| 考虑年出力与短期出力不确定性的分布式清洁能源消纳能力分析 |
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| 引用本文：黄玉辉1,程孟增2,刘禹彤2,蒋海玮2.考虑年出力与短期出力不确定性的分布式清洁能源消纳能力分析[J].电网与清洁能源,2025,41(4):68~76 |
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| 基金项目:国家电网公司总部科技项目（5400-202128572A-0-5-SF） |
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| 中文摘要:当前，能源结构逐渐向清洁化、低碳化转型，能源系统逐步发展为综合性的城市能源系统。在此背景下，分布式清洁能源消纳能力分析受到多重不确定因素的影响。为此，研究以光伏能源为例，充分考虑了年出力与短期出力不确定性，提出了相应的消纳能力分析方法。针对光伏年出力不确定性分析，引入了极端梯度提升树算法，并采用Bagging算法对其进行优化。针对光伏短期出力不确定分析，引入了回声状态网络。引入多元变分模态分解法实现频率分量提取，在此基础上，建立了优化模型以实现光伏不确定性的平抑。结果显示，考虑2种出力不确定性与光储系统平抑效果的方案在电力系统与城市能源系统中均取得了最大的光伏接入容量，消纳能力明显更强。其中，该方案在城市能源系统中的接入容量高达4 628 kW，配置成本为1 882元，而运行成本仅为20 132元。说明研究所提方法能够有效评估城市能源系统的光伏消纳能力。 |
| 中文关键词:分布式 清洁能源 光伏 消纳 出力 不确定性 |
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| Distributed Clean Energy Consumption Capacity Considering Uncertainty of Annual and Short Term Output |
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| Abstract:Currently， the energy structure is gradually transitioning towards cleaner and lower-carbon sources， while energy systems are progressively evolving into integrated urban energy systems. In this context， the analysis of the consumption capacity of distributed clean energy is affected by multiple uncertain factors. Therefore， taking photovoltaic energy as an example， this study fully considers the uncertainty of annual and short-term output and proposes corresponding analysis methods for consumption capacity. For the uncertainty analysis of photovoltaic annual output， the extreme gradient boosting tree algorithm is introduced and optimized using the Bagging algorithm. For the uncertainty analysis of short-term photovoltaic output， an echo state network is introduced. The multivariate variational mode decomposition method is introduced to extract frequency components， and on this basis， an optimization model is established to suppress photovoltaic uncertainty. The results show that the scheme considering two types of output uncertainty and the smoothing effect of the photovoltaic storage system achieves the maximum total photovoltaic access capacity in both the power system and urban energy system， with significantly stronger absorption capacity. Among them， the total connected capacity of this scheme in the urban energy system is as high as 4 628 kW， with a configuration cost of 1 882 Yuan and an operating cost of only 20 132 Yuan. The proposed method can effectively evaluate the photovoltaic consumption capacity of urban energy systems， providing reliable technical support for the sustainable development of urban energy systems. |
| keywords:distributed clean energy photovoltaics consumption output uncertainty |
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