Date of Award

Spring 5-1-2023

Document Type

Geospatial Analysis Masters Capstone

Degree Name

Master of Science

Department

Geography

Department Chair or Program Director

Gallagher, Jackie

First Advisor

Marco Millones, Ph.D

Second Advisor

Ping Yin, Ph.D.

Third Advisor

Jackie Gallagher, Ph.D.

Major or Concentration

Geospatial Analysis

Abstract

As urbanization and energy consumption increase, the need to transition from fossil fuels to renewable energy has become urgent. Achieving sustainable energy consumption practices through solar energy has become an increasingly viable option in the United States (US). One of the ways to facilitate this transition at the local scale is to utilize Geographic Information Systems (GIS) to estimate the solar power potential and assess the spatial distribution of electrical power generation hot spots. At an urban residential neighborhood scale, GIS can aid the planning and location of efficient rooftop solar systems that have the ability to harvest the maximum amount of solar energy (Hestnes 1999).

This study aims to determine the suitability for the installation of rooftop photovoltaic (PV) systems based on their solar potential and corresponding electricity generation potential within a residential neighborhood in Cleveland Park, in the District of Columbia (D.C.). To achieve this goal, the Area Solar Radiation tool was utilized to produce a one year estimate of the total solar radiation that rooftops within the neighborhood receive. Thresholds for factors like slope, aspect, solar radiation receipt, and surface area were then applied to remove unsuitable surfaces resulting in a layer portraying suitable surfaces for rooftop solar panels. Using suitable surfaces, a conversion formula was then applied to calculate the electrical power production per individual suitable rooftops throughout the neighborhood. In addition, a hot spot analysis was performed to locate hot spots of electrical power production within the neighborhood, which was used in tandem with the Median Center tool to identify the best location for a battery storage facility for excess electrical power. ArcGIS Online was then used to create an interactive 2D web app of the solar power potential of the Cleveland Park neighborhood to portray the ability of the neighborhood to convert to solar development. The web app enables residents and solar panel developers to assess solar radiation levels and electrical power production in order to best design a rooftop solar array that harvests the maximum amount of solar radiation.

Following analysis, 202,168 m2 of unsuitable rooftop surfaces were removed from the study area. Results highlighted that, of 1,997 buildings, 1,110 (55%) were suitable for rooftop PV systems based on the criteria applied. The estimation returned that the suitable rooftops received 71,677.5 megawatt hours (MWh) of solar radiation which produced 9,862 MWh of electricity annually. The Cleveland Park neighborhood suitable buildings could produce an average of 8.9 MWh per year from solar radiation, which could cover 84% of the average yearly US household electrical consumption needs if they were to all be equipped with rooftop solar panels. Additionally, the hot spot analysis identified high productions of electrical power production primarily in the northeastern and southeastern regions of the study area along Connecticut Avenue Northwest (NW), and areas of low production in the northwestern region of the study area. Based on the results of the hot spot analysis, the optimal location for a battery storage facility was determined to be in the eastern region of the neighborhood near Connecticut Ave. NW. The resulting GIS layers from the analysis were successfully brought into a web app which provides users with the ability to assess the solar potential of the neighborhood based on solar radiation receipt and electricity production.

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