Modeling and Grid Integration of Large Dish‐Stirling Solar Farm

Dustin Howard, Ronald G. Harley and Ganesh K. Venayagamoorthy

Modeling and Grid Integration of Large Dish‐Stirling Solar FarmDish-Stirling systems are a form of concentrating solar power (CSP) emerging as an efficient and reliable source of renewable energy. Various technical hurdles are involved in the grid interconnection of dish-Stirling systems, particularly with issues related to power factor correction, low voltage ride-through capability, and reactive power planning. While there are no gridinterconnection requirements specific to dish-Stirling technology, the requirements currently established for wind farms are used as a starting point due to the similar design and operating characteristics between wind farms and dish-Stirling solar farms. A dish-Stirling solar farm requires external reactive power compensation to meet the power factor requirements presently set for wind farms.

Dynamic Performance Model for Wind Turbine Generators

Prajwal Gautam and  Ganesh Kumar Venayagamoorthy

Wind turbine power curves are based on the industry standard IEC 61400-12-1. Power curves are used for planning purposes and estimating total wind power production. Wind velocity are collected and averaged over 10-minute periods.  Traditional methods do not explain varying characteristics in wind dynamics where multiple power productions are observed for same wind speed. When the input parameters such as wind speed and wind directions are known and the output parameter wind power are known for an installed wind turbine generation plant, a dynamic computational network such as neural network is used to develop operation model and estimate the wind power generation.

Modeling and Intelligent Control for an Electric Power Micro-Grid

Yi Deng, Ganesh Kumar Venaygamoorthy and Ronald G Harley

The micro-grid will be an important part of future power system. It contains the typical elements in present and future power systems and also contains some renewable energy sources, eg. wind power, photovoltaic energy, and energy storage. Power electronic devices/converters act as interface between the renewable energy sources and the power grid. An intelligent controller will be necessary to ensure stability of the micro-grid.

Gridable (Plug-in) Vehicles -Smart Grid Integration

Ahmed Y. Saber and Ganesh K. Venayagamoorthy

Gridable (Plug-in) Vehicles -Smart Grid IntegrationSmart grid consists of conventional generations, wind, solar and gridable vehicles (GVs). Intelligent optimization methods result in reduction of cost of energy and emission. GVs operate in two modes: grid-to-vehicle (G2V, loads and storage), and vehicle-to-grid (V2G, sources). “Smartparks with GVs” are as virtual power plants consisting of several small portable power plants (vehicles).

Impact of Plug-in Vehicles on Power System Stability

Pinaki Mitra and Ganesh K. Venayagamoorthy

Impact of Plug-in Vehicles on Power System StabilityV2G power transactions are going to be an integrated part of the smart grid. This study shows how sudden charging and discharging of the SmartParks will impact the power system stability and demonstrates the potential of a wide-area controller to mitigate the impacts.

Scalable Monitoring and DSOPF Control for Smart Grids

Karthikeyan Balasubramaniam and Ganesh Kumar Venayagamoorthy

An adaptive, optimal, real-time controller based on adaptive critics design called dynamic stochastic optimal power flow (DSOPF) controller is proposed. Stochastic nature in power system can arise as a result of load and generation stochastic behaviors and due to random noise in PMU data which arises due to communication noise and measurement error. DSOPF controller can perform real-time control action but system wide information cannot be made available to DSOPF controller in real-time because of power system communication delays which can range from a few milliseconds to several seconds depending on distance and communication media.

If state variables can be predicted ahead of time, then communication delay can be compensated for. Hence, a scalable wide area monitoring system that can predict state variables ahead of time is developed. Scalability is achieved by using cellular architecture called cellular computational network (CCN). This module can effectively compensate for communication delays and hence can enable DSOPF controller to perform real-time control with system wide information.

Scalable Integrated Situational Awareness System for Smart Grid

Bipul Luitel and Ganesh Kumar Venayagamoorthy

In a smart grid, monitoring of system variables such as voltages and speed deviations of generators is important for assessing its stability, and making proper control decisions. Development of wide area monitoring system is, hence, important for situational awareness; especially in a smart grid where integration of renewable resources, distributed generation and bidirectional power flows can lead to instabilities if proper control action is not taken at the right time, place and context.

Emergent Intelligence in Cellular Neural Networks

Bipul Luitel and Ganesh K. Venayagamoorthy

Emergent Intelligence in Cellular Neural NetworksIntelligence in CNN emerges from a group of cells that are learning subsystems, all of which either utilize the same or  a different learning method, that either adapt themselves in synchrony with the other subsystems or independent of the others in their own pace. Intelligence in CNN emerges over time through progressive learning and adaptation of these distributed interacting subsystems represented as cells.