A fuzzy-logic-based control methodology for secure operation of a microgrid in interconnected and isolated modes

Abstract

Summary Due to the global concerns regarding the climate change, integration of renewable energy sources is considered as a mitigation approach in electric power generation. This requires advanced frequency and voltage control methodologies to overcome the challenges especially in microgrids. This paper presents a 2‐step frequency and voltage control methodology for microgrids with high penetration of variable renewable energy sources. An optimized Proportional‐Integral controller is designed for a Superconductor Magnetic Energy Storage System to minimize the transient frequency deviations. In cases that the Superconductor Magnetic Energy Storage System cannot stabilize the microgrid frequency in the isolated mode, the microgrid controller activates the next level of the frequency control. In the second level, an intelligent fuzzy‐logic frequency controller is designed to adjust controllable loads, controllable generation units as well as perform load shedding. In the interconnected mode, the microgrid controller is able to activate the second level to contribute to the system frequency control. Finally, an intelligent fuzzy‐logic voltage controller, realized through distribution static synchronous compensator, is devised to control the voltage magnitude of the main feeders of the microgrid. In this work, a real‐time operation algorithm for frequency as well as voltage control is proposed and has been tested by set of simulations on a low voltage benchmark network.

Coordinated operation strategies for natural gas and power systems in presence of gas‐related flexibilities

“…To simplify the complexity of solving the MINLP problem, several algorithms such as generalised benders decomposition (GBD), outer approximation (OA), feasibility approach, OA with equality relaxation (OA/ER), generalised OA, and generalised cross decomposition are developed [14]. A number of previous works have applied deterministic and meta-heuristic solution techniques to solve MINLP problems [15][16][17][18][19][20][21][22][23][24][25]. Deterministic methods such as priority list [16], branch and bound (BB) [17], Lagrangian relaxation (LR) [18], and benders decomposition (BD) [22] have been applied to solve MINLP problems.…”

“…2.1.3 Linepack: Due to the fact that supplying gas from sources take time to reach demand centres (typically hours), linepack [34] is used to meet the rapid changes in the network. The linepack L within a pipe, calculated through combining (8), (23), (24), and considering parameter K as in (25), is shown in (26)…”

Sine cosine adopted Harris' hawks optimization for function optimization and power system frequency controller design

“…Therefore, the effectiveness of the proposed controller alongside the system parameter variations and random load fluctuations is also taken into account for further consideration. Ameli et al 20 have proposed a fuzzy based‐PID controller for voltage and frequency regulation of microgrids in interconnected and isolated modes. Patel et al 21 have suggested a fuzzy tilt‐integral‐derivative controller with filter for frequency stabilization in a hybrid microgrid system while Kumar et al 22 have addressed frequency control of isolated microgrid for stochastic wind and PV variation using autoregressive integrated moving average method.…”

Compulsory Islanding Transition Strategy Based on Fuzzy Logic Control for a Renewable Microgrid System

“…In [15][16][17][18], a unified scheme based on droop control is designed to only change the voltage reference rather than control structure so that inrush currents and voltage distortions of mode transfer can be eliminated. In [19][20][21][22], fuzzy-based parameter regulation is implemented to improve the performance of dynamic response and stability when transferring. However, before getting power supply from the MG system, loads should disconnect from the utility completely [23,24].…”