
Planning, operation and flexibility contribution of multi‐carrier energy storage systems in integrated energy systems
Author(s) -
Keihan Asl Dariush,
Hamedi Alireza,
Reza Seifi Ali
Publication year - 2020
Publication title -
iet renewable power generation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.005
H-Index - 76
eISSN - 1752-1424
pISSN - 1752-1416
DOI - 10.1049/iet-rpg.2019.0128
Subject(s) - flexibility (engineering) , computer science , energy storage , energy carrier , mathematical optimization , energy (signal processing) , demand response , scheduling (production processes) , real time computing , engineering , electrical engineering , renewable energy , electricity , power (physics) , mathematics , statistics , physics , quantum mechanics
Development in utilising 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 utilise 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 utilises the well‐known teaching‐learning based optimisation 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 utilised for load shedding and tracking the load demand curve more effectively.