Load Forecasting Of Power System Research Articles

Short term load forecasting of Taiwan power system using a knowledge-based expert system

A knowledge-based expert system was developed for the short-term load forecasting of the Taiwan power system. The developed expert system, which was implemented on a personal computer, was written in PROLOG using a 5-year database. To benefit from the expert knowledge and experience of the system operator, eleven different shapes, each with different means of load calculations, were established. With these load shapes at hand, some peculiar load characteristics pertaining to the Taiwan Power Company can be taken into account. The special load types considered by the expert system include the extremely low load levels during the week of the Chinese New Year, the special load characteristics of the days following a tropical storm or a typhoon, the partial shutdown of certain factories on Saturdays, the special event caused by a holiday on Friday or on Tuesday, etc. A characteristic feature of the knowledge-based expert system is that it is easy to add new information and new rules to the knowledge base. To illustrate the effectiveness of the system, short-term load forecasting is performed on the Taiwan power system by using both the developed algorithm and the conventional Box-Jenkins statistical method. It is found that a mean absolute error of 2.52% for one year is achieved by the expert system approach as compared to an error of 3.86% by the statistical method.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Improvement of electric power system load forecasting and operational planning for control automation

Methodological approaches to solving long-term and short-term electrical power system and interconnected power system load-forecasting and operational planning problems existing in the USSR are described, as well as information and system technological aspects of these problems. The present state of the art and future directions of methodological and program elaborations in this field are also considered.

Microprocessor Based Parameter and State Estimator and its Application to Load Forecasting of Interconnected Power Systems

This paper describes the implementation of a combined parameter and state estimation algorithm for multivariable stochastic systems on PACE 16-bit microprocessor with only necessary software without utilizing any sophisticated software packages which result in an economical package of small physical dimensions and cost. The dedicated microprocessor system has been applied to solve the problem of short-term load forecasting of interconnected power systems. Real load data from the Eastern Province of Saudi Arabia is employed to check the microprocessor implementation and good results have been obtained compared with the results obtained from large scale computer.

Application of a Multivariable System Identification Technique in Power System Load Forecasting Problem

The paper is concerned with the development of a computationallv efficient algorithm for forecasting the future values of a vector variable involved in the power system load forecasting problem. It is shown that the stochastic multivariable svstem identification techniaue proposed recentlv by Tse and Weinert (1975) can be emploved for this Purpose with advantace in some cases. Results of real data orocessina are presented in order to illustrate the advantages and disadvantaaes of the proposed forecasting algorithm.