Open AccessMarket‐based generator cost functions for power system test cases
Author(s) -
Durvasulu Venkat,
Hansen Timothy M.
Publication year - 2018
Publication title -
iet cyber‐physical systems: theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.308
H-Index - 7
ISSN - 2398-3396
DOI - 10.1049/iet-cps.2018.5046
Subject(s) - generator (circuit theory) , electricity market , marginal cost , electricity , electric generator , electric power system , restructuring , electricity generation , computer science , energy market , operator (biology) , clearance , reliability engineering , power (physics) , automotive engineering , economics , engineering , electrical engineering , microeconomics , finance , physics , quantum mechanics , medicine , biochemistry , chemistry , repressor , transcription factor , urology , gene
Post‐restructuring, generators are dispatched using cleared offers in the day‐ahead market in the cyber‐physical power system. This study proposes a novel method to design generator cost functions to emulate existing market costs for power system test cases. Cost functions on existing test cases are based on fuel costs, which do not represent organised markets. In such markets, the marginal cost of energy is determined by generator offers , not fuel costs. In this work, the authors classify real market generator offers from an independent system operator organised electricity market into generator types . Generator offers are used to develop market‐based generator cost functions for use in power system test cases to emulate electricity market behaviour. The proposed method is illustrated using PJM data on eight standard power system test cases from a six bus 240 MW generation case to 2000 buses with 95,000 MW of generation. The marginal price of the proposed market‐based generator costs shows on average 280% improvement in accuracy of simulating the day‐ahead PJM marginal energy price over existing fuel‐cost‐based test cases from 2014 to 2016. By using the new market‐based generator cost functions, power system simulation studies will better represent actual economic impacts.