An Improved Simplex based Particle Swarm Optimization for Environmentally Constrained Economic Dispatch Problem in Thermal Power Plants

2020 ◽  
pp. 1-17
Author(s):  
Namarta Chopra ◽  
Yadwinder Singh Brar ◽  
Jaspreet Singh Dhillon
Keyword(s):  
Particle Swarm Optimization ◽  
Power Plants ◽  
Thermal Power ◽  
Economic Dispatch ◽  
Particle Swarm ◽  
Thermal Power Plants ◽  
Swarm Optimization ◽  
Economic Dispatch Problem

scholarly journals Nonconvex Economic Dispatch Using Particle Swarm Optimization with Time Varying Operators

2014 ◽  
Vol 2014 ◽  
pp. 1-13 ◽  
Author(s):  
Vinay Kumar Jadoun ◽  
Nikhil Gupta ◽  
K. R. Niazi ◽  
Anil Swarnkar
Keyword(s):  
Particle Swarm Optimization ◽  
Power Plants ◽  
Optimization Problems ◽  
Thermal Power ◽  
Economic Dispatch ◽  
Particle Swarm ◽  
Substantial Improvement ◽  
Standard Test ◽  
Swarm Optimization ◽  
Control Equation

This paper presents a particle swarm optimization (PSO) to solve hard combinatorial constrained optimization problems such as nonconvex and discontinuous economic dispatch (ED) problem of large thermal power plants. Several measures have been suggested in the control equation of the classical PSO by modifying its operators for better exploration and exploitation. The inertia operator of the PSO is modulated by introducing a new truncated sinusoidal function. The cognitive and social behaviors are dynamically controlled by suggesting new exponential constriction functions. The overall methodology effectively regulates the velocity of particles during their flight and results in substantial improvement in the classical PSO. The effectiveness of the proposed method has been tested for economic load dispatch of three standard test systems considering various operational constraints like valve-point loading effect, prohibited operating zones (POZs), network power loss, and so forth. The application results show that the proposed PSO method is very promising.

scholarly journals Optimal short-term hydro-thermal scheduling using multi-function global particle swarm optimization

2020 ◽  
Vol 20 (1) ◽  
pp. 537
Author(s):  
Surender Reddy Salkuti
Keyword(s):  
Power Generation ◽  
Particle Swarm Optimization ◽  
Power Plants ◽  
Thermal Power ◽  
Particle Swarm ◽  
Test System ◽  
Thermal Power Plants ◽  
Fuel Cost ◽  
Short Term ◽  
Swarm Optimization

<p>An optimal short-term hydro-thermal scheduling (ST-HTS) problem is solved in this paper using the multi-function global particle swarm optimization (MF-GPSO). A multi-reservoir cascaded hydro-electric system with a non-linear relationship between water discharge rate, power generation and net head is considered in this paper. The ST-HTS problem determines the optimal power generation of hydro and thermal generators which is aimed to minimize total fuel cost of thermal power plants during a determined time period. Effects of valve point loading and prohibited operating zones in the fuel cost function of the thermal power plants is examined. Power balance, reservoir volume, water balance and operation constraints of hydro and thermal plants are considered. The effectiveness and feasibility of MF-GPSO algorithm is examined on a standard test system, and the simulation results are compared with other algorithms presented in the literature. The results show that the MF-GPSO algorithm appears to be the best in terms of convergence speed and optimal cost compared with other techniques reported in the literature.</p>

scholarly journals Perbandingan Metode Gaussian Particle Swarm Optimization (GPSO) dan Lagrange Multiplier pada Masalah Economic Dispatch

2012 ◽  
Vol 3 (1) ◽  
pp. 228
Author(s):  
Siti Komsiyah
Keyword(s):  
Particle Swarm Optimization ◽  
Electric Power ◽  
Lagrange Multiplier ◽  
Economic Dispatch ◽  
Particle Swarm ◽  
Economic Planning ◽  
Electric Power System ◽  
Planning Problem ◽  
Swarm Optimization ◽  
Economic Dispatch Problem

On electric power system operation, economic planning problem is one variable to take into account due to operational cost efficiency. Economic Dispatch problem of electric power generation is discussed in this study to manage the output division on several units based on the the required load demand, with minimum operating cost yet is able to satisfy equality and inequality constraint of all units and system. In this study the Economic Dispatch problem which has non linear cost function is solved using swarm intelligent method is Gaussian Particle Swarm Optimization (GPSO) and Lagrange Multiplier. GPSO is a population-based stochastic algorithms which their moving is inspired by swarm intelligent and probabilities theories. To analize its accuracy, the Economic Dispatch solution by GPSO method is compared with Lagrange Multiplier method. From the test result it is proved that GPSO method gives economic planning calculation better than Lagrange Multiplier does.

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