电力系统及其自动化学报2011，Vol.23Issue(2)：131-134,4.
马尔科夫链在电力负荷组合预测中的应用
Combination Load Forecast with Time-varying Weights Based on Markov Chain
李敏 1江辉 1黄银华 1宋小明1
作者信息
- 1. 湖南大学电气与信息工程学院,长沙,410082
- 折叠
摘要
Abstract
In view of the specific utilization scope and condition of each single forecasting model, a novel combinatorial forecasting algorithm with nonnegative time-varying based on Markov chain is proposed in this paper.Firstly, Markov chain is used to fit the law of status probability distribution of these filtered models, and then the estimating problem of the one-step status probabilities transition matrix is translated into constrained multivariate self-regression analysis model. Secondly, the combination weights of these filtered models are determined through the estimation of the one-step status probabilities transition matrix and the distribution of status probability. Results of calculation examples show that the forecasting results by the proposed model is accurate and the proposed method is practicable.关键词
中长期负荷/组合预测/马尔科夫链/一步概率转移矩阵/组合权重Key words
medium-term and long-term load/ combination forecast/ Markov chain/ one-step status probabilities transition matrix/ combination determining weights分类
信息技术与安全科学引用本文复制引用
李敏,江辉,黄银华,宋小明..马尔科夫链在电力负荷组合预测中的应用[J].电力系统及其自动化学报,2011,23(2):131-134,4.
