NDLI: A new multiobjective evolutionary algorithm for environmental/economic power dispatch

Content Provider	IEEE Xplore Digital Library
Author	Abido, A.A.
Copyright Year	2001
Description	Author affiliation: Dept. of Electr. Eng., King Fahd Univ. of Pet. & Miner., Dhahran, Saudi Arabia (Abido, A.A.)
Abstract	In this paper, a new multiobjective evolutionary algorithm for environmental/economic power dispatch (EED) optimization problem is presented. The EED problem is formulated as a nonlinear constrained multiobjective optimization problem with both equality and inequality constraints. A new nondominated sorting genetic algorithm (NSGA) based approach is proposed to handle the problem as a true multiobjective optimization problem with competing and noncommensurable objectives. The proposed approach employs a diversity-preserving technique to overcome the premature convergence and search bias problems and produce a well-distributed Pareto-optimal set of nondominated solutions. A hierarchical clustering technique is also imposed to provide the decision maker with a representative and manageable Pareto-optimal set. Several optimization runs of the proposed approach are carried out on a standard IEEE test system. The results demonstrate the capabilities of the proposed NSGA based approach to generate the true Pareto-optimal set of nondominated solutions of the multiobjective EED problem in one single run. Simulation results with the proposed approach have been compared to those reported in the literature. The comparison shows the superiority of the proposed NSGA based approach and confirms its potential to solve the multiobjective EED problem.
Sponsorship	Power Eng. Soc.
Starting Page	1263
Ending Page	1268
File Size	702939
Page Count	6
File Format	PDF
ISBN	0780371739
DOI	10.1109/PESS.2001.970254
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2001-07-15
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Evolutionary computation Power generation economics Environmental economics Fuel economy Costs Power system economics Power generation Optimization methods Constraint optimization Thermal pollution
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Environmental/economic power dispatch using multiobjective evolutionary algorithms

Environmental/economic dispatch of thermal units using an elitist multiobjective evolutionary algorithm

Elitist multiobjective evolutionary algorithm for environmental/economic dispatch

Multiobjective particle swarm for environmental/economic dispatch problem

Epsilon-dominance based multiobjective genetic algorithm for economic emission load dispatch optimization problem

Environmental/economic power dispatch using multiobjective evolutionary algorithms

A novel multi-objective genetic algorithm for economic power dispatch

Emission-Economic Dispatch using a Novel Constraint Handling Particle Swarm Optimization Strategy

Multiobjective Bees Algorithm with clustering technique for environmental/economic dispatch

A new multiobjective evolutionary algorithm for environmental/economic power dispatch

Similar Documents

Environmental/economic power dispatch using multiobjective evolutionary algorithms

Environmental/economic dispatch of thermal units using an elitist multiobjective evolutionary algorithm

Elitist multiobjective evolutionary algorithm for environmental/economic dispatch

Multiobjective particle swarm for environmental/economic dispatch problem

Epsilon-dominance based multiobjective genetic algorithm for economic emission load dispatch optimization problem

Environmental/economic power dispatch using multiobjective evolutionary algorithms

A novel multi-objective genetic algorithm for economic power dispatch

Emission-Economic Dispatch using a Novel Constraint Handling Particle Swarm Optimization Strategy

Multiobjective Bees Algorithm with clustering technique for environmental/economic dispatch

A new multiobjective evolutionary algorithm for environmental/economic power dispatch