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Energy optimization and controller performance assessment in a pulp mill cogeneration facility

University of British Columbia

Over the past few decades, the production and sale of “green" electricity from cogeneration has become a critical component of economic and environmental sustainability for the pulp and paper industry. As with almost every complex industrial process, the true value of a cogeneration facility is highly dependent on how efficiently and effectively it is utilized. This thesis develops and demonstrates two optimization-based process management tools that maximize the economic outputs from cogeneration: a high level unit economic performance assessment method, and an energy management strategy for optimal real time cogeneration facility management. The economic performance assessment tool simultaneously optimizes the steady state operating setpoints and process variability loads according to an economic objective function. Setpoints are optimized based on a back-off approach to constraint handling, and variability loads are optimized based on the comparison of current control with LQG control strategies. The result is a realistic quantification of potential process performance. Additionally, the convex form of the optimization problem results in quick solution times. Results are presented in the form of two case studies. The energy management system maximizes cogeneration profitability in real time by effectively coordinating key process parameters and various external influences according to an economic objective function. Potential process configurations are constrained using a cogeneration plant model. The optimization procedure is carried out using a flexible forecast horizon that predicts such time-dependant influences as electricity sale prices, limited fuel costs and supplies, and special cases of dynamic operational safety constraints. By constructing such a complete optimization problem based on the complex operation of a cogeneration facility, a sustainable and economically optimal plant management strategy is achieved. Additionally, the convex form of the optimization problem results in quick solution times, which is critical to effective online implementation. Results are presented in the form of three case studies.

Text

2010-08-11

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/27240

Chemical and Biological Engineering

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/4.0/