Short-term bulk energy storage system scheduling for load leveling in unit commitment: modeling, optimization, and...

Area of Science:

• Electrical Engineering
• Power Systems Engineering
• Operations Research

Background:

• Energy storage systems (ESSs) are crucial for enhancing power system reliability and economic efficiency.
• ESSs, particularly bulk units, enable load leveling by shifting energy consumption from peak to off-peak hours.
• Effective modeling and optimization tools are needed to integrate ESSs into power system studies.

Purpose of the Study:

• To develop a model for bulk energy storage systems (ESSs) considering technical characteristics.
• To integrate the proposed ESS model into the thermal unit commitment (UC) problem.
• To analyze the impact of ESSs on power system operation, including sensitive parameter variations.

Main Methods:

• A Mixed Integer Linear Programming (MILP) model was developed for bulk ESSs.
• The model incorporates technical limitations of thermal units and transmission network constraints.
• The proposed model was implemented and analyzed on a test system using commercial solvers like CPLEX.

Main Results:

• The study successfully modeled bulk ESSs within the unit commitment framework.
• Optimal scheduling of ESSs for load leveling demonstrated significant operational cost reductions.
• The model's effectiveness was validated on a test system, showing considerable cost savings.

Conclusions:

• The proposed MILP model provides a practical tool for incorporating bulk ESSs into large-scale power system planning.
• Effective load leveling through optimized ESS scheduling leads to substantial reductions in power system operational costs.
• The research highlights the economic benefits of integrating ESSs for improved grid management and efficiency.