Keywordenergy use model
transportation fuel use
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AbstractWe have constructed a simple but comprehensive village energy use model that includes space heating and transportation fuel use as well as electricity. Because people in isolated remote northern communities pay about 2/3 of their overall energy bills for heat and transportation (WH Pacific et al. 2012), knowledge of overall energy demand by major end use is important when considering energy systems that can make the best use of efficiency and renewables as resources to offset costly fossil fuels. Previous work (Devine & Baring-Gould 2004) provides community planners and policy makers with a good tool for estimating community electricity demand. This paper builds on that work with an integrated model that can be used to estimate overall village energy usage based on a relatively small number of socioeconomic characteristics, such as population; number of residential, commercial and public facilities; housing and building stock characteristics; and transportation patterns and equipment types. The Alaska Village Energy Model (AVEM) model uses the best available primary data from recent collection efforts, and can easily incorporate new data that may become available."
PublisherInstitute of Social and Economic Research, University of Alaska
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Development of scalable energy distribution models to evaluate the impacts of renewable energy on food, energy, and water system infrastructures in remote Arctic microgrids of AlaskaKarenzi, Justus; Wies, Richard; Huang, Daisy; Al-Badri, Maher (2020-08)Experience and observations from remote Alaska communities have shown that energy is inarguably at the center of food, energy, and water (FEW) security. The availability of potable water, fresh produce, food storage, or processed seafood ultimately depends on a reliable and adequate energy supply. For most communities, diesel fuel is the primary source of power, which comes at high cost because of the logistics associated with importing the fuel to these relatively isolated communities. Integrating locally available renewable energy resources not only enhances energy supply, but the impacts further translate to food and water security in remote microgrids. The focus of this work is to investigate how intermittent renewable energy sources impact community level food and water infrastructure systems in a remote Arctic microgrid. Energy distribution models are mathematically developed in MATLAB® Simulink® to identify, describe, and evaluate the connections between intermittent renewable resources and the FEW loads. Energy requirements of public water systems, greenhouses, cold storage units, seafood processing loads, and modular water and food system loads are evaluated. Then energy sources including solar PV, solar thermal collectors, wind, hydro, energy storage, and diesel electric generation are modeled and validated. Finally, simulations of scenarios using distributed energy resources to serve water and food infrastructure loads are carried out including the incorporation of dispatchable loads. The results indicate that the impacts of renewable energy on FEW infrastructure systems are highly seasonal, primarily because of the variability of renewable resources. The outcome of this work helps in gaining firsthand insights into FEW system dynamics in a remote islanded microgrid setting.
Analysis of energy consumption on the environmental Kuznets curve hypothesis in the United States: does renewable energy play a role?Ohnesorge, Michelle; Little, Joseph; Baek, Jungho; Greenberg, Joshua (2018-05)Using CO₂ emissions as a representation of environmental degradation an empirical econometric analysis is conducted to see if there is evidence of an Environmental Kuznets Curve in the United States and if renewable energy consumption plays a significant role in CO₂ emission mitigation. The renewable energy consumption variable was broken down further to isolate geothermal, hydroelectric, biomass, solar, and wind energy consumption and explore their role in the analysis. An Auto-Regressive Distributed Lag approach to cointegration with Pooled Mean Groups and Mean Groups estimations was used on U.S. state (including District of Columbia) specific data from 1987 to 2015 to calculate the long and short run results that would support an Environmental Kuznets Curve hypothesis. The panel of states was divided into low, medium, and high GDP brackets as disaggregate models and those were examined along with a model of the entire United States. Evidence for an Environmental Kuznets Curve for the United States could not be established in the aggregate model, however it was found that renewable energy consumption did have a negative coefficient, which indicates CO₂ emission mitigation through renewable energy consumption. Out of the individual renewable energy consumption variables tested, only wind energy consumption was found to be statistically significant while the model also exhibited evidence to support an Environmental Kuznets Curve hypothesis in this aggregate model. Looking at the different GDP state brackets, low GDP states were the only bracket that yielded evidence of an Environmental Kuznets Curve in the disaggregate models. For estimations with the low GDP states bracket looking at the individual renewable energy consumption variables, hydroelectric, biomass, solar, and wind energy consumption variables were statistically significant as well. The medium GDP bracket states aggregate model did not yield conclusive results, stemming from the lack of slope in the GDP variable for this model. Out of the individual renewable energy consumption variables tested in the subset, biomass was the only energy consumption to be statistically significant while the model exhibited evidence of an Environmental Kuznets Curve. The high GDP bracket aggregate model did not yield results showing evidence of an Environmental Kuznets Curve, while the individual renewable energy consumption variable subset models geothermal and wind energy consumption were statistically significant within models showing evidence of an Environmental Kuznets Curve. Breaking out these separate renewable energy consumption variables in an Environmental Kuznets Curve analysis can provide empirical support for policy and investment in specific renewable energy technology.
Aligning electricity energy policies in Alaska: analysis of the power cost equalization and renewable energy fund programsVillalobos Meléndez, Alejandra; Little, Joseph; Huskey, Lee; Baek, Jungho (2012-05)Most rural Alaska communities are not road connected and must cope with challenging arctic environmental conditions. Due to their remoteness and sparse populations, these villages depend on isolated non-grid connected electric generation systems that operate on fuel oil. In Alaska, the Power Cost Equalization program is a 25 year long energy subsidy that targets rural residents to provide energy costs relief. A more recent state incentive program, the Renewable Energy Fund, was developed to expand the use of renewable resources and lower the cost of energy. Some rural communities have benefited from this program and have integrated renewable energy to their systems, particularly installing Wind-Diesel systems. Both programs have congruent goals of alleviating dependence on high cost fossil fuels to generate electricity as means to foster development and higher quality of life in rural Alaska communities. However, their incentive structure may conflict. This paper provides a review of these two energy subsidy policies with a particular focus on the Power Cost Equalization program and offers potential changes to its structure such that social cost impacts to rural residents are minimized while removing incentive barriers against energy efficiency and integration of renewable energy in rural Alaska communities.