气候变化领域集成服务门户(CCPortal): Optimization of bidding strategy in the day-ahead market by consideration of seasonality trend of the market spot price

CCPortal

DOI	10.1016/j.enpol.2020.111740
	Optimization of bidding strategy in the day-ahead market by consideration of seasonality trend of the market spot price
	Motamedi Sedeh O.; Ostadi B.
发表日期	2020
ISSN	03014215
卷号	145
英文摘要	Due to the liberalization of the electricity market, evaluation of competitor behaviors, as an uncertainty factor, is a critical information for a Generation Company (GenCo) to maximize its profit by optimizing bidding strategies. In this paper, a new bidding strategy model has been presented based on the Genetic Algorithm and a refined Monte Carlo simulation model. This process is done through the similarity function and consideration of the seasonality trend as the main characteristic of the electricity spot price. The main contributions of this paper include: (a): Consideration of the similarity value for all days in historical dates in the database, (b): Consideration of the seasonality trend of market clearing price by applying K-Means algorithm for clustering historical data based on demand, (c): Application of the proposed model for each cluster's data, (d): Performance evaluation of the fitness function of each generated strategy by a simulation model based on historical data. The proposed model has been tested for the 10 subsets of Iran's electricity market 2016. The obtained results show that the proposed model is statistically efficient, and the prediction accuracy of MCP by the proposed model can be improved by more than 25% and 11% compared with a simple simulation model and the hybrid of simulation and Q-learning model. © 2020 Elsevier Ltd
关键词	Deregulated market Genetic algorithm Monte Carlo simulation Pay-as-bid Similarity function
英文关键词	Electric industry; Function evaluation; Genetic algorithms; K-means clustering; Monte Carlo methods; Reinforcement learning; Day ahead market; Electricity spot price; Fitness functions; Generation companies; Market Clearing Price; Prediction accuracy; Similarity functions; Uncertainty factors; Power markets; computer simulation; electricity supply; genetic algorithm; Monte Carlo analysis; optimization; price dynamics; seasonality; Iran
语种	英语
来源期刊	Energy Policy
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/204784
作者单位	Faculty of Industrial and Systems Engineering, Tarbiat Modares UniversityTehran, Iran; Faculty of Industrial and Systems Engineering, Tarbiat Modares UniversityTehran 1411713116, Iran
推荐引用方式 GB/T 7714	Motamedi Sedeh O.,Ostadi B.. Optimization of bidding strategy in the day-ahead market by consideration of seasonality trend of the market spot price[J],2020,145.
APA	Motamedi Sedeh O.,&Ostadi B..(2020).Optimization of bidding strategy in the day-ahead market by consideration of seasonality trend of the market spot price.Energy Policy,145.
MLA	Motamedi Sedeh O.,et al."Optimization of bidding strategy in the day-ahead market by consideration of seasonality trend of the market spot price".Energy Policy 145(2020).