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.
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.
Roza Gholamin
Abstract
The combined heating, cooling, and power source (CCHP) system is a good tool for the optimal consumption of fossil fuel thermal energy. In CCHPs, the produced waste heat from the hot gases can be recycled for generating power, heat, and water cooling and oil in electrical power generation systems which ...
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The combined heating, cooling, and power source (CCHP) system is a good tool for the optimal consumption of fossil fuel thermal energy. In CCHPs, the produced waste heat from the hot gases can be recycled for generating power, heat, and water cooling and oil in electrical power generation systems which can improve the efficiency of the system to more than 85%. This study presents an optimum structure for the combined heating, cooling, and power source energy flow to decrease the power demand in a building in Yazd city, Iran. In this research, a developed version of collective animal behavior optimizer is introduced to develop the combined heating, cooling, and power source system efficiency compared to the separation generation system. Two different scenarios have been studied for analyzing system efficiency. In one scenario, a constant value (670 kW) was assumed to the capacity while the electric cooling (EC) to cool load ratio (CLR) is assumed variant in a determined range and at the other scenario, an opponent condition with 0.75 constant EC to CLR were assumed. Simulation achievements of the presented technique are put in comparison with standard balanced moth search optimizer and genetic algorithm to indicate the efficiency of the algorithm.
