Title :
Using Storage to Minimize Carbon Footprint of Diesel Generators for Unreliable Grids
Author :
Singla, Swati ; Ghiassi-Farrokhfal, Yashar ; Keshav, S.
Author_Institution :
Comput. Sci. Dept., Carnegie Mellon Univ., Pittsburgh, PA, USA
Abstract :
Although modern society is critically reliant on power grids, modern power grids are subject to unavoidable outages. The situation in developing countries is even worse, with frequent load shedding lasting several hours a day due to a large power supply-demand gap. A common solution for residences is, therefore, to back up grid power with local generation from a diesel generator (genset). To reduce carbon emissions, a hybrid battery-genset is preferable to a genset-only system. Designing such a hybrid system is complicated by the tradeoff between cost and carbon emission. Toward the analysis of such a hybrid system, we first compute the minimum battery size required for eliminating the use of a genset, while guaranteeing a target loss of power probability for an unreliable grid. We then compute the minimum required battery for a given genset and a target-allowable carbon footprint. Drawing on recent results, we model both problems as buffer sizing problems that can be addressed using stochastic network calculus. Specifically, a numerical study shows that, for a neighborhood of 100 homes, we are able to estimate the storage required for both the problems with a fairly small margin of error compared to the empirically computed optimal value.
Keywords :
carbon capture and storage; diesel-electric generators; hybrid power systems; load shedding; numerical analysis; power generation reliability; power grids; probability; stochastic processes; buffer sizing problem; carbon emission reduction; diesel generator; genset-only system; hybrid battery-genset; load shedding; loss of power probability; numerical study; power supply-demand gap; stochastic network calculus; target-allowable carbon footprint minimization; unreliable power grid; Batteries; Carbon dioxide; Diesel engines; Performance evaluation; Power demand; Power system faults; Power system reliability; Smart grids; Batteries; diesel engines; performance analysis; power demand; power system reliability; smart grids;
Journal_Title :
Sustainable Energy, IEEE Transactions on
DOI :
10.1109/TSTE.2014.2345613