| 引用本文: | 林湘宁,黄 京,熊卫红,翁汉琍,朱黎明,张 贞,谢志成.变压器油中溶解气体浓度的区间预测[J].电力自动化设备,2016,36(4): |
| LIN Xiangning,HUANG Jing,XIONG Weihong,WENG Hanli,ZHU Liming,ZHANG Zhen,XIE Zhicheng.Interval prediction of dissolved-gas concentration in transformer oil[J].Electric Power Automation Equipment,2016,36(4): |
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| 摘要: |
| 应用灰色关联度分析方法确定了与待预测状态量关联度较高的因素，并利用熵理论建立了具有客观权重的组合预测模型。预测区间可有效量化由不确定因素引起的油中溶解气体浓度波动，应用比例系数法和粒子群优化算法建立了一定置信水平下油中溶解气体浓度的区间预测模型，且不受传统区间预测方法中必须服从正态分布的限制。实例结果验证了所提模型的有效性。 |
| 关键词: 变压器 溶解气体 关联度 熵 预测 组合预测 正态分布 预测区间 模型 |
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| 基金项目:国家自然科学基金资助项目（51277082）；武汉市黄鹤英才（科技）计划 |
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| Interval prediction of dissolved-gas concentration in transformer oil |
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LIN Xiangning1,2, HUANG Jing1, XIONG Weihong3, WENG Hanli1, ZHU Liming2, ZHANG Zhen4, XIE Zhicheng2
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1.College of Electrical & New Energy，China Three Gorges University，Yichang 443002，China;2.School of Electrical and Electronic Enginneering，Huazhong University of Science and Technology，Wuhan 430074，China;3.Central China Grid Company Limited of State Grid Corporation of China，Wuhan 430077，China;4.Huaneng Beijing Thermal Power Co.，Ltd.，Beijing 100023，China
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| Abstract: |
| The factors highly related to the variables to be predicted are confirmed by the grey relational analysis and a combination prediction model with objective weight is built based on the entropy theory. Since uncertain factors may influence the dissolved-gas concentration in transformer oil and the prediction interval can effectively quantify its fluctuation，the proportionality coefficient method and particle swarm algorithm are adopted to build an interval prediction model of dissolved gas in transformer oil at a certain confidence level，which，different from the traditional interval prediction method，does not have to obey the normal distribution limitation. The calculative results for an example show the effectiveness of the proposed model. |
| Key words: electric transformers dissolved gas relevance entropy prediction combination prediction normal distribution prediction interval models |
