M. Hajibeigy; V. Talavat; S. Galvani
Abstract
Due to ever-increasing energy requirements, modern distribution systems are integrated with renewable energy sources (RESs), such as wind turbines and photovoltaics. They also bring economic, environmental, and technical advantages. However, they face the network operator with decision-making challenges ...
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Due to ever-increasing energy requirements, modern distribution systems are integrated with renewable energy sources (RESs), such as wind turbines and photovoltaics. They also bring economic, environmental, and technical advantages. However, they face the network operator with decision-making challenges due to their uncertain nature. Modern distribution systems usually operate at safety margins, and any contingency may lead to power supply losses. In this regard, any attempts to increase the planner/operator's awareness of the network situation will help improve the decision quality. This paper determines the optimal locations of the RESs to enhance the expected power not served as a reliability index. Besides, it reduces power losses and minimizes the 95\% confidence interval of power losses, as much as possible for having more awareness of network states. The K-medoids data clustering method is applied to handle the uncertainties of the RESs and demand loads. The MOPSO, NSGA II, and MOGWO algorithms are used to solve the proposed problem. The efficiency of the proposed approach is tested on the IEEE standard 33-bus and 118-bus distribution networks. The obtained results show that it is possible to reach a better confidence interval while keeping the losses and reliability index at a desired level. Considering solutions with identical losses and reliability index, the confidence interval of power losses using the MOPSO algorithm is 6.86% and 39.82% better rather than the NSGA II and MOGWO algorithms in the 33-bus distribution network and it is 30.23% and 129.63% better in the 118-bus distribution network.
A. Bagheri; A. Rabiee; S. Galavani; H. Yassami; A. Moeini
Abstract
Transmission lines switching and tap adjustment of power transformers are short-term alternatives to enhance the flexibility of power system operation. By a proper implementation of these alternatives, the operational problems such as lines congestion, bus voltage violations and excessive power losses ...
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Transmission lines switching and tap adjustment of power transformers are short-term alternatives to enhance the flexibility of power system operation. By a proper implementation of these alternatives, the operational problems such as lines congestion, bus voltage violations and excessive power losses can be alleviated. Traditionally, these two alternatives are applied separately due to the complexity of their simultaneous implementation as well as their coordination. In this paper, a DIgSILENT-based improved particle swarm optimization (IPSO) algorithm is proposed to implement the transmission switching and coordinated voltage control of power transformers, concurrently. The IPSO is implemented in DPL environment of Powerfactory-DIgSILENT, as a powerful software package commonly used by the electrical utilities. The proposed approach is applied to IEEE-14 bus system and the real transmission network of Zanjan Regional Electric Company (ZREC) located in Iran, in different scenarios considering all the existing practical constraints. The obtained results verify the effectiveness of the presented approach.
Planing & Reliability
A. Bagheri; A Rabiee; S. Galavani; F. Fallahi
Abstract
Flexible AC Transmission Systems (FACTS) devices have shown satisfactory performance in alleviating the problems of electrical transmission systems. Optimal FACTS allocation problem, which includes finding optimal type and location of these devices, have been widely studied by researchers for improving ...
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Flexible AC Transmission Systems (FACTS) devices have shown satisfactory performance in alleviating the problems of electrical transmission systems. Optimal FACTS allocation problem, which includes finding optimal type and location of these devices, have been widely studied by researchers for improving variety of power system technical parameters. In this paper, a DIgSILENT-based Discrete Particle Swarm Optimization (DPSO) algorithm is employed to manage the power flow, alleviate the congestion, and improve the voltage profile in a real case study. The DPSO have been programmed in DPL environment of DIgSILENT software and applied to the power grid of Gilan Regional Electric Company (GilREC), located in north of Iran. The conducted approach is a user-friendly decision making tool for the engineers of power networks as it is executed in DIgSILENT software which is widely used in electric companies for the power system studies. The simulation results demonstrate the effectiveness of the presented method in improving technical parameters of the test system through several case studies.
