Date of Award
Master of Science
Jun Zhang, Xiao Qin
Electrical Power System, Reliability Analysis, Smart Grid, Water Distribution Network
With the rapid growth of population, the modern human society is becoming more and more dependent on the proper operation of critical infrastructures - the interconnected electrical power system, the drinking water distribution and supply system, the natural gas transmission and distribution system, and so forth. It has become an important issue to maintain reliable functions of these critical systems. As a result, comprehensive reliability evaluation is highly needed to quantify their reliability in an objective manner. Conventionally, deterministic criteria were used in reliability evaluations. However, it lacked the ability to model and quantify the stochastic nature of system behaviors such as component failures. In light of these facts, this thesis deploys probabilistic methodologies for conducting quantitative reliability modeling and assessment for nation’s critical infrastructures including electrical power networks incorporating smart grid technologies and water distribution networks.
Power system operators are faced with the increasingly complicated operating conditions in bulk power systems. Yet due to the huge investment needed to build new power delivery facilities, cost-effective solutions such as new operational strategies are becoming more attractive and viable in recent years. Optimal transmission switching (OTS) and dynamic thermal rating (DTR) are two such technologies which offer a potential solution to improving the power system reliability by more fully utilizing the existing power delivery assets. In this thesis, these two technologies are first discussed, which are then incorporated into the power system reliability evaluation procedure. Case studies are conducted on modified RTS-79 and RTS-96 systems using MATLAB and IBM CPLEX. The obtained simulation results have shown that with the enforcement of either OTS or DTR technology, the overall system reliability can be improved, and system reliability can be further improved if both technologies are enforced.
The growing urban population has brought great stress to the aging drinking water distribution systems. It is becoming more challenging to maintain a reliable drinking water distribution system so as to meet the growing water demand. Thus, a comprehensive reliability evaluation of the aging water delivery infrastructure is of critical importance to enable informed decision-making in asset management of the potable water sector. This thesis also proposes a probabilistic reliability evaluation methodology for water distribution systems based on Monte Carlo simulation (MCS) that takes into account both mechanical failures and hydraulic failures. Additionally, a C++ based software tool is developed to implement the proposed method. Case studies based on two representative water distribution systems are performed to demonstrate the effectiveness of the proposed method.
A comparison is made between the reliability analysis of electrical power systems and that of water distribution systems. As interconnected capacitated networks, both systems share similarities in certain aspects such as component modeling and adequacy constraints. However, the specific features of the target systems should also be taken into consideration in the reliability modeling and evaluation in order to obtain a more comprehensive and accurate estimation of the actual system reliability.
Xiao, Ruosong, "Probabilistic Reliability Analysis of Electric Power Systems with Smart Grid Technologies and Water Distribution Networks: Modeling, Assessment, and Comparison" (2016). Theses and Dissertations. 1322.
Available for download on Wednesday, August 30, 2017