AbstractsPhysics

Research Doctorate - Doctor of Philosophy (PhD) In recent years, power system has been undergoing rapid development. One of the most significant trends of modern power system is the increasing penetration of the renewable energy sources. Most common renewable energies include the wind power, solar power, etc. The integration of renewable energy can lower the CO2 emission and release the pressure of the global climate warming. However, the stochastic nature and uncertain power output of many kinds of renewable energy sources challenge the grid in the aspects of effective data collection and analysis, system dispatch, and system stability and security. This research focuses on studying the advanced analysis methods to address the challenges of the power system with high penetration of renewable energy, mainly including three parts: architecture of the new information infrastructure, new system dispatch methods, and new system stability and security analysis methods. In the first part, this work first proposes a cloud computing-based information infrastructure for the next-generation power system with high penetration of renewable energy and deployment of smart grid. The operation model of the infrastructure and the structure of the power cloud data center are discussed in details. The major benefits of the proposed infrastructure to power system are analyzed as well. To demonstrate how the proposed information infrastructure can be used to integrate renewable energy into system operation, a cloud computing based distributed bargaining framework is proposed for the micro grids and the distribution utilities. Compared with currently centralized computing mode, the proposed cloud based bargaining framework is more secure, data-centric and scalable. In the second part, this research studies the new methods of the system dispatch with high penetration of renewable energy. This research mainly studies two problems. The first one is the dispatch of the wind farm with a battery energy storage system (BESS) and the second one is the unit commitment (UC) model by considering the probabilistic wind generation. For the wind farm dispatch problem, a novel short-term dispatch scheme is proposed for dispatching the charge/discharge behaviors of the BESS to better mitigate the wind power forecast uncertainties than the traditional method. The methodology of determine the necessary power and energy capacities of the BES under the proposed dispatch scheme is also discussed. For the UC problem, a UC framework is proposed by integrating the stochastic model of the wind power generation. A novel algorithm called Fuzzy Adaptive Particle Swarm Optimization (FAPSO) is also developed to solve the model. In order to enhance the performance of the FAPSO algorithm, a cloud computing based parallel computational framework is developed for the FAPSO algorithm. The parallel frame work is implemented on top of the Amazon Elastic Cloud (Amazon EC2). In the third part, this research studies some new methods to do fast and robust online system…