Open AccessImpact of battery energy storage, controllable load and network reconfiguration on contemporary distribution network under uncertain environment
Author(s) -
Sharma Sachin,
Niazi Khaleequr Rehman,
Verma Kusum,
Rawat Tanuj
Publication year - 2020
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2020.0369
Subject(s) - control reconfiguration , renewable energy , computer science , energy storage , battery (electricity) , reliability engineering , constraint (computer aided design) , distributed computing , engineering , power (physics) , electrical engineering , embedded system , physics , quantum mechanics , mechanical engineering
The design of future distribution systems involves the application of flexible technologies such as renewable‐based distributed generations (DGs), battery energy storage systems (BESSs), demand response for controllable load management and distribution network reconfiguration for achieving assets optimisation and for improving the efficiency of the distribution systems. The renewable‐based DGs are the source of uncertainty that can be overcome by the proper modelling of renewable resources and application of energy storage devices. However, the coordination of these flexible technologies is essential to avoid counterproductive results and to extract maximum possible benefits from these technologies. This work, therefore, aims to study the coordinated impact of controllable load with renewable‐based DGs, BESSs and network reconfiguration for improving the performance of distribution systems. The coordination of these technologies is a very complex optimisation problem due to various constraints associated with charging and discharging of BESSs, complex nature of controllable load management and feeder current limits of distribution network. In this study, an improved water evaporation optimisation algorithm is developed to solve this multi‐constraint complex optimisation problem to minimise the network loss and voltage profile improvement for distribution system. The results show that this coordinated operational problem significantly improves the performance of distribution systems.