针对目前微电网监控系统存在的协同性差、缺少动态配置支持、连续动态行为和离散事件共存的混杂性等问题,该文提出了一种基于设备网络服务框架(device profile for web service,DPWS)与解释Petri网模型的新型微电网监控方法。根据微电网监控系统功能需求,建立基于DPWS的分布式微源运行状态监控模型。利用DPWS技术的自动发现、自动组网机制对微电网监控系统进行重新配置,结合事件订阅机制实现微电网系统状态的实时监控,进而分析微电网系统在运行过程中的多重状态及其转换关系。基于DPWS技术信息加密机制,解决了微电网监控系统的信息传输安全问题。运用解释Petri网建立了微电网系统控制模型,提高了微网监控设备端的自动化程度,并完成了相应的数值仿真试验。试验结果表明,该模型能较全面地描述微电网系统中的并发及混杂现象,所提出的控制策略符合微电网系统实际运行要求,为微电网系统的安全、稳定地运行提供技术依据。
Concave clouds will cause miscalculation by the power prediction model based on cloud features for distributed photovoltaic( PV) plant. The algorithm for decomposing concave cloud into convex images is proposed. Adopting minimum polygonal approximation( MPP) to demonstrate the contour of concave cloud,cloud features are described and the subdivision lines of convex decomposition for the concave clouds are determined by the centroid point scattering model and centroid angle function,which realizes the convex decomposition of concave cloud. The result of MATLAB simulation indicates that the proposed algorithm can accurately detect cloud contour corners and recognize the concave points. The proposed decomposition algorithm has advantages of less time complexity and decomposition part numbers compared to traditional algorithms. So the established model can make the convex decomposition of complex concave clouds completely and quickly,which is available for the existing prediction algorithm for the ultra-short-term power output of distributed PV system based on the cloud features.
