Optimal and robust synthesis of the biodiesel production process using waste cooking oil from different feedstocks

Waste cooking oil (WCO) is generally collected from different sources, e.g., restaurants as an economic feedstock for biodiesel production. The variations of the quality of the collected oil can create uncertainty in the components of the WCO processed in the biodiesel production process. Therefore, the optimal synthesis of an alkali-catalyzed process considering the uncertainty in the WCO components was studied. The uncertain quality of the WCO feed was modeled using a Gaussian random variable. Then, a stochastic optimization approach was proposed for the design of the plant and a chance-constrained based methodology was adopted as the solution technique of the problem. The effects of the proposed approach on the design and operating parameters were studied. It was shown that the stochastic formulation can provide a safety margin to be able to tolerate the feed quality variations. The economic performance of the plant designed using different scenarios was also compared. It was shown that a plant designed using the proposed stochastic approach has 11.9% extra fixed capital investment and revenue as high as the nominal case. The proposed design can handle a range of feed qualities without major constraint violation which was not the case for designs obtained using deterministic formulation.