Muhammad A. Choudhry

PSO-based Evolutionary Optimization for Parameter Identification of an Induction Motor

In this paper a particle swarm optimization (PSO) algorithm with a constriction factor is applied to identify the parameters of an induction motor. The variables used to estimate electrical and mechanical parameters are the measured stator currents and voltages. Performance of the identification scheme is demonstrated through simulation and compared with parameters obtained with a nonlinear least square technique. The estimated parameters compare well with the actual parameters.

Intelligent reconfiguration of smart distribution network using multi-agent technology

The distribution network reconfiguration is a process that consists of changing the status of the network switches for re-routing the power after a fault occurrence, or to optimize some given criteria. Traditionally, feeder reconfiguration is a complex combinatorial and constrained optimization problem because of the numerous combinations of candidate switches. A multi-agent based system for distribution network reconfiguration is proposed. The system consists of load agents and switch agents located at the loads and switches in the network and a global agent located at the substation. The objective is to supply the critical loads while maintaining an acceptable system voltage profile. Simulation results are presented for a typical distribution system named Circuit of the Future (CoF), which is developed by Southern California Edison (SCE).

Fault location and isolation using multi agent systems in power distribution systems with distributed generation sources

This paper presents a Multi Agent System (MAS) design with distributed intelligence for fault location and isolation in power distribution systems with the presence of Distributed Generation Sources (DGS). In the proposed MAS, agents all over the feeder communicate with their neighbors and use the local differential current information to locate the faulty zone and isolate the fault. Agents update their local knowledge by exchanging their voltage and current phasor data with their neighbors and monitoring the local current. The distributed generation penetration is considered to be up to 50 percent. The multi-agent models are simulated in Matlab® Simulink using user defined s-functions and the power system is modeled using the Simulink Simpower toolbox. The proposed method has been tested on a model of an existing Mon Power company circuit. Both faulted zone and fault type have been successfully identified.

Real-time multi agent system modeling for fault detection in power distribution systems

This paper presents a decentralized multi agent system (MAS) which works in real time with a power distribution system for fault detection applications. The agents use local voltage and current rms values. The multi-agent models are simulated in Matlab® Simulink using user defined s-functions and the power system is modeled using the Simulink Simpower toolbox. The proposed method has been tested on a model of an existing Mon Power circuit. Both faulted zone and fault type have been successfully identified.

Multi-Agent systems hardware development and deployment for smart grid control applications

A Multi-Agent System (MAS) for Smart Grid control is developed as part of the West Virginia Super Circuit (WVSC) Smart Grid Demonstration project. Both software and hardware deployment of the technology is being carried out on an Analog Power Simulator upgraded and automated to meet the Smart Grid requirements. The Multi-Agent System which is developed is based on mimicking the Human Immune System Cells behavior to intelligently perform feeder fault location, isolation, reconfiguration and restoration for a specific layout of the existing Allegheny Power West Run circuit.

Smart MAS restoration for distribution system with Microgrids

Fault Location, Isolation, and Restoration (FLIR) is the key concept of Distribution Automation (DA) in todays Smart Grid arena. A novel hybrid Multi Agent System (MAS) fault restoration solution has been proposed in this paper that uses both centralized and decentralized concepts for fault restoration on feeders with Microgrids. The main goal is to automatically reenergize un-faulted portions of feeders and restore power to as much as customers as possible while maintaining system constraints like voltage limits and loading levels. The proposed MAS concept is designed to be implemented on a couple of circuits in the territory of local utility, Mon Power, under the efforts of a DOE demonstration project named West Virginia Super Circuit (WVSC). The real distribution network is simulated in CYMDIST and Matlab/Simpower whereas the MAS is designed in Java Agent Development Framework (JADE). Simulation results show promising advantages of using proposed MAS solution for fault restoration using Microgrids.

A Multiagent Design for Power Distribution Systems Automation

A new multiagent system (MAS) design for fault location, isolation, and restoration in power distribution systems (PDSs) is presented. When there is a fault in the PDS, MAS quickly isolates the fault and restores the service to the fault-free zones. Hierarchical coordination strategy is introduced to manage the agents, which integrate the advantages of both centralized and decentralized coordination strategies. Proposed MAS is composed of zone agents (ZAs), feeder agents (FAs), and substation agents. In this framework, ZA locate and isolate the fault based on the locally available information, and assist the FA for reconfiguration and restoration. FA can solve the restoration problem using the existing algorithms for the 0-1 knapsack problem. A novel

Novel Load Frequency Control approach based on Virtual Area Error in a microgrid including PV and battery

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Distributed Multi-Agent based Load Shedding in Power Distribution Systems

-learning mechanism is also introduced to support the FA in decision making for restoration. The design is illustrated by the use of case studies of fault location, isolation, and restoration on West Virginia super circuit. The results from the case studies indicate the performance of proposed MAS design.

On an SVC backstepping damping nonlinear controller design for power systems

In this paper, the frequency of a microgrid, that contains a PV generation and a battery energy storage, is controlled. The paper presents a new approach for Load Frequency Control (LFC) in a microgrid considering the low voltage microgrid as an artificial multi-area network and providing a new strategy which can significantly improve the frequency regulation of the microgrid. A Virtual Area Control Error (VACE) is introduced which utilizes a virtual tie-line and includes the State of Charge (SOC) of the battery to take into consideration the realistic characteristics of the device. The system is simulated using PSCAD. The results show a good improvement in frequency regulation.