Research And Implementation Of Intelligent Decision Support System For Power Grid Dispatching

Because of the expending scale and complexity of power grid, the power system operator is facing with much greater challenge the duty of ensuring the system's security, stability, economy and operating quality. However, the energy management system (EMS) which serves as a major tool to support decision making can't fully meet the requirement of power system operation monitoring, its function and intelligent level need to be improved. Under this background, this paper presents a notion of constructing an intelligent decision support system for perfect function, convenient using and online self-coordinated operation. More AI techniques are used in the intelligent decision support system to provide better decision results to the operators. Based on the research of power system transient stability prediction and switching sequence generation of power grid, this paper improves the analysis function of the intelligent decision support system, realizes online coordinated operation capacity by adopting multi-agent technology. By such means the system can provide integrated decision support for the operator. This paper includes two hierarchies: the expansion of the decision-making analysis tools and the realization of system autonomous running and coordinated decision-making capacity.Considering security and stability of power grid as the primary goal, this paper presents a transient stability online prediction method based on machine learning algorithm. According to the theorem of inverting block matrix, the standard machine learning algorithm is improved, and the learning efficiency is enhanced. In order to satisfy the online transient stability prediction of multi-machine system, polymerization technology of trajectories is used to reduce the computing burden. Based on the theory of extended equal area criteria (EEAC), transient stability of power system is estimated by identifying the dynamic saddle point (DSP). According to the simulation results, the validity of proposed method is proved in respects of prediction precision and computing time.As to switching sequence generation of power grid, this paper analyses the disadvantage of production knowledge representation which has been widely used in operating command expert system, and indicates that dependent relation between inference program and rules is the main reason that restricts the adaptability of operating command expert system. To solve the above problem, firstly, this paper establishes a more flexible model of production knowledge based on Petri net; secondly, a new inference engine is brought forward, which can separate inference program from knowledge representation and improve adaptability of operating command expert system.In order to realize system autonomous running, this paper introduces multi-agent technology into the research of the intelligent decision support system. By defining power system operation states and typical events, the field model that agents live in is constructed. Based on the recognition of operation states and events, this paper granted sensation capacity to intelligent agents. By the research of multi-agent collaboration based on interactive theory and applying to the dispatching schemes auto-generation, the system can actively provide decision results for power grid operator according to current power grid operation state.