Improve Distribution System Reliability Research Articles

Efficient allocation of energy storage and renewable energy system for performance and reliability improvement of distribution system

This paper aims to investigate the impact of optimal planning of renewable energy systems and independent battery energy storage systems (BESS) on the performance and reliability of distribution systems (DS). A unique energy management scheme (EMS) controls the charging and discharging schedules of the BESS. The transit search optimization (TSO) algorithm determines the optimal allocation of wind turbine (WT) and solar photovoltaic (SPV) generator units, along with BESS units. The optimization focuses on improving the DS reliability in terms of energy supply, increasing the feeder security margin, and reducing apparent power loss. Multiple case studies are designed to study the efficacy of the problem outcomes and are validated using Bus 4 of the Roy Bollington Test System (RBTS). To obtain results that are close to actual operating conditions, the modelling process takes into account the time-varying load profile and the dynamic power outputs from the SPV and WT units. The findings show that the suggested method works well by enhancing the feeder security margin by a maximum of 11.25%, reducing expected energy not supplied (EENS) by 4.3%, and improving the power loss profile by 11.5%. In addition, the feeder upgrade deferral (FUD) years also show a maximum improvement of 20.8%.

Optimal placement of uPMUs to improve the reliability of distribution systems through genetic algorithm and variable neighborhood search

Due to the dynamic nature of modern distribution systems, the deployment of micro-phasor measurement units (uPMU) is becoming increasingly common among utilities to improve system monitoring and reliability. However, given their high investment costs, deploying a large number of these devices becomes unfeasible. Hence, unlike other approaches found in the literature that focus on observability criteria, this work presents an algorithm for optimal placement of uPMUs aimed at improving distribution system reliability. The algorithm defines the optimal number and location of the uPMUs through an objective function based on the resolution of a fault location technique that works in conjunction with pseudo-measurements to successfully locate a contingency. The meta-heuristics Genetic Algorithm and Reduced Variable Neighborhood Search are employed to address this problem. The proposed method has been validated on a three-phase 39-bus distribution system and a real distribution feeder with 962 buses from an Ecuadorian electric distribution utility. The results obtained confirm the effectiveness of the method, as with the deployment of only two uPMUs, the energy not supplied decreases by 13.84 % and 24.96 % for the 39-bus and 962-bus systems, respectively. Moreover, in the 962-bus system, the System Average Interruption Duration Index (SAIDI) is reduced by 20.36 %.

Optimizing Distributed Generation Placement and Sizing in Distribution Systems: A Multi-Objective Analysis of Power Losses, Reliability, and Operational Constraints

The integration of distributed generation (DG) into distribution networks introduces uncertainties that can substantially affect network reliability. It is crucial to implement appropriate measures to maintain reliability parameters within acceptable limits and ensure a stable power supply for consumers. This paper aims to optimize the location, size, and number of DG units to minimize active power losses and improve distribution System (DS) reliability while considering system operational constraints. To achieve this objective, multiple tests are conducted, and the particle swarm optimization (PSO) technique is implemented. The simulation studies are performed using the ETAP software 19.0.1 version, while the PSO algorithm is implemented in MATLAB R2018a. ETAP enables a comprehensive evaluation of the DG system’s performance, providing valuable insights into its effectiveness in reducing power losses and enhancing system reliability. The PSO algorithm in MATLAB ensures accurate optimization, facilitating the identification of the optimal DG unit location and size. This study uses a modified IEEE-13 bus unbalanced radial DS as the test system, assessing the effects of photovoltaic (PV) and wind DG units under various scenarios and penetration levels. The results demonstrate that the optimal DG unit location and size of either a single PV or wind DG unit significantly reduce power losses, improve DS reliability, and enable effective load sharing with the substation. Moreover, this study analyzes the impact of DG unit uncertainty on system performance. The findings underscore the potential of optimized DG integration to enhance DS efficiency and reliability in the presence of renewable energy sources.

An MILP Model for Switch, DG, and Tie Line Placement to Improve Distribution Grid Reliability

Remote controlled switches (RCSs) have the ability to isolate the faulted area from other parts of the distribution system. On the other hand, the dispatchable distributed generators (DDGs) and tie lines can supply the interrupted loads after fault occurrence trough microgrids and reduce the outage time. In this regard, this article proposes a planning model for simultaneous placement of RCSs, DDGs, and tie lines to improve distribution system reliability. The presence of renewable distributed generations (RDGs) and energy storage systems, which have an increasing penetration in today's distribution networks are also considered. Moreover, two different practical load shedding methods are considered to balance the total generation and consumption in microgrids. The predetermined expansion plan of RDGs is also considered. To simplify the implementation of the proposed optimization model and ensure the global optimal solution, the planning model is formulated as a mixed integer linear programming model which can be solved by various commercial solvers. Finally, the effectiveness of the proposed model is illustrated by implementation on bus 4 of Roy Billinton test system through various case studies and sensitivity analyses. The results demonstrate the significant impact of the proposed planning model on improving the distribution system reliability.

Reliability Assessment Based on Optimal DGs Planning in the Distribution Systems

Due to increased load demands, distribution systems suffer from high power losses, low voltage levels, high current, and low reliability. To solve these problems, integrate distributed generator units (DG) into the distribution system. DG units are among the most popular methods of improving distribution system reliability, power losses, and bus voltage improvement through the placement and selection of distributed generator units in an optimal location and size. This work proposed Enhanced Particle Swarm Optimization (EPSO) technology to find the optimum location and size of DG units to reduce power losses, improve bus voltage level, and employed the Transient Electricity Analyzer (ETAP) to evaluate the reliability of the distribution system network. ETAP is a programming tool for modeling, analysis, design, optimization, operation, and control of electrical power systems. These findings may be useful in conducting reliability assessments and correctly utilizing dispersed generation sources for future power system growth by power utilities and power producer companies. The proposed method was employed on the Iraqi distribution system (AL-Abasia distribution network (F10 feeder)). After adding three DG units to the distribution system, theer adding three DG units to the distribution system, the obtained simulation results showed a significant reduction in power losses, voltage levels, and reliability enhancement.

A Nexus among Reliability Improvement of Distribution System with Optimal Placement and Capacity of Wind-Based Distributed Generation Management

Along with the world population growth, the need for a source of electrical energy is higher, so a reliable system with higher capacities is expected. Renewable energy becomes an alternative that supports the goal of reducing the risk of disruption, thus increasing the distribution system’s reliability. A lot of industries and public settlement uses renewable sources of energy as an alternative power supply to comply their energy needs. This research uses wind turbine as a source of renewable energy in the distributed generation (DG). However, the required investment in wind-based DG is commonly considered too costly to deploy and require a proper planning on its placement method. The flower pollination algorithm (FPA) method could be a solution to achieve optimal placement of wind-based DG, thus increase the distribution system’s reliability, which is indicated by minimum energy not supplied (ENS) index.

Reliability Enhancement of Electric Distribution Network Using Optimal Placement of Distributed Generation

As energy demand is increasing, power systems’ complexities are also increasing. With growing energy demand, new ways and techniques are formulated by researchers to increase the efficiency and reliability of power systems. A distribution system, which is one of the most important entities in a power system, contributes up to 90% of reliability problems. For a sustainable supply of power to customers, the distribution system reliability must be enhanced. Distributed generation (DG) is a new way to improve distribution system reliability by bringing generation nearer to the load centers. Artificial intelligence (AI) is an area in which much innovation and research is going on. Different scientific areas are utilizing AI techniques to enhance system performance and reliability. This work aims to apply DG as a distributed source in a distribution system to evaluate its impacts on reliability. The location of the DG is a design criteria problem that has a relevant effect on the reliability of the distribution system. As the distance of load centers from the feeder increases, outage durations also increase. The reliability was enhanced, as the SAIFI value was reduced by almost 40%, the SAIDI value by 25%, and the EENS value by 25% after injecting DG into the distribution network. The artificial neural network (ANN) technique was utilized to find the optimal location of the DG; the results were validated by installing DG at prescribed localities. The results showed that the injection of DG at proper locations enhances the reliability of a distribution system. The proposed approach was applied to thte Roy Billinton Test System (RBTS). The implementation of the ANN technique is a unique approach to the selection of a location for a DG unit, which confirms that applying this computational technique could decrease human errors that are associated with the hit and trial methods and could also decrease the computational complexities and computational time. This research can assist distribution companies in determining the reliability of an actual distribution system for planning and expansion purposes, as well as in injecting a DG at the most optimal location in order to enhance the distribution system reliability.

A hybrid method for recloser and sectionalizer placement in distribution networks considering protection coordination, fault type and equipment malfunction

An effective way to improve distribution system reliability is to place switches and protective equipment in the optimal location. Commonly, in the placement problem, the use of equipment in the designated location is assumed to be possible. But in practice, to establish protection coordination between the equipment, it is necessary to remove or relocate some of the equipment. This paper aims to increase distribution companies' profits and reduce customer interruption costs through a feasible solution. A new hybrid method for equipment placement has been proposed that simultaneously solves the protection coordination problem. While determining the optimal number and location of reclosers and sectionalizers, the proposed method ensures protection coordination between equipment (new and existing devices). Furthermore, to achieve a more realistic and accurate model, factors such as equipment malfunction, fault types (transient and permanent), and the relationship between these faults have been carefully considered to formulate the proposed method. In this method, to solve the optimization problems related to equipment placement and protection coordination, genetic algorithm, and linear programming in MATLAB software have been used, respectively. A real-life distribution network has been utilized to evaluate the proposed method, and the results show the capability and robustness of this method.

배전계통의 신뢰도 향상을 위한 전력회사 관점에서의 경제성 평가

Economic evaluation from the perspective of electric utility is performed about the reliability improvement of distribution system. The benefit from the perspective of the electric utility for improving the reliability of distribution system is the reduction of interruption cost, and the cost is assumed to be investment in distribution facilities. Therefore, the reduction in the cost of interruption for the case where SAIDI improves in a virtual distribution system is quantified. The total investment cost of automatic switch and Energy Storage System (ESS) invested to improve reliability of distribution system is calculated. The result of economic evaluation is presented as Benefit-Cost Ratio(B/C Ratio) by comparing the calculated benefit and cost. The sensitivity analysis on ESS capacity and unit price of interruption cost is conducted to reflect the uncertainty of future cost.

Reliability improvement of distribution system considering EV parking lots

Metropolitan cities have hundreds of parking lots (PLs), where each PL may have a capacity to hold hundreds of cars. Large-scale use of electric vehicles coupled with technological advancements in battery storage systems provide several technical and economic benefits of integrating PLs into the grid. This study presents the impacts of electric vehicle PLs on the distribution system reliability. The reliability indices of the distribution feeder are determined using recently proposed novel storage capacity model of a PL that accounts for the load and component outage data of the distribution feeder. The paper uses average interruption duration, average interruption frequency, and energy not served as feeder reliability indices. For load point reliability indices interruption frequency, interruption duration and energy not served are used. Numerical results, thus attained, show that for the backup operation mode of the PL; the feeder reliability indices and load point reliability indices improve up to 26% and 44% respectively.

Rekonfigurasi Jaringan Menggunakan Binary Particle Swarm Optimization (BPSO) Pada Penyulang Suryagraha

A radial distribution electrical network at a certain distance will have a large voltage loss due to conductive losses, especially at the endpoint. The tip voltage is determined by the distance of the distribution and the amount of load. The form of configuration also affects the amount of power loss and voltage loss. So that a good configuration is needed in order to obtain good efficiency. Reconfiguration of the distribution network is used to reset the network configuration form by opening and closing switches on the distribution network. Reconfiguration is expected to reduce power losses and improve distribution system reliability. Many feeders and buses on the network if calculated manually will be difficult and require a very long time. So it is necessary to solve problems using program assistance. In this case, use Particle Swarm Optimization (PSO). Particle Swarm Optimization (PSO) algorithm based on the behavior of a herd of insects, such as ants, termites, bees, or birds. BPSO is a development of the PSO algorithm designed to solve the optimization problem in a discrete combination, where the particle takes the value of binary vectors with length n and speed which is defined as the probability of bits to reach value 1. The results show a significant reduction in losses.

Integrating the PV-Diesel Hybrid System for Reliability Improvement in Distribution System

In Myanmar, as the main power generation is hydro power generation. the utility cannot supply sufficient power to customers during the dry season. Besides interruptions occur frequently due to aging system and lack of prospered protection. Therefore, reliability is an urgent issue in Myanmar. As a result of unbalance between generation and load, the distribution system is getting poor voltage profile, instability and high power losses in high load condition. According to network characteristics, the failure of a component always leads to consequence interruption in a radial distribution system. Therefore, it is a must consideration to mitigate these challenges to enhance the system reliability. There are many techniques to solve the reliability problems such as reclosers, switching devices (manual and automated switches), system reconfiguration, feeder re-conducting and integration of distributed generation (DG). In this paper, system reliability assessment is evaluated in detail with the integration of the distributed generation such as PV-Diesel Hybrid System. The location of DG is chosen according to the expected energy not supply (EENS) and the voltage drop in proposed system. Next, the optimal sizing of DG is chosen depends on the penetration level of generator. Reliability indices can be evaluated depending on the failure rate(λ), repair time(r) and annual outage time(U) in Electrical Transient and Analysis Program (ETAP) software. The case study of this thesis is carried out in 33/11 kV network which is connected Kyatminton Substation, Kyaukse, Middle Myanmar.

Rekonfigurasi Jaringan Radial Distribusi Tenaga Listrik Penyulang Suryagraha Menggunakan Binary Particle Swarm Optimization (BPSO)

A radial distribution electrical network at a certain distance will have a large voltage loss due to conductive losses, especially at the end point. The tip voltage is determined by the distance of the distribution and the amount of load. The form of configuration also affects the amount of power loss and voltage loss. So that a good configuration is needed in order to obtain good efficiency. Reconfiguration of the distribution network is used to reset the network configuration form by opening and closing switches on the distribution network. Reconfiguration is expected to reduce power losses and improve distribution system reliability. Many feeders and buses on the network if calculated manually will be difficult and require a very long time. So it is necessary to solve problems using program assistance. In this case, use Particle Swarm Optimization (PSO). Particle Swarm Optimization (PSO) algorithm based on the behavior of a herd of insects, such as ants, termites, bees or birds. BPSO is a development of the PSO algorithm designed to solve the optimization problem in a discrete combination, where the particle takes the value of binary vectors with length n and speed which is defined as the probability of xn bits to reach value 1. The results show a significant reduction in losses .

Study Effect of Components Availability on Distribution System Reliability Through Multilevel Monte Carlo Method

Reliability model of a power distribution system is influenced by its components reliability and availability. The paper investigates the effect of some basic protection components availability on the distribution system reliability improvement. For this purpose, we use a new approach called multilevel Monte Carlo to speed up the conventional Monte Carlo simulation based reliability assessment. The proposed method is implemented through solving stochastic differential equations of the system components random failure process using Milstein discretization scheme. To illustrate the proposed method, two commonly used reliability indices are evaluated for a test distribution network.

Modified Techniques for Distribution System Reliability Improvement by Parallel Operation of Transformers

Modified Techniques for Distribution System Reliability Improvement by Parallel Operation of Transformers

A Game Theory Approach to Distribution System Reliability Improvement Based on Customer Requests

A Game Theory Approach to Distribution System Reliability Improvement Based on Customer Requests

Rekonfigurasi Jaringan Radial Distribusi Tenaga Listrik Penyulang Suryagraha Menggunakan Binary Particle Swarm Optimization (BPSO)

A radial distribution electrical network at a certain distance will have a large voltage loss due to conductive losses, especially at the end point. The tip voltage is determined by the distance of the distribution and the amount of load. The form of configuration also affects the amount of power loss and voltage loss. So that a good configuration is needed in order to obtain good efficiency. Reconfiguration of the distribution network is used to reset the network configuration form by opening and closing switches on the distribution network. Reconfiguration is expected to reduce power losses and improve distribution system reliability. Many feeders and buses on the network if calculated manually will be difficult and require a very long time. So it is necessary to solve problems using program assistance. In this case, use Particle Swarm Optimization (PSO). Particle Swarm Optimization (PSO) algorithm based on the behavior of a herd of insects, such as ants, termites, bees or birds. BPSO is a development of the PSO algorithm designed to solve the optimization problem in a discrete combination, where the particle takes the value of binary vectors with length n and speed which is defined as the probability of xn bits to reach value 1. The results show a significant reduction in losses.

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.

Aplikasi Modified-Imperialist-Competitive-Algorithm (MICA) Untuk Merekonfigurasi Jaringan Radial Tenaga Listrik Pada Penyulang Mojoagung

The reconfiguration distribution network is used to reset the network configuration form by opening and closing switches on the distribution network. Reconfiguration is expected to reduce power losses and improve distribution system reliability. Many feeders and buses on the network if calculated manually will be difficult and require a very long time. So the solution of the problem must use artificial intelligence or Artificial Intelligent (AI). Imperialist Competitive Algorithm (ICA) widely used research in solving the optimization problem. Some studies comparing ICA with other artificial intelligence and ICA produce better results than other artificial intelligence. MICA is an ICA modification designed to solve a discrete combination of optimizations. MICA can find the best network reconfiguration so that it can reduce power loss by 35,7928% and fix voltage 0,0185 pu. This method can later use other artificial intelligence or can be applied to other repeater. So it can be used for recommendations to PT. PLN (Persero)

Evaluation of Smart Grid Technologies Employed for System Reliability Improvement: Pacific Northwest Smart Grid Demonstration Experience

The Pacific Northwest Smart Grid Demonstration (PNWSGD) was a smart grid technology performance evaluation project that included multiple U.S. states and cooperation from multiple electric utilities in the northwest region. One of the local objectives for the project was to achieve improved distribution system reliability. Toward this end, some PNWSGD utilities automated their distribution systems, including the application of fault detection, isolation, and restoration and advanced metering infrastructure. In light of this investment, a major challenge was to establish a correlation between the implementation of these smart grid technologies and the actual improvements of distribution system reliability. This paper proposes using Welch's t-test to objectively determine and quantify whether distribution system reliability is improving over time. The proposed methodology is generic, and it can be implemented by any utility after calculation of the standard reliability indices. The effectiveness of the proposed hypothesis testing approach is demonstrated through comprehensive practical results. It is believed that wider adoption of the proposed approach can help utilities to evaluate a realistic long-term performance of smart grid technologies.