Open AccessBidding strategies of the joint wind, hydro, and pumped‐storage in generation company using novel improved clonal selection optimisation algorithm
Author(s) -
Afshari Igder Mosayeb,
Niknam Taher,
Khooban MohammadHassan
Publication year - 2017
Publication title -
iet science, measurement and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.418
H-Index - 49
eISSN - 1751-8830
pISSN - 1751-8822
DOI - 10.1049/iet-smt.2017.0014
Subject(s) - bidding , profit (economics) , wind power , electricity market , computer science , electricity generation , site selection , renewable energy , pumped storage hydroelectricity , selection (genetic algorithm) , environmental economics , electricity , business , operations research , engineering , distributed generation , power (physics) , electrical engineering , economics , microeconomics , physics , quantum mechanics , artificial intelligence , political science , law , marketing
The wind and hydro technologies express a significant part of the electricity generation section. This study presents an optimal coordinated bidding strategy of wind, cascaded hydro generation, and pumped‐storage (PS) units. One of the chief purposes of this study is maximisation the profit of the wind and hydro plants by participating in the day‐ahead energy and ancillary service markets. The regulation and spinning reserve markets are regarded as ancillary services. Thanks to the inherent variability and uncertainty of wind power, it does not participate in the ancillary service market. Hydro company is constructed of several cascaded hydro units which design alongside a river basin as well as a PS unit. In this study, the risk is modelled by using conditional value at risk. To reach the optimum solution, a new improved clonal selection algorithm is applied which shows the effectiveness of the proposed method for optimising a generation companies (GENCOs) profit.