Thermal Efficiency Optimization for Industrial Power Plants Under Load Fluctuations Using Fuzzy Logic

The automation of the control to a power plant is indeed a challenge mainly because of the occurrences of random and unpredictable variations in output demands as well as because of highly non-linear behavior of the system itself. It is sometimes argued that the 'best' control for a power plant is the operators themselves. Experienced operators are capable of making decisions on the basis of incomplete and imprecise information. The extent to which these decisions are correct is a matter of speculation. Erroneous conclusions, established post facto, are chalked up to the learning process and in fact, contribute to the forming of a good, experienced control team. The need to automate the control process for a plant is even more acutely felt when considering the complexity of the plants themselves and the volume of data that would have to be processed before a control decision can be taken. Factored into this decision would also be several governing parameters such as costs, reliability, other constraints and their interdependency, as well as planned and unscheduled outages for maintenance and so on. In this paper, however, only one facet of a power plant operation is considered. It is intended to demonstrate that thermal efficiency may be improved by better techniques for automated control of throttle valves in the steam turbine of the plant. One of these options, fuzzy logic, is selected, and defended, as being the more effective than current approaches. A comparative analysis is conducted of control methods for plant operations followed by a brief overview of fuzzy control and its application to control of non-linear systems. A method of applying this 'new' computer-based technique to control of non-linear, somewhat erratic plants is presented and discussed