| 引用本文: | 端木陈睿,史林军,蹇德平,丁仁山,吴峰,李杨.计及多时间尺度的梯级水-风-光互补基地储能容量优化配置[J].电力自动化设备,2024,44(7):173-179 |
| DUANMU Chenrui,SHI Linjun,JIAN Deping,DING Renshan,WU Feng,LI Yang.Optimization of energy storage capacity allocation in multi-time scales cascaded hydro-wind-solar base[J].Electric Power Automation Equipment,2024,44(7):173-179 |
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| 摘要: |
| 含高比例风光发电的清洁能源基地是碳中和的有效途径，但风光发电出力的随机性和波动性严重影响电网的安全稳定运行。为此，提出了一种计及水-风-光互补和电池分组运行的多时间尺度嵌套清洁能源基地储能容量优化配置方法。在含梯级水-风-光的清洁能源基地中加入电池组，并研究其三分组充放电控制运行策略。构建计及水-风-光互补的多时间尺度嵌套双层储能容量优化配置模型，其中内层利用水-风-光互补性，平抑大时间尺度的风光出力大波动，外层计及衰减度对储能进行优化，以平抑小时间尺度的风光出力小波动。通过算例分析表明所提模型能充分利用灵活调控的水电与快速响应电池的互补优势有效平抑清洁能源基地功率波动，并对比验证了所提三电池组分组控制策略在节约成本以及减缓损耗方面的有效性。 |
| 关键词: 电池储能 梯级水电 联合发电 遗传算法 容量配置 分组控制 |
| DOI：10.16081/j.epae.202405011 |
| 分类号:TM715 |
| 基金项目:国家自然科学基金资助项目(U23B20140) |
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| Optimization of energy storage capacity allocation in multi-time scales cascaded hydro-wind-solar base |
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DUANMU Chenrui1, SHI Linjun1, JIAN Deping2, DING Renshan2, WU Feng1, LI Yang1
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1.School of Electrical and Power Engineering, Hohai University, Nanjing 211100, China;2.Yalong River Basin Hydropower Development Co.,Chengdu 610051, China
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| Abstract: |
| Clean energy base containing a high proportion of wind and solar power generation is an effective way to carbon neutrality, but the stochasticity and volatility of wind and solar power generation have serious influence on the security and stability of the grid. Therefore, a multi-time scales nested method for optimizing the allocation of energy storage capacity of clean energy base considering hydro-wind-solar complementation and battery grouping operation is proposed. Batteries are added to a clean energy base with cascaded hydro-wind-solar, and its three-group charge-discharge control operation strategy is investigated. A multi-time scales nested two-layer energy storage capacity allocation optimization model considering hydro-wind-solar complementarity is constructed, in which the inner layer takes advantage of the hydro-wind-solar complementarity to suppress large fluctuations of wind-photovoltaic output in large time scale and the outer layer takes into account the attenuation degree factor to optimize the energy storage in order to suppress small fluctuations of wind-photovoltaic output in small time scale. An example analysis shows that the proposed model can make full use of the complementary advantages of flexible hydropower regulation and fast response batteries to effectively smooth the power fluctuations of clean energy base and verifies the effectiveness of the proposed three-battery grouping strategy in cost saving and loss mitigation. |
| Key words: battery storage cascading hydropower combined power generation genetic algorithms capacity configuration grouping control |
