Lance Chun Che Fung, Murdoch University, Australia Title: Neural Solutions for problems in the Power and Energy Industry

Abstract: Two of the imminent challenges to the human society are how to meet the rising demands in energy, and how to reduce impacts on the environment. To these ends, neural techniques have been used to tackle many problems in the power and energy industry. Examples of such applications have included load demand forecasting, power generator modeling, emission control, economic and emission scheduling, fault diagnosis, maintenance planning, and price forecasting. On the other hand, developments in the power and energy industry are moving towards deregulated markets, increasing deployment of renewable energy, distributed and micro power generation, smart and intelligent grids, differential pricing and demand management. This tutorial is application oriented and it targets audience who are new to this problem domain, and those who are interested to learn how neural computing has played its part in solving today and tomorrow's world problems.