Reliability Studies of Distribution Systems Integrated with Energy Storage
Date
2019-01-10
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
ORCID
0000-0003-0823-244X
Type
Thesis
Degree Level
Masters
Abstract
The integration of distributed generations (DGs) - renewable DGs, in particular- into distribution networks is gradually increasing, driven by environmental concerns and technological advancements. However, the intermittency and the variability of these resources adversely affect the optimal operation and reliability of the power distribution system. Energy storage systems (ESSs) are perceived as potential solutions to address system reliability issues and to enhance renewable energy utilization. The reliability contribution of the ESS depends on the ownership of these resources, market structure, and the regulatory framework. This along with the technical characteristics and the component unavailability of ESS significantly affect the reliability value of ESS to an active distribution system. It is, therefore, necessary to develop methodologies to conduct the reliability assessment of ESS integrated modern distribution systems incorporating above-mentioned factors. This thesis presents a novel reliability model of ESS that incorporates different scenarios of ownership, market/regulatory structures, and the ESS technical and failure characteristics. A new methodology to integrate the developed ESS reliability model with the intermittent DGs and the time-dependent loads is also presented. The reliability value of ESS in distribution grid capacity enhancement, effective utilization of renewable energy, mitigations of outages, and managing the financial risk of utilities under quality regulations are quantified. The methodologies introduced in this thesis will be useful to assess the market mechanism, policy and regulatory implications regarding ESS in future distribution system planning and operation.
Another important aspect of a modern distribution system is the increased reliability needs of customers, especially with the growing use of sensitive process/equipment. The financial losses of customers due to industrial process disruption or malfunction of these equipment because of short duration (voltage sag and momentary interruption) and long duration (sustained interruption) reliability events could be substantial. It is, therefore, necessary to consider these short duration reliability events in the reliability studies. This thesis introduces a novel approach for the integrated modeling of the short and long duration reliability events caused by the random failures. Furthermore, the active management of distribution systems with ESS, DG, and microgrid has the potential to mitigate different reliability events. Appropriate models are needed to explore their contribution and to assist the utilities and system planners in reliability based system upgrades. New probabilistic models are developed in this thesis to assess the role of ESS together with DG and microgrid in mitigating the adverse impact of different reliability events. The developed methodologies can easily incorporate the complex protection settings, alternate supplies configurations, and the presence of distributed energy resources/microgrids in the context of modern distribution systems.
The ongoing changes in modern distribution systems are creating an enormous paradigm shift in infrastructure planning, grid operations, utility business models, and regulatory policies. In this context, the proposed methodologies and the research findings presented in this thesis should be useful to devise the appropriate market mechanisms and regulatory policies and to carry out the system upgrades considering the reliability needs of customers in modern distribution systems.
Description
Keywords
Distribution system reliability, distributed generation, electricity market, energy storage, microgrid, momentary interruption, protection system, renewable energy, sustained interruption, voltage sag
Citation
Degree
Master of Science (M.Sc.)
Department
Electrical and Computer Engineering
Program
Electrical Engineering