Scholarlink

<p>The optimal solar-wind ratio (SWR) plays a critical role in shaping the cost and reliability of renewable electricity systems, yet its adaptability under climate change remains poorly understood. Here, we develop a climate-driven SWR optimization framework that couples multi-model climate projections with an integrated investment and dispatch model to quantify how future climate variability reshapes cost-optimal solar-wind configurations. We find that optimal SWRs exhibit pronounced latitudinal differences and show modest changes under climate change. Deployment pathways inherited from the historical preference scenario may diverge from optimal SWRs, leading to increases in system costs and capacity requirements. In many regions, these SWR mismatches amplify electricity supply costs far more than the cost impacts associated with climate-induced changes in renewable resources alone. Cost escalation is driven mainly by SWR mismatch rather than solely by climate-induced resource changes. These findings highlight the importance of climate-responsive and region-specific SWR optimization as a key element of resilient and economically efficient power system planning.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Navigating optimal solar-wind trade-offs under climate change

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月24日

查看全文
  • Jingyun Li,
  • Dan Tong,
  • Dongsheng Zheng,
  • Yuanyuan Lin,
  • Yuan Xu,
  • Qiang Zhang

摘要

The optimal solar-wind ratio (SWR) plays a critical role in shaping the cost and reliability of renewable electricity systems, yet its adaptability under climate change remains poorly understood. Here, we develop a climate-driven SWR optimization framework that couples multi-model climate projections with an integrated investment and dispatch model to quantify how future climate variability reshapes cost-optimal solar-wind configurations. We find that optimal SWRs exhibit pronounced latitudinal differences and show modest changes under climate change. Deployment pathways inherited from the historical preference scenario may diverge from optimal SWRs, leading to increases in system costs and capacity requirements. In many regions, these SWR mismatches amplify electricity supply costs far more than the cost impacts associated with climate-induced changes in renewable resources alone. Cost escalation is driven mainly by SWR mismatch rather than solely by climate-induced resource changes. These findings highlight the importance of climate-responsive and region-specific SWR optimization as a key element of resilient and economically efficient power system planning.