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Stochastic optimal battery storage sizing and scheduling in home energy management systems equipped with solar photovoltaic panels
HighlightsAn efficient home energy management system is addressed.Battery energy storage system and photovoltaic system are utilized.Charging-discharging regime and capacity of BESS are optimally determined.Home can sell energy to network, buy energy from network, and work on islanding mode.The proposed HEMS significantly reduces annual electricity bill in the home.
AbstractThis paper presents an efficient home energy management system (HEMS) by optimal utilizing battery energy storage system (BESS) and photovoltaic (PV) systems. In the proposed HEMS, charging-discharging regime, capacity, and power of BESS are considered as design variables and optimally determined. Three operating conditions are considered for the home including: (i) home can receive energy from the network during off-peak low-cost hours, (ii) home can send energy to the main grid during on-peak high-cost hours for making the profit, and (iii) home can work on net-zero energy (NZE) model or standalone mode. The BESS is utilized to store energy during off-peak low-cost hours and discharge energy during on-peak high-cost hours. The proposed planning for determining the optimal operation strategy and sizing of BESS is expressed as a stochastic mixed integer nonlinear programming (MINLP). As well, output power produced by photovoltaic (PV) system is regarded as uncertain parameter and modeled by probability distribution function (PDF). Monte-Carlo Simulation (MCS) is applied to cope with uncertainties. The proposed stochastic MINLP is solved by Meta-heuristic optimization techniques. Simulation results demonstrate that the proposed HEMS can significantly reduce annual electricity bill. As well, NZE model can also be achieved by installing BESS and PV system at the same time.
Stochastic optimal battery storage sizing and scheduling in home energy management systems equipped with solar photovoltaic panels
HighlightsAn efficient home energy management system is addressed.Battery energy storage system and photovoltaic system are utilized.Charging-discharging regime and capacity of BESS are optimally determined.Home can sell energy to network, buy energy from network, and work on islanding mode.The proposed HEMS significantly reduces annual electricity bill in the home.
AbstractThis paper presents an efficient home energy management system (HEMS) by optimal utilizing battery energy storage system (BESS) and photovoltaic (PV) systems. In the proposed HEMS, charging-discharging regime, capacity, and power of BESS are considered as design variables and optimally determined. Three operating conditions are considered for the home including: (i) home can receive energy from the network during off-peak low-cost hours, (ii) home can send energy to the main grid during on-peak high-cost hours for making the profit, and (iii) home can work on net-zero energy (NZE) model or standalone mode. The BESS is utilized to store energy during off-peak low-cost hours and discharge energy during on-peak high-cost hours. The proposed planning for determining the optimal operation strategy and sizing of BESS is expressed as a stochastic mixed integer nonlinear programming (MINLP). As well, output power produced by photovoltaic (PV) system is regarded as uncertain parameter and modeled by probability distribution function (PDF). Monte-Carlo Simulation (MCS) is applied to cope with uncertainties. The proposed stochastic MINLP is solved by Meta-heuristic optimization techniques. Simulation results demonstrate that the proposed HEMS can significantly reduce annual electricity bill. As well, NZE model can also be achieved by installing BESS and PV system at the same time.
Stochastic optimal battery storage sizing and scheduling in home energy management systems equipped with solar photovoltaic panels
Hemmati, Reza (author) / Saboori, Hedayat (author)
Energy and Buildings ; 152 ; 290-300
2017-07-14
11 pages
Article (Journal)
Electronic Resource
English
DOAJ | 2023
|Distributed Demand Side Management with Battery Storage for Smart Home Energy Scheduling
DOAJ | 2017
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