System Average Interruption Frequency Index Research Articles

Application Study in the Field of Solutions for the Monitoring Distribution Transformers of the Overhead Power Grid

This paper will present the development and application of overhead transformers of the distribution grid, as well as the different technologies used for the gathering of electrical quantities, in the field of a monitoring solution. The solution reports the values of the quantities and alarms of operation remotely and almost in real-time. The development of this solution seeks to provide an electrical grid with greater reliability, proposing the reduction of KPIs (Key Performance Indicator), such as SAIDI (System Average Interruption Duration Index) and SAIFI (System Average Interruption Frequency Index), through more transparent monitoring of the behavior of the electrical distribution grid and its equipment. Through the research and development (R&D) project Urban Futurability, ENEL (Ente nazionale per l’energia elettrica) Distribution São Paulo seeks to apply the solution by implementing the concept of smart grids, an idea that has been growing each year by virtue of technological developments and the employment of new sensors in electrical distribution grids. Urban Futurability seeks to innovate the automation area, digital twin, and construction enhancement in the Vila Olímpia neighborhood of São Paulo, Brazil.

Advanced Metering Infrastructure—Towards a Reliable Network

In order to ensure continuous energy supply, Distribution System Operators (DSOs) have to monitor and analyze the condition of the power grid, especially checking for random events, such as breakdowns or other disturbances. Still, relatively little information is available on the operation of the Low Voltage (LV) grid. This can be improved thanks to digital tools, offering online processing of data, which ultimately increases effectiveness of the power grid. Among those tools, the use of the Advanced Metering Infrastructure (AMI) is especially conducive for improving reliability. AMI is one of the elements of the system Supervisory Control and Data Acquisition (SCADA) for the LV grid. Exact knowledge of the reliability conditions of a power grid is also indispensable for optimizing investment. AMI is also key in providing operational capacity for carrying out energy balance in virtual power plants (VPPs). This paper deals with methodology of identification and location of faults in the AMI-supervised LV grid and with calculating the System Average Interruption Duration Index (SAIDI) and System Average Interruption Frequency Index (SAIFI) on the basis of the recorded events. The results presented in the paper are based on data obtained from seven MV/LV transformer stations that supply over 2000 customers.

A mixed integer optimization model for reliability indices enhancement in Micro-grid system with renewable generation and energy storage

With increased awareness on environmental concerns, there has been a significant shift toward the use of renewable energy sources (RES). In this regard, smart grid technologies have been presented in order to facilitate greater RES penetration. Microgrids are critical components of smart grids. Microgrids enable the integration of various distributed energy resources (DER) into the distribution system, such as distributed generation (DGs) and energy storage systems (ESSs), and thus eliminate the need for distribution system expansion. This research focuses on an islanding operation of a microgrid. This paper employs a hybrid analytical-simulation method to assess the reliability of a microgrid with prioritised loads and distributed RES. The stochasticity of RES complicates the evaluation of reliability. The problem is solved using a mixed integer optimization model that maximizes the reliability of the micro-grid system by determining the number of critical and non-critical loads that can be satisfied at each time step. The maximum number of loads is limited by the available renewable and stored generation in the system at each time step. The results show that the presence of the microgrid topology improves the overall system's reliability. The incorporation of energy storage into the micro-grid improves the system's System Average Interruption Frequency Index, as demonstrated in this study.

Battery Energy Storage System for Emergency Supply and Improved Reliability of Power Networks

This paper introduces the concept of a battery energy storage system as an emergency power supply for a separated power network, with the possibility of island operation for a power substation with one-side supply. This system, with an appropriately sized energy storage capacity, allows improvement in the continuity of the power supply and increases the reliability of the separated network at a specified time during the limitation of power transmission as a result of damage or disconnection of the main power line. This paper presents and describes a specific method of energy storage system dimensioning based on real measurement data. Based on the obtained parameters, an analysis of the reliability improvement of the considered network was performed. The implementation of the battery energy storage system will contribute to a more than 5-fold reduction in the occurrence of power outages in the time interval from 3 min to 1.5 h, which will clearly reduce the System Average Interruption Frequency Index and System Average Interruption Duration Index factors. In this paper, the network conditions for operational normality and failure are presented and the cost for implementation of an energy storage system (about EUR 1 million) is compared with the possible implementation of an additional power line (about EUR 5 million) to a specific power substation.

Dynamic Programming Method to Optimally Select Power Distribution System Reliability Upgrades

This paper presents a novel dynamic programming (DP) technique for the determination of optimal investment decisions to improve power distribution system reliability metrics. This model is designed to select the optimal small-scale investments to protect an electrical distribution system from disruptions. The objective is to minimize distribution system reliability metrics: System Average Interruption Duration Index (SAIDI) and System Average Interruption Frequency Index (SAIFI). The primary input to this optimization model is years of recent utility historical outage data. The DP optimization technique is compared and validated against an equivalent mixed integer linear program (MILP). Through testing on synthetic and real datasets, both approaches are verified to yield equally optimal solutions. Efficiency profiles of each approach indicate that the DP algorithm is more efficient when considering wide budget ranges or a larger outage history, while the MILP model more efficiently handles larger distribution systems. The model is tested with utility data from a distribution system operator in the U.S. Results demonstrate a significant improvement in SAIDI and SAIFI metrics with the optimal small-scale investments.

Load Curtailment Optimization Using the PSO Algorithm for Enhancing the Reliability of Distribution Networks

Power systems are susceptible to disturbances due to their nature. These disturbances can cause overloads or even contingencies of greater impact. In case of an extreme situation, load curtailment is considered the last resort for reducing the contingency impact, its activation being necessary to avoid the collapse of the system. However, load shedding systems seldom work optimally and cause either excessive or insufficient reduction of the load. To resolve this issue, the present paper proposes a methodology to enhance the load curtailment management in medium voltage distribution systems using Particle Swarm Optimization (PSO). This optimization seeks to minimize the amount of load to be cut off. Restrictions on the optimization problem consist of the security operation margins of both loading and voltage of the system elements. Heuristic optimization algorithms were chosen, since they are considered an online basis (allowing a short processing time) to solve the formulated load curtailment optimization problem. Best performances regarding optimal value and processing time were obtained using a PSO algorithm, qualifying the technique as the most appropriate for this study. To assess the methodology, the CIGRE MV distribution network benchmark was used, assuming dynamic load profiles during an entire week. Results show that it is possible to determine the optimal unattended power of the system. This way, improvements in the minimization of the expected energy not supplied (ENS) as well as the System Average Interruption Frequency Index (SAIDI) at specific hours of the day were made.

Reliability Analysis of 20 KV Electric Power Distribution System

The reliability of the distribution system is the ability of a system to supply electrical energy continuously without causing failure to consumers. The reliability of the distribution system can be analyzed based on the SAIDI (System Average Interruption Duration Index), SAIFI (System Average Interruption Frequency Index), and CAIDI (Customer Average Interruption Duration Index) indices. The SAIFI, SAIDI and CAIDI values are determined by simulating using ETAP 12.0.6 software, which is by running reliability assessment analysis. The simulation process was carried out an IEEE 9 bus network distribution system. The simulation results show a SAIFI value of 1.113 frequency/customer.yr, a SAIDI value of 17.306 hours / customer.yr and a CAIDI value of 15,549 hours / customer interruption. For normal operating conditions, the total demand for loads supplied from secondary substations to the 20 KV distribution network is 12,955 MW and 5,234 MVAR, with losses of 8.06%

Analysis and improvement on reliability of 66/11 kV distribution substation and its associated feeders: A case study of Lainchour substation in Nepal

Electric power interruption is becoming a day to day phenomenon in our distribution system. For distribution system to be effective there should be less outage in the system and if fault occur these faults should be cleared as soon as possible. Sustained power interruption occurs several times a day from few minutes to hours. Interruptions may be due to failure of substation equipment or failure of distribution network elements. This paper attempts to identify different causes of interruption and problems that customers in Nepal have been facing due to frequent planned and unplanned sustained interruptions by evaluating various reliability indices and parameters of Lainchaur distribution substation and its associated feeders operated under Nepal Electricity Authority. First, reliability analysis of substation configuration only is done followed by analysis of reliability improvement measures like use of double bus bar, parallel distribution feeders and underground cables in DIgSILENT PowerFactory only considering sustained failures of equipment and feeders. Calculated reliability indices like System Average interruption Duration Index (SAIDI), System Average Interruption Frequency Index (SAIFI), Energy Not Served (ENS) are compared for different cases so that it will be easy to make choice between options to the utility to upgrade/improve the system. Considering all feeders, result shows that main cause of interruption in the distribution system is failure of distribution lines showing 104 interruptions for total duration of 107 hours per annum in the system, followed by failure of distribution transformers indicating 19 interruptions for total duration of 47 hours per annum. Simulation result in DIgSILENT shows yearly total ENS of distribution system is high due to present configuration, and can be reduced by the use of parallel feeders and underground cables respectively. It is seen that ENS due to failure of substation components only is very low and huge revenues can be saved if auto-reclosures are used or a provision of charging feeders as soon as possible is made.

Optimal design of hybrid DG systems for microgrid reliability enhancement

While the concept of microgrids and renewable energy systems is not entirely new, these integrated technologies have become a special topic of interest for researchers, utility providers and governments. Many challenges must be overcome to achieve better integration of renewable sources into the energy framework. This study presents some viable possibilities for the utilisation of a hybridised microgrid system. The hybridisation is achieved by an efficient design approach for the enhancement of both load and system reliability indices through the intelligent placement and sizing of hybrid distributed generation (DG) systems. Real-time models of solar photovoltaics, wind turbines, batteries and thermal DGs are presented and implemented. Also, network component failures are stochastically modelled via Monte Carlo simulations, and a general tie-set algorithm using an adapted breadth-first search is proposed. Moreover, mixed-integer multi-objective particle swarm optimisation is employed, giving a four-dimensional Pareto solution that is attained by optimising four reliability-related objectives, namely system average interruption frequency index, System Average Interruption Duration Index (SAIDI), Energy Not Supplied (ENS) and total cost.

Reliability Assessment and Study the Effect of Substation Feeder Length on Failure Rate and Reliability Indices

Today, utilities are trying to maximize system reliability, improve efficiency, and reduce costs by using protection system, distributed generation system, by reconfiguring the feeder, by connecting the end of feeder to other substation and so on. However, when it tries to use some techniques (reconfiguring the feeder, connecting the end of the feeder to another substation); the techniques have positive and negative impact on reliability improvement. The substation which is taken in this paper has the System Average Interruption Frequency Index (SAIFI) and System Average Interruption Duration Index (SAIDI) is 521.46 interruptions per customer per year and 446.82 hours per customer per year respectively. The historical outage interruption data of the years of 2016-2018 has been used as a base year. The study has evaluated the new substation to improve the system reliability. The simulation results have been done with the help of Electrical Transient Analysis Program (ETAP 12.6) software. In this paper includes improvement of the system reliability of the feeder is supplied from two substations or new substation should be connected at the end of the feeder. Due to the new substation, the length of the feeder will vary, and the variation of the feeder has significant effect on power reliability. The value of SAIFI and SAIDI after the new substation connected is 169 and 96 respectively. Since the new substation has negative impact, the value of indices is not reduced more.

Optimal procedure for remote-controlled switch devices siting in distribution systems using heuristic algorithms

The growing demand for improved quality of service increases the importance of network automation. This allows improving the fault isolation and reconfiguration time and therefore increasing the system quality of service. Since the investment in remote-controlled switch (RCS) devices comes at a cost, this study proposes a heuristic approach to solve the problem of optimal siting RCS devices in distribution systems. For doing that, RCS devices are located to improve the reliability of the system based on the optimal open ties deriving from the distribution network (DN) reconfiguration problem. A Genetic Algorithm has been developed to optimise the radial layout of the DN taking into account the reliability of the system. As a measure of the system reliability, the authors use a risk index which is expected to well estimate, based on the statistical data available, the system average interruption frequency index. The risk index is based on two parameters: the length of the feeders, which measures the failure probability, and the number of customers, which measures the failure impact. The solution approach has been tested on a real distribution subsystem of Milano.

Charging Load Prediction and Distribution Network Reliability Evaluation Considering Electric Vehicles’ Spatial-Temporal Transfer Randomness

Integration of large-scale cluster electric vehicles (EVs) and their spatial-temporal transfer randomness are likely to affect the safety and economic operation of the distribution network. This paper investigates the spatial-temporal distribution prediction of EVs’ charging load and then evaluates the reliability of the distribution network penetrated with large-scale cluster EVs. To effectively predict the charging load, trip chain technology, Monte Carlo method and Markov decision process (MDP) theory are employed. Moreover, a spatial-temporal transfer model of EVs is established, and based on which, an EV energy consumption model and a charging load prediction model are constructed with consideration of temperature, traffic condition and EV owner’s subjective willingness in different scenarios. With the application of sequential Monte Carlo method, the paper further evaluates distribution network reliability in various charging scenarios. In the evaluation, indices including per unit value (PUV), fast voltage stability index (FVSI), loss of load probability (LOLP), system average interruption frequency index (SAIFI), system average interruption duration index (SAIDI), and expected energy not supplied (EENS) are incorporated. To validate the proposed prediction model and evaluation method, a series of numerical simulations are conducted on the basis of taking the traffic-distribution system of a typical city as an example. The result demonstrates that the proposed spatial-temporal transfer model is more practical in charging load prediction than the popularly used Dijkstra’s shortest path algorithm. Moreover, high temperature, congestion and the increment of EV penetration rate will further weaken distribution network reliability.

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%.

A Comparative Analysis of Reliability Indices of Kaduna and Kano Distribution Systems

Reliability indices such as System Average Interruption Duration Index (SAIDI), System Average Interruption Frequency Index (SAIFI) and Customer Average Interruption Duration Index (CAIDI) are so significant in assessing the reliability levels of power systems.A comparative analysis of reliability indices of Kaduna and Kano distribution systems was carried out. Ten years of outage data information from ten selected distribution feeders of Kaduna and Kano distribution systems were used in this paper. The mean and standard deviation of the basic reliability indices were computed using appropriate mathematical relations as input parameters. The variances of these parametric indicators were also computed.FDR3 feeder of Kaduna distribution system recorded the highest mean SAIDI of 0.1064 compared to all other feeders in the selected distribution system. Customers on this feeder were interrupted for a prolonged time while fewer of the customers were adequately served. Junction Road feeder of Kaduna distribution system had the least mean SAIDI of 0.0704 because customers’ interruption was for a short period of time even though; more customers were being served by the feeder.Bangauda feeder of Kano distribution system recorded the highest mean SAIDI of 0.1462. More customers were interrupted compared to all other feeders in the distribution system while fewer of them were adequately served while Spare feeder had a least mean SAIDI of 0.0497 because fewer of the customers attached to this feeder were interrupted while many of them were adequately served.The result of this research paper will provide a comparative analysis of the reliability indices of the selected distribution feeders on Kaduna and Kano distribution systems which will go a long way providing background information for distribution system engineers for adequate planning and maintenance of distribution feeders. Keywords: SAIDI, SAIFI, CAIDI, Customers’ interruptions, Power systems, Reliability indices, Distribution systems. DOI : 10.7176/JETP/9-8-05 Publication date: November 30 th 2019

Reliability based optimal DG planning for a meshed distribution network

Distributed generation (DG) sources are becoming more popular nowadays because of their technoeconomic and environmental benefits. These benefits are maximized only when the DG sources are properly planned and installed in the distribution networks. Several studies have been carried out in this field considering various objectives and constraints, for single as well as multiple DG placement and sizing. In this paper, an optimization methodology based on particle swarm optimization is used for the optimal planning of multiple DG sources in a meshed distribution network. The solution consists of the possible DG locations, DG capacities, and its operating power factor. The objectives considered are the improvement of reliability indices namely the system average interruption frequency index and system average interruption duration index, reduction of real power loss, and voltage profile improvement. Unlike other works, reliability evaluation is done considering many realistic constraints and it is used as one of the criteria for DG planning. Reliability indices are evaluated using the encoded Markov cut set algorithm. The real power loss and the voltage index are obtained by means of a simple load flow technique. The stochastic nature of the renewable DG output and the load are taken into account during the reliability evaluation along with islanding probability. The optimal planning of DG sources is done for bus 4 of the Roy billinton test system consisting of seven feeders, 102 nodes, and 106 components. Optimal planning for solar based DG sources is done considering three different load models namely residential, commercial, and mixed load.

MILP Model of Electricity Distribution System Expansion Planning Considering Incentive Reliability Regulations

This paper aims at proposing a mixed-integer linear formulation to incorporate reliability-oriented costs into the expansion planning model of electricity distribution networks. In this respect, revenue lost associated with the undelivered energy caused by network interruptions as well as costs incurred by the widely used reward–penalty regulations is considered as the major reliability-related costs from distribution companies point of view. A set of mixed-integer linear equations is proposed to calculate the most common distribution system reliability indices, i.e., expected energy not served, system average interruption frequency index, and system average interruption duration index. It is found that these equations can also facilitate the formulation of radiality constraint in the presence of distributed generation units. Moreover, application of the proposed method is investigated through various case studies performed on two test distribution networks with 24 and 54 nodes.

Statistical Analysis of Reliability Indices of Ikeja and Port-Harcourt Distribution Systems

In the evaluation of the reliability levels of electrical power systems, reliability indices play a vital role. These indicators are System Average Interruption Duration Index (SAIDI), System Average Interruption Frequency Index (SAIFI) and Customer Average Interruption Duration Index (CAIDI). Statistical analysis of reliability indices of Ikeja and Port-Harcourt distribution system was carried out in this research paper.. Ten years of outage data information from ten selected distribution feeders of Ikeja and Port-Harcourt distribution systems were used in this work. The mean and standard deviation of the basic reliability indices were computed using appropriate mathematical relations as input parameters. Olowu feeder of Ikeja distribution system recorded the highest mean SAIDI of 01040 compared to all other feeders in the selected distribution system. Customers on this feeder were interrupted for a prolonged time while fewer of the customers were adequately served. 7-UP feeder of Ikeja distribution system had the least mean SAIDI of 0.0693 because customers’ interruption was for a short period of time even though; more customers were being served by the feeder. Airport of Port-Harcourt distribution system recorded the highest mean SAIDI of 0.1050. More customers were interrupted compared to all other feeders on the distribution system while fewer of them were adequately served. Airport feeder of Port Harcourt distribution system had a least mean SAIFI of 0.1392 because fewer of the customers attached to this feeder were interrupted while many of them were adequately served. The result of the work will provide a background information for distribution system engineers for adequate planning and effective maintenance of Ikeja and Portharcourt distribution systems. Keywords: Statistical analysis, Mean SAIDI, Mean SAIFI, Mean CAIDI, SAIDI standard deviation, SAIFI standard deviation, CAIDI standard deviation . DOI : 10.7176/APTA/77-06 Publication date :May 31 st 2019

Distribution system versus bulk power system: identifying the source of electric service interruptions in the US

This study reports on the results from efforts by the Institute of Electric and Electronics Engineers (IEEE) Distribution Reliability Working Group (DRWG) and the U.S. Energy Information Administration (EIA) to improve the usefulness of reliability metrics by developing and then applying consistent, yet distinct measures of the continuity of supply based on the portion of the electric power system from which power interruptions originate: the lower voltage distribution system versus the high-voltage bulk power system. The modified metrics better support reliability planning in the US because they separately measure the effectiveness of actions to improve reliability made by the two distinct groups of firms (and their regulators or oversight bodies) that are responsible for planning and operating each portion of the US electric power system. The authors then present for the first time quantitative information on the reliability of each portion of the US electric power system. When reliability is measured using the system average interruption duration index and the system average interruption frequency index, they find that the distribution system accounts for at least 94 and 92%, respectively, of all interruptions. They also find that these relationships have been stable over the recent past.

Reliability Varying Characteristics of PV-ESS-Based Standalone Microgrid

Reliability is of critical importance for the microgrid (MG) and deserved more attention. Aiming at photovoltaics (PV) and energy storage system (ESS) based MG, the microturbine (MT), PV, ESS and comprehensive load (CL) which is composed of hourly time-varying component, stochastic component, and controllable component, are chronologically modeled and combined with model of load shedding minimization and sequential Monte Carlo (SMC) simulation algorithm. Then, the reliability assessment framework is developed and employed in the comprehensive case studies. Firstly, varying characteristics of reliability indices, including loss of load probability (LOLP), average service availability index (ASAI), system average interruption duration index (SAIDI), system average interruption frequency index (SAIFI) and customer average interruption duration index (CAIDI), over PV penetration are investigated, and the surge effect of SAIFI (SE-SAIFI) is especially put forward and studied, followed by the principle of PV capacity decision considering SE-SAIFI. Secondly, the clear pictures of reliability profiles over ESS sizes are depicted and analyzed, following with a novel method to reasonably decide ESS sizes based on the definition of expected hourly redundant power (EHRP). At last, reliability indices of multiple scenarios with different percentages of controllable load are calculated and the benefits of load management are analyzed in the viewpoint of reliability of standalone MG. Results of the case studies also confirm the necessities of reliability assessment during the MG planning and size optimization, and the validity of the methodologies developed in this work.

Long-Term Impact Evaluation of Advanced Under Frequency Load Shedding Schemes on Distribution Systems With DG Islanded Operation

This paper presents a long-term impact evaluation algorithm to assess advanced under frequency load shedding (UFLS) schemes on distribution systems with intentional islanding of distributed generation (DG). The algorithm is based on a combined discrete-continuous simulation model which is utilized to verify the effect of the schemes on reliability indices such as the system average interruption frequency index, system average interruption duration index, and energy not supplied. Moreover, a polynomial neural network-based approach to advanced load shedding is implemented to support DG islanding in order to illustrate the applicability of the evaluation. Simulation results highlight the long-term effect of employing UFLS to support intentional islanding of DG using an actual network from the South of Brazil.