Myo Thwin
Abstract
In this study, a new optimized version of multi-layer perceptron neural network has been used for modeling achieving an optimized configuration in biofuel production process. 25 semi-pilot fermentation runs are used to determine the best arrangement of percentage selection for the combined substrate ...
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In this study, a new optimized version of multi-layer perceptron neural network has been used for modeling achieving an optimized configuration in biofuel production process. 25 semi-pilot fermentation runs are used to determine the best arrangement of percentage selection for the combined substrate of rice bran, cow dung, paper waste, banana stem, and saw dust to develop the biogas generation process efficiency and speed. The neural network is optimized by an improved version of Monarch Butterfly Optimization (DMBO) algorithm and the results have been compared with basic MBO algorithm and GA based algorithm from literature to illustrate the algorithm capability.
Nasser Yousefi
Abstract
In this study, economic, environmental, and technical optimization of a hybrid Microturbine-Solid Oxide Fuel Cell (SOFC) system is performed in a full load for the distributed generated electricity. To achieve better results, a new modified metaheuristic, called Balanced Manta Ray Foraging Optimization ...
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In this study, economic, environmental, and technical optimization of a hybrid Microturbine-Solid Oxide Fuel Cell (SOFC) system is performed in a full load for the distributed generated electricity. To achieve better results, a new modified metaheuristic, called Balanced Manta Ray Foraging Optimization Algorithm is adopted for multi-objective optimization of the problem. The system has been thermodynamically modeled and the results validated the system efficiency by considering the available data from the reference. During the optimization, the decision variable values have been evaluated by considering the system constraints to achieve an optimal criterion for the cost and exergy efficiency objective functions. Also, the cost of environmental degradation penalty has been added to the system total cost. The effect of the fuel price, investment cost, and the system output power value on the system are taken into consideration. The results show that the most sensitive and the most significant design parameter of the system is the current density of the fuel cell where the accurate selection of it, has a big effect on forming a trade-off between the system cost and the efficiency.
Zumrat Druzhinin
Abstract
A new optimal hybrid solar/diesel/battery system was suggested in this paper for covering the load demand in a rural area in Taklamakan Desert located in China. The major idea is to design a new improved version of the Student Psychology Based Optimization Algorithm for minimizing the load probability ...
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A new optimal hybrid solar/diesel/battery system was suggested in this paper for covering the load demand in a rural area in Taklamakan Desert located in China. The major idea is to design a new improved version of the Student Psychology Based Optimization Algorithm for minimizing the load probability loss, the annualized system expense, and the value of the CO2 release. The study also used the ε-constraint method to make a single objective problem from the multi-objective problem. The final results are compared with two other methods from the literature to indicate the higher capability of the method. The study also applied sensitivity analysis on the εCO2, εLLP, and the load consumption to show proper results of the system against different variations.
Mohammad Mohammaditab
Abstract
This paper proposes a new methodology for optimal sizing of a combined cooling heating and power (CCHP) system with a gas turbine as its primary mover in a residential building in Xihu area in Hangzhou, Zhejiang, China. Due to the significant impact of four substantial parameters including energetic, ...
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This paper proposes a new methodology for optimal sizing of a combined cooling heating and power (CCHP) system with a gas turbine as its primary mover in a residential building in Xihu area in Hangzhou, Zhejiang, China. Due to the significant impact of four substantial parameters including energetic, exergetic, environmental, and economic (4E), their features are used during the gas engine size optimization of the CCHP system. The paper also proposes a new modified version of the Farmland Fertility Optimization (FFO) Algorithm to solve the sizing problem. The new algorithm is designed to resolve the premature convergence and the local optimum of the basic algorithm. The results of the proposed MFFO-based system compared with the GA-based system and the basic FFO-based system. Simulation results show that the optimal cost value for the MFFO, FFO, and the GA are 0.191, 0.191, and 0.192, respectively that are achieved after 25, 35, and 50 iterations. This shows the effectiveness of the proposed method in terms of convergence and accuracy.
Giorgos Jimenez
Abstract
This paper addresses one of the most important challenges in utilization of renewable energy source the design of a system that incorporates this type of energy sources, which is the size determination of system component. A meta-model of hybrid renewable power system is studied here which can include ...
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This paper addresses one of the most important challenges in utilization of renewable energy source the design of a system that incorporates this type of energy sources, which is the size determination of system component. A meta-model of hybrid renewable power system is studied here which can include many sorts of renewable and nonrenewable energy sources as well as energy storage. This system is then optimized in terms of component size to supply the load with minimum overall cost. In addition, a novel optimization algorithm is proposed here named modified marine predators optimization technique which addresses the shortcomings observed in classic and metaheuristic optimization algorithm which are slow convergence, local optima, and immature convergence. Moreover, a real-world case study in an isolated location is analyzed here and a hybrid renewable power system with diesel generator, PV panels, and battery and the proposed optimization algorithm are implemented to determine optimum component size. The results suggest that, due to high investment cost, only a battery with very small capacity is economically advisable. Utilization of the proposed methodology here can help the system designers and operators to increase renewable energy penetration with higher reliability and lower costs.
Antonella Pasternak
Abstract
The main idea of this paper is to multi-criteria optimal designing of a combined cooling, heat and power (CCHP) system in an industrial unit by considering cooling loads, electricity, and heating. Different scenarios such as selling scenarios, no-selling scenario, as well as the possibility of electricity ...
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The main idea of this paper is to multi-criteria optimal designing of a combined cooling, heat and power (CCHP) system in an industrial unit by considering cooling loads, electricity, and heating. Different scenarios such as selling scenarios, no-selling scenario, as well as the possibility of electricity selling with identical capacities of the gas engine have been utilized. Because of the complexity of this problem, a new developed metaheuristic methodology, called Balanced Tree Growth Algorithm (BTGA) is designed and utilized. Relative Annual Benefit (RAB) as a multi-criterion function along with a gas engine is utilized as the primary mover during the optimization. Final simulation indicate that the proposed approach has well results toward the method from the literature. The results also specified that however using of the proposed configuration gives suitable results for different scenarios, selling scenario is more profitable.
