Modelling Energy Conservation and COcapture and biomass gasification.
Pathways of Sustainable Development between Business and Society.
The latter creates a tremendous number of controllable intelligent endpoints such as smart buildings and appliances, electric vehicles, energy storage devices, and power electronic devices that can sense, compute, communicate, and actuate.
Most of these endpoints are distributed on the load side of power systems, in contrast to traditional control resources such as centralized bulk generators.
By exploiting distributed algorithms to solve OLC and analyzing convergence of these algorithms, we design distributed load-side controllers and prove stability of closed-loop power systems governed by these controllers.
This general framework is adapted and applied to different types of power systems described by different models, or to achieve different levels of control goals under different operation scenarios.
Corporate strategies to mitigate climate change- two essays on practices in Swedish energy-intensive companies.
Perspectives on future bioenergy use and trade in a European policy context .
This thesis focuses on controlling power systems in real time, using these load side resources. (1) Distributed load-side frequency control: We establish a mathematical framework to design distributed frequency control algorithms for flexible electric loads.
In this framework, we formulate a category of optimization problems, called optimal load control (OLC), to incorporate the goals of frequency control, such as balancing power supply and demand, restoring frequency to its nominal value, restoring inter-area power flows, etc., in a way that minimizes total disutility for the loads to participate in frequency control by deviating from their nominal power usage.