Operation optimisation of direct current microgrids toward stability and economy: a model-data co-driven framework.

Area of Science:

• Electrical Engineering
• Power Systems
• Optimization

Background:

• Direct current (DC) microgrids are crucial for clean energy integration.
• Microgrid stability is often compromised by economic optimization, especially during faults.
• Balancing stability and economy in DC microgrids remains a significant challenge.

Purpose of the Study:

• To develop a stability-constrained operation optimization for islanded DC microgrids.
• To ensure that economic objectives do not compromise system stability.
• To propose an efficient and reliable optimization method.

Main Methods:

• Formulation of a nonlinear optimization model for stability-constrained operation.
• Development of a model-data co-driven solution algorithm.
• Integration of local convex approximations and stability evaluation for efficiency.

Main Results:

• The proposed method strictly guarantees microgrid stability requirements.
• The method demonstrates high efficiency, with solution times in seconds.
• It is robust against prediction errors and avoids stability constraint violations.

Conclusions:

• Stability-constrained operation optimization effectively balances economy and stability in DC microgrids.
• The model-data driven approach offers a computationally efficient and reliable solution.
• This method enhances the practical implementation of stable and economical DC microgrids.