TY - JOUR
T1 - Optimal operation of hybrid electrical and thermal energy storage systems under uncertain loading condition
AU - Mehrjerdi, Hasan
AU - Rakhshani, Elyas
PY - 2019
Y1 - 2019
N2 - This paper presents a hybrid model of an energy storage system including thermal and electrical energy storage systems in the building with thermal and electrical loads. Building receives its energy from electrical grid and purpose is to reduce the daily energy cost by optimal operation of hybrid energy storage system. Load forecast error is included as uncertainty and both thermal and electrical loads are modeled by Gaussian probability distribution function. The proposed problem for optimal cooperation of hybrid thermal-electrical storage systems is mathematically expressed as mixed integer binary linear programming. The scenario-based stochastic modelling is also included to deal with uncertainty in loading. The expressed stochastic optimization programming minimizes the daily energy cost in building and determines the optimal charging-discharging pattern for both thermal and electrical storage systems at the same time. The results demonstrate that electrical energy storage system reduces the cost about 15%, the thermal energy storage system decreases the cost about 17%, and coordinated thermal-electrical energy storage system reduces the cost about 34%. As a result, the best operation is achieved by the coordinated thermal-electrical energy storage system.
AB - This paper presents a hybrid model of an energy storage system including thermal and electrical energy storage systems in the building with thermal and electrical loads. Building receives its energy from electrical grid and purpose is to reduce the daily energy cost by optimal operation of hybrid energy storage system. Load forecast error is included as uncertainty and both thermal and electrical loads are modeled by Gaussian probability distribution function. The proposed problem for optimal cooperation of hybrid thermal-electrical storage systems is mathematically expressed as mixed integer binary linear programming. The scenario-based stochastic modelling is also included to deal with uncertainty in loading. The expressed stochastic optimization programming minimizes the daily energy cost in building and determines the optimal charging-discharging pattern for both thermal and electrical storage systems at the same time. The results demonstrate that electrical energy storage system reduces the cost about 15%, the thermal energy storage system decreases the cost about 17%, and coordinated thermal-electrical energy storage system reduces the cost about 34%. As a result, the best operation is achieved by the coordinated thermal-electrical energy storage system.
KW - Electrical energy storage system
KW - Hybrid storage
KW - Load uncertainty
KW - Stochastic programming
KW - Thermal energy storage system
UR - http://www.scopus.com/inward/record.url?scp=85068653717&partnerID=8YFLogxK
U2 - 10.1016/j.applthermaleng.2019.114094
DO - 10.1016/j.applthermaleng.2019.114094
M3 - Article
AN - SCOPUS:85068653717
SN - 1359-4311
VL - 160
SP - 1
EP - 6
JO - Applied Thermal Engineering
JF - Applied Thermal Engineering
M1 - 114094
ER -