An optimizing software system was developed to predict technically feasible, economically optimum operating points for a multi-faceted combined heat and power facility. The software combines detailed technical performance with a flexible purchase and sale model to predict equipment load levels that optimize net plant revenue subject to operational constraints. The optimization technique is iterative and relies on successive linear approximation of the true nonlinear behavior of the plant. Detailed production capability of each plant component is pre-simulated over the entire range of operation using a widely-accepted, commercially-available simulation package. Pre-simulated results are stored in look-up tables for fast evaluation during optimization calculations. Sensitivity of predicted optimum load point is analyzed using further constrained optimization runs. This paper provides description of the optimization technique, its implementation, and numerical sensitivity analysis, as well as insightful example cases.

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