Momentary Average Interruption Frequency Index Research Articles

Reliability Analysis of Distribution Network Based on Reliability Index Assessment Method: A Case Study.

A primary requirement of a modern electric power system is reasonable ability to satisfy the customer load requirements. Electric utilities involve generation, transmission, and distribution facilities each one of which contributes its own inherent difficulties to the problem of satisfying customer requirement. A power system should be designed and expanded the facilities in order to perform its intended function with a reasonable risk. With increasing the electrical energy demand and the potential of disruption that may occur in the system, the distribution system must have high reliability and continues supply to customer. In this case, the reliability of the distribution system needs to be evaluated by monitoring and analyzing the level of distribution system failure in a certain period of time. A study on a practical distribution system with application of automatic circuit reclosers (ACRs) which plays an important role in enhancing the reliability index of system is presented. The reliability index assessment analyze the reliability index of the existing system before and after application of ACRs. From the simulation point of view, the system average interruption frequency index (SAIFI) is about 19.43% or decreased the failure frequent event from 11.4 failure/ customer.year to 9.25 failure/customer.year); while the momentary average interruption frequency index (MAIFI) has decreased from 6.72 failure/customer.year to 5.05 failure/ customer.year, or increase the reliability index of about 24.85%.

Approach to reduce momentary average interruption frequency index – the quality of service indicator for momentary interruptions – the experience of the Portuguese DSO

Approach to reduce momentary average interruption frequency index – the quality of service indicator for momentary interruptions – the experience of the Portuguese DSO

Multiobjective formulation of the integration of storage systems within distribution networks for improving reliability

A new approach to improve reliability in distribution networks using energy storage systems is presented in this paper. Electric utilities have been using switching devices in distribution networks mainly to improve network reliability considering sustained interruptions. Temporary interruptions have been relegated to second place. However in modern societies appliances with electronic components are becoming more sensitive to temporary interruptions. Because of this, reliability indexes like the Momentary Average Interruption Frequency Index (MAIFI) that considers temporary interruptions are receiving more attention by electric utilities. The integration of storage systems into the multiobjective planning of distribution networks is proposed in this paper, to improve the reliability index MAIFI. This approach considers the optimization of storage systems integrated in a problem with multiple objective functions. The reliability index MAIFI is the first objective function, minimized by optimally choosing the size and location of battery banks in the distribution network. The second objective function, System Average Interruption Frequency Index (SAIDI) is optimized by finding the optimal number and location of switching devices. The third objective function consists on the minimization of the equipment cost. The optimization of these conflicting functions is achieved by the use of the Non-Dominated Sorting Genetic Algorithm II (NSGA-II).

Why Existing Utility Metrics Do Not Work for Industrial Reliability Analysis

Electrical utility reliability indices such as System Average Interruption Frequency Index, System Average Interruption Duration Index, Customer Average Interruption Duration Index, Customer Average Interruption Frequency Index, and Momentary Average Interruption Frequency Index are adequately defined in IEEE Std. 1366-2012, and serve the purpose for which they were developed. However, the explosive growth of the electronics industry moving toward internet of things, along with the data center development necessary to support such explosive growth, has had significant impact on an aging power distribution system. As the utility world evolves toward the notion of smart grid, several new reliability metrics are needed to evaluate the electrical power to the customer's side of the meter.

Reconfiguration of Distribution Networks with Presence of DGs to improving the Reliability

In this paper, the network reconfiguration in the presence of distributed generation units with the aim of improving the reliability of the network is studied. For this purpose four reliability parameters in the objective function are considered, which is average energy not supplied system average interruption frequency index, system average interruption duration index and momentary average interruption frequency index. The new method will be normalized objective function. Another suggestion of this paper are considering the different fault rates, locating time of faults type and prioritization of customers based on their importance. This nonlinear problem has optimized by particle swarm optimization (PSO) algorithm.

Optimum Network Reconfiguration to Improve Power Quality and Reliability in Distribution System

In this paper, network reconfiguration has been conducted to improve the power quality and reliability of distribution systems in presence of distributed generations. In this case, network reconfiguration is analyzed for different indices. The most important indices are the number of propagated voltage sags (N sag), sustained average interruption frequency index, average system interruption frequency index and momentary average interruption frequency index. The Imperialist competitive algorithm (ICA) is hired to find the optimal configuration of the distribution system in order to minimize the mentioned indices. Simulation result is discussed with and without distributed generation.

Reconfiguration of Distribution Networks with Presence of DGs to improving the Reliability

In this paper, the network reconfiguration in the presence of distributed generation units with the aim of improving the reliability of the network is studied. For this purpose four reliability parameters in the objective function are considered, which is average energy not supplied system average interruption frequency index, system average interruption duration index and momentary average interruption frequency index. The new method will be normalized objective function. Another suggestion of this paper are considering the different fault rates, locating time of faults type and prioritization of customers based on their importance. This nonlinear problem has optimized by particle swarm optimization (PSO) algorithm.

Solving a novel multiobjective placement problem of recloser and distributed generation sources in simultaneous mode by improved harmony search algorithm

This article deals with optimal placement of Distributed Generation (DG) sources and recloser in simultaneous mode and develops an improved harmony search (iHS) algorithm to solve it. For this, two important control parameters have been adjusted to reach better solution from simple HS algorithm to obtain better solution from simple HS algorithm. The proposed multiobjective function consists of two parts; first is improving reliability indices and second is minimizing power loss. The reliability indices have been selected based on satisfactory requirements of costumer and electric company as well as response to transient and permanent faults. Then, four reliability indices has been used in objective function; that is, system average interruption duration index (SAIDI), cost of energy not supplied, momentary average interruption frequency index, and system average interruption frequency index (SAIFI). Simulation has been performed on a practical distribution network in North West of Iran. Three scenarios have been introduced; that is, scenario (i) First, placement of DGs, and then recloser, scenario (ii) First, placement of recloser, and then DG, and scenario (iii) simultaneous placement of DG and recloser. Also, three cases are defined based on the number of used DG and recloser. Results of the proposed algorithm have been compared with related values of particle swarm optimization and simple HS algorithms. The core contribution of the presented study is introducing several novel indices to analyze and discuss the obtained results from simulation. © 2014 Wiley Periodicals, Inc. Complexity 21: 328–339, 2015

Power quality and reliability enhancement in distribution systems via optimum network reconfiguration by using quantum firefly algorithm

Network reconfiguration (NR) is the process of varying the topological arrangement of distribution feeders by changing the open/closed status of sectionalizing and tie switches. This paper presents a method to improve the power quality (PQ) and reliability of distribution systems by employing optimal NR. Optimal NR is applied independently to a system in a specified period to minimize the number of propagated voltage sags (Nsag) and other reliability indexes such as the average system interruption frequency index, sustained average interruption frequency index, and momentary average interruption frequency index. The quantum-inspired binary firefly algorithm (QBFA) is used to find the optimal NR. The QBFA performance for the application of optimal NR to minimize Nsag is first compared with other established optimization methods such as the standard binary firefly algorithm and gravitational search algorithm. Case studies are conducted by using other objective functions, and reliability assessment is performed to observe the reliability improvement caused by the new network topology. Simulation results show that the proposed optimum NR effectively enhances system reliability level and PQ.

A Fuse-Blow Scheme

A fuse-blow philosophy has been adopted by some utilities in an effort to decrease the number of momentary average interruption frequency index (MAIFI) seen by their customers. This practice has the inherent drawback that, by converting a temporary fault (e.g., lightning and animals) into a sustained interruption, they are in effect decreasing the reliability of their system [i.e., system average interruption duration index (SAIDI) will increase]. This article addresses the impact of a fuse-blow philosophy on long lines commonly found in rural electric utilities as well as shorter lines that are ubiquitous in more urban areas. It also assesses the differences in the impact of these schemes in terms of both power quality (momentaries) and reliability issues. Detailed analysis of the impact on the utility system is presented and discussed.