An Adaptive D-FACTS for Power Quality Enhancement in an Isolated Microgrid

Abstract

Technologies of microgrids (MGs) help power grid evolve into one that is more efficient, less polluting, reduced losses, and more flexible to provide energy consumers' want and need. Because of the nature of various renewable energy sources (RESs) integrated into the MGs such as variability and inability to accurately predict and control, different technical problems are created. Power quality is one of the most important issues to be addressed, especially harmonic distortion and voltage stabilization. Many devices have been proposed to improve these two aspects that may result from loads nonlinearity and sources uncertainty. In this study, an adaptive switched filter compensator (ASFC) with developed proportionalintegral-derivative (PID) controller is proposed to improve the overall dynamic performance of the MGs. The PID's controller gains are optimally tuned via the application of grasshopper's optimization algorithm (GOA) to act adaptively with self-tuning as the operating conditions may subject to change during MG operation. Different case studies are proposed to reveal the robustness of the presented ASFC on harmonic mitigation, dynamic voltage stabilization, reactive power compensation and power factor improvement considering the features of RESs such as variations of wind speed, solar PV irradiation and temporary fault conditions. A distribution synchronous static compensator (D-STATCOM), as one of the most popular D-FACTS, with optimal tuned PID controller by using the GOA is also proposed. To validate both the proposed ASFC topology and the modified D-STATCOM, comparative studies including what has been published in literature are examined by using MATLAB/Simulink platform. The results advocate the effectiveness, robustness and latency of the proposed devices. INDEX TERMS Microgrids (MGs), adaptive switched filter capacitor (ASFC), distribution synchronous static compensator (D-STATCOM), distribution flexible alternative current transmission system (D-FACTS), power quality (PQ), grasshopper's optimization algorithm (GOA), PID Controller.

High-Level Penetration of Renewable Energy Sources Into Grid Utility: Challenges and Solutions

“…As reported in [149], harmonics compensation and fundamental load component extraction are achieved with a new least mean mixed norm (LMMN) control strategy. The flexible AC transmission systems (FACTS) devices play an important role to improve different aspects of power quality, like harmonics, power factor, oscillations in electrical quantities, voltage dip, in highly renewable penetrated systems [152]- [154]. Various FACTS devices, such thyristorcontrolled series capacitor (TCSC), static VAR compensator (SVC), and static synchronous compensator (STATCOM), are presented in the literature to handle harmonics issues of renewable energy system.…”

“…Power quality improvement of PV and DFIG systems is presented [175], [176] with superconducting magnetic energy storage (SMES [152], [155] These methods improve dynamic voltage stabilization Further improvement is possible by systematic D-FACTS design Harmonics mitigation is achieved and power factor is improved SSFC [154] Harmonics mitigation and voltage stabilization Losses reduction and power factor improvement STATCOM [156]- [158] Point of common coupling harmonic mitigation…”

Cyber-Security Constrained Placement of FACTS Devices in Power Networks From a Novel Topological Perspective

“…The optimal placement of FACTS devices is a common yet important research topic in literature and has been investigated via various approaches. These include (1) conventional methods (such as indexing [11], controlling [12], residue analysis [13], numerical optimization [14], sensitivity [15], and eigenvalue [16]), (2) optimization methods (such as optimal power flow [17], linear programming [18], dynamic programming [19], mixed integer programming [20], stochastic load flow [21], and adaptive control law [22]), (3) artificial intelligence techniques (such as Monte Carlo simulation [23], artificial bee colony [24], artificial neural network [25], symbiotic organism search algorithm [26], fuzzy systems [27], and particle swarm optimization [28]), (4) hybrid techniques (such as hybrid of bee colony and neural networks [29], hybrid of genetic algorithm and fuzzy systems [30], mixed optimal power flow and particle swarm optimization [31], mixed bee colony and optimal power flow [32], and hybrid of fuzzy systems and Lyapunov theory [33]), and (5) other approaches (such as energy approach [34], active control [35], graph search algorithms [36], whale optimization [37], Gray Wolf optimizer [38], salp swarm optimizer [39], Grasshooper optimization [40], ant lion optimization [41], and spider monkey optimization [42]).…”

Distributed FACTS for Power System Transient Stability Control

“…This architecture allows huge savings in terms of voltage insulation and on-site installation. Recent applications of D-FACTS have been studied for voltage control and stabilization of microgrids [21] and distribution systems [22].…”