Hybrid energy storage systems for stand-alone electric power systems: optimization of system performance and cost through control strategies

Abstract

The development of remote, renewable-based energy is hindered in part by the lack of affordable energy storage. Requiring power-on-demand from an energy system powered by intermittent or seasonal sources may necessitate one-month’s energy storage—an expensive proposition using conventional storage technologies. If multiple energy storage devices with complementary performance characteristics are used together, the resulting ‘hybrid energy-storage system’ can dramatically reduce the cost of energy storage over single storage systems. The coupling of conventional storage batteries with emerging hydrogen technologies provides one such hybrid system. Hydrogen energy storage in this context includes an electrolyzer, hydrogen storage tank, and a fuel cell. An additional component that must be considered is the control system that determines when the various components are used. Since the control system has an effect on component sizes and thus system and operating costs, the control algorithm must be carefully considered for any system with energy storage. For this study, a time-dependent model of a stand-alone, solar powered, battery-hydrogen hybrid energy storage system was developed to investigate energy storage options for cases where supply and demand of energy are not well matched daily or seasonally. Simulations were performed for residential use with measured solar fluxes and simulated hourly loads for a site at Yuma, Arizona, USA, a desert climate at 32.7 N latitude. Renewable-based power not needed to satisfy the load is stored for later use. Two hybrid energy-storage algorithms were considered. The first is a conventional ‘state-of-charge’ control system that uses the current state of the storage system for control. The second control system presumes knowledge of future demand through a feed-forward, neural net or other ‘intelligent’ control systems. Both algorithms use battery storage to provide much of the daily energy shifting and hydrogen to provide seasonal energy shifting, thus using each storage technology to its best advantage. The cost of storing energy with a hybrid energy-storage scheme was found to be much less expensive than either single storage method, with a hybrid system storage costing 48% of the cost of a hydrogen-only system and only 9% of the cost of a conventional, battery-only system. In addition, the neural-net control system is compared to a standard battery state-of-charge control scheme, and it is shown that neural-net control systems better utilize expensive components and result in less expensive electric power than state-of-charge control systems.