Open AccessResearch on Simulation and identification method of abnormal bidding behavior of power market members based on cloud technology
Author(s) -
Youyi Chang,
Dunnan Liu,
Qingchun Li,
Zexiang Cai,
Xiaoyang He,
Ye Zhang,
Jian Zhang
Publication year - 2021
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/621/1/012047
Subject(s) - bidding , identification (biology) , ebidding , database transaction , cloud computing , real time bidding , market power , electricity market , computer science , transaction data , microeconomics , business , electricity , economics , engineering , database , monopoly , botany , electrical engineering , biology , operating system
In order to solve the problem that abnormal bidding behaviors are difficult to be identified and controlled in the electricity market, a method based on cloud technology is proposed to simulate and identify abnormal bidding behaviors of power market members, which can give real-time early warning of potential abnormal bidding behaviors in the transaction process. The application of cloud technology big data in simulation identification effectively solves the problem that potential bidding abnormal behavior is difficult to be quantitatively identified, and also overcomes the defect that general identification methods are not easy to understand. Firstly, the paper combs the members, trading methods and types of electricity market, and analyzes the influencing factors of bidding decision-making behavior of power market members; secondly, it designs the general framework and steps of identifying potential abnormal bidding behavior; at the same time, it studies the dynamic evolution trend of bidding behavior of market members, on this basis, realizes the identification of abnormal bidding behavior of market members, and manages and regulates market members.