Standardized Communication-based Diverse Structure Model Predictive Controller with Demand Response for Frequency Regulation in Microgrids

Interconnected microgrids offer numerous benefits, such as increased power system reliability, security, and optimized operation. To maintain the integrity of power system dynamics in two area interconnected microgrids (TAIμG), load frequency control in combination with demand response (DR) strategies have been studied in the literature. However, the effectiveness of the control scheme depends on the design and tuning of a robust controller. To address this issue, this paper proposes a diverse structure model predictive controller with demand response (DR) scheme tuned using a novel quasi-oppositional African vulture's optimization technique (QOAVOT) to achieve faster convergence rates in a highly dynamic TAIμG system. As TAIμGs encompass both physical electrical systems and cyber systems spread over a large geographical area, communication delays due to control and measurement signal exchanges significantly impact the dynamic performance of the control scheme. Previous works have generally ignored these communication delays or considered them as a constant computed through estimation models. To fill this research gap, this paper proposes an IEC 61850 standard based communication model for implementing the proposed control scheme to compute realistic communication delays in TAIμGs. For this, an integrated network emulation platform, comprising emulated IEC 61850 communication models and a network simulator, is developed. Detailed performance analysis of the proposed control scheme under different communication technologies is presented, and a strategic delay compensator is analyzed to reduce the impact of communication delay. Furthermore, stability analysis of the proposed controller is carried incorporating communication delays.