scholarly journals The Most Economical Design of Hybrid PV/Wind/Battery/Diesel Generator Energy System Considering Various Number of Design Parameters Based on Genetic Algorithm

2021 ◽  
Vol 4 (1) ◽  
pp. 191-206
Author(s):  
Eslam Ahmed ◽  
Mennatullah Albarawy ◽  
Khaled Ibrahim
Keyword(s):  
Genetic Algorithm ◽  
Energy System ◽  
Design Parameters ◽  
Diesel Generator ◽  
Economical Design

scholarly journals Accessibility and Sustainability of Hybrid Energy Systems for a Cement Factory in Oman

2020 ◽  
Vol 13 (1) ◽  
pp. 93
Author(s):  
Wesam H. Beitelmal ◽  
Paul C. Okonkwo ◽  
Fadhil Al Housni ◽  
Wael Alruqi ◽  
Omar Alruwaythi
Keyword(s):  
Functional Limitations ◽  
Energy Systems ◽  
Energy System ◽  
Electricity Production ◽  
Diesel Generator ◽  
Hybrid Energy ◽  
Electric System ◽  
Cement Factory ◽  
Hybrid Energy Systems ◽  
Cost Of Energy

Diesel generators are being used as a source of electricity in different parts of the world. Because of the significant expense in diesels cost and the requirement for a greener domain, such electric generating systems appear not to be efficient and environmentally friendly and should be tended to. This paper explores the attainability of utilizing a sustainable power source based on a cross-breed electric system in the cement factory in Salalah, Oman. The HOMER software that breaks down the system setup was utilized to examine the application and functional limitations of each hybridized plan. The result showed that a renewable-energy (RE)-based system has a lower cost of energy (COE) and net present cost (NPC) compared to diesel generator-based hybrid electric and standalone systems. Although the two pure renewable hybrid energy systems considered in this study displayed evidence of no emissions, lower NPC and COE values are observed in the photovoltaic/battery (PV/B) hybrid energy system compared with photovoltaic/wind turbine/battery (PV/WT/B). The PV/WT/B and PV/B systems have higher electricity production and low NPC and COE values. Moreover, the PV/B has the highest return on investment (ROI) and internal rate of return (IRR), making the system the most economically viable and adjudged to be a better candidate for rural community electrification demands.

Closed-Form Correlation of Buildings Energy Use With Key Design Parameters Calibrated Using a Genetic Algorithm

2011 ◽  
Vol 133 (4) ◽  
Author(s):  
Raed I. Bourisli ◽  
Adnan A. AlAnzi
Keyword(s):  
Genetic Algorithm ◽  
Closed Form ◽  
Energy Use ◽  
Building Design ◽  
Office Buildings ◽  
Design Parameters ◽  
Wide Range ◽  
Variable Function ◽  
Real Coded Genetic Algorithm ◽  
The Difference

This work aims at developing a closed-form correlation between key building design variables and its energy use. The results can be utilized during the initial design stages to assess the different building shapes and designs according to their expected energy use. Prototypical, 20-floor office buildings were used. The relative compactness, footprint area, projection factor, and window-to-wall ratio were changed and the resulting buildings performances were simulated. In total, 729 different office buildings were developed and simulated in order to provide the training cases for optimizing the correlation’s coefficients. Simulations were done using the VisualDOE TM software with a Typical Meteorological Year data file, Kuwait City, Kuwait. A real-coded genetic algorithm (GA) was used to optimize the coefficients of a proposed function that relates the energy use of a building to its four key parameters. The figure of merit was the difference in the ratio of the annual energy use of a building normalized by that of a reference building. The objective was to minimize the difference between the simulated results and the four-variable function trying to predict them. Results show that the real-coded GA was able to come up with a function that estimates the thermal performance of a proposed design with an accuracy of around 96%, based on the number of buildings tested. The goodness of fit, roughly represented by R2, ranged from 0.950 to 0.994. In terms of the effects of the various parameters, the area was found to have the smallest role among the design parameters. It was also found that the accuracy of the function suffers the most when high window-to-wall ratios are combined with low projection factors. In such cases, the energy use develops a potential optimum compactness. The proposed function (and methodology) will be a great tool for designers to inexpensively explore a wide range of alternatives and assess them in terms of their energy use efficiency. It will also be of great use to municipality officials and building codes authors.

Optimization of Turbofan Propulsion Cycle Using a Genetic Algorithm

2010 ◽  
Author(s):  
Adel Ghenaiet
Keyword(s):  
Genetic Algorithm ◽  
Fuel Consumption ◽  
Pressure Ratio ◽  
Engine Performance ◽  
Optimization Procedure ◽  
Specific Fuel Consumption ◽  
High Mass ◽  
Design Parameters ◽  
Inlet Temperature ◽  
Simplifying Assumptions

This paper presents an evolutionary approach as the optimization framework to design for the optimal performance of a high-bypass unmixed turbofan to match with the power requirements of a commercial aircraft. The parametric analysis had the objective to highlight the effects of the principal design parameters on the propulsive performance in terms of specific fuel consumption and specific thrust. The design optimization procedure based on the genetic algorithm PIKAIA coupled to the developed engine performance analyzer (on-design and off-design) aimed at finding the propulsion cycle parameters minimizing the specific fuel consumption, while meeting the required thrusts in cruise and takeoff and the restrictions of temperatures limits, engine size and weight as well as pollutants emissions. This methodology does not use engine components’ maps and operates on simplifying assumptions which are satisfying the conceptual or early design stages. The predefined requirements and design constraints have resulted in an engine with high mass flow rate, bypass ratio and overall pressure ratio and a moderate turbine inlet temperature. In general, the optimized engine is fairly comparable with available engines of equivalent power range.

Design and Feasibility Analysis of Hybrid Energy-Based Electric Vehicle Charging Station

2021 ◽  
Author(s):  
Venkatesh Boddapati ◽  
S Arul Daniel
Keyword(s):  
Electric Vehicle ◽  
Autonomous Vehicles ◽  
Operating Cost ◽  
Energy System ◽  
Solar Pv ◽  
Diesel Generator ◽  
Hybrid Energy ◽  
Charging Station ◽  
Electric Vehicle Charging ◽  
Vehicle Charging

Mobility has been changing precipitously in recent years. With the increasing number of electric vehicles (EV), travel-sharing continues to grow, and ultimately, autonomous vehicles (AV) move into municipal fleets. These changes require a new, distributed, digitalised energy system, maintenance, and growing electrification in transportation. This paper proposes the designing of an Electric Vehicle Charging Station (EVCS) by using hybrid energy sources such as solar PV, wind, and diesel generator. The proposed system is mathematically modelled and designed using the Hybrid Optimization Model for Multiple Energy Resources (HOMER). The system is analysed and assessed in both autonomous mode and grid-connected mode of operation. The optimum sizing, energy yields of the system in each case is elaborated, and the best configuration is found for design. The variations in Levelized Cost Of the Energy (LCOE), Net Present Cost (NPC), initial cost, and operating cost of the various configuration are presented. From the results, it is observed that the grid-connected EVCS is more economical than the autonomous EVCS. Further, a sensitivity analysis of the EVCS is also performed.

Optimization of Supersonic Axial Turbine Blades Based on Surrogate Models

2020 ◽  
Author(s):  
Markus Waesker ◽  
Bjoern Buelten ◽  
Norman Kienzle ◽  
Christian Doetsch
Keyword(s):  
Reynolds Number ◽  
Turbine Blade ◽  
Surrogate Model ◽  
Cfd Simulation ◽  
Turbine Blades ◽  
Energy System ◽  
Design Parameters ◽  
Blade Design ◽  
Axial Turbine ◽  
Velocity Coefficient

Abstract Due to the transition of the energy system to more decentralized sector-coupled technologies, the demand on small, highly efficient and compact turbines is steadily growing. Therefore, supersonic impulse turbines have been subject of academic research for many years because of their compact and low-cost conditions. However, specific loss models for this type of turbine are still missing. In this paper, a CFD-simulation-based surrogate model for the velocity coefficient, unique incidence as well as outflow deviation of the blade, is introduced. This surrogate model forms the basis for an exemplary efficiency optimization of the “Colclough cascade”. In a first step, an automatic and robust blade design methodology for constant-channel blades based on the supersonic turbine blade design of Stratford and Sansome is shown. The blade flow is fully described by seven geometrical and three aerodynamic design parameters. After that, an automated numerical flow simulation (CFD) workflow for supersonic turbine blades is developed. The validation of the CFD setup with a published supersonic axial turbine blade (Colclough design) shows a high consistency in the shock waves, separation zones and boundary layers as well as velocity coefficients. A design of experiments (DOE) with latin hypercube sampling and 1300 sample points is calculated. This CFD data forms the basis for a highly accurate surrogate model of supersonic turbine blade flow suitable for Mach numbers between 1.1 and 1.6. The throat-based Reynolds number is varied between 1*104 and 4*105. Additionally, an optimization is introduced, based on the surrogate model for the Reynolds number and Mach number of Colclough and no degree of reaction (equal inlet and outlet static pressure). The velocity coefficient is improved by up to 3 %.

Investigation of magnet segmentation techniques for eddy current losses reduction in permanent magnets electrical machines

2015 ◽  
Vol 34 (1) ◽  
pp. 46-60 ◽  
Author(s):  
Belli Zoubida ◽  
Mohamed Rachid Mekideche
Keyword(s):  
Genetic Algorithm ◽  
Finite Elements ◽  
Eddy Current ◽  
Permanent Magnets ◽  
Skin Effect ◽  
Electrical Machines ◽  
Design Parameters ◽  
Finite Elements Analysis ◽  
Eddy Current Losses ◽  
Content Type

Purpose – Reducing eddy current losses in magnets of electrical machines can be obtained by means of several techniques. The magnet segmentation is the most popular one. It imposes the least restrictions on machine performances. This paper investigates the effectiveness of the magnet circumferential segmentation technique to reduce these undesirable losses. The full and partial magnet segmentation are both studied for a frequency range from few Hz to a dozen of kHz. To increase the efficiency of these techniques to reduce losses for any working frequency, an optimization strategy based on coupling of finite elements analysis and genetic algorithm is applied. The purpose of this paper is to define the parameters of the total and partial segmentation that can ensure the best reduction of eddy current losses. Design/methodology/approach – First, a model to analyze eddy current losses is presented. Second, the effectiveness of full and partial magnet circumferential segmentation to reduce eddy loss is studied for a range of frequencies from few Hz to a dozen of kHz. To achieve these purposes a 2-D finite element model is developed under MATLAB environment. In a third step of the work, an optimization process is applied to adjust the segmentation design parameters for best reduction of eddy current losses in case of surface mounted permanent magnets synchronous machine. Findings – In case of the skin effect operating, both full and partial magnet segmentations can lead to eddy current losses increases. Such deviations of magnet segmentation techniques can be avoided by an appropriate choice of their design parameters. Originality/value – Few works are dedicated to investigate partial magnet segmentation for eddy current losses reduction. This paper studied the effectiveness and behaviour of partial segmentation for different frequency ranges. To avoid eventual anomalies related to the skin effect an optimization process based on the association of the finite elements analysis to genetic algorithm method is adopted.

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