Optimum Load Dispatching Model in Intelligent Distribution Network

2014 ◽  
Vol 915-916 ◽  
pp. 1433-1437
Author(s):  
Xiu Ge Zhang ◽  
Ye Ren ◽  
Xun Cheng Huang
Keyword(s):  
Optimization Problem ◽  
Distribution Network ◽  
Integrated System ◽  
Parallel Genetic Algorithm ◽  
Dynamic Constraints ◽  
Optimum Load ◽  
Pollution Emission ◽  
Constraints Handling ◽  
Strength Pareto Evolutionary Algorithm ◽  
Intelligent Distribution

The increase of the intensive power proportion in distribution network brings new challenges to load dispatch of power plant, and intelligent distribution would be a key issue in the future power integrated system. The paper combined the strength Pareto evolutionary algorithm with the parallel genetic algorithm (PGA) ,namely the Pseudo-parallel SPEA2 Algorithm for solving the dynamic economic load dispatch problem. This problem is formulated as a nonlinear constrained multi-objective optimization problem, meanwhile, synthetically considers dynamic constraints handling, the minimum of fuel cost and the pollution emission. Besides, the paper analyzed the feasibility and validity of this algorithm in the load dispatch of power system.

Task-based torque minimization of a 3-PṞR spherical parallel manipulator

Robotica ◽  
2021 ◽  
pp. 1-30
Author(s):  
Soheil Zarkandi
Keyword(s):  
Closed Form ◽  
Dynamic Modeling ◽  
Dynamic Equation ◽  
Parallel Manipulator ◽  
Optimization Problem ◽  
Dynamic Constraints ◽  
Part C ◽  
Euler Approach ◽  
Three Degree Of Freedom ◽  
Spherical Parallel Manipulator

Abstract A comprehensive dynamic modeling and actuator torque minimization of a new symmetrical three-degree-of-freedom (3-DOF) 3-PṞR spherical parallel manipulator (SPM) is presented. Three actuating systems, each of which composed of an electromotor, a gearbox and a double Rzeppa-type driveshaft, produce input torques of the manipulator. Kinematics of the 3-PṞR SPM was recently studied by the author (Zarkandi, Proc. Inst. Mech. Eng. Part C J. Mech. Eng. Sci. 2020, https://doi.org/10.1177%2F0954406220938806). In this paper, a closed-form dynamic equation of the manipulator is derived with the Newton–Euler approach. Then, an optimization problem with kinematic and dynamic constraints is presented to minimize torques of the actuators for implementing a given task. The results are also verified by the SimMechanics model of the manipulator.

scholarly journals Application of FA in intelligent distribution network

2021 ◽  
Vol 631 ◽  
pp. 012122
Author(s):  
Lingkai Zhu ◽  
Qian Wang ◽  
Weishuai Wang ◽  
Haijing Zhang
Keyword(s):  
Distribution Network ◽  
Intelligent Distribution

Intelligent distribution network in the new situation

2016 ◽  
Author(s):  
Xuesong Zhou ◽  
Mingpeng Sun ◽  
Youjie Ma ◽  
Zhiqiang Gao ◽  
Yanjuan Wu ◽  
...  
Keyword(s):  
Distribution Network ◽  
New Situation ◽  
Intelligent Distribution

Reactive Power Optimization with Chaotic Firefly Algorithm and Particle Swarm Optimization in A Distribution Subsystem Network

2016 ◽  
Vol 12 (1) ◽  
pp. 71-78
Author(s):  
Hamza Yapıcı ◽  
Nurettin Çetinkaya
Keyword(s):  
Particle Swarm Optimization ◽  
Firefly Algorithm ◽  
Optimization Problem ◽  
Reactive Power ◽  
Power Optimization ◽  
Distribution Network ◽  
Reactive Power Optimization ◽  
Power Losses ◽  
Swarm Optimization ◽  
Real Distribution

In this paper the minimization of power losses in a real distribution network have been described by solving reactive power optimization problem. The optimization has been performed and tested on Konya Eregli Distribution Network in Turkey, a section of Turkish electric distribution network managed by MEDAŞ (Meram Electricity Distribution Corporation). The network contains about 9 feeders, 1323 buses (including 0.4 kV, 15.8 kV and 31.5 kV buses) and 1311 transformers. This paper prefers a new Chaotic Firefly Algorithm (CFA) and Particle Swarm Optimization (PSO) for the power loss minimization in a real distribution network. The reactive power optimization problem is concluded with minimum active power losses by the optimal value of reactive power. The formulation contains detailed constraints including voltage limits and capacitor boundary. The simulation has been carried out with real data and results have been compared with Simulated Annealing (SA), standard Genetic Algorithm (SGA) and standard Firefly Algorithm (FA). The proposed method has been found the better results than the other algorithms.

Cooperative Task Assignment and Trajectory Planning of Unmanned Systems Via HFLC and PSO

2019 ◽  
Vol 07 (02) ◽  
pp. 65-81 ◽  
Author(s):  
Ahmed T. Hafez ◽  
Mohamed A. Kamel
Keyword(s):  
Trajectory Planning ◽  
Optimization Problem ◽  
Fuzzy Logic Controller ◽  
Hybrid Approach ◽  
Task Assignment ◽  
Time Discretization ◽  
Planning Problem ◽  
Dynamic Constraints ◽  
Ground Station ◽  
Novel Approach

This paper investigates the problems of cooperative task assignment and trajectory planning for teams of cooperative unmanned aerial vehicles (UAVs). A novel approach of hierarchical fuzzy logic controller (HFLC) and particle swarm optimization (PSO) is proposed. Initially, teams of UAVs are moving in a pre-defined formation covering a specified area. When one or more targets are detected, the teams send a package of information to the ground station (GS) including the target’s degree of threat, degree of importance, and the separating distance between each team and each detected target. Based on the gathered information, the ground station assigns the teams to the targets. HFLC is implemented in the GS to solve the assignment problem ensuring that each team is assigned to a unique target. Next, each team plans its own path by formulating the path planning problem as an optimization problem. The objective in this case is to minimize the time to reach their destination considering the UAVs dynamic constraints and collision avoidance between teams. A hybrid approach of control parametrization and time discretization (CPTD) and PSO is proposed to solve this optimization problem. Finally, numerical simulations demonstrate the effectiveness of the proposed algorithm.

A New Method for Simultaneous Optimization of a Structure With Active and Passive Control Variables

2015 ◽  
Author(s):  
Ui-Jin Jung ◽  
Gyung-Jin Park
Keyword(s):  
Control Systems ◽  
Large Scale ◽  
Optimization Problem ◽  
Integrated System ◽  
Static Loads ◽  
Design Variables ◽  
Response Optimization ◽  
The Time Domain ◽  
Control Forces ◽  
And Control

An optimization method is proposed for the simultaneous design of structural and control systems using the equivalent static loads. The two structural and control systems are not completely independent and need to be considered in a unified fashion. Furthermore, an integrated system design is unavoidable to exhibit a good performance in the time domain. The analysis for the integrated system is conducted for the transient-state in a dynamic manner. The constraints for the structural and control systems are defined in the time domain as well. Therefore, a physically small scale problem in structural analysis easily becomes quite a large scale in an optimization problem. A new equivalent static loads (ESLs) method, which deals with the structural design variables as well as the control design variables, is proposed to solve physically large scale problems. A finite element dynamic equation is defined with control forces and a dynamic response optimization problem is formulated. Linear static response optimization is carried out with the ESLs. The control forces for the linear static response optimization are considered as design variables. Shape variables are utilized to handle the design variables for the control forces. Several examples are solved to validate the proposed method.

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