FPGA control system technology for integrating the PV/wave/FC hybrid system using ANN optimized by MFO techniques

Talaat, M.; Alblawi, Adel; Tayseer, M.; Elkholy, M.H.

doi:10.1016/j.scs.2022.103825

Cited by 21 publications

(3 citation statements)

References 37 publications

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“…Specifically, we consider SCA [12], OBSCA [20], HISCA [26], ISCA [34], GWO [35], AGWO [36], EGWO [37], MFO [38], WOA [39], and OWOA [40]. These algorithms have been extensively studied and have shown good performance in solving complex numerical optimization problems in various engineering fields [41][42][43][44][45][46][47][48]. For a fair comparison, we set the population size of all algorithms to 30, the maximum number of iterations to 10000, and the dimension of all benchmark functions to 30.…”

Section: Comparison Algorithms and Parameter Settingsmentioning

confidence: 99%

An improved sine cosine algorithm with greedy selection for global optimization

Ma,

Chen,

Tong

et al. 2023

Preprint

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The sine cosine algorithm (SCA) is a simple and efficient optimization algorithm that utilizes sine and cosine trigonometric functions to update solutions. The SCA may suffer from premature convergence to local optima due to its insufficient utilization of population information and lack of mechanism to escape from local optima. Therefore, this study proposes an improved version of the SCA called the novel sine cosine algorithm (NSCA). NSCA incorporates a new solution update equation, a greedy selection mechanism, and a disturbance mechanism to improve population diversity and prevent search stagnation. Experimental results on the Congress on Evolutionary Computation (CEC) 2017 benchmark function set and six point cloud registration problems demonstrate the effectiveness and robustness of NSCA compared to other algorithms.

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Section: Comparison Algorithms and Parameter Settingsmentioning

confidence: 99%

An improved sine cosine algorithm with greedy selection for global optimization

Ma,

Chen,

Tong

et al. 2023

Preprint

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“…In industrial workplaces, these are often used to provide mechanical energy for various loads, including massive pumps and compressors, tanks, ships, and other transport vehicles, as well as for powering generators that create electricity. In electricity generation plants, GTs may be used independently or in conjunction with a steam turbine, either in mixed cycles or in cogeneration, to provide both electrical energy and industrial heat processing (Talaat et al, 2019;Talaat et al, 2021;Talaat et al, 2022). To provide high efficacy, the mixed cycle plant, which is often utilized for energy production, is equipped with more than one GT and, frequently, one steam turbine (Cohen et al, 1987;Talaat et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Model-based performance study of an industrial single spool gas turbine 9EA-GT by changing the inlet guide vane angle and modifying the compressor map

Alblawi

2024

Front. Mech. Eng.

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In this article, an industrial gas turbine engine with a single spool (single spool 9EA-GT) is discussed, and a thermodynamic model for computing steady-state performance is presented. In addition, a novel component map production method for investigating a gas turbine engine (GTE) is developed for a different compressor and turbine by downloading from the GasTurb 12 tool and scaling to the compressor and turbine’s design points. A system of controlling engine flow capacitance by changing inlet guide vanes (IGVs) is presented. Adjusting the controllable IGV blades can optimize all the engine units by continuously correcting the compressor features map. The airflow via the compressor, which in turn controls the airflow throughout the entire system, is managed by IGVs. The computations for steady-state performance involve two models: steady-state behavior at engine startup (from 65% to 100% speed, without load) and steady-state behavior while loading (continuous speed of 100%). In this model, the challenges brought by the lack of understanding of stage-by-stage performance are resolved by building artificial machine maps using suitable scaling methods to generalized maps derived from the previous research and validating them with experimental observations from real power plants. The engine performance simulation utilizing the maps is carried out using MATLAB. Assessment results are found to be in good agreement with the actual performance data. During a steady start, the control system used in this study decreased the fuel consumption, exhaust gas mass flow rate, and compressor-driven power for the GTE by 9.5%, 19.3%, and 37.5%, respectively, and those variables decreased by 1%, 12.2%, and 19.7%, respectively, when loading the engine.

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“…The author also compared the WOA, AIS, BA, and PSO algorithms in maximizing the overall electrical output power from the wave turbine while constrained [25,26]. The power transfer capability of transmission networks is determined by the DG, societal well-being (weight 1), and network security (weight 2) weighting factors [27]. FPGA's operational inaccuracies can be alleviated by combining the moth flame optimization (MFO) method with an artificial neural network (ANN) to improve forecasting accuracy for the suggested hybrid system.…”

Section: Introductionmentioning

confidence: 99%

Optimization of a Fuel Cost and Enrichment of Line Loadability for a Transmission System by Using Rapid Voltage Stability Index and Grey Wolf Algorithm Technique

Rambabu¹,

Nuvvula²,

Muyeen

et al. 2022

Sustainability

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Efficient transmission of power is a pressing concern in modern power systems as it could relieve additional investments (e.g., right of way) and may improve stability. Non-uniform loading of transmission lines (which normally occurs due to the inefficient transmission of power) may lead to overloading of a few lines. These lines would then be prone to voltage instability. However, this problem would be aggravated under the network contingency condition. This paper focuses on improving the line loadability of the transmission system by considering the benchmark voltage stability index named rapid voltage stability index. The optimal loadability problem is considered using the grey wolf algorithm. The proposed work is implemented on a standard IEEE 30 bus test system using MATLAB software by addressing the problem by using line stability voltage index and grey wolf algorithm in optimal power flow. Minimizations of cost of generation, carbon emissions, voltage deviation, and line losses have been considered as objectives and improve the line loadability of the transmission system. The simulation results show that the proposed method is very effective in improving line loadability, reducing line congestion and fuel cost. Furthermore, the methodology is tested rigorously under various contingency conditions and is shown to be very effective. The proposed method relieves transmission line congestion and reduces fuel costs using the rapid voltage stability index (RVSI) is tested on an IEEE 30-bus standard test system utilizing MATLAB for various contingency lines

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FPGA control system technology for integrating the PV/wave/FC hybrid system using ANN optimized by MFO techniques

Cited by 21 publications

References 37 publications

An improved sine cosine algorithm with greedy selection for global optimization

An improved sine cosine algorithm with greedy selection for global optimization

Model-based performance study of an industrial single spool gas turbine 9EA-GT by changing the inlet guide vane angle and modifying the compressor map

Optimization of a Fuel Cost and Enrichment of Line Loadability for a Transmission System by Using Rapid Voltage Stability Index and Grey Wolf Algorithm Technique

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