Short-term load forecasting in market environment
نویسندگان
چکیده
In the paper the problem of the application of neural predictors for Short-Term Load Forecasting (STLF) for energy transactions planning in utility is presented. Several aspects of this topic are discussed, including identification of different load patterns for holidays and customer profiles, estimation of prediction intervals and optimal size of the order, according to the financial conditions on the market.
منابع مشابه
Short term electric load prediction based on deep neural network and wavelet transform and input selection
Electricity demand forecasting is one of the most important factors in the planning, design, and operation of competitive electrical systems. However, most of the load forecasting methods are not accurate. Therefore, in order to increase the accuracy of the short-term electrical load forecast, this paper proposes a hybrid method for predicting electric load based on a deep neural network with a...
متن کاملApplication of a New Hybrid Method for Day-Ahead Energy Price Forecasting in Iranian Electricity Market
Abstract- In a typical competitive electricity market, a large number of short-term and long-term contracts are set on basis of energy price by an Independent System Operator (ISO). Under such circumstances, accurate electricity price forecasting can play a significant role in improving the more reasonable bidding strategies adopted by the electricity market participants. So, they cannot only r...
متن کاملShort 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 کاملEfficient Short-Term Electricity Load Forecasting Using Recurrent Neural Networks
Short term load forecasting (STLF) plays an important role in the economic and reliable operation ofpower systems. Electric load demand has a complex profile with many multivariable and nonlineardependencies. In this study, recurrent neural network (RNN) architecture is presented for STLF. Theproposed model is capable of forecasting next 24-hour load profile. The main feature in this networkis ...
متن کاملComparative Analysis of Short-Term Price Forecasting Models: Iran Electricity Market
As the electricity industry has changed and became more competitive, the electricity price forecasting has become more important. Investors need to estimate future prices in order to take proper strategy to maintain their market share and to maximize their profits. In the economic paradigm, this goal is pursued using econometric models. The validity of these models is judged by their forecastin...
متن کامل