دانلود مقاله ISI انگلیسی شماره 140751
ترجمه فارسی عنوان مقاله

اندازه گیری باتری مناسب بهینه و برنامه ریزی در سیستم های مدیریت انرژی خانه که مجهز به پانل های فتوولتائیک خورشیدی است

عنوان انگلیسی
Stochastic optimal battery storage sizing and scheduling in home energy management systems equipped with solar photovoltaic panels
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
140751 2017 31 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Energy and Buildings, Volume 152, 1 October 2017, Pages 290-300

ترجمه کلمات کلیدی
سیستم ذخیره انرژی باتری، مدیریت انرژی خانه، سیستم فتوولتائیک، عدم قطعیت،
کلمات کلیدی انگلیسی
Battery energy storage system; Home energy management; Photovoltaic system; Uncertainty;
پیش نمایش مقاله
پیش نمایش مقاله  اندازه گیری باتری مناسب بهینه و برنامه ریزی در سیستم های مدیریت انرژی خانه که مجهز به پانل های فتوولتائیک خورشیدی است

چکیده انگلیسی

This 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.