A Robust Fractional-Order Control Scheme for PV-Penetrated Grid-Connected Microgrid

Abstract

This article presents a new cascaded control strategy to control the power flow in a renewable-energy-based microgrid operating in grid-connected mode. The microgrid model is composed of an AC utility grid interfaced with a multi-functional grid interactive converter (MF-GIC) acting as a grid-forming converter, a photovoltaic (PV) power-generation system acting as grid-feeding distributed generation unit, and various sensitive/non-sensitive customer loads. The proposed control strategy consists of a fractional order PI (FO-PI) controller to smoothly regulate the power flow between the utility grid, distributed generation unit, and the customers. The proposed controller exploits the advantages of FO (Fractional Order) calculus in improving the steady-state and dynamic performance of the renewable-energy-based microgrid under various operating conditions and during system uncertainties. To tune the control parameters of the proposed controller, a recently developed evaporation-rate-based water-cycle algorithm (ERWCA) is utilized. The performance of the proposed control strategy is tested under various operating conditions to show its efficacy over the conventional controller. The result shows that the proposed controller is effective and robust in maintaining all the system parameters within limits under all operating conditions, including system uncertainties.

Modeling and Performance Analysis of a Grid-Connected Photovoltaic System with Advanced Controller considering Varying Environmental Conditions

“…Module efficiency can be defined as the ratio of PV panel output power (P max solar module ) to input power of the PV panel (P in sun ). P in sun calculation is very important; it varies from place to place and time to time [7,8]. The calculated value below is under standard test conditions (STC), i.e., sunlight incident intensity and spectrum (1 kW/m 2 ), the temperature of the cell (25 °C), and cell area 100 * 100 mm 2 ) at AM1.5 spectrum conditions without partial shedding [7][8][9].…”

“…Perturbation and observation (P&O) tracking algorithms are better than traditional technologies. The trace starts in the wrong direction during the rapid change of radiation [8]. For the low-cost implementation of MPPT technology, the P&O algorithm is more convenient and easy to develop.…”

“…Classical techniques are slightly narrower in distinguishing between these two MPPs and locating the oscillations at peak energy. Much literature is available on the timing of operations and hybrid control techniques to give effective results [8][9][10], and detailed runs are tabulated. Murtaza et al [11] describe a new procedure for reducing hot spots using a platebound MOSFET which is a thermal shaft equipped with an infrared (FLIR) camera that was used to perceive these hot spots.…”

Comparative Analysis between Proportional-Integral and Artificial Neural Network Control of a Grid-Connected PV System

“…3 as being situated between the PV panel and the inverter. Its purpose is to increase the voltage a solar panel based on the duty cycle (α) [15].…”

Robust Control for Cancer Chemotherapy Through Time Delayed Estimation Philosophy

“…Various robust control techniques are also investigated for cancer treatment procedures, namely, adaptive control [21], sliding mode control (SMC) [22], fractional order control [23], fuzzy control [24], extended Kalman filter [25], etc. In [26], an adaptive and robust control technique is developed that can effectively modify drug delivery schedules, with the potential to reduce tumor growth.…”