Distribution System Reliability Indices Research Articles

Determining target levels of power distribution system reliability indices using machine learning

Electrical distribution system (EDS) reliability has always been a critical subject due to the considerable share of distribution systems in power interruptions to end-users. Meeting regulatory service quality standards requires distribution companies to achieve defined reliability levels for performance improvement. Conventionally, specialists determine target reliability based on experience, experimental knowledge, and rules of thumb. However, these methods are error-prone and may result in suboptimal investments, economic inefficiency, and inadequate resource allocation in EDS operation and planning. Accordingly, this paper presents a machine learning-based method to determine the target level for EDS's reliability indices based on its historical performance. The approach involves comprehensive analysis of historical EDS reliability data, followed by a data envelopment analysis (DEA) to assess performance across subdivisions like substations or feeders, identifying the most effective units. Subsequently, machine learning models—Random Forest (RF), Support Vector Machine (SVM), and Radial Basis Function (RBF) network—are trained on optimal subdivisions from the DEA stage. These models accurately estimate target reliability for all subdivisions, contributing to the overall determination of the EDS target reliability level. A three-scenario case study validates the proposed method, suggesting its potential applicability as a valuable tool for regulatory agencies in setting EDS reliability targets. While admitting the potential challenges, notably the method's reliance on the quality and completeness of the historical data collected by distribution companies, the paper emphasizes the importance of collaborative efforts to ensure data accuracy and sufficiency. The proposed method leads to a fair mechanism to determine the target level for a real EDS's reliability indices in comparison with a business-as-usual scenario. Moreover, it provides a reliability performance ranking for the EDS's subdivisions.

Impacts of Transactive Energy Trading on the Load Point Reliability Indices of LV Distribution System

Impacts of Transactive Energy Trading on the Load Point Reliability Indices of LV Distribution System

Reliability-Oriented Reconfiguration of Power Distribution Systems Considering Load and RES Production Scenarios

The ever-increasing integration of non-dispatchable distributed generation, i.e., renewable energy sources (RES), arises new challenges in the field of power system's reliability. Distribution network reconfiguration (DNR) is a cost-effective approach for the distribution system operator (DSO) that wishes to enhance system's reliability without infrastructure upgrades. This paper introduces a novel path-based mixed-integer second-order cone programming model to optimally solve the reliability-oriented DNR problem. The DSO's objectives that are optimized are: a) improvement of distribution system's reliability indices and b) minimization of power losses. The proposed model is enriched with a scenario-based stochastic programming formulation that considers multiple levels of load and RES production. The standard 33-nodes distribution system and a real-world 83-nodes distribution system are employed to prove the efficiency and applicability of the model. Firstly, the multi-objective nature of the reliability-oriented DNR problem is investigated by conducting a sensitivity analysis, which reveals a trade-off region between reliability indices and power losses. Moreover, the obtained results show different global optimal solutions when the variability of load and RES production is considered. This highlights the importance of considering a scenario-based approach for load and RES production when solving the reliability-oriented DNR problem.

Improving System Reliability of Secondary Distribution Networks Through Smart Monitoring

This paper presents results of studies of the impacts of substation monitoring on reliability indices of distribution systems. It was detected that the fault detecting and repair time was the main cause of the prolonged outages experienced in the system which increases the poor reliability indices of the system. The intelligent monitoring device detect open circuit faults and relay to the base station in 30s compared with 3 to 24 hours it was taking to detect fault. The intelligent substation monitoring device reduced the fault detection time and hence improves the reliability of distribution systems. The system was simulated, and result showed that SAIDI was reduced from 244 hours of outage per annum to just 98 hours of outage per annum while CAIDI was improved from 10 hours of interruption per outage to 5 hours of interruption per outage. This paper demonstrated that the fault detection and reporting time can be greatly reduced by the use of intelligent monitoring system and reliability indices.

Reliability Assessment of Power Distribution System Using Relative Customer Average Interruptions Duration Index Model

Reliability assessment of power distribution system deals with the adequacy of overall system supply and indicates the system behaviour and response at the customer end. In order to attain satisfactory degree of reliability in electric power distribution system, there is the need to develop a model that will improve the three major system reliability indices via Systems Average Interruptions Duration Index (SAIDI), Systems Average Interruptions Frequency Index (SAIFI) and Customer Average Interruptions Duration Index (CAIDI). This research paper therefore, developed a Relative CAIDI model for assessment of reliability indices of electrical power distribution system. In this paper, ten (10) years outage data from selected distribution feeders of Ibadan, Ikeja and Port-Harcourt distribution systems were obtained and analyzed using curve fitting tools in MATLAB. The system reliability indices served as input parameters for the development of Relative CAIDI model. The best curves that fitted the relationship between the Relative CAIDI and the number of feeders were obtained using Lagrange polynomial functions, Newton polynomial functions and Chebyshev polynomial functions as performance evaluation metrics. The results showed that Ibadan, Ikeja and Port-Harcourt distribution systems had Relative CAIDI of 0.718, 0.3976 and 0.5279 respectively and the validation results produced by Largrange polynomial function, Newton polynomial function and Chebyshev polynomial function were 0.717, 0.3979 and 0.5278 respectively. The model developed is a polynomial of order six which depends majorly on the power requirements of the distribution systems. The developed model can be used for effective reliability assessment of electrical power distribution systems as well as forming a base-line information for system planning and maintenance strategies. Keywords: Reliability Indices, SAIDI, SAIFI, CAIDI, Chebyshev Polynomial Function, Lagrange Polynomial Function, Newton Polynomial Function. DOI: 10.7176/NCS/14-01 Publication date: August 31 st 2022

A Bi-level optimizer for reliability and security assessment of a radial distribution system supported by wind turbine generators and superconducting magnetic energy storages

This paper is aimed at improving the reliability and security of radial distribution system supported by wind turbine generators (WTGs) and superconducting magnetic energy storages (SMESs). For reliability indices assessment, the load-oriented indices including energy not supplied (ENS) and average energy not supplied (AENS) as well as the customers-oriented indices including system average interruption duration index (SAIDI), system average interruption frequency index (SAIFI), customer average interruption duration index (CAIDI), and average service unavailability index (ASUI) are evaluated. Network security index (NSI) is also addressed, which refers to the risk level for current flow in the lines prior reaching to extremis. A multi-objective function is composed and formulated in order to simultaneously minimize ENS, SAIFI, SAIDI, ASUI, and NSI as indices which characterize the performance of distribution system using a hybrid approach based on equilibrium optimizer (EO) along with the loss sensitivity factors. A bi-level optimizer based on the hybrid approach addressing all constraints is applied for simultaneous minimization of reliability and security indices of distribution system. The outer level looks for an optimal sizing and sitting of WTGs and SMESs as well as optimal weighting coefficients whose evaluation is no longer assumed arbitrarily or left to the preferences of the decision maker. The inner level optimizes charging and discharging powers as well as initial state of charge of SMESs. Modeling of feeder's failure rate applying several mathematical functions is considered. The effectiveness of proposed approach is validated on the IEEE 33-bus test system considering commercial, industrial, residential, and mixed time-varying voltage-dependent load models. The performance of the distribution system is also checked as regards the energy loss in feeders, the bus voltage deviation from rated value as well as the voltage stability of the system. For validating the effectiveness of the EO algorithm, the obtained results using the EO algorithm are compared with those predicted by particle swarm optimization (PSO) and genetic algorithm (GA). Moreover, the obtained results display that the bi-level optimization can successfully achieve satisfactory improvement of the reliability and security indices of the distribution system.

Evaluation of Distribution System Reliability Indices Using Fuzzy Reasoning Approach

The most fundamental problems in the distribution system are the quality, the continuity, and the power supply. Political and economic changes were accompanied by changes in the structure of the electric load in the distribution network. Lack of investment and aging of the distribution company assets was accompanied by a decrease in the reliability of the distribution system. Identification and classification of assets from the point of view of their maintenance and replacement was one of the problems that were posed to the engineers. Fuzzy logic can be successfully used to evaluate distribution system reliability indices. In this paper fuzzy logic is used to evaluate the distribution system reliability indices of lines and transformers using six input variables. These variables considered the most important are: Age, Operation, Maintenance, Electrical current loading, Exposure and Weather conditions (Wind or Temperature). The fuzzy inferences knowledge-based IF-THEN rule is developed using Matlab Fuzzy software. The detailed analysis of the fuzzy system surfaces shows that the factors taken in consideration are dynamically and accurately connected to each other. The constructed rules based in engineering experience accurately represent the Reliability Indices.

Effects of On-Site PV Generation and Residential Demand Response on Distribution System Reliability

In the last few decades, there has been a strong trend towards integrating renewable-based distributed generation systems into the power grid, and advanced management strategies have been developed in order to provide a reliable, resilient, economic, and sustainable operation. Moreover, demand response (DR) programs, by taking the advantage of flexible loads’ energy reduction capabilities, have presented as a promising solution considering reliability issues. Therefore, the impacts of combined system architecture with on-site photovoltaic (PV) generation units and residential demand reduction strategies were taken into consideration on distribution system reliability indices in this study. The load model of this study was created by using load data of the distribution feeder provided by Bosphorus Electric Distribution Corporation (BEDAS). Additionally, the reliability parameters of the feeder components were determined based on these provided data. The calculated load point and feeder side indicators were analyzed comprehensively from technical and economic perspectives. In order to validate the effectiveness of the proposed structure, four case studies were carried out in both DigSILENT PowerFactory and MATLAB environments.

Evaluation of Distributed Generation Impact on Reliability of a Distribution System using DIgSILENT PowerFactory

As an effective supplement to the centralized fossil fuel based traditional generation, Distributed Generation (DG) has become an effective alternative choice and has been rapidly increasing since past few years due to growing demand for electricity and the new policies of governing bodies for usage of green energy. In overall power system, distribution systems are more vulnerable to faults and reliability aspects of such systems becomes an important issue. With higher penetration of DG into the distribution network, it will be necessary to study the impact of such generation on the various aspects of distribution system. Thus, increase in rate of penetration DGs into the distribution system on one side and increased faults in distribution network on another side, will make the study of impact of DG integration on distribution system reliability an interesting topic of research. The present work focuses on evaluation of impacts of integration of such DGs on reliability of local distribution network, typically in an urban scenario By using the simulation method using DIgSILENT PowerFactory software, the impacts of integration of DG in terms of enhancement in distribution system reliability indices and reduction in system losses for different scenarios are studied and presented in this paper. Based on the simulation results obtained and after analysis of the distribution system, overall results are summarized by focusing on the installation of suitable capacity of DG and the location of DG which are important factors affecting the system losses and system reliability indices.

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

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.

A Composite Reliability Index for Power Distribution System in Renewable Microgrid Penetrated Energy Market

High penetration of renewable micro-grids in power distribution system has given rise to unique reliability issues owing to their intermittent nature. Moreover, individual reliability indices of power distribution systems tend to present conflicting results. Therefore, a single index to quantify the overall reliability of substations is necessary. In essence, this work proposes a Composite Reliability Index (CRI) for renewable penetrated Indian power distribution system. In this work, reliability indices are normalized using Z-scores, followed by Principal Component Analysis (PCA) for weight decision. Particularly, indices recommended in IEEE Std 1366-2003 and practiced by Indian utilities in real-time are studied. Finally, results of test-systems data analysis show that proposed CRI can expedite the reliability assessment process in multiple permutations of systems and operational choices.

An Enhanced Algebraic Approach for the Analytical Reliability Assessment of Distribution Systems

The calculation of standard reliability indices is critical for assessing quality service and guiding the planning and operation of distribution systems. Traditionally, such calculation has relied on the application of analytical methods based on simulation techniques, which preclude the use of exact methodologies when reliability assessment is incorporated into operation and planning models. This shortcoming has been recently addressed by the development of two optimization-based approaches for the analytical reliability assessment of distribution systems. Unfortunately, both methods are either incomplete or computationally expensive as compared with those based on simulation. In order to overcome these issues, this paper presents a novel and efficient algebraic approach to calculate the standard network-dependent reliability indices of distribution systems. As a distinctive feature over previous non-simulation-based methods, no optimization process is involved. Thus, the proposed approach relies on the solution of a set of linear equations for which effective algorithms are available. Several benchmarks including a real-life 1080-node system have been used to demonstrate the computational superiority of the proposed method. The successful numerical experience supports the suitability of the proposed algebraic model for reliability-constrained distribution system operation and planning.

A Sensitivity Based Approach for Assessment of Reliability Indices of Electrical Distribution Systems.

In Nigeria, satisfactory degree of reliability has not been attained in the power system in recent times. The average duration of interruptions that customers experience is very high and the degree varies widely especially in urban and commercial cities of the country. This research paper therefore presents the sensitivity analysis of electrical distribution systems. Ten years of outage information from seven major distribution systems – Ibadan, Ilorin, Ikeja, Portharcourt, Kaduna, Kano and Benin were used as input data for computation of the mean and standard deviation for the system reliability indices using statistical analysis. The computed system reliability indices were used as input parameters in the analysis. A sensitivity analysis is performed to assess how the operation parameters could influence the numerical results. The results of the sensitivity studies indicate that Etete feeder of Benin distribution system has the highest SAIDI sensitivity of 0.5478 because of prolonged customers‘ interruptions on the feeder while waterworks feeder of Ilorin distribution system has the least SAIDI sensitivity of 0.0019. Cocoa feeder of Ibadan distribution system has the highest SAIFI sensitivity of 1.0459 because of the frequent interruptions while waterworks feeder of Ilorin distribution system has the least SAIFI sensitivity of 0.0268. Ikpoba Dam of Benin distribution system recorded the highest CAIDI sensitivity of 0.8466 with waterworks feeder also recording the least CAIDI sensitivity of 0.0075. The results from this research paper provides baseline information for planning and managing distribution system on Nigeria national grid. Keywords: Sensitivity, Reliability indices, Distribution systems, SAIDI, SAIFI, CAIDI, Interruptions. DOI : 10.7176/APTA/77-07 Publication date :May 31 st 2019

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

Simultaneous placement of renewable DGs and protective devices for improving the loss, reliability and economic indices of distribution system with nonlinear load model

ABSTRACT In this paper, the simultaneous placement of renewable distributed generation (DG) and protective devices are discussed in the distribution system with nonlinear load model. The load model is considered as a combination of various customers’ daily load patterns and sensitive to voltage frequency. The considered DGs are wind turbine and photovoltaic. The breaker, relay and fuse are considered as protective devices. The objective functions of the problem consist of the active and reactive power loss, the reliability index and the profit of company of distribution system. The whale optimisation algorithm is used for multi-objective optimisation. Moreover, a method based on fuzzy set theory is employed to extract one of the Pareto-optimal solutions as the best compromise one. The proposed algorithm is implemented on the 69-bus distribution system and actual 101-bus distribution system in Khoy–Iran. The results indicate the high performance of the proposed method in improving the technical and economic indices of the network.

Reliability Improvement of Distribution System by Optimal Sitting and Sizing of Disperse Generation

Recent studies have publicized that renewable energy resources are the only answer to trim down energy crisis and also able to diminish green house gases. Thats why disperse generation is very significant for sustainable development in power sector. This paper presents an analytical algorithm to find optimal location and a best suitable size of distributed generator (DG) to minimize system losses. Authors also prove that scatter generation is used not only to reduce the gap between demand and supply of power with minimum amount losses, but it can also improve the reliability of distribution system. The results obtained from a case study of 34 bus radial distribution system have proved the efficiency of algorithms for loss minimization and competency of DG to enhance the reliability indices of the conventional distribution system.

Prioritizing the Restoration of Network Transformers Using Distribution System Loading and Reliability Indices

A method is proposed to prioritize the repair or replacement of out-of-service transformers that feed a heavily meshed secondary grid. Priority assigned to the restoration of a specific transformer is based on the risk reduction that results from this replacement. Risk is defined as the reduction in the probable number of customers out of service should the transformer return to service. This measure of risk addresses the possibility of network collapse following feeder failures (occasioned by load-induced failure of transformers or feeders) and local customer impact on the secondary network. The prediction of risk makes extensive use of load predictions for feeder sections, network transformers, and secondary mains. A software tool has been developed to implement the equations proposed in this paper. This software gives system planners and operators the ability to quickly and economically select the next transformer to be repaired or replaced.

Optimal switch placement considering costs and annual reliability improvement during the regulatory period

Summary The introduction of reward/penalty mechanisms by the national regulation authorities has strongly increased the utilities' interest in distribution systems reliability improvement. Usually, the regulator correlates such mechanisms with the annual number and/or duration of interruptions per customer, requiring the utilities to reach a target value for these reliability indicators each year for a given regulatory period. Installing switches along the distribution network positively affects reliability but does involve utility costs. Therefore, utilities need a method to schedule annually the switches' placement to obtain the required annual reliability improvement in a cost-effective manner. This paper proposes a simple and effective model of the optimization problem that enables the distribution network operator to try to achieve uniform levels of improvement in distribution system reliability indices during the regulatory period. In this perspective, the paper presents a way to provide the optimal number, type, and position of the switches that must be installed each year to achieve both the targeted annual reliability improvement and the cheapest investment cost during the overall regulatory period. The proposed approach is formulated as a multiobjective optimization problem and is solved using a genetic algorithm. The proposed approach is useful for the distribution network operator since it is able to provide the overall minimum investment cost required for each desired reliability level to be reached annually over the regulatory period, as well as the maximum annual reliability that can be achieved for each overall economic investment by performing only one single optimization.

State of Art, Reliability In Electrical Distribution Systems Based On Markov Stochastic Model

This paper presents a technical model for the study and evaluation of the expected reliability indices of an electrical distribution system, this assessment focuses on the classification and determination of states of different network components, considering flaws in the other elements. An algorithm to define these states, for any distribution network based on Markov chain is proposed. Particularly, a Markov model is used to calculate the frequency of the availability and network failure based on known global indices as system average interruption frequency index (SAIFI) and the system average interruption duration index (SAIDI). The goal is to ensure the availability, continuity and quality of electricity supply to each end user by predicting future distribution system based mainly on the operation and failure of a system with a given number of elements. The proposed model focuses on the evaluation of cycle and residence time of each state, in order to reduce the state space at each load point. The proposed techniques reduce the number of states and size of the transition matrix without affecting the accuracy of calculation.