Optimizing PV and Battery Energy Storage Systems for Peak Demand Reduction and Cost Savings in Malaysian Commercial Buildings
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Marzband, M
Kalam, A
Hossain, MA
Manojkumar, R
Saeed, N
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London, United Kingdom
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Abstract
This study proposes a technique to optimize the sizing capacities of solar photovoltaic (PV) and battery energy storage (BES) systems in Malaysian commercial buildings to reduce peak demand and energy costs. Real-time hourly data on solar irradiance, air temperature, and load patterns are utilized, along with Malaysian energy rates (net energy metering and retail price) and the limitation of maximum export power to the grid. The proposed system configuration uses energy management real-time rules with a control strategy of peak shaving, and the optimal capacity of the PV-BES system is derived based on scenarios with limited rooftop space and net energy metering tariffs. The case study shows that the optimal systems reduced the cost of electricity by 26.03% for the commercial building case of the C1 tariff, with annual energy consumption and peak demand reductions of 20.47% and 16.41%, respectively. The proposed system also allowed for the sale to the grid of 10232.83 kWh of electricity. The foundation of the optimization process over a 20-year period, the lowest life cycle cost which is consisted of PV-BES system costs and electricity costs. Overall, this study provides a practical approach for customers to determine the optimal sizing capacity of PV-BES systems in commercial buildings to reduce energy costs and peak demand.
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2023 IEEE IAS Global Conference on Emerging Technologies (GlobConET)
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Electrical energy storage
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Hossain, J; Marzband, M; Kalam, A; Hossain, MA; Manojkumar, R; Saeed, N, Optimizing PV and Battery Energy Storage Systems for Peak Demand Reduction and Cost Savings in Malaysian Commercial Buildings, 2023 IEEE IAS Global Conference on Emerging Technologies (GlobConET), 2023