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文章摘要
基于回归—马尔科夫链的光伏发电功率预测
Photovoltaic power generation forecasting based on Regression -Markov chain
Received:February 28, 2018  Revised:March 05, 2018
DOI:
中文关键词: 电网  光伏发电  功率预测  回归模型  马尔科夫链
英文关键词: power  grid , photovoltaic  generation , power  forecasting , regression  model , Markov  chain
基金项目:江苏省自然科学基金
Author NameAffiliationE-mail
WANG Jituo* College of Energy and Electrical Engineering,Hohai University jtwang_edu@163.com 
WANG Wancheng College of Energy and Electrical Engineering,Hohai University wcwang@hhu.edu.cn 
CHEN Hongwei College of Energy and Electrical Engineering,Hohai University 2418550465@qq.com 
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中文摘要:
      随着光伏发电系统在电网中的比重逐步增大,其对电网的影响也越来越大。提前对光伏发电功率进行准确预测有利于电网及时调度、保证电能质量,从而保证电网的安全运行。针对光伏发电功率预测问题,本文给出一种基于回归分析和马尔科夫链的发电功率预测模型。考虑到季节、天气类型和气象等主要影响因素,通过回归模型得到初步预测值和相对残差序列,再结合马尔科夫链理论建立状态转移概率矩阵,从而修正误差序列,提高算法的精度。根据某光伏电站的实测功率数据对所提模型进行测试评估,验证了回归分析和马尔科夫链组合模型的准确性、简便性和适用性。
英文摘要:
      With the increasing proportion of the photovoltaic power system in the power grid , the influence of the photovoltaic power system on the power grid is becoming more and more high . The accurate forecasting of the photovoltaic power in advance is beneficial to the timely dispatching of the power grid and the guarantee of the power quality, so as to ensure the safe operation of the power grid. A power generation forecasting model based on regression analysis and Markov chain is proposed to predict the power of photovoltaic power generation. Considering the main influencing factors , e.g. season, weather type and meteorology , etc , we get the initial prediction value and relative residual sequence through regression model, and then combine the Markov chain theory to establish the state transition probability matrix, so as to correct the error sequence and improve the accuracy of the algorithm .According to the measured power data of a photovoltaic power station, the proposed model is tested and evaluated, which verifies the accuracy, simplicity and applicability of the regression analysis and Markov chain combination model.
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