Optimization of Energy Storage for Frequency Control in Autonomous AC Power Systems – Frameworks for Planning and Operation

Abstract

AC power systems have been designed to balance active power from the generation side, adopting technologies that offer three important properties: dispatch capability, ability to participate in frequency control, and large energy storage capacity. Such technologies have been displaced by variable renewable energy sources, such as wind and solar power, interfaced to the system via power electronic converters, which do not offer concurrently the three key properties of established equipment, thus introducing new dilemmas for planning and operation of power systems. Alternative schemes are being deployed to increase control of power flows and optimize energy storage capacity. Flexible loads and distributed energy storage devices, for instance, can be coordinated by energy management systems to provide power balancing mechanisms. Such advances, on the one hand, allow adequate power dispatch, balancing reserves, and storage capacity to be reached. On the other hand, they have major technical and economic impacts, affecting capital and operational expenditures, security of supply, and power system stability. Therefore, it is necessary to review and improve the tools and methods employed for planning and operation of power systems to accommodate these changes. This issue becomes more critical in autonomous grids, where a limited number of generators and storage devices are regularly available. This thesis is a collection of eight publications addressing this challenge. Together, they: 1) review the active power balance problem and the principles of frequency control and stability in ac power systems, 2) identify gaps in current modeling practices that can affect planning and operation of autonomous systems where high penetration of variable renewable energy sources exists, and 3) explore howfrequency control and stability constraints can be integrated into different power system optimization models. The main result is a set of frameworks that can be applied to optimization problems typically employed in planning and operation of autonomous systems. They are used for optimal sizing or scheduling of equipment and for ensuring stable and secure operation under dynamic uncertainty in different case studies of industrial oil and gas installations. Despite the focus in oil and gas applications, the main ideas and propositions can be generalized and applied to other autonomous systems, such as microgrids in islanded mode.