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Secondary distribution systems provide electrical energy at the utilization voltage levels from distribution transformers to customer meters. Typical secondary voltages in the United States include 120/240 V for residential use, 208Y/120 V for residential and commercial use, and 480Y/277 V for industrial and high-rise commercial use.
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Power system distribution involves delivering electrical energy from power plants to consumers through a network of transmission and distribution systems. The process begins at power plants, where energy from coal, gas, nuclear, water, and wind is converted into electrical energy. These plants use three-phase generators, typically rated between 50 to 1300 MVA, with terminal voltages ranging from a few kV to 20 kV, depending on the size and age of the units.
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Distribution reliability in electrical power systems is critical for ensuring an uninterrupted power supply to consumers at minimal cost. According to IEEE Standard Terms, reliability is the probability that a device will function without failure over a specified time period or amount of usage. For electric power distribution, this translates to maintaining continuous power supply and addressing customer concerns over power outages. Several indices, as defined by IEEE Standard 1366-2012, are...
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Primary distribution systems deliver electrical power from substations to consumers through various voltage classes, with 15-kV class voltages being predominant among U.S. utilities. Older 2.5- and 5-kV classes are being replaced by 15-kV primaries, while higher 25- to 34.5-kV classes are used in high-density urban areas and rural regions with long feeders. Three-phase, four-wire multigrounded systems are widely employed for balanced power delivery, using the neutral wire as a grounding point.
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A multi-year campus-level smart meter database.

Mingchen Li1,2, Zhe Wang3,4, Yao Qu1,2

  • 1Department of Civil and Environmental Engineering, The Hong Kong University of Science and Technology, Hong Kong SAR, China.

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|November 26, 2024
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This study presents a comprehensive campus energy dataset from HKUST, crucial for understanding electricity load patterns and improving energy efficiency. The curated data supports research in load recognition, fault detection, and forecasting.

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Area of Science:

  • Energy Management
  • Building Science
  • Data Science

Background:

  • Precise campus electricity management requires understanding building and equipment load patterns.
  • Lack of detailed electricity load data hinders energy efficiency research.
  • Optimizing energy use in academic environments is a growing concern.

Purpose of the Study:

  • To introduce a novel, research-ready energy consumption monitoring dataset from a university campus.
  • To facilitate research in campus-level energy management and efficiency.
  • To provide a foundation for studies on load patterns, fault detection, and demand response.

Main Methods:

  • Collected electricity load data from over 1400 meters across more than 20 buildings at HKUST over 2.5 years.
  • Utilized the Brick Schema curation strategy to process raw data into a standardized format.
  • Organized data to support diverse research applications in energy systems.

Main Results:

  • Developed a comprehensive dataset covering extensive campus energy consumption.
  • Successfully curated raw data into a research-ready format using a standardized schema.
  • Dataset encompasses detailed information suitable for advanced energy analytics.

Conclusions:

  • The HKUST energy consumption dataset is a valuable resource for campus energy management research.
  • The Brick Schema approach provides a scalable method for curating building energy data.
  • This dataset will advance research in energy efficiency, load forecasting, and smart grid technologies.