The field of micro-energy systems is moving towards increased integration of electric vehicles, renewable energy sources, and energy storage systems. Researchers are exploring innovative optimization and control methods to address the challenges posed by the temporal uncertainty and distribution complexity of energy interaction in these systems. A key direction is the development of multi-time scale rolling optimization scheduling methods, which can reduce the scale of preventive curtailment and improve the economy of the system. Another important area is the techno-economic optimization of hybrid energy systems, which can minimize net energy costs and maximize the utilization of excess heat. Islanding strategies for smart grids are also being investigated to enhance resilience and optimize power supply ranges. Furthermore, adaptable droop gains are being used to improve microgrid operation control and increase renewable utilization. Notable papers in this area include:
- A study on a multi-time scale rolling optimization scheduling method for micro-energy networks, which proposes a charging station aggregation model and integrates price-based and incentive-based demand response mechanisms.
- A paper on the techno-economic optimization of hybrid steam-electric energy systems, which investigates the economic viability and optimal configuration of a hybrid industrial energy system.
- A research on islanding strategy for smart grids, which establishes a mathematical model for islanding division and proposes a method to determine the maximum power supply range of distributed energy resources.
- A work on microgrid operation control with adaptable droop gains, which introduces a bilinear formulation for microgrid operation control and designs a robust minmax model predictive control scheme.
