Open AccessEconomic risk‐based bidding strategy for profit maximisation of wind‐integrated day‐ahead and real‐time double‐auctioned competitive power markets
Author(s) -
Panda Rajesh,
Tiwari Prashant Kumar
Publication year - 2019
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2018.5905
Subject(s) - cvar , bidding , market clearing , profit (economics) , expected shortfall , computer science , mathematical optimization , wind power , economics , microeconomics , operations research , risk management , engineering , mathematics , finance , electrical engineering
This study proposes a unique method of bidding strategy which is based on bi‐level optimisation model for analysing the profits of the generation companies (GENCOs) and distribution companies in the day‐ahead and real‐time competitive power markets. The bi‐level optimisation problem includes lower‐level and upper‐level problems. In the lower‐level problem, market clearing model is presented, in which market clearing problem is solved, locational marginal price is minimised at load buses, net generation cost is also minimised with a simultaneous increase in profit with optimal placement of wind generator by assessing the conditional value‐at‐risk (CVaR). In the upper level, the profit is maximised by selecting the proper bidding strategy based on double‐auctioned market mechanism. To check the effectiveness of the proposed strategy, Monte Carlo simulation and scenario‐based approach are used to generate the scenarios considering the random line outages, generator outages and load variations. The CVaR is used as a risk assessment tool for the uncertainties that would inadvertently affect the profit of the GENCOs. The proposed approach is applied to the modified IEEE 30‐bus system to show the effectiveness of the proposed model and its impact on the bidders and suppliers.