Preprint Article Version 1 This version is not peer-reviewed

Real-Time Demand Side Management Algorithm Using Stochastic Optimization

Version 1 : Received: 4 April 2018 / Approved: 4 April 2018 / Online: 4 April 2018 (08:37:59 CEST)

A peer-reviewed article of this Preprint also exists.

Amoasi Acquah, M.; Kodaira, D.; Han, S. Real-Time Demand Side Management Algorithm Using Stochastic Optimization. Energies 2018, 11, 1166. Amoasi Acquah, M.; Kodaira, D.; Han, S. Real-Time Demand Side Management Algorithm Using Stochastic Optimization. Energies 2018, 11, 1166.

Journal reference: Energies 2018, 11, 1166
DOI: 10.3390/en11051166

Abstract

A Demand-side management technique are deployed along with battery energy-storage systems (BESSs) to lower the electricity cost by mitigating the peak load of a building. Most of the existing methods rely on manual operation of the BESS, or even an elaborate building energy-management system resorting to a deterministic method that is susceptible to unforeseen growth in demand. In this study we propose a real-time optimal operating strategy for BESS based on density demand forecast and stochastic optimization. This method takes into consideration uncertainties in demand when accounting for an optimal BESS schedule, making it robust compared to the deterministic case. The proposed method is verified and tested against existing algorithms. Data obtained from a real site in South Korea is used for verification and testing. The results show that the proposed method is effective, even for the cases where the forecasted demand deviates from the observed demand

Subject Areas

demand-side management; peak demand control; dynamic-interval density forecast; stochastic optimization; dimension reduction; battery energy-storage system (BESS)

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