Power generator quotation model based on RE Learning algorithm

• Main Authors: LI BAOJU, ZHANG HAIFENG, DING QIA, WANG JIARUI, LYU XIANGYU, LI ZHENYUAN, ZHANG JIAJUN, SUN YONG, LIU CHANG, CAO RONGZHANG, LU WEN, LI DEXIN, QU KEDING, ZHANG YU, TU MENGFU, ZHUANG GUANQUN
• Format: Patent
• Language: Chinese; English
• Published: 09.02.2021
• Subjects: CALCULATING; COMPUTING; COUNTING; DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES; PHYSICS; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR

The invention discloses a power generator quotation model based on an RE Learning algorithm, and the invention comprises the steps of firstly constructing a strategy set which can effectively describethe bidding behaviors of a power generator, making a judgment according to each transaction, and adjusting the bidding strategy of the next round, so as to achieve the purpose of profit maximization;obtaining power generator agency quotation through a self-adaptive learning method for learning through interaction with the environment, and the invention is mainly used for simulating the quotationprocess of power generators in the incomplete information market. 本发明公开了一种基于RE Learning算法的发电商报价模型，首先构造能够有效描述发电商竞价行为的策略集，根据每次交易作出判断，调整下一轮的竞价策略，以期实现利润最大化的目标；通过与环境交互进行学习的自适应学习方法获得发电商代理报价，主要用于仿真发电商在不完全信息市场中的报价过程。