基于自适应模型预测控制的区域能源互联网两阶段协同调度

为解决系统内风光可再生能源及冷热电负荷的不确定性造成的运行困难,实现机组出力的精确化和平滑控制,提出一种基于自适应模型预测控制的两阶段区域能源互联网协同优化策略,将优化调度分为日前和日内两个阶段。在日前调度阶段,以总运行成本最小为目标建立系统经济调度机组组合模型;在日内优化阶段,采用自适应的模型预测控制方法,基于各机组的实际运行状态,以前一阶段优化调度出力为参考,对未来有限时域内系统各机组运行状态进行实时滚动修正,消除不确定性的影响,确保系统的稳定运行。算例分析验证了所提出模型及方法的有效性和可行性。

A Two-stage Coordinated Optimization Method of Regional Energy Internet Based on Adaptive Model Predictive Control

In this paper, due to operation difficulty of power system caused by uncertainty of hybrid wind and PV renewable energy and load of combined cooling heating and power, a two-stage coordinated optimization strategy based on adaptive model predictive control is proposed to realize the precision of turbine power output and smoothly control, in which the optimized dispatching is divided into day-ahead and intraday phases. In the day-ahead dispatching phase, the economic dispatching unit combination model is built with the objective of minimum operation cost. And in the intraday optimization phase, the adaptive model predictive control method is used to adjust the power output of each unit within a rolling horizon based on real operation status of each unit and pre-phase optimized dispatching power output as reference to eliminate the effect of uncertainty and to guarantee operation stability of power system. Cases analysis verifies the validity and feasibility of proposed model and method.