本文提出用于电力系统发电规划和输电规划负荷预测的时间序列分析法。
The time series analysis is proposed for load forecasting of power-generating and power transmission programming in power systems.
电力系统恢复；过电压预测；节点重要性；蚁群算法；网架重构；负荷恢复。
Power system restoration; Over-voltage prediction; Node importance; Ant Colony algorithm; Skeleton - network reconfiguration; Load recovery.
文中给出了这种算法在电力系统负荷预测中的实际应用，并与标准BP算法作了比较。
An example of the algorithm's application in electric power system load forecasting is shown and compared with standard BP algorithm.
负荷预测是电力系统运行和规划的依据。
Power system load forecasting is the foundation of power system operation and planning.
负荷预测是电力系统规划、计划、用电、调度等部门的基础工作。
Load forecasting is the foundation of power system planning and operation.
负荷预测是电力系统规划的基础，其准确度直接影响到电网建设。
As the basis of electric power system planning, the accuracy of load forecast is directly related to the construction of power network.
提出了一种预测电力系统负荷的新方法。
提出一种时间序列算法和模糊逻辑技术相结合的电力系统短期负荷预测方法。
An improved method for short term electric load forecasting is presented. It is based on time series methods and fuzzy logic techniques.
短期电力负荷的预测对电力系统具有重要的意义。
Short-term load forecasting is of great importance for electric power systems.
负荷预测是电力系统一项重要而基础的工作。
Load forecast is an important and basic job in power system.
电力系统短期负荷预测使用的方法有传统建模方法，诸如时间序列、回归分析等方法。
There are traditional model methods of forecasting short-term load, such as time series, regression analysis, and so on.
电力负荷预测的准确性对于电力系统的合理规划与建设意义重大。
The accuracy of power load forecasting is significant to the reasonable planning and construction of power system.
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.
负荷预测是电力系统规划和运行研究的重要内容，属于战略预测，是保证电力系统可靠供电和经济运行的前提。
Load forecasting is an important research content of power system planning and running, belongs to stratagem forecasting, and is a premise for reliable supplying and economic running.
说明：电力系统负荷预测程序，短期预测，考虑天气、人体舒适度等因素。
Power system load forecasting process, short-term forecasting, considering the weather, human comfort and other factors.
电力系统负荷预测是电力系统运行、控制和规划不可缺少的一部分，是电力市场技术支持系统的基础。
Power system load forecast, which is the base of power market technique supporting system, is an essential part of power system operation, control and planning.
提出了一种交替梯度算法对径向基函数(RBF)神经网络的训练方法进行改进，并将之运用于电力系统短期负荷预测。
This paper proposes one kind of alternant gradient algorithm for improving the training of RBF neural network, which is applied to short-term electric load.
电力负荷预测是电力系统调度、用电、计划、规划等管理部门的重要工作之一。
Electric power system load forecasting is one of important operations in dispatching, demanding, scheduling and planning of power system management sectors.
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.
线性回归是电力系统中期负荷预测的常用方法。
Linear regression analysis is a most common method for mid term load forecasting.
计算结果表明，用该预测方法预测电力系统季负荷具有较高的预测精度。
It sampling calculation shows that this forecasting method has high forecasting precision in the seasonal load forecasting of power system.
短期负荷预测的准确与否将直接关系到电力系统的安全运行和经济调度，便于更合理地安排电网设备调度及检修计划；
Load forecasting is related to operation security and economical dispatching of power system , which is used to arrange the equipments dispatching and repairing .
针对电力系统负荷变化具有明显的分形自相似性的特点，提出了一种新的基于弹性系数的短期负荷预测方法。
A new method of short time load forecasting on the base of elasticity coefficient is put forward according to the characteristic of obvious fractal self similarity of load change in power system.
南京市实施的部分结果表明，负荷管理可以改变电力系统负荷曲线的形状，从而达到期望的目标，同时还可以为电力负荷的预测提供修正的参数。
Part of implementary result shows that load management can shape the load curve of power system to reach the expected aim and supply revised parameters for load forecast.
电力系统负荷预测是电力系统规划与运行的基础，是电力市场运作中的重要组成部分。
Power load forecasting is the basis of planning and operation of electric power system. It is also an important part of electric power market performing.
提出一种采用神经网络进行电力系统短期负荷预测的降维方法。
A reduced dimensions method applying neural network is proposed for short term load forecasting.
提出了一种免疫聚类径向基函数神经网络(ICRBFNN)模型来预测电力系统短期负荷。
The paper presents an immune clustering RBF neural network (ICRBFNN) model for short-term load forecasting.
负荷是电力系统运行和规划的依据，准确的负荷预测有利于提高电力系统运行的经济性和可靠性。
Load is the foundation of power system operation and planning. Accurate load forecasting is advantageous to improving the reliability and economic effect of power system.
负荷是电力系统运行和规划的依据，准确的负荷预测有利于提高电力系统运行的经济性和可靠性。
Load is the foundation of power system operation and planning. Accurate load forecasting is advantageous to improving the reliability and economic effect of power system.
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