A heuristic ranking approach on capacity benefit margin determination using Pareto-based evolutionary programming...

Area of Science:

• Electrical Engineering
• Power Systems Analysis

Background:

• Capacity Benefit Margin (CBM) is crucial for Load-Serving Entities (LSEs) to ensure reliable generation access in interconnected systems.
• Existing methods may lack flexibility in simultaneously determining CBM for all areas while considering tie-line reliability.

Purpose of the Study:

• To introduce a novel multiobjective approach for simultaneous Capacity Benefit Margin (CBM) assessment in interconnected power systems.
• To enhance the reliability of generation access by incorporating tie-line reliability into CBM calculations.
• To provide independent system operators with a flexible tool for CBM selection.

Main Methods:

• A Pareto-based evolutionary programming (EP) technique is employed for simultaneous CBM determination across all system areas.
• A heuristic ranking index, considering Loss of Load Expectation (LOLE), is used to select CBM from the Pareto optimal front.
• Available Transfer Capability (ATC) is calculated considering both firm and nonfirm CBM transfers.

Main Results:

• The proposed method successfully determines CBM simultaneously for all areas of an interconnected system.
• Tie-line reliability and system loss of load expectation are effectively integrated into the CBM assessment.
• Numerical studies on the modified IEEE-RTS79 validate the performance and flexibility of the proposed approach.

Conclusions:

• The novel multiobjective approach offers a flexible and effective solution for CBM assessment in interconnected power systems.
• The method enhances system reliability by considering tie-line performance and LOLE.
• This technique empowers independent system operators with improved decision-making capabilities for managing transfer capabilities.