JournalTOCs

Journal of Smart Systems and Stable Energy
Number of Followers: 2

This is an Open Access Journal

Open Access journal
ISSN (Online) 2958-0293
Published by Forscher Publication

[1 journal]

Optimization of Combined Cooling, Heating, And Power System using Amended
supply-demand-based optimizer
- Abstract: The required cold and heat are supplied by recycling the heat lost from the stimulus in combined cooling, heating, and power (CCHP) generation system. The present study proposes a new optimal arrangement for a CCHP system for annual dynamic simulation. This study uses CCHP system to design a separated stand-alone generation system to provide higher effectiveness. The system is then improved by a new enhanced metaheuristic technique, namely supply-demand-based optimization algorithm to enhance the efficiency of the designed system. The method is implemented on a hospital and its achievements are put in comparison with several different newest optimization techniques. The achievements indicate that the electricity system purchased from the utility network and fuel consumption for the optimized combined cooling, heating, and power system in comparison with the system of separated generation provides a decreasing trend.
Optimum Sizing of CCHP System using Modified Group Teaching Optimization
Algorithm
- Abstract: A new technique is prsented in this paper for optimum design of a combined cooling heating and power (CCHP) system. The prime mover in this study is a gas turbine and this is designed for a rural area in Zhaoping County, Guangxi, China. The effectiveness of the method is assessed based on four main parameters: exergetic, energetic, economic, and environmental features. A Modified Group Teaching Optimization Algorithm (MGTO)is utilized for achieving resuls with better accuracy and convergence. The achievements of the suggested MGTO-based technique are put in comparison with genetic optimizer-based method and improved owl optimization algorithm-based method to illustrate the method higher efficiency.
Developing Hierarchical RBF Neural Network for Model Identification of
SOFCs using a Developed Coronavirus Herd Immunity Algorithm
- Abstract: A new Blackbox technique has been presented in the current paper for model estimation of the solid oxide fuel cells (SOFCs) for providing better results. The proposed method is based on a Hierarchical Radial Basis Function (HRBF). The presented method is then developed by a new modified metaheuristic, called Developed Coronavirus Herd Immunity Algorithm. The suggested model has been named DCHIA-HRBF. The proposed model is then trained by some data and prepared for the identification and prediction. The model is then analyzed and were put in comparison with several latest techniques for validation of the efficiency of the technique. It is also verified by the empirical data to prove its validation with the real data. Simulation results specified that the suggested DCHIA-HRBF delivers high effectiveness as an identifier and prediction tool for the SOFCs.
Improved Mayfly Algorithm for Optimal Design of Hybrid PV/Diesel Generator
along with Battery: Application to Shilisha Village in Maowusu Desert,
China
- Abstract: This paper presents an optimal size selection of a hybrid renewable PV/DG/Battery system in a remote area in Maowusu Desert, China. The idea is to select optimal numbers of PV panels, DGs, and battery storage units by minimizing of the total annual cost of the hybrid system. The optimization of the problem is performed based on a new improved version of Mayfly Algorithm (IMA) which is introduced for improving the effectiveness of the optimization in terms of accuracy, convergence, and consistency. Simulation results of the suggested algorithm are compared with some different optimization algorithm to show the prominence of the method. The proposed method shows that the optimal numbers for the optimized system includes 28 PV panels, 88 battery units, and 1 DG unit. Final results show that utilizing the suggested hybrid system gives the best minimum operational cost of the system compared with others. 
Optimal Configuration of a HRES system by Amended Rain Optimizer
- Abstract: In this paper, a new technical and economic analysis for a hybrid system of energy has been performed. The study presents a new procedure for optimal modeling of the hybrid renewable energy system (HRES). The main idea is to optimize the hybrid system configuration based on a multiple-criteria optimization, including three objectives. To simplify the problem and turning it to a single objective problem of optimization, ε-constraints technique has been used. This optimization is done by minimizing the capital cost (CC) and maximizing the electrical power effectiveness and the power supply consistency. To provide a well solution, a new amended design of the rain optimizer has been employed. The method provided a pareto solution with three groups that can be selected based on the decision maker’s purpose.
Optimum Structure for a CCHP System by Amended Coyote Optimizer
- Abstract: The present study proposes a new optimal configuration of a combined cooling, heating, and power (CCHP) system for annual dynamic simulation. To provide higher efficiency from the CCHP system, a new enhanced bio-inspired algorithm, namely Amended Coyote Optimizer is designed and utilized. The proposed optimal technique is then carried out to a commercial building in Tongchuan, China. The simulations of the suggested method are finally confirmed by the data achieved by the case study which is done to show the method efficacy. Simulation achievements showed that the suggested technique has better effectiveness to provide similar data with the real value.