Optimal battery utilization for energy management and load scheduling in smart residence under demand response scheme

被引:9
|
作者
Singh, Paramvir [1 ]
Dhundhara, Sandeep [2 ]
Verma, Yajvender Pal [1 ]
Tayal, Nisha [1 ]
机构
[1] Panjab Univ, Dept Elect & Elect Engn, UIET, Chandigarh, India
[2] CCS Haryana Agr Univ, Coll Agr Engn & Technol, Dept Basic Engn, Hisar, Haryana, India
来源
关键词
Smart grid; Energy management; Demand response; MILP; Rainflow Cycle Counting algorithm; Battery capacity estimation; SIDE MANAGEMENT; HOME; SYSTEM; OPTIMIZATION; OPERATION; CONSUMPTION;
D O I
10.1016/j.segan.2021.100432
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Smart residences that could optimally integrate the actions of all their components are essential in the smart grid architecture. This paper proposes a mixed-integer linear programming (MILP) based model of a single residence that optimally operates the residential appliances and manages the energy received from the Distributed Energy Resources (DERs) apart from the utility grid according to the day-head Time of Use prices. To achieve this, an Energy Management and Load Scheduling System (EMLSS) has been incorporated into the residence. Further, the user thermal comfort was maintained by optimally operating the air conditioner in coordination with a dehumidifier to keep the indoor temperature and relative humidity within the desired limits. For observing the EMLSS's operation under the intermittent weather conditions, the simulation of the MILP model was conducted for 26 different days of the year. Using these days' results, an annual study was conducted whose results were input into the Rainflow Cycle Counting algorithm for assessing the capacity degradation of the residential Battery Energy Storage System (BESS) until its End of Life (EoL). The energy expenditure evaluation conducted until the BESS's EoL, confirmed the effectiveness of the EMLSS in reducing the replacement costs of the old BESS battery. (c) 2021 Elsevier Ltd. All rights reserved.
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页数:11
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