Energy routing on the future grid: A stochastic network optimization approach

Abstract

Population expansion and broad deployment of wind and solar renewable power generation has highlighted concerns over the long-standing strategy for grid deployment, expansion and upgrade. Due to their stochastic and often volatile nature, these renewable sources are difficult to integrate into the grid in its current power-on-demand paradigm. In this work, we propose a novel stochastic framework, leveraging distributed storage, that alleviates many of the problems of the current grid. Our proposed energy routing algorithm is distributed, agile to failures, and provably maximizes the carrying capacity of the existing power-line resources. We evaluate the performance of our proposed solution using analytical performance guarantees and sample simulation results. We hope the the result of our work provides a strong motivation for further development and application of large scale distributed storage.