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Automated Distribution Networks Reliability Optimization in the Presence of DG Units Considering Probability Customer Interruption: A Practical Case Study

Automation in power distribution systems and supervisory control and data acquisition (SCADA), which perform network switching automatically and remotely, allows distribution companies to flexibly control distribution power grids. Cross-section switches also has a significant role in the automation in distribution systems, in that the operational optimization of these switches is able to enhance the supply power quality and reliability indicators, and can be a prosperous solution to increase the reliability, efficiency and overall service quality in services to customers. In this regard, in this work, the genetic optimization algorithm (GOA) approach which integrated the Steepest Descend Technique (SDT) is proposed and enhanced based on the features of the mentioned issue to sketch the optimal location and control of automatic and manual cross-section switches and protection relay systems in distribution power systems. The GOA is able to search globally that can prevent the result from locally convergence, also, GOA gives superior primary solutions for the SDT. Thus, the SDT can search locally with higher performance which increase the solutions’ accuracy. Therefore, an optimization formulation is proposed to improve the value-based reliability of the suggested layout considering the cost of customer downtime and the costs related to segmentation of switches and relay protection devices. Also, a distributed generation (DG) system in distribution networks is considered based on the islanded state of generation units. The effectiveness of the optimal suggested procedure is evaluated and represented via performing a practical test system in the distribution network of Ahvaz city in Iran. The results show that using proposed method and by optimally allocating switches maneuver, energy losses without switches are reduced from 310.17 (MWh) to 254.2 (MWh), and also by using DG, losses are reduced from 554.01 to 533.61 which confirms the ability and higher accuracy of the proposed method to improve reliability indices.
- Aarhus University Denmark
- Islamic Azad University of Falavarjan Iran (Islamic Republic of)
- Islamic Azad University Sari Branch Iran (Islamic Republic of)
- Technological University of Tajikistan Tajikistan
- Tajik Technical University named after academic M.S.Osimi Tajikistan
reliability, distributed generation, customer interruption cost model, sectionalizing switch placement, Automated distribution networks, TK1-9971, genetic algorithm, Electrical engineering. Electronics. Nuclear engineering
reliability, distributed generation, customer interruption cost model, sectionalizing switch placement, Automated distribution networks, TK1-9971, genetic algorithm, Electrical engineering. Electronics. Nuclear engineering
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