Procedure for acquiring short cycle data for energy monitoring and for network control in smart metering / smart grid using intelligent, distributed intermediate software

摘要

The invention relates to a method for the short-cyclic data capture of energy system data in the power supply system for energy monitoring and for system control in the smart metering/smart grid using a piece of distributed, intelligent middleware. Customary systems implement the data capture in the power supply system and implement the intelligence of the data processing on an application level, which is executed on central servers, or on the measurement and control level. A piece of middleware is at best located on the application level and then allows the communication between the applications. The middleware used in the method acts as an intelligent layer between the application level with energy monitoring and/or billing systems, for example, and the measurement and control level with a multiplicity of digital meters and actuators of the widest variety of designs, as shown in Fig. 1. In this case, the middleware allows the communication with the digital meters and actuators via interfaces in the device-specific transmission protocols. Therefore, the meter communication is totally isolated from the application level. The method is characterized in that it distributes the intelligence locally, according to need, in the information infrastructure of the "Smart Grid" as distributed middleware. Said intelligence can therefore be optimally matched to an available energy supply system topology and installed as appropriate (clustering). The distributed middleware is capable of capturing the state of the respective energy supply system cluster in short cycles (in real time), using digital meters and further sensors. It operates in a manner detached from the application level and is always active. Following the data capture, the middleware either initiates an appropriate agent-supported optimization strategy, for example for regulating the flow of energy, itself or calls the optimization via a superordinate application (App). In addition, it provides an ideal infrastructure for the migration of further software agents and middleware services. By way of example, a local optimization middleware service allows the formation of "virtual power stations" and/or "virtual households" directly on the middleware level and therefore reduces the volume of information for superordinate applications. Each intelligent node of the distributed middleware can be implemented by a low-resource system (embedded system) and designed dynamically and flexibly.