A Scoping Review of Energy Load Disaggregation

Tolnai, Balázs András; Ma, Zheng; Jørgensen, Bo Nørregaard

doi:10.1007/978-3-031-49011-8_17

Cited by 3 publications

(1 citation statement)

References 85 publications

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“…If any article was in the scope but poorly written, the article would be kept for full text searching and analysis. Because only the scope of an article needed to be identified during this step, the abstracts provided enough information regarding the relevance of the scope of a scientific publication [20]. This step resulted in 68 articles being removed and 44 articles remaining.…”

Section: Methodsmentioning

confidence: 99%

A Scoping Review of Energy-Efficient Driving Behaviors and Applied State-of-the-Art AI Methods

Ma,

Jørgensen,

2024

Energies

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The transportation sector remains a major contributor to greenhouse gas emissions. The understanding of energy-efficient driving behaviors and utilization of energy-efficient driving strategies are essential to reduce vehicles’ fuel consumption. However, there is no comprehensive investigation into energy-efficient driving behaviors and strategies. Furthermore, many state-of-the-art AI models have been applied for the analysis of eco-friendly driving styles, but no overview is available. To fill the gap, this paper conducts a thorough literature review on ecological driving behaviors and styles, and analyzes the driving factors influencing energy consumption and state-of-the-art methodologies. With a thorough scoping review process, thirty-seven articles with full text were assessed, and the methodological and related data are compared. The results show that the factors that impact driving behaviors can be summarized into eleven features including speed, acceleration, deceleration, pedal, steering, gear, engine, distance, weather, traffic signal, and road parameters. This paper finds that supervised/unsupervised learning algorithms and reinforcement learning frameworks have been popularly used to model the vehicle’s energy consumption with multi-dimensional data. Furthermore, the literature shows that the driving data are collected from either simulators or real-world experiments, and the real-world data are mainly stored and transmitted by meters, controller area networks, onboard data services, smartphones, and additional sensors installed in the vehicle. Based on driving behavior factors, driver characteristics, and safety rules, this paper recommends nine energy-efficient driving styles including four guidelines for the drivers’ selection and adjustment of the vehicle parameters, three recommendations for the energy-efficient driving styles in different driving scenarios, and two subjective suggestions for different types of drivers and employers.

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Section: Methodsmentioning

confidence: 99%

A Scoping Review of Energy-Efficient Driving Behaviors and Applied State-of-the-Art AI Methods

Ma,

Jørgensen,

2024

Energies

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Standard Energy Data Competition Procedure: A Comprehensive Review with a Case Study of the ADRENALIN Load Disaggregation Competition

Tolnai,

Ma,

Jørgensen

2023

Lecture Notes in Computer Science

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Crowdsourcing data science competitions has become popular as a cost-effective alternative to solving complex energy-related challenges. However, comprehensive reviews on hosting processes remain scarce. Therefore, this paper undertakes a detailed review of 33 existing data competitions and 12 hosting platforms, complemented by an in-depth case study of the ADRENALIN load disaggregation competition. The review identifies essential elements of competition procedure, including platform selection, timeline, datasets, and submission and evaluation mechanisms. Based on proposed 16 evaluation criteria, the similarities and differences between data competition hosting platforms can be categorized into platform scoring and popularity, platform features, community engagement, open-source platforms, region-specific platforms, platform-specific purposes, and multi-purpose platforms. The case study underscores strategic planning's critical role, particularly platform selection. The case study also shows the importance of defining competition scope which influences the whole competition content and procedure, especially the datasets.

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