Wind turbine participation in micro‐grid frequency control through self‐tuning, adaptive fuzzy droop in de‐loaded area. Issue 2 (13th May 2019)

• Record Type: Journal Article
• Authors: Abazari, Ahmadreza; Ghazavi Dozein, Mehdi; Monsef, Hassan; Wu, Bin
• Is Part Of: IET smart grid. Volume 2:Issue 2(2019)
• Page Start: 301
• Page End: 308
• Publication Date: 2019-05-13
• Subjects: power generation faults -- wind turbines -- three‐term control -- frequency response -- power generation control -- decision making -- voltage control -- power grids -- power system control -- load regulation -- distributed power generation -- optimisation -- wind power plants -- power generation reliability -- fuzzy control -- frequency control -- decentralised control; wind turbine participation -- microgrid frequency control -- adaptive fuzzy droop -- de‐loaded area -- innovative load frequency control -- islanded MG -- insufficient primary frequency response -- variable wind turbines -- frequency control problems -- de‐load area -- frequency disturbances -- proportional integral derivative droop control -- PFR; B0170N Reliability -- B0260 Optimisation techniques -- B8110C Power system control -- B8245 Wind power plants -- C1180 Optimisation techniques -- C1310 Control system analysis and synthesis methods -- C1340B Multivariable control systems -- C1340F Fuzzy control -- C3110B Voltage control -- C3110G Frequency control -- C3340H Control of electric power systems -- B8120K Distributed power generation; Smart power grids -- Periodicals; Computer science -- Periodicals; Energy industries -- Periodicals; Broadcasting -- Periodicals; 333.79110285
• DOI: 10.1049/iet-stg.2018.0095
• Languages: English
• ISSNs: 2515-2947

Abstract

Abstract : The purpose of this research is to present an innovative load frequency control in the presence of wind turbines in islanded micro‐grid (MG). As islanded MG suffers from low inertia and insufficient primary frequency response (PFR), utilising the variable wind turbines in de‐loaded area can be considered as an alternative solution to deal with frequency control problems. In this context, the de‐load area is referred to a region where wind turbines release their stored kinetic energy in rotational masses following frequency disturbances. For effective utilisation of wind turbines, a self‐tuning, adaptive fuzzy droop is proposed, whose membership function parameters are optimised through artificial bee colony algorithm based on a multi‐objective decision making process. A comparison is made between the obtained results of the self‐tuning, adaptive fuzzy droop with conventional proportional integral derivative droop control in order to assess the proposed method performance in different disturbances.