QUALITY ASSESSMENT OF POWER SYSTEM USING ARTIFICIAL NEURAL NETWORK S. GUPTA & J. SHUKLA Professor, Department of Electrical, NIT, Raipur, Chhattisgarh, India ABSTRACT In recent years Artificial Intelligence has been proposed as an alternative tool to provide quick solutions to certain difficult power system problems. With intelligent systems, such as ANN, the available information regarding the power system can be stored and retrieved as a part of new solution process. ANN computing may require larger time for off line training but is capable of giving instant response for a given condition and hence, is suitable for on-line applications. This paper describes ANN base technique for obtaining the quality of interconnected power system. Desired level of voltage has been maintained using back propagation algorithm base network, which is trained to represent the system as ANN model. The well-trained model can use to predict the quality and the losses of the power system. This trained model can also predict the behavior of the network as load increase. KEYWORDS: Artificial Intelligence, ANN, Alternative Tool, Off Line Training, Quality of Interconnected Power System INTRODUCTION There has been a remarkable progress in the development of software and hardware for the design and analysis of power systems. However, much still depends on judgment of human experts. Experienced planning and design personnel make efficient and viable decisions on the basis of their comprehensive experience and the knowledge of prevailing circumstances. This paper mainly gives the description of the concept of Artificial Neural Network in the field of assessment of power system. The IEEE-30 bus model has been taken for the analysis of voltage, phase angle and losses variation. Simulated model has been trained for the production of quality of load flow. Artificial Intelligence based Demand Side Management has been developed by I.E.Hopley et al [1] and A.S.Zadgaokkar [2] to support energy management in power system during abnormal situations. Hoyong Kim et al [3] and E.A. Mohamed [4] suggested Artificial Neural Network based feeder reconfiguration for loss reduction in distribution systems. ANN Models have been suggested to give direct and accurate results nearly instantly for the sample IEEE 30-Bus power systems. The study includes bus voltage distribution and phase angle. ANN FOR LOAD FLOW SOLUTION The conventional solution techniques use series mode of iterative calculations that makes it more time consuming. The strong parallel processing capability of Artificial Neural Network is therefore applied to solve the load flow problem. The ANN technique is totally different from the conventional techniques. The ANN model does not at all represent the inherent intricate mathematical non-linear relationships among the input-output parameters constituting the power system International Journal of Electrical and Electronics Engineering Research (IJEEER) ISSN(P): 2250-155X; ISSN(E): 2278-943X Vol. 3, Issue 5, Dec 2013, 39-44 © TJPRC Pvt. Ltd.