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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.
Quasi real-time ZIP load modeling for Conservation Voltage Reduction of smart distribution networks using disaggregated AMI data
This paper aims to investigate quasi real-time ZIP load models for new Smart Grid-based Volt-VAR Optimization (VVO) techniques. As recent VVO solutions are able to perform in quasi real-time using Advanced Metering Infrastructure (AMI) data, more accurate load modeling could give distribution network operators and/or planners more precise Conservation Voltage Regulation (CVR) and energy saving values at each operating time stage. Furthermore, more accurate load modeling of each quasi real-time stage could improve VVO efficiency. As type, amount and operating time of each residential appliance varies throughout a day, this paper aims to discover ZIP load model of each quasi real-time stage separately through disaggregated data (i.e. decomposing residential load consumption into home appliance consumptions). This paper shows that the energy conservation achieved by CVR operation through presented quasi real-time ZIP load modeling could lead AMI-based VVO solutions to higher level of accuracy and data resolution compared with conventional techniques. Therefore, this paper primarily introduces a new quasi real-time AMI-based VVO engine. Then, it investigates ZIP load model of each quasi real-time stage through statistical data to conserve energy consumption. To check the authenticity and the applicability of presented model in a whole system, 33-node distribution feeder is employed., Published. Received 16 March 2015, Revised 14 May 2015, Accepted 3 June 2015, Available online 2 July 2015.