Hybrid Microgrid Control with Fractional Sliding Mode
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Solution Overview
Problem
Hybrid microgrid systems face challenges in efficiently managing renewable energy sources due to fluctuations and uncertainties, leading to unsatisfactory transient and steady-state performances under parametric uncertainties and sudden changes, particularly when using linear control mechanisms.
Innovation Solution
Implementing a global sliding-mode control method with fractional-order terms (GSMCFO) that utilizes fractional calculus to improve the control of hybrid microgrid systems, enabling maximum power point tracking, robust steady-state performance, and efficient power management through a controller that monitors and adjusts power flow between renewable sources, batteries, and the grid.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If linear control mechanisms are used in hybrid microgrid systems, then the system structure is simple and easy to implement, but the transient and steady-state performances are unsatisfactory under parametric uncertainties and sudden changes
Solution Approach 1:
The patent transforms the control approach by changing the mathematical order parameter from integer (linear control) to fractional order. The fractional-order sliding mode control introduces derivative orders between 0 and 1, allowing the system to achieve both simplicity and robustness. This parameter change enables the controller to handle parametric uncertainties and sudden changes while maintaining satisfactory transient and steady-state performances.
Solution Approach 2:
The patent implements dynamic control by using sliding mode control with fractional-order terms that adapt to changing system conditions. The controller dynamically adjusts its response based on the system state, enabling it to handle sudden changes and uncertainties in renewable energy sources while maintaining stability and performance.
2Reliability
If fractional-order sliding mode control is implemented, then transient and steady-state performance are improved and robustness against parameter variations is enhanced, but the control system complexity increases
Solution Approach 1:
The patent manages complexity by carefully selecting fractional-order parameters within specific ranges (0 < α < 1) and using systematic methods to determine controller gains. This parameter optimization approach achieves robust performance while avoiding excessive complexity in implementation.
Solution Approach 2:
The sliding mode control mechanism incorporates feedback from system state variables to dynamically adjust control actions. This feedback structure enables the system to achieve robustness against parameter variations without requiring complex predictive models or extensive computational resources, as the controller responds in real-time based on actual system behavior.
Data Source
AI summary
A system and a method for controlling a hybrid microgrid system (HMS) is disclosed. The HMS includes a WTG, an RSC, a GSC, a DC-link connecting the RSC and the GSC, a PV system that outputs a DC current to the DC-link, a rechargeable battery, a bidirectional BBC connected between the DC-link and the rechargeable battery, and a controller. The method for controlling the HMS includes: preparing a definition set including a characteristic element ci and equations defining desired value ci*, a fractional order sliding mode surface ζi, and a control law element uicnt; monitoring ci(t) and the HMS status; calculating the equations based on monitored information; and controlling the HMS based on the uicnt (t) calculated and in accordance with a global sliding mode control with fractional order terms. The ζi comprises a fractional time integral and fractional time derivative of ei(t), where ei(t)=ci(t)−ci*(t). The uicnt(t) satisfiesζi(t)dζi(t)dt<0,when ζi(t)≠0.