基于半马尔可夫控制过程的智能电网最优储能控制

针对具有多种类型业务需求的智能电网储能控制问题,在考虑业务需求和用户行为的随机分布特性,以及储能设备的充放电特性的基础上,建立了基于半马尔可夫控制过程的系统分析模型和策略优化框架。在此基础上,以电网运行的长期平均代价最小为目标,结合性能势基于样本轨道的估计,提出一种基于仿真的策略迭代优化算法。该算法有效缓解了系统大状态空间导致的维数灾问题,具有较快的收敛速度和良好的应用效果。仿真结果验证了该方法的有效性。

Optimal Energy Storage Control for Smart Grid Based on Semi-Markov Control Processes

In view of the energy storage control problems of smart grid with multi-type service demands, an analytical model and strategy optimization framework based on semi-Markov control processes are developed by capturing the characteristics of stochastic distributions of service demands, behaviors of users and charging/discharging of energy storage devices. On this basis, with the minimization of long-run average cost of the operation in smart grids as the objective, and by combining with the performance potentials estimate on sample paths, a simulation based policy iteration optimization algorithm is presented. This algorithm alleviates the curse of dimensions induced by the large system state space, and is able to find a near-optimal policy with rapid convergence rate. Simulation results demonstrate the effectiveness of the presented method. This work is supported by National Natural Science Foundation of China (No. 61374158, No. 6123303, No. 61174186) and International Science and Technology Cooperation Program of China (No. 2011DFA10440).