Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Optimized Energy Management and Storage Sizing in Smart Homes with Renewable Energy Sources Under Safe Operating Conditions
Integrating renewable energy sources (RESs) such as solar and wind generation systems introduces challenges in ensuring a safe and stable power supply to the power system due to their inherent output variability. Addressing this issue requires the development of advanced technologies and methodologies to mitigate power variability while enabling the integration of high levels of renewable energy into the existing power system. One practical approach to managing the variability of RESs is incorporating an energy storage system (ESS), which enhances the reliability and stability of the power supply from RESs. This study focuses on optimized energy management and storage capacity sizing while ensuring safe operation amid output variability to maximize the benefits of combining RESs and two ESSs (i.e., primary and secondary) for a smart home energy management system. To achieve this, a linear programming (LP) model is employed to investigate the relationship between RESs, ESSs, and energy loads to determine the storage capacity under safety conditions. Here, safety refers to preserving the capacity limitations of each ESS in the power system against fluctuations. The optimization problem is mathematically formulated, and a feasible solution is found using the LP Solver in MATLAB. To validate the proposed optimal sizing of ESS and energy balancing against fluctuations, power generation, and consumption data from apartment facility, iHouse smart apartment facilities are employed during all seasons, i.e., spring, summer, winter, and autumn. Additionally, several case studies are analyzed, representing a distinct physical arrangement of connectivity between power devices, from the most densely connected to the least connected. The results indicate that the strategic power distribution significantly reduces the total ESS size, including the primary and secondary storage systems, for each season. The optimal secondary ESS size decreased to 25.7 % for the spring season, 17.29% for the summer season, 6.79 % for the winter season, and 7.01 % for the autumn season from the least connectivity from power devices to dense connectivity. The findings highlight the seasonal variations of generation and consumption and their impact on ESS sizing while preserving the limitations and ensuring the safety of the power system. Hence, it is a novel methodology for seasonal storage sizing and strategic energy management, guaranteeing stable and resilient power system operation.
Optimized Energy Management and Storage Sizing in Smart Homes with Renewable Energy Sources Under Safe Operating Conditions
Integrating renewable energy sources (RESs) such as solar and wind generation systems introduces challenges in ensuring a safe and stable power supply to the power system due to their inherent output variability. Addressing this issue requires the development of advanced technologies and methodologies to mitigate power variability while enabling the integration of high levels of renewable energy into the existing power system. One practical approach to managing the variability of RESs is incorporating an energy storage system (ESS), which enhances the reliability and stability of the power supply from RESs. This study focuses on optimized energy management and storage capacity sizing while ensuring safe operation amid output variability to maximize the benefits of combining RESs and two ESSs (i.e., primary and secondary) for a smart home energy management system. To achieve this, a linear programming (LP) model is employed to investigate the relationship between RESs, ESSs, and energy loads to determine the storage capacity under safety conditions. Here, safety refers to preserving the capacity limitations of each ESS in the power system against fluctuations. The optimization problem is mathematically formulated, and a feasible solution is found using the LP Solver in MATLAB. To validate the proposed optimal sizing of ESS and energy balancing against fluctuations, power generation, and consumption data from apartment facility, iHouse smart apartment facilities are employed during all seasons, i.e., spring, summer, winter, and autumn. Additionally, several case studies are analyzed, representing a distinct physical arrangement of connectivity between power devices, from the most densely connected to the least connected. The results indicate that the strategic power distribution significantly reduces the total ESS size, including the primary and secondary storage systems, for each season. The optimal secondary ESS size decreased to 25.7 % for the spring season, 17.29% for the summer season, 6.79 % for the winter season, and 7.01 % for the autumn season from the least connectivity from power devices to dense connectivity. The findings highlight the seasonal variations of generation and consumption and their impact on ESS sizing while preserving the limitations and ensuring the safety of the power system. Hence, it is a novel methodology for seasonal storage sizing and strategic energy management, guaranteeing stable and resilient power system operation.
Optimized Energy Management and Storage Sizing in Smart Homes with Renewable Energy Sources Under Safe Operating Conditions
Saher Javaid (Autor:in) / Yuto Lim (Autor:in) / Yasuo Tan (Autor:in)
2025
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
Metadata by DOAJ is licensed under CC BY-SA 1.0
| DOAJ | 2023
Smart Homes and Regions as Building Blocks for 100% Renewable Energy Globally
| Springer Verlag | 2019
Optimal dynamic energy management system in smart homes
| TIBKAT | 2014
Optimal dynamic energy management system in smart homes
| UB Braunschweig | 2014