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In the high proportion hydropower market, it is of great practical significance to establish a reasonable day-ahead quotation strategy for hydropower plants to ensure the effective participation of hydropower in the market. Firstly, the uncertainty of the clearing price of the system on the operation day was considering. Based on the identification of historical similar days, Gaussian process regression was used to establish the probability prediction method of the day-ahead clearing price. Furthermore, considering the revenue preference and risk aversion psychology of decision makers, and taking the maximum expectation of the hydropower plant's own power sales revenue as the goal, the day-ahead piecewise capacity optimization bidding method for cascade hydropower stations was constructed. Finally, the feasibility and effectiveness of the proposed method were verified by the simulation analysis of the day-ahead piewise capacity declaration of the actual cascade hydropower stations.
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高比例水电电力市场中，建立合理的水电厂日前报价策略对保障水电有效参与市场具有重要意义。先考虑运行日系统出清电价的不确定性，基于历史相似日识别采用高斯过程回归提出了日前出清电价概率预测方法。进而考虑决策者的收益偏好和风险规避心理，以水电厂自身售电收益期望最大为目标，构建了梯级电站日前分段容量优化报价方法。最后以实际梯级电站进行日前分段容量申报仿真分析，验证了所提优化报价方法的可行性和有效性。
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, authorsList=李华取, 周娜, 吴滇宁, 和珮珊)}, authors=[Author(id=1223210597739778699, tenantId=1146029695717560320, journalId=1205116964453384197, articleId=1223210595697152585, orderNo=0, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=lihuaqu2018@163.com, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1223210597827859092, tenantId=1146029695717560320, journalId=1205116964453384197, articleId=1223210595697152585, authorId=1223210597739778699, language=EN, stringName=Hua-qu LI, firstName=Hua-qu, middleName=null, lastName=LI, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=null, address=Kunming Power Exchange Center Co, Ltd, Kunming 650011, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1223210597924328088, tenantId=1146029695717560320, journalId=1205116964453384197, articleId=1223210595697152585, authorId=1223210597739778699, language=CN, stringName=李华取, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=null, address=昆明电力交易中心有限责任公司，云南 昆明 650011, bio={"content":"
李华取（1996-），男，硕士、工程师，研究方向为高比例水电电力市场，E-mail：lihuaqu2018@163.com
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李华取（1996-），男，硕士、工程师，研究方向为高比例水电电力市场，E-mail：lihuaqu2018@163.com
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