Are multi microgrid scheduling optimization and hydrogen energy storage configuration applications important?

Finally, microgrids are the mainstream of future power system construction and capacity allocation and scheduling issues are important directions for power system research. This paper lays the foundation for future research on multi microgrid scheduling optimization and hydrogen energy storage configuration applications. 2. Model building 2.1.

What are the components of a microgrid?

Each microgrid is composed of four parts: wind and solar power generation system, hydrogen energy storage system (including electrolytic cells, hydrogen storage tanks, and fuel cells), shared energy storage system, and power load. Fig. 1. System structure diagram. The wind and solar power generation system is the main energy source of microgrids.

Should power transmission be allowed between microgrids?

If power transmission is allowed between microgrids, simultaneously configuring hydrogen energy storage and electrochemical energy storage is the most cost-effective and environmentally friendly solution. The investment price of hydrogen energy storage is the most important factor affecting the allocation of energy storage capacity.

How do microgrids maintain system balance?

Comparing the output diagrams of the four microgrids, it can be found that MG1 and MG2 mainly maintain system balance through electrochemical energy storage charging and discharging, while MG3 and MG4 maintain system balance more through hydrogen energy storage and power transmission between microgrids.

What are the evaluation metrics for Microgrid optimization?

The evaluation metrics encompass life cycle emissions, the optimal microgrid cost, and customer billing. Simulation results demonstrate the superiority of the proposed DA in achieving the lowest microgrid cost and customer bill, outperforming the other optimization methods.

Which optimization techniques are used to optimize a microgrid?

The study conducts a thorough comparative analysis involving four optimization techniques: Dandelion Algorithm (DA), Particle Swarm Optimization (PSO), Nature-Inspired Optimization Algorithm (NOA), and Knowledge Optimization Algorithm (KOA). The evaluation metrics encompass life cycle emissions, the optimal microgrid cost, and customer billing.