Application of linear and dynamic programming to the optimization of the production of hydroelectric power

Application of the methods of control theory to industrial problems demands a match of the necessary computational tools to the actual financial constraints. The development of suboptimal control algorithms allows performance gains that were limited in the past to installations with extensive computer facilities to be reached now by smaller ones. Advances in this domain lead naturally to a rational use of modern control tools based on mini- and microcomputers. Within this framework, we present a general method for the optimal control of electric power plants. The optimization problem is described and formulated as the optimal control of a multivariable state-space model in which the state and control vectors are constrained by sets of equality or inequality relations. The solution is obtained in two steps with linear and dynamic programming methods; the results are expressed in the form of parametric algorithms which set up the working point of the turbine-generator units so that the resulting profit represents a maximum. The application of the method to the optimization of the production of a Swiss electricity company illustrates the approach.