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BCIT Citations Collection
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- 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.
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- Predictive algorithm for Volt/VAR optimization of distribution networks using Neural Networks
- Proceedings of IEEE Canadian Conference on Electrical and Computer Engineering (CCECE2014),May 2014, Toronto, Canada. Smart Grid functions such as Advanced Metering Infrastructure, Pervasive Control and Distribution Management Systems have brought numerous control and optimization opportunities for distribution networks through more accurate and reliable techniques. This paper presents a new predictive approach for Volt/VAr Optimization (VVO) of smart distribution systems using Neural Networks (NN) and Genetic Algorithm (GA). The proposed predictive algorithm is capable of predicting the load profile of target nodes a day ahead by employing the historical metrology data of Smart Meters, It can further perform a comprehensive VVO in order to minimize distribution network loss/operating costs and run Conservation Voltage Reduction (CVR) to conserve more energy. To test the merits of the proposed algorithm, British Columbia Institute of Technology north campus distribution grid is used as research case study., Conference paper, Published.
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- Real-time co-simulated platform for novel Volt-VAR Optimization of smart distribution network using AMI data
- Accepted in IEEE International Conference on Smart Energy Grid Engineering, May 2015. This paper presents a real-time co-simulated platform for novel voltage and reactive power optimization (VVO) of distribution grids through a real-time digital simulator (RTDS) in presence of a reliable communication platform. The proposed VVO engine is able to capture quasi real-time data from local Advanced Metering Infrastructure (AMI) and optimizes the distribution network for each quasi real-time stage (every 5 minutes) based on system main characteristics (i.e. active/reactive power of nodes). At each time stage, the VVO engine tries to minimize losses in the distribution network as well as to improve the voltage profile of the system. In order to test robustness, performance and the applicability of proposed Volt-VAR Optimization engine, a 33 node distribution network has been modeled and studied in a real-time Co-simulated environment by real-time simulator (RTDS) and a real communication platform with DNP.3 protocol. The preliminary results prove well-performance of proposed AMI-based VVO engine and show that the engine enables system to achieve higher level of loss/operating cost reduction through a sophisticated optimization engine compare with conventional approaches., Conference paper, Published.