All\u27s right with the world = 歌舞昇平

Film Director: Cheung King Wai (張經緯) Film Release Year: 2007https://commons.ln.edu.hk/ccs_worksheet/1002/thumbnail.jp

Multi-objective Transmission Planning Paper

2008-2009 > Academic research: refereed > Refereed conference pape

Probabilistic forecasting of wind power generation using extreme learning machine.

Accurate and reliable forecast of wind power is essential to power system operation and control. However, due to the nonstationarity of wind power series, traditional point forecasting can hardly be accurate, leading to increased uncertainties and risks for system operation. This paper proposes an extreme learning machine (ELM)-based probabilistic forecasting method for wind power generation. To account for the uncertainties in the forecasting results, several bootstrap methods have been compared for modeling the regression uncertainty, based on which the pairs bootstrap method is identified with the best performance. Consequently, a new method for prediction intervals formulation based on the ELM and the pairs bootstrap is developed. Wind power forecasting has been conducted in different seasons using the proposed approach with the historical wind power time series as the inputs alone. The results demonstrate that the proposed method is effective for probabilistic forecasting of wind power generation with a high potential for practical applications in power systems

Advanced Control Strategy of DFIG Wind Turbines for Power System Fault Ride Through

This paper presents an advanced control strategy for the rotor and grid side converters of the doubly fed induction generator (DFIG) based wind turbine (WT) to enhance the low-voltage ride-through (LVRT) capability according to the grid connection requirement. Within the new control strategy, the rotor side controller can convert the imbalanced power into the kinetic energy of the WT by increasing its rotor speed, when a low voltage due to a grid fault occurs at, e.g., the point of common coupling (PCC). The proposed grid side control scheme introduces a compensation term reflecting the instantaneous DC-link current of the rotor side converter in order to smooth the DC-link voltage fluctuations during the grid fault. A major difference from other methods is that the proposed control strategy can absorb the additional kinetic energy during the fault conditions, and significantly reduce the oscillations in the stator and rotor currents and the DC bus voltage. The effectiveness of the proposed control strategy has been demonstrated through various simulation cases. Compared with conventional crowbar protection, the proposed control method can not only improve the LVRT capability of the DFIG WT, but also help maintaining continuous active and reactive power control of the DFIG during the grid faults

Optimal prediction intervals of wind power generation

Accurate and reliable wind power forecasting is essential to power system operation. Given significant uncertainties involved in wind generation, probabilistic interval forecasting provides a unique solution to estimate and quantify the potential impacts and risks facing system operation with wind penetration beforehand. This paper proposes a novel hybrid intelligent algorithm approach to directly formulate optimal prediction intervals of wind power generation based on extreme learning machine and particle swarm optimization. Prediction intervals with associated confidence levels are generated through direct optimization of both the coverage probability and sharpness to ensure the quality. The proposed method does not involve the statistical inference or distribution assumption of forecasting errors needed in most existing methods. Case studies using real wind farm data from Australia have been conducted. Comparing with benchmarks applied, experimental results demonstrate the high efficiency and reliability of the developed approach. It is therefore convinced that the proposed method provides a new generalized framework for probabilistic wind power forecasting with high reliability and flexibility and has a high potential of practical applications in power systems

Oscillatory Stability and Eigenvalue Sensitivity Analysis of A DFIG Wind Turbine System

2010-2011 > Academic research: refereed > Publication in refereed journa

Particle filter approach to dynamic state estimation of generators in power systems

Emami, K ORCiD: 0000-0001-5614-4861This paper presents a novel particle filter based dynamic state estimation scheme for power systems where the states of all the generators are estimated. The proposed estimation scheme is decentralized in that each estimation module is independent from others and only uses local measurements. The particle filter implementation makes the proposed scheme numerically simple to implement. What makes this method superior to the previous methods which are mainly based on the Kalman filtering technique is that the estimation can still remain smooth and accurate in the presence of noise with unknown changes in covariance values. Moreover, this scheme can be applied to dynamic systems and noise with both Gaussian and non-Gaussian distributions. © 1969-2012 IEEE

An evaluation of the leading role of Hong Kong International Airport as a regional aviation hub among Greater Pearl River Delta airports

Recently ranked Skytrax 5-Star Airport, Hong Kong International Airport (HKIA) is well known for its extensive airline networks and quality supporting services. This paper is to evaluate the performance of HKIA as a leading regional aviation hub when encountering the keen competition of four other major airports in Greater Pearl River Delta (GPRD) region; all of which are within a radial distance of 100km of one another. An in-depth comparative analysis for the five GPRD airports is carried out with the application of the Aviation Hub Model and the Airport Competitiveness Index. Together with the review of the development of hub-and-spoke operation strategies, the worldwide air freedom liberalization as well as the national and regional policies, the study highlights the implications and significance drawn from the analysis upon the HKIA and four other GPRD airports. A series of feasible recommendations will be provided on the future development of their positioning and functions.published_or_final_versionUrban Planning and DesignMasterMaster of Science in Urban Plannin

Flexible transmission network planning considering distributed generation impacts

The restructuring of global power industries has introduced a number of challenges, such as conflicting planning objectives and increasing uncertainties, to transmission network planners. During the recent past, a number of distributed generation technologies also reached a stage allowing large-scale implementation, which will profoundly influence the power industry, as well as the practice of transmission network expansion. In the new market environment, new approaches are needed to meet the above challenges. In this paper, a market simulation-based method is employed to assess the economical attractiveness of different generation technologies, based on which future scenarios of generation expansion can be formed. A multi-objective optimization model for transmission expansion planning is then presented. A novel approach is proposed to select transmission expansion plans that are flexible given the uncertainties of generation expansion, system load, and other market variables. Comprehensive case studies will be conducted to investigate the performance of our approach. In addition, the proposed method will be employed to study the impacts of distributed generation on transmission expansion planning. © Copyright 2011 IEEE – All Rights Reserve