Performance analysis of hybrid energy storage integrated with distributed renewable energy

Abstract

This paper proposes a microgrid (MG) system integrating distributed renewable energy (RE) and hybrid energy storage system (HESS), which is an effective solution of power supply for remote areas and islands. The distributed generation (DG) unit of the system includes photovoltaic (PV) power and wind power, and the HESS includes lithium-ion (Li-ion) battery, super capacitor (SC) and compressed air energy storage (CAES). In this study, the Confidence Interval Method (CIM) is used to establish the wind power output and PV power output model, and the DG power curves under different confidence levels are calculated. Taking the minimum annual total cost of the system as the optimization objective, the capacity allocation of the wind-PV-Li-ion battery system is optimized by using the genetic algorithm (GA) tool. Based on the quadratic moving average filtering method, the energy storage power is divided into different frequencies, and the rated power, rated capacity and initial state of charge (SOC) of three kinds of ESSs are calculated. The results show that the wind-PV-HESS can better meet the power demand of users with a good economic performance.

Keywords

• Energy storage technology
• Renewable energy
• Controlling strategy
• Capacity optimization
• Load forecasting