تجزیه و تحلیل حساسیت اعمال شده برای بهینه سازی چندهدفه کارخانه هیبرید MCFC
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|26600||2012||9 صفحه PDF||سفارش دهید||5577 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Energy Conversion and Management, Volume 60, August 2012, Pages 180–187
In this paper, the multi-objective optimization of a molten carbonate fuel cell (MCFC) based hybrid plant fueled with landfill gas is performed. System operation is significantly affected by off-design conditions. These are due to variations methane concentration occurring as the landfill depletes, performance degradations of the components, particularly the fuel cell, and ambient conditions. For these reasons, the objective functions are defined considering the plant lifetime. Some of the parameters affecting the results, as the voltage degradation, the cost of fuel cell, the methane concentration and the unit cost of landfill gas can be only estimated or forecasted and their actual values are uncertain. Therefore, the optimization is performed considering a sensitivity analysis in order to estimate the effects of possible variations on the Pareto front. The following free design variables are considered: pressure and temperature operation of the MCFC, turbine inlet temperature, fuel mass flow rate. In addition, the optimal configuration of the heat exchanger network is selected for each set of the design variable.
Biogas in the next future will represent a non-negligible energy resource. In Europe, it currently covers less than 0.4% of the primary energy consumption (landfill gas represents about 50% of the total biogas production), but the sustainable potential for 2020 is more than 2.5% . High temperature fuel cells are particularly promising for electricity production from biogas  and , as they are able to improve the typical efficiencies of internal combustion engines. High efficiencies can be achieved with hybrid systems, obtained by integrating fuel cells with gas turbines  and . The main drawbacks concern the high investment costs of these systems. This paper is focused on the optimization of a landfill gas fueled hybrid system, which produces electricity and hydrogen. The system is defined “hybrid” because it is obtained by integrating three different subsystems: a microturbine, a molten carbonate fuel cell (MCFC) section and a pressure swing absorption system (PSA) for hydrogen production. Each subsystem is constituted of various components, which are described in the next section. Components are modeled considering design and off-design conditions. The objective of this paper is the optimal design of the entire system. Optimization involves the selection of the configuration of the heat transfer network and the value of the main design parameters. The optimization of hybrid systems is conducted in various papers available in the literature. In  the multi-objective optimization of a biogas fueled hybrid system obtained by integrating a MCFC and a microturbine is performed. A single design point is considered, but changes in the performances due to cell degradation are considered. In , a molten carbonate fuel cell (MCFC) and a gas turbine are thermally integrated to obtain a hybrid system. The system is then optimized by varying the fuel cell size and the fuel utilization coefficient. In , the optimization of plant configuration (synthesis) and the design optimization of a hybrid SOFC-gas turbine is performed. The optimization is obtained by applying a genetic algorithm followed by gradient basis algorithm. The design point corresponding to the minimum cost is obtained. In , a multi-objective optimization of a natural gas fueled SOFC-micro-gas turbine considering minimum cost and maximum efficiency is performed. The optimal heat integration is obtained by using pinch analysis, which means that the heat transfer structure is modified during the optimization process. In , a solid oxide fuel cell and intercooled gas turbine (SOFC–ICGT) hybrid cycle is considered. The optimal design is investigated by applying a design of experiment technique. Four free parameters are considered in the optimization: moisture content in the gas out of the humidifier, excess air, overall pressure ratio, low pressure compressor pressure ratio. In , a SOFC/GT system with CO2-capture is optimized using genetic algorithms. The system structure is considered as fixed, while six design parameters are considered: pressure ratio, reformer duty, cell voltage, air inlet temperature in the stacks, fuel mass flow rate, supplementary fuel mass flow rate and air mass flow rate. In the present paper, a multi-objective optimization, considering minimization of the unit cost of electricity and maximization of electrical efficiency, is performed. These quantities are evaluated along the plant lifetime, in order to account for the effect of fuel cell degradation and variations in landfill gas composition and ambient temperature. In addition, appropriate distributions of the uncertainties associated to the operation variables are obtained on the basis of experimental data or information from the literature. The effect of these uncertainties on the Pareto front of the optimal designs is considered.
نتیجه گیری انگلیسی
In this paper the multi-objective optimization of a landfill gas fueled hybrid MCFC system for electricity generation and hydrogen production is performed. The plant lifetime is considered in the optimization procedure in order to account for the effects due to the degradation in the fuel cell performance and variations in the landfill gas composition. The results show that it is particularly important to include considerations related with plant lifetime in the evaluation of the plant efficiency and on the average unit cost of electricity. In fact, there are system designs that allow one to achieve high performances when the plant is new but are less robust, which causes large unit costs. The effects of uncertainties on various operating and design variables have been also evaluated. It is shown that introducing such considerations produce significant reduction in the expected plant efficiency and increase in the unit cost of electricity. In particular, the most important effects are produced by uncertainties on ambient temperature, landfill gas composition and the methane conversion in the steam reformer.