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Load Forecasting has an important role in load generation, scheduling, planning etc. in power system. Different computational intelligent techniques are used in Short Term Load Forecasting (STLF) to make it more effective. Neural Networks (NN) is an effective mapping algorithm that can map complex input-output relationships, which is an important technique to do STLF having existing dataset. Usually...
It is an irresistible trend of the electric power improvement for developing the smart grid, which applies a large amount of new technologies in power generation, transmission, distribution and utilization to achieve optimization of the power configuration and energy saving. As one of the key links to make a grid smarter, load forecast plays a significant role in planning and operation in power system...
With the development of power systems, the accuracy of electric power load forecasting plays a more important role in the safe operation of power system and raising the level of the national economy. Load forecasting is a very important element of the power system operation scheduling, an important module of the energy management system (EMS), and is the basis to ensure safe and economical operation...
Short-term load forecasting is important for electricity load planning and dispatches the loading of generating units in order to meet the electricity system demand. The precision of the load forecasting is related to electricity company's economic. This paper presents a approach named an autoregressive moving average (ARMA) cooperate with BP Artificial Neural Network (BPNN) approach, which can combine...
The power load forecasting precision being influenced by many factors, the traditional forecasting tools are not very taking the role. In fact, BP network has the characteristics of the applicable and self-learning, and grey method has the growth characteristics,this paper used the correcting coefficient to improved the grey method, so the grey BP network method can better reflect the increasing and...
Short-term load forecast is an essential part of electric power system planning and operation. Forecasted values of system load affect the decisions made for unit commitment and security assessment, which have a direct impact on operational costs and system security. Conventional regression methods are used by most power companies for load forecasting. However, due to the nonlinear relationship between...
Accurate models for electricity power load forecasting are essential to the operation and planning of an electricity company. Neural Networks are considered as a computational model that is capable of doing nonlinear curve fitting. In this research, the application of neural networks to study the design of Short Term load Forecasting (STLF) Systems for Sri Lanka was explored. Three layered neural...
Long-term load forecasting has a vital role in generation, transmission and distribution network planning. Traditional studies for long-term load forecasting were based on regression method, which could not provide a true representation of power system behavior in a volatile electricity market. The purpose of this paper is to introduce two approaches based regression method and artificial neural network...
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