Data analyzed in "Data-driven planning of distributed energy resources amidst socio-technical complexities."
- New distributed energy resources (DER) are rapidly replacing centralized power generation due to their environmental, economic and resiliency benefits. Previous analysis of DER systems have been limited in their ability to account for socio-technical complexities, such as intermittent supply, heterogeneous demand and balance-of-system cost dynamics. Here we develop ReMatch, an interdisciplinary modeling framework, spanning engineering, consumer behavior and data science, and apply it to 10,000 consumers in California, USA. Our results show that deploying DER would yield nearly a 50% reduction in the levelized cost of electricity (LCOE) over the status quo even after accounting for socio-technical complexities. We abstract a detailed “matching” of consumers to DER infrastructure from our results and discuss how this matching can facilitate the development of smart and targeted renewable energy policies, programs and incentives. Our findings point to the large-scale economic and technical feasibility of DER and underscore the pertinent role DER can play in achieving sustainable energy goals.
|Type of resource
|Jain, Rishee K.
|distributed energy resources
|energy infrastructure planning
|Department of Civil & Environmental Engineering
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- Preferred Citation
- Jain, Rishee K. and Qin, Junjie and Rajagopal, Ram. (2015). Data analyzed in "Data-driven planning of distributed energy resources amidst socio-technical complexities." Stanford Digital Repository. Available at: http://purl.stanford.edu/ch101zb1823
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