Modelling and Simulation of Biodiesel Production in a PFR

Guide

Dr. Chinta Sankar Rao

Members

Aditya Reddy P

Abhijeet Singh

Devendra

Aim

The aim of the project was to create a simplified Model of a biodiesel plant and implement a suitable Controller operating in a Plug Flow Reactor (PFR) using Matlab-Simulink.

Introduction

The motivation for creating a biodiesel model has been related to the increased energy demand and the development towards new energy resources. Biodiesel is made from plant oils, animal fats or even waste cooking oils through transesterification and esterification reactions with alcohols. It constitutes a renewable, biodegradable and carbon neutral alternative to petroleum diesels. The use of sustainable energy sources have increased focus amongst the population so a study of biodiesel can be related to a society interest in addition to the engineering perspective.

Reactions

Raw Materials: Triglyceride (TG) and Methanol (MeOH)

Product: Methyl Ester (ME)

By-Product: Glycerol (GL)

Intermediates: Diglyceride(DG)and Monoglyceride (MG)

• TG + 3 MeOH <=> GL + 3 ME
• TG + MeOH <=> DG + ME
• DG + MeOH <=> MG + ME
• MG + MeOH <=> GL + ME

Operating Parameters

Component Balances

Implementation of Controller

Control system design is necessary to achieve a production level of consistency, purity, economy and safety which cannot be achieved purely by human manual control. It can be seen from the dynamic models equations of biodiesel that all equations are highly nonlinear in nature which cannot be used directly to achieve the specified objectives. Hence, these models need to be approximated to FOPTD model so that an efficient controller can be designed. Here we tune the controller by various methods based on the FOPTD model and try to get the controller settings that best control our system. The control system has been implemented for both the product ME and by-product GL. The FOPTD model parameters are enlisted in Table 1 and the controller parameters are enlisted in Table 2. Figure 2 depicts the Response curves of ME for both the controllers.

Conclusion

An identification of Biodiesel model has been done in this study. The PID settings are designed based on the identified FOPTD model using IMC and ECM method and compared. The set of two settings is implemented on the nonlinear Biodiesel plant and evaluated the efficacy of the controller. From the simulation studies it is observed that the PID settings obtained from IMC method produces a superior closed loop response for servo type disturbances in terms of time integral errors such as IAE, ISE etc than that of the ECM method.

Future Scope

• Taking the outcomes and results of current project as basis the plant will be simulated in Aspen plus, a industry standard software,for the purification of the product from the reactor.
• A Model Predicive Control (MPC) will be embedded in the current project.