2. Power system reliability assessment

The power system reliability is a measure of the ability of the system to meet the consumer requirements with quality electrical energy. In general "reliability" is usually divided into two aspects of system adequacy and system security [9, 10], as shown in Figure 1.

According to the North American Electric Reliability Corporation (NERC), adequacy and security are defined as [11]:

Figure 1. Power system reliability subdivision.

Adequacy—"The ability of the power system to supply the total electrical demand and power requirements of the end use customers at all times, by taking into the account of scheduled and reasonably expected unscheduled outages of system components."

Security—"The ability of the power system to withstand sudden disturbances such as electric short circuits or unexpected loss of system elements."

The work reported in this chapter is limited to adequacy assessment of the power system. The fundamental techniques used for the assessment of adequacy can be categorized in terms of their application to segments of a complete power system. These segments of the power system are shown in Figure 2 and can be defined as the functional zones of generation, transmission and distribution [12]. Hierarchical levels are formed by combining the functional zones of the power system.

The assessment of reliability at hierarchical level I (HL-I) is only concerned with the generation facilities. In this level, the total power system generation including interconnected renewable generation is examined to decide its ability to serve the total system load demand considering the possible contingencies. The reliability assessment at HL-I is usually defined as generating capacity reliability assessment. The reliability assessment at hierarchical level II (HL-II) combines both the generation and transmission in evaluation of the integrated ability of the composite power system to deliver energy to the bulk supply points. This analysis is generally termed as composite power system reliability assessment or bulk power system reliability assessment. The reliability assessment by considering all the three functional segments is

Figure 2. Structure of hierarchical level.

Keywords: composite power system reliability, failure rate, repair rate, minimal cut set,

The modern power system has become a highly complex network, due to the integration of a large number of generating sources and large transmission and distribution networks. The above-stated reasons will affect the reliability of the smart grid. The main requirement of the power system is to provide electricity for a wide range of consumers with various requirements. It is not possible to serve the consumers continuously due to the random failures of equipment in the power system network. This causes the consumers' service interruptions frequently irrespective of the planned maintenance. It affects the reliability of power supply at the consumer bus and smart grid as well. Therefore the power engineers must consider the term "reliability" at the level of designing and planning of the power system network or smart grid. Reliability is the general quality of the system and defined as "It is an ability of the system to perform a desired function within a specified period of time under stated conditions" [1]. In view of above-mentioned reasons, there is a need for complete reliability assessment of the present power system. The evaluation of reliability plays an important role in power system analysis, design, upgrades and operations, especially in bulk power system. Power system reliability assessment methods have been developed over the years, and many publications are

The power system reliability is a measure of the ability of the system to meet the consumer requirements with quality electrical energy. In general "reliability" is usually divided into two

According to the North American Electric Reliability Corporation (NERC), adequacy and

aspects of system adequacy and system security [9, 10], as shown in Figure 1.

Monte Carlo simulation

available on this subject [1–8].

security are defined as [11]:

Figure 1. Power system reliability subdivision.

2. Power system reliability assessment

1. Introduction

100 Smart Microgrids

known as HL-III analysis. The work reported in this book is confined to the reliability assessment at HL-II level (composite power system) and is focused on adequacy analysis.

system behavior is stochastic in nature, and therefore it is reasonable to believe that the probabilistic methods are able to react to the real factors that influence the reliability of the system. Probabilistic methods present quantitative indices (reliability indices), which can be used to make a decision on whether the power system performance is acceptable or if changes

Assessment of Reliability of Composite Power System Including Smart Grids

http://dx.doi.org/10.5772/intechopen.75268

103

An analytical method will constantly give the same numerical result for the same system, same model and same set of input data. Hence these methods tend to provide a high degree of confidence in the reliability assessment. Analytical methods, however, usually need assumptions to simplify the solutions. This is particularly the case with complex network and generating system with integration of renewable generation. The resulting analysis can therefore lose some of the confidence on the results obtained. This difficulty can be reduced or eliminated by using a simulation approach. Monte Carlo simulation method is a well-known method and is used to estimate the reliability indices by simulating the actual process and random nature of the failure and repair of the system/components. This method, therefore, treats the problem as a series of experiments. There are advantages and disadvantages in both methods. Generally, Monte Carlo simulation method requires a large computation time compared to analytical methods. Monte Carlo simulation methods, however, can theoretically take into account virtually all aspects and contingencies inherent in the planning, design and

Considerable research has been done in the last two decades in the area of composite power system reliability assessment using analytical, Monte Carlo simulation and mixing of both methods [1–14]. There are two types of Monte Carlo methods, such sequential and nonsequential types. Nonsequential method is widely used in the evaluation of power system reliability. The research work presented in this book is mainly concentrating on the difficulties associated with

The research work presented in this book concentrates on HL-II, i.e., composite power system reliability assessment. These reliability studies will assess the ability of the composite generation and transmission system (composite power system) to not only satisfy the consumer requirements but also tolerate the random failures and execute preventive maintenance of electrical components. The reliability performance of any system is generally evaluated by the reliability parameters or indices. The composite power system reliability is judged in this research work by considering "average power availability" and "loss of load expected" as reliability indices at the bulk consumer buses. There are many publications that are dealing with composite power system reliability assessment [1–14]. In the evaluation of reliability in composite power system, many technical issues are involved such as load uncertainty, generation adequacy, integration of nonconventional sources, multiple outages, etc. [4, 13]. By keeping these technical issues in view, this research work addresses some new and improved

the traditional methods and presented some simpler methods for reliability assessment.

4. Composite power system reliability assessment

methods for the assessment of composite power system reliability.

need to be made.

operation of a power system [12, 14].

The basic role of an electric power system is to supply its customers with electrical energy as economically as possible and with a reasonable degree of continuity and quality. Power system reliability is generally expressed in terms of indices that reveal the system capability and the quality of service provided to its customers. The reliability concept and techniques first applied on practical power systems were mostly based on empirical experience and were all deterministically based. Many of methods are still in use today. These earlier concepts of reliability assessment, however, are inherently deterministic and do not account for the probabilistic or stochastic nature of system behavior, customer demands or component failures. The application of probabilistic methods for reliability assessment can consider the inherent stochastic nature of the power system and provide quantitative measures for power system reliability and thus complement the limitations of deterministic methods. Power system reliability assessment using probabilistic methods has been in practice since 1947. These are discussed in detail in the following sections. Research on reliability assessment over the last 60 years has been directed toward the evaluation of reliability indices applying probabilistic methods [13, 14]. Many reliability indices are defined over the years to judge reliability of the power system. The most commonly used reliability indices are discussed in [15]. The research work reported in this book is mainly focused on the average power availability for the bulk consumers connected to the power system network.
