A Novel MPPT Method Based on Cuckoo Search Algorithm and Golden Section Search Algorithm for Partially Shaded PV System

2018 ◽  
Author(s):  
Dimas Aji Nugraha ◽  
Kuo-Lung Lian ◽  
Suwarno
Keyword(s):  
Search Algorithm ◽  
Golden Section ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Pv System ◽  
Golden Section Search

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 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 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

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.

scholarly journals Optimization strategy of wireless charger node deployment based on improved cuckoo search algorithm

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Yang Wang ◽  
Feifan Wang ◽  
Yujun Zhu ◽  
Yiyang Liu ◽  
Chuanxin Zhao
Keyword(s):  
Sensor Network ◽  
Sensor Node ◽  
Search Algorithm ◽  
Optimal Solution ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Sensor Nodes ◽  
Optimization Strategy ◽  
Multi Objective ◽  
Received Power

AbstractIn wireless rechargeable sensor network, the deployment of charger node directly affects the overall charging utility of sensor network. Aiming at this problem, this paper abstracts the charger deployment problem as a multi-objective optimization problem that maximizes the received power of sensor nodes and minimizes the number of charger nodes. First, a network model that maximizes the sensor node received power and minimizes the number of charger nodes is constructed. Second, an improved cuckoo search (ICS) algorithm is proposed. This algorithm is based on the traditional cuckoo search algorithm (CS) to redefine its step factor, and then use the mutation factor to change the nesting position of the host bird to update the bird’s nest position, and then use ICS to find the ones that maximize the received power of the sensor node and minimize the number of charger nodes optimal solution. Compared with the traditional cuckoo search algorithm and multi-objective particle swarm optimization algorithm, the simulation results show that the algorithm can effectively increase the receiving power of sensor nodes, reduce the number of charger nodes and find the optimal solution to meet the conditions, so as to maximize the network charging utility.

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