to prevent blackouts. More recently, a TSA model based on pattern discovery (PD) method has been proposed and demonstrated on several IEEE standard test systems. It has exhibited many attractive features, including high accuracy, ability to provide classification rules and system weak-points information, etc. In this paper, the PD-based TSA method is further improved by use an alternative feature selection method which is very computational efficient and tend to result in better performance. The improved model is examined on China Southern Power Grid dynamic equivalent system and compared with state-of-art IS methods. The simulation results show that the improved model has been significantly improved in modelling efficiency and its accuracy is competitive with state-of-the-art IS techniques.

A modified pattern recognition algorithm and its application in power system transient stability assessment

A modified pattern recognition algorithm based on the residual analysis and the recursive partition is proposed in this paper, which is more effective than the original algorithm in cases of high-dimension finite-sample practical engineering problems. The proposed approach is first verified with artificial testing data and then applied to power system transient stability assessment (TSA). Case studies show that the proposed pattern recognition scheme can successfully find out the relationships between the pre-contingency steady state quantities and the stability indices under each specified fault. According to the spatial description of the obtained patterns in the feature space, the transient stability levels can be predicted according to the system operation states. Thus the TSA scheme obtained can not only predict the stability index, such as the CCT value, of faults but also offer instability preventive control strategies. Simulation results on the IEEE New-England test system verifies the feasibility and good performance of the proposed algorithm. As a pattern recognition technique, it can be widely applied in different engineering domains to realize knowledge acquisition.

Power System Sensitivity Identification—Inherent System Properties and Data Quality

The increasing amount of data recorded during power system operations and recently developed data-driven methods make online sensitivity identification (SI) a possibility. However, due to the inherent properties of power systems—nonlinearity, time variance, and collinearity—the effective data that carry the sensitivity information are insufficient. Consequently, the online SI information collected with existing methods may result in unexpected estimates. In this paper, a sufficient effective data condition that guarantees the success of online SI is proposed. The inherent properties of power systems and their impacts on this condition are then investigated. A series of metrics to qualify online whether the data meet the condition is put forward to assess the online SI results. A method is also proposed to select the effective data to improve the online computational efficiency. Finally, the findings and methods are validated in an eight-generator 36-node bus system with operations data recorded from actual power systems.

Instantaneous sensitivity identification in power systems - challenges and technique roadmap

Statistical machine learning methods based on operational data are believed to have high potentials to solve the mismatch problems in power system models, vis-à-vis the real time operational conditions. As a fundamental tool in the field of situational awareness, the instantaneous sensitivity identification (ISI) using data driven methods also raises with high expectations, but in reality, it suffers from many practical issues, including data collection, evaluation, storage, and analysis problems. After spending more than five years in this research area, we now proposes a technique roadmap for online ISI with the main purpose of clarifying the challenges, analyzing the existed technologies and proposing a solution path. This paper focuses on the whole picture of the future work rather than a detailed algorithm.

Voltage Supporting Strength Evaluation Of The HVDC Receiving Grid In Synchronous And Asynchronous Interconnecting Power System

This paper simulates the voltage sags caused by HVDC failures in both the asynchronous interconnecting and the AC/DC parallel power systems and studies their relationships with the short circuit ratio (SCR) series indices. Its found that in the asynchronously interconnected power system the SCR indices can quantitatively indicate the voltage supporting ability of the receiving-end AC system under HVDC failures. However in the AC/DC parallel system the SCR indices are ineffective. An improved SCR index is then proposed to solve the problem. Simulations prove its feasibility in the AC/DC parallel power systems.

Effect of electricity feed-in tariff on the planning of CCHP Micro-systems

The electricity feed-in tariff has a profound influence on economic efficiency of a combined cooling heating and power (CCHP) micro-systems. In this paper, economic analysis of a CCHP micro-grid system is performed in different electricity feed-in tariff cases, based on a comprehensive CCHP micro-grid system framework and mathematical model considering energy storage equipment, electrical heating equipment and electrical cooling equipment. Then, the influences of electricity feed-in tariff on system design and capacity sizing of the equipment are studied.

Research and application of small time-step simulation for MMC VSC-HVDC in RTDS

This paper explores a new approach in MMC small time-step modelling which is implemented on a Xilinx ML-605 FPGA board for the RTDS simulator. The method for picking R L and C parameters of fixed-conductance valve models applied in short time-step EMT simulation is also introduced. The comparisons simulation results between RTDS and PSCAD shows two models produced very close simulation results, which demonstrats that the FPGA based MMC HVDC valve model in small time step on RTDS is correct and effective.

The Research of the Control Strategies for 4-terminal VSC-HVDC System Based on Multi Point Voltage Control and Their Implement

This paper presents the droop control strategies for 4-terminal MMC VSC-HVDC system based on multi point voltage control, which make it possible the automatic coordination among t he converter stations in the VSC-MTDC system independence of the interstation communication. Moreover, the 4-terminal MMC VSC-HVDC system control equipments, upon which the droop control strategies are realized, are designed and implemented. The 4-terminal MMC VSC-HVDC real-time simulation and testing platform, which is mainly the closed-loop connection between the MMC control equipments and RTDS, is also set up in this paper. The simulation and testing results based on the platform prove the validity and accuracy of the droop control strategies for 4-terminal MMC VSC-HVDC system based on multi point voltage control which are presented in this paper.

Guishan off-shore wind power farm interconnection: A real project study

This paper presents the study to evaluate the scheme of Guishan off-shore wind power farm interconnection. The main aim of this paper is to answer whether the planning of 200MW off-shore wind power interconnection will cause problems and to investigate the maximum off-shore wind power permitted to be interconnected to the same substation in the future. In China, the off-shore wind farm is connected to the distribution network in coastal cities. The study shows that Voltage fluctuation caused by the fluctuation of wind power is the major problem. Wind speed changes that wind speed drops from the rated value to a lower level leads to the greatest voltage fluctuation. Theres no problem to plan an off-shore wind power installation of 200MW to be interconnected. The maximum capacity of wind power to be interconnected from the islands nearby to the same substation reaches 650MW.