Michael Negnevitsky

Very short-term wind forecasting for Tasmanian power generation

Summary form only given. This paper describes very short-term wind prediction for power generation, utilising a case study from Tasmania, Australia. Windpower presently is the fastest growing power generation sector in the world. However, windpower is intermittent. To be able to trade efficiently, make best use of transmission line capability and address concerns with system frequency in a reregulated system, accurate very short-term forecasts are essential. The research introduces a novel approach the application of an adaptive neural fuzzy inference system (ANFIS) to forecasting a wind time series. Over the very short-term forecast interval, both wind speed and wind direction are important parameters. To be able to be gain the most from a forecast on this time scale, the turbines must be directed towards on oncoming wind. For this reason, this paper forecasts wind vectors, rather than wind speed or power output

A Novel Control Strategy for a Variable Speed Wind Turbine with a Permanent Magnet Synchronous Generator

This paper presents a novel control strategy for the operation of a direct drive permanent magnet synchronous generator (PMSG) based stand alone variable speed wind turbine. The control strategy for the generator side converter with maximum power extraction is discussed. The stand alone control is featured with output voltage and frequency controller capable of handling variable load. The potential excess of power is dissipated in the damp resistor with the chopper control and the dc link voltage is maintained. Dynamic representation of dc bus and small signal analysis are presented. Simulation results show that the controllers can extract maximum power and regulate the voltage and frequency under varying wind and load conditions. The controller shows very good dynamic and steady state performance.

Distributed generation for minimization of power losses in distribution systems

Appropriate size and location of distributed generation (DG) play a significant role in minimizing power losses in distribution systems. This paper represents techniques to minimize power losses in a distribution feeder by optimizing DG model in terms of size, location and operating point of DG. Sensitivity analysis for power losses in terms of DG size and DG operating point has been performed. The proposed sensitivity indices can indicate the changes in power losses with respect to DG current injection. The proposed techniques have been developed with considering load characteristics and representing loads with constant impedance and constant current models, separately. The optimal size and location of DG in a distribution feeder can be obtained through the developed techniques, with minimum effort. The proposed techniques have been tested on a practical long radial system and results are reported. Test results have proven that up to eighty-six percent of real power loss can be reduced with a DG of optimal size, located at optimal place in the feeder

Pool-Based Demand Response Exchange—Concept and Modeling

In restructured power systems, there are many independent players who benefit from demand response (DR). These include the transmission system operator (TSO), distributors, retailers, and aggregators. This paper proposes a new concept-demand response eXchange (DRX)-in which DR is treated as a public good to be exchanged between DR buyers and sellers. Buyers need DR to improve the reliability of their own electricity-dependent businesses and systems. Sellers have the capacity to significantly modify electricity demand on request. Microeconomic theory is applied to model the DRX in the form of a pool-based market. In this market, a DRX operator (DRXO) collects DR bids and offers from the buyers and sellers, respectively. It then clears the market by maximizing the total market benefit subject to certain constraints including: demand-supply balance, and assurance contracts related to individual buyer contributions for DR. The DRX model is also tested on a small power system, and its efficiency is reported.

A Neural-Fuzzy Classifier for Recognition of Power Quality Disturbances

This article presents a neural-fuzzy technology-based classifier for the recognition of power quality disturbances. The classifier adopts neural networks in the architecture of frequency-sensitive competitive leaning and learning vector quantization. With given size of code words, the neural networks are trained to determine the optimal decision boundaries separating different categories of disturbances. To cope with the uncertainties in the involved patten recognition, the neural network outputs, instead of being taken as the final classification, are used to activate the fuzzy-associative-memory recalling for identifying the most possible type that the input waveform may belong to. Furthermore, the input waveforms are preprocessed by the wavelet transform for feature extraction so as to improve the classifier with respect to recognition accuracy and scheme simplicity. Each sub-band of the transform coefficients is then utilized to recognize the associated disturbances.

Control of a stand alone variable speed wind turbine with a permanent magnet synchronous generator

A novel control strategy for the operation of a permanent magnet synchronous generator (PMSG) based stand alone variable speed wind turbine is presented in this paper. The direct drive PMSG is connected to the load through a switch mode rectifier and a vector controlled pulse width modulated (PWM) IGBT-inverter. The generator side switch mode rectifier is controlled to achieve maximum power from the wind. The load side PWM inverter is using a relatively complex vector control scheme to control the amplitude and frequency of the inverter output voltage. As there is no grid in a stand-alone system, the output voltage has to be controlled in terms of amplitude and frequency. The stand alone control is featured with output voltage and frequency controller capable of handling variable load. A damp resistor controller is used to dissipate excess power during fault or over-generation. The potential excess of power will be dissipated in the damp resistor with the chopper control and the dc link voltage will be maintained. Extensive simulations have been performed using Matlab/Simpower. Simulation results show that the controllers can extract maximum power and regulate the voltage and frequency under varying load condition. The controller performs very well during dynamic and steady state condition.

Short term wind power forecasting using hybrid intelligent systems

This panel paper summarizes the current trends in wind power development and describes a proposed approach for short term wind power forecasting using a hybrid intelligent system.

Optimal Distributed Generation Parameters for Reducing Losses with Economic Consideration

Distributed generation (DG) represents a reliable option for solving current major problems of distribution companies, such as load growth, overloaded lines, quality of supply and reliability. Moreover, it has been proven that the additional benefits brought by DG could be substantial if properly used. This paper addresses the issue of optimizing DG planning in term of DG size and location to reduce the amount of line losses in the distribution networks. The optimization methodology, which is based on the sequential quadratic programming (SQP) algorithm, firstly assesses the compatibility of different generation schemes upon the level of power loss reduction and DG cost. The solutions obtained are finally validated with the constraints of maximum number and size of DG, as well as voltage violation and DG penetration. The proposed method is tested on IEEE 33 bus system, proving that the technique is effective and applicable.

A Novel Operation and Control Strategy for a Standalone Hybrid Renewable Power System

This paper proposes a novel operation and control strategy for a renewable hybrid power system for a standalone operation. The proposed hybrid system consists of a wind turbine, a fuel cell, an electrolyzer, a battery storage unit, and a set of loads. The overall control strategy is based on a two-level structure. The top level is the energy management and power regulation system. Depending on wind and load conditions, this system generates reference dynamic operating points to low level individual subsystems. The energy management and power regulation system also controls the load scheduling operation during unfavorable wind conditions under inadequate energy storage in order to avoid a system blackout. Based on the reference dynamic operating points of the individual subsystems, the local controllers control the wind turbine, fuel cell, electrolyzer, and battery storage units. The proposed control system is implemented in MATLAB Simpower software and tested for various wind and load conditions. Results are presented and discussed.

Dynamic operation and control of a hybrid wind-diesel stand alone power systems

This paper presents the dynamic operation and control strategies of a hybrid wind-diesel-battery energy storage based power supply system for isolated communities are investigated. Control strategies for voltage and frequency stabilization and efficient power flow among the hybrid system components are developed. The voltage and frequency of the hybrid wind-diesel system is controlled either by a load side inverter or by diesel generation depending on the wind conditions. During high penetration of wind, the wind turbine supplies the required power to the load. A battery energy storage system is connected to the dc-link to balance the power generated from the wind turbine and the power demand by load. Under low wind conditions, a diesel generator is used with wind energy conversion system to generate the required power to the load. A power sharing technique is developed to allocate power generation for diesel generator in low wind conditions. Results show that the control strategies work very well under dynamic and steady state condition to supply power to the load.