Real-Time Adaptive VVO/CVR Topology Using Multi-Agent System and IEC 61850-Based Communication Protocol

A novel Volt-VAR Optimization engine for smart distribution networks utilizing Vehicle to Grid dispatch

“…A necessary coordination by DDC of different feeder controls under its authority is needed due to their connection with the High Voltage (HV) grid. More information regarding the structure of proposed VVO can be found in [2].…”

“…Moreover, rising electricity demand, combined with environmental impact of fossil-fuel power generation, have motivated electric utility companies to seek new technologies and/or techniques to re-optimize their distribution networks. One of the main techniques traditionally employed to minimize losses in distribution grid is Volt-VAR Optimization (VVO) [2]. VVO is able to optimize voltage and/or reactive power (VAR) of a distribution network using Volt-VAR components such as transformer on-load tap changers (OLTCs), Voltage Regulators (VRs), Capacitor Banks (CBs) and other existing Volt-VAR control devices in distribution substations and/or distribution feeders.…”

“…Some research papers have tried to address different aspects of Smart Grid and their specifications [11,12,14,18,19,23,24,[26][27][28]37] before IEEE 2030 standard. Most such papers have focused on concepts such as: advantages, challenges and functional requirements of VVO in Smart Grids [1,2,[15][16][17]20,23,39], which have covered the fundamentals of Smart Grid based VVO. Some other works such as [40-,41] [28][29][30].…”

Quasi real-time ZIP load modeling for Conservation Voltage Reduction of smart distribution networks using disaggregated AMI data

“…It can be observed from literature survey that there has been insufficient works on finding accurate load models for new quasi real-time AMI-based VVO solutions. There are few papers which theoretically assessed CVR as a part of VVO engine in real-time operating conditions [3], [11], [17], [27], [29]- [30], [49]- [51]. Even fewer works have been done regarding load modeling of new VVO engines [49]- [51].…”

Predictive algorithm for Volt/VAR optimization of distribution networks using Neural Networks

“…This could prevent sending huge amount of data required for VVO to the back-office. Hence, VVO engine receives its required downstream data from Multi-Agent systems (detailed structure and the main tasks of Multi Agent systems are explained in [13] by the authors). Moreover, it obtains the required global attributes from DMS/SCADA and saves them to its database.…”