scholarly journals Maximum Penetration of Distributed Generations and Improvement of Technical Indicators in Distribution Systems

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Thuan Thanh Nguyen ◽  
Thang Trung Nguyen ◽  
Ngoc Au Nguyen
Keyword(s):  
Distribution System ◽  
Distribution Systems ◽  
Search Algorithm ◽  
Optimal Solution ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Placement Problem ◽  
Distributed Generations ◽  
Technical Indicators ◽  
Power Loss Reduction

Increasing the possible capacity of distributed generations (DGs) supplying to distribution system (DS) is a highly effective solution to attract the investment of distributed generation (DG) installation in the DS. However, the presence of DGs will affect the technical indicators of the DS. This paper determines solutions of the DG placement problem for maximizing the size of distributed generations (DGs) and improving the technical indicators consisting of power loss reduction, increasing of balance among feeders and balance among branches, and voltage deviation reduction. A max-min method is proposed to combine the membership objective functions. The location and size of DGs are optimized based on an improved cuckoo search algorithm (ICSA). The simulation results for the 84-node system show that the proposed multiobjective problem not only helps to increase the capacity of DGs but also improves the technical factors. Moreover, the DG’s uncertainty is also validated to show its negative impacts on the technical indicators of the DS. Furthermore, ICSA is worthy for finding the optimal solution for the DG placement problem.

scholarly journals Optimization of location and size of distributed generations for maximizing their capacity and minimizing power loss of distribution system based on cuckoo search algorithm

2021 ◽  
Vol 10 (4) ◽  
pp. 1769-1776
Author(s):  
Thuan Thanh Nguyen ◽  
Trieu Ton Ngoc ◽  
Thang Trung Nguyen ◽  
Thanh-Phuc Nguyen ◽  
Ngoc Au Nguyen
Keyword(s):  
Distribution System ◽  
Power Loss ◽  
Search Algorithm ◽  
Distribution Network ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Power Losses ◽  
Distributed Generations ◽  
Test Systems ◽  
Reliable Methods

Maximizing capacity of distributed generations (DGs) embed into distribution network is a solution to attract investment for DGs installation on the distribution system. This paper introduces a approach of optimizing location and capacity of DGs for maximizing DGs capacity and minimizing the system’s power loss based on cuckoo search algorithm (CSA). The proposed problem and method are simulated on two test systems including the 33-node and 69-node networks. The numerical results have demonstrated that the proposed method not only reduces power losses but also maximizes the power of DGs embed into the distribution network. The results also introduce that the proposed CSA method is better performance that some previous methods in terms of power loss and DGs capacity. The results obtained in many independent runs for two test systems indicate that CSA in one of the reliable methods for the DGs placement problems.

scholarly journals Power Loss Reduction using Instantaneous Network Reconfiguration and DG Placement with Cuckoo Search Algorithm in Distribution System

2020 ◽  
Vol 8 (6) ◽  
pp. 2393-2398
Keyword(s):  
Radial Distribution ◽  
Distribution System ◽  
Power Loss ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Network Reconfiguration ◽  
Radial Distribution System ◽  
Distributed Generator ◽  
Power Loss Reduction

The aim of reducing power loss, enhancing profile of voltage in a radial distribution system at which consumers are connected and also determining the ratings of power, optimal placement of Distributed generator. In this paper to resolve the drop in voltage profile by using network reconfiguration that gives possible switching possibilities with an efficient Cuckoo Search Algorithm (CSA) is discussed and Sensitivity analysis are carried out simultaneously for finding sizing and possible location of distributed generation. To confirm the usefulness of the discussed method it was conducted on radial distribution system of 33 bus connected by various load levels, the result shows that the discussed method is fast and efficient. However to meet power requirement and lack of transmission capabilities importance for DG is rapidly evolving in electrical systems. For reliability and stability for the power system best possible location of Distributed Generator is needed in distribution system. To overcome the shortcomings of mathematical optimization practices, soft computing algorithms have been actively introduced during the last decade.

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.

scholarly journals Simultaneous Placement and Sizing of Distributed Generation Units and Shunt Capacitors on Radial Distribution Systems Using Cuckoo Search Algorithm

2021 ◽  
pp. 43-58
Author(s):  
Sunday Adeleke Salimon ◽  
Gafari Abiola Adepoju ◽  
Isaiah Gbadegesin Adebayo ◽  
Oluwadamilare Bode Adewuyi ◽  
Saheed Oluwasina Amuda
Keyword(s):  
Radial Distribution ◽  
Distribution Systems ◽  
Reactive Power ◽  
Search Algorithm ◽  
Stability Index ◽  
Cuckoo Search ◽  
Optimal Placement ◽  
Power Loss Reduction ◽  
Operational Test ◽  
Shunt Capacitors

This paper presents a Cuckoo Search (CS) algorithm-based methodology for simultaneous optimal placement and sizing of Shunt Capacitors (SCs) and Distributed Generations (DGs) together in radial distribution systems. The objectives of the work are to minimize the real power and reactive power losses while maximizing the voltage stability index of the distribution network subjected to equality and inequality constraints. Different operational test cases are considered namely installation of SCs only, DGs only, SCs before DGs, DGs before SCs, and SCs and DGs at one time. The proposed method has been demonstrated on standard IEEE 33-bus and a practical Ayepe 34-bus radial distribution test systems. The highest percentage power loss reduction of 94.4% and other substantial benefits are obtained when SCs and DGs are optimally installed simultaneously. Simulated results obtained from the proposed technique are compared with other well-known optimization algorithms and found to be more effective.

scholarly journals Simultaneous Allocation Renewable DGs and Capacitor for Typical Indian Rural Distribution Network using Cuckoo Search Algorithm

2018 ◽  
Vol 7 (3.12) ◽  
pp. 1011
Author(s):  
Balamurugan P ◽  
T Yuvaraj ◽  
Muthukannan P
Keyword(s):  
Search Algorithm ◽  
Cuckoo Search ◽  
Distribution Networks ◽  
Cuckoo Search Algorithm ◽  
System Stability ◽  
Quality Enhancement ◽  
Distributed Generations ◽  
Environmental Threats ◽  
Shunt Capacitors ◽  
Power Factor Improvement

Nowadays, simultaneous allocation of renewable distributed generations (REDGs) along with shunt capacitors (SCs) in RDS distribution networks is getting more attention by the researchers. Since it mitigates the system losses, enhance the bus voltages, power factor improvement, power quality enhancement and reduces the environmental threats. In the proposed work an advanced approach is implemented for simultaneous allocation REDGs and SC for Indian 28- rural bus network. For decrease the losses and maximize the system stability  is the  main objective of thispaper. The locations and sizing of theses REDGs and SCs have been determined with help of cuckoo search algorithm (CSA).  

scholarly journals Fuzzy optimization based Water Distribution Network design using Self-Adaptive Cuckoo Search Algorithm

2021 ◽  
Author(s):  
A. Vasan ◽  
K. Srinivasa Raju ◽  
B. Sriman Pankaj
Keyword(s):  
Membership Function ◽  
Water Distribution ◽  
Search Algorithm ◽  
Fuzzy Optimization ◽  
Optimal Solution ◽  
Water Distribution Network ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Pareto Optimal Solutions ◽  
Optimal Solutions

Abstract Water Distribution Network(s) (WDN) design is gaining prominence in the urban planning context. Several factors that play a significant role in design are uncertainty in data, non-linear relation of head loss & discharge, combinatorial nature of the problem, and high computational requirements. In addition, many conflicting objectives are possible and required for effective WDN design, such as cost, resilience, and leakage. Most of the research work published has used multiobjective evolutionary optimization in solving such complex WDN. However, the challenge of such population based evolutionary approaches is that they provide multiple trade-off Pareto optimal solutions to the decision-maker who will have to choose another set of techniques to arrive at a single optimal solution. The present study employs a fuzzy optimization approach that would provide a single optimal WDN design for Hanoi and Pamapur, India. Maximization of network resilience (NR) and minimization of network cost (NC) are employed in a multiobjective context. Later, minimization of network leakages (NL) is also incorporated, leading to three objective problems. Hyperbolic Membership Function (HMF), Exponential Membership Function (EMF), and Non-linear Membership Function (NMF) are employed in Self-Adaptive Cuckoo Search Algorithm based fuzzy optimization. HMF is found suitable to determine the best possible WDN design for chosen case studies based on the highest degree of satisfaction. HIGHLIGHT Most of the research conducted till now have used evolutionary multiobjective optimization in solving WDNs. But, the challenge of such evolutionary approaches is that they provide multiple trade-off pareto optimal solutions to the decision maker who will have to further choose another methodology to converge to a single optimal solution. The proposed methodology would simplify the decision-making process for an engineer.

scholarly journals Optimization Strategy of Wireless Charger Node Deployment Based on Improved Cuckoo Search Algorithm

2020 ◽  
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

Abstract In 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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