Co-Optimization Operation of Distribution Network-Containing Shared Energy Storage Multi-Microgrids Based on...

Area of Science:

• Electrical Engineering
• Energy Systems
• Optimization Theory

Background:

• The global push for carbon peaking and carbon neutrality necessitates efficient integration of renewable energy sources.
• Coordinated operation of distribution networks and microgrids is crucial for accommodating fluctuating renewable energy and ensuring grid stability.

Purpose of the Study:

• To propose a novel collaborative optimization method for distribution networks and multi-microgrids incorporating shared energy storage.
• To enhance renewable energy accommodation and system operational stability under carbon reduction goals.

Main Methods:

• A two-stage game-theoretic approach is employed, modeling the system as a leader-follower game.
• The first stage optimizes shared energy storage configuration using multi-objective optimization.
• The second stage utilizes a nested genetic algorithm and solver to determine optimal energy trading prices and operational strategies.

Main Results:

• The proposed method effectively determines electricity purchase and sale prices, minimizing operational costs across the distribution network, microgrids, and shared energy storage.
• An improved Shapley value method ensures equitable cost allocation and benefit distribution.
• Significant reductions in required energy storage capacity (44.89%) and power limits (37.23%) were achieved.

Conclusions:

• The collaborative optimization framework based on multi-body game theory offers an effective solution for integrating renewable energy in distribution networks and microgrids.
• The method enhances economic efficiency and promotes fair benefit sharing among stakeholders.
• The proposed approach optimizes shared energy storage utilization, leading to substantial resource savings.