A power grand composite curves approach for analysis and adaptive operation of renewable energy smart grids

Abstract

This work proposes the use of the power grand composite curves (PGCC) method to identify energy recovery targets in renewable energy smart grids and to adaptively adjust their operation in short-term energy requirements through appropriately selected power management strategies (PMS). A PMS is the sequence of decisions offering efficient utilization of resources and equipment to meet specific targets. The aim is to identify the appropriate PMS within recurrent subsequent time intervals that efficiently serves the desired operating goals in view of operating variability. This is approached by predicting the PGCC for a time horizon extending into the future. Subsequently, the PGCC is appropriately shifted to set a target for the minimum energy inventory needed by the end of the current interval for which decisions about the system operation are sought in order to satisfy the system operating goals. The target energy inventory is guaranteed in the current interval by selecting the PMS that best matches the identified target. A formal mathematical framework is presented, associating Pinch analysis with PMS within a generic model considering numerous structural and temporal grid interactions. The proposed method is implemented on an actual hybrid smart grid considering multiple RES-based energy generation and storage options.