Long-Term Economic Analysis and Optimization of an HT-PEM Fuel Cell based Micro Combined Heat and Power Plant

Multi-objective optimization method using genetic algorithm is employed in order to optimize design and operating parameters of a high temperature proton exchange membrane (HT-PEM) fuel cell based combined heat and power system. Net electrical efficiency of the plant, indicating the system's performance (to be maximized) and the total capital cost (to be minimized) are considered as optimization objectives. Current density (indicating the stack size), steam to carbon ratio, burner outlet temperature and auxiliary to process fuel ratio have been chosen as design parameters. Two different multi-objective optimization approaches have been utilized: steady state (without degradation) and long-term optimization while considering the degradation in fuel cell stack and the fuel processor. The results of the optimization procedures are Pareto frontiers which are a set of optimal points each of which is a trade-off between the considered objective functions. The performance indexes and operating conditions of three points with the maximum cumulative net electrical efficiency, minimum capital cost, and the same fuel cell area as that of the initial design are compared. It can be observed that while attempting to maximize the electrical efficiency, the cumulative net electrical efficiency of 29.96% can be achieved although it results in a total capital cost of 115711 €. On the other hand, the capital cost can be reduced down to 39,929 € which significantly diminishes cumulative net electrical efficiency. Finally, by locating the point on the Pareto frontier in which the fuel cell area is the same as that of the initial design, a cumulative net electrical efficiency of 27.07% was achieved which is 1% higher than the value obtained using the operating conditions of the initial design

4E Analysis and Multi-Objective Optimization of an Integrated Molten Carbonate Fuel Cell (MCFC) and Organic Rankine Cycle (ORC) System

This article proposes a novel hybrid system, integrating high temperature MCFC-GT (molten carbonate fuel cell-gas turbine) and ORC (organic Rankine cycle), which provides the possibility to achieve high electrical and exergetic efficiencies owing to the subsequent electrical power output in the bottoming cycle. After developing a mathematical model, comprehensive energetic, exergetic, economic and environmental evaluations (4E analysis) are performed and a multi-objective optimization method is utilized to find optimal solutions while considering the exergetic and economic objectives simultaneously. Two conflicting objectives including total exergetic efficiency and total cost rate of the system in multi-objective optimization are taken into account to build a set of Pareto optimal solutions. This optimum solution results in the exergetic efficiencies of 35.6%, 44.3%, and 54.9% for the fuel cell system, ORC cycle and the whole hybrid system respectively, while the total cost of the plant is 0.294 M€ per year. The study reveals that introducing the ORC bottoming cycle leads to about 5% improvement in the exergetic efficiency of the proposed plant. Furthermore, a sensitivity analysis is conducted to investigate the effect of variation in economic parameters, the fuel unit cost and interest rate, on the Pareto optimal solutions

Long-term performance analysis of an HT-PEM fuel cell based micro-CHP system: Operational strategies

In the present study, long term performance of an HT-PEM fuel cell based micro CHP system, considering the degradation within the HT-PEM fuel cell stack and the steam methane reformer has been investigated. The variations in the generated electrical and thermal power and the corresponding efficiencies, in the first 15,000 h of operation of the plant, have been studied. Two strategies have been proposed and applied in order to remedy the excursion of thermal and electrical generation of the plant from the steady state production. In the partialization strategy, by means of reducing the fuel fed to the system, the thermal generation of the plant is kept in a specified range. On the other hand, in the recovery strategy, the supplied fuel is gradually increased to suppress the progressive reduction in the power production. The long term performance analysis of the system in normal condition reveals that, due to the degradation within the system, the power production diminishes from 28.2 kW to 23.4 kW while the thermal generation increases from 52.4 kW to 57.5 kW. The results of partialization strategy show that, in order to confine the thermal generation amplification, the partialization factor should be increased up to 7.2%. On the other hand, in the recovery strategy, the supplied fuel should be progressively increased up to 34.2% in order to preserve the electrical output at the initial level. Nevertheless, the recovery strategy has an adverse effect on the electrical efficiency as it diminishes the obtained efficiency to 21.6% compared to 24% obtained for the normal operation. In the last part of the study, the overall performance indexes of the plant, while operating in normal condition and under operational strategies, are compared. It is shown that operating under recovery strategy results in overall electrical efficiency of 24.7% which is notably lower than efficiencies of 26.1% and 26.4% obtained by operating in normal condition and under partialization strategy respectively. However, it was also demonstrated that applying this strategy results in generation of 422.6 MW h of electrical energy which is higher than the values obtained by normal operation (381.3 MW h) and partialization strategy (369.8 MW h)

Techno-Economic feasibility of photovoltaic, wind, diesel and hybrid electrification systems for off-grid rural electrification in Colombia

Electrification to rural and remote areas with limited or no access to grid connection is one of the most challenging issues in developing countries like Colombia. Due to the recent concerns about the global climatic change and diminishing fuel prices, searching for reliable, environmental friendly and renewable energy sources to satisfy the rising electrical energy demand has become vital. This study aims at analyzing the application of photovoltaic (PV) panels, wind turbines and diesel generators in a stand-alone hybrid power generation system for rural electrification in three off-grid villages in Colombia with different climatic characteristics. The areas have been selected according to the "Colombia's development plan 2011-2030 for non-conventional sources of energy". First, different combinations of wind turbine, PV, and diesel generator are modeled and optimized to determine the most energy-efficient and cost-effective configuration for each location. HOMER software has been used to perform a techno-economic feasibility of the proposed hybrid systems, taking into account net present cost, initial capital cost, and cost of energy as economic indicators

Handling complete short-term data logging failure in smart buildings: Machine learning based forecasting pipelines with sliding-window training scheme

This paper implements a machine learning(ML)-based procedure for constructing the missing sensor(s) data in a net zero energy building in case of complete failure in data recording (for up to one hour). In the first scenario, missing temperature data is re-created using the sensor's ex-ante data, the HVAC system's status flag, and the ambient conditions. In the second scenario, the temperature data (until failure occurred) from two close-by spaces are also utilized as inputs. For each scenario, ML-based pipelines' performance is first assessed by considering different prediction horizons using a benchmark algorithm. Next, each pipeline's most promising features and the most suitable algorithm are identified. Using the obtained optimal pipeline, a sliding window-based training scheme is implemented, and the size of the training window is optimized. It is shown that feature selection, algorithm optimization procedures, and the sliding window-based training scheme notably improve the forecasting performance. The proposed methodology can be deployed as a tool in intervals with total data logging failure, providing data to ML-based controllers in smart buildings and avoiding disruptions in the building management system

A Technical Analysis Investigating Energy Sustainability Utilizing Reliable Renewable Energy Sources to Reduce CO2 Emissions in a High Potential Area

©2020 Elsevier Ltd. All rights reserved. This is the accepted manuscript version of an article which has been published in final form at https://doi.org/10.1016/j.renene.2020.09.042Reduction of carbon dioxide (CO 2) emissions will have a positive impact on the environment by preventing adverse effects of global warming. To achieve an eco-environment, the primary source of energy needs to shift from fossil fuels to clean renewable energy. Thus, increased utilization of renewable energy overtime reduces air pollution and contributes to securing sustainable energy supply to satisfy future energy needs. The main purpose of this study is to investigate several sustainable hybrid renewable systems for electricity production in Iran. In this regard, critical indicators that have the strongest impact on the environment and energy sustainability are presented in this study. After a comprehensive review of environmental issues, data was collected from the meteorological organization and a techno-economic assessment was performed using HOMER software. It was concluded that the hybrid configuration composed of photovoltaic (PV), wind turbine, diesel generator and battery produced the best outcome with an energy cost of 0.151$/kWh and 15.6% return on investment. In addition, the results showed that with a higher renewable fraction exceeding 72%, this hybrid system can reduce more than 2000 Kg of CO 2 emission per household annually. Although excess electricity generation is a challenge in stand-alone systems, by using the fuel cell, an electrolyzer, and a hydrogen tank unit, the amount of energy loss was reduced to less than one-sixth. These results show that selecting useful indicators such as appropriate implementation of policies of new enabling technologies and investments on renewable energy resources, has three potential benefits namely: CO 2 reduction, greater sustainable electricity generation and provides an economic justication for stakeholders to invest in the renewable energy sector.Peer reviewe