Mixed integer non-linear programming and Artificial Neural Network based approach to ancillary services dispatch in competitive electricity markets

•Ancillary services market management.•Ancillary services requirements forecast based on Artificial Neural Network.•Ancillary services clearing mechanisms without complex bids and with complex bids. Ancillary services represent a good business opportunity that must be considered by market players. T...

Full description

Saved in:
Bibliographic Details
Published in:Applied energy Vol. 108; pp. 261 - 270
Main Authors: Canizes, Bruno, Soares, João, Faria, Pedro, Vale, Zita
Format: Journal Article
Language:English
Published: Kidlington Elsevier Ltd 01.08.2013
Elsevier
Subjects:
Ancillary services
Applied sciences
Artificial Neural Networks
Business
business enterprises
California
Clearing
Electricity
Electricity markets
Energy
Exact sciences and technology
Linear programming
Markets
Mixed integer
Mixed integer non-linear programming
neural networks
Optimization
Power systems
prediction
Programming
California
ANN
RS
RU
LP
SCED
CAISO
FERC
Mixed integer non-linear programming
MASCEM
Artificial Neural Networks
AGC
SR
GAMS
ISO
MINLP
Linear programming
CM
MAPE
NSR
Ancillary services
AS
RD
Electricity markets
SCUC
Power systems
FD
Electricity
Markets
Non linear programming
Neural network
ISSN:0306-2619, 1872-9118
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:•Ancillary services market management.•Ancillary services requirements forecast based on Artificial Neural Network.•Ancillary services clearing mechanisms without complex bids and with complex bids. Ancillary services represent a good business opportunity that must be considered by market players. This paper presents a new methodology for ancillary services market dispatch. The method considers the bids submitted to the market and includes a market clearing mechanism based on deterministic optimization. An Artificial Neural Network is used for day-ahead prediction of Regulation Down, regulation-up, Spin Reserve and Non-Spin Reserve requirements. Two test cases based on California Independent System Operator data concerning dispatch of Regulation Down, Regulation Up, Spin Reserve and Non-Spin Reserve services are included in this paper to illustrate the application of the proposed method: (1) dispatch considering simple bids; (2) dispatch considering complex bids.
Bibliography:http://dx.doi.org/10.1016/j.apenergy.2013.03.031
ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:0306-2619
1872-9118
DOI:10.1016/j.apenergy.2013.03.031