Volume 5, Issue 2 (Summer 2021)
Abstract
Research subject: Iran is a country with high potentials for access to renewable energy sources such as solar, hydropower, wind, and biomass. Biodiesel is one of the renewable fuels that has always been proposed as a suitable and stable alternative (non-toxic, safe, and degradable) to fossil fuels.
Research approach: The experiences of different countries in the use of edible sources for biodiesel production shows that the use of edible sources has caused problems such as lack of food resources for human communities, lack of feed for livestock, and upsetting the balance in the food industry, and it can lead to a significant increase in the price of these resources. Therefore, many researchers have proposed the use of non-edible sources to address these problems. So far, very large non-edible sources for biodiesel production have been identified. In this paper, non-edible sources of biodiesel that are produced or have the potential to be produced in Iran are introduced and studied and a potential assessment study is presented for them.
Main results: In this work, the non-edible sources for biodiesel production are classified into four categories: agricultural waste, waste cooking oils, microalgae, and non-edible seeds. These sources are compared based on various parameters such as oil percentage, oil content per hectare, biodiesel production efficiency, viscosity, saponification number, and cultivation period, which according to the results, non-edible seeds, especially Nowruzak seeds, Castor, and safflower have been identified as the most rational and sustainable sources of biodiesel production in Iran. The present work also deals with the policies and incentives that the responsible institutions can apply for the prosperity of the biodiesel industry.
Volume 5, Issue 4 (Winter 2021)
Abstract
Research subject: Bio-hydrogen is a renewable energy source with many economic and environmental benefits as a fuel. Controlling the concentration of the substrate in the reactor has a significant effect on the amount of hydrogen production. However, bio-hydrogen production is a nonlinear process that requires the implementation of nonlinear control methods. In this paper, substrate concentration in an anaerobic bio-reactor is controlled using the feedback linearization method.
Research approach: The model employed for the simulation is a well-known model consisting of three state variables. The proposed controller is a globally linearized controller (GLC) designed based on the feedback linearization technique. In this method, the nonlinear system is precisely linearized by a transformation of the coordinate system. As a result, the linearized system can be controlled using a linear controller. In order to linearize the system, a nonlinear compensator is designed using the design model and applying the concepts of differential geometry. Proportional-integral (PI) controller is adopted as a linear controller. GLC controller performance has been compared with a nonlinear controller (NC) and a PI controller. The performance of these controllers has been studied by numerical simulation based on the integral of time-square error (ITSE).
Main results: The simulation results show that substrate concentration control can contribute to the hydrogen production. The control method applied has better set-point tracking than the other two control approaches. The ITSE performance index for the feedback linearization method is lower than the other two methods. The nonlinear feedback controller fails if the kinetic parameters are changed by 25%, but the PI method and the feedback linearization are robust against model uncertainty. An efficient controller guarantees stable bio-hydrogen production. Comparing open-loop and closed-loop simulation results shows that controlling the substrate concentration increases hydrogen production by 90%.
Volume 8, Issue 2 (6-2024)
Abstract
Research Subject: Identifying and evaluating investment opportunities across the entire network of Iranian petrochemical units is of particular importance for developing the petrochemical industry's value chain, maximizing added value, and ensuring the optimal use of oil and gas resources.
Research Approach: The purpose of this research is to create a mathematical model to identify and evaluate investment opportunities by analyzing technical and economic-financial data of process units active in the Iranian petrochemical industry. This tool can process a large volume of information in a limited time and with acceptable accuracy and provide the desired output. Process information of petrochemical complexes, including operational units, production and consumption of materials, technologies used, and prices of raw materials and products, is the main data that form the basis for preparing mathematical models. In addition to process units, environmental variables affecting the system, along with their effect on the model, are also modeled and integrated with the network of process units.
Main Results: By creating a model and performing the simulation process, the various outputs of the system include: technical and economic-financial analysis, estimation of investment costs of process units, sensitivity analysis of the network of process units to technical and economic parameters and variables such as feed and product prices, as well as the operational capacity of process units. For example, to validate the simulator outputs, the actual data of the Amirkabir Petrochemical Complex were compared with the outputs obtained from the simulator, and accordingly, the error rate of the simulator was estimated to be 3.36 percent in the estimation of the production rate of main products and 22 percent in the estimation of the production rate of by-products. Finally, based on the simulator outputs, investment opportunities in the value chain of the Iranian petrochemical industry were identified, evaluated, and validated, and on this basis, the establishment of a methanol-to-olefin (MTO) conversion unit was introduced as a valid investment opportunity in the downstream part of the methanol value chain.
