Network Optimization
Javad Pourqasem; Soheil Fakheri
Abstract
Peer-to-peer (P2P) systems have grown significantly in recent years due to the ability to share multiple resources. Using the super-peer nodes in peer-to-peer networks has increased the efficiency of these networks. The main problem in these systems is the selection of high-capacity nodes as the ...
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Peer-to-peer (P2P) systems have grown significantly in recent years due to the ability to share multiple resources. Using the super-peer nodes in peer-to-peer networks has increased the efficiency of these networks. The main problem in these systems is the selection of high-capacity nodes as the super-peer node to join other nodes. The optimal choice is dependant on various parameters such as heterogeneous capacity and dynamic nature of the network. Given the predominant position of the super-peer nodes in the network, the selection of the top node requires a protocol that is aware of the capacity of the nodes. In this paper, we present a method for selecting a super-peer node based on the SG-2 model utilizing the broadcast-service and distance-delay-based Gossip protocol, and use the status messages between neighboring nodes, and search messages to select the most powerful node. Using this method, the efficiency of peer-to-peer networks will increase and the time of convergence to the optimal overlay network will be reduced.
Network Optimization
Mohammad Saberi; Behzad Taghipoor
Abstract
This paper presents a methodology for detecting and classifying the errors occurring on smart power transmission lines. In the proposed method, the voltage and current phases are estimated by the phasor measurement unit (PMU) installed in the generator bus, and then the equivalent voltage and current ...
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This paper presents a methodology for detecting and classifying the errors occurring on smart power transmission lines. In the proposed method, the voltage and current phases are estimated by the phasor measurement unit (PMU) installed in the generator bus, and then the equivalent voltage and current angles are obtained. These angles are analyzed by fast fourier transform (FFT) and used to detect of transmission line errors. Detection of the transmission line error is performed using the nerve- fuzzy inference system methodology, and the diagnostic error classification is performed using support vector machine (SVM). Validation of the proposed method for the IEEE 14 system is also tested in the MATLAB software environment.
Network Optimization
Javad Pourqasem
Abstract
While the Grid systems are distributing geographically, the heterogeneity and dynamic features of their resources are increasing. One of the important issues in this systems is adaptation the discovery services with more scalable and dynamic environments to improve the discovery performance. In this ...
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While the Grid systems are distributing geographically, the heterogeneity and dynamic features of their resources are increasing. One of the important issues in this systems is adaptation the discovery services with more scalable and dynamic environments to improve the discovery performance. In this paper, we concentrate on the Decentralized mechanisms based on the Peer-to-Peer (P2P) networks and classify the discovery approaches into two main categories: the Unstructured and Super-Peer models. We review the major development of these categories and provide discussion about the efficiency, scalability, and dynamic terms.
Network Optimization
Mohammad Saberi; Mehdi Hatef
Abstract
The purpose of Transmission expansion planning (TEP) is to find the required network lines with the lowest investment cost So that the future burden will be provided economically by observing the system security indicators. Due to the uncertainty of the load, Distributed wind power and Responsive resources ...
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The purpose of Transmission expansion planning (TEP) is to find the required network lines with the lowest investment cost So that the future burden will be provided economically by observing the system security indicators. Due to the uncertainty of the load, Distributed wind power and Responsive resources to load and competitive markets for Transmission expansion planning, Faced with challenges that require new models to be felt more than ever. In this paper, a multi-objective TEP model is presented taking into account investment costs, Responsive resources to load, along with an index for determining system security. These target functions are optimized for obtaining a non-dominant solution set based on operator priorities (cost or risk), using pareto power evolutionary algorithms based on multi-objective particle pool optimization (SPEA2-MOPSO). The proposed model is numerically verified on the modified IEEE RTS 24- bus and 118-bus systems. According to the simulation results, the proposed model can provide information regarding variants of risks and coordinate the optimum planning and DR solutions.