scholarly journals Comparative Study of Solar PV System Performance under Partial Shaded Condition Utilizing Different Control Approaches

2021 ◽  
Author(s):  
Ibrahim Al-wesabi ◽  
Fang Zhijian ◽  
M.B Shafik ◽  
Galal Al-Muthanna ◽  
M. A. K. Yousaf Shah
Keyword(s):  
Heuristic Algorithms ◽  
Search Algorithm ◽  
Local Maximum ◽  
Weather Conditions ◽  
Cuckoo Search ◽  
Photovoltaic Cell ◽  
Cuckoo Search Algorithm ◽  
Solar Pv ◽  
Pv System ◽  
Modified Particle Swarm Optimization

Abstract The solar system characteristics are affected due to few obscure terms, causing a reduction of photovoltaic system's power output. Also, partial shaded conditions (PSCs) lead to several peaks on photovoltaic (PV) curves, which decrease conventional techniques' efficiency Also, in these (PSCs), standard equations might not be implemented entirely. Therefore, this study aims, first to modify and re-establish the mathematical model of PV array under (PSCs). Second, heuristic algorithms (Cuckoo Search Algorithm (CSA) and Modified Particle Swarm Optimization (MPSO)) have been suggested and applied with PV system to promote output power under varying weather conditions and PSCs. Moreover, these algorithms can improve the dynamic response and steady-state PV systems' performance simultaneously and effectively. Later on, the following approaches, modified (MP&O) and (ANN), are also proposed to extract the photovoltaic system's maximum power. Then, MPPT problem is modeled and optimized on MATLAB environment where it is reliable to connect the programmable optimizer with Simulink of photovoltaic cell used to validate results. Finally, proposed methods are examined under several scenarios for (PSCs) to investigate its effectiveness. The results ensure that proposed tracker based on CSA can distinguish between the global and local maximum peaks of PV system effectively comparing to others MPPT approaches.

scholarly journals Optimization of Reservoir Operation Using Cuckoo Search Algorithm: Example of Adiguzel Dam, Denizli, Turkey

2016 ◽  
Vol 2016 ◽  
pp. 1-7 ◽  
Author(s):  
Mutlu Yasar
Keyword(s):  
Energy Production ◽  
Heuristic Algorithms ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Complex Problem ◽  
Cuckoo Search Algorithm ◽  
Optimal Operation ◽  
Operating Rules ◽  
Operation Rule ◽  
Production Regime

The Adiguzel Dam is located in Denizli in the western part of Turkey. It was built for irrigation purposes, but it also produces energy at the same time. The dam’s energy-production regime is not regular since there are no reservoir-operating rules. Thus, this study develops a reservoir optimization rule to generate a corresponding gain in energy production. It is well known that operating a reservoir is a complex problem that depends on many parameters such as inflow, storage capacity, water elevation, tailwater elevation, and evaporation. Therefore, in order to optimize energy production, there is a need to use heuristic algorithms such as the Cuckoo Search (CS). This study develops a CS algorithm-based solution to optimize the reservoir’s operational system and generate an optimal operation rule curve. Results show that the CS algorithm improves the system operation, and the energy production will be increased by about 10% to a value of 160000 MWh with a corresponding economic gain of about $12 × 106in total for 183 months.

scholarly journals Maximum power point tracking of partially shading PV system using cuckoo search algorithm

2019 ◽  
Vol 10 (2) ◽  
pp. 1081 ◽  
Author(s):  
Ahmed Ibrahim ◽  
Raef Aboelsaud ◽  
Sergey Obukhov
Keyword(s):  
High Efficiency ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Maximum Power ◽  
Global Maximum ◽  
Pv System ◽  
Maximum Power Point ◽  
Partial Shading ◽  
Power Point

This paper presents a cuckoo search (CS) algorithm for determining the global maximum power point (GMPP) tracking of photovoltaic (PV) under partial shading conditions (PSC). The conventional methods are fail to track the GMPP under PSC, which decrease the reliability of the power system and increase the system losses. The performance of the CS algorithm is compared with perturb and observe (P&O) algorithm for different cases of operations of PV panels under PSC. The CS algorithm used in this work to control directly the duty cycle of the DC-DC converter without proportional integral derivative (PID) controller. The proposed CS model can track the GMPP very accurate with high efficiency in less time under different conditions as well as in PSC.

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 A Review of Cuckoo Search Algorithm Based Optimal Siting and Sizing of Shunt Capacitors in Radial Distribution Systems

2019 ◽  
Vol 1 (2) ◽  
Author(s):  
O.E. Olabode
Keyword(s):  
Radial Distribution ◽  
Distribution Systems ◽  
Reactive Power ◽  
Heuristic Algorithms ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Sensitivity Factor ◽  
Voltage Profile ◽  
Shunt Capacitors

Compensating reactive power deficiency on power grids is a central concern in the distribution of energy management systems. Several approaches have been adopted over time to minimize the total real power loss and enhancing bus voltage profile. Shunt capacitor has been used from time immemorial for addressing issue of reactive power compensation at the distribution end of power systems, and the extent of benefits derivable from its usage depend solely on correct siting and sizing. To this effect, meta-heuristic algorithms are promising optimization tools for achieving these objectives. This paper, therefore, presents a comprehensive review of cuckoo search algorithm based on optimal siting and sizing of shunt capacitors in radial distribution systems. The suitability, in addition to strengths and weakness of each approaches reported in the reviewed articles have been painstakingly x-rayed. Based on the review, it was observed that a two-stage approach is always adopted in the compensation process: the pre-selection of potential or sensitive nodes and the optimal sizing of shunt capacitors needed for the compensation. For the pre-location, Voltage Stability Index and Loss Sensitivity Factor were found to be comparatively less complex and highly suitable techniques. Another cogent discovery from this review is that less attention has been drawn to the use of cuckoo search algorithm by Nigerian researchers. Therefore, regarding Nigerian electric grid system, the use of cuckoo search algorithm in reactive power support presents a research gap for further investigations.

scholarly journals Maximum Power Point Tracking of PV system Based Cuckoo Search Algorithm; review and comparison

2019 ◽  
Vol 162 ◽  
pp. 117-126 ◽  
Author(s):  
Mohamed I. Mosaad ◽  
M. Osama abed el-Raouf ◽  
Mahmoud A. Al-Ahmar ◽  
Fahd A. Banakher
Keyword(s):  
Search Algorithm ◽  
Maximum Power Point Tracking ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Maximum Power ◽  
Pv System ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Power Point

A Cuckoo Search Algorithm With Elite Opposition-Based Strategy

2016 ◽  
Vol 25 (4) ◽  
pp. 567-593 ◽  
Author(s):  
Kang Huang ◽  
Yongquan Zhou ◽  
Xiuli Wu ◽  
Qifang Luo
Keyword(s):  
Heuristic Algorithms ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Search Space ◽  
Global Optimum ◽  
Cuckoo Search Algorithm ◽  
Neighborhood Search ◽  
Complex Functions ◽  
Dynamic Search ◽  
Searching Ability

AbstractIn this paper, a cuckoo search (CS) algorithm using elite opposition-based strategy is proposed. The opposite solution of the elite individual in the population is generated by an opposition-based strategy in the proposed algorithm and form an opposite search space by constructing the opposite population that locates inside the dynamic search boundaries, then, the search space of the algorithm is guided to approximate the space in which the global optimum is included by simultaneously evaluating the current population and the opposite one. This approach is helpful to obtain a tradeoff between the exploration and exploitation ability of CS. In order to enhance the local searching ability, local neighborhood search strategy is also applied in this proposed algorithm. The experiments were conducted on 14 classic benchmark functions and 28 more complex functions from the IEEE CEC’2013 competition, and the experimental results, compared with five other meta-heuristic algorithms and four improved cuckoo search algorithms, show that the proposed algorithm is much better than the compared ones at not only the accuracy of solutions but also for the convergence speed.

Optimal broadcast scheduling method for VANETs: An adaptive discrete firefly approach

2020 ◽  
Vol 39 (6) ◽  
pp. 8125-8137
Author(s):  
Jackson J Christy ◽  
D Rekha ◽  
V Vijayakumar ◽  
Glaucio H.S. Carvalho
Keyword(s):  
Intelligent Transportation System ◽  
Search Algorithm ◽  
Mac Protocol ◽  
High Mobility ◽  
Optimal Solution ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Traffic Density ◽  
Scheduling Problem ◽  
Broadcast Scheduling

Vehicular Adhoc Networks (VANET) are thought-about as a mainstay in Intelligent Transportation System (ITS). For an efficient vehicular Adhoc network, broadcasting i.e. sharing a safety related message across all vehicles and infrastructure throughout the network is pivotal. Hence an efficient TDMA based MAC protocol for VANETs would serve the purpose of broadcast scheduling. At the same time, high mobility, influential traffic density, and an altering network topology makes it strenuous to form an efficient broadcast schedule. In this paper an evolutionary approach has been chosen to solve the broadcast scheduling problem in VANETs. The paper focusses on identifying an optimal solution with minimal TDMA frames and increased transmissions. These two parameters are the converging factor for the evolutionary algorithms employed. The proposed approach uses an Adaptive Discrete Firefly Algorithm (ADFA) for solving the Broadcast Scheduling Problem (BSP). The results are compared with traditional evolutionary approaches such as Genetic Algorithm and Cuckoo search algorithm. A mathematical analysis to find the probability of achieving a time slot is done using Markov Chain analysis.

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