T.M. Iwayemi, O.S. Tomomewo, S. Choudhary, D.K. Boakye
University of North Dakota,
United States
Keywords: hybrid energy storage, renewable energy, energy management systems, automatic switch, grid decarbonization
Summary:
Hybrid Energy Storage Systems (HESS) are increasingly critical for mitigating the intermittency of renewable energy and supporting grid decarbonization targets. This study develops and evaluates a lithium-ion battery–supercapacitor–flywheel HESS architecture governed by a Unified Mathematical Method (UMM) and an embedded Energy Management System (EMS) for a grid-connected office load. Meteorological data from NSRDB and NWTC, and load data from NREL’s website, are combined with manufacturer and HOMER Pro datasets to model a 160 kW load with 4-h (800 kWh) storage and 200 kW wind and 200 kW PV generation for the Grand Fork, North Dakota, location. The storage portfolio consists of a 270 kWh lithium-ion battery, a 265 kWh supercapacitor bank, and a 265 kWh flywheel, each constrained by technology-specific voltage, temperature, and state-of-charge (SOC) limits. The UMM applies a common set of moving-average and threshold-based equations to all devices, enabling unified charging/discharging decisions and cutoff logic across normal operation, renewable outages, and component-failure scenarios. Five operating scenarios are formulated, including normal conditions, renewable-source absence, and isolated failures of the battery, supercapacitor, or flywheel. For each case, the algorithm prioritizes devices based on their functional strengths, enforces SOC, voltage, and temperature windows, and triggers load shedding only when aggregate stored energy falls below critical thresholds. A supervisory EMS coordinates a network switch and an automatic transfer switch so that, at any instant, only the most appropriate device: battery for long-duration energy, supercapacitor for fast transients, flywheel for frequency regulation is used. The framework is implemented in HOMER Pro and evaluated in three system-level configurations: (i) grid + renewables without storage, (ii) grid + renewables with a single lithium-ion battery, and (iii) a full HESS with all three storage technologies. The results show that, relative to the no-storage baseline, the single-battery case improves load matching and enables 79,825.5 kWh/yr of arbitrage energy, while the full HESS achieves the highest total useful output (1,032,319.5 kWh/yr) by exploiting the complementary roles of all three devices. The unified moving-average cutoff logic reduces false trips, keeps all devices within their operational envelopes, and extends effective cycle life by avoiding unnecessary switching events. The hybrid configuration also maximizes environmental benefits, increasing annual avoided CO₂ emissions from 393,655 kg (no storage) to 1,360,451 kg. Valued using the Social Cost of Carbon ($51 per tonne) and 45Q tax credit ($85 per tonne), these avoided emissions correspond to $69,383–$115,638 per year in environmental value, exclusive of additional grid-services revenues. Sensitivity analysis across four benchmark scenarios (grid only, grid + renewables, single-storage, and HESS) confirms that the hybrid configuration delivers the greatest synergy, with 77% higher energy output and 345% greater carbon avoidance than the grid + renewables case. In conclusion, the proposed HESS controlled by the UMM-based EMS enhances technical performance, reliability, and sustainability while providing a clear economic rationale for multi-technology storage in future low-carbon grids. The work highlights unified control and integrated techno-economic–environmental assessment as key enablers for large-scale HESS deployment and points toward future integration of AI-driven control and field-scale validation.