scholarly journals A hybrid genetic algorithm and linear regression for prediction of NOx emission in power generation plant

2013 ◽  
Vol 16 ◽  
pp. 012101 ◽  
Author(s):  
Muhammad Afif Bunyamin ◽  
Keem Siah Yap ◽  
Nur Liyana Afiqah Abdul Aziz ◽  
Sheih Kiong Tiong ◽  
Shen Yuong Wong ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Power Generation ◽  
Linear Regression ◽  
Hybrid Genetic Algorithm ◽  
Nox Emission ◽  
Generation Plant ◽  
Power Generation Plant

Simulated performance analysis of a solar aided power generation plant in fuel saving operation mode

Energy ◽  
2019 ◽  
Vol 166 ◽  
pp. 918-928 ◽  
Author(s):  
Nan Zhang ◽  
Hongjuan Hou ◽  
Gang Yu ◽  
Eric Hu ◽  
Liqiang Duan ◽  
...  
Keyword(s):  
Power Generation ◽  
Performance Analysis ◽  
Operation Mode ◽  
Fuel Saving ◽  
Simulated Performance ◽  
Generation Plant ◽  
Power Generation Plant

scholarly journals Intelligent Airflow Controls for a Stalling-Free Operation of an Oscillating Water Column-Based Wave Power Generation Plant

Electronics ◽  
2019 ◽  
Vol 8 (1) ◽  
pp. 70 ◽  
Author(s):  
Fares M’zoughi ◽  
Izaskun Garrido ◽  
Soufiene Bouallègue ◽  
Mounir Ayadi ◽  
Aitor J. Garrido
Keyword(s):  
Power Generation ◽  
Intelligent Control ◽  
Irregular Waves ◽  
Superior Performance ◽  
Wave Power ◽  
Wells Turbine ◽  
Control Engineering ◽  
Generation Plant ◽  
Power Generation Plant ◽  
Intelligent Pid

Control engineering in renewable energy systems is a delicate and tedious task, especially due to the unpredictable nature of the renewable resources, which requires precision and robustness. These requirements can be ensured using intelligent control, which provides better performance than many conventional techniques and methods. This paper focuses on the modeling and the intelligent control of the NEREIDA wave power plant of Mutriku in Spain. In this context, the design of two novel intelligent airflow controls for a stalling-free operation of the Wells turbine-based power take-off system is presented and compared. The airflow control will ensure the avoidance of the stalling behavior using an intelligent PID controller. The first control design methodology is based on the metaheuristic algorithms to ensure the optimization of the controller gains. The second methodology is based on the fuzzy gain scheduling of the gains. Two study cases were performed to compare the optimized-PID and FGS-PID to a conventional PID in two wave conditions. The results show the superior performance of both proposed controls over the conventional PID, providing power generation improvement in regular and irregular waves.

scholarly journals The Optimization of the Location and Capacity of Reactive Power Generation Units, Using a Hybrid Genetic Algorithm Incorporated by the Bus Impedance Power-Flow Calculation Method

2020 ◽  
Vol 10 (3) ◽  
pp. 1034
Author(s):  
Insu Kim
Keyword(s):  
Genetic Algorithm ◽  
Power Generation ◽  
Calculation Method ◽  
Power Flow ◽  
Distribution Systems ◽  
Optimal Power Flow ◽  
Reactive Power ◽  
Hybrid Genetic Algorithm ◽  
Power Flow Calculation ◽  
Flow Calculation

Dynamic and static reactive power resources have become an important means of maintaining the stability and reliability of power system networks. For example, if reactive power is not appropriately compensated for in transmission and distribution systems, the receiving end voltage may fall dramatically, or the load voltage may increase to a level that trips protection devices. However, none of the previous optimal power-flow studies for reactive power generation (RPG) units have optimized the location and capacity of RPG units by the bus impedance matrix power-flow calculation method. Thus, this study proposes a genetic algorithm that optimizes the location and capacity of RPG units, which is implemented by MATLAB. In addition, this study enhances the algorithm by incorporating bus impedance power-flow calculation method into the algorithm. The proposed hybrid algorithm is shown to be valid when applied to well-known IEEE test systems.

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