Automated Fault Location In Smart Distribution Systems

Fault location in distribution systems is a critical component of outage management and service restoration, which directly impacts feeder reliability and quality of the electricity supply. Improving fault location methods supports the Department of Energy (DOE) “Grid 2030” initiatives for grid modernization by improving reliability indices of the network. Improving customer average interruption duration index (CAIDI) and system average interruption duration index (SAIDI) are direct advantages of utilizing a suitable fault location method. As distribution systems are gradually evolving into smart distribution systems, application of more accurate fault location methods based on gathered data from various Intelligent Electronic Devices (IEDs) installed along the feeders is quite feasible. How this may be done and what is the needed methodology to come to such solution is raised and then systematically answered. To reach this goal, the following tasks are carried out: 1) Existing fault location methods in distribution systems are surveyed and their strength and caveats are studied. 2) Characteristics of IEDs in distribution systems are studied and their impacts on fault location method selection and implementation are detailed. 3) A systematic approach for selecting optimal fault location method is proposed and implemented to pinpoint the most promising algorithms for a given set of application requirements. 4) An enhanced fault location method based on voltage sag data gathered from IEDs along the feeder is developed. The method solves the problem of multiple fault location estimations and produces more robust results. 5) An optimal IED placement approach for the enhanced fault location method is developed and practical considerations for its implementation are detailed

Automated Fault Location In Smart Distribution Systems

Fault location in distribution systems is a critical component of outage management and service restoration, which directly impacts feeder reliability and quality of the electricity supply. Improving fault location methods supports the Department of Energy (DOE) “Grid 2030” initiatives for grid modernization by improving reliability indices of the network. Improving customer average interruption duration index (CAIDI) and system average interruption duration index (SAIDI) are direct advantages of utilizing a suitable fault location method. As distribution systems are gradually evolving into smart distribution systems, application of more accurate fault location methods based on gathered data from various Intelligent Electronic Devices (IEDs) installed along the feeders is quite feasible. How this may be done and what is the needed methodology to come to such solution is raised and then systematically answered. To reach this goal, the following tasks are carried out: 1) Existing fault location methods in distribution systems are surveyed and their strength and caveats are studied. 2) Characteristics of IEDs in distribution systems are studied and their impacts on fault location method selection and implementation are detailed. 3) A systematic approach for selecting optimal fault location method is proposed and implemented to pinpoint the most promising algorithms for a given set of application requirements. 4) An enhanced fault location method based on voltage sag data gathered from IEDs along the feeder is developed. The method solves the problem of multiple fault location estimations and produces more robust results. 5) An optimal IED placement approach for the enhanced fault location method is developed and practical considerations for its implementation are detailed

Study and evaluate the effect of marketing mix on export performance (case study: Nestle Corporation in Qazvin Province)

As a success of enterprises within the national boundaries depend on effectiveness and correct marketing, when activity domain of an enterprise develops outside the boundaries, reach to success depends on correct understanding of the foreign market coordinates and adapting proper strategies to manage it. The main challenges of export marketing include choosing proper market and/or countries through marketing research and make decision about how to express marketing mix strategy. The decision more than anything is influenced by the philosophical foundation accepted to the firm about how the activity will be in the foreign market. Thus, the object of research is to study and evaluate the effect of marketing mix on export performance in Nestle Co. Research method was survey-descriptive approach. Statistical population of the research included managers and experts of Nestle Company. Sampling has been conducted in simple random sampling approach. It has been used descriptive statistics, inferential statistics, one-sample t-test, linear regression, and analysis of variance to analyze data. Results showed that marketing mix (product, place, price, promotion) has a positive and significant effect on export performance

Voltage Sag Data Utilization for Distribution Fault Location

Abstract-Fault location in distribution systems is an important function for outage management and service restoration directly impacting feeder reliability. In this paper, a fault location method based on matching calculated voltage sag data and data gathered at some nodes in the network is proposed. A method for characterization of voltage sags is utilized to reduce amount of transferred data. The proposed method can pinpoint fault location precisely, and is applicable to any complex distribution systems with load taps, laterals, and sub-laterals, single-phase loads, as well as networks with heterogeneous lines. The performance of the proposed method is demonstrated on the IEEE 123-node distribution test system via computer simulations in Alternate Transients Program software

Optimal Distribution Network Reconfiguration Using Dynamic Fuzzy Based Genetic Algorithm

Optimal reconfiguration of power distribution systems is a complex combinatorial optimization problem with the purpose of identifying a radial network that optimizes given objectives. In this paper, a dynamic fuzzy-based genetic algorithm is presented to find an optimal configuration for the distribution networks that minimizes the total power loss of the network. The efficiency of the proposed algorithm is demonstrated by its application on a 33-bus distribution system. The simulation results demonstrate the superior performance of the proposed method compared to the classic genetic algorithm based methods. © 2014 IEEE

Optimal distribution network reconfiguration using dynamic fuzzy based genetic algorithm

Optimal reconfiguration of power distribution systems is a complex combinatorial optimization problem with the purpose of identifying a radial network that optimizes given objectives. In this paper, a dynamic fuzzy-based genetic algorithm is presented to find an optimal configuration for the distribution networks that minimizes the total power loss of the network. The efficiency of the proposed algorithm is demonstrated by its application on a 33-bus distribution system. The simulation results demonstrate the superior performance of the proposed method compared to the classic genetic algorithm based methods. © 2014 IEEE

The Impacts Of Distributed Energy Sources On Distribution Network Reconfiguration

Thanks to the recent improvements in renewable energy technologies throughout the world, distributed energy sources are now playing an undeniable role in supplying the electricity in distribution networks. This paper studies the impacts of utilizing distributed generation units on the task of network reconfiguration in distribution systems. Considering the importance of reducing voltage drops and voltage sags in distribution systems, network reconfiguration is formulated as a multiobjective optimization problem in this study to minimize these two objective functions. A Pareto-based metaheuristic optimization algorithm is proposed to identify a Pareto frontier representing the alternative high-quality suboptimal configurations. The proposed optimization method is tested on a 69-bus distribution system to demonstrate the performance of the algorithm