Artificial intelligence techniques

Abstract

Traditional analytic and time analysis approaches may not easily handle online real-time applications for large systems due to computational time requirements. In particular, the power systems being non-linear and time varying, application of traditional approaches to a power system for the purpose of identifying its parameters, controlling the operation to maintain stability and damping oscillations following disturbances is not suitable for online monitoring. They are more suitable for offline design and investigations. Advent of artificial intelligence (AI) techniques based on logic mathematics has encouraged power system engineers, planners and designers to employ these techniques with the goal of reducing computation time and designing fast algorithms that are adequate for power system online applications. Many AI and computational intelligence techniques, such as artificial neural network (ANN), fuzzy logic (FL), neuro-FL (NFL), particle swarm optimisation (PSO), genetic algorithms, exist. The basics of ANN, FL and NFL as well as the adaptive neuro-fuzzy control (ANFC) are presented in this chapter as they are used, in addition to the time analysis techniques, for some applications (e.g. power system stabilisers and static var compensators) to power systems in the subsequent chapters.