基于小波包分解-概率模糊集特定策略下马尔可夫决策过程的微电网公共耦合点功率优化控制

并网运行下微电网内功率波动将通过公共耦合点(PCC)由大电网承担。为抑制不同时间尺度下的功率波动,使微电网通过PCC友好并网,基于马尔科夫决策过程(MDP)建立了反应微电网PCC不同时间尺度下交换功率大小和波动性的熵值回馈函数,以网内混合储能中超级电容器当前荷电状态(SOC)组成状态集合,决策过程通过策略迭代求解最优策略及其对应的最优熵值函数。在策略迭代中,提出一种以小波包分解-概率模糊理论为基础的特定策略集,作为当前状态到各分布式电源行动集合的映射。最后通过算例计算分析,验证了所提方法的正确性和有效性。

Microgrid PCC Power Optimal Control with Markov Decision Process Using the Specific Policy of Wavelet Packet-Probability Fuzzy Set

This paper presents a microgrid power optimal dispatch scheme by using Markov decision process (MDP). To decrease the exchange power of PCC and smooth the fluctuations in different time scales, the reward function of MDP is established as entropy. During the decision process the optimal policy and optimal entropy value are solved through policy iteration. In the policy iteration, a specific policy set of wavelet packet-probability fuzzy has been proposed. It is used as the mapping from the state set of state of charge (SOC) of energy storage to action set of charge/discharge power of hybrid energy storage. The performance of this optimal method is discussed by study cases in the end.