基于递阶预测控制的多微电网系统能量管理

Hierarchical Model Predictive Control for Energy Management Optimization of Multi-Microgrids System

微网能量优化管理是实现微网经济、高效运行的重要保障。针对由多个相互关联的微电网组成的多微电网系统,提出基于分解-协调思想的递阶预测控制能量优化管理方法。通过协调利用多微电网系统中富余/缺省的能量,实现微电网的供需平衡和供电成本最小化。首先,根据多微电网系统中能量在微电网间的分配关系,建立多微电网系统的能量流动模型和能量管理优化问题;然后,采用对偶分解方法将多微电网能量管理优化问题分解成两层结构,并引入拉格朗日协调因子,通过迭代更新协调求得最优解。最后,通过数值仿真证明文中提出的算法能有效提高新能源利用率,并实现对用户负荷需求的实时跟踪。

A hierarchical model predictive control approach based on decomposition-coordination principle is presented to optimize energy management of multi-microgrids system. Through coordinated energy usage of multi-microgrids system, balance between energy supply and demand was kept and electricity operation cost was minimized. Firstly, based on the power flow among microgrids, the description of multi-microgrids system model and the energy management optimization problem were given. Then, a dual decomposition approach was imposed to decompose the optimization problem into two layers and a Lagrangian multiplier was introduced to achieve the optimal solutions by iterating and coordination. Simulation results show the effectiveness of the proposed method, which can provide consumers demanding energy in real time and improve the renewable energy efficiency.