Smart Grid Adaptive Volt-VAR Optimization in Distribution Networks

The electrical distribution networks across the world are witnessing a steady infusion of smart grid technologies into every aspect of their infrastructure and operations. Technologies such as Energy Management Systems (EMS), Distribution Management Systems (DMS) and Advanced Metering Infrastructure (AMI) have partially addressed the needs of the distribution networks for automation, control, monitoring and optimization. Many utilities intend to explore the capabilities of advanced AMI systems for other functionalities within their grids. AMI systems produce an extensive amount of data that can be collected from termination points, for various optimization, control and energy conservation functions. Moreover, deployment of smart grid assets and smart system utilizations provide unprecedented opportunities for network operators and planners to adopt more efficient and reliable strategies for the technical/economic issues of their grids. Accordingly, new smart grid adaptive optimization and control techniques can be constituent components of future distribution grids. The present thesis aims to propose a novel smart grid adaptive solution for one of the well-known techniques typically employed for distribution network voltage and reactive power optimization called Volt-VAR Optimization (VVO). Proposed VVO engine enables capturing AMI data to solve the VVO problem through its comprehensive objective function in quasi real-time intervals. Furthermore, this thesis investigates the impacts of disparate smart grid components such as Distributed Generation (DGs), Electric Vehicles (EVs) and Distributed Energy Resources (DERs) on proposed smart grid adaptive VVO. Solving maintenance scheduling problem of Volt-VAR Control Components (VVCCs), proposing a new solution for VVCC number of switching per day issue, offering a quasi-real-time load modeling approach to enhance the accuracy of energy conservation calculations, presenting a predictive VVO solution and considering Conservation Voltage Reduction (CVR) as a part of VVO objective to save the energy consumption of loads are some of the novel VVO studies presented in this thesis. This thesis examines proposed VVO performance and applicability through a real-time co-simulation platform using advanced communication protocols/standards such as DNP3 and IEC 61850. The results of thesis studies prove that applying proposed VVO engine could considerably enhance smart distribution system levels of accuracy, efficiency and reliability.