Coordinated operations of distributed wind generation in a distribution system using PMUs

Abstract

Wind energy is becoming one of the most widely implemented forms of renewable energy worldwide. Traditionally, wind has been considered a non-dispatchable source of energy due to the uncertainty of wind speed and hence the variable availability of wind power. Advances in technology allow the consideration of the impact of distributed wind turbines and farms on distribution systems. It is possible to combine the clean energy attributes of wind with the quickly dispatchable nature of a storage facility in order to provide the maximum amount of locally available power economically to the loads present on the distribution feeder. However, a monitoring and control system needs to be provided that is capable of detecting the changes associated with the distribution feeder load and also the variable generation output from the wind farms. This task can be accomplished using a Phasor Measurement Unit (PMU) which has very high sampling rates and hence can measure very rapid and dynamic changes in power levels associated with distribution feeder load and wind generation. The data which is obtained from these PMUs can be used to calculate the amount of distributed generation and storage that can be dispatched locally at the distribution feeder, thus resulting in a reduction in the peak load levels associated with the distribution feeder as seen by the substation monitoring system. Simulations will work to balance load requirements, wind generation output, and distributed storage providing a stable system utilizing maximum renewable resources. The standard IEEE 37-node distribution test feeder is used in the study. Probabilistic models are implemented for distribution feeder load, and the models are analyzed through simulations. Four different combinations of charging and discharging methods have been investigated. Two analytically different algorithms have been used for wind and battery dispatch, one based on forecasted load information and the other based on historical measurements obtained from PMUs. The strategies being investigated can also be used to implement other important applications such as distribution system state estimation, protection and instability prediction.