Reliability-constrained optimal scheduling of PV-based microgrids using deterministic time-series forecasting and load prioritization strategies

Abstract

This paper presents an advanced MPC-based energy scheduling framework for islanded microgrids operating under uncertain and dynamic conditions where photovoltaic (PV) generation and energy storage systems (ESS) are integrated, and load management is hierarchically prioritized. The framework employs a hybrid ARIMA and random forest forecasting model to improve day-ahead and intra-day predictions of PV generation and load demand, enabling intelligent demand response, prioritized load shedding, and adaptive storage operation. Moreover, the proposed framework incorporates time-of-use (TOU) pricing and load importance weighting to minimize operational costs while ensuring a reliable power supply for critical loads. Simulation results across four operational scenarios demonstrate that the proposed method achieves approximately 32% improvement in critical load protection, 30% reduction in total operating cost, and 33.3% decrease in total load shedding compared to conventional MPC-based approaches. The proposed approach, therefore, provides a comprehensive, dynamic, and cost-efficient solution for microgrid scheduling and can be extended to multi-microgrid cluster applications in future research.