Set-point optimization for plant-wide control of a sugarcane mill under process and market prices disturbances: Energy and economic perspectives

Abstract

Optimization and control strategies are necessary to keep factory operations profitable while minimizing energy usage. Like many industries, the need for the sugarcane industry to improve its energy and economic efficiency is often interrupted by random variations in process inputs and market prices. Therefore, this study seeks to present a plant-wide steady-state optimal operation policy. The strategy uses a steady-state process model and a surrogate optimization algorithm to find optimal set-points that maximize factory revenue in the presence of disturbances. The controlled variables are considered as the decision variables and, after solving the optimization problem, they are provided as setpoints for the closed-loop control systems. To assign an economic value to optimal plant-wide control, the factory net revenue is defined as the objective function. A Monte Carlo method is used to randomly sample from a distribution of process and economic disturbances and to simulate the effect thereof on the energy efficiency and economics of a sugar mill. With set-point optimization, an 8.5% increase in surplus bagasse production was economically optimal despite a 0.43% reduction in sugar yield, improving the net revenue by 2.4%. Therefore, the optimizer managed to determine the optimal points at which excess energy expenditure no longer justifies the revenue gain from sugar. Considering, the global shift towards bio-based products, the increase in surplus bagasse makes it possible for a relatively large bio-refinery that uses bagasse as feedstock to be annexed to a set-point optimized sugarcane mill.