Optimal sizing and operating strategy of a stand‐alone generation–load–storage system: An island case study

Abstract

Component sizing optimization and technoeconomic feasibility studies for stand-alone power systems have been actively discussed in recent years. However, most models and studies overlook the importance of individual component performance, input data resolution and their integration with the system. This article compares the rapidly evolving battery storage technology applications using the context of a stand-alone system, through a case study on Bruny Island, Tasmania, Australia, where the current electricity infrastructure is approaching its end of life. We constructed a mixed-integer linear programming model to achieve optimal balance between modeling accuracy and computational complexity. The model was constructed to obtain the optimal component sizing on the basis of minimum lifetime net present cost. It was shown in our work that any transition of islands to become fully stand alone should be carefully considered, where a limited grid connection could still provide significant value to the infrastructure, greatly reduce its stress over peak hours. This concept was illustrated further with another set of model scenarios aiming to explore the performance of battery storage systems with different power output allowances, limited by the time-series data resolution, were developed. It was shown that the selection of incomplete input data cycle, reliance on standardized average values and utilization of low resolution timeseries data could heavily skew the results of a model, as the use of incomplete dataset and oversimplified average values subtly conceal some of the critical sizing and operation issues in a technoeconomic feasibility study, impacting the accuracy of the model to reflect the real problem. K E Y W O R D Scase study, energy storage, microgrid, MILP, optimization

A review of key functionalities of battery energy storage system in renewable energy integrated power systems

“…Energy storage technologies have the capability to regulate their output and thus minimize the adverse impact of RES indeterminacy. Among many existing energy storage technologies, such as a flywheel, pump hydro, capacitor, supercapacitor, and compressed air energy storage, battery energy storage system (BESS) offers better flexibility in terms of capacity, siting facility, and fast response to fulfill the requirements of storage system application 11,12,13 . BESS can store energy and is able to control active and reactive power flow independently at the point of common coupling (PCC) and provides various services.…”