Search cIRcuit

BCIT Citations Collection

: Community Energy Storage impacts on smart grid adaptive Volt-VAR Optimization of distribution networks; Accepted in 7th International Symposium on Power Electronics for Distributed Generation Systems (PEDG 2016), Jun. 2016, Vancouver, BC, Canada. This paper aims to investigate Community Energy Storage (CES) impacts on AMI-based Volt-VAR Optimization (VVO) solutions for advanced distribution networks. CES is one of the technologies employed to improve system stability, reliability and quality. As such, it could have considerable impacts on voltage control, reactive power optimization and energy conservation. Conservation Voltage Reduction (CVR) is one of the main tasks of advanced VVO engines in distribution networks. Moreover, in order to check the performance of the discussed VVO engine in the presence of CES during peak time intervals, 33-node distribution feeder is employed. The results of this paper show significant improvement in the performance of the VVO engine when CES is forced to discharge in peak times. Moreover, the results present how CES could affect Volt-VAR Control Component (VVCC) switching and how it affects the energy conservation efficiency., Conference paper, Published.

: Impact of V2G on real-time adaptive Volt/VAr optimization of distribution networks; Proceeding of IEEE ElectricalPower and Energy Conference (EPEC 2013), Aug. 2013, Halifax, Canada. Deployment of Smartgrid downstream features such as Smart Metering, pervasive control and Distributed Management Systems has brought great opportunities for distribution network planners to optimize the network in more precise methods. Moreover, the advent of Electric Vehicles (EVs) has brought more opportunities for grid optimization. Recent studies stipulate that EVs are able to inject reactive power into the grid by changing their inverter's operating mode. This paper primarily discusses a real-time adaptive Volt/VAr Optimization (VVO) engine, designed to minimize system apparent power losses, optimize voltage profiles, and reduce the operating costs of Switched Capacitor Banks of the grid. The paper goes on to study the impact of EVs on the distribution network VVO, taking into account different EV charging and penetration levels and checks the validity of the proposed algorithm by employing revised IEEE-37 Node Test Feeder in presence of various load types as a case study., Conference paper, Published.

: Maintenance scheduling of Volt-VAR control assets in smart distribution networks using advanced metering infrastructure; This paper investigates a novel approach for maintenance scheduling of volt-VAR control components (VVCCs) of distribution networks with the aid of new generation of volt-VAR optimization (VVO) solutions called quasi-real-time VVO. The new quasi-real-time VVO technique optimizes distribution network using advanced metering infrastructure (AMI) data of each quasi-real-time stage. As this VVO performs automatically and online, it is necessary for VVCCs to undergo maintenance without disturbing VVO performance. Moreover, the lost benefits that could be gained by online VVO have to be minimized. Hence, this paper proposes an AMI-based VVO consisting of a VVO engine and a maintenance scheduling engine (MSE) that operate in tandem to optimize distribution network and find the optimal maintenance scheduling of different VVCCs. To test the accuracy and the applicability of the proposed solution, a 33-node distribution feeder is employed. Furthermore, five different maintenance scenarios are investigated to check the proposed VVO performance. The results prove that the integration of VVO with MSE could be a reliable approach that can solve maintenance scheduling of VVCCs without interrupting and/or resetting VVO., Article, Published

: Real-time co-simulation platform for Smart Grid Volt-VAR Optimization using IEC 61850; This paper presents an implementation of an IEC 61850-based real-time co-simulation platform for verification of the performance of a volt-VAR optimization (VVO) engine for smart distribution networks. The proposed VVO engine is able to minimize grid loss, volt-VAR control asset operational costs, and conservation voltage reduction operational costs through its comprehensive objective functions, weighted by fuzzification using advanced metering infrastructure (AMI) data. The optimization engine receives the AMI data stream through measurement aggregators. Moreover, it sends control commands to volt-VAR control components modeled in real-time digital simulator (RTDS) through DNP.3 protocol. To check the performance and the precision of proposed VVO, a fault scenario is imposed upon the system. IEC 61850 GOOSE messages are generated and sent to change the status of specified breakers, while the VVO engine receives system reconfiguration commands via IEC61850 Manufacturing Message Specification (MMS) protocol. The results of the study on 33-node feeder showed adequate performance of proposed VVO in grid operating scenarios., Article, Published.