Neuro PID control of power generation using a low temperature gap

Abstract

Power generation using a low temperature gap converts heat energy into electricity by using the temperature difference. In this article, a simulation model for power generation using a low temperature gap, which uses a circulation cycle with ammonia as the working fluid, is constructed as a linear multiple input/multiple output (MIMO) model which has 2 inputs and 2 outputs based on the step response method. A PID controller using a back propagation neural network is designed so that the difference in pressure between the turbine inlet and outlet is kept at 0.3 Mpa.