Q. H. Wu

Coordinated scheduling of energy resources for distributed DHCs in an integrated energy grid

As more and more distributed renewable energy resources connected to electric power grids, the conventional power system evolves into an integrated energy grid (lEG) in order to satisfy various types of energy demands. This paper proposes a model of the coordinated scheduling of energy resources (CSoERs) for distributed district heating and cooling systems (DHCs) in an lEG. The model takes into consideration both the dispatchable grid-connected generators and distributed renewable energy resources, such as wind energy, solar energy and natural gas. The objective is to minimize the operation costs in the lEG in order to satisfy not only the electrical loads but also the heating loads and cooling loads. Furthermore, an energy storage system for heating loads and cooling loads is also developed in the DHCs to improve the operation reliability in the distributed DHCs. Detailed simulation studies are carried out to verify the effectiveness of the CSoERs under two different operation scenarios: grid-connected scenario and stand-alone scenario. Simulation results demonstrate that the performance of the CSoERs contributes to significant energy saving and reliability operation in both grid-connected scenario and standalone scenario in the lEG.

Finite-Element Modeling for Analysis of Radial Deformations Within Transformer Windings

This paper develops computational models for undeformed and deformed transformers, using the finite-element method (FEM) to calculate frequency dependent parameters accounting for diamagnetic properties. In this manner, properly estimated inductances and capacitances can be derived and applied into a winding model for frequency response analysis (FRA). This research uses a hybrid winding model, so that frequency responses in the high frequency range ( >1 MHz) can be explored for the investigation of radial winding deformation. Meanwhile, computational models with respect to winding radial deformation are constructed, so that corresponding inductances and capacitances in specific radial deformed cases can be obtained by FEM. Therefore, the influence of the capacitances as well as the inductances can be taken into account for FRA of radial deformation in high frequencies. The frequency response in the undeformed case is compared with the experimental data to verify the accuracy of the frequency dependent parameters and mathematical winding models. The analyzed results in radial deformed cases are compared with the fault features derived from experimental studies reported in relevant literatures.

A Hybrid Least-square Support Vector Machine Approach to Incipient Fault Detection for Oil-immersed Power Transformer

Abstract In this article, incipient fault detection methods using a novel hybrid classifier are developed for dissolved gas analysis of oil-immersed power transformers. New fault features are derived by analyzing various industry standards of dissolved gas analysis. Two effective data pre-processing methods are employed for improving diagnosis accuracies. Bootstrap is first utilized to equalize sample numbers of different fault types, and then the logarithmic transform is applied to generate additional classification features. In experiments, a least-square support vector machine, support vector machine, and support vector data description are developed as fault classifiers, and the optimal parameters of the three classifiers are obtained using particle swarm optimization. A comprehensive comparison is made regarding the performance of the three support vector machine based classifiers for the first time in the area of dissolved gas analysis. Moreover, classification boundaries are illustrated to provide an in-depth understanding upon the performance of each classifier with clear visualization figures. The results indicate that least-square support vector machine can significantly improve the diagnosis accuracy of dissolved gas analysis along with the proposed pre-processing methods.

Dual-Mode Control of AC/VSC-HVDC Hybrid Transmission Systems With Wind Power Integrated

This paper proposes a novel dual-mode control scheme for the control of an ac/voltage-source converter (VSC)-HVDC hybrid transmission system with the wind farm connected. First, a novel ac voltage and phase-angle control scheme is designed for the active power control of the wind farm side voltage-source converter (WFVSC) such that the switching of control schemes of WFVSC is no longer required when the ac lines are switched on or off the transmission system. This results in the proposed dual-mode control scheme being able to accommodate different operation modes of the ac/dc hybrid transmission systems. Second, an improved direct-current vector control scheme has been designed for the control of grid-side VSC (GVSC) to provide better control of the dc voltage of the GVSC. Moreover, simulation studies have been undertaken on a two-terminal VSC-HVDC and an ac hybrid transmission system under a variety of operating conditions, which have validated the feasibility performance of the proposed control scheme.

Power system dispatch with wind power integrated using mean-variance model and group search optimizer

This paper presents the mean-variance (MV) model to solve power system dispatch problems with wind power integrated. In the MV model, the profit and the risk are taken into account simultaneously under the uncertain wind power (speed) environment. To describe this uncertain environment, the Monte Carlo (MC) simulation method is used to sample uncertain wind speeds. The optimization algorithm, group search optimizer (GSO), then optimize the MV model by introducing the risk tolerance parameter. The simulation is conducted based on the IEEE 30-bus power system, and the results demonstrate the applicability of the proposed model into power system dispatch problems with wind power integrated.

Identification of current transformers saturation intervals using morphological gradient and morphological decomposition

This paper proposes a novel method to detect the saturation intervals of current transformer (CT) secondary current. The method features the waveform properties of the distorted secondary current, which has abrupt changes where saturation begins and ends. Two algorithms, the improved morphological gradient and the morphological decomposition, are designed to extract the saturation intervals, respectively, and the detection results are combined using the AND logic to give the final detection result. The proposed saturation detection scheme is implemented and tested on a sample power system model built in PSCAD/EMTDC. The simulation results show that the proposed method can accurately detect the onsets and ends of saturations under a variety of operation conditions.

Detection and classification of low-frequency power disturbances using a morphological max-lifting scheme

This paper presents a morphological max-lifting scheme for the detection and classification of low-frequency power disturbances. In order to extract waveform features of low-frequency disturbances, the proposed scheme employs mathematical morphology (MM) for its advantage in noise removing and max-lifting for its ability of information preserving. Afterwards, two aided variables are constructed to assist the classification of low-frequency disturbances. A variety of low-frequency power disturbances have been included in simulation studies and simulation results have demonstrated the effectiveness and feasibility of the proposed scheme.

Saturation detection of current transformers for protection blocking based on waveform symmetry using morphological skeleton

This paper proposes a novel scheme to detect the saturation of current transformers (CTs) for protection blocking. The scheme modifies the morphological skeleton method and applies it to analyze the shape information of CT secondary current. Afterwards, two indices are introduced to determine the existence of saturation. Simulation studies under a variety of fault conditions have been conducted using PSCAD/EMTDC to evaluate the performance of the proposed scheme. The results have shown that the proposed scheme is able to detect CT saturation accurately, and is robust to noise and sensitive to mild saturation.

Modeling of a central heating electric boiler integrated with a stand-alone wind generator

This paper proposes a model of a central heating electric boiler integrated with a stand-alone wind generator. The paper also investigates control schemes for the wind turbine generator and the electric boiler. For the wind turbine generator, the two control schemes are proposed for control of the pitch angle and generator rotor speed respectively. The pitch angle control uses the generator output power as the input signal to ensure normal operation in high wind speed. The speed control is realized by adjusting the resistive load to trace the maximum output power. For the boiler, the temperature control is used to regulate the outlet water temperature by changing the electric power obtained from the power grid. In order to verify the proposed model and control schemes, simulation studies have been conducted using MATLAB/Simulink. Simulation results demonstrate that the wind turbine generator can trace the maximum power in the low and medium wind speeds and operate at the rated output in the high wind speeds, with the help of the proposed control schemes. It is also proved that the outlet water temperature of the boiler can be regulated by its temperature controller according to a set point.

Multi-objective optimization of generation maintenance scheduling

For the generation maintenance scheduling (GMS) problem, a producer hopes to maximize its profit while ISO is to guarantee the system reliability. Thus, the GMS is a multi-objective optimization problem. In the GMS, there are large numbers of both continuous and integer variables, which complicates the resolving of the GMS. This paper proposes a new GMS model, which is suitable to be solved by the non-dominated sorting genetic algorithm-II (NSGA-II). In the GMS model, the maintenance status of a generator is encoded into an integer variable and both the online status and the start-up status are represented by the generation variables. The GMS model on the IEEE reliability test system is solved by NSGA-II with a set of Pareto-optimal solutions obtained. The simulation results show that the GMS can be efficiently solved by NSGA-II. The simulation results also show that one producers profit conflicts with another ones, and that the reliability objective is independent of the other objectives.