scholarly journals Cuckoo search algorithm for integration wind power generation to meet load demand growth

2017 ◽  
Author(s):  
Saida Makhloufi ◽  
Saheb Djohra Koussa ◽  
Gobind Gopalakrishna Pillai
Keyword(s):  
Power Generation ◽  
Wind Power ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Wind Power Generation ◽  
Demand Growth ◽  
Load Demand

Research on Optimal Gradient - Climbing Algorithm in Wind Power Generation

2013 ◽  
Vol 385-386 ◽  
pp. 1100-1103 ◽  
Author(s):  
Qiang Zhao ◽  
Chang Cui
Keyword(s):  
Power Generation ◽  
Wind Power ◽  
Search Algorithm ◽  
Buck Converter ◽  
Wind Power Generation ◽  
Generation System ◽  
Load Impedance ◽  
Point Tracking ◽  
Power Generation System ◽  
Step Climbing

Maximum power point tracking for wind power generation system fixed step climbing algorithm prone to miscalculation and oscillation shortcomings. Adaptive improved optimal gradient method is put forward to overcome the shortcomings and optimize the existing fixed step climbing algorithm. By Controlling Buck Converter duty radio rapidly match between wind power generation system and load impedance. The simulation result shows that the anti-interference and convergence of the improved hill-climb search algorithm is better than that of the traditional one.

The Application of Improved Hill-Climb Search Algorithm in Wind Power Generation

2013 ◽  
Vol 46 (20) ◽  
pp. 263-267 ◽  
Author(s):  
Hua Li ◽  
Qun Li ◽  
Xu Jiang ◽  
Ying Ruan ◽  
Wenhui Huang
Keyword(s):  
Power Generation ◽  
Wind Power ◽  
Search Algorithm ◽  
Wind Power Generation

scholarly journals Minimize electricity generation cost for large scale wind- thermal systems considering prohibited operating zone and power reserve constraints

2021 ◽  
Vol 11 (3) ◽  
pp. 1905
Author(s):  
Phan Nguyen Vinh ◽  
Bach Hoang Dinh ◽  
Van-Duc Phan ◽  
Hung Duc Nguyen ◽  
Thang Trung Nguyen
Keyword(s):  
Wind Power ◽  
Electricity Generation ◽  
Power Plants ◽  
Large Scale ◽  
Search Algorithm ◽  
Thermal Power ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Working Zone ◽  
Generation Cost

Wind power plants (WPs) play a very important role in the power systems because thermal power plants (TPs) suffers from shortcomings of expensive cost and limited fossil fuels. As compared to other renewable energies, WPs are more effective because it can produce electricity all a day from the morning to the evening. Consequently, this paper integrates the optimal power generation of TPs and WPs to absolutely exploit the energy from WPs and reduce the total electricity generation cost of TPs. The target can be reached by employing a proposed method, called one evaluation-based cuckoo search algorithm (OEB-CSA), which is developed from cuckoo search algorithm (CSA). In addition, conventional particle swarm optimization (PSO) is also implemented for comparison. Two test systems with thirty TPs considering prohibited working zone and power reserve constraints are employed. The first system has one wind power plant (WP) while the second one has two WPs. The result comparisons indicate that OEB-CSA can be the best method for the combined systems with WPs and TPs.

scholarly journals Controller design for DFIG‐based WT using gravitational search algorithm for wind power generation

2021 ◽  
Author(s):  
Om Prakash Bharti ◽  
Kumari Sarita ◽  
Aanchal Singh S. Vardhan ◽  
Akanksha Singh S. Vardhan ◽  
R. K. Saket
Keyword(s):  
Power Generation ◽  
Wind Power ◽  
Controller Design ◽  
Search Algorithm ◽  
Gravitational Search Algorithm ◽  
Wind Power Generation ◽  
Gravitational Search

scholarly journals Multi-Objective Optimal Reactive Power Planning under Load Demand and Wind Power Generation Uncertainties Using ε-Constraint Method

2020 ◽  
Vol 10 (8) ◽  
pp. 2859 ◽  
Author(s):  
Amir Hossein Shojaei ◽  
Ali Asghar Ghadimi ◽  
Mohammad Reza Miveh ◽  
Fazel Mohammadi ◽  
Francisco Jurado
Keyword(s):  
Power Generation ◽  
Power Systems ◽  
Wind Power ◽  
Reactive Power ◽  
Test System ◽  
Wind Power Generation ◽  
Multi Objective ◽  
Load Demand ◽  
Reactive Power Planning ◽  
Constraint Method

This paper presents an improved multi-objective probabilistic Reactive Power Planning (RPP) in power systems considering uncertainties of load demand and wind power generation. The proposed method is capable of simultaneously (1) reducing the reactive power investment cost, (2) minimizing the total active power losses, (3) improving the voltage stability, and (4) enhancing the loadability factor. The generators’ voltage magnitude, the transformer’s tap settings, and the output reactive power of VAR sources are taken into account as the control variables. To solve the probabilistic multi-objective RPP problem, the ε-constraint method is used. To test the effectiveness of the proposed approach, the IEEE 30-bus test system is implemented in the GAMS environment under five different conditions. Finally, for a better comprehension of the obtained results, a brief comparison of outcomes is presented.

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