Day-ahead electricity price prediction applying hybrid models of LSTM-based deep learning methods and feature selection algorithms under consideration of market coupling
نویسندگان
چکیده
The availability of accurate day-ahead electricity price forecasts is pivotal for market participants. In the context trade liberalisation and harmonisation in European markets, forecasting becomes difficult participants to obtain because requires consideration features from ever-growing coupling markets. This study provides a method exploring influence on prediction. We apply state-of-the-art long short-term memory (LSTM) deep neural networks combined with feature selection algorithms prediction under coupling. LSTM models have good performance handling nonlinear complex problems processing time series data. our empirical Nordic market, proposed considerably results. results show that essential achieving prediction, integrated markets an impact importance analysis implies German has salient role generation Nord Pool.
منابع مشابه
Application 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 کاملPrice Eastimation for Day-ahead Electricity Market Using Fuzzy Logic
Price estimation is becoming increasingly relevant to producers and consumersin the new competitive electric power markets. Both for spot markets and short termcontracts, price forecasts are necessary to develop bidding strategies in order to maximizetheir benefits and utilities, respectively. Price estimation has become a very valuable toolin the current upheaval of electricity market deregula...
متن کاملDay-ahead Price Forecasting of Electricity Markets by a New Hybrid Forecast Method
Energy price forecast is the key information for generating companies to prepare their bids in the electricity markets. However, this forecasting problem is complex due to nonlinear, non-stationary, and time variant behavior of electricity price time series. Accordingly, in this paper a new strategy is proposed for electricity price forecast. The forecast strategy includes Wavelet Transform (WT...
متن کاملAgent-Based Modeling of Day-Ahead Real Time Pricing in a Pool-Based Electricity Market
In this paper, an agent-based structure of the electricity retail market is presented based on which day-ahead (DA) energy procurement for customers is modeled. Here, we focus on operation of only one Retail Energy Provider (REP) agent who purchases energy from DA pool-based wholesale market and offers DA real time tariffs to a group of its customers. As a model of customer response to the offe...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Energy
سال: 2021
ISSN: ['1873-6785', '0360-5442']
DOI: https://doi.org/10.1016/j.energy.2021.121543