论文部分内容阅读
With increasing apprehensions about environment and energy independence problems,more and more renewable energy resources such as wind and solar are anticipated to be incorporated into the future power grid.The balance between demand and supply could be troubled by the integration of renewable generation on large scale,because renewable energy resources have intermittent and inadequate dispatch-ability.To uphold grid reliability,outdated approaches include adding more operating assets such as fast-responsive generators,which in turn incurs an enlarged cost and meanwhile reduce the environmental benefits of renewable energy resources.By leveraging the flexibility of energy storage system and loads in grid-wide services,in this thesis,an alternative solution is considered to combat the sporadic nature of renewable energy resources.The over-all objective of this thesis is to facilitate the macro-scale renewable energy resources integration,so as to enhance the long-standing performance of power grids(e.g.,reliability,cost effectiveness)with the support of innovative smart grid technologies(e.g.,information technology,control,and economics).Numerous challenges are come across,such as uncertain nature of system,time coupling of system’s operational constraints,and large scale of power grids in achieving this objective.To accommodate a wide continuum of vital characteristics of a power system,this work builds on more comprehensive system models.System’s uncertainty(e.g.,uncertainty of renewable generation,electricity price,and loads)is explicitly incorporated into the problem formulation.We provide centralized algorithms that are easy to implement in reality,and at the same time ensure strong analytical performance for the control of energy storage,fix and controllable loads.