基于WPD-SCA-ELM模型的天然气负荷短期预测

Short-term prediction of natural gas load based on WPD-SCA-ELM model

随着天然气消耗量的不断增加,准确预测未来天然气的日负荷用量对于天然气资源的合理配置具有重要意义。针对此问题,在“分解—预测—重构”的思想上建立了基于WPD-SCA-ELM模型的天然气负荷预测模型,对影响小波包分解的小波基函数和分解层数进行优选,选取了对日负荷影响较大的因素,并针对气温因素的滞后性进行了平移修正,最后与其余模型算法进行了对比验证。结果表明,供暖期的日负荷数据是非正态分布,具有较大的波动性;Fk4阶2层分解更能反映日负荷的变化趋势和特征;日最高气温和日最低气温的相关系数均大于平均气温,通过对气温进行平移滑动操作,可提高气温与日负荷的相关性;WPD-SCA-ELM模型的MAPE、RMSE、DS分别为0.59、7321.87、0.9205,与其他模型相比评价指标最优,证明了该模型的科学性。

With increasing natural gas consumption,it is of great significance to accurately predict the daily consumption load of natural gas in the future for the rational allocation of natural gas resources.To solve this problem,a natural gas load prediction model based on the WPD-SCA-ELM model was established based on the idea of“decomposing-prediction-reconstruction”.The wavelet basis function and decomposition layers affecting the wavelet packet decomposition were optimized,and the factors affecting the daily load were selected,and the temperature factor hysteresis was corrected by a translation operation.Finally,the algorithm is compared with other models.The results show that the daily load data in the heating period is not normally distributed and has great fluctuation.The Fk4-order two-layer decomposition can better reflect the variation trends and daily load characteristics.The correlation coefficients of daily maximum temperature and daily minimum temperature are larger than average temperature,and the correlation between temperature and daily load can be improved by translating and sliding the temperature.The MAPE,RMSE and DS of WPD-SCA-ELM model are 0.59,7321 and 0.920,respectively.Compared with other models,the evaluation index is the best,which proves that the model is useful.