Predictive Hierarchical Control of Power Flow in Large-Scale PV Microgrids With Energy Storage

Abstract

Large-scale PV microgrids constitute a growing portion of distributed renewable generation in many grids worldwide and are expected to continue their growth in the foreseeable future. Managing the operation of such microgrids and in particular their interaction with the main electricity grid is a challenging task as it involves controlling large intermittent PV resources. The addition of auxiliary DERs and energy storage systems to such microgrids is a promising solution that provides some flexibility to the operation of these fluctuating PV resources. In this work, a hierarchical predictive controller is designed to perform daily scheduling and real-time control of a PV microgrid with energy storage and auxiliary diesel generation. The controller aims to increase utilization of available PV resources, reduce the daily variability of power flow to the main grid, while at the same time controlling power fluctuations at the point of connection. The controller is designed to utilize updating load and PV predictions on a receding time horizon and uses the flexibility of energy storage and diesel resources to compensate for fluctuations and prediction errors. A study of multiple operational scenarios demonstrates successful performance of the proposed controller.