Wang Zesen, Li Qi, Kong Shuaihao, Li Weiyu, Luo Jing, Huang Tianxiao
Electric Power Research Institute State Grid Jibei Electric Power Company Limited, Beijing, 100045, China.
Sci Rep. 2023 Nov 21;13(1):20376. doi: 10.1038/s41598-023-47401-4.
As renewable energy becomes increasingly dominant in the energy mix, the power system is evolving towards high proportions of renewable energy installations and power electronics-based equipment. This transition introduces significant challenges to the grid's safe and stable operation. On the one hand, renewable energy generation equipment inherently provides weak voltage support, necessitating improvements in the voltage support capacity at renewable energy grid points. This situation leads to frequent curtailments and power limitations. On the other hand, the output of renewable energy is characterized by its volatility and randomness, resulting in substantial power curtailment. The joint intelligent control and optimization technology of "renewable energy + energy storage + synchronous condenser" can effectively enhance the deliverable capacity limits of renewable energy, boost its utilization rates, and meet the demands for renewable energy transmission and consumption. Initially, the paper discusses the mechanism by which distributed synchronous condensers improve the short-circuit ratio based on the MRSCR (Multiple Renewable Energy Station Short-Circuits Ratio) index. Subsequently, with the minimum total cost of system operation as the optimization objective, a time-series production simulation optimization model is established. A corresponding optimization method, considering the joint configuration of "renewable energy + energy storage + synchronous condenser," is proposed. Finally, the effectiveness of the proposed method is verified through common calculations using BPA, SCCP, and the production simulation model, considering a real-world example involving large-scale renewable and thermal energy transmission through an AC/DC system. The study reveals that the joint intelligent control and optimization technology can enhance both the sending and absorbing capacities of renewable energy while yielding favorable economic benefits.
随着可再生能源在能源结构中日益占据主导地位，电力系统正朝着高比例可再生能源装机和基于电力电子设备的方向发展。这种转变给电网的安全稳定运行带来了重大挑战。一方面，可再生能源发电设备本身提供的电压支撑较弱，需要提高可再生能源接入点的电压支撑能力。这种情况导致频繁的限电和功率限制。另一方面，可再生能源的输出具有波动性和随机性，导致大量的功率削减。“可再生能源+储能+同步调相机”联合智能控制与优化技术能够有效提高可再生能源的可输送容量极限，提升其利用率，满足可再生能源传输和消纳的需求。本文首先基于多可再生能源站短路比（MRSCR）指标探讨了分布式同步调相机提高短路比的机理。随后，以系统运行总成本最小为优化目标，建立了时序生产模拟优化模型。提出了一种考虑“可再生能源+储能+同步调相机”联合配置的相应优化方法。最后，通过使用BPA、SCCP和生产模拟模型进行通用计算，并结合一个涉及通过交直流系统进行大规模可再生能源和热能传输的实际例子，验证了所提方法的有效性。研究表明，联合智能控制与优化技术既能提高可再生能源的送出能力，又能提高其吸纳能力，同时还能产生良好的经济效益。
