Water Cycle Algorithm Based Parametric Tuning of Non-Negative LMMN Control of Grid Tied Renewable Energy Systems

ABSTRACT

This work proposes a hydrological cycle-based optimisation technique for performance enhancement of a non-negative least mean mixed norm (NNLMMN) based voltage source control (VSC) for a three-phase grid integrated wind/photovoltaic (PV) system. Water cycle algorithm (WCA) is employed to tune the proportional–integral (PI) controller parameters of VSC to regulate voltage variations at DC link generated during dynamic load and wind conditions. This results in generation of a specific loss component (I_loss) of current to boost the performance of VSC. The NNLMMN control deals with system identification troubles with a non-negativity limitation in varied Gaussian noise conditions. It generates accurate I_loss to upgrade the ability of VSC to accurately extricate weight signals and the fundamental load current component in terms of improvement in DC link voltage (vdc) and total harmonic distortion. The proposed algorithm mitigates problems like voltage fluctuations besides performing operations like reactive power compensation, enhancement of power quality, load and power balancing at the point of coupling during steady-state and dynamic conditions. In conjunction with the NNLMMN algorithm, the proposed technique reduces the surplus mean square error iteratively, resulting in a compact expression of step size. The proposed topology stands out with an improved performance of vdc under wind gusts and the well-known bell-shaped irradiance curve. For relative evaluations, the performance of non-optimised PI and particle swarm optimised PI has been added to analyse the improved response of vdc and I_loss. Extensive simulation results obtained in MATLAB/Simulink are exhibited to corroborate the efficacy of the suggested system.

KEYWORDS:

• Power electronics
• Power quality
• Wind energy
• Photovoltaic systems
• Hybrid systems
• Water cycle optimisation

DISCLOSURE STATEMENT

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Masood I. Nazir

Masood Ibni Nazir graduated from GCET, Jammu in 2013 and completed his master’s from VIT, Vellore in 2016. He is pursuing his PhD from NIT Srinagar and his research domain encompasses power quality and AI techniques.

Aijaz Ahmad

Aijaz Ahmad received his BE from NIT, Srinagar, MTech and PhD from IIT Delhi. He is currently working as a professor and his research interests include power system operation, optimization and deregulation. Email: [email protected]

Ikhlaq Hussain

Ikhlaq Hussain (M’14) received his BE from University of Jammu, MTech from Jamia Millia Islamia and PhD from IIT Delhi. He is working as an assistant professor in University of Kashmir, Srinagar. He specialises in optimisation and microgrid. Email: [email protected]