Electricity load forecasting: a systematic review
IK Nti, M Teimeh, O Nyarko-Boateng… - Journal of Electrical …, 2020 - Springer
The economic growth of every nation is highly related to its electricity infrastructure, network,
and availability since electricity has become the central part of everyday life in this modern …
and availability since electricity has become the central part of everyday life in this modern …
A review on short‐term load forecasting models for micro‐grid application
Load forecasting (LF), particularly short‐term load forecasting (STLF), plays a vital role
throughout the operation of the conventional power system. The precise modelling and …
throughout the operation of the conventional power system. The precise modelling and …
Day-ahead electricity price forecasting based on hybrid regression model
Since the deregulation of the power markets, accurate short term Electricity Price
Forecasting (EPF) has become crucial in maximizing economic benefits and mitigating …
Forecasting (EPF) has become crucial in maximizing economic benefits and mitigating …
Forecasting day-ahead electricity prices for the Italian electricity market using a new decomposition—combination technique
Over the last 30 years, day-ahead electricity price forecasts have been critical to public and
private decision-making. This importance has increased since the global wave of …
private decision-making. This importance has increased since the global wave of …
Model-based deep reinforcement learning for wind energy bidding
M Sanayha, P Vateekul - International journal of electrical power & energy …, 2022 - Elsevier
Wind energy is an important source of clean energy. Due to the common trade through
bidding, many attempts have been made to apply deep reinforcement learning techniques to …
bidding, many attempts have been made to apply deep reinforcement learning techniques to …
Machine learning and internet of things applications in enterprise architectures: Solutions, challenges, and open issues
The rapid growth of the Internet of Things (IoT) has led to its widespread adoption in various
industries, enabling enhanced productivity and efficient services. Integrating IoT systems …
industries, enabling enhanced productivity and efficient services. Integrating IoT systems …
Performance analysis of short and mid-term wind power prediction using ARIMA and hybrid models
Due to the high market penetration of wind power, efficient prediction methodologies are of
paramount importance to promote wind power generation in the electricity market against …
paramount importance to promote wind power generation in the electricity market against …
Electricity price instability over time: Time series analysis and forecasting
Competition in electricity markets leads to volatile conditions which cause persistent price
fluctuations over time. This study explores the problem of electricity pricing fluctuations in the …
fluctuations over time. This study explores the problem of electricity pricing fluctuations in the …
A hybrid regression model for day-ahead energy price forecasting
D Bissing, MT Klein, RA Chinnathambi… - Ieee …, 2019 - ieeexplore.ieee.org
Accurate forecast of the hourly spot price of electricity plays a vital role in energy trading
decisions. However, due to the complex nature of the power system, coupled with the …
decisions. However, due to the complex nature of the power system, coupled with the …
Day-Ahead Electricity Demand Forecasting Using a Novel Decomposition Combination Method
In the present liberalized energy markets, electricity demand forecasting is critical for
planning of generation capacity and required resources. An accurate and efficient electricity …
planning of generation capacity and required resources. An accurate and efficient electricity …