Currently, electrical power distribution systems rely on permanently energized grids - electricity is transmitted constantly from the provider to users. Consequently, loads can be connected to the power grid without prior consent from the provider, giving rise to discretionary load access and thereby straining the grid's stability. Safety margins are required to satisfy sudden and spontaneous demands. At the same time, the intermittent availability of renewable sources adds yet another pressing condition on balancing existing grids. Finally, the discretionary and essentially unrestricted access to power comes at the price of grid vulnerabilities, such as cascading failures. The PIs propose a proactive digital management approach to the power grid called the controlled-delivery grid (CDG), which is cognizant of the load before energy is delivered. Users have specific addresses and issue requests for energy in advance and for a specific duration of time in the CDG. Distribution points then manage the amount and duration of energy delivery. The PIs central hypothesis is that techniques derived from network management and control research can be applied to the smart grid enabling more efficient, more robust, and more secure delivery of energy. This high-risk / high-reward proposal will investigate feasibility of this approach. Through the implementation and use of a micro-grid test bed, the PIs propose to analyze the feasibility of fusion of digital data and high-voltage signals and demonstrate seamless integration of alternative energy sources (e.g., solar energy) with the micro-grid while using the CDG's framework. The PIs will also study methods for allocation and distribution of electrical power for a CDG framework. The novel concept ascertains targeted delivery of energy to specific users, thus simultaneously minimizing overall power overhead and conservation of non-renewable energy resources. This new grid will also increase robustness against failures and enable sudden resumption of service through proactive surge management, an ability to negotiate reduced power rates in return for lower consumption in real time, and an ability to route energy from alternative sources back to the grid without compromising grid stability.
|Effective start/end date||8/15/16 → 7/31/18|
- National Science Foundation