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Related papers: Short-Term Power Demand Forecasting for Diverse Co…

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The planning and operation of renewable energy, especially wind power, depend crucially on accurate, timely, and high-resolution weather information. Coarse-grid global numerical weather forecasts are typically downscaled to meet these…

Short-term forecasting of residential electricity demand is an important task for utilities. Yet, many small and medium-sized utilities still use simple forecasting approaches such as Synthesized Load Profiles, which treat residential…

Computers and Society · Computer Science 2025-03-10 Daniel R. Bayer , Felix Haag , Marco Pruckner , Konstantin Hopf

Electricity load forecasting plays an important role in the energy planning such as generation and distribution. However, the nonlinearity and dynamic uncertainties in the smart grid environment are the main obstacles in forecasting…

Neural and Evolutionary Computing · Computer Science 2018-11-09 Faisal Mohammad , Ki Boem Lee , Young-Chon Kim

We propose a simple empirical scaling law that describes load forecasting accuracy at different levels of aggregation. The model is justified based on a simple decomposition of individual consumption patterns. We show that for different…

Applications · Statistics 2017-09-01 Raffi Sevlian , Ram Rajagopal

Recent developments related to the energy transition pose particular challenges for distribution grids. Hence, precise load forecasts become more and more important for effective grid management. Novel modeling approaches such as the…

Machine Learning · Computer Science 2023-05-19 Elena Giacomazzi , Felix Haag , Konstantin Hopf

Consumer energy forecasting is essential for managing energy consumption and planning, directly influencing operational efficiency, cost reduction, personalized energy management, and sustainability efforts. In recent years, deep learning…

Machine Learning · Computer Science 2025-02-10 Muhammad Umair Danish , Katarina Grolinger

The Optimal Power Flow (OPF) problem is pivotal for power system operations, guiding generator output and power distribution to meet demand at minimized costs, while adhering to physical and engineering constraints. The integration of…

Machine Learning · Computer Science 2023-11-27 Chen Li , Alexander Kies , Kai Zhou , Markus Schlott , Omar El Sayed , Mariia Bilousova , Horst Stoecker

Accurate forecasting of the electrical load, such as the magnitude and the timing of peak power, is crucial to successful power system management and implementation of smart grid strategies like demand response and peak shaving. In…

Machine Learning · Computer Science 2024-11-26 Dafang Zhao , Xihao Piao , Zheng Chen , Zhengmao Li , Ittetsu Taniguchi

The large scale deployment of Advanced Metering Infrastructure among residential energy customers has served as a boon for energy systems research relying on granular consumption data. Residential Demand Response aims to utilize the…

Systems and Control · Computer Science 2016-07-05 Datong Zhou , Maximilian Balandat , Claire Tomlin

Accurate load forecasting is critical for efficient and reliable operations of the electric power system. A large part of electricity consumption is affected by weather conditions, making weather information an important determinant of…

Machine Learning · Computer Science 2023-10-16 Jonathan Yang , Mingjian Tuo , Jin Lu , Xingpeng Li

The dynamics of power consumption constitutes an essential building block for planning and operating energy systems based on renewable energy supply. Whereas variations in the dynamics of renewable energy generation are reasonably well…

Short-term load forecasting is a critical element of power systems energy management systems. In recent years, probabilistic load forecasting (PLF) has gained increased attention for its ability to provide uncertainty information that helps…

Machine Learning · Computer Science 2019-03-27 Qicheng Chang , Yishen Wang , Xiao Lu , Di Shi , Haifeng Li , Jiajun Duan , Zhiwei Wang

Electric load forecasting is essential for power management and stability in smart grids. This is mainly achieved via advanced metering infrastructure, where smart meters (SMs) are used to record household energy consumption. Traditional…

Machine Learning · Computer Science 2024-11-19 Ratun Rahman , Neeraj Kumar , Dinh C. Nguyen

Short-term load forecasting is of paramount importance in the efficient operation and planning of power systems, given its inherent non-linear and dynamic nature. Recent strides in deep learning have shown promise in addressing this…

Machine Learning · Computer Science 2023-09-20 Paapa Kwesi Quansah , Edwin Kwesi Ansah Tenkorang

Long-term load forecast (LTLF) for area distribution feeders is one of the most critical tasks frequently performed in electric distribution utility companies. For a specific planning area, cost-effective system upgrades can only be planned…

Systems and Control · Electrical Eng. & Systems 2020-07-02 Ming Dong , Jian Shi , QingXin Shi

The increasing global demand for clean and environmentally friendly energy resources has caused increased interest in harnessing solar power through photovoltaic (PV) systems for smart grids and homes. However, the inherent unpredictability…

Machine Learning · Computer Science 2023-10-24 Saman Soleymani , Shima Mohammadzadeh

Precise energy load forecasting in residential households is crucial for mitigating carbon emissions and enhancing energy efficiency; indeed, accurate forecasting enables utility companies and policymakers, who advocate sustainable energy…

Machine Learning · Computer Science 2024-11-25 Ahmed Ala Eddine Benali , Massimo Cafaro , Italo Epicoco , Marco Pulimeno , Enrico Junior Schioppa

In electricity markets, retailers or brokers want to maximize profits by allocating tariff profiles to end consumers. One of the objectives of such demand response management is to incentivize the consumers to adjust their consumption so…

Machine Learning · Computer Science 2022-02-14 Jyoti Narwariya , Chetan Verma , Pankaj Malhotra , Lovekesh Vig , Easwara Subramanian , Sanjay Bhat

Generation and load balance is required in the economic scheduling of generating units in the smart grid. Variable energy generations, particularly from wind and solar energy resources, are witnessing a rapid boost, and, it is anticipated…

Machine Learning · Computer Science 2017-04-07 Mohamed Abuella , Badrul Chowdhury

Advancements in smart metering technologies have significantly improved the ability to monitor and manage water utilities. In the context of increasing uncertainty due to climate change, securing water resources and supply has emerged as an…