Open AccessReal‐time deterministic power flow control through dispatch of distributed energy resources
Author(s) -
Fazeli Amir,
Sumner Mark,
Johnson Mark Christopher,
Christopher Edward
Publication year - 2015
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.2015.0182
Subject(s) - computer science , electrification , robustness (evolution) , distributed computing , flexibility (engineering) , renewable energy , electricity , reinforcement learning , control (management) , power control , reliability engineering , power (physics) , engineering , electrical engineering , biochemistry , chemistry , statistics , mathematics , artificial intelligence , gene , physics , quantum mechanics
Integration of intermittent renewable resources and mass electrification of heat and transport into the existing electricity network, with limited network asset reinforcement requires incorporation of intelligence in the form of active management of flexible resources within different sections of the distribution network. A hierarchical multi‐level control framework is proposed for this purpose which incorporates the appropriate optimisation and control strategies at different levels. In particular, a novel deterministic control algorithm for controlling power flows at the community cell level has been developed and presented in this study. This algorithm incorporates robustness to communication and device failure and is easily expandable to an arbitrary number of devices. The simulation results presented in this study show that the effectiveness of the proposed control technique depends on distributed energy resources flexibility and storage capacity.