M. Daneshdoost

A Simplified Dynamic Model of Grid-Connected Fuel-Cell Generators

This article describes a reduced-order dynamic model for a grid-connected fuel-cell power plant that is suitable for preliminary stability assessment. Generic voltage and power control loops are included. The model is applied to a distributed utility that uses fuel cells and gas turbines to investigate the nature and magnitude of their interaction. The studies presented in the paper show the effect of the mix between fuel cell and gas turbine generation on the system stability. The developed model, being simple, could provide a useful tool for the planning of distributed generation.

AI approach to optimal VAr control with fuzzy reactive loads

This paper presents an artificial intelligence (AI) approach to the optimal reactive power (VAr) control problem. The method incorporates the reactive load uncertainty in optimizing the overall system performance. The artificial neural network (ANN) enhanced by fuzzy sets is used to determine the memberships of control variables corresponding to the given load values. A power flow solution determines the corresponding state of the system. Since the resulting system state may not be feasible in real-time, a heuristic method based on the application of sensitivities in an expert system is employed to refine the solution with minimum adjustments of control variables. Test cases and numerical results demonstrate the applicability of the proposed approach. Simplicity, processing speed and ability to model load uncertainties make this approach a viable option for online VAr control. >

Neural network with fuzzy set-based classification for short-term load forecasting

Electric power utilities require forecast of system demand or electrical load for one to seven days ahead. This paper studies a short-term electric load forecasting technique using a multi-layered feedforward artificial neural network (ANN) and a fuzzy set-based classification algorithm. The hourly data is subdivided into various class of weather conditions using the fuzzy set representation of weather variables and then the ANNs are trained and used to perform the load forecasting up to 120 hours ahead with a remarkable accuracy.

Local sliding control for damping interarea power oscillations

In this paper, a sliding control (SC) algorithm design is considered for damping local power oscillations in a multiple area power transmission system. The control algorithm utilizes static Var compensators (SVC) to supply reactive power to the transmission system to stabilize the system in the event of faults. The controller is capable of achieving full utilization of the SVC and is insensitive to parameter variations and modeling errors. In general, more than one SVC is needed to effectively damp modes of power oscillation in a multiple area system. The simulation results for multiple area power system show the effectiveness of the proposed sliding controller in damping the interarea power oscillations, and in enhancing the stability as well as loadability of the transmission system.

A PC based integrated software for power system education

This paper presents the implementation of an integrated software package to run under PC-DOS for the analysis and design of Electric Power Networks. Graphics and windows are embedded in the user interface to form the basis of the interactive environment. System configuration is entered graphically, while system data is entered directly through tabular windows. A variety of analysis programs are provided in this environment such as different types of load flow solution techniques. In addition, this paper demonstrates a novel use of PC enhanced graphics capability to display the real and reactive power flows by means of animation. A modular interactive expert system is an element of this environment. Popular features such as help menus and icons selection menus are also included. The modular design of this environment permits the user to interface any custom made analysis package regardless of the computer language used. This environment proves to be useful for educational and research purposes. Recent work in CAE (Computer Aided Engineering) and CAI (Computer Assisted Instruction) areas show a clear trend toward more sophisticated user interfaces. One of the primary goals of any interactive environment is to enhance the bandwidth of communication between the user and the application program. Wider bandwidth of communications means that more information is conveyed to the user in a shorter period of time. The user interface is the aspect of the program that governs the communication between the user and the application.

Neural network approach to power system security

A neural network approach to power systems static security analysis Is presented. This security analysis includes both security assessment and enhancement. For security assessment, a three-layer feedlorward network has been developed for a small 5-bus system. This network represents the nonlinear nature of the power system accurately enough to identify severe security violations. The momentum method was used to train the network. For security control(enhancement) of power systems, a recurrent network approach Is proposed to replace the existing expert system technique. Given an insecure operating state, the proposed approach will produce the operating points which result in a secure operation of the system. The preliminary results Indicate that neural network approach (given neural network hardware availability) can be used for on-line security analysis in a power systems control center enviroment.

Local sliding control for damping inter-area power oscillations

Summary form only given. A sliding control (SC) algorithm design is considered for damping local power oscillations in a multiple area power transmission system. The control algorithm utilizes static VAr compensators (SVC) to supply reactive power to the transmission system to stabilize the system in the event of faults. The controller is capable of achieving full utilization of the SVC and is insensitive to parameter variations and modeling errors. In general, more than one SVC is needed to effectively damp modes of power oscillation in a multiple area system. The simulation results for multiple area power system show the effectiveness of the proposed sliding controller in damping the interarea power oscillations, and in enhancing the stability as well as loadability of the transmission system.

Smart actuators for active vibration control

In this paper, the design and implementation of smart actuators for active vibration control of mechanical systems are considered. A smart actuator is composed of one or several layers of piezo-electric materials which work both as sensors and actuators. Such a system also includes micro- electronic or power electronic amplifiers, depending on the power requirements and applications, as well as digital signal processing systems for digital control implementation. In addition, PWM type micro/power amplifiers are used for control implementation. Such amplifiers utilize electronic switching components that allow for miniaturization, thermal efficiency, cost reduction, and precision controls that are robust to disturbances and modeling errors. An adaptive control strategy is then developed for vibration damping and motion control of cantilever beams using the proposed smart self-sensing actuators.

Application independent interactive environment for power systems education

The authors present an interactive software package for the simulation of power system stability studies. The package is intended as a supplementary tool for the teaching of power system stability courses at the graduate level. The development of the package was done exclusively for IBM-PC and compatible computers. The hardware mainly requires VGA display and 640 kbyte of memory. Professional libraries used for the development of the package include Meta Windows, graphics Menu, and Object Professional. The authors describe the methods used for the integration of various analysis programs and the organization of the data and information pertinent to a system study. >

A Computational Model For Sensing Depth From A Single 2-D Image

It is generally a difficult task to obtain a complete geometrical model of a scene given a limited number of storage spaces, or to construct a 3-D scene geometry from one or more 2-D images. In this paper we focus on extracting information about a 3-D scene geometry given a 2-D image. The degree of blurriness (or sharpness) gives rise to computation of depth of an object. A method of shape from sharpness, based on this concept, is introduced. Given a point source image, its distance from a lens is obtained. This can be applied to an arbitrary scene consisting of superposition of many point sources.