New River Light and Power Data: A Data Ecosystem for Electric Power Systems Research (I1.A4)

Ed Hassler,Preston Macdonald,Jamie Russell,Joseph Cazier

doi:10.51269/ecmu2283

Abstract

This article provides data useful for electric power systems research by students, faculty and the community to download or to use in a cloud-based analytics environment with state of the art analytics tools. The work includes carefully cleaning, documenting, preparing and enriching 12+ years of non-personally identifiable substation data for the 5 substations managed by New River Light and Power (NRLP), a non-profit electric utility operated by Appalachian State University's Division of Business Affairs. This data includes bulk summary data for the aggregate 8,000+ meters NRLP manages with a record of the total energy used per substation for each hour of day. This data has been enriched with matching hourly weather and solar radiation data, town daily water and sewer flows to measure town occupancy, a list of university and community events likely to influence power consumption, and a description of each substation region.

Highlights

This paper presents hourly substation data from the town of Boone, North Carolina collected over a 13 year period from 2007 through 2020
The work includes carefully cleaning, documenting, preparing and enriching 12+ years of non-personally identifiable substation data for the 5 substations managed by New River Light and Power (NRLP), a non-profit electric utility operated by Appalachian State University's Division of Business Affairs
This data has been enriched with matching hourly weather and solar radiation data, town daily water and sewer flows to measure town occupancy, a list of university and community events likely to influence power consumption, and a description of each substation region

Summary

Introduction

This paper presents hourly substation data from the town of Boone, North Carolina collected over a 13 year period from 2007 through 2020. This data has been enriched with matching hourly weather and solar radiation data, town daily water and sewer flows to measure town occupancy, a list of university and community events likely to influence power consumption, and a description of each substation region.

Results

Conclusion