|
|
|
|
|
Daniel Manfre Jaimes, Manuel Zamudio López, Hamidreza Zareipour and Mike Quashie
This paper proposes a new hybrid model to forecast electricity market prices up to four days ahead. The components of the proposed model are combined in two dimensions. First, on the ?vertical? dimension, long short-term memory (LSTM) neural networks and...
ver más
|
|
|
|
|
|
|
|
|
|
|
Nika Nizharadze, Arash Farokhi Soofi and Saeed Manshadi
Predicting the price gap between the day-ahead Market (DAM) and the real-time Market (RTM) plays a vital role in the convergence bidding mechanism of Independent System Operators (ISOs) in wholesale electricity markets. This paper presents a model to pre...
ver más
|
|
|
|
|
|
|
|
|
|
|
Stephen Haben, Julien Caudron and Jake Verma
The energy sector is moving towards a low-carbon, decentralised, and smarter network. The increased uptake of distributed renewable energy and cheaper storage devices provide opportunities for new local energy markets. These local energy markets will req...
ver más
|
|
|
|
|
|
|
|
|
|
|
Sajjad Khan, Shahzad Aslam, Iqra Mustafa and Sheraz Aslam
Day-ahead electricity price forecasting plays a critical role in balancing energy consumption and generation, optimizing the decisions of electricity market participants, formulating energy trading strategies, and dispatching independent system operators...
ver más
|
|
|
|
|
|
|
|
|
|
|
Belén Vega-Márquez, Cristina Rubio-Escudero, Isabel A. Nepomuceno-Chamorro and Ángel Arcos-Vargas
The importance of electricity in people?s daily lives has made it an indispensable commodity in society. In electricity market, the price of electricity is the most important factor for each of those involved in it, therefore, the prediction of the elect...
ver más
|
|
|
|
|
|
|
|
|
|
|
Zezheng Zhao, Chunqiu Xia, Lian Chi, Xiaomin Chang, Wei Li, Ting Yang and Albert Y. Zomaya
From the perspective of energy providers, accurate short-term load forecasting plays a significant role in the energy generation plan, efficient energy distribution process and electricity price strategy optimisation. However, it is hard to achieve a sat...
ver más
|
|
|
|
|
|
|
|
|
|
|
Sergei Kulakov
The main goal of the present paper is to improve the X-model used for day-ahead electricity price and volume forecasting. The key feature of the X-model is that it makes a day-ahead forecast for the entire wholesale supply and demand curves. The intersec...
ver más
|
|
|
|
|
|
|
|
|
|
|
Javier Menéndez, Jesús Manuel Fernández-Oro and Jorge Loredo
The electricity generated by some renewable energy sources (RESs) is difficult to forecast; therefore, large-scale energy storage systems (ESSs) are required for balancing supply and demand. Unlike conventional pumped storage hydropower (PSH) systems, un...
ver más
|
|
|
|
|
|
|
|
|
|
|
Radhakrishnan Angamuthu Chinnathambi, Anupam Mukherjee, Mitch Campion, Hossein Salehfar, Timothy M. Hansen, Jeremy Lin and Prakash Ranganathan
Forecasting hourly spot prices for real-time electricity markets is a key activity in economic and energy trading operations. This paper proposes a novel two-stage approach that uses a combination of Auto-Regressive Integrated Moving Average (ARIMA) with...
ver más
|
|
|
|
|
|
|
|
|
|
|
Behnam Rasouli, Mohammad Javad Salehpour, Jin Wang and Gwang-jun Kim
This paper presents a new model based on the Monte Carlo simulation method for considering the uncertainty of electric vehicles? charging station?s load in a day-ahead operation optimization of a smart micro-grid. In the proposed model, some uncertain ef...
ver más
|
|
|
|
|
|