Distributed industrial energy operation optimization platform for automatically constructing intelligent model and algorithm

A technology of operation optimization and automatic construction, applied in the information field, can solve problems such as the inability to judge the operation trend of the energy system, optimize scheduling suggestions, etc., and achieve the effect of improving development efficiency and accuracy and reducing development costs

Active Publication Date: 2021-07-16
DALIAN UNIV OF TECH
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  • Application Information

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Problems solved by technology

However, the above-mentioned platforms only provide real-time simulation functions of the system, and cannot

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  • Distributed industrial energy operation optimization platform for automatically constructing intelligent model and algorithm
  • Distributed industrial energy operation optimization platform for automatically constructing intelligent model and algorithm
  • Distributed industrial energy operation optimization platform for automatically constructing intelligent model and algorithm

Examples

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Example Embodiment

[0060] In order to better understand the technical route and implementation of the present invention, the data pretreatment of a large steel enterprise energy system in China is used as an example, and the platform's modeling end of the platform. The algorithm is described in detail with the hardware design of the edge side server embedded industrial controller. Its energy systems include a variety of energy streams such as steam, gas, electricity, such as Figure 4 Indicated. By-product gas as an important secondary energy of steel enterprises, due to its high-calorie value, low cost advantages, can replace energy (natural gas) in many links, so accurate prediction and optimization of its production-consumption-storage process Scheduling is of great significance for energy saving and emission reduction of enterprises.

[0061] (1) Construction of the model: data pretreatment, energy production - elimination - storage trend prediction and multi-energy stream optimization scheduling...

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Abstract

The invention discloses a distributed industrial energy operation optimization platform capable of automatically constructing an intelligent model and an algorithm. The platform is divided into a modeling end, a server end and an operation end. The modeling end encapsulates algorithm models such as data preprocessing, energy production-elimination-storage trend prediction and optimization scheduling decision making into visual modules oriented to different production scenes, and convenient construction of complex function models and algorithms is achieved in a module dragging mode. And the server automatically constructs sequences of training samples, production plans/manufacturing signals and the like corresponding to equipment model requirements of each edge side, interacts with the trained intelligent model through a corresponding interface, outputs a calculation result and stores the calculation result in a specified relational database. And the operation end displays the calculation result through a friendly user interface, adjusts the real-time state of the working condition through man-machine interaction and feeds back the real-time state to the cloud server, and the cloud server rapidly triggers parameter updating of each edge side model to enable the edge side model to rapidly adapt to working condition change, so that edge-cloud cooperation of the platform is realized.

Description

technical field [0001] The invention belongs to the field of information technology, relates to technologies such as data-driven modeling, multi-objective optimization, and edge-cloud collaboration, and is a distributed industrial energy operation optimization platform that automatically builds intelligent models and algorithms. The platform is divided into three parts: modeling end, server end and operation end. On the modeling side, an automated intelligent modeling framework is proposed, which encapsulates algorithm models such as data preprocessing, energy production-consumption-storage trend prediction, and optimal scheduling decisions into visualized modules for different production scenarios. This method realizes the convenient construction of complex function models and algorithms. At the same time, each module is embedded with an adaptive algorithm to dynamically optimize parameters, and can be saved as an intelligent model file compatible with multiple programming l...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06Q10/06G06Q50/06G06N20/00G06N3/04G06N3/08
CPCG06Q10/04G06Q10/067G06Q10/0637G06Q50/06G06N20/00G06N3/08G06N3/045Y02P80/10G05B2219/32301G05B19/41865G05B19/4183G05B19/41885G05B2219/25387G05B19/4188
Inventor 赵珺金锋陈龙周帆韩中洋刘洋王伟
Owner DALIAN UNIV OF TECH
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