Yang Yihan

Bio: Yang Yihan is an academic researcher from North China Electric Power University. The author has contributed to research in topics: Fault (power engineering) & Electric power system. The author has an hindex of 10, co-authored 72 publications receiving 365 citations.

Voltage fluctuation and flicker caused by wind power generation

Abstract: During the continuous operation and the switching-option of wind turbines connected to the power grid, the voltage fluctuation and flicker occur and affect the power quality in the local power network Starting from the fluctuation of the power output of wind turbines, the main reasons causing the voltage fluctuation and flicker by wind power generation are analyzed, then the IEC Standard 61400-21 for the power quality of grid-connected wind turbines is introduced The calculation formulae for flicker and relative voltage change which occurs during the continuous operation and the switching-option of wind turbines are given The research achievements in the calculation methods and the influencing factors of the voltage fluctuation and flicker caused by wind power generation is summarized Finally, the research area and the key problems to be researched in the future are viewed

Three-phase-to-four-phase transformer for four-phase power-transmission systems

Abstract: In this paper, a new three-phase-to-four-phase transformer with four-phase four-leg structure is first proposed, its electromagnetism principle is analyzed, and the properties and features of the transformer are also discussed. This transformer may be applicable to either four-phase transmission systems or autotransformer (AT) traction power-supply systems in electric railways.

Analysis of transient stability of power system including large scale wind power based on the extended equal area rule

Abstract: When wind farms are connected into the grid with high capacity and multi-point, and they are centralized and located far away from load centers, the electrical connection between wind farms and the grid is usually weak. So the impact of large scale wind power on the grid is extended from local issues to the issue of system stability. Unlike conventional power plants, grid-connected wind farms have their inherent characteristics which make the power system transient stability become more complex. In the paper, the power system transient stability including large scale wind farms is analyzed theoretically based on extended equal area rule. The value of wind turbines power is equaled to the mechanical power of the equivalent synchronous generators. The effect of the control of wind farms on the equivalent mechanical power of synchronous machine is also considered. Then according to the method, the power system transient stability including large scale wind farms is discussed. At last, the effectiveness of the mechanism is verified by simulation. In this paper, the equal area rule is extended to analyze the power system transient stability including wind farm.

Practicalization of Fault Location in Distribution Lines

Abstract: Via analyzing modern methods for fault location in distribution lines, a proper method aiming at single-phase to ground is put forward to transfer theory to practice, as well as the concept of line structure feature-wave. Two steps are in this method. Firstly, high rate waveform picking from the fault line is recorded utilizing C-type traveling-wave scheme, and by adaptive filter and differencing the data is processed and fault distance is calculated. Secondly, scanning the peak value of recorded waveform and excluding pseudo-features, so the line structure feature waveform is extracted, thus the fault branch is fixed. The combined two results of fault distance and fault branch make fault location accurately. After experiments on spot, this method is proved correctly, as well as its good practicality prospect.

Integrating genetic algorithm with expert system for service restoration in distribution system

Abstract: A new method for service restoration in a distribution system is proposed, which combines the advantage of an expert system (ES) and that of a genetic algorithm (GA). The method makes full use of ES' reasoning ability to prepare data concerned with GA, and to determine switching operation planning. Furthermore, network reconfiguration is carried out with GA, which means that each blackout area is divided into several sub-areas providing electricity through different power sources. As a result, the restoration scheme is ultimately formed. Through tested with practical power network, not only can the system provide the optimum solution, but also several sub-optimum solutions. So that operators can get more reference information.

Power Quality Issues in Railway Electrification: A Comprehensive Perspective

Abstract: Since the beginning of railway electrification, power quality has been a main problem in railway networks because of their special characteristics. Many ways of power quality improvement have been investigated and applied to ac and dc traction systems through railway electrification history. This paper presents a perspective on power quality issues through railway electrification development and investigates the necessity of power quality and system requirements for appropriate power quality. Compensation strategies are classified and compared. This aims to provide a comprehensive perspective of the power quality issue in railway power/distribution networks for researchers and engineers working on railway electrification. Less than 100 research articles are referenced for researchers to obtain good background information.

Optimal Restoration of Distribution Systems Using Dynamic Programming

Abstract: This paper solves the distribution system restoration problem using dynamic programming with state reduction. The algorithm is an operator-permissive, automated approach to the restoration of distribution systems after a blackout. The timing and selection of feeders to be energized are represented as states in a dynamic programming formulation. An enhanced dynamic programming method reduces the number of states by grouping states that are close to each other and selecting the best state. The algorithm was tested on an 8 feeder/32 load distribution system. The method is applicable to radially configured systems.

A Multi-Purpose Balanced Transformer for Railway Traction Applications

Abstract: A multi-purpose balanced (MPB) transformer is proposed in this paper for electric railway applications. The MPB transformer is developed from impedance-matching (IM) transformers widely used in China's railway systems. The proposed MPB transformer has three main functions: (1) it provides a symmetrical two-phase voltage of 27.5 kV for railway overhead lines to power electric trains; (2) it supplies a three-phase balanced voltage of 10.5 kV for railway substations; and (3) it can accommodate a three-phase harmonic filter with improved power factor and reduced manufacturing cost. In this paper, the operating principles of the MPB transformer are elaborated, the design of the harmonic filters is discussed, and the results of computer simulations are provided. A 16-MVA MPB transformer was designed and commissioned, and real-time field measurements are provided.

Improving Knowledge-Based Systems with statistical techniques, text mining, and neural networks for non-technical loss detection

Abstract: Currently, power distribution companies have several problems that are related to energy losses. For example, the energy used might not be billed due to illegal manipulation or a breakdown in the customer's measurement equipment. These types of losses are called non-technical losses (NTLs), and these losses are usually greater than the losses that are due to the distribution infrastructure (technical losses). Traditionally, a large number of studies have used data mining to detect NTLs, but to the best of our knowledge, there are no studies that involve the use of a Knowledge-Based System (KBS) that is created based on the knowledge and expertise of the inspectors. In the present study, a KBS was built that is based on the knowledge and expertise of the inspectors and that uses text mining, neural networks, and statistical techniques for the detection of NTLs. Text mining, neural networks, and statistical techniques were used to extract information from samples, and this information was translated into rules, which were joined to the rules that were generated by the knowledge of the inspectors. This system was tested with real samples that were extracted from Endesa databases. Endesa is one of the most important distribution companies in Spain, and it plays an important role in international markets in both Europe and South America, having more than 73 million customers.