An optimized model of electricity price forecasting in the electricity market based on fuzzy timeseries
An optimized model of electricity price forecasting in the electricity market based on fuzzy timeseries
复制标题
基于模糊时间序列的电力市场电价预测优化模型
DOI：
10.1080/21642583.2014.970733
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发表时间：
2014
期刊：
影响因子：
--
通讯作者：
M. Rakhshan
中科院分区：
文献类型：
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作者：
B. Safarinejadian;Masihollah Gharibzadeh;M. Rakhshan
电力市场中的电价预测是在竞争激烈的电力市场中提高市场参与者绩效、增加其利润的重要目的之一。由于系统负荷是影响电价变化的重要因素之一，本文提出了一种基于模糊时间序列的双因子电价预测模型，利用前几天的电价和系统负荷进行电价预测。在该方法中，价格和系统负荷的时间序列模糊化的模糊集的基础上创建的模糊C-均值聚类算法。通过基于教学的优化算法确定模型系数后，将该模型用于次日电价的预测。使用澳大利亚和新加坡电力市场的数据检查所提出的模型的有前途的性能。
Electricity price forecasting in the electricity market is one of the important purposes for improving the performance of market players and increasing their profits in a competitive electricity market. Since the system load is one of the important factors affecting electricity price changes, a two-factorial model based on fuzzy time series is presented in this paper for electricity price forecasting using the electricity prices of the previous days and the system load. In the proposed method, price and system load time series are fuzzified by fuzzy sets created based on the fuzzy C-means clustering algorithm. After determining proposed model coefficients by the Teaching–Learning-Based Optimization algorithm, this model is used for forecasting the next day electricity price. The promising performance of the proposed model is examined using Australia and Singapore electricity markets data.