Boundary Technology Costs for Economic Viability of Long-Duration Energy Storage Systems - Dataset

This dataset presents a representation of California's power system, encompassing existing generators and projections for the year 2050. The dataset's spatial resolution is at the state level (California), with hourly temporal resolution spanning 8760 periods. The system model considers four balancing areas (BA) nodes, a reference energy matrix developed by NREL’s Cambium [1], however without the representation of transmission lines.The dataset is compiled from multiple reliable sources to offer a comprehensive view of California's projected energy matrix in 2050. Data on system load, available generation technologies, and their installed capacities are sourced from NREL's Cambium 2022 [2]. Specific parameters such as ramp rates of power plant technologies and capacity factors are extracted from Cambium 2022 documentation [1].Fixed operation and maintenance (FO&M) costs for each generator are derived from the Regional Energy Deployment System (ReEDS) base [3], publicly available on GitHub, and supplemented by information in the 2022 Annual Technology Baseline (ATB) [4]. Fuel prices reported in the Annual Energy Outlook (AEO) 2023 [5] are incorporated in the variable operation and maintenance (VO&M) costs, and relevant investment costs associated with renewable power plants are sourced from ATB 2022.This dataset serves as a valuable resource for researchers seeking insights into the future of California's energy landscape. It provides a foundation for computational experiments and analyses, offering a detailed perspective on various aspects of the state's power generation, from technology capacities to associated costs.[1] P. Gagnon, B. Cowiestoll, and M. Schwarz, “Cambium 2022 scenario descriptions and documentation,” NREL, Tech. Rep., January 2023, NREL/TP-6A40-84916. [Online]. Available: https://nrel.gov/publications.html[2] ——. (2023) Cambium 2022 data. Accessed on May 17, 2023. [Online]. Available: https://scenarioviewer.nrel.gov[3] J. Ho, J. Becker, M. Brown, P. Brown, I. Chernyakhovskiy, S. Cohen, W. Cole, S. Corcoran, K. Eurek, W. Frazier et al., “Regional energy deployment system (ReEDS) model documentation: Version 2020,” NREL, Tech. Rep., June 2021, NREL/TP-6A20-78195. [Online]. Available: https://nrel.gov/publications.html[4] NREL. (2022) ATB electricity data 2022. Accessed on March 29, 2023. [Online]. Available: https://atb.nrel.gov/electricity/2022/data[5] U.S. Energy Information Administration. (2023, March) Annual energy outlook 2023. Accessed on July 1, 2023. [Online]. Available: https://www.eia.gov/outlooks/aeo/

本数据集呈现了加利福尼亚州电力系统的表征，涵盖现有发电设施及至2050年的预测。该数据集的空间分辨率以州级（加利福尼亚州）为单位，时间分辨率为每小时，共覆盖8760个时段。系统模型考虑了四个平衡区域（BA）节点，以及由美国国家可再生能源实验室（NREL）的Cambium项目（[1]）开发的参考能源矩阵，但未包含输电线路的表征。数据集由多个可靠来源汇编而成，旨在全面展现加利福尼亚州2050年的预测能源矩阵。系统负荷、可用发电技术和其装机容量数据源自NREL的Cambium 2022项目（[2]）。具体参数，如发电技术爬坡速率和容量系数，来自Cambium 2022项目文档（[1]）。各发电设施的固定运营维护（FO&M）成本源自区域能源部署系统（ReEDS）基准（[3]），该基准可在GitHub上公开获取，并辅以2022年年度技术基准（ATB）[4]中的信息。年度能源展望（AEO）2023（[5]）中报告的燃料价格纳入了可变运营维护（VO&M）成本，相关可再生能源发电设施的投资成本来源于ATB 2022。该数据集对于寻求洞察加利福尼亚州能源未来前景的研究者而言具有重要价值，它为计算实验和分析提供了坚实的基础，详细阐述了该州电力生成的多个方面，从技术能力到相关成本。[1] P. Gagnon, B. Cowiestoll, 和 M. Schwarz, “Cambium 2022场景描述与文档，” NREL，技术报告，2023年1月，NREL/TP-6A40-84916。[在线]。可获取：https://nrel.gov/publications.html[2] ——. （2023）Cambium 2022数据。访问时间：2023年5月17日。[在线]。可获取：https://scenarioviewer.nrel.gov[3] J. Ho, J. Becker, M. Brown, P. Brown, I. Chernyakhovskiy, S. Cohen, W. Cole, S. Corcoran, K. Eurek, W. Frazier等，“区域能源部署系统（ReEDS）模型文档：版本2020，” NREL，技术报告，2021年6月，NREL/TP-6A20-78195。[在线]。可获取：https://nrel.gov/publications.html[4] NREL. （2022）ATB电力数据2022。访问时间：2023年3月29日。[在线]。可获取：https://atb.nrel.gov/electricity/2022/data[5] 美国能源信息署。 （2023年3月）年度能源展望2023。访问时间：2023年7月1日。[在线]。可获取：https://www.eia.gov/outlooks/aeo/