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The objective of this paper is to discuss the design and implementation of a multi-agent system that provides intelligence to a distributed smart grid - a smart grid located at a distribution level. A multi-agent application development will be discussed that involves agent specification, application analysis, application design and application realization. The message exchange in the proposed multi-agent...
A hybrid neural network-fuzzy expert system is developed to forecast one hour to forty-eight hour ahead electric load accurately. The fuzzy membership values of load and other weather variables are the inputs to the neural network and the output comprises the membership value of the predicted load. An adaptive fuzzy correction scheme is used to forecast the final load by using a fuzzy rule base and...
This paper addresses short-term load forecasting using machine learning and neural network techniques. Neural networks, though accurate in weekday load forecasting, are poor at forecasting maximum daily load, weekend and holiday loads. This necessitates development of a robust forecasting technique to complement the neural networks for enhanced reliability of forecast and improved overall accuracy...
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