电力系统自动化
電力繫統自動化
전력계통자동화
AUTOMATION OF ELECTRIC POWER SYSTEMS
2014年
5期
19-24
,共6页
黄磊%舒杰%姜桂秀%张继元
黃磊%舒傑%薑桂秀%張繼元
황뢰%서걸%강계수%장계원
光伏功率预测%微网(微电网)%多维时间序列相空间重构%支持向量回归%局部预测
光伏功率預測%微網(微電網)%多維時間序列相空間重構%支持嚮量迴歸%跼部預測
광복공솔예측%미망(미전망)%다유시간서렬상공간중구%지지향량회귀%국부예측
photovoltaic (PV) power forecast%microgrid%phase space reconstruction of multidimensional time-series%support vector regression%local forecast
目前光伏发电预测普遍采用采样间隔较大的单一时间尺度功率序列建模,模型简单但对功率时序特征的模拟精度不高。文中提出了一种基于小采样间隔光伏功率数据的多维时间序列局部预测方法。通过构造不同时间尺度的光伏功率均值序列,形成以小时平均光伏功率序列为主要研究序列的多维时间序列;基于相关性分析、C-C方法和嵌入维最小预测误差法确定多维时间序列相空间重构的时间延迟和嵌入维;采用支持向量回归方法建立提前1h 的光伏功率局部预测模型。以国内某微网的光伏功率预测为例进行仿真实验,计算结果表明,多维时间序列局部预测模型优于基于单一时间尺度功率序列的局部预测模型,更具应用价值。
目前光伏髮電預測普遍採用採樣間隔較大的單一時間呎度功率序列建模,模型簡單但對功率時序特徵的模擬精度不高。文中提齣瞭一種基于小採樣間隔光伏功率數據的多維時間序列跼部預測方法。通過構造不同時間呎度的光伏功率均值序列,形成以小時平均光伏功率序列為主要研究序列的多維時間序列;基于相關性分析、C-C方法和嵌入維最小預測誤差法確定多維時間序列相空間重構的時間延遲和嵌入維;採用支持嚮量迴歸方法建立提前1h 的光伏功率跼部預測模型。以國內某微網的光伏功率預測為例進行倣真實驗,計算結果錶明,多維時間序列跼部預測模型優于基于單一時間呎度功率序列的跼部預測模型,更具應用價值。
목전광복발전예측보편채용채양간격교대적단일시간척도공솔서렬건모,모형간단단대공솔시서특정적모의정도불고。문중제출료일충기우소채양간격광복공솔수거적다유시간서렬국부예측방법。통과구조불동시간척도적광복공솔균치서렬,형성이소시평균광복공솔서렬위주요연구서렬적다유시간서렬;기우상관성분석、C-C방법화감입유최소예측오차법학정다유시간서렬상공간중구적시간연지화감입유;채용지지향량회귀방법건립제전1h 적광복공솔국부예측모형。이국내모미망적광복공솔예측위례진행방진실험,계산결과표명,다유시간서렬국부예측모형우우기우단일시간척도공솔서렬적국부예측모형,경구응용개치。
Currently power series with single time scale and large sampling intervals are generally used in modeling photovoltaic generation forecast.Simple as the model is,its simulation accuracy of the time-series characteristics of photovoltaic (PV) power series is not high.In order to solve this problem,this paper proposes a local forecasting method for multidimensional time-series based on PV power series with small sampling interval.By constructing the main value series of PV power with different time-scales,the multidimensional time-series with hourly average PV power series as the main series is obtained.The correlation analysis,C-C method and minimum prediction error method of embedding dimension are used to compute the time-delay and embedding dimensions of the reconstructed phase space of the multidimensional time-series.The 1-hour ahead local forecasting model for PV power is developed by using support vector regression after phase space reconstruction. To demonstrate the effectiveness,the model is applied and tested in a microgrid.Simulation results show that the proposed local forecasting model based on multidimensional time-series outperforms the local forecasting model based on one-dimensional series,hence it has a better application value.