Droop Method Development for Microgrids Control Considering Higher Order Sliding Mode Control Approach and Feeder Impedance Variation

Abstract

Due to the growing power demands in microgrids (MGs), the necessity for parallel production achieved from distributed generations (DGs) to supply the load required by customers has been increased. Since the DGs have to procure the demand in parallel mode, they are faced with several technical and economic challenges, such as preventing DGs overloading and not losing network stability considering feeder impedance variation. This paper presents a method that upgrades the droop controller based on sliding mode approach, so that DGs are able to prepare a suitable reactive power sharing without error even in more complex MGs. In the proposed strategy, the third-order sliding mode controller significantly reduces the V-Q error and increases the accuracy in adjusting the voltage at the DG output terminals. Various case studies conducted out in this paper validate the truthfulness of the proposed method, considering the stability analysis using Lyapunov function. Finally, by comparing the control parameters of the proposed technique with existing methods, the superiority, simplicity and effectiveness of the 3rd order sliding mode control (SMC) method are determined.

Spatial‐temporal learning structure for short‐term load forecasting

“…In the reconstructed power systems, the power quality and reliability concern have been increased in recent years due to the emergence of new concepts such as microgrids, smart grids [1]. Hence, power systems infrastructure has been reformed and the problems have been reshaped [2].…”

Robust Errorless-Control-Targeted Technique Based on MPC for Microgrid with Uncertain Electric Vehicle Energy Storage Systems

“…With reference to [21][22][23][24][25], to solve the uncertainty problem arising from the droop coefficients, two methods can be potentially adopted, that is, adaptive droop coefficients and coefficient elimination. In [21], the fuzzy logic-based and model reference-based adaptive droop coefficient design methods are presented to adjust the adaptability of the droop controllers, improving the transient response of the system.…”

“…In [21], the fuzzy logic-based and model reference-based adaptive droop coefficient design methods are presented to adjust the adaptability of the droop controllers, improving the transient response of the system. Reference [22] introduces a method that upgrades the droop coefficients based on a sliding mode strategy to optimize the power-sharing operations. In [23], for the sake of high performance, a stability-constrained adaptive droop approach is proposed for autonomous power-sharing of the grid.…”

State-Space Modeling and Analysis for an Inverter-Based Intelligent Microgrid under Parametric Uncertainty

“…However, the authors did not consider the capacitor voltage variation of the load itself. The authors of [22], based on droop control, designed a sliding mode control method to overcome the difference caused by feedback line impedance, reduce the error of voltage and reactive power, and improve the accuracy of data adjustment. In [23], the authors proposed that the stabilization algorithm was bound to deal with a class of boundless uncertainties, but the algorithm was too simple and not applicable to various types of uncertainties.…”