引用本文: | 郭慧,马志程,王秀丽,李宛洳,马春喆.促进新能源消纳的光热电站现货交易模式及竞价策略[J].电力自动化设备,2023,43(5): |
| GUO Hui,MA Zhicheng,WANG Xiuli,LI Wanru,MA Chunzhe.Spot trading mode and bidding strategy of solar power station for promoting renewable energy consumption[J].Electric Power Automation Equipment,2023,43(5): |
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摘要: |
随着光热电站建设规模的增大,光热电站发电商将具有一定的市场力,有必要研究光热电站作为定价型市场主体参与日前电能量市场的策略。建立一个随机双层优化模型,考虑风电出力的不确定,将全场景可行随机优化算法应用于投标报价问题以处理不确定性,保证在所有场景下决策的可行性。改进的IEEE 30节点测试系统及西北地区实际系统的算例结果验证了所提竞价决策方法在提高光热电站发电商获利能力和社会效益、促进新能源消纳等方面的实用性和有效性。 |
关键词: 光热电站 策略报价 随机双层优化 全场景可行随机优化算法 |
DOI:10.16081/j.epae.202209009 |
分类号:TM73 |
基金项目:甘肃省科技重大专项计划(19ZD2GA003) |
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Spot trading mode and bidding strategy of solar power station for promoting renewable energy consumption |
GUO Hui1, MA Zhicheng2, WANG Xiuli1, LI Wanru1, MA Chunzhe1
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1.School of Electrical Engineering, Xi’an Jiaotong University, Xi’an 710049, China;2.Electric Power Research Institute of State Grid Gansu Electric Power Company, Lanzhou 730070, China
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Abstract: |
With the increase of construction scale of solar power station, the power supplier of solar power station will have a certain market power, so it is necessary to study the strategy of solar power station participating in the day-ahead electricity market as a pricing type market entity. A stochastic bi-level optimization model is established, the uncertainty of wind power output is considered, and the all-scenario-feasible stochastic optimization algorithm is applied to the bidding problem for dealing with the uncertainty, which ensures the feasibility of decision-making in all scenarios. The case results of a modified IEEE 30-bus test system and a real system in Northwest China area verify the practicality and effectiveness of the proposed bidding decision-making method in the aspects such as improving profitability of solar power station power supplier and social benefits, and promoting renewable energy consumption. |
Key words: solar power station strategic bidding stochastic bi-level optimization all-scenario-feasible stochastic optimization algorithm |