Summary
The renewable energy (e.g., solar photovoltaic)‐based grid‐connected microgrid (MG) with composite energy storage system (CESS) is feasible to ensure sustainable and quality power to the commercial and domestic load demands. Effective control systems provide the dynamic performance of such deployed MGs. This paper investigates the application of the finite control‐set model predictive controller (FCS‐MPC) for solar photovoltaic‐based grid‐connected MGs with composite energy storage. FCS‐MPC considers the discrete nature of interfacing (DC–AC and DC–DC) converters into the control algorithm to predict the optimal control command for reference current tracking. Compared to classical control approaches, FCS‐MPC provides a fast‐dynamic response, discards the modulation stage, and effectively handles the effects of dynamic source and load variations and nonlinear loads. The control system encapsulates a proportional–integral (PI) controller, low‐pass filter (LPF), power management algorithm (PMA) unit, and followed by the FCS‐MPC approach. The CESS unit consists of a battery and supercapacitor storage system. The efficacy of the FCS‐MPC approach is verified through the MATLAB/Simulink results. Solar photovoltaic variation due to irradiance, utility grid availability, electricity pricing, and dynamic load variations are considered in the implementation. Furthermore, real‐time simulation of the proposed method is validated using OPAL‐RT OP4510 real‐time simulator.
Summary
The paper presents a new configuration of a grid‐connected converter centering on the needs of voltage‐sensitive nonlinear loads with source current compensation and photovoltaic (PV) power injection capability. The presented system consists of a six‐switch converter, which gives dual single‐phase output. The first output is connected in shunt near the source end to inject PV‐generated power along with the supply of load current harmonics and reactive power. The second output forms a series connection near the load end to protect the voltage‐sensitive nonlinear load from supply‐side voltage variations such as sags and harmonics. The system operation is validated through MATLAB simulation and real‐time simulation using Opal‐RT (OP4510) under different dynamic conditions such as variations in supply voltage, variation in solar irradiance, and load variation which is typically encountered in a modern distribution network. The performance of the proposed multifunctional converter is found to be satisfactory in all operating conditions by meeting the desired PV power injections along with the compensation of sensitive nonlinear load terminal voltage and source current harmonic issues within the standard allowable limit specified by IEEE.
Summary
This paper presents a DC microgrid integrated series active power filter (Se‐APF) to improve the voltage profile of the utility distribution system under sag, swell, and harmonics scenario. The DC microgrid encompasses a solar photovoltaic generation unit and a composite energy storage unit (CESU). A lithium‐ion battery and supercapacitor as a CESU are envisioned in this work. Compared to conventional Se‐APF supported by the capacitor/battery storage, the integrated DC microgrid prolonged the operational features of the Se‐APF for voltage quality improvement and feeding the localized dc loads or charging the CESU occasionally from the PV generation system. Further, a power management algorithm is implemented to coordinate the operations of the sources in the DC microgrid to accomplish the above‐mentioned features. The Se‐APF and associated power converters in the DC microgrid are regulated by a nonlinear controller based on optimal switching vector‐model predictive control algorithm. The proposed control method can be used to help distribution networks with voltage fluctuations by offering much faster and more precise voltage regulation. The feasibility and effectiveness of the proposed control strategy are verified in MATLAB/Simulink platform and then validated in a real‐time simulation platform using Opal‐RT Lab real‐time simulator OP4510.
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