Electricity Consumption Optimization Using Thermal and Battery Energy Storage Systems in Buildings

Energy storage system (ESS) plays a key role in peak load shaving to minimize power consumption of buildings in peak hours. This paper proposes a novel energy management unit (EMU) to define an optimal operation schedule of ESSs by employing metaheuristic and mathematical optimization approaches. The proposed EMU uses a thermal energy storage system (TESS) and a battery energy storage system (BESS) to store the energy in off-peak periods and discharge it in high load demands. We formulate the charging/discharging schedule of TESS and BESS as an optimization problem. Then, particle swarm optimization (PSO) is employed to obtain the optimal schedule due to its computational time efficiency. The mathematical approach is also applied to prove the convexity of the problem and the uniqueness of the solution. Due to the different characteristics of the building loads, this paper divides the total load into shiftable and fixed loads. Moreover, to model the building components and loads, grey-box modeling is adopted. Results show that employing a combination of TESS and BESS achieves peak load shaving while reducing 42.2% of the required BESS capacity compared with the case where the BESS is only used. In addition, the results indicate the effectiveness and robustness of the proposed algorithm.

Automated summary

This paper proposes a novel energy management unit (EMU) to define an optimal operation schedule of energy storage systems (ESS) in order to minimize power consumption of buildings in peak hours. The proposed EMU uses a thermal energy storage system (TESS) and a battery energy storage system (BESS) to store energy during off-peak periods and discharge it during high load demands. The results show that the combination of TESS and BESS achieves peak load shaving while reducing the required BESS capacity.