Dariush Keihan Asl

Development in utilizing the energy storage system (ESS) has led to increasing flexibility in the planning of energy networks. This study presents optimal day-ahead scheduling for multi-carrier energy networks in the presence of ESS. To achieve this purpose, a new economic approach for ESS is proposed that aims to utilize for generation management in the multi-carrier networks. Also, the proposed economic approach presents a novel pricing policy that reduces the total cost of the system at each time interval. Therefore, the proposed pricing policy results in obtaining the charging and discharging pattern of ESS adaptively. To solve the multi-period optimal energy flow problem in multi-carrier energy networks, this study utilizes the well-known teaching-learning based optimization algorithm. The investigated multi-carrier energy system consists of electrical, natural gas and district heating sub-networks in which an ESS is included in the electrical sub-network. The performance of the proposed approach is validated by comparing the ESS daily charging and discharging pattern and the daily load demand curve. The results show that the proposed method could be utilized for load shedding and tracking the load demand curve more effectively.