S084023 Optimization of the Dispersed Power Supply in a Energy Network system by the Genetic Algorithm

2013 ◽  
Vol 2013 (0) ◽  
pp. _S084023-1-_S084023-4
Author(s):  
Riku MACHEDA ◽  
Yudai YAMASAKI ◽  
Shigehiko KANEKO
Keyword(s):  
Genetic Algorithm ◽  
Power Supply ◽  
Network System ◽  
Energy Network

scholarly journals Structural Combinatorial of Network Information System of Systems based on Evolutionary Optimization Method.pdf

2020 ◽  
Author(s):  
Tingting Zhang ◽  
Yushi Lan ◽  
Aiguo Song ◽  
Kun Liu ◽  
Nan Wang
Keyword(s):  
Genetic Algorithm ◽  
Information System ◽  
System Of Systems ◽  
Information Architecture ◽  
Information Network ◽  
Network System ◽  
System Construction ◽  
Network Information ◽  
Evolution Characteristics ◽  
Evolutionary Simulation

<p>The network information system is a military information network system with evolution characteristics. Evolution is a process of replacement between disorder and order, chaos and equilibrium. Given that the concept of evolution originates from biological systems, in this article, the evolution of network information architecture is analyzed by genetic algorithms, and the network information architecture is represented by chromosomes. Besides, the genetic algorithm is also applied to find the optimal chromosome in the architecture space. The evolutionary simulation is used to predict the optimal scheme of the network information architecture and provide a reference for system construction.</p><br>

scholarly journals DECENTRALIZE ENERGY NETWORK SYSTEM(DEN) IN ASSIMILATION WITH BLOCKCHAIN

2020 ◽  
Vol Special (Issue3) ◽  
pp. 100-107
Author(s):  
Shafali Dhall ◽  
Chetanya Ved ◽  
Saransh Khetarpaul ◽  
Sanjana Deswal ◽  
Anmol Dhingra
Keyword(s):  
Network System ◽  
Energy Network

scholarly journals Economic Load Dispatch using Lambda Iteration, Particle Swarm Optimization & Genetic Algorithm

2021 ◽  
Vol 9 (8) ◽  
pp. 972-977
Author(s):  
Zaineb Nisar Jan
Keyword(s):  
Genetic Algorithm ◽  
Power Supply ◽  
Optimization Technique ◽  
Particle Swarm ◽  
Economic Load Dispatch ◽  
Swarm Optimization ◽  
Load Demand ◽  
Reduced Costs ◽  
Reliable Power Supply ◽  
Fuel Costs

Abstract: In economic load dispatch problem scheduling of loads is done in order to achieve reliable power supply with reduced costs. With the increase in load demand with each passing year energy crisis is increasing hence an area of study where fuel costs can be reduced was proposed. This can be achieved using various methods among which the methods discussed in this paper are Lambda Iteration, Particle Swarm Operation and Genetic Algorithm. Based on numerical results the best optimization technique can be figured out among the discussed methods. Keywords: Lambda Iteration, PSO, GA, economic load dispatch, optimization solutions

Operating Schedule of a Combined Energy Network System

2014 ◽  
pp. 1-37
Keyword(s):  
Fuel Cell ◽  
Energy System ◽  
Network System ◽  
Operation Planning ◽  
Cell Network ◽  
Operating Schedule ◽  
Operation Pattern ◽  
Cell Capacity ◽  
Load Leveling ◽  
Energy Network

This chapter consists of two sections, ‘Operating Schedule of a Combined Energy Network System with Fuel Cell’ and ‘Fuel Cell Network System Considering Reduction in Fuel Cell Capacity Using Load Leveling and Heat Release Loss’. The chromosome model showing system operation pattern is applied to GA (genetic algorithm), and the method of optimization operation planning of energy system is developed in the 1st section. In the case study, the operation planning was performed for the energy system using the energy demand pattern of the individual residence of Sapporo, Japan. Reduction in fuel cell capacity linked to a fuel cell network system is considered in the 2nd section. Such an energy network is analyzed assuming connection of individual houses, a hospital, a hotel, a convenience store, an office building, and a factory.

A Concept of Energy Network Combined With Distributed Power Generation and Internet Systems

2002 ◽  
Author(s):  
Yoichi Tone ◽  
Kunihiko Mouri
Keyword(s):  
Power Generation ◽  
Energy Density ◽  
High Energy ◽  
High Energy Density ◽  
The Internet ◽  
Network System ◽  
Distributed Power ◽  
Distributed Power Generation ◽  
Business Application ◽  
Energy Network

For the near future business application, the new idea of the distributed energy network system is proposed to secure lower cost and highly reliable power and heat supply system for the limited local area such as high energy density urban area. In Japan, tariff of the electric power is same for urban consumers and rural consumers under the present power law. However the wave of the power deregulation may affect to small business users and home users and the free-market of power purchase may emerge in public domain. Towards the realization of the future active power market, the new idea is created to promote the intelligent distributed power generation systems and heat utilization systems using the Internet application and local energy network construction. This system has been discussed in the consortium, consisting of Nagoya University, Gas Company, Power utility, Trade Company, IT Company etc since May 2000. The idea of the proposed eL-power network system is to supply necessary power and heat to the only customers in the high energy density area like near the railway station using energy management by mean of the Internet technologies.

scholarly journals Optimal multi-objective distributed generation location and capacity by elite strategy genetic algorithm considering timing characteristics

2020 ◽  
Vol 185 ◽  
pp. 01018
Author(s):  
Xinquan Wei ◽  
Xiangjun Duan ◽  
Lei Chen ◽  
Weiyan Zheng
Keyword(s):  
Genetic Algorithm ◽  
Distributed Generation ◽  
Power Supply ◽  
Retention Mechanism ◽  
Improved Genetic Algorithm ◽  
Distributed Power ◽  
Elite Strategy ◽  
Voltage Quality ◽  
Voltage Deviation ◽  
Node Voltage

In this paper, a distributed generation location and capacity optimization model considering the probability of scenario occurrence is established. The optimization objective is to minimize the total cost of investment, annual power loss of distribution network and node voltage deviation. The improved genetic algorithm with elitist retention mechanism is used to solve the model. The IEEE33 system is used to show the location and constant capacity of the distributed power supply under different conditions. It shows that the reasonable and optimized configuration of the distributed power supply can obtain better voltage quality and minimize the cost function, which verifies the effectiveness of the proposed model.

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