System Average Interruption Frequency Index Research Articles

A new multi-objective-stochastic framework for reconfiguration and wind energy resource allocation in distribution network incorporating improved dandelion optimizer and uncertainty

Improving the reliability and power quality of unbalanced distribution networks is crucial for ensuring consistent and reliable electricity supply. In this research, multi-objective optimization of unbalanced distribution networks reconfiguration integrated with wind turbine allocation (MORWTA) is implemented considering uncertainties of networks load, and also wind power incorporating a stochastic framework. The multi-objective function is defined by the minimization of power loss, voltage sag (VS), total harmonic distortion (THD), voltage unbalance (VU), energy not-supplied (ENS), system average interruption frequency index (SAIFI), system average interruption duration index (SAIDI), and momentary average interruption frequency (MAIFI). A new improved dandelion optimizer (IDO) with adaptive inertia weight is recommended to counteract premature convergence to identify decision variables, including the optimal network configuration through opened switches and the best location and size of wind turbines in the networks. The stochastic problem is modeled using the 2m + 1 point estimate method (PEM) combined with K-means clustering, taking into account the mentioned uncertainties. The proposed stochastic methodology is implemented on three modified 33-bus, and unbalanced 25-, and 37-bus distribution networks. The results demonstrated that the MORWTA enhanced all study objectives in comparison to the base networks. The results also demonstrated that the IDO had superior capability to solve the deterministic- and stochastic-MORWTA in comparison to the conventional DO, grey wolf optimizer (GWO), particle swarm optimization (PSO), and arithmetic optimization algorithm (AOA) in terms of achieving greater objective value. Moreover, the results demonstrated that when the stochastic-MORWTA model is considered, the power loss, VS, THD, VU, ENS, SAIFI, SAIDI, and MAIFI are increased by 18.35%, 9.07%, 10.43%, 12.46%, 11.90%, 9.28%, 12.16% and 14.36%, respectively for 25-bus network, and also these objectives are increased by 12.21%, 10.64%, 12.37%, 9.82%, 14.30%, 12.65%, 12.63% and 13.89%, respectively for 37-bus network compared to the deterministic-MORWTA model, which is related to the defined uncertainty patterns.

Statistical characterization of reliability indices in medium voltage networks using a Monte Carlo-based method

Distribution companies are compelled to provide high-quality services to their customers in compliance with existing regulations. Key performance indicators such as system average interruption duration index and system average interruption frequency index are commonly employed to assess the quality of service provided by these utilities. In certain countries, distribution system operators may face penalties or receive bonuses based on their performance within specified thresholds in their reliability indices. This paper introduces a novel, integrated algorithm, based on Monte Carlo simulations, for conducting a risk assessment in real MV networks using local data from the distribution system operator. The proposed technique is tested in a real MV network, and the obtained results are analyzed both at feeder level and for the entire network. The feeder-level results might be used to identify the sections of the network with the worst quality of power supply, based on the estimated KPIs. The overall results of the study offer valuable insights into the likelihood of specific KPI values using probability density function. The Weibull distribution and log-logistic distribution are found to be those with the best-fitting probability density functions for the two indices evaluated in this work. Furthermore, a penalty-based rate approach is presented as an application of the proposed method to assess the economic risk of the MV network. The findings reveal that the test system is expected to incur penalties amounting to 7.55 million dollars per year.

Reliability and Availability of Renewable Energy Sources in Kenya: A Review

The research sought to evaluate the reliability and availability of renewable energy sources in Kenya by examining the available literature regarding the state of energy production and consumption of the renewable energy sources. Several studies have been conducted to establish the capacity of the renewable electrical power sources including hydroelectric power, geothermal sources, wind power, solar energy and biofuels. Regarding production of electricity, the existing capacity is barely able to keep up with demand. The research used systematic review as the methodology of collecting relevant data for analysis. Given that more than 38% (2021) of Kenya’s electricity comes from hydropower, the situation is particularly difficult during the dry months of the year when water levels are low. Capacity gaps are then compensated by expensive thermal generation based on fossil fuels. Geothermal power has the capacity to be the most significant source of renewable energy with a potential of up to 7000MW. The reliability indices of the renewable energy sources, based on System Average Interruption Frequency Index (SAIFI) are at 1.98 (SAIFI) and at 4.37, based on the Customer Average Interruption Duration Index (CAIDI), which are below the international global standards. The research concluded that increased consumption of electricity, availability of alternate energy sources, amount of restoration time and number of planned interruptions have a significance influence on the reliability of a renewable energy source, with restoration time being the most significant. It is therefore recommended that new technologies and innovations that lead to reduced power interruptions and greenhouse gas emission be adopted.

Reliability Evaluation of Radial Distribution System with different locations and ratings of Photovoltaic

The primary objective of this work is to examine how strategically positioning Photovoltaic (PV) units can have effect on reliability of a distribution system. Feeder-1 of RBTS BUS2 system is used for the reliability evaluation. The study utilizes FMEA technique to evaluate the reliability indices, System Average Interruption Frequency Index (SAIFI), System Average Interruption Duration Index (SAIDI), Energy Not Supplied (ENS) and Average Service Availability (ASAI) linked to electrical interruptions in two different situations such as no PV unit and PV units are placed at different locations with different ratings along the feeder. The outcomes of installing PV units at different points along the distribution feeder are examined and compared. The prime focus lies in identifying the reliability based optimal placement of the PV unit, a determination made based on the reliability indices. By systematically analyzing and comparing the reliability indices under varying conditions, the research aims to provide insights into how the strategic positioning of PV units can lead to a substantial enhancement in the overall reliability of the distribution system. The findings contribute to the broader understanding of integrating renewable energy sources for reliability improvement within distribution systems and offer practical guidance for decision-makers in the field of energy distribution and planning.

Optimisation of the Distribution System Reliability with Shielding and Grounding Design Under Various Soil Resistivities

Lightning strikes can cause equipment damage and power outages, so the distribution system's reliability in withstanding lightning strikes is crucial. This research paper presents a model that aims to optimise the configuration of a lightning protection system (LPS) in the power distribution system and minimise the System Average Interruption Frequency Index (SAIFI), a measure of reliability, and the associated cost investment. The proposed lightning electromagnetic transient model considers LPS factors such as feeder shielding, grounding design, and soil types, which affect critical current, flashover rates, SAIFI, and cost. A metaheuristic algorithm, PSOGSA, is used to obtain the optimal solution. The paper's main contribution is exploring grounding schemes and soil resistivity's impact on SAIFI. Using 4 grounding rods arranged in a straight line under the soil with 10 Ωm resistivity reduces grounding resistance and decreases SAIFI from 3.783 int./yr (no LPS) to 0.146 int./yr. Unshielded LPS has no significant effect on critical current for soil resistivity. Four test cases with different cost investments are considered, and numerical simulations are conducted. Shielded LPSs are more sensitive to grounding topologies and soil resistivities, wherein higher investment, with 10 Ωm soil resistivity, SAIFI decreases the most by 73.34%. In contrast, SAIFIs for 1 kΩm and 10 kΩm soil resistivities show minor decreases compared to SAIFIs with no LPS. The study emphasises the importance of considering soil resistivity and investment cost when selecting the optimal LPS configuration for distribution systems, as well as the significance of LPS selection in reducing interruptions to customers.

Reliability Analysis of a Typical 33kV Distribution Network Using MATLAB (A Case Study of Ile-Oluji 33kV Distribution Line)

The significance of a dependable and sufficient electrical power supply in societal development cannot be overstated. The distribution of electrical power holds a crucial position in the power system chain, representing the final stage where it reaches consumers. At this phase, various types of losses, including technical loss and theft, among others are associated. The Ile-Oluji community is situated in Ondo State, a south-western part of Nigeria, A region which is host to federal, state, local and private institutions. This community grapples with inconsistent power supply experiencing intermittent trips without a clear originating cause from components in the Ile-Oluji injection substation and its feeder in Ondo. This study analyses the power distribution patterns in this locality focusing on three primary elements (transformer, switch gear and supply line) extracting data on; failures, outage time, numbers of customers and total hours for the year 2019 to 2022. Reliability indices were employed to assess its performance utilising the MATLAB software. Codes were crafted to extract these indices; Availability, Failure rates, Mean Time to Repair (MTTR), Mean Time Between failure (MTBF), System Average Interruption Duration Index (SAIDI), System Average Interruption Frequency Index (SAIFI), and Customer Average Interruption Duration Index (CAIDI). The results show that there is a strong relationship among the reliability indices. It is adduced that the lower the failure rate, the higher the availability of a system. It was concluded that the power system switchgear recorded the highest failure rate amongst the three elements with 0.037341 hrs/year followed by supply line with 0.022541 hrs/year and the transformer with 0.0148 hrs/year in 2022. In corollary, transformer has the highest availability of 0.94441 followed by supply line with 0.81681 and switchgear with 0.78004 in 2021, switchgear recorded the highest failure rates because it is responsible for executing both forced and planned outages.

Effects of integration of distributed generation on reliability in distribution system

The reliability of power supply to consumers is the main factor that is to be considered while designing, planning and operation of a distribution network. This problem can be solved by incorporating distributed generation (DG) at the consumer side itself. In order to enhance service availability, power quality, reliability, and loss reduction, DG is positioned optimally at the consumer end within the system. The optimal DG location and size is to be calculated in such a way that the total loss in the system should be minimal and cost savings should be maximal. In this study, for the investigation of effects of DG on reliability of distribution system, a practical 11 KV feeder with 41-bus, was employed. The selected practical feeder is modelled using the power world simulator (PWS) software and reliability of the system is verified by calculating various reliability indices such as system average interruption frequency index (SAIFI), system average interruption duration index (SAIDI), customer average interruption duration index (CAIDI), average system utility index (ASUI) and average service availability index (ASAI). After applying proposed loss sensitivity factor (LSF) method, the active and reactive power loss reduction are 41.30 % and 38.64 % respectively, least bus voltage is enhanced to 0.9405 pu from 0.8978 pu and the reliability indices are also improved.

Improving the reliability of power distribution substations equipment for life extension by considering Condition Based Maintenance

Maintenance of aged power equipment is a proven technique for establishing systems reliability and longevity. It is extensively relevant when combined with Condition Based Maintenance (CBM) approaches for predicting power system infrastructure life, especially with imminent obsolescence. The research focuses on distribution companies with mixed aged power infrastructure, which continuously degradate. A significant setback in older systems is the scarcity of replacement parts leading to unplanned investment in substantial infrastructure due to unexpected failed components that are no longer in production. To guarantee excellent infrastructure health in older equipment, utility companies should consider applying Condition Based Maintenance (CBM) using Artificial Neural Network (ANN) to stabilize older equipment and restore malfunctioning assets. Studies have shown that the life span of older equipment can be extended when adequate maintenance strategies are put in place through the prediction of possible failures using equipment inspections and risk matrix. CBM's strategy improved the Key Performance Indicator (KPIs) System Average Interruption Duration Index (SAIDI) has improved by lowering the average monthly customers power interruptions by 19,15 % lesser time spent without electricity. The System Average Interruption Frequency Index (SAIFI) was improved by lowering the average monthly power interruptions frequency by 20,63% lesser outage frequency. The Distribution Supply Loss Index (DSLI) was improved by dropping the average monthly power losses by 7,5% power losses saved. The Customers Average Interruption Duration Index (CAIDI) was improved by lowering the average customer interruption by 36.1% improvement from the average period before the CBM optimization. The Average System Availability Index (ASAI) was improved by shortening the average annual interruption durations by 1,36%. The ASUI was improved by increasing the average duration of electrical power availability by 1.28%. The optimization of CBM was measured over 24 moths period.

Application of Power System Reliability and Outage Cost Indices on 33/11 kV Distribution Injection Substation: A Case Study of Asaba Business District

The energy satisfaction that consumers can obtain from a power service provider solely depends on how reliable the feeder to which such customers are connected guarantees adequate and secure energy delivery. This research work is, therefore, to assess the reliability indices and the cost of expected electricity not supplied to the Asaba metropolis through the Benin Electricity Distribution Company (BEDC) Asaba 33/11 kV distribution injection substation. The method used consists of computing the System Average Interruption Duration Index (SAIDI), System Average Interruption Frequency Index (SAIFI), Customer Average Interruption Duration Index (CAIDI), Average Service Availability Index (ASAI), and Expected Energy Not Supplied Index (EENS) of the four feeders emanating from the substation and radiating into the metropolis. This is achieved by first collecting the outage hour, frequency of outage, and expected energy at the point of outage from the station's hourly logbook. The input data is fed into a program written in a MATLAB/OCTAVE environment. The values of the most important reliability index, ASAI, or availability, computed on the SPC, Anwai, Express, and Asaba Commercial feeders are 0.24, 0.23, 0.23, and 0.76 p.u., respectively, in 2020, while in 2021, these values are 0.32, 0.31, 0.33, and 0.83 p.u., respectively. Using the ASAI standard value from IEEE Standard 1366-2003, which is 0.999 as a benchmark, shows that all the feeders can be categorized as less reliable in the years under study. The annual cost of expected energy not supplied during power interruptions to Asaba electricity consumers in 2020 is $2,426,187.046 and $2,214,669.91 in 2021, respectively.

Pengaruh Automatic Change Over Switch Terhadap Peningkatan Keandalan Gardu Distribusi T3-200A/1 Penyulang PLR-04

The process of distributing electrical energy has the potential to cause disturbances that can occur due to natural disturbances, disturbances to electrical equipment, disturbances at the generating center, transmission lines, and disturbances in the distribution network that can disrupt the reliability and service quality of the distribution of electrical energy. The quality of reliability can be rated by the length of outages, which can be determined using the System Average Interruption Duration Index (SAIDI), and how often blackouts occur in one unit of time, which can be determined using the System Average Interruption Frequency Index (SAIFI). In maintaining the reliability of electrical energy, additional equipment is needed that is capable of supplying backup energy to the load when a disturbance occurs, namely the Automatic Change Over Switch (ACOS). ACOS is a device that works automatically for the process of maneuvering the network from two voltage sources to maintain electricity availability without having to have long blackouts due to disturbances or loss of voltage at the main source. The use of the Automatic Change Over Switch (ACOS) is proven to be able to increase the reliability of electrical energy at distribution substation T3-200A/1 feeder PLR-04 by reducing the length of time outages (SAIDI) and reducing the frequency, because customers don't feel outages when the disturbance occurs. In addition, the use of Automatic Change Over Switch (ACOS) can also reduce the energy not supplied (ENS)

Analysis of the quality indicators of electricity supply services on the example of the distribution system operator JSC "Kharkivoblenergo"

The resolution of the National Commission in 2021 for the operator of the distribution system JSC “Kharkivoblenergo”, which operates in the territory of the city of Kharkiv and the Kharkiv region, established a tariff for electricity distribution services with the application of incentive regulation, which provides for tariff formation on the basis of long-term regulation of tariffs and adjustment of the necessary income of the Company based on the performance of the task of achieving the target values of the quality indicators of electric energy and compliance with the guaranteed standards. In accordance with this Resolution, the indicators of the quality of services System Average Interruption Duration Index (SAIDI) and System Average Interruption Frequency Index (SAIFI) for the supply of electric energy were analysed using the example of the operator of the distribution system JSC “Kharkivoblenergo”. The SAIDI quality indicator is characterized by the duration of long interruptions in electricity supply in the distribution system of JSC “Kharkivoblenergo”. The SAIFI quality indicator provides information on the frequency of long interruptions in electricity supply in the distribution system of JSC “Kharkivoblenergo”. The analysis of SAIDI and SAIFI indicators was performed for the short-term period of operation of the operator of the distribution system JSC “Kharkivoblenergo”, namely for December 2021. Based on the results of the analysis of SAIDI and SAIFI indicators, it follows that the achievement of the target values of quality indicators allows adjusting the necessary rate of income for the operator of the distribution system JSC “Kharkivoblenergo”, and also creates a favourable investment climate, which ensures modernization, reconstruction and construction for the renewal of the energy infrastructure with the aim of improving the quality of providing services for the supply of electric energy to consumers. Also, the analysis of the indicated indicators made it possible to evaluate the work of JSC “Kharkivoblenergo” in terms of the implementation of established quality indicators, to identify problem areas in the Company's activities regarding the provision of guaranteed quality standards, to form and practically implement an investment program, to determine how quality indicators are reflected in tariff formation in the incentive regulation.

Customer Orientated Indices and Reliability Evaluation of Meshed Power Distribution System

Aim. Reliability evaluation of a system or component or element is very important in order to predict its availability and other relevant indices. Reliability is the parameter which tells about the availability of the system under proper working conditions for a given period of time. The study of different reliability indices are very important considering the complex and uncertain nature of the power system. In this paper reliability evaluation of the meshed distribution system is presented. This paper also evaluates basic indices such as average failure rate, average outage time and average annual outage time. Along with basic indices, customer orientated indices such as system average interruption frequency index, system average interruption duration index and customer average interruption duration index of an electrical power distribution system is also evaluated. The electrical power distribution system taken for study is meshed distribution system in nature.Aditya Tiwary. "Customer Orientated Indices and Reliability Evaluation of Meshed Power Distribution System" Reliability: Theory & Applications, vol. 15, no. 1, 2020, pp. 10-19. doi:10.24411/1932-2321-2020-11001

Analysis of The Reliability of The 20kV Distribution System of PT PLN (Persero) ULP Tarakan Using Root Cause Problem Solving Methods

The distribution system is one of the components of the power system that cannot be separated from the occurrence of interference or damage, which causes factors from within the equipment and factors from outside that can cause blackouts. In this final project, the reliability problems of SAIDI, SAIFI and CAIDI in 2021 at PT PLN (Persero) ULP Tarakan will be discussed using the RCPS (Root Cause Problem Solving) method. The parameters used to see the reliability of the distribution network are SAIDI (System Average Interruption Duration Index), SAIFI (System Average Interruption Frequency Index) and CAIDI (Customer Average Interruption Duration Index). By comparing the SAIDI, SAIFI and CAIDI reliability indices with the IEEE 1366-2003, SPLN 68-2: 1986 and WCS&WCC reliability indices. Where the comparison results of SPLN 68-2: 1986 and SAIDI = 21.09 j/p/t and 6.45 j/p/t (Meets Standard), SPLN 68-2: 1986 and SAIFI = 3.2 k/p/t and 7.38 k/p/t (Does Not Meet Standard), IEEE 1366-2003 and SAIDI = 2.3 j/p/t (Does Not Meet Standard), IEEE 1366-2003 and SAIFI = 1.45 k/p/t and 7.38 k/p/t (Does Not Meet Standard), IEEE 1366-2003 and CAIDI = 1.47 j/g/t and 9.89 j/g/t (Does Not Meet Standard), WCS&WCC and SAIDI = 3 j/p/t and 6.45 j/p/t (Does Not Meet Standard), WCS&WCC and SAIFI = 1.666 k/p/t and 7.38 k/p/t (Does Not Meet Standard). If it does not meet the predetermined standards, Root Cause Problem Solving analysis is carried out.

Electric power distribution maintenance model for industrial customers: Total productive maintenance (TPM), reliability-centered maintenance (RCM), and four-discipline execution (4DX) approach

The reliability of the electric power distribution system is crucial for industrial consumers, particularly in Karawang Regency, one of the industrial centers in Indonesia. The management of electricity supply for industries in Karawang Regency is entrusted to the Indonesian State Electricity Enterprises, also known as PLN. However, there are still disturbances in the distribution system that affect industrial customers. The primary causes of these disturbances are 39% jointing damage, 36% damage caused by third parties, and 15% damage to cubicles. The occurrence of these disturbances is closely tied to maintenance activities on the electric power distribution system. To assess the distribution system's reliability, various indices are calculated, including the System Average Interruption Frequency Index (SAIFI), System Average Interruption Duration Index (SAIDI), energy not supplied (ENS), and feeder disturbance indices. Currently, PT PLN (Persero) UP3 Karawang employs a maintenance model that combines corrective and preventive methods with the four-discipline execution (4DX) approach. This study aims to develop an improved maintenance model that enhances the overall performance of the electric power distribution system for industrial customers. In this study, a maintenance model is proposed by integrating the total productive maintenance (TPM) method, reliability-centered maintenance (RCM) method, and four-discipline execution (4DX) approach. The developed maintenance model is tested on 40 feeders serving industrial customers. A comparative analysis is performed before and after implementing the maintenance model, considering the SAIFI, SAIDI, ENS, feeder disturbance, and overall equipment effectiveness (OEE) indexes. The analysis of the 40 feeders reveals improvements in performance following the implementation of the maintenance model using the TPM, RCM, and 4DX methods. Prior to implementation, the SAIFI was 0.24 times/cust.yr, SAIDI was 1.877 min/cust.yr, ENS was 60,470 kWh, feeder disturbance occurred 8 times, and OEE was 0.99935. After implementation, the SAIFI improved to 0.016 times/cust.yr, SAIDI reduced to 1.342 min/cust.yr, ENS decreased to 41,241 kWh, feeder disturbance reduced to 4 times, and OEE increased to 0.99962. Consequently, the performance improvements are as follows: SAIFI by 33%, SAIDI by 29%, ENS by 32%, feeder interference by 50%, and OEE by 0.027%.

Reliability evaluation method for distribution network with distributed generations considering feeder fault recovery and network reconfiguration

AbstractThis paper presents a reliability evaluation method for distribution network with distributed generations considering feeder fault recovery and network reconfiguration, and mainly addresses issues: 1) insufficient consideration of the characteristics for the components and distributed generations (DGs) of distribution network such as time sequences, randomness and intermittency; 2) changes in the feeder area of the distribution network after the access of DGs; and 3) multi‐dimensional reliability index for distribution network with DGs has not been formed perfectly. Firstly, Markov reliability model for distribution network components/DGs is established in our study. Then, considering the fault recovery and network reconfiguration of the feeder area, island partitioning method of distribution network with DGs is also proposed. Moreover, a reliability evaluation model is presented for distribution network with DGs based on sequential Monte Carlo method. Case study is performed on the improved IEEE RBTS BUS6 F4 feeder system, and the research results indicate the validity and effectiveness of the proposed method. In addition, the system reliability indicators, such as system average interruption frequency index (SAIFI), system average interruption duration index (SAIDI), customer average interruption duration index (CAIDI), and average system availability index (ASAI), are studied and discussed in detail from three dimensions: the access of DGs, the types of DGs, and the capacity of DGs.

PENINGKATAN KEANDALAN PENYULANG TUKAD MUSI DAN PENYULANG BATANGHARI PT.PLN (PERSERO) UP3 BALI SELATAN ULP SANUR DENGAN POLA RADIAL

The reliability of the distribution system will affect the quality of the electrical energy received by customers. The system will be said to be reliable if the disturbances and power outages that occur for a certain period of time are below the index set by an institution. The measure of the reliability of a system can be measured through the value of SAIDI (System Average Interruption Duration Index) or how long the system is interrupted and SAIFI (System Average Interruption Frequency Index) or how often a system is interrupted within 1 year and it was found that SAIFI's Tukad Musi Feeders were 1.9255 interruptions/subscribers per year, SAIDI were 26.5966 hours/customers per year and SAIFI's Batanghari Feeders were 1.6992 interruptions/subscribers per year, and SAIDI were 18.1486 hours/ subscribers per year by adding a component in the form of LBS to the two feeders will increase the reliability of the Tukad Musi feeder SAIFI of 1.8855 interruptions/customer per year, SAIDI of 26.0606 hours/customer per year and of Batanghari SAIFI feeder of 1.6814 interruptions/subscriber per year, SAIDI of 15.7925 hours / customer per year.

PENINGKATAN KEANDALAN PENYULANG TUKAD MUSI DENGAN PENAMBAHAN PENYULANG BATANGHARI DENGAN POLA LOOP

Reliability of the distribution system is one of the critical challenges and important indicators in the electricity power system. The indicators determining reliability are SAIFI (System Average Interruption Frequency Index) and SAIDI (System Average Interruption Duration Index). The method used to improve the reliability of the distribution system in this research is by converting two radial feeders, namely Tukad Musi feeder and Batanghari feeder, into a loop configuration.The calculation results show that before the improvement, the SAIDI value for the Tukad Musi feeder is 26.59 hours/customer/year, and the SAIFI is 1.92 interruptions/customer/year. The initial values of SAIDI for the Batanghari feeder are 18.14 hours/customer/year, and SAIFI is 1.69 interruptions/customer/year. By implementing a loop configuration through the addition of extra channels at both ends of the feeders, the SAIDI is reduced to 24.79 hours/customer/year, and SAIFI becomes 1.89 interruptions/customer/year. Further improvements are achieved by maneuvering a portion of the load, resulting in SAIDI of 21.51 hours/customer/year and SAIFI of 1.83 interruptions/customer/year.This study contributes to enhancing the reliability of the distribution system by converting radial feeders into loop configuration. The findings can serve as guidelines for planning and developing a more reliable and efficient distribution system.

Distribution Network System Reliability Index Study PLN North Banten in 2023

An important aspect in the distribution of electrical energy is the reliability of the system. Therefore, the authors conducted research on SAIFI (System Average Interruption Frequency Index) and SAIDI (System Average Interruption Duration Index). To analyze the values of SAIDI and SAIFI, data on disturbances are needed. For SAIDI and SAIFI values from January to March 2023. The smallest SAIDI and SAIFI values occurred in February. This indicates that in February there was minimal disruption due to routine inspections and periodic maintenance on the SUTM network in the PLN UP3 North Banten area.

Techno-Economic analysis of distributed generation for power system reliability and loss reduction

ABSTRACT This paper presents a techno-economic analysis of the impact of distributed generation (DG) integration for power loss reduction and reliability of two 33 kV radial outgoing feeders at the Motta distribution substation in Ethiopia. Transient earth faults and permanent short-circuits were identified to be the most common causes of interruptions. The substation's system average interruption frequency index (SAIFI) is 806 and its system average interruption duration index (SAIDI) is 1394.145 for planned outages. This necessitates the pursuit of effective methods to increase the reliability of the distribution system. The results show that the distribution system is more reliable with the SAIFI and customer average interruption frequency index (CAIFI) reduced by 97.8%, SAIDI reduced by 76%, average service availability index (ASAI) increased by 14.38%, and average service unavailability index (ASUI) reduced by 76%, resulting in a total power loss reduction of 0.32 MW. The cost analysis was performed using the Monte Carlo (MC) reliability analysis and the DG net present cost analysis results in a payback period of less than five years indicating that the system is profitable.

Improving the efficiency of medium voltage (MV) distribution lines using risk matrix for optimized maintenance

Medium Voltage overhead lines within North-West power utility companies in South Africa are confronted by higher volumes of deficiencies leading to frequent power failures. An essential quality of service factor considered in power distribution is the electricity supply to customers free of interruptions. Due to the higher number of electrical power line faults associated with the power system life span, achieving the desired level of reliability becomes an enormous task. The paper shares the findings of a study on performance improvement of MV distribution overhead lines using a risk matrix for deficiency analysis and clearing of such defects. A pilot study was conducted, and the risk matrix strategy developed in the study improved the reliability and key performance indicators by trimming down the overhead power line deficiencies. Defect clearing lowered outage frequency, durations, and power losses. The System Average Interruption Duration Index (SAIDI) was enhanced by lowering the outage duration by 108.64 h annually. The System Average Interruption Frequency Index (SAIFI) improved by reducing the outage frequency by 45.45 sustained occurrences annually and Reticulation Supply Loss Index (RSLI) by 8.31 MVA monthly.