PROMOTING DISTRIBUTED ENERGY DEPLOYMENT AND DIFFUSION FOR SUSTAINABLE CIVIL INFRASTRUCTURE USING MULTI-AGENT BASED MODELING AND QUANTITATIVE ANALYTICS
2022
- 24Usage
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
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Thesis / Dissertation Description
"Distributed Solar Generation (DSG) using small-scale Photo-Voltaic (PV) is an evolving technology with increasingly growing market penetration due to its significant benefits to consumers and broader power systems. DSG is sustainable, provides reliability, and is cost-effective where solar energy is abundant. However, the increasingly growing adoption of DSG creates uncertainties in forecasting electric power demand and market behavior. It also causes concerns of a “utility death spiral”. To this end, the goal of this research is to critically analyze the diffusion and benefits of DSG in the electric power infrastructure as a complex System-of-Systems (SoS). Specifically, this dissertation addresses the following five objectives: (1) investigating the relationship between the electric power sector and socio-economic parameters; (2) developing a complex simulation of electric power infrastructure and market impacted by the adoption of DSG; (3) exploring dynamic pricing by generating companies and the occurrence of a utility death spiral; (4) studying the impact of incentives on the adoption of DSG using complex sensitivity analysis; and (5) examining the benefits of DSG in reducing the vulnerability of the power infrastructure against natural disasters. As such, and as shown from the results, this research provided a novel holistic investigation of the complex relationship between DSG adoption and the electric power market and infrastructure in a multidisciplinary approach that combines infrastructure engineering, electric power engineering, economics, social science, machine learning, and computer modeling. The findings should benefit researchers, power system operators, and policy makers towards a sustainable DSG diffusion"-- Abstract, p. iv
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