Ecological Network Analysis of State-Level Energy Consumption in Maryland, USA

Graham Hyde and Brian D. Fath ()
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Graham Hyde: Department of Physics, Astronomy & Geosciences, Towson University, Towson, MD 21252, USA
Brian D. Fath: Department of Biological Sciences, Towson University, Towson, MD 21252, USA

Energies, 2022, vol. 15, issue 16, 1-24

Abstract: Renewable and clean energy sources are being integrated into the United States’ modern energy industry to mitigate climate change effects, creating a more complex network of energy production, distribution, and consumption. This study defines the state of Maryland’s energy industry as a network of producers and consumers and analyzes the network’s characteristics by using ecological network analysis (ENA), an analytical tool useful for identifying a system’s indirect effects. The energy industry within Maryland is analyzed over a nine-year time span to understand how its evolution is influencing the network’s characteristics. Maryland’s renewable portfolio standard (RPS) for the year 2030 is then simulated by adjusting renewable and non-renewable energy sources according to energy trends and related state policy. Results from the ENA over the nine-year period of 2010–2019 indicate that the energy industry is highly linear. While typical cycling indices range from 5–15% in ecological energy flow models, cycling indices in this study ranged from 0.007% to 0.0082%. Maryland’s energy industry in the year 2030 is simulated and displays increased cycling because renewable sources typically feed the electricity sector for energy distribution, increasing indirect pathways within the system. The percentage of electricity generated by renewable energy increased from 9.71% in 2019 to 50% in 2030, as mandated in the RPS. Network analyses here emphasize the large gap between Maryland’s current energy infrastructure and what is necessary to meet its renewable targets in 2030. Furthermore, they indicate that a more uniform distribution of energy to consumers may increase efficiency in modern energy industries.

Keywords: ecological network analysis; cycling; total system throughflow; renewable portfolio standard (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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