A Multi-objective PSO (MOPSO) algorithm for optimal active power dispatch with pollution control

Sen, Govind; Sharma, Jitendra; Goyal, Govind Rai; Singh, Alok

doi:10.18280/mmep.040301

Cited by 19 publications

(15 citation statements)

References 7 publications

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“…Objectives of combined economic emission dispatch (CEED) problem and their constraints are formulated mathematically by nonlinear functions as given in [21]:…”

Section: Problem Formulationmentioning

confidence: 99%

Solution of Combined Economic Emission Dispatch with Demand Side Management Using Meta-heuristic Algorithms

Goyal¹,

Vadhera²

2019

JESA

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This paper deals with application of meta-heuristic algorithms to resolve the problem of combined economic emission dispatch (CEED) with peak load management for a mediumsized power system in an efficient manner. The objective is to optimize the fuel cost of generation simultaneously minimizing the environmental pollution caused by fossil fuel based power generating units working at their peak limits. In this paper combined problem of minimizing fuel cost and emission of flue gases (NOx, CO2, SO2), is solved using Cuckoo search (CS) and Grasshopper optimization algorithm (GOA) via composite function of all four objectives with help of weight ratios and price penalty factors. Demand Side Management (DSM) measure is also applied at least expensive areas to manage the peak load condition at generating units. The problem is implemented on IEEE 30-bus system with 6 generator units. The simulation results of the CS algorithm for CEED with and without DSM have been compared with the results of GOA algorithm. The compound results obtained by CS algorithm for the problem of CEED with DSM validated its potential.

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“…Objectives of combined economic emission dispatch (CEED) problem and their constraints are formulated mathematically by nonlinear functions as given in [21]:…”

Section: Problem Formulationmentioning

confidence: 99%

Solution of Combined Economic Emission Dispatch with Demand Side Management Using Meta-heuristic Algorithms

Goyal¹,

Vadhera²

2019

JESA

Self Cite

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“…There are many literatures [8][9][10][11][12][13][14] extensive research is carried out on the application of FR for and Optimal Capacitor Placement (OCP) in distribution system for minimizing power loss, maximize voltage stability and improve voltage profile. To solve multi-objective optimization problems the algorithms like MOPSO algorithm for power dispatch, machine learning algorithm based static VAR compensator to enhance voltage stability, partitioning differential transform method for solving nonlinear integrodifferential equations and integration of DG system with PV module to grid with modelling are reported [15][16][17][18]. Effective methodologies are proposed to incorporate FR and OCP in distribution network under deregulated environment.…”

Section: Introductionmentioning

confidence: 99%

Impact of Distribution Network Reconfiguration and Optimal Capacitor Placement under Wheeling Transactions

Sreedhar¹,

Ramana²

2020

MMEP

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Distribution Network reconfiguration (DNR) and Optimal Capacitor Placement (OCP) are well known techniques to reduce power loss and maintain stable voltage levels in Distribution network. Minimization of power loss has immense effect on cost, quality and reliability of supply. Following the present trends of power trading methods, this paper explores the necessity of reconfiguration of the network and Optimal Capacitor Placement under wheeling transaction, incorporating market dispatching considerations. Wheeling transactions will add additional loss which is taken into consideration while modelling. Distribution System Operator (DSO) plays responsible role and knows how to reconfigure the network for the optimal operation of the entire system. DSO optimizes the objective function (minimization of power loss) by satisfying constraints of all the participants that includes technical as well as commercial. By its nature, DNR or Feeder Reconfiguration (FR) and OCP are a complex multi constrained optimization problem. The chosen optimization algorithm should improve the effective operation of DSO. Differential Search Algorithm (DSA) is adapted to solve this optimization problem due to its simple structure and proven faster convergence. The proposed methodology was tested on standard IEEE 33-bus distribution system. Simulation results are presented and compared with existing popular methodologies.

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“…Multi-objective optimization (MO) problems are a large class in optimization [1][2][3][4][5][6][7][8]. Fractional multi-objective optimization (FMO) problems are an important subclass of MO problems, [9][10][11][12][13].…”

Section: Introductionmentioning

confidence: 99%

Pareto optimal solutions for fractional multi-objective optimization problems using MATLAB

Abou-El-Enien¹

2018

AMA_C

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The purpose of this paper is to generate numerical Pareto optimal solutions for fractional multi-objective optimization (FMO) problems based on the Charens -Cooper transformation method and the weighting method using MATLAB ® (R2014a). I introduce a MATLAB ® code and a numerical hybrid algorithm for solving FMO problems. Also, i give an illustrative numerical example to clarify the main results developed in this paper. The hand solution of the numerical example and the solution by the code give the same results. The scientists and the engineers can apply the introduced code and the numerical hybrid algorithm to different practical FMO problems to obtain numerical solutions.

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A Multi-objective PSO (MOPSO) algorithm for optimal active power dispatch with pollution control

Cited by 19 publications

References 7 publications

Solution of Combined Economic Emission Dispatch with Demand Side Management Using Meta-heuristic Algorithms

Solution of Combined Economic Emission Dispatch with Demand Side Management Using Meta-heuristic Algorithms

Impact of Distribution Network Reconfiguration and Optimal Capacitor Placement under Wheeling Transactions

Pareto optimal solutions for fractional multi-objective optimization problems using MATLAB

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