Pith. sign in

REVIEW

Bidding Strategy with Forecast Technology Based on Support Vector Machine in Electrcity Market

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 0709.3710 v1 pith:OLWNIVBY submitted 2007-09-24 q-fin.GN physics.data-an

classification q-fin.GNphysics.data-an
keywords marketforecastpricebiddingapproachesbeenmachineproposed
verification ladder T0 review T1 audit T2 compute T3 formal

Signed reviews

No signed human review yet.

0 comments
read the original abstract

The participants of the electricity market concern very much the market price evolution. Various technologies have been developed for price forecast. SVM (Support Vector Machine) has shown its good performance in market price forecast. Two approaches for forming the market bidding strategies based on SVM are proposed. One is based on the price forecast accuracy, with which the being rejected risk is defined. The other takes into account the impact of the producer's own bid. The risks associated with the bidding are controlled by the parameters setting. The proposed approaches have been tested on a numerical example.

Discussion (0). Continue with ORCID to comment.

Pith tools