A Novel Hybrid-HHOPSO Algorithm Based Optimal Compensators of Four-Layer Cascaded Control for a New Structurally Modified AC Microgrid

Abstract

This paper proposes a new modified architecture for AC microgrid consisting of multiple grid-supporting master units (MUs) and multiple grid-feeding slave units (SUs). In this study, a coordinated four-layer hierarchal control (HC) approach is applied to the proposed structure for allowing the MUs, SUs and loads to be easily integrated as a microgrid and operated in both grid-integrated and standalone operation mode. The proposed structure of the AC microgrid enhances the system redundancy to prevent the single point of failure of MU and has more stability, efficiency, flexibility and reliability than the conventional structures. Furthermore, optimal design guidelines, based on a new hybrid Harries hawks and particle swarm optimization algorithm (H-HHOPSO) with the cooperation of different types of proposed multi-objective functions, are presented to fulfill the study objectives. The optimization constraints/objectives are employed for optimal parameters selection of HC controllers to improve the power quality, enhance dynamic and steady-state performance and guarantee a seamless transition between operation modes. To accomplish this work, the newly modified structure is modeled, constructed in MATLAB/SIMULINK and tested under the variations of generations and loads. This structure is also examined when the fault occurs at any one of the MUs and during the connecting and disconnecting of utility grid. This testing is to verify its flexibility and reliability, and confirm the effectiveness and robustness of the proposed optimal controllers. Additionally, the experimental work is carried out using the hardware-in-the-loop real-time emulation to prove the optimal controllers' feasibility. Finally, the experimental and simulation results are compared.

Keywords

• Distributed generation
• heuristic algorithm
• hierarchal control
• microgrids
• optimization techniques
• renewable energy resources