英文_IRENA_面向极端天气的可再生能源优质基础设施_40页_12mb

Quality Infrastructure Summary for Renewables Facing Extreme Weather

Introduction and Context

• Extreme weather events, driven by climate change, threaten the structural integrity and reliability of renewable energy systems, increasing risks to PV and wind installations.
• These events cause significant economic and operational impacts, with costs rising as renewable energy penetration grows.
• Robust quality infrastructure (QI) is recommended as a cornerstone for resilience, encompassing standards, testing, certification, and accreditation to ensure safety and performance throughout the lifecycle.
• Global trends, such as the nearly doubled frequency of major disasters since 2000, highlight the urgent need for adaptive strategies.

Key Findings from Report

• Risk Assessment: Utilize historical and predictive data from meteorology and climate models to identify vulnerabilities, including specific factors like temperature, humidity, wind, and ice.
• Mitigation Measures: Implement a multi-layered approach, combining site selection, equipment design, operational protocols, and insurance to reduce risks; international standards from IEC and national guidelines are vital.
• Cost-Benefit Analysis: Extensive mitigation measures generally improve internal rate of return (IRR) and reduce long-term costs, outweighing initial investments.
• Financial Implications: Yield losses, component failures, and downtime due to extreme events can significantly impact project profitability; proactive measures are economically attractive.

Recommendations

• Project Developers: Focus on comprehensive risk assessment and integrate QI into design, construction, and operations.
• Standardization Bodies: Elevate standards to address emerging climate risks and ensure resilience.
• Policymakers: Strengthen national QI systems, incorporate weather-related standards into procurement, and support R&D.
• Other Stakeholders: Manufacturers should innovate for extreme conditions, investors should factor risks into financial models, and collaboration is key for effective deployment.