Integrated energy scheduling for grid-connected microgrids using battery degradation-aware optimization and...

Area of Science:

• Electrical Engineering
• Energy Systems
• Optimization Theory

Background:

• Integrating household Battery Energy Storage (BES) with Renewable Energy Sources (RES) creates regional energy clusters functioning as grid-connected microgrids (MGs).
• Increasing MG penetration necessitates efficient energy management for technical compatibility and operational constraint adherence.
• Understanding battery degradation impacts is crucial for cost-effective, long-term energy management strategies.

Purpose of the Study:

• To present a novel Grid-Connected Microgrid Energy Management (GCM-EM) model incorporating economic and technical constraints, with BES as the central flexible resource.
• To develop a model that captures real-world BES degradation dynamics (cycle aging, Depth-of-Discharge) within an optimization-based energy scheduling framework.
• To support both uncoordinated (MG-autonomous) and coordinated (DSO-integrated) scheduling schemes.

Main Methods:

• Utilized mixed-integer programming, AC optimal power flow, and rolling-horizon control for scheduling.
• Incorporated BES degradation dynamics, including cycle aging and Depth-of-Discharge (DoD) effects.
• Validated the model using simulations on a university campus grid and a 33-bus power network, and implementation in a building-level microgrid.

Main Results:

• Localized MG optimization reduced energy costs by up to 2%.
• Coordination with the Distribution System Operator (DSO) enhanced grid-level cost efficiency, with a 3% reduction in combined annual energy and degradation costs compared to models ignoring battery wear.
• The model preserved data privacy during coordination and maintained distribution grid constraint compliance.

Conclusions:

• The proposed GCM-EM model offers a comprehensive and practically validated energy management architecture for BES-integrated microgrids.
• Combining advanced scheduling with accurate degradation modeling and multi-agent coordination advances economically sustainable and technically robust distributed energy networks.
• The model effectively minimized BES operational and degradation costs in a real building-level microgrid, demonstrating practical applicability and benefits.