A Stochastic Simulation of Battery Sizing for Demand Shifting and Uninterruptible Power Supply Facility

This paper presents a stochastic simulation using Monte Carlo technique to size a battery to meet dual objectives of demand shift at peak tariff times and outage protection (an uninterruptible power supply function) for commercial buildings. Both functions require battery storage and the sizing of battery using numerical optimization is popularly used. However, outage and demand peaks are not of deterministic nature or location. A given battery size can only offer a particular probability of surviving an outage or completing a demand shift, this offers an opportunity to battery sizing using stochastic methods. In this work, the Monte Carlo method takes into account the historical outage statistics and building load profiles. Further, it describes the life-cycle cost of the system and the ratio of saving and investment for ten cases of demand shifting. It also reports on the customer outage costs which were calculated based on a weekday load profile for different outage durations. By considering the statistics of both problems together, customers can assess the risk of not being able to survive in an outage and the success rate of meeting the demand shift capability based on the results of the proposed method.