BitTorrent-inspired management of residential distributed energy resources

Abstract

Distributed resources such as solar PV, Li-ion batteries, fuel cell systems, and large flexible loads such as water heaters and HVAC equipment could, if properly managed, provide a significant resource to the grid and consumer for peak-shaving, load- balancing, and resiliency during blackouts. However, due to the tremendous number of possible devices of this class, it becomes necessary and practical to pursue a distributed management strategy. In this work we show that BitTorrent, a popular Internet filesharing protocol, can be modified to provide such a strategy. This is demonstrated through simulation with BTPower, a platform developed to simulate BitTorrent-like networks of homes with distributed energy resources.

Finally, we show that Li-ion cells can be reclaimed from electronic waste, such as dead laptop batteries, and re-configured inexpensively for a secondary application such as home energy storage or even electric vehicles.

We also show that hardware that is now commonly available due to the Internet-of- Things revolution can be used to add controllability and intelligence to standard household loads, such as a window air conditioner. Powerful new microcomputers, such as the Raspberry Pi, allow for advanced control algorithms such as model predictive control to be used to operate these connected loads in a truly ‘smart’ manner by interfacing them with real-time electricity pricing, weather forecasting, and wireless sensor networks.

Ubiquitous IP-connectivity and low-power, high-performance mobile computing hardware (the so-called "Internet-of-things") enables exciting new opportunities for adding sophisticated operational modes to a wide array of traditionally passive devices. At the same time, the electric power grid is being challenged by integration of renewables, charging of electric vehicles, and increasingly strict environmental regulations. These things, combined with a rising consumer interest in sustainable energy, provide the motivation for developing intelligent loads and generators at all levels, including residential.