Optimal allocation of TCSC using adaptive cuckoo search algorithm

2016 ◽  
Author(s):  
M. Taleb ◽  
A. Salem ◽  
A. Ayman ◽  
M. A. Azma
Keyword(s):  
Optimal Allocation ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm

scholarly journals A New Approach to Optimal Location and Sizing of DSTATCOM in Radial Distribution Networks Using Bio-Inspired Cuckoo Search Algorithm

Energies ◽  
2020 ◽  
Vol 13 (18) ◽  
pp. 4615 ◽  
Author(s):  
Devabalaji Kaliaperumal Rukmani ◽  
Yuvaraj Thangaraj ◽  
Umashankar Subramaniam ◽  
Sitharthan Ramachandran ◽  
Rajvikram Madurai Elavarasan ◽  
...  
Keyword(s):  
Radial Distribution ◽  
Optimal Allocation ◽  
Search Algorithm ◽  
Clean Energy ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Sensitivity Factor ◽  
Optimal Size ◽  
Total System ◽  
New Approach

This article proposes a new approach based on a bio-inspired Cuckoo Search Algorithm (CSA) that can significantly envisage with several issues for optimal allocation of distribution static compensator (DSTATCOM) in Radial Distribution System (RDS). In the proposed method, optimal locations of the DSTATCOM are calculated by using the Loss Sensitivity Factor (LSF). The optimal size of the DSTATCOM is simulated by using the newly developed CSA. In the proposed method, load flow calculations are performed by using a fast and efficient backward/forward sweep algorithm. Here, the mathematically formed objective function of the proposed method is to reduce the total system power losses. Standard 33-bus and 69-bus systems have been used to show the effectiveness of the proposed CSA-based optimization method in the RDS with different load models. The simulated results confirm that the optimal allocation of DSTATCOM plays a significant role in power loss minimization and enhanced voltage profile. The placement of DSTATCOM in RDS also plan an important role for minimizing uncertainties in the distribution level. The proposed method encourages one to use renewable-based resources, which results in affordable and clean energy.

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.

Sign in / Sign up

Export Citation Format

Share Document