Rescheduling of real power for congestion management using Cuckoo Search Algorithm

2014 ◽  
Author(s):  
Subhasish Deb ◽  
Arup Kumar Goswami
Keyword(s):  
Search Algorithm ◽  
Cuckoo Search ◽  
Congestion Management ◽  
Cuckoo Search Algorithm ◽  
Real Power

scholarly journals Cuckoo Search Algorithm for Congestion Alleviation with Incorporation of Wind Farm

2018 ◽  
Vol 8 (6) ◽  
pp. 4871
Author(s):  
Kaushik Paul ◽  
Niranjan Kumar
Keyword(s):  
Power System ◽  
Wind Farm ◽  
Search Algorithm ◽  
Past Research ◽  
Cuckoo Search ◽  
Congestion Management ◽  
Cuckoo Search Algorithm ◽  
Optimization Techniques ◽  
Management Approach ◽  
Sensitivity Factor

The issue to alleviate congestion in the power system framework has emerged as an alluring field for the power system researchers. The research conducted in this article proposes a cuckoo search algorithm based congestion alleviation strategy with the incorporation of wind farm. The bus sensitivity factor data are computed and utilized to sort out the sutiable position for the installation of the wind farm. The generators contributing in the real power rescheduleing process are selected as per the generator sensitivity values. The cuckoo search algorithm is implemented to minimize the congestion cost with the embodiment of the wind farm.The proposed method is tested on 39 bus New England framework and the results obtained with the cuckoo search based congestion management approach outperforms the results opted with other heuristic optimization techniques in the past research literatures.

scholarly journals Finding Optimal Load Dispatch Solutions by Using a Proposed Cuckoo Search Algorithm

2019 ◽  
Vol 2019 ◽  
pp. 1-29 ◽  
Author(s):  
Thang Trung Nguyen ◽  
Cong-Trang Nguyen ◽  
Le Van Dai ◽  
Nguyen Vu Quynh
Keyword(s):  
Power System ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
System Optimization ◽  
Cuckoo Search Algorithm ◽  
Engineering Problem ◽  
Method Performance ◽  
Real Power ◽  
Power System Optimization ◽  
Optimal Load

Optimal load dispatch (OLD) is an important engineering problem in power system optimization field due to its significance of reducing the amount of electric generation fuel and increasing benefit. In the paper, an improved cuckoo search algorithm (ICSA) is proposed for determining optimal generation of all available thermal generation units so that all constraints consisting of prohibited power zone (PPZ), real power balance (RPB), power generation limitations (PGL), ramp rate limits (RRL), and real power reserve (RPR) are completely satisfied. The proposed ICSA method performance is more robust than conventional Cuckoo search algorithm (CCSA) by applying new modifications. Compared to CCSA, the proposed ICSA approach can obtain high quality solutions and speed up the solution search ability. The ICSA robustness is verified on different systems with diversification of objective functions as well as the considered constraint set. The results from the proposed ICSA method are compared to other algorithms for comparison. The result comparison analysis indicates that the proposed ICSA approach is more robust than CCSA and other existing optimization approaches in finding solutions with significant quality and shortening simulation time. Consequently, it should lead to a conclusion that the proposed ICSA approach deserves to be applied for finding solutions of OLD problem in power system optimization field.

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.

Sign in / Sign up

Export Citation Format

Share Document