Lifetime financial analysis of a model predictive control retrofit for integrated PV-battery systems in commercial buildings
Max Bird, Reewa Andraos, Salvador Acha, Nilay Shah
Abstract
As electrical grids decarbonise, the need for flexible, real-time energy management systems becomes crucial to handle the variability of renewable sources. This paper investigates the lifetime performance of a commercial PV-battery system under three potential control approaches. Two rule-based controllers and one economic MPC approach are simulated over the lifetime of the battery, considering both the upfront capital and ongoing operational costs. Under the nominal rule-based control, installing the battery system saves 2.9% in operational costs per year. An informed rule-based schedule was then created, based on observing the typical PV and building loads and electricity price dynamics, increasing savings to 4.3%. These additional savings can be realised without any additional capital or operational investment. A supervisory MPC approach is integrated with the existing system control, requiring an upfront investment of $13.7k, combined with additional operational costs of $5.89k/yr. Accounting for these additional costs, net operational savings increase to 6% compared to the baseline operation without a battery system, while also reducing carbon emissions by 9.8%. MPC savings increase to 13.2% when considering the volatile electricity prices seen during the 2022 energy crisis. Despite these encouraging savings, current battery systems remain financially unattractive due to their high upfront cost, and all three control scenarios result in a negative NPV. A sensitivity analysis demonstrates that optimal sizing of batteries and reductions in their cost are the most significant factors when evaluating the lifetime performance of PV-battery systems. • Capital and operating costs for deploying MPC with PV-battery systems are analysed. • Sensitivity analysis performed to understand MPC performance under different conditions. • MPC reduces operating costs by 6% compared to 4.3% for informed rule-based control. • MPC improves with reduced battery costs and increased electricity price volatility.