范宏,李年龙
FAN Hong,LI Nianlong

• 1:上海电力大学电气工程学院

摘要(Abstract)：

随着高比例新能源持续接入新型电力系统，其出力的随机性与波动性导致系统应对极端天气造成的电力供需失衡的能力显著下降。为此，针对频发的极端天气事件，提出一种考虑安全保障的风光火储协同规划方法。首先，构建考虑气候参数的源荷储模型；然后，采用长短期记忆网络与生成对抗网络相结合的方法生成极端天气场景集；进而，建立以投资与运行成本最小为目标的两阶段协同规划模型，并引入弹性评价指标；最后，基于中国北方某省电网数据的算例分析表明，所提方法虽使总投资成本有所增加，但能显著提升系统在极端天气下的供电可靠性与运行弹性。
With the continuous integration of high shares of renewable energy into modern power systems, the inherent randomness and variability of their output have significantly weakened the systems' capability to cope with power supply-demand imbalance caused by extreme weather events. To address increasingly frequent extreme weather conditions, a coordinated planning method for wind-solar-thermal-storage systems considering security assurance is proposed. First, source-load-storage models incorporating climatic parameters are established. Then, a combination of long short-term memory(LSTM) networks and generative adversarial networks(GAN) is employed to generate extreme weather scenario sets. Subsequently, a two-stage coordinated planning model is formulated with the objective of minimizing investment and operational costs, and resilience evaluation indices are introduced. Finally, case studies based on data from a provincial power grid in northern China demonstrate that, although the proposed method slightly increases total investment cost, it significantly enhances power supply reliability and operational resilience under extreme weather conditions.

关键词(KeyWords)： 新型电力系统;极端天气;供需平衡;长短期记忆网络;生成对抗网络;协同规划
modern power system;extreme weather;supply-demand balance;LSTM;GAN;coordinated planning

Abstract:

Keywords:

基金项目(Foundation): 国家自然科学基金（U22B6008）

作者(Author): 范宏,李年龙
FAN Hong,LI Nianlong

DOI: 10.19585/j.zjdl.202606005

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