Distribution System Reliability Assessment Research Articles

Reliability assessment of distribution system using Petri net for enhancement of situational awareness

The sprawl of power system network paved a challenge to achieve quality and uninterrupted power to the consumers. Lack of situational awareness (SA) is a key concern, because it adversely affects the reliability of the system. This paper concerns about the co-ordination of protective equipment in distribution side of the power system network when there is a fault on any section of the network. Petri net (PN) based approach has been proposed for modeling the co-ordination between protective equipment for different fault scenarios to assess the operational reliability. The PN model encapsulates the dynamic behavior of the protective equipment together with their co-ordination. This assists in predicting the future disturbances and helps to take precautionary measures for the pre-warning situation and prevent cascaded failures, leading to enhanced SA. To analyze the effect of uncertainties in the operating time of protective equipment, fuzzy Petri net (FPN) approach has been explored. In addition, this research also incorporates a comparison between PN and fault tree, to analyze the impact of protection co-ordination modeling on power system reliability. Furthermore, event tree analysis (ETA) is used to evaluate the loss of probability of SA. The studies have been carried out on a part of distribution system and 14 bus ABB distribution system for implementation and validation of the proposed method.

A weather-based power distribution system reliability assessment

The continuity of power supply is affected by many factors; the weather conditions to which power system components are exposed are considered the most effect. A new methodology to assess the reliability of distribution system considering the impact of different weather conditions is presented in this paper. The proposed method considers possible future changes in the weather patterns that might occur differently from what it was in the past. Modified sets of reliability indices are presented for mathematically predicting reliability performance based on historical reliability data under specific past weather conditions combined with forecasted future weather conditions. The proposed method is applied to the distribution system components of RBTS; the results demonstrate the significance of considering the forecast of weather conditions in reliability assessment.

Effect of a Single Fault Passage Indicator Placement on Radial Distribution System Reliability under Two Weather Conditions

The components in the overhead electrical network are continuously exposed to the physical environment of varying weather conditions. If the weather around an electrical network is normal and consistent throughout a certain period of time, then the weather can be modelled as normal or single weather (SW). However, in practice, the overhead electrical network is always subjected to varying weather conditions such as normal weather and adverse weather then the weather is modelled as two weather (TW) model. Adverse weather (AW) can cause significant physical damage to the components, resulting in higher average failure rates and longer durations for power restoration. Without considering the weather conditions, the reliability assessment of the overhead electric power distribution system can be over-optimistic, and influence the planning and design decisions. The investigation of system reliability under two weather conditions provides the effect of percentage failures that occurs in severe weather conditions on average interruption duration per customer per year and the amount of energy not supplied per customer per year. This paper evaluates the reliability of a radial distribution system (RDS) considering single weather and two weather conditions. Further, the effect of the fault passage indicator placement on RDS under SW and TW is also evaluated. A fault passage indicator (FPI) is a device that indicates and communicates the fault's location to the operator hence reducing the fault identification time and improving the system reliability by reducing the outage duration time.

Reliability assessment and improvement of distribution system with virtual energy storage under exogenous and endogenous uncertainty

Exploiting flexibility of low-cost but uncertain demand-side resources attracts great attention in the recent research of the distribution system with special respect to reliability assessment and improvement. While various kinds of uncertainties and risks exist, such as the stochastic power of renewable energy resources (RES), etc., the literature overlooked the exogenous and endogenous uncertainties along with the utilization of these resources denoted as virtual energy storage (VES). Instead, this manuscript proposes a novel approach for reliability assessment and improvement of the distribution system in special consideration of the endogenous uncertainties in VES operations, also denoted as decision-dependent uncertainties (DDUs). The modified and unified probabilistic model of VES is first presented to reveal the dynamic process and human behavior of VES. Additionally, we extend our recent work on probabilistic optimization under DDUs to the reliability assessment problem which addresses the optimal load curtailment with the support of VES. Moreover, reliability indices are newly introduced to (1) calculate the response losses of VES and the consequence of overlooking these uncertainties, and (2) explain the difference between theoretical and practical reliability. Case studies based on the ground truth data verify that the available capacity of VES will gradually reduce (maximum of 40 %–60 %) because of DDUs and it reveals the overlooked risks by using “greedy” strategies in the previous models, while the best practical reliability performance (increased 5 %) is witnessed via the proposed methods. We further investigate four key factors affecting the reliability performance, i.e., probability level of chance constraints, DDUs levels, dispatch time period, and locations of VES. Eventually, reasonable suggestions are provided for better flexibility utilization of VES, and the system's reliability is further improved by around 30 %.

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

On the explicit formulation of reliability assessment of distribution systems with unknown network topology: Incorporation of DG, switching interruptions, and customer-interruption quantification

This paper presents an original approach for the evaluation of reliability of active distribution networks with unknown topology. Built upon novel reformulations of conventional definitions for distribution reliability indices, the dependence of system-oriented reliability metrics on network topology is explicitly formulated using a set of mixed-integer linear expressions. Unlike previously reported works also modeling mathematically the relationship between reliability assessment and network topology, the proposed approach allows considering the impact of distributed generation (DG) while accounting for switching interruptions. Moreover, for the first time in the emerging closely related literature, the nonlinearity and nonconvexity of the customer average interruption duration index are precisely characterized. The proposed mixed-integer linear model is suitable for various distribution optimization problems in which the operational topology of the network is not specified a priori. Aiming to exemplify its potential applicability, the proposed formulation is incorporated into a distribution reconfiguration optimization problem. The effectiveness and practicality of the proposed approach are numerically illustrated using various test networks.

Modeling of Adverse Weather Events in an Integrated Reliability and Power Quality Assessment of Distribution System Using Stochastic Diffusion Process

This paper presents the modeling of adverse weather events and their impact on the integrated reliability and power quality assessment of power distribution systems. With respect to previous works, stochastic modeling of adverse weather events is integrated into the Monte Carlo Simulation approach and its impacts on reliability and voltage sag indices are highlighted. In this paper, the aleatory and epistemic uncertainty are modeled into sampling of Time to Failure (TTF) using the Stochastic Diffusion Process. The Stochastic Diffusion Process, including the Jump diffusion is used to model the impact of adverse weather events on permanent and temporary failure rates. The proposed method is applied to the modified IEEE 34 node test feeder, and three case studies have been performed to investigate the impact of various uncertainties and adverse weather events. Numerical results for the IEEE 34 node test feeder are presented to quantify adverse weather impacts on both reliability and voltage sag indices.

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.

Development of Predictive Reliability Model of Solar Photovoltaic System Using Stochastic Diffusion Process for Distribution System

Reliability assessment of power distribution systems is an essential concern for electric utilities to maintain supply continuity. In the event of supply failure, distributed energy resources play a vital role in restoring the supply to customers. This paper presents the development of a predictive reliability model for distribution system with solar Photovoltaic (PV) system. At the initial stage, the hourly solar irradiance and temperature are forecasted using Stochastic Diffusion Process (SDP)-based Monte Carlo simulation from historical data. Later, the cloud transients are modeled using the Jump Diffusion Process integrated into SDP. The monthly failure rates of PV system components are evaluated from historical data using the Physics of Failure (PoF) reliability model. Finally, the predictive reliability evaluation of the practical distribution system integrated with the proposed solar PV model is carried out. Results demonstrate the capability of the developed model to handle continuous and discrete uncertainties with more accuracy.

Physics-Based Reliability Assessment of Community-Based Power Distribution System Using Synthetic Hurricanes

Physics-Based Reliability Assessment of Community-Based Power Distribution System Using Synthetic Hurricanes

Analytical reliability assessment of cyber-physical distribution system with distributed feeder automation

Cyber-physical distribution system (CPDS) handles power grid faults by feeder automation. The reliability assessment of CPDS has been intensively discussed for centralized feeder automation (CFA) in existing researches. However, the inapplicability of CFA reliability models, and the low computation efficiency issue of the mostly used Monte Carlo method greatly limits their application in practical engineering cases of the large-scale CPDS with the distributed feeder automation (DFA) mode. Thus, this paper proposes a region-based analytical reliability assessment method for DFA, which has high computation efficiency in the large-scale CPDS. Firstly, the reliability impacts of cyber system anomalies in the DFA mode are analysed and the cyber reliability models are built considering both cyber device failures and cyber-attacks. Then, the cyber system status is integrated into malfunction probability modelling of switches for reliability assessment. Finally, the load reliability is assessed based on the fault region division by the proposed analytical method and the reliability indices are calculated. The accuracy, efficiency and scalability of the proposed method are verified in case studies.

신뢰도지표를 활용한 신 가치기반신뢰도평가 (VBDRA) 기반의 배전 설비 투자 선택 방안 연구

We select the optimal distribution system investment plan, which has the largest ratio of the financial benefit and investment cost. We measure the financial benefit of investment plan based on the improvement level of reliability index on the target distribution system. However, in the classical value based distribution system reliability assessment (VBDRA), the financial benefit was measured based on the reliability index itself, so our approach is a new VBDRA. The improvement level of reliability index is converted to the financial benefit by multiplying the electricity interruption cost. In this study, we also introduce the reliability index calculation method based on three basic reliability parameters: average failure rate, average power outage time, and average annual power outage time. Then, we calculate the reliability index of six different distribution systems. Finally, we measure reliability index and financial benefits of three virtual distribution systems with different investment plans on distribution components. Based on the ratio of financial benefits to investment costs, we select the optimal distribution system investment plan.

Reliability Assessment and Improvement of Electrical Distribution Systems by Using Multinomial Monte Carlo Simulations and a Component Risk Priority Index

In this paper, a method of assessing and improving the reliability of power distribution systems based on Monte Carlo simulation and a novel risk priority index is proposed. The initialization of the assessment process is carried out by using Multinomial Monte Carlo simulation with a nonsequential technique to assess system reliability in the form of SAIFI and SAIDI indices. Then, the novel per-time-based component reliability indices representing the insights obtained from root-cause analysis for each component in the system are evaluated to make suitable decisions on improvement measures. The proposed indices are derived as a component risk priority index based on the principle of the failure mode and an effect analysis to prioritize and select the implementation points by the Pareto principle. By applying the proposed method, a reliability improvement should be achieved at the correct point with minimal operations. In addition, the proposed method can be used to study the effect of uncertainty regarding some device operations on the system reliability. To verify the performance of the proposed method and demonstrate its application, three case studies were performed on the IEEE RBTS Bus-2 test system. From the first case study, the results of the proposed assessment process were validated by comparison with a standard benchmark. The second case study showed the performance of applying the entire process to improve system reliability, and the results showed that system reliability can be improved significantly. The third case study was performed to determine the effect of uncertainty in protective device operations. The results of the third case showed that there was a significant decrease in overall reliability in terms of a higher level of power outages, while the performance of the protective components was slightly reduced.

Reliability Assessment in Rural Distribution Systems With Microgrids: A Computational- Based Approach

Rural distribution systems, especially in developing countries, tend to be less reliable than urban distribution systems because customers are (1) located remotely and (2) connected to weak aerial networks with radial topologies without redundancy. To improve reliability in rural areas, microgrids (MGs) are being integrated into conventional power systems. This study evaluates the effect on the reliability of rural distribution systems when MGs are introduced considering different penetration levels for renewable and nonrenewable distributed generation, and under rated power of energy storage. Here, we first formulate a reliability model for a rural distribution system with MGs. Based on this model, an interactive method using a sequential Monte Carlo simulation method is proposed and applied to calculate different conventional reliability indices. We show that this approach facilitates the selection of the parameters of the different systems constituting the MGs in order to comply with a predefined reliability objective. For instance, by introducing only photovoltaic distributed generation systems to the rural distribution systems under study, achieving the reliability objective is next to impossible. However, when correctly dimensioned-hybrid MGs are introduced, such an objective is successfully achieved. In the future, our model and the results provided herein could be combined with technical and economic studies to obtain an optimal solution that meets a certain reliability objective.

Reliability assessment of distribution system with the integration of photovoltaic and energy storage systems

With the current focus on energy and the environment, efficient integration of renewable energies, especially solar energy into power systems, is becoming indispensable. Moreover, to fully capture solar potentials and to recognize the unique characteristics associated with solar energy in power systems reliability assessment, a profound investigation is needed. Accordingly, this paper attempts to establish a comprehensive analytical approach for modeling the reliability of a hybrid system (Photovoltaic (PV) system with Energy Storage System (ESS)). To this end, the output of the PV system is modeled by a multi-state model, and the ESS system is modeled as a two-state Markov model. Moreover, the failure of the hybrid system’s components is considered by using the Failure Modes and Effects Analysis (FMEA) method. It then continues with the integration of the PV and ESS system model and the model associated with the failure of their components, thereby allowing the hybrid system to be represented as a multi-state model in analytical studies. Also, the conditional probability approach is used and related indices have been extracted. Finally, a discussion of a methodology for optimal hybrid system allocation and sizing in distribution systems, to minimize the electrical network losses and to guarantee acceptable reliability level and voltage profile is presented. The results obtained from the implementation of the case study, validate the major features of the proposed analytical model along with optimal placement of the hybrid system more efficiently.

Stochastic Diffusion Process-based Multi-Level Monte Carlo for Predictive Reliability Assessment of Distribution System

Reliability assessment of electrical distribution systems is an important criterion to determine system performance in terms of interruptions. Probabilistic assessment methods are usually used in reliability analysis to deal with uncertainties. These techniques require a longer execution time in order to account for uncertainty. Multi-Level Monte Carlo (MLMC) is an advanced Monte Carlo Simulation (MCS) approach to improve accuracy and reduce the execution time. This paper provides a systematic approach to model the static and dynamic uncertainties of Time to Failure (TTF) and Time to Repair (TTR) of power distribution components using a Stochastic Diffusion Process. Further, the Stochastic Diffusion Process is integrated into MLMC to estimate the impacts of uncertainties on reliability indices. The Euler Maruyama path discretization applied to evaluate the solution of the Stochastic Diffusion Process. The proposed Stochastic Diffusion Process-based MLMC method is integrated into a systematic failure identification technique to evaluate the distribution system reliability. The proposed method is validated with analytical and Sequential MCS methods for IEEE Roy Billinton Test Systems. Finally, the numerical results show the accuracy and fast convergence rates to handle uncertainties compared to Sequential MCS method.

Reliability analysis of an active distribution network integrated with solar, wind and tidal energy sources

The global trends toward increasing clean and sustainable power generation have brought significant changes and developments in electrical distribution networks. The existing passive networks are being restructured to facilitate renewable distributed generations to ensure high degree of reliability of power supply to customers. A distribution system reliability assessment (DSRA) is crucial to analyze the risk and cost associated with power interruptions and take necessary preventive and corrective actions. This paper presents an approach to DSRA and carries out a comprehensive reliability assessment of an active distribution network (ADN) connected with solar, wind, and tidal energy sources. A multi-state reliability model is developed, combining the Markov and well-being frameworks to determine the reliability of a network energized by multiple renewable energy sources (RESs). The load point reliability and worth-oriented indices, namely SAIDI, SAIFI, CAIDI, AENS, EENS, ECOST and IEAR, are evaluated to analyze the impacts of the three RESs on the reliability of the ADN. The paper also proposes two new metrics to estimate the benefits of adding RESs from the reliability worth and cost perspectives. The analyses have been carried out on the Roy Billinton Test System. The results show that the maximum reliability worth and cost benefits can be extracted from a combined operation of multiple RESs. A combination of solar-wind-tidal energy sources, therefore, can be an effective solution for countries having long coastlines to fulfill not only the sustainable energy goals but also to improve the grid's reliability and reduce the monetary losses incurred due to customer interruptions.

Reliability Evaluation in Distribution Networks with Microgrids: Review and Classification of the Literature

Modern power systems must provide efficient, reliable, and environmentally responsible energy. Recently, the inclusion of Microgrids (MGs) has allowed us to overcome some difficulties and face important challenges in this direction, especially related to the use of alternative energy sources. Increased and probabilistic demand, as well as limited energy supply, pose the need to evaluate the reliability of any distribution system (DS) when MGs are introduced. Here we reviewed and classified the state-of-the-art of reliability assessment (RA) in MGs. Initially, we contextualize RA in distribution systems. Next, each of the MGs subsystems components are introduced and the questions (1) why is it important to evaluate the reliability in Microgrids? (2) how do Microgrids influence the reliability of distribution systems? and (3) how does each of its subsystems influence the reliability of the Microgrids? are addressed. A total of 1395 research studies were published between 2002 and 2020. Using the PRISMA model, 147 met the inclusion criteria (71% correspond to research papers and 29% to reviews; 62% were published in journals, 34% were conference papers and 4% were books). The first study dates from 1971. Despite immense advances in MGs, we identified that (1) real test systems constitute an emerging trend; (2) although new MG configurations sound promising, the development and application of new RA techniques are a necessary step towards the identification of potential pitfalls of such architectures; (3) new RA methods or variations of the existing ones, whether analytical or simulation-based, are constantly being proposed, but their comparison for a particular DS, including MGs, are yet to be performed; and (4) more research studies are needed to assess how new control strategies and information and communications technology impact MGs reliability. Future lines of research could build upon these gaps to enhance reliability, especially when alternative energy resources are available.

Assessment of Distribution System Reliability and Possible Mitigation by Using Reclosers and Disconnectors: The Case of Cotobie Distribution Station

Assessment of Distribution System Reliability and Possible Mitigation by Using Reclosers and Disconnectors: The Case of Cotobie Distribution Station

ELECTRICAL LOAD RELIABILITY ASSESSMENT USING ANALYTICAL METHOD, CASE STUDY: FUPRE 1 X 2.5MVA INJECTION SUBSTATION

This research work presents the reliability assessment of electrical load distribution system in Federal University of Petroleum Resources, Effurun (FUPRE), Warri using the Analytical method and ETAP software as the simulation tool to run the reliability assessment of the System. The analytical analysis was conceded out by using August 2018 – August 2019 historical data of Tetfund Classrooms Blocks, Hostels, College of Technology, Administration Block, Health Center, and College of Science Feeder obtained from the Benin Electricity Distribution Company [BEDC]. The results conceded revealed that College of Technology Injection Substation is the most reliable in the distribution network when compared to the other five substations around the institution premises as it recorded system indices of ASAI: 99.30, SAIFI: 1.10, SAIDI: 55.35, CAIDI: 123.04 in August 2018 to August 2019. Nevertheless, the total reliability indices of the six substations under investigation as obtained from the analysis, and it shows that availability of power to FUPRE distribution is very poor as compared with the benchmark of IEEE ASAI of 99.99 for distribution substation availability.