本文基于指数平滑的基本原理讨论了电力系统日负荷预测方法。
This paper is concerned with the fundamentals of the smooth index and their application in the day-load prediction for electrical power systems.
结合鞍山市燃气日负荷预测，论述了历史燃气负荷数据的处理方法。
Based on the forecast of daily gas load in Anshan City, the method for processing history data of gas load is discussed.
提出了基于气温变化的燃气日负荷预测方法——温差系数法，取得了较好的预测效果。
A method for forecasting daily gas load based on air temperature variation, namely temperature difference coefficient method is put forward, and the satisfactory forecasting result is acquired.
运用系统日负荷预测的数据，尝试性地进行无功优化控制的理论分析，并进行了实例计算。
Using data of daily load prediction, theory analysis and calculate of reactive optimal control have been tried.
采用加权最小二乘法参数估计方法，得到应用于电力系统日负荷预测和月负荷预测的ARMA模型。
In this paper, the method of weighted least square estimate is proposed to construct ARMA model, which can be applied in power system load forecasting.
本文的工作包括日负荷历史数据的处理、预测模型建模理论研究和日负荷预测的软件实现问题三个方面。
This thesis covers three aspects: the process method of daily load data, the research of forecast model and the software development of daily loadforecast.
日负荷曲线预测是电力市场运营的基本内容。
Next-day load curve prediction is the important items of electricity market operation system.
论述了北京市天然气日负荷的特点、预测模型的建立及优化过程。
The characteristics of natural gas daily load, the establishment and the optimization process of the forecast model for Beijing City are described.
传统的电力系统日生产模拟算法是在确定的负荷预测基础上仅对发电侧进行优化管理。
The traditional algorithm of plant scheduling is to optimize only the generating side management based on the defined load forecast.
本文提出了运用灰色预测模型和几何回归模型预测重大节日期间电网日负荷曲线的方法，并编制了相应软件。
A method to use the grey prediction model and geometric regression model to predict the daily load curve of power systems during the great holiday is proposed. A relevant software is presented.
此外建立了一些特定因素的模糊函数，在超短期负荷预测过程中采用了聚类分析法提取负荷相似日。
In addition, the fuzzy functions for specified factors are built, and in ultra short-term load forecasting the similar load days are extracted by clustering analysis.
然后利用电力负荷数据的不同分形特性，将分形外推插值算法应用于电力日负荷、日峰值负荷及年用电量预测中。
Then by use of different fractal property of power load data the proposed fractal extrapolation algorithm is applied to the forecasting of daily load, daily peak load and annual power consumption.
最后通过模糊推理策略预测日最大负荷和日最小负荷。实际算例表明，所提出的方法能够提高短期负荷预测的精度。
The results of practical calculation examples show that the accuracy of forecasted short-term load can be improved by the proposed method.
从非线性动力系统理论角度看，相似日预测的实质是对负荷序列中平衡点和准周期行为的预测。
From the viewpoint of nonlinear dynamic system theory, the substance of load forecasting by the loads in similar days is the forecasting for the behaviors of equilibrium points and quasi-periods.
对于受不确定因素影响的短期电力负荷，提出了一种基于相似日的神经网络预测方法。
For the short -term electric power load with uncertainty influence factors, we put forward the load forecasting method using ANN based on similar historical day.
日电力负荷预测是电力市场运营的基本内容。
通过对华东某地市电网日负荷96点曲线的预测结果显示，该方法效果较好，日预测均方根误差在1.78%以内，能较好地满足实际电力系统的负荷预测要求。
The forecasting results of a city in east China showed that, the MSE forecasting error of 96 points daily load is only about 1.78%. The method can satisfy the request of real power system well.
该模型利用RBF神经网络的非线性逼近能力对预测日负荷进行了预测，并采用在线自调整因子的模糊控制对预测误差进行在线智能修正。
The model forecasts the daily load by the nonlinear approaching capacity of the RBF neural network, than corrects the errors by on-line self-tuning factors of fuzzy control.
首先，本文给出了选出合理相似日的方法，用于提高负荷预测精度。
First, this paper discussed a method to select similar days (similar-day method, SD in short) in order to improve the accuracy of forecasting.
鉴于时负荷的日周期性及周周期性，基于灰色系统理论，提出一种周期比值灰色预测模型，对未来24小时负荷进行预测。
In view of weekly periodicity and daily periodicity of hourly load, a periodic ratio grey model for hourly load forecasting has been set up with grey system theory.
鉴于时负荷的日周期性及周周期性，基于灰色系统理论，提出一种周期比值灰色预测模型，对未来24小时负荷进行预测。
In view of weekly periodicity and daily periodicity of hourly load, a periodic ratio grey model for hourly load forecasting has been set up with grey system theory.
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