NDLI: Unit commitment for power plants with tracking speed limits

Content Provider	IEEE Xplore Digital Library
Author	Tao Fan Wen Tan
Copyright Year	2011
Description	Author affiliation: School of Control and Computer Engineering, North China Electric Power University, Beijing, China (Tao Fan; Wen Tan)
Abstract	Unit commitment is an efficient method to lower the total cost of the power plant by scheduling units' generation and meeting the constraint condition. However, in practice, few power plants implement the algorithm for fear that the load response in the power plant would not be fast enough to track the unscheduled load demand from the power grid if some units of the power plant are shut down. This paper proposes a new unit commitment method that tries to solve this problem effectively. The proposed method guarantees the desired speed limit by setting the plant-level load tracking speed. In this method a ‘one-at-a-time’ unit commitment is accomplished. The most expensive unit (which is determined by computing its cost) is optimized, the unit commitment schedule is updated, and the load dispatch result is re-computed. The result will be repeatedly optimized until the spinning reserve or load tracking speed is lack. The optimization loop will breaks out as well if the unit schedules of two consecutive iterations over the time period remain unchanged. The test results from 10-machine system shows that the proposed method is easy to understand and quick to solve, and is of practical use.
Starting Page	2800
Ending Page	2803
File Size	335712
Page Count	4
File Format	PDF
ISBN	9781424481620
e-ISBN	9781424481651
DOI	10.1109/ICECENG.2011.6057744
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-09-16
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Schedules Spinning reserve Unit commitment Educational institutions Power systems Spinning Mathematical model Plant-level load tracking speed Power generation Optimization Genetic algorithms Load dispatch
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

Solution of unit commitment problem using enhanced genetic algorithm

Robust optimization method for unit commitment with network losses considering wind uncertainties

The value of operational flexibility in power systems with significant wind power generation

Optimal dispatch with reactive power compensation by Genetic Algorithm

Local optimal search algorithm for unit commitment problem

Spinning reserve computation for a power system with WPG using Point-Estimate Methods

Particle swarm optimization to solving economic load dispatch with spinning reserve

On spinning reserve determination and power generation dispatch optimization for wind power integration systems

Thermal unit commitment considering pumped storage hydro electricity plants

Unit commitment for power plants with tracking speed limits

Similar Documents

Solution of unit commitment problem using enhanced genetic algorithm

Robust optimization method for unit commitment with network losses considering wind uncertainties

The value of operational flexibility in power systems with significant wind power generation

Optimal dispatch with reactive power compensation by Genetic Algorithm

Local optimal search algorithm for unit commitment problem

Spinning reserve computation for a power system with WPG using Point-Estimate Methods

Particle swarm optimization to solving economic load dispatch with spinning reserve

On spinning reserve determination and power generation dispatch optimization for wind power integration systems

Thermal unit commitment considering pumped storage hydro electricity plants

Unit commitment for power plants with tracking speed limits