针对太阳能资源与水电资源富集地区的电站规划问题,考虑到太阳能发电的波动性及电网灵活性需求,提出一种抽水蓄能电站规划方法。首先,同时考虑集中式、分布式光伏电源与太阳能热电站,分析光-水-蓄的互补机理,研究各电站之间的关联制约关系,建立光-水-蓄协调互补框架。然后,考虑投资建设成本及灵活性优化目标,建立抽水蓄能电站双层规划模型。并采用具有自适应数据迁移功能的深度卷积条件生成对抗网络（C-DCGAN）对规划后的光-水-蓄系统发电场景进行生成,结合适用于双层规划模型迭代求解的NSGA-Ⅱ算法对模型进行求解。最后,结合实际地区电网与河道数据对提出的抽蓄电站规划方法可行性进行验证,结果表明该文提出的规划方法能有效平抑水电富集地区的新能源出力波动,充分发挥地区特有优势。
Abstract
Aiming at the problem of power station planning in areas with abundant solar energy resources and hydropower resources, considering the volatility of solar power generation and the flexibility requirements of power grid, a planning method of pumped storage power station is proposed. Firstly, considering the centralized and distributed photovoltaic power supply and solar thermal power station at the same time, the complementary mechanism of light-water-storage is analyzed, the correlation and restriction relationship between each power station is studied, and the coordinated complementary framework of light-water-storage is established. Then, considering the investment construction cost and flexibility optimization goal, a bi-level programming model of pumped storage power station is established. The C-DCGAN with adaptive data migration function is used to generate the planned power generation scenario of the optical-water-storage system, and the NSGA-Ⅱ algorithm suitable for the iterative solution of the bi-level programming model is used to solve the model. Finally, combined with the actual regional power grid and river data, the feasibility of the proposed pumping station planning method is verified. The results show that the proposed planning method can effectively suppress the fluctuation of new energy output in hydropower-rich areas and give full play to the unique advantages of the region.
关键词
太阳能发电 /
C-DCGAN /
抽水蓄能 /
储能电站规划 /
联合发电系统 /
梯级水电站
Key words
solar power generation /
C-DCGAN /
pumped storage /
energy storage power station planning /
combined power generation system /
cascade hydropower stations
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参考文献
[1] 王永真, 康利改, 张靖, 等. 综合能源系统的发展历程、典型形态及未来趋势[J]. 太阳能学报, 2021, 42(8): 84-95.
WANG Y Z, KANG L G, ZHANG J, et al.Development history, typical form and future trend of integrated energy system[J]. Acta energiae solaris sinica, 2021, 42(8): 84-95.
[2] 吴智泉, 贾纯超, 陈磊, 等. 新型电力系统中储能创新方向研究[J]. 太阳能学报, 2021, 42(10): 444-451.
WU Z Q, JIA C C, CHEN L, et al.Research on innovative direction of energy storage in new power system construction[J]. Acta energiae solaris sinica, 2021, 42(10): 444-451.
[3] 熊伟, 马志程, 张晓英, 等. 计及风、光消纳的风电-光伏-光热互补发电二层优化调度[J]. 太阳能学报, 2022, 43(7): 39-48.
XIONG W, MA Z C, ZHANG X Y, et al.Two-layer optimal dispatch of WF-PV-CSP hybrid power generation considering wind power and photovoltaic consumption[J]. Acta energiae solaris sinica, 2022, 43(7): 39-48.
[4] 陈伟, 刘文翰, 魏占宏, 等. 计及需求响应的光热电站参与深度调峰的分层优化调度策略[J]. 太阳能学报, 2024, 45(3): 579-590.
CHEN W, LIU W H, WEI Z H, et al.Hierarchical optimal scheduling strategy for concentrating solar power participating in deep peak shaving considering demand response[J]. Acta energiae solaris sinica, 2024, 45(3): 579-590.
[5] 冉金周, 李华强, 李彦君, 等. 考虑灵活性供需匹配的孤岛微网优化调度策略[J]. 太阳能学报, 2022, 43(5): 36-44.
RAN J Z, LI H Q, LI Y J, et al.Optimal scheduling of isolated microgrid considering flexible power supply and demand[J]. Acta energiae solaris sinica, 2022, 43(5): 36-44.
[6] 鞠立伟, 吕硕硕, 李鹏. 新型电力系统需求侧灵活性资源时空协同优化与动态均衡机制研究综述[J]. 电力建设, 2024, 45(9): 142-163.
JU L W, LYU S S, LI P.Review of novel demand-side flexibility resource spatio-temporal co-optimization and dynamic equilibrium mechanism of power systems[J]. Electric power construction, 2024, 45(9): 142-163.
[7] 张国斌, 陈玥, 张佳辉, 等. 风-光-水-火-抽蓄联合发电系统日前优化调度研究[J]. 太阳能学报, 2020, 41(8): 79-85.
ZHANG G B, CHEN Y, ZHANG J H, et al.Research on optimization of day-ahead dispatching of wind power-photovoltaic-hydropower-thermal power-pumped storage combined power generation system[J]. Acta energiae solaris sinica, 2020, 41(8): 79-85.
[8] 张童彦, 唐飞, 廖清芬, 等. 考虑水电外送及负荷中心功能属性的区域电网规划方法[J]. 发电技术, 2021, 42(6): 741-750.
ZHANG T Y, TANG F, LIAO Q F, et al.Regional power grid planning method considering hydropower transmission and load center function properties[J]. Power generation technology, 2021, 42(6): 741-750.
[9] 胡学东, 吴来群, 袁玉, 等. 抽水蓄能与风电、光伏联合发电系统容量配置研究[J]. 人民长江, 2024, 55(4): 244-251.
HU X D, WU L Q, YUAN Y, et al.Study on capacity configuration of pumped storage, wind power and photovoltaic combined power generation system[J]. Yangtze river, 2024, 55(4): 244-251.
[10] 苏祥瑞, 周保荣, 程兰芬, 等. 电力市场环境下的抽水蓄能规划方法[J]. 电力系统及其自动化学报, 2024, 36(11): 50-58.
SU X R, ZHOU B R, CHENG L F, et al.Method of pumped storage planning in the electricity market environment[J]. Proceedings of the CSU-EPSA, 2024, 36(11): 50-58.
[11] 肖剑, 但斌, 张旭梅. 供货商选择的双层规划模型及遗传算法求解[J]. 重庆大学学报(自然科学版), 2007, 30(6): 155-158.
XIAO J, DAN B, ZHANG X M.Bi-level programming model and genetic algorithms for the selection of vendors[J]. Journal of Chongqing University (natural science edition), 2007, 30(6): 155-158.
[12] 娄素华, 崔继纯. 考虑动态功能的抽水蓄能电站综合规划模型[J]. 电力系统自动化, 2009, 33(1): 27-31.
LOU S H, CUI J C.An integrated planning model of pumped-storage station considering dynamic functions[J]. Automation of electric power systems, 2009, 33(1): 27-31.
基金
国网东北分部绿源水力发电公司云峰发电厂科技项目（SGDBLYYFWZJS2210083）
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