论文标题
考虑到多时间尺度动力学
Tertiary Regulation of Cascaded Run-of-the-River Hydropower in the Islanded Renewable Power System Considering Multi-Timescale Dynamics
论文作者
论文摘要
为了使农村地区的电源供应并利用清洁能源,全世界建造了由级联的水力发电和挥发性能源(例如PV和Wind)组成的完全可再生能源系统。在岛化操作模式下,主要和次要频率控制,即水力调节和自动生成控制(AGC),负责频率稳定性。但是,由于河流水电和河流动态限制的储水容量有限,而没有级联植物之间的协调,因此具有固定参与因子的传统AGC无法完全利用级联水力发电的可调性。当发生挥发性能量和负载之间的不平衡时,可以不可避免地脱落负载。为了解决这个问题,本文通过共同考虑电力系统动力学和河流动力学,并提出了一种协调的第三级控制方法。电力系统和河流动力学的时间尺度大不相同。为了统一多时间尺度动力学以建立一个模型预测控制器,以协调级联的植物,在一个时间间隔内,AGC参数与涡轮机放电之间的关系近似于基于数据的二阶多项式替代模型。级联的植物通过以恢复的方式优化AGC参与因子来协调,并最大程度地减少负荷脱落。在现场收集的实时PV数据的现实生活系统模拟显示,在PV波动率下,提出的方法大大降低了负载损失。
To enable power supply in rural areas and to exploit clean energy, fully renewable power systems consisting of cascaded run-of-the-river hydropower and volatile energies such as pv and wind are built around the world. In islanded operation mode, the primary and secondary frequency control, i.e., hydro governors and automatic generation control (AGC), are responsible for the frequency stability. However, due to limited water storage capacity of run-of-the-river hydropower and river dynamics constraints, without coordination between the cascaded plants, the traditional AGC with fixed participation factors cannot fully exploit the adjustability of cascaded hydropower. When imbalances between the volatile energy and load occur, load shedding can be inevitable. To address this issue, this paper proposes a coordinated tertiary control approach by jointly considering power system dynamics and the river dynamics that couples the cascaded hydropower plants. The timescales of the power system and river dynamics are very different. To unify the multi-timescale dynamics to establish a model predictive controller that coordinates the cascaded plants, the relation between AGC parameters and turbine discharge over a time interval is approximated by a data-based second-order polynomial surrogate model. The cascaded plants are coordinated by optimising AGC participation factors in a receding-horizon manner, and load shedding is minimised. Simulation of a real-life system with real-time pv data collected on site shows the proposed method significantly reduces load loss under pv volatility.