高比例新能源接入下电力系统负荷调峰分配方法  

作　　者：王炯[1] 郑旭[1] 陈秋寒 黄敏[1] 

机构地区：[1]国网无锡供电公司,江苏无锡214000

出　　处：《中国能源》2024年第12期68-77,共10页Energy of China

基　　金：国网无锡供电公司营销服务中心2024年负控专项数据治理服务(编号:B21030245UE2)

摘　　要：由于新能源发电具有随机性和波动性,因此在大规模接入电网时,会对电力系统的稳定性造成挑战。传统调峰分配方法受限于仅考虑少数约束条件,如负荷平衡或运行成本,而忽视了新能源发电的复杂性和波动性,导致在新能源发电大幅度波动时,难以灵活应对,不能实时调整。对此,本研究设计了一种新的电力系统负荷调峰分配方法。该方法旨在通过合理的调度和分配,确保电网在新能源发电高度不确定的环境中,仍能维持安全稳定的运行状态。首先,根据高比例新能源接入后的电力系统特性,构建以最小化系统损耗为目标的目标函数,同时设定了多重约束条件,包括电力系统输出功率与负荷间的精确平衡、维持充足的备用容量、合理安排机组启停时间,及控制每日发电量的合理分配,这些约束条件共同对构建的目标函数进行制约。本文针对目标函数及其约束条件,通过灰狼算法进行寻优,以寻找最佳的调峰分配方案。最后,通过调控收敛因子并引入动态权重对灰狼算法进一步优化,以更好地适应新能源发电的波动性和不确定性。实验结果表明,该方法在提升电力系统稳定性、优化资源配置方面取得了显著成效。在连续24小时的测试周期内,该方法确保了调峰裕度值稳定在1.9以上,新能源消纳率保持在88%以上,充分证明了该方法在实际应用中的优越性和可靠性。New energy,due to its randomness and volatility,poses a challenge to the stability of the power system when connected to the grid on a large scale.The traditional peak shaving allocation method is limited by considering only a few constraints,such as load balancing or operating costs,while ignoring the complexity and volatility of new energy generation.This makes it difficult to flexibly respond and adjust in real-time when there are significant fluctuations in new energy generation.In response to this,this study proposes an innovative method for load regulation and allocation in the power system.This method aims to ensure the safe and stable operation of the power grid in a highly uncertain environment for new energy generation through reasonable scheduling and allocation.Firstly,based on the characteristics of the power system after the high proportion of new energy integration,an objective function is constructed with the goal of minimizing system losses.Multiple constraints are set,including precise balance between power output and load,maintaining sufficient reserve capacity,arranging unit start and stop times reasonably,and controlling the reasonable allocation of daily power generation.These constraints collectively constrain the constructed objective function.Then,based on the objective function and its constraints,the grey wolf algorithm is used for optimization to find the optimal peak shaving allocation scheme.Finally,by adjusting the convergence factor and introducing dynamic weights,the grey wolf algorithm is further optimized to better adapt to the volatility and uncertainty of new energy generation.The experimental results show that this method has achieved significant results in improving the stability of the power system and optimizing resource allocation.During a continuous 24-hour testing period,this method ensured that the peak shaving margin value remained stable at 1.9 or above,and the new energy consumption rate remained above 88%,fully demonstrating its superiority and reliability in pract

关 键 词：高比例新能源接入 电力系统 负荷调峰分配 目标函数 灰狼算法 

分 类 号：TM73[电气工程—电力系统及自动化]