Adaptive coordinated feeder flow control in distribution system with the support of distributed energy resources

This paper aims to minimize the feeder power flow deviation from scheduled value by balancing generation and load demand within the distribution system under various local disturbances. The available distributed energy resources (DER) can be properly utilized to control the feeder flow which gains significant advantages (i) to support load frequency control (LFC) problem at transmission level (ii) reduces unscheduled interchange in feeder which is priced higher (iii) increased reliability of the grid. The deviation in feeder flow is reduced by properly coordinating the power output from DER such as fuel cell, battery storage system and responsive loads (demand response) through an adaptive fuzzy controller with optimally tuned gains using particle swarm optimization. The level of participation from each DER units are decided using fuzzy inference system based on the availability of resources and level of disturbance. The photovoltaic array and wind turbine are also considered in the system and always operated at the maximum power point. The proposed method is examined on IEEE 37 bus system implemented in the MATLAB based Power Analysis Toolbox (PAT) for performing time-domain dynamic analysis. It is shown that the proposed adaptive controller exhibits better performance for various disturbance conditions.