Wind farm topology-finding algorithm considering performance, costs, and environmental impacts

Area of Science:

• Renewable Energy Systems
• Environmental Engineering
• Operations Research

Background:

• Wind farm investment decisions face complex performance, economic, and environmental challenges.
• Optimizing installed capacity (topology) is crucial for maximizing profitability and operational efficiency.
• Existing algorithms require enhancement to integrate economic and environmental factors comprehensively.

Purpose of the Study:

• To determine the optimal wind farm topology for maximum performance and profit.
• To integrate global warming potential (GWP) as a key environmental constraint.
• To provide a robust methodology for wind farm investment assessment.

Main Methods:

• Utilized a topology-finding algorithm incorporating multi-state systems (MSS) and universal generating functions (UGF).
• Calculated wind and load charge functions to model system performance and availability.
• Incorporated economic analysis, including net present value (NPV) and levelized cost of energy (LCOE).

Main Results:

• Identified optimal wind farm topologies that maximize availability and profitability.
• Quantified the global warming potential (GWP) for various configurations.
• Economic assessments revealed the financial viability of the proposed optimal topologies.

Conclusions:

• The proposed method effectively balances economic and environmental factors in wind farm design.
• Optimal topology selection is critical for enhancing wind farm sustainability and investment returns.
• This approach supports informed decision-making for wind farm investors and developers.