Forecasting Minimum Production Costs with Linear Programming

This paper presents an approach to and the results of applying Linear Programming to the forecasting of minimum production costs of electric utility systems. It describes the linear problem format used in the optimization of the start-up and load allocation of generating units. Included are results from investigations of the influence of linear versus nonlinear unit cost/output curves and the number of time segments used to approximate a load duration curve. A comparison is made with production costs obtained from an established program. The results show that production costing can be reduced to a linear problem with little loss of accuracy. The speed, accuracy, and flexibility achieved by using Linear Programming techniques make it a desirable method of production costing for many study purposes.