We address strategies of retrofitting the urban building stock. We propose a novel ranking algorithm that allows the scaling of the buildings’ energy consumption from records of energy bills with building footprint and physical attributes of heat losses to the size of national and global sustainability goals. The method entails a statistical screening of the intricate interplay between natural, infrastructural, spatial, and behavioral variables to determine building gas energy consumption and potential savings at city scale. Implemented for 6,204 residential buildings in Cambridge, MA, we demonstrate that the proposed ranking algorithm based on the inferred heat loss rate of buildings exhibits a power-law data distribution akin to Zipf’s Law, which provides a means to map an optimum path for energy savings per retrofit at city scale.
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In regards of electric consumption, we investigate distributed energy resources (DERs). The ultimate goal is the local matching of demand and generation in the form of microgrids, for battling the instabilities that grid infrastructures face against the ever-increasing demand and adoption of intermittent renewable energy sources. Among DERs, solar photovoltaics are gaining more and more popularity as a clean and affordable distributed generation option. In our research project, we aim to address the impending challenges on power infrastructures
from the point of view of implementing solar-powered microgrids in the urban context, where existing consumers that are part of the distribution grid are also part of local microgrid neighborhoods. We propose to employ DC power flow as the network dynamics and use real generation and demand profiles of users in the city, modeled after high temporal-resolution smart-grid data, to propose optimized microgrid topologies that benefit both the consumer and the grid while being resilient against failures. We plan to have a versatile simulation scheme that is portable to any city, and use it firsthand on real data from the city of Rio de Janeiro in Brazil. We believe the proposed research fills an important gap in literature, linking the engineering viewpoint with a complex systems approach by proposing a data-driven, urban-scale, optimization based approach that we hope will ultimately impact urban planning policies in the adoption and effective utilization of solar microgrids.
Keep tuned, we’ll add more information on these projects soon!