Intelligent droop control and power management of active generator for ancillary services under grid instability using fuzzy logic technology. (December 2018)

• Record Type: Journal Article
• Authors: Krim, Youssef; Abbes, Dhaker; Krim, Saber; Mimouni, Mohamed Faouzi
• Is Part Of: Control engineering practice. Volume 81(2018)
• Page Start: 215
• Page End: 230
• Publication Date: 2018-12
• Subjects: Adaptive fuzzy logic droop control -- Fuzzy logic supervisor -- Active generator -- Hybrid energy storage system -- Fuzzy logic islanding detection; Automatic control -- Periodicals; 629.89
• DOI: 10.1016/j.conengprac.2018.09.013
• Languages: English
• ISSNs: 0967-0661

Abstract

Abstract: In this paper, a control and power supervisor for a flexible operation of a Renewable Distributed Generator (RDG) is introduced. This RDG consists of a combination of a wind system and a hybrid storage system made up of Batteries (BT) and Super-Capacitors (SC). RDG is associated with a load and a fluctuating grid to form an Active Generator (AG). According to the grid fluctuation, AG can operate in a grid-connected and standalone mode. The objective of this work is to investigate a novel control strategy for AG integrated into the grid in order to maintain its voltage and frequency in an allowable range and to ensure the continuity of the power supply in case of a grid fault. The structure of the proposed control strategy consists of a Fuzzy Logic Supervisor (FLS), an adaptive Fuzzy Logic Droop Control (FLDC) and a Fuzzy Logic Islanding Detection (FLID). FLS is developed to manage the power flows between the storage devices by choosing the optimal operating mode, thereby ensuring the grid stability and the continuous supply of the load by maintaining the state of charge of SC and BT at acceptable levels and to reduce stresses on BT and improve their life cycle. FLID is used to detect de standalone mode in case of grid failure. Finally, FLDC is used to control the active and reactive powers exchanged with the grid, ensuring its stability by maintaining its frequency and its voltage in optimal margins. The effectiveness of the proposed control method is validated by simulation results and compared with a generalized control technique. Highlights: A fuzzy logic supervisor is developed to manage the power flow. Detect the standalone mode in case of grid defaults. Calculates the quantity of powers to be exchanged with grid ensuring its stability. Fuzzy adaptive droop control used to control the transferred powers with the grid. Comparison based on control performance, control capability and robustness.