NDLI: Function Optimization by Reinforcement Learning for power system dispatch and voltage stability

Content Provider	IEEE Xplore Digital Library
Author	Wu, Q.H. Liao, H.L.
Copyright Year	2010
Description	Author affiliation: Department of Electrical Engineering and Electronics, University of Liverpool, L69 3GJ, U.K. (Wu, Q.H.; Liao, H.L.)
Abstract	This paper presents a new algorithm, Function Optimisation by Reinforcement Learning (FORL), to solve large-scale and complex function optimisation problems, in particular for those in a high-dimensional space. FORL undertakes the dimensional search in sequence, in contrast to evolutionary algorithms (EAs) which are based on the population-based search, and has the ability of memory of history incorporated via estimating and updating of the values of states that have been visited, which is different from EAs that aggregate the individuals of a population towards the best selected in a current population. FORL is applied to solve the optimal power system dispatch and voltage stability problem. Simulation studies are carried out on the standard IEEE 30-bus and 57-bus power systems respectively. Advantages of FORL have been demonstrated by comparing its performance with that of Particle Swarm Optimization (PSO) and Genetic Algorithm (GA). The results have shown that FORL outperforms PSO and GA by reducing the fuel cost while enhancing the voltage stability of the power system significantly.
Starting Page	1
Ending Page	8
File Size	535453
Page Count	8
File Format	PDF
ISBN	9781424465491
ISSN	19449925
e-ISBN	9781424465514
e-ISBN	9781424483570
DOI	10.1109/PES.2010.5589845
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-07-25
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Optimization Generators Power system stability Fuels Reactive power Learning reinforcement learning Power dispatch voltage stability
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

Multi-objective optimization by reinforcement learning for power system dispatch and voltage stability

Reactive power dispatch using Big Bang-Big Crunch optimization algorithm for voltage stability enhancement

Reactive power optimization using GSA

A hybrid method for voltage stability constrained optimal reactive power dispatch

MVAr management on the pre-dispatch problem for improving voltage stability margin

Optimal reactive power dispatch using particle swarm optimization in deregulated environment

Voltage stability and economical optimization of reactive power in power systems with wind generators by harmony search method

Optimal reactive power dispatch by pseudo-gradient guided particle swarm optimization

Reactive power rescheduling with generator ranking for voltage stability improvement

Function Optimization by Reinforcement Learning for power system dispatch and voltage stability

Similar Documents

Multi-objective optimization by reinforcement learning for power system dispatch and voltage stability

Reactive power dispatch using Big Bang-Big Crunch optimization algorithm for voltage stability enhancement

Reactive power optimization using GSA

A hybrid method for voltage stability constrained optimal reactive power dispatch

MVAr management on the pre-dispatch problem for improving voltage stability margin

Optimal reactive power dispatch using particle swarm optimization in deregulated environment

Voltage stability and economical optimization of reactive power in power systems with wind generators by harmony search method

Optimal reactive power dispatch by pseudo-gradient guided particle swarm optimization

Reactive power rescheduling with generator ranking for voltage stability improvement

Function Optimization by Reinforcement Learning for power system dispatch and voltage stability