scholarly journals Stability analysis of multimachine thermal power systems using the nature-inspired modified cuckoo search algorithm

2014 ◽  
Vol 22 ◽  
pp. 1099-1115 ◽  
Author(s):  
Shivakumar RANGASAMY ◽  
Panneerselvam MANICKAM
Keyword(s):  
Stability Analysis ◽  
Power Systems ◽  
Search Algorithm ◽  
Thermal Power ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm

scholarly journals Optimal Scheduling of Large-Scale Wind-Hydro-Thermal Systems with Fixed-Head Short-Term Model

2020 ◽  
Vol 10 (8) ◽  
pp. 2964 ◽  
Author(s):  
Thang Trung Nguyen ◽  
Ly Huu Pham ◽  
Fazel Mohammadi ◽  
Le Chi Kien
Keyword(s):  
Power Plants ◽  
Search Algorithm ◽  
Thermal Power ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Optimal Scheduling ◽  
Thermal Power Plants ◽  
Short Term ◽  
Thermal Systems ◽  
Hydropower Plants

In this paper, a Modified Adaptive Selection Cuckoo Search Algorithm (MASCSA) is proposed for solving the Optimal Scheduling of Wind-Hydro-Thermal (OSWHT) systems problem. The main objective of the problem is to minimize the total fuel cost for generating the electricity of thermal power plants, where energy from hydropower plants and wind turbines is exploited absolutely. The fixed-head short-term model is taken into account, by supposing that the water head is constant during the operation time, while reservoir volume and water balance are constrained over the scheduled time period. The proposed MASCSA is compared to other implemented cuckoo search algorithms, such as the conventional Cuckoo Search Algorithm (CSA) and Snap-Drift Cuckoo Search Algorithm (SDCSA). Two large systems are used as study cases to test the real improvement of the proposed MASCSA over CSA and SDCSA. Among the two test systems, the wind-hydro-thermal system is a more complicated one, with two wind farms and four thermal power plants considering valve effects, and four hydropower plants scheduled in twenty-four one-hour intervals. The proposed MASCSA is more effective than CSA and SDCSA, since it can reach a higher success rate, better optimal solutions, and a faster convergence. The obtained results show that the proposed MASCSA is a very effective method for the hydrothermal system and wind-hydro-thermal systems.

scholarly journals Stability Evaluation of Rock Slope in Hydraulic Engineering Based on Improved Support Vector Machine Algorithm

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Fei Li ◽  
Hongyun Zhang
Keyword(s):  
Support Vector Machine ◽  
Stability Analysis ◽  
Permeability Coefficient ◽  
Engineering Geology ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Support Vector ◽  
Svm Algorithm ◽  
Improved Support Vector Machine

The safety problem of the slope has always been an important subject in engineering geology, which has a wide range of application background and practical significance in reality. How to correctly evaluate the stability of the slope and obtain the parameters of the slope has always been the focus of research and production personnel at home and abroad. In recent years, various artificial intelligence calculation methods have been applied to the field of rock engineering and engineering geology, providing some new ideas for the solution of slope stability analysis and parameter back analysis. Support vector machine (SVM) algorithm has unique advantages and generalization in dealing with finite samples and highly complex and nonlinear problems. At present, it has become a research hotspot of intelligent methods and has been widely paid attention to in various application fields of slope engineering. In this paper, a cuckoo search algorithm-improved support vector machine (CS-SVM) method is applied to slope stability analysis and parameter inversion. Aiming at the problem of selecting kernel function parameters and penalty number of SVM, a method of using cuckoo search algorithm to improve support vector machine was proposed, and the global optimization ability of cuckoo search algorithm was used to improve the algorithm. Aiming at the slope samples collected, the classification algorithm of support vector machine (SVM) was used to identify the stable state of the test samples, and the improved SVM algorithm was used to analyze the safety factor of the test samples. The results show that the proposed method is reasonable and reliable. Based on the inversion of the permeability coefficient of the test samples by the improved support vector machine, the comparison between the inversion value and the theoretical value shows that it is basically feasible to invert the permeability coefficient of the dam slope by the improved support vector machine.

scholarly journals Application of a new constraint handling method for economic dispatch considering electric market

2020 ◽  
Vol 9 (4) ◽  
pp. 1542-1549
Author(s):  
Thanh Long Duong ◽  
Ly Huu Pham ◽  
Thuan Thanh Nguyen ◽  
Thang Trung Nguyen
Keyword(s):  
Power Systems ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Constraint Handling ◽  
Effective Technique ◽  
Unit System ◽  
Electric Market ◽  
Optimal Load ◽  
Handling Method

In this paper, optimal load dispatch problem under competitive electric market (OLDCEM) is solved by the combination of cuckoo search algorithm (CSA) and a new constraint handling approach, called modified cuckoo search algorithm (MCSA). In addition, we also employ the constraint handling method for salp swarm algorithm (SSA) and particle swarm optimization algorithm (PSO) to form modified SSA (MSSA) and modified PSO (MPSO). The three methods have been tested on 3-unit system and 10-unit system under the consideration of payment model for power reserve allocated, and constraints of system and generators. Result comparisons among MCSA and CSA indicate that the proposed constraint handling method is very useful for metaheuristic algorithms when solving OLDCEM problem. As compared to MSSA, MPSO as well as other previous methods, MCSA is more effective by finding higher total benefit for the two systems with faster manner and lower oscillations. Consequently, MCSA method is a very effective technique for OLDCEM problem in power systems.

scholarly journals Optimal power generation for wind-hydro-thermal system using meta-heuristic algorithms

2020 ◽  
Vol 10 (5) ◽  
pp. 5123
Author(s):  
Thuan Thanh Nguyen ◽  
Van-Duc Phan ◽  
Bach Hoang Dinh ◽  
Tan Minh Phan ◽  
Thang Trung Nguyen
Keyword(s):  
Power Plants ◽  
Heuristic Algorithms ◽  
Search Algorithm ◽  
Thermal Power ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Optimal Operation ◽  
Total Cost ◽  
Lower Total Cost ◽  
Operation Parameters

In this paper, Cuckoo search algorithm (CSA) is suggested for determining optimal operation parameters of the combined wind turbine and hydrothermal system (CWHTS) in order to minimize total fuel cost of all operating thermal power plants while all constraints of plants and system are exactly satisfied. In addition to CSA, Particle swarm optimization (PSO), PSO with constriction factor and inertia weight factor (FCIWPSO) and Social Ski-Driver (SSD) are also implemented for comparisons. The CWHTS is optimally scheduled over twenty-four one-hour interval and total cost of producing power energy is employed for comparison. Via numerical results and graphical results, it indicates CSA can reach much better results than other ones in terms of lower total cost, higher success rate and faster search process. Consequently, the conclusion is confirmed that CSA is a very efficient method for the problem of determining optimal operation parameters of CWHTS.

scholarly journals Comparative performance analysis of one rank cuckoo search technique based optimization for automatic generation control of interconnected power systems

2017 ◽  
Vol 7 (1.2) ◽  
pp. 37
Author(s):  
N. Manoharan ◽  
Subhransu Sekhar Dash ◽  
Raghuraman Sivalingam ◽  
Dheeraj P. R.
Keyword(s):  
Power Plant ◽  
Power Systems ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Automatic Generation ◽  
Cuckoo Search Algorithm ◽  
Automatic Generation Control ◽  
Solution Technique ◽  
Interconnected Power Systems ◽  
Generation Control

This paper presents a one rank cuckoo search optimization technique is proposed to design classical PID Controllers for Automatic Generation Control (AGC) of interconnected power systems. This method is proposed based on the original cuckoo search method. It was found in original cuckoo search the convergence speed is comparative lesser in reaching optimal solutions. To overcome the above mentioned problem one rank cuckoo search algorithm has been proposed which uses a bound by best solution technique to get the valid dimension so as to improve the system performance and rate of convergence. The proposed approach is applied to a four area hydro-thermal system in which area-1 and area-2 are steam reheat power plant and area-3 and area-4 are hydro power plant. The controller gains are derived using original cuckoo search and one rank cuckoo search methods. The superiority of the proposed approach is compared with the results obtained with original cuckoo search algorithm.

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 Cuckoo Search Algorithm Optimization Approaches for Solving Economic Load Dispatch: A Review

2018 ◽  
pp. 1-15 ◽  
Author(s):  
Ganiyu Adedayo Ajenikoko ◽  
Olusoji Simeon Olaniyan ◽  
John Oludayo Adeniran
Keyword(s):  
Power Systems ◽  
Power System ◽  
Search Algorithm ◽  
Low Cost ◽  
Electrical Power ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Optimal Operation ◽  
Economic Load Dispatch ◽  
Optimization Approach

Cuckoo search algorithm (CSA) is an effective and highly reliable swarm intelligence based optimization approach. It is a technique of determining the most efficient, low cost and reliable operation of a power system by dispatching the available electricity generation resources to supply the load on the system. This paper presents a comprehensive review of CSA application in Economic Load Dispatch (ELD) problem. This review will assist power system engineers with a view to enhancing the optimal operation of available thermal plants in electrical power systems.

scholarly journals Available Transfer Capability Determination for the Electricity Market using Cuckoo Search Algorithm

2020 ◽  
Vol 10 (1) ◽  
pp. 5340-5345
Author(s):  
T. L. Duong ◽  
T. T. Nguyen ◽  
N. A. Nguyen ◽  
T. Kang
Keyword(s):  
Power Systems ◽  
Electricity Market ◽  
Search Algorithm ◽  
Accurate Determination ◽  
System Security ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Available Transfer Capability ◽  
Transmission Congestion ◽  
Transfer Capability

In the electricity market, power producers and customers share a common transmission network for wheeling power from generation to consumption points. All parties in this open access environment may try to produce energy from cheaper sources for greater profit margin, which may lead to transmission congestion, which could lead to violation of voltage and thermal limits, threatening the system security. To solve this, available transfer capability (ATC) must be accurately estimated and optimally utilized. Thus, accurate determination of ATC to ensure system security while serving power transactions is an open and trending research topic. Many optimization approaches to deal with the problem have been proposed. In this paper, Cuckoo Search Algorithm (CSA) is applied for determining ATC problem between the buses in deregulated power systems without violating system constraints such as thermal, voltage constraints. The suggested methodology is tested on IEEE 14 and IEEE 24-bus for normal and contingency cases. The simulation results are compared with the corresponding results of EP, PSO, and GWO and show that the CSA is an effective method for determining ATC.

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