考虑用户利益的柔性负荷优化控制算法

Optimal Control Algorithm of Flexible Load Considering User Interests

为解决电网峰谷差持续扩大带来的影响,从用户侧角度出发,针对空调房间、电热水器和电动汽车分别提出了柔性负荷优化控制算法。该算法基于分时电价,同时考虑用户经济效益和舒适度进行双目标优化控制,并通过智能用户终端实现。在算法中,改进了传统的空调房间和热水器负荷模型,将复杂的多变量强耦合过程解耦为多个独立的单变量子过程,并采用参数回归获取模型参数,减少算法中的随机变量。其次,将电动汽车纳入优化控制,分别研究了单向充电电动汽车(grid to vehicle,G2V)和双向供电电动汽车(vehicle to grid,V2G)的优化算法。采用粒子群算法分别求解优化结果。基于MATLAB的仿真结果验证了所提算法在经济利益、用户体验和电网削峰填谷方面上的优势。

To solve the problem of rising peak-valley load difference, the paper proposes an optimized flexible load control algorithm for air-conditioned room, electric water heater, and electric vehicle respectively from the view of customers. Based on time-of-use price, the algorithm completes the dual-objective optimization control considering constraints of economic benefits and user comfort, and can be realized through intelligent user terminals. In the algorithm, traditional load models for air-conditioner room and water- heater are improved, the multivariable thermodynamic process is separated into several independent univariate sub-processes, the model parameters are obtained by parametric regression from history data, therefore, random parameters are reduced in the algorithm. Opti- mized control considering two main kinds of electric vehicles, grid to vehicle （G2V）and vehicle to grid （V2G）by the algorithm are also studied; particle swarm optimization（PSO） algorithm is used to solve the optimal results. Finally, simulation result on MATLAB shows the advantage of the algorithm at economic benefits, user experience, and load shifting effect.