The number of sensors connected to the electric power system is expected to grow by several orders of magnitude by 2020. However, the information networks which will transmit and analyze the resulting data are ill-equipped to handle the resulting volume with reliable real-time delivery. Without the ability to manage and use this data, deploying sensors such as phasor measurement units in the transmission system and smart meters in the distribution system will not result in the desired improvements in the power grid. The ability to exploit the massive data being generated by new sensors would allow for more efficient flow of power and increased survivability of the grid. Additionally, the power systems of today are not capable of managing two-way power flow to accommodate distributed generation capabilities due to concerns about system stability and lack of system flexibility. The research that we are performing creates a framework to add “intelligence” to the sensors and actuators being used today in the electric power system. Sensors that use our framework will be capable of sharing information through the various layers of the electric power system to enable two-way information flow to help facilitate integration of distributed resources. Several techniques are considered including use of peer-to-peer communication as well as distributed agents. Specifically, we will have software agents operating on systems with differing levels of computing power. The agents will cooperate to bring computation closer to the data. The types of computation considered are control decisions, data analysis, and demand/response. When paired with distributed autonomous controllers, the sensors form the basis of an information system that supports deployment of both micro-grids and islanding. Our efforts in the area of developing the next generation information infrastructure for sensors in the power grid form the basis of a broader strategy that enables better integration of distributed generation, distribution automation systems and decentralized control (micro-grids).
Dynamic Behavior of Three phase Inductions Motors as Loads in an Electric Power System with Distributed Generation, a Case of Study
