Highly-decoupled industrial energy scheduling system and method based on distributed architecture

Abstract

The invention relates to a highly-decoupled industrial energy scheduling system and method based on a distributed architecture. The initial configuration information is transmitted to other servers through the configuration server, and initialization starting deployment of other servers is completed; the data server records historical energy consumption operation data of each industrial energy consumption department; the prediction server predicts the energy consumption and the output load value of each industrial energy consumption department in the next day according to the historical energy consumption operation data to obtain the energy load demand of each industrial energy consumption department in the next day; the scheduling server generates a day-ahead scheduling instruction corresponding to each industrial energy consumption department according to the energy load demand, and sends the day-ahead scheduling instruction to the energy storage server; the energy storage server executes energy scheduling operation according to the received day-ahead scheduling instruction and schedules energy to a corresponding industrial energy use department; and the disaster recovery server monitors each server, rejects the server with the fault, and accesses the standby server corresponding to the server with the fault. And the disaster recovery capability of the system is improved.

Description

technical field [0001] The present application relates to the technical field of industrial Internet energy scheduling, and in particular, to a highly decoupled industrial energy scheduling method and system based on a distributed architecture. Background technique [0002] Through the construction of industrial energy dispatching system (a sub-category of CPS), intelligent manufacturing and intelligent energy consumption can be combined to achieve energy saving and consumption reduction, participate in friendly interaction with the power grid, and improve energy utilization efficiency. [0003] At the enterprise level, the construction of industrial energy dispatching system is a typical application of the ubiquitous power Internet of Things. Real-time monitoring, dynamic analysis, scientific prediction. The construction of an industrial energy dispatching system can effectively support the construction of the ubiquitous power Internet of Things. Through real-time regulati...

AI Technical Summary

Problems solved by technology

[0004] At the customer level, there are many problems in the energy management of industrial enterprises and industrial parks: First, the energy consumption per unit of product is 47% higher than the world's advanced level. The energy status is opaque, and scientific management and monitoring cannot be realized. Customers cannot analyze and evaluate energy consumption in detail, let alone carry out transformation and optimization.

Second, there is a lack of ways and strategies to achieve linkage among various energy supply and consumption systems, and it is impossible to truly realize the coordination and optimization of vertical source network load storage and horizontal multi-energy complementarity, and fail to realize the effective use of clean energy

The third is that the energy management systems of most industrial enterprises and parks are highly coupled in terms of design architecture, which affects the whole body, which is not conducive to the horizontal capacity expansion and vertical business expansion of the system

Fourth, most energy management systems are designed based on a single architecture, which is prone to severely degrade system performance in the face of network failures and network delays, and even cause system services to be paralyzed

[0007] The shortcomings of this solution are: first, in the whole system design process, the granularity of system splitting is not obvious enough, and there are still many couplings within each subsystem, for example, each subsystem has functions such as load data extraction, load forecasting, and system configuration. The degree of coupling is extremely high, and it is very complicated to modify the relevant functions of the energy management system; second, the design is not conducive to the expansion of the system's capacity and business logic. When the system needs to be upgraded due to performance and new business logic , will affect the whole body, and the entire distributed energy subsystem needs to be redesigned. Therefore, the disaster tolerance and scalability of the current energy dispatching system are low

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