基于可重构petri网与贝叶斯推理的分布式发电系统协调优化控制研究

项目名称： 基于可重构petri网与贝叶斯推理的分布式发电系统协调优化控制研究

项目编号： No.51307128

项目类型： 青年科学基金项目

立项/批准年度： 2014

项目学科： 电工技术

项目作者： 陆宁

作者单位： 武汉理工大学

项目金额： 25万元

中文摘要： 可再生能源具有资源潜力大、对环境影响小并可永续利用的特点，但同时都具有不可控制和间歇随机的特点，要大规模开发利用可再生能源，必须采取技术措施解决可再生能源发电的不连续性与用电需求连续性之间的问题。由此，传统的调度运行控制中考虑发电用电两者的即产即销的平衡，现在转为发电、用电、储能三者平衡的模式。本研究拟从分布式能源自身的特点出发，考虑不确定随机因素存在，拟用Petri网描述分布式发电系统的能量分布状态以及动态行为，并进行协调优化控制。主要解决的关键问题：1电源、负载、储能各对象的动态行为分析以及Petri网描述；2贝叶斯推理在变迁触发机制中的应用；3.可重构Petri网在动态分布式系统建模中的应用以及协调优化控制的实现。研究意义：结合可再生能源发电特点，丰富和发展了分布式微网调度的理论方法，具有一定理论价值；为电力系统调度的工作提供了新技术，具有较大的应用价值。

中文关键词： 可重构Petri网；可再生能源；分布式能源；协调控制；Stateflow

英文摘要： Renewable energy resource has minor impact on the environment and also has the characteristics of sustainable use, but at the same time it has uncontrollable and intermittent random characteristics. To realize large-scale development and utilization with renewable energy ,technical measures must be taken to solve the problem of discontinuity renewable energy power generation and the continuity for the electricity demand. The operation of traditional power generation between electricity demand and sales has changed to the balance model of power generation, electricity demand and energy storage. This study intends to start from the characteristics of distributed energy with the considering of uncertain random factors exist, and to describe the energy distribution and dynamic behavior by Petri net, then to implement the coordinated control . The key problem: 1 To analysis and describe dynamic behavior of power supply, load, energy storage by Petri network; 2 The trigger mechanism of Bayesian inference in change; 3 Reconfigurable Petri nets in dynamic distributed system modeling and optimal coordination control. The significance of the study: it enriches the theory of distributed system scheduling with the combination of renewable energy power generation characteristic which has a certain theoretical value; it pr

英文关键词： reconfigurable Petri-net；renewable energy；distributed generation；coordinated control；Stateflow