Date of Degree
MS (Master of Science)
Electrical and Computer Engineering
Within the broad topical designation of “smart grid,” research in demand response, or demand-side management, focuses on investigating possibilities for electrically powered devices to adapt their power consumption patterns to better match the availability of intermittent renewable energy sources, especially wind. Devices such as battery chargers, heating and cooling systems, and computers can be controlled to change the time, duration, and magnitude of their power consumption while still meeting workload constraints such as deadlines and rate of throughput. This thesis presents a system by which a computer server, or multiple servers in a data center, can estimate the power imbalance on the electrical grid and use that information to dynamically change the power consumption as a service to the grid. Implementation on a testbed demonstrates the system with a hypothetical but realistic usage case scenario of an online video streaming service in which there are workloads with deadlines (high-priority) and workloads without deadlines (low-priority). The testbed is implemented with real servers, estimates the power imbalance from the grid frequency with real-time measurements of the live outlet, and uses a distributed, real-time algorithm to dynamically adjust the power consumption of the servers based on the frequency estimate and the throughput of video transcoder workloads. Analysis of the system explains and justifies multiple design choices, compares the significance of the system in relation to similar publications in the literature, and explores the potential impact of the system.
Traditionally, in the electrical power grid, generators must change the amount of power they generate in order to match the amount of power used by consumers (loads). In such a system, some generators are continually ramping up and down their output in order to match demand which is not fuel efficient. Moreover, wind power generators compound the variability of the generation-load imbalance due to the intermittent nature of wind power. Demand response proposes that electrical loads can participate in generation-load balancing by changing how much power they consume in order to allow fuel powered generators to run closer to a more efficient constant rate. Computer servers in data centers are good candidates as demand responsive loads due to their ability to quickly change their power consumption and the fact that many of their computational jobs are deferrable, meaning they can be processed later. Distributed demand response is an approach that allows each device in a network to make its own control decisions while at the same time acting in collaboration with other devices to produce a desired result on the aggregate. This thesis presents an experimental demonstration of a distributed control algorithm for servers to participate in demand response.
publicabstract, Deferrable Load, Demand Response, Distributed Control, Generation-Load Balancing, Integration of Renewable Power Generation, Power Grid
Copyright 2015 Joseph Edward Hall