Daily Nigerian Peak Load Forecasting Using Network
نویسنده
چکیده
A daily peak load forecasting technique that uses artificial neural network presented in this paper. A neural network of used to predict the daily peak load for a period available using one step ahead prediction load to the actual load. The ith index is used as load for the ith day of the year following networks are trained by the back propagation algorithm. from the Nigerian national electric power system. Results obtained requirements of practical systems and sh prediction with neural network.
منابع مشابه
Short Term Load Forecasting by Using ESN Neural Network Hamedan Province Case Study
Abstract Forecasting electrical energy demand and consumption is one of the important decision-making tools in distributing companies for making contracts scheduling and purchasing electrical energy. This paper studies load consumption modeling in Hamedan city province distribution network by applying ESN neural network. Weather forecasting data such as minimum day temperature, average day temp...
متن کاملDaily Electric Load Forecasting Based on RBF Neural Network Models
This paper presents a method of improving the performance of a day-ahead 24-h load curve and peak load forecasting. The next-day load curve is forecasted using radial basis function (RBF) neural network models built using the best design parameters. To improve the forecasting accuracy, the load curve forecasted using the RBF network models is corrected by the weighted sum of both the error of t...
متن کاملModeling and Forecasting Electric Daily Peak Loads Using Abductive Networks
Forecasting the daily peak load is important for secure and profitable operation of modern power utilities. Machine learning techniques including neural networks have been used for this purpose. This paper proposes the alternative modeling approach of abductive networks, which offers simpler and more automated model synthesis. Resulting analytical input-output models automatically select influe...
متن کاملAuto-regressive Recurrent Neural Network Approach for Electricity Load Forecasting
this paper presents an auto-regressive network called the Auto-Regressive Multi-Context Recurrent Neural Network (ARMCRN), which forecasts the daily peak load for two large power plant systems. The auto-regressive network is a combination of both recurrent and non-recurrent networks. Weather component variables are the key elements in forecasting because any change in these variables affects th...
متن کاملEvolutionary Techniques Based Combined Artificial Neural Networks for Peak Load Forecasting
This paper presents a new approach using Combined Artificial Neural Network (CANN) module for daily peak load forecasting. Five different computational techniques –Constrained method, Unconstrained method, Evolutionary Programming (EP), Particle Swarm Optimization (PSO), and Genetic Algorithm (GA) – have been used to identify the CANN module for peak load forecasting. In this paper, a set of ne...
متن کامل