An Intelligent Temperature Controller for the Insulation Tool Storeroom of Power System

The storeroom of live working insulated tools of power system has some special requirements such as temperature and humidity. In general, the temperature is stabilized at a particular value and the humidity is higher than a certain value. The storeroom temperature and humidity are mainly controlled by the heater, dehumidifier and air-conditioning compressor. In order to well maintain the stability of the temperature, fuzzy neural network is used to control temperature which makes parameters and rules optimized by the neural network learning. So the designed controller has strong self-adapting character in controlling process. In order to improve learning speed, GA algorithm is used to optimize those initial values of fuzzy reasoning networks. And in order to overcome the shortcoming of local optimization, designed learning parameters can be adjusted according to error and error change in training. Simulating experiment shows that the designed controller has better controlling effect than other conventional controller and which can be used in the storeroom of live working insulation tools in power system.