Investigation Of Power System Blackouts And Reliability Improvement For Power Distribution Systems
Abstract
Modern power systems often consist of thousands of equipments, each of which
may have an affect on the security of the system. The trend toward deregulation has
forced utilities to operate their systems closer to security boundaries [1]. This has fueled
the need of faster and more accurate methods of reliability and security assessment.
Power system reliability is defined as the probability that the power system will
perform the function of delivering electric power to customers adequately on a
continuous basis and with an acceptable quality [2]. Power system security assessment
deals with the system’s ability to continue to provide service in the event of an
unforeseen contingency. Security evaluation has to encompass pre-disturbance
conditions and transient performance of the system [3]. The definitions leave many detail undefined and exemplifies the ambiguity in reliability analysis. They may include
the unexpected loss of an important transmission circuit or a sudden change in a large
load. Either of which could lead to service disruption on part or entire system. The goal
of reliability and security assessment is to determine when service disruption is likely to
occur and to take steps to reduce the risk.
The fact that power system operation is subject to an enormous number of
random events that makes reliability and security analysis a rather complex issue. A
complete analytical approach to a not so precisely defined problem is practically
impossible. Monte Carlo simulation is often used as an alternative to analytical
methods. The main advantages of Monte Carlo simulation include: (1) the ability to
model very complex systems (like power systems) more accurately than analytical
methods; (2) the model is easy to build and understand; and (3) the method can
calculate both the expected value of reliability indices and their distributions [4]. The
main disadvantage of Monte Carlo simulation is that it usually requires long simulation
times in order to obtain accurate results. Due to the advance in computer technology,
parallel computation is widely used for complicated calculation. Monte Carlo
simulation is a typical application that is suitable for parallel computation. With this
method, calculation time could be greatly reduced.
This dissertation analyzes the reliability of transmission and distribution system.
First, this dissertation investigates the general features of power system
blackouts from the study of its mechanism through the employment of statistical and
probability theory. The mechanism model of blackouts is presented, and the deterministic and probabilistic factors involved in blackouts are introduced. The
probability distribution of blackouts is derived based on the mechanism model. The
implementation of sequential Monte Carlo Simulation is used to justify the validity of
proposed theory of power system blackouts. Models of transient stability analysis and
automatic generator control (AGC) are included; the model of hidden failures and
normal reliability model are also described. The theoretical proofs are provided to
justify the validity of the proposed distribution which is shown to be independent of the
definition of blackouts and the modeling of power systems. Numerical results verify the
validity of the derived probability distribution of the time to blackouts.
Second, Monte Carlo simulation is used to evaluate the quantitative impact of
automatic switches on the reliability of power distribution systems. Based on the
characteristics of the studied system’s topology, the reliability model is developed for
the implementation of Monte Carlo simulation. Reliability indices on each load are
computed to obtain an overall reliability assessment of the system, and the sensitivity of
the reliability indices to the location of automatic switches is also studied. Simulation
results are used to illustrate the validity of the approach and are compared with the
historical reliability records.