Equipment energy-saving control optimization method and system based on expert controller

Abstract

The invention discloses an equipment energy-saving control optimization method and system based on an expert controller, and the method comprises the steps: determining an equipment task target, and obtaining the real-time operation energy consumption data of equipment; according to the task target and the energy consumption data, utilizing an expert controller to obtain an equipment control scheme; and optimizing equipment control according to the control scheme. According to the scheme, the technical level of energy conservation and consumption reduction can be improved; the intelligent degree of the energy-saving technology is improved; and active prediction and judgment are carried out on equipment energy consumption deviation or faults in actual operation, optimization suggestions are provided, and support is provided for clients and operation and maintenance personnel.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of device energy saving, and more particularly to a device energy saving control optimization method and system based on an expert controller. BACKGROUND

[0002] Currently, in the process of device energy saving and consumption reduction, the biggest problem is that the energy saving professional technical level of operation and maintenance personnel is limited, so that energy saving opportunity points cannot be found in time, resources cannot be reasonably configured and optimized, and energy saving solutions cannot be quickly provided, and energy consumption data and operation trends cannot be scientifically analyzed.

[0003] Although expert knowledge can solve problems in this field to some extent, over-reliance on expert support makes energy saving and consumption reduction difficult to be implemented quickly, so that the ideal effect cannot be achieved.

[0004] Therefore, it is necessary to use rapid artificial intelligence technology to quickly find and solve problems and improve energy saving and operation and maintenance efficiency. SUMMARY

[0005] To achieve the above-mentioned purpose, the present application provides a device energy saving control optimization method and system based on an expert controller, which aims to intelligently and quickly improve device energy saving and operation and maintenance efficiency.

[0006] The specific technical solutions are as follows:

[0007] On the one hand, the present application discloses a device energy saving control optimization method based on an expert controller, comprising:

[0008] determining a device task target and obtaining real-time running energy consumption data of the device;

[0009] obtaining a device control scheme by using an expert controller according to the task target and the energy consumption data;

[0010] optimizing device control according to the control scheme.

[0011] As a preferred, a load prediction model is constructed for predicting the device task target according to device historical running data.

[0012] As a preferred, the device task target is adjusted according to requirements.

[0013] As a preferred, a device performance model is constructed for predicting the best running state of the device according to device historical running data, and obtaining real-time running energy consumption data of the device in the best running state.

[0014] As preferred, the device is modeled based on the appearance and mechanism model of the device, and the device portrait is constructed by combining the real-time running energy consumption data of the device, which is used as input to the expert controller to assist in obtaining the device control scheme.

[0015] As preferred, the Modelica simulation platform is used for modeling, and the IoT system is used to obtain the real-time running energy consumption data of the device.

[0016] As preferred, after obtaining the real-time running energy consumption data of the device, verification and cleaning are performed.

[0017] In another aspect, the present application discloses a device energy-saving control optimization system based on an expert controller, comprising,

[0018] A data processing module for receiving real-time running energy consumption data of the device, performing verification and cleaning;

[0019] A device task target setting module for setting / adjusting the task target;

[0020] A device running state recommendation module for storing and obtaining the optimal running state of the device according to the device performance model;

[0021] An expert controller module for obtaining the device control scheme according to the processed real-time running energy consumption data of the device, the device task target and the optimal running state of the device and outputting;

[0022] An execution module for controlling the device according to the control scheme.

[0023] As preferred, the device task target setting module comprises:

[0024] A load prediction unit for storing a load prediction model, predicting the device task target according to historical running data; and

[0025] A task target adjustment unit for adjusting the predicted device task target according to requirements.

[0026] According to the above technical solution, the present application provides a device energy-saving control optimization method and system based on an expert controller, which has the following advantages compared with the prior art:

[0027] 1. Improving the energy-saving and consumption-reducing technical level and the intelligent degree of energy-saving technology;

[0028] 2. Establishing an energy-saving professional knowledge system to provide support for customers and operation and maintenance personnel;

[0029] 3. Actively predicting and determining the energy consumption deviation or failure of the device in actual operation, and providing optimization suggestions.

[0030] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the written description, claims, and drawings.

[0031] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0032] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0033] Figure 1 This is a flowchart of the equipment energy-saving control optimization method based on an expert controller according to the present invention;

[0034] Figure 2 This is a control process diagram of the equipment energy-saving control optimization method based on an expert controller according to the present invention;

[0035] Figure 3 This is a control principle diagram of the expert controller of the present invention;

[0036] Figure 4 This is a structural diagram of the equipment energy-saving control optimization system based on an expert controller according to the present invention. Detailed Implementation

[0037] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0038] An expert control system is an intelligent computer program system that contains a large amount of knowledge and experience at the level of experts in a certain field. It can use the knowledge and problem-solving methods of human experts to handle problems in that field.

[0039] While expert knowledge can solve problems in this field to some extent, over-reliance on expert support can prevent energy conservation and emission reduction from being implemented quickly and effectively, thus failing to achieve the desired results.

[0040] To address this issue, this invention discloses a method and system for optimizing energy-saving control of equipment based on an expert controller. Primarily based on equipment task objectives and under optimal operating conditions, the method utilizes an expert controller to optimize the equipment's control scheme using real-time energy consumption data. This system and method are intended to solve problems in the field of energy-saving retrofitting.

[0041] The core of this invention lies in adding a modeling process for energy-saving equipment and obtaining a profile of the equipment in actual operation based on relevant operational monitoring data. This allows for the development of reasonable energy-saving diagnostic schemes and improvement suggestions based on the characteristics of the equipment and its actual operation. This application provides a more accurate energy-saving optimization method, rather than being limited to a fixed knowledge base.

[0042] It is mainly used in the field of energy-saving control or retrofitting of general equipment such as industrial boilers, motors, transformers, fans, water pumps, and compressors.

[0043] Specifically, the implementation process of the solution in this application is as follows:

[0044] Example 1

[0045] An energy-saving control optimization method for equipment based on an expert controller, such as Figure 1 As shown, it includes:

[0046] First, determine the equipment's task objectives and obtain real-time energy consumption data for equipment operation;

[0047] In this embodiment, an IoT system is used to obtain real-time energy consumption data of the device.

[0048] Preferably, the present invention constructs a load forecasting model for predicting equipment task targets based on historical equipment operating data. The equipment task targets can be adjusted as needed, such as... Figure 2 As shown.

[0049] In addition, this embodiment also constructs a device performance model to predict the optimal operating state of the device based on the device's historical operating data, and obtains the device's real-time energy consumption data under the optimal operating state.

[0050] All energy-consuming equipment has energy consumption and product output. For example, a boiler consumes natural gas to produce steam, and a refrigeration unit consumes electricity to output cold air. Different equipment has different energy consumption data indicators, and the corresponding energy-saving technologies are also different. Taking boiler data indicators as an example, they include: gas consumption per ton of steam, instantaneous maximum steam flow rate, daily operating time, annual operating days, customer's annual steam consumption, condensate recovery temperature, flue gas oxygen content, flue gas CO content, flue gas temperature, and average operating load of the equipment.

[0051] In this embodiment, the optimal operating load value of the equipment is calculated based on customer needs and the basic conditions of the equipment, and reasonable optimization suggestions are given. The deviation of energy consumption in actual operation is monitored and adjusted to achieve the best operating state of the equipment and ensure the energy-saving effect of the entire project.

[0052] In this embodiment, the load forecasting model and the equipment performance model are trained in advance based on the historical operating data of the equipment. The historical data includes raw data and summary data. The raw data is real-time data generated at a certain frequency (e.g., one data point every 5 minutes), and the summary data is data summarized from the raw data at a certain time step.

[0053] Furthermore, in industrial production environments, equipment does not operate independently. For example, a heat pump in a food processing plant is a working environment formed by the organic combination of multiple devices.

[0054] Therefore, in order to improve the prediction accuracy of the control scheme, in this embodiment, the device is modeled using the Modelica simulation platform based on the device's appearance and mechanism model, and combined with the device's real-time operating energy consumption data to construct a device profile, which is then input into the expert controller to provide auxiliary reference.

[0055] In one embodiment, the acquired energy consumption data is divided to obtain multi-dimensional data labels and assigned corresponding weights.

[0056] In constructing device profiles, the acquired energy consumption data undergoes feature analysis and unified representation processing to obtain multiple types of unified operation and maintenance data. Then, multi-dimensional data labels are established based on these various types of operation and maintenance data. Device profiles are constructed according to the weights corresponding to each label.

[0057] Second, based on the task objectives and the energy consumption data, an equipment control scheme is obtained using an expert controller;

[0058] In this embodiment, real-time energy consumption data of the device is acquired, verified, and cleaned before being input into the expert controller.

[0059] The expert controller includes:

[0060] knowledge base

[0061] The knowledge base is used to store specialized knowledge of expert systems in the field of energy conservation, including facts, feasible operations, and rules.

[0062] Inference engine

[0063] The inference engine is a program that memorizes the rules and control strategies employed, enabling the entire expert system to function logically and harmoniously. Rather than simply searching for ready-made answers, the inference engine reasones and derives conclusions based on knowledge.

[0064] interpreter

[0065] The interpreter can explain the behavior of the expert system to the user, including the correctness of the reasoning conclusions and the reasons why the system outputs other candidate solutions.

[0066] Its working principle is as follows Figure 3 As shown,

[0067] The knowledge acquisition module enables knowledge acquisition for the knowledge base. Specifically, the knowledge acquisition module learns from new instance information and automatically obtains new network weight distributions, thereby updating the knowledge base.

[0068] Furthermore, the inference engine is equipped with a rule base and a rule engine. The rule engine retrieves the corresponding rules and performs inference based on the acquired equipment operation information to obtain an energy-saving control optimization scheme for the equipment.

[0069] Third, optimize the equipment control based on the aforementioned control scheme.

[0070] This invention adds energy-saving equipment modeling and related IoT big data for operation monitoring to the original expert controller. It can provide reasonable energy-saving diagnosis solutions and improvement suggestions based on the characteristics of each device and its actual operation. The opinions obtained in this way are more accurate, rather than just based on a fixed knowledge base.

[0071] Example 2

[0072] This embodiment discloses an energy-saving control optimization system for equipment based on an expert controller, including:

[0073] The data processing module is used to receive real-time energy consumption data from the equipment, and to perform verification and cleaning.

[0074] The equipment task target setting module is used to set / adjust task targets;

[0075] The device operating status recommendation module is used to store and determine the optimal operating status of the device based on the device performance model.

[0076] The expert controller module is used to obtain and output the equipment control scheme based on the processed real-time energy consumption data of the equipment, the equipment task objectives, and the optimal operating state of the equipment.

[0077] The execution module is used to control the device according to the control scheme.

[0078] The equipment task target setting module includes:

[0079] The load forecasting unit stores load forecasting models and forecasts equipment task targets based on historical operating data; and

[0080] The task target adjustment unit is used to adjust the predicted equipment task targets according to needs.

[0081] The energy-saving optimization method disclosed in this application is mainly applied in manufacturing, industrial parks, supermarkets, agriculture, residential buildings and office buildings. The simulation platform can model the customer's energy-saving scenarios and equipment mechanisms, and then monitor the operation of the field equipment through the Internet of Things. The actual equipment profile is integrated with the expert control system to form an organic whole, thereby forming an energy-saving diagnosis method based on the expert control system.

[0082] In one embodiment, the present invention models the appearance and mechanism of the equipment using a simulation platform, acquires equipment operation data using the Internet of Things, and then establishes data indicators of the equipment using big data technology. The above technologies together form a profile of the project site and the equipment, so as to optimize energy saving of the equipment based on an expert controller.

[0083] The solution disclosed in this invention can obtain a more accurate energy-saving optimization scheme based on the simulation operation strategy, and can perform predictive maintenance on equipment, including actively predicting and judging equipment energy consumption deviation or failure, while providing optimization schemes.

[0084] The specific beneficial effects are as follows:

[0085] 1. Establish a clear equipment mechanism model and operational process indicator system;

[0086] 2. The accumulation of professional knowledge in the field of energy conservation and consumption reduction has led to continuous updates and upgrades in methodology and effectiveness during the actual solution of energy conservation and consumption reduction problems;

[0087] 3. It can effectively assist on-site energy-saving operation and maintenance personnel in carrying out daily maintenance work.

[0088] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the apparatus disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to the method section.

[0089] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for optimizing energy-saving control of equipment based on an expert controller, characterized in that, include: Define the equipment's task objectives and obtain real-time energy consumption data for equipment operation; Based on the task objectives and the energy consumption data, an equipment control scheme is obtained using an expert controller. The equipment control is optimized based on the aforementioned control scheme.

2. The equipment energy-saving control optimization method based on an expert controller according to claim 1, characterized in that, Build a load forecasting model to predict equipment task targets based on historical equipment operating data.

3. The equipment energy-saving control optimization method based on an expert controller according to claim 2, characterized in that, Adjust the equipment's task objectives according to requirements.

4. The equipment energy-saving control optimization method based on an expert controller according to claim 1, characterized in that, Build a device performance model to predict the optimal operating state of the device based on historical operating data, and obtain real-time energy consumption data of the device under the optimal operating state.

5. The equipment energy-saving control optimization method based on an expert controller according to claim 1, characterized in that, The equipment is modeled based on its appearance and mechanism, and combined with real-time energy consumption data to construct a profile of the equipment. This profile is then input into an expert controller to assist in obtaining a control scheme for the equipment.

6. The equipment energy-saving control optimization method based on an expert controller according to claim 5, characterized in that, Modelica simulation platform is used for modeling, and IoT system is used to obtain real-time energy consumption data of the device.

7. The equipment energy-saving control optimization method based on an expert controller according to claim 1, characterized in that, After obtaining real-time energy consumption data of the equipment, verification and cleaning are performed.

8. A device energy-saving control optimization system based on an expert controller, characterized in that, include, The data processing module is used to receive real-time energy consumption data from the equipment, and to perform verification and cleaning. The equipment task target setting module is used to set / adjust task targets; The device operating status recommendation module is used to store and determine the optimal operating status of the device based on the device performance model. The expert controller module is used to obtain and output the equipment control scheme based on the processed real-time energy consumption data of the equipment, the equipment task objectives, and the optimal operating state of the equipment. The execution module is used to control the equipment according to the equipment control scheme.

9. The equipment energy-saving control optimization system based on an expert controller according to claim 8, characterized in that, The equipment task target setting module includes: The load forecasting unit stores load forecasting models and forecasts equipment task targets based on historical operating data; and The task target adjustment unit is used to adjust the predicted equipment task targets according to needs.

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