Open AccessEnabling cyber‐physical demand response in smart grids via conjoint communication and controller design
Author(s) -
Mishra Swaroop Ranjan,
Korukonda Meher Preetam,
Behera Laxmidhar,
Shukla Anupam
Publication year - 2019
Publication title -
iet cyber‐physical systems: theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.308
H-Index - 7
ISSN - 2398-3396
DOI - 10.1049/iet-cps.2018.5021
Subject(s) - smart grid , computer science , cyber physical system , demand response , grid , distributed computing , controller (irrigation) , pooling , linear matrix inequality , telecommunications network , control theory (sociology) , control engineering , computer network , mathematical optimization , control (management) , engineering , electricity , electrical engineering , agronomy , biology , operating system , geometry , mathematics , artificial intelligence
This study proposes a novel user‐centric cyber‐physical framework to achieve distributed demand response (DDR) in a distribution system where local schedulers (LS) present at individual buses program both local and non‐local loads to reduce the maximum load within a sparse communication setting. A COnjoint Methodology for communication and controller DESign (COMDES) has been proposed to design the topology of the communication network while considering various cyber and physical properties of the smart grid like bandwidth, load profile and voltage controller stability margin. The designed communication network provides a unified pathway for exchanging multiple types of data among different points in the grid to consummate the advanced ideas of DDR and multi‐input multi‐output voltage control concurrently. Concepts of Lyapunov stability and linear matrix inequalities are employed to design optimisation frameworks for tuning the values of voltage controllers which, in turn, play a vital role in pooling the loads to be scheduled by the individual LS for execution. Established algorithms like earliest deadline first, least laxity first and dynamic rate priority are used to generate switching schedules for redistributed loads and achieve peak shaving. IEEE 4 bus and 14 bus models have been used to demonstrate the efficacy of the proposed framework.