3. Literature review

The main function of the modern power system is to satisfy the energy needs of the consumer as economical as possible and with reasonable level of continuity and quality. The power system is made up of different components like circuit breakers, transformers, relays, etc. Failure of these components will result into customer supply interruption and cause loss of load. In order to assess the continuity of power supply to the consumers and improve it if possible, there is need of complete reliability assessment. By considering the failure (λ) and repair (μ) rates of all the components in the system, the average power availability is calculated with tracing of power flow paths. This is a basic method followed by power engineers earlier [1–14]. After tracing of paths, the equivalent failure and repair rates are calculated by seriesparallel approach. But in the present complex power system, it is very difficult to identify those paths. Later star-delta and delta-star conversion methods developed, but again identification of those networks is a difficult task in complex systems [14]. The reliability of any system is determined using either deterministic or probabilistic methods. Deterministic methods present the reliability assessment with the information on how a system/component failure (called contingencies) can happen or how system/component success can be achieved. The traditional deterministic criterion used particularly in bulk electric systems (BES) is known as the N-1 security criterion [14] under which the loss of any bulk system component will not result in system failure. The main weakness of deterministic method is that they do not react to the stochastic nature of power system behavior, consumer demands or component failures. Power 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 need to be made.

known as HL-III analysis. The work reported in this book is confined to the reliability assess-

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 con-

The main function of the modern power system is to satisfy the energy needs of the consumer as economical as possible and with reasonable level of continuity and quality. The power system is made up of different components like circuit breakers, transformers, relays, etc. Failure of these components will result into customer supply interruption and cause loss of load. In order to assess the continuity of power supply to the consumers and improve it if possible, there is need of complete reliability assessment. By considering the failure (λ) and repair (μ) rates of all the components in the system, the average power availability is calculated with tracing of power flow paths. This is a basic method followed by power engineers earlier [1–14]. After tracing of paths, the equivalent failure and repair rates are calculated by seriesparallel approach. But in the present complex power system, it is very difficult to identify those paths. Later star-delta and delta-star conversion methods developed, but again identification of those networks is a difficult task in complex systems [14]. The reliability of any system is determined using either deterministic or probabilistic methods. Deterministic methods present the reliability assessment with the information on how a system/component failure (called contingencies) can happen or how system/component success can be achieved. The traditional deterministic criterion used particularly in bulk electric systems (BES) is known as the N-1 security criterion [14] under which the loss of any bulk system component will not result in system failure. The main weakness of deterministic method is that they do not react to the stochastic nature of power system behavior, consumer demands or component failures. Power

ment at HL-II level (composite power system) and is focused on adequacy analysis.

sumers connected to the power system network.

3. Literature review

102 Smart Microgrids

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 operation of a power system [12, 14].

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 traditional methods and presented some simpler methods for reliability assessment.
