Open AccessIllustration of demand response supported co‐ordinated system performance evaluation of YSGA optimized dual stage PIFOD‐(1 + PI) controller employed with wind‐tidal‐biodiesel based independent two‐area interconnected microgrid system
Author(s) -
Latif Abdul,
Chandra Das Dulal,
Kumar Barik Amar,
Ranjan Sudhanshu
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.2019.0940
Subject(s) - control theory (sociology) , microgrid , pid controller , controller (irrigation) , particle swarm optimization , turbine , wind power , sensitivity (control systems) , electric power system , engineering , computer science , control engineering , power (physics) , renewable energy , mathematics , mathematical optimization , electronic engineering , electrical engineering , control (management) , temperature control , mechanical engineering , agronomy , physics , quantum mechanics , artificial intelligence , biology
This study proposes an earliest approach toward coordinated frequency stabilisation of wind turbine driven generator‐tidal power generation‐biodiesel driven generator‐micro‐turbine generator‐based islanded two‐area interconnected microgrid system with demand response support (DRS) mechanism. A recent bio‐inspired optimisation technique, named yellow saddle goatfish algorithm (YSGA) is employed to optimally tune the controller gains. The comparative dynamic performance of conventional proportional–integral–derivative (CPID), fractional order (FO) PID, dual‐stage PIFOD‐one plus PI [PIFOD‐(1 + PI)] controllers’ parameters optimised by several algorithmic tools such as particle swarm optimisation, firefly algorithmic tool, salp swarm technique and YSGA clearly designates the superiority of YSGA‐PIFOD‐(1 + PI) controller under different scenarios (considering the real‐time recorded wind and load data) in terms of change in frequency, tie‐line power fluctuation and objective function. Furthermore, the impact of the DRS mechanism in both areas is analysed first time under real‐time wind and load disturbances. Finally, the rigorous sensitivity analysis of YSGA‐optimised PIFOD‐(1 + PI) controller has been conducted with the variation of wind turbine driven generator gain, ±30% change in synchronising tie‐line factor, frequency bias value, microgrid system time constant and + 30% change in loading magnitude without retuning the optimal base condition values.