Sharif Digital Repository

This paper focuses on multi-objective optimisation (MOO) to optimise the planar solid oxide fuel cell (SOFC) stacks performance using a genetic algorithm. MOO problem does not have a single solution, but a complete Pareto curve, which involves the optional representation of possible compromise solutions. Here, two pairs of different objectives are considered as distinguished strategies. Optimisation of the first strategy predicts a maximum power output of 108.33 kW at a breakeven per-unit energy cost of 0.51 $/kWh and minimum breakeven per-unit energy cost of 0.30 $/kWh at a power of 42.18 kW. In the second strategy, maximum efficiency of 63.93%at a breakeven per-unit energy cost of 0.42... 

In the context of stationary power generation, fuel cell based systems are being predicted as a valuable option to tabernacle the thermodynamic cycle based power plants. In this paper, multi objective optimization approach is used to optimize the planer solid oxide fuel cell (SOFC) stacks performance using genetic algorithm technique. Multi objective optimization generates the most attractive operating conditions of a SOFC system. This allows performing the optimization of the system regarding to two different objectives. Two pairs of different objectives are considered in this paper as distinguished strategies. In the first strategy, minimization of the breakeven per-unit energy cost... 

The interaction between design parameters and operation variables is a complex problem that affects system techno-economic performance. The aim of this paper is to optimize the design and operation of an SOFC/MGT integrated system. The problem consists of design and operation optimization of an integrated SOFC/MGT system. Decision variables including design parameters (number of SOFC cells) as well as the operation parameters (air pressure ratio, methane and air flow rates). The multi objective approach using genetic algorithm is applied considering two pairs of proposed objectives: (1) maximization of output power and minimization of the electricity cost and (2) maximization of system... 

In this paper, a methodology for energy management system (EMS) based on the multi-objective receding horizon optimization (MO-RHO) is presented to find the optimal scheduling of hybrid renewable energy system (HRES). The proposed HRES which is experimentally installed in educational building comprising the PV panels, wind turbine, battery bank and diesel generator as the backup system. The data acquisition system provides input profiles for receding horizon optimizer. A mixed-integer convex programing technique is used to achieve the optimal operation regarding to two conflicting operation objectives including diesel fuel cost and battery wear cost. The Pareto frontiers are presented to... 

In this work, a novel convex sequence framework for real-time receding horizon operation optimization of a hybrid renewable energy system integrated with optimal sizing is presented to increase the penetration rate of renewable energy in supplying the demand. The proposed framework optimizes the entire lifetime cost of a system consisting of two main steps which are 1) design & installation and 2) operation as two sequence modules. This framework is applied to a hybrid renewable energy system which includes PV, wind turbine, batteries and a diesel generator. In the operation optimization, receding horizon strategy is used to optimize the operation schedule. Mixed integer convex programming... 

The aim of this study is to couple molten carbonate fuel cell (MCFC) stack with integrated gasification combined cycle fed by refinery residues, to remove CO2 from gas turbine exhaust gases that have CO2 emission rate of 14,200 ton/year. By applying multi-objective optimisation (MOO) using genetic algorithm, the optimal values of operating load and the corresponding values of objective functions are obtained. The MOO of the MCFC system regarding two scenarios is performed. The first scenario is minimisation of cost of electricity (COE) and CO2 emission rate. Objective functions of the second scenario are the same as in the first scenario while CO2 tax is taken into account. Results show that... 

Low Grade Heat Driven Multi-effect Distillation and Desalination describes the development of advanced multi-effect evaporation technologies that are driven by low grade sensible heat, including process waste heat in refineries, heat rejection from diesel generators or microturbines, and solar and geothermal energy. The technologies discussed can be applied to desalination in remote areas, purifying produced water in oil-and-gas industries, and to re-concentrate process liquor in refineries.
This book is ideal for researchers, engineering scientists, graduate students, and industrial practitioners working in the desalination, petrochemical, and mineral refining sectors, helping them...