Reliability Of Distribution Network Research Articles

Characteristics of Partial Discharge on 10 kV Covered Conductor Around Tower Head

The widely use of covered conductor increases the reliability of distribution network. However, a new problem of partial discharge caused by covered conductor at the position of tower head is generated at the same time. This kind of partial discharge will damage the insulation layer or accelerate the deterioration of insulation, which may cause the single-phase grounding fault and affect the power supply reliability. At present, there is few systematic studies on the characteristics of this partial discharge. This paper mainly analyzes the electric field distribution near the covered conductor around tower head, builds the partial discharge experiment platform, and obtains the pulse current characteristics of partial discharge under different working conditions. The results show that the maximum electric field intensity is located at the interface between covered conductor, binding wire and air. The main causes of partial discharge are the wet and dirty of the surface of porcelain insulator and conductor insulation. The minor cause is the breakage of covered conductor insulation. Under different conditions, the initial partial discharge pulse current wave front time is 8ns ~ 45ns, the tail time is 30ns ~ 150ns. The discharge time interval can be as low as 30μs. In addition, it is found that there are two types of partial discharge through spectral analysis. One occurs when the covered conductor insulation is damaged under binding wire; the other is the covered conductor insulation is intact.

Editorial to the 'Special Issue—Distribution network reliability in Smart Grids and Microgrids' of AIMS Energy

Editorial to the 'Special Issue—Distribution network reliability in Smart Grids and Microgrids' of AIMS Energy

STUDY OF HTA DISTRIBUTION NETWORK RELIABILITYIN NIAMEYCITY

With the growth of demand for electrical energy, electrical networks are nowadays subjected to very high loads, sometimes beyond their capacity. This leads to their malfunction and their inability to meet expectations. But given the importance of electricity in our lives, this disruption cannot be tolerated for long, which leads distribution operators to implement maintenance programs to ensure continuity of service. However, these measures, although extremely important, are time consuming, costly and sometimes do not provide complete satisfaction, resulting in the absence of electricity to consumers. The study of reliability of medium voltage distribution network in Niamey allowed us to analyze the performance indices of latter. Indeed, we based ourselves on the number of incidents (opening of HV outlets) and their duration while taking into account the origin of the associated disturbances. In the light of this analysis, the reliability of lines is close to 95% only for a period of one (1) hour (h) and is almost zero beyond 100 hours of operation. As for maintainability, it is only guaranteed within a period of 10 hours after the occurrence of incident on network.

Monitoring and Evaluation of The Reliability of Distribution Network with Distributed Generation

With the growing population of Ezenei 11KV feeder radiating from the Asaba mains Injection Substation and overstretched distribution network, monitoring and evaluation of the reliability and improvement of distribution network feeder is essential. Failure of some of the equipment at supply restoration is frequent due to weakness of some of the line conductors and long usage of the equipment. In this research work, simulation, analysis and evaluation of the reliability and improvement of Ezenei 11kV feeder was investigated. Load data used were collected from Benin Electricity Distribution Company (BEDC) Asaba between February and April 2018 and this was used to model the sixty – seven (67) buses on the network using Electrical Transient and Analysis Program (ETAP). Load flow analysis was carried out on the modelled network using Newton – Raphson (N-R) iteration method to determine the various bus power (active and reactive) and voltage magnitude using the base and distributed generation injected power. Reliability study was carried out on the network and result showed that the load point indices were increasing as distance of load point increased from feeder. The Seventeen load buses which was Okeke bus to Starcom bus forms the location A. and St. Rebecca bus to Chief Ofili bus forms location B. while Odogu bus to Old Deputy Govt. bus forms location, Iyabi bus to MTN III bus forms location D. Okeke and Jimok water which are the closest load buses to the feeder have an Average Interruption Rate (f/yr) and Annual Output Interruption Rate (hr/yr) of 8.9264f/yr, 417.1507hr/yr while Victor Odogu and Auditor General has an Average Interruption Rate (f/yr) and Annual Output Interruption Rate (hr/yr) of 8.9318f/yr, 417.2857hr/yr and 8.9264 f/yr, 417.1507hr/yr. It was also observed that Chief Osita, Anacho and Estate buses had the highest Average Interruption Rate (f/yr) and Annual Output Interruption Rate (hr/yr).

An Overview on Reliability Analysis and Evaluation Methods Applied to Smart Grids

The reliability can be defined as to carry out predefined requirements in a predefined duration. The importance of reliability analysis increases day by day as the customers become more conscious about a product or service which they buy. The application area of reliability analysis is very wide. Any product\ system or service including smart grids can be subject of the reliability analysis. As power system technology and computer science improving, the concept of smart grids begins to take part in our lives. Therefore, it is very essential to make reliability analysis for smart grids. In this paper, reliability analysis methods applied to smart grids are focused on and the classifications in reliability analysis have been explained. Besides, distribution networks reliability concept and different methods such as simulation and analytical approaches to assess the reliability have been introduced. The applications of these methods on smart grids are well explained. In addition to these, smart grids and conventional grid is compared. Different approaches such as tree analysis, failure mode effect analysis, Markov process and Monte Carlo simulation methods are carried out with wind turbines.

Optimal planning of distributed generation and battery energy storage systems simultaneously in distribution networks for loss reduction and reliability improvement

The use of electrical energy storage system resources to improve the reliability and power storage in distribution networks is one of the solutions that has received much attention from researchers today. In this paper, Distributed Generators (DGs) and Battery Energy Storage Systems (BESSs) are used simultaneously to improve the reliability of distribution networks. To solve the optimization problem, Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D) is used to reduce the Energy Not Supplied (ENS) in the 30 and 69-bus distribution networks. The objective functions used in the proposed algorithm include minimization of ENS, reduction of load losses, reduction of load cost and reduction of voltage drop in the network. To evaluate the efficiency of the proposed model, different scenarios for increasing the capacity of the distribution system by DGs and battery energy storage systems are considered and each of the results is examined simultaneously and separately. Analyzes in the simulation results show that the amount of ENS and power losses in the 30-bus network are reduced by 90% and 85.20%, respectively, and in the 69-bus network are reduced by 85% and 80%, respectively. The proposed model shows that it has good stability compared to other algorithms in distribution networks. On the other hand, with the presence of BESS along with DG, the lack of reactive power in the network can be compensated to increase reliability and reduce the purchase cost in the network.

Real-time operation of distribution network: A deep reinforcement learning-based reconfiguration approach

With the growing penetration of renewable energy sources and remotely controllable switches, reconfiguration processes have increasingly played a critical role in the real-time operation of distribution networks. A dynamic network reconfiguration strategy is developed in this study with the objective of minimizing both the operation cost and the amount of load shedding. A three-stage deep reinforcement learning-based optimization method is proposed to determine the optimal reconfiguration and set-points of distributed generators in real-time operation. In stage 1, day-ahead scheduling is carried out for unit commitment and economic dispatch. In stage 2, the optimal configuration is determined to consider different events in the distribution system. These events are usually the disconnection of various branches or buses in the system to isolate the faults in different locations. In stage 3, the real-time set-points of distributed generators are determined considering uncertainties. Using deep neural networks as function approximators, the proposed method is able to find out the optimal configuration and real-time set-points immediately. The fast response of the proposed method enhances the stability and service reliability of distribution networks. The performance of various reinforcement learning algorithms is also analyzed to determine the best method for the proposed strategy. A microgrid and IEEE 33-bus networks are used to validate the performance of the proposed method.

Time-Dependent Reliability Analysis of Buried Water Distribution Network: Combined Finite-Element and Probabilistic Approach

Corrosion deterioration is the predominant factor for a large number of cast iron (CI) water main breaks. The reliability of CI pipelines decreases overtime as corrosion growth on pipe walls significantly reduces the strength of pipeline materials. To predict the reliability of water pipelines accurately, this study used a finite-element analysis (FEA) approach to determine the maximum pipeline stress at various stages of the pipeline’s life. A series of FEAs was performed to consider uncertainties in parameters associated with stress analysis. The circumferential stress was found to be the most critical stress for pipelines. Time-variant circumferential stress was obtained by accounting for the time-dependent corrosion pit growth on the pipeline wall. The time-variant failure probability of pipelines was determined by comparing the circumferential stress and the tensile failure strength of the pipeline at the burst limit state. The FEA model developed in this study was validated with the results obtained from previous studies. Monte Carlo simulation was performed to generate the fragility curves in a probabilistic manner. This study also compared the fragility curves obtained utilizing FEA and conventional equations (elastic ring theory and the Spangler formula). The results showed that analytical equations are too conservative and provide a higher failure probability of pipeline. A sensitivity analysis was performed to identify the relative importance of parameters contributing to the pipeline’s performance. Additionally, the reliability of the water distribution network (WDN) was calculated based on the minimum cut set (MCS) and graph decomposition methods. The results showed that the two methods provide similar outcomes, however, MCS provides a greater safety margin. The proposed approach was illustrated for an example WDN.

Research on reliability evaluation of complex distribution network considering N-1 verification

With the rapid development of power system, the distribution network structure is gradually mature and the connection situation is more complex. The traditional distribution network reliability calculation method can not accurately calculate the reliability index of complex distribution network. Based on the traditional simple power supply reliability evaluation method of radial distribution network, this paper completely considers the influence of circuit breaker, tie switch, branch line, standby transformer and other equipment, and puts forward an improved network equivalence method model. The model first treats the complex distribution system in layers, and then gradually equates it into a simple radial distribution network to calculate the reliability of the system. At the same time, this paper analyzes the distribution network with multi connection structure in a provincial capital city. The results show that this model simplifies the complexity of distribution system reliability calculation, improves the accuracy and speed of reliability calculation, and more truly reflects the reliability of actual distribution system.

Residential Demand Response Coordination for Distribution Network Reliability Enhancement

This paper establishes a centralized model to activate residential demand response in order to improve distribution network reliability. The model aims at minimizing the damage cost imposed by load curtailments following occurrence of unexpected events. In this model, distribution system operator (DSO) and responsive customers have already signed a contract authorizing the DSO alters the operation of responsive appliances whenever system reliability is jeopardized. The model addresses consumers’ preferences and guarantees that the operation of appliances is displaced within the bounds defined by the owners. Once an unexpected event occurs, the DSO commits responsive appliances to avoid likely violations in the network operational limits and costly load curtailments. The proposed model is mathematically formulated in the form of mixed integer linear programming (MILP) and its capability is depicted via applying to a real-world distribution network with some residential consumers. The comparison of service reliability indices after and before utilizing demand response potentials illustrates the effectiveness of the model.

Performance of Gradient-Based Optimizer on Charging Station Placement Problem

The electrification of transportation is necessary due to the expanded fuel cost and change in climate. The management of charging stations and their easy accessibility are the main concerns for receipting and accepting Electric Vehicles (EVs). The distribution network reliability, voltage stability and power loss are the main factors in designing the optimum placement and management strategy of a charging station. The planning of a charging stations is a complicated problem involving roads and power grids. The Gradient-based optimizer (GBO) used for solving the charger placement problem is tested in this work. A good balance between exploitation and exploration is achieved by the GBO. Furthermore, the likelihood of becoming stuck in premature convergence and local optima is rare in a GBO. Simulation results establish the efficacy and robustness of the GBO in solving the charger placement problem as compared to other metaheuristics such as a genetic algorithm, differential evaluation and practical swarm optimizer.

Distribution Network Reliability and Efficiency Enhancement Using Distributed Generation

The Nigerian power sector is faced with many challenges such as: generation deficit, inefficiency and power loss over lengthy transmission and distribution lines, contribution to greenhouse gas emission, weak and dilapidated transmission and distribution infrastructure, dependence on fossil fuels, insufficient power. Efforts should be put in place by relevant authorities to improve the power sector. With the distribution network being the closest to the final consumer, efforts should be made to make it more efficient. This study therefore aims at improving the performance of poor distribution network using Distributed Generation (DG), optimally placed and sized in the network. The Asaba, 2 X 15MVA, 33/11kV injection substation in Asaba, Delta state of Nigeria consisting of Anwai road feeder and SPC feeder radiating outwardly from this injection substation was the focus of this study. Relevant data collected from Benin Electricity Distribution Company (BEDC) was used to carry out load flow study. The simulation and analysis of the result and injection of photovoltaic (PV) DG of Asaba injection substation distribution network using Newton-Raphson iteration technique in ETAP 12.6environment to ascertain the overall performance of the network under base loading condition was modelled from a drawn detailed single line diagram of the network. DGs were optimally placed in specific buses in the network using loss sensitivity analysis. The result revealed that prior to DG placement in the network, only 10.4% of the buses were within statutory voltage limit (394.25V – 435.75V or 0.95p.u – 1.05p.u) and 89.6% of the load buses in the network violated the statutory voltage limit and high losses (active and reactive) of 1329.08kW and 2031kVar. After the optimal placement of DG, the active and reactive power losses on the network reduced by 57.5% and 70.7%. While the voltage profile improved by 94.8%, thereby increasing the capacity, reliability and efficiency of distribution network.

A Protection Method for DC Distribution Network with Single Pole Grounding Based on Integrative Two-terminal MMC

Based on the analysis model of unipolar grounding fault occurred in two-terminal MMC DC distribution network, the characteristics of unipolar grounding fault are studied. The similarity characteristics of transient currents between the fault line and the non-fault line are analyzed when the fault is located in the feeder, tie line and bus respectively. According to the characteristics of single-pole grounding fault and the similarity principle, a new single-pole grounding protection method for DC distribution network based on two-terminal MMC is proposed. The simulation results show that the proposed single-pole grounding protection method can accurately determine the single-pole grounding fault at any position of the DC distribution network. The research results can effectively solve the problem of single-pole grounding protection in DC distribution network, and effectively improve the security and reliability of DC distribution network.

Effects of Orifice Diameter and Retention Time of Local Tanks on the Reliability and Carbon Footprint of Water Distribution Networks

The role of private tanks is to provide excess storage to the consumer to satisfy the water demand. However, they are disregarded during the design stage, in favor of simplified network analysis. This affects the accuracy of the simulation because vital components, such as tank inlets and volume sizes, are completely ignored. Hence, the purpose of this study is to demonstrate the effectiveness of advanced modeling of water distribution networks (WDNs), encompassing the presence of local private tanks, to determine the optimum values of different parameters of private tanks by conducting time- and volume-based reliability analyses. Two network models are used to perform the analysis: a small sample network and a real network that resembles the area of Dubai Silicon Oasis, Dubai, United Arab Emirates. The results obtained from the simulation of networks indicated that the lowest orifice and volume sizes to achieve the required reliability of unity is the optimum values. Furthermore, it implied that any change in their optimum values would either result in tank failure or increase in the head loss and carbon footprint of the network.

Quantitative evaluation of power supply reliability improvement in distribution network by customer-side integrated energy system

In order to solve the problem of quantifying the construction benefit of distribution system with integrated energy system, a quantitative evaluation method is proposed, taking into account the impact of demand response. Firstly, the power supply model is established to determine power supply region of integrated energy system after distribution network failure. Then, the demand response model integrating time-of-use price and incentive is used to show the load changes before and after the implementation of demand response. Furthermore, the improvement effect analysis method of distribution network reliability by integrated energy system are proposed based on the sequential Monte Carlo method. In addition, the influence of various factors on the reliability is also studied. At last, take the improved RBTS 6 bus F4 as an example. Case study results show that the integrated energy system and demand response can improve the reliability of the distribution network.

Research on Distribution Network Reliability and Power Supply Soft Self-healing

The reliability of distribution network is an important index to ensure high-quality power supply. In this paper, the FMEA table is established based on the traditional power supply mode consequence analysis method, and the network topology after power supply isolation is determined by querying the table according to the power supply information. Then, the control mode of VSC is adjusted according to the VSC control strategy under different power supply conditions. Finally, through network reconfiguration and island operation, the continuous spatiotemporal power grid topology power supply restoration optimization model is established. On this basis, this paper combines sequential Monte Carlo method to evaluate the reliability of continuous spatiotemporal power grid topology, and illustrates the reliability evaluation difference caused by the difference of distribution network topology information.

Quantifying the contribution of EV battery swapping stations to the economic and reliability performance of future distribution system

This paper proposes a comprehensive framework to investigate the potential role of grid-connected battery swapping station (BSS) with vehicle-to-grid (V2G) in improving the economy and reliability of the distribution system. For this aim, we first develop an empirical operating model considering operating characteristics of the distribution system with the BSS explicitly. Then, on this basis, a rolling optimization scheduling model of the distribution network is established. In particular, a refined BSS model including a new calculation method of available generation capacity (AGC) is included. Finally, a quantitative method to quantify the effect of BSS on reliability and economy of distribution networks is proposed. Compared with existing works, the main contribution of this paper is threefold. (i) A battery-level BSS operational model including AGC calculation is proposed to fully explore the V2G potential of the BSS. (ii) A rolling optimization scheduling model is established, which fully exploits the potential interaction between economy and reliability of system operation. (iii) An assessment framework is proposed to analyze the special value of BSS resources from aspects of both economy improvement and reliability enhancement, which can provide more practical instruction for BSS planning. Numerical studies are conducted based on IEEE 33-bus distribution network to verify the accuracy and efficiency of our approach. The simulation results show that if V2G of the BSS is orderly exploited and managed, the net profit of the distribution system will increase by 11.97%, and system expected energy not supplied (SEENS) will decrease by 14.34%. The reliability and economy are two contradictory factors, the dispatch model we proposed can achieve better economy with the same reliability level. The location of the BSS also has important effect of the economy and reliability of distribution system.© 2017 Elsevier Inc. All rights reserved.

Distribution network reliability enhancement and power loss reduction by optimal network reconfiguration

Voltage instability, power imbalance, and unreliability are all caused by power interruptions and losses in the distribution system. The optimal reconfiguration of the distribution network is offered in this research as a solution to such challenges. The investigation is carried out using an actual distribution system in Kombolcha, Ethiopia. Modified shark smell optimization (MSSO) is used in the MATLAB environment to improve system reliability and voltage profile with low power loss. Tie switches are optimally placed to reduce power losses, total cost of outages, and reliability indices such as the system average interruption frequency index (SAIFI), system average interruption duration index (SAIDI), and expected energy not supply (EENS) all at the same time. The MSSO's effectiveness is demonstrated through a comparison with other approaches. Furthermore, a real-time digital simulator is used to implement the suggested task in real time with allowable mistakes in the results (RTDS).

Causal Algebras on Chain Event Graphs with Informed Missingness for System Failure.

Graph-based causal inference has recently been successfully applied to explore system reliability and to predict failures in order to improve systems. One popular causal analysis following Pearl and Spirtes et al. to study causal relationships embedded in a system is to use a Bayesian network (BN). However, certain causal constructions that are particularly pertinent to the study of reliability are difficult to express fully through a BN. Our recent work demonstrated the flexibility of using a Chain Event Graph (CEG) instead to capture causal reasoning embedded within engineers’ reports. We demonstrated that an event tree rather than a BN could provide an alternative framework that could capture most of the causal concepts needed within this domain. In particular, a causal calculus for a specific type of intervention, called a remedial intervention, was devised on this tree-like graph. In this paper, we extend the use of this framework to show that not only remedial maintenance interventions but also interventions associated with routine maintenance can be well-defined using this alternative class of graphical model. We also show that the complexity in making inference about the potential relationships between causes and failures in a missing data situation in the domain of system reliability can be elegantly addressed using this new methodology. Causal modelling using a CEG is illustrated through examples drawn from the study of reliability of an energy distribution network.

Power marketing and distribution network remote visual control system based on big data architecture

As the main power transmission system connecting power supply equipment and power customers, whether the distribution network is safe and reliable in production and operation directly determines whether the work capacity of power supply equipment and power consumption equipment can be improved. The application of big data centralized control system can help us timely and accurately grasp the reasons for the decline of security and reliability of distribution network, and provide safe and stable power energy for power customers while improving the operation efficiency of power supply system. On the basis of previous research results, the author systematically analyzes the role of big data centralized control system in distribution network production and operation management, and puts forward some suggestions on applying big data centralized control system to distribution network production and operation management according to his many years of work experience. The comparative experiment proves that the fault location accuracy of the system designed in this paper is higher than 90%, which effectively increases the fault detection accuracy.