Summary:Energy control is a necessary means for industrial parks to achieve overall energy conservation and emission reduction. Taking Shanghai Electric Lingang Heavy Equipment Industrial Park as the object, a smart energy management and control platform has been established using good information technology, from energy supply in the park to energy consumption at enterprise terminals. While realizing online monitoring and statistics of energy data, enterprise production optimization scheduling technology and park energy supply coordination mechanism have been introduced.

key word:Industrial park; Energy management and control; Information technology; energy saving

Since entering the 21st century, China's industrialization and urbanization construction have accelerated, and industrial parks have sprung up like mushrooms after rain. At present, the construction and development of industrial parks in China have gone through a development process from scratch, from small to large, from single function to diversification, and from decentralization to centralization, playing an increasingly important role in promoting the development of the national economy. Due to the increasingly severe energy shortage and environmental pollution, energy conservation and emission reduction have become one of the key points in the construction and development of industrial parks.

Due to the large number of enterprises in industrial parks, which often have independent energy production and supply systems, their system energy conservation is not limited to a single energy production system, energy transmission system, or energy utilization system, but rather an integrated energy-saving process from energy production to terminal equipment application. To achieve this, it is necessary to build an energy monitoring platform for the entire park based on energy information monitoring and industrial Internet of Things, diagnose and analyze data, and use optimization techniques to achieve energy-saving management. The Ministry of Industry and Information Technology's document [2014] No. 30 also pointed out that "by building an energy consumption data information system and using online monitoring, energy diagnosis and other analysis methods", the ability of energy conservation supervision work can be improved.

1. Current situation of energy management in domestic industrial parks

From the perspective of energy management level, the development of energy management has gone through the following three stages:

(1) Extensive energy management only has total energy consumption data (monthly and annual bills); Lack of understanding of energy consumption data for processes and facilities; Lack of effective energy management mechanisms.

(2) Basic energy management has personnel arranged for manual meter reading, and summarizes and tables the meter reading data; There is a simple meter reading and power detection system; Lack of statistics, organization, and analysis of massive data.

(3) The energy management system analyzes and organizes energy consumption data; Allocate energy consumption and energy cost; Generate various key energy consumption indicators; Conduct demand side management based on system analysis data; Utilize energy management systems to identify waste; Utilize energy systems for performance evaluation.

At present, the energy management of domestic industrial parks is between the second and third stages: there is basic statistics of thermal meter reading data, and some enterprises have simple indicator analysis such as energy consumption classification statistics and energy consumption allocation statistics. But the main problems are: firstly, the degree of informatization is weak, and the functions of automatic meter reading, automatic recording and archiving, and automatic report generation have not been realized; Secondly, the data statistics are not precise, and there is no detailed and reasonable classification and statistics for massive data; Thirdly, the data analysis is not timely, and there is no analysis of the data, no core indicators related to production are provided, and only considered in annual statistics; The fourth issue is that energy conservation and emission reduction have not been effective, and data analysis has not been utilized to provide recommendations for energy conservation and emission reduction in enterprises; The fifth issue is that the linkage management between the park and enterprises is not tight.

2 Scheme Design

This article takes Shanghai Electric Lingang Heavy Equipment Industrial Park as the object, with the intelligent energy service system as the core, organically combining the upstream terminals of energy production and the downstream terminals of energy consumption through the industrial Internet of Things to construct an intelligent energy management and control platform for the park, as shown in Figure l. This platform includes multiple elements such as energy production, transmission, distribution, service, and users. It relies on production equipment and process flow, supported by scientific management processes, and uses intelligent information analysis and decision-making modules to implement centralized control and rapid response of energy production, transmission, and allocation. It establishes a closed-loop energy control system to optimize the interaction between energy supply and energy consumption, thereby improving equipment utilization, reducing energy consumption per unit output value in a wide area, and achieving systematic energy conservation from energy production to terminal equipment energy consumption.

The information support platform is the foundation of the intelligent energy management and control platform. It adopts an industrial gateway product that integrates multi protocol conversion technology. Through on-site instruments, sensors, actuators, and industrial control systems, various data are collected and transmitted to the data center through the park network; The data center provides massive heterogeneous data storage, mining and other technologies to provide data security for various application systems of the intelligent energy control center; At the production application level, energy management and related services in the park are completed based on data information, and various users are served through terminal interfaces. The information structure of the Intelligent Energy Management Center is shown in Figure 2.

3 Energy Control Software System

Considering the management mode of the park, it is divided into two parts: the park version and the enterprise version, and a complete system is formed through internal coordination mechanisms.

3.1 Enterprise Edition

(1) Refined Management System for Production Energy Consumption

Establish a basic unit standard processing procedure library for manufacturing enterprises to achieve electronic management of basic processing procedures. On this basis, according to the design of the technical personnel, establish the processing technology process of a certain product, and establish the processing procedures and time management of the product process flow. Then, based on the production schedule formulated by the management personnel and combined with the product process information, the production energy consumption of the enterprise is estimated.

(2) Enterprise energy consumption monitoring and statistics

Establish a monitoring system for enterprise production energy consumption and environmental energy consumption as needed, and print reports according to user needs.

(3) Production energy consumption optimization scheduling

With the aim of reducing energy consumption and minimizing fluctuations in production energy consumption, an intelligent scheduling method combining BP neural network and fuzzy judgment is adopted to optimize production scheduling. Management personnel can modify production plans based on the results of intelligent scheduling to achieve energy-saving management.

3.2 Park version

(1) Solar power generation monitoring

Monitor the power generation parameters of the solar power generation system through real-time data and display them in real-time to form records. A multiple polynomial regression model was used to establish a prediction model for solar power generation, and the operating status of the solar power generation system was determined by comparing the predicted values with the measured values.

(2) Energy consumption monitoring and statistics in the park

We have established an energy consumption monitoring system for the park and output monthly energy consumption reports according to user needs.

(3) Enterprise energy consumption summary and coordination

One is the total energy consumption control of the park. After reporting the energy consumption demand data of each enterprise, the total energy consumption demand for the next month can be obtained, from which the total energy consumption of the park can be determined. If it exceeds the energy supply capacity of the park, management personnel need to coordinate with the enterprise. The second is the estimation of energy supply margin. Based on the total energy consumption forecast for the next month and the energy supply capacity of the park, the energy consumption margin value of the park can be obtained and fed back to enterprises for reference in increasing and adjusting production. The third is the coordination of energy consumption among various enterprises. Establish an effective energy dispatch interactive platform between the park and enterprises through the internet. When electricity consumption exceeds the standard, coordinate production between enterprises, especially under the premise of experimentation, and strengthen coordination.

Introduction to Ankerui Industrial Energy Control Platform

The Ankerui Industrial Energy Control Platform adopts automation, information technology, and centralized management mode to implement centralized and flat dynamic monitoring and data management of the production, transmission, distribution, and consumption links of enterprises. It monitors the consumption of various energy sources such as electricity, water, gas, steam, and compressed air in enterprises. Through data analysis, mining, and trend analysis, it helps enterprises to conduct energy consumption statistics, month on month analysis, energy cost analysis, energy consumption prediction, and carbon emission analysis for various energy demands and consumption situations, energy quality, product energy consumption per unit, energy consumption of each process, and energy utilization of major energy consuming equipment. It provides basic data and support for enterprises to strengthen energy management, improve energy utilization efficiency, explore energy-saving potential, and energy-saving evaluation.

4.1 System Structure

4.2 Application Sites

Steel, petrochemicals, metallurgy, non-ferrous metals, mining, pharmaceuticals, cement, coal, logistics, railway, aviation industry, wood, chemical raw materials, as well as manufacturing of mechanical and electrical equipment, electrical products, and tools.

4.3 System Functions

4.3.1 Visual Display

Display the total energy consumption, conversion value, energy cost, energy consumption trend, proportion of sub item energy consumption, regional energy consumption comparison, as well as the current weather and pollution situation of the enterprise, and 3D display the energy consumption dynamics of important processes or sections of the enterprise.

4.3.2 Real time monitoring

Real time monitoring of energy usage, alarms, and other situations at various points of the enterprise. So that enterprise users can monitor the operation status of each point in real time, and at the same time, be able to quickly and effectively grasp the alarm of each point.

4.3.3 Transformer Monitoring

Display the load situation of each voltage transformer, so as to make scientific and reasonable planning for the transformer situation. By comparing and analyzing the electrical efficiency under various operating parameter states, identify the optimal operating mode. Adjust the load according to the optimal operating mode to reduce electricity consumption and minimize energy loss.

4.3.4 Energy consumption statistics

From the dimensions of energy usage types, monitoring areas, production process/section time, sub items, etc., curve, pie chart, histogram, cumulative chart, numerical table and other methods are used to analyze enterprise energy consumption statistics, year-on-year, month on month analysis, actual performance analysis, benchmark comparison, unit product energy consumption, unit output value energy consumption statistics, identify loopholes and unreasonable areas in the energy use process, and adjust energy allocation strategies to reduce waste in the energy use process.

4.3.5 Product/Output Unit Consumption

Integrate with the enterprise MES system, generate product consumption trend charts in product consumption based on product output and energy consumption data collected by the system, and conduct year-on-year and month on month analysis. So that enterprises can adjust their production processes based on the unit consumption of products, thereby reducing energy consumption.

4.3.6 Performance Analysis

Conduct daily, weekly, monthly, annual, and * time period performance statistics for various energy usage, consumption, and conversion according to teams, regions, production lines, and sections. Compare and evaluate KPI performance indicators based on energy plans or quotas to help enterprises understand internal energy efficiency levels and energy-saving potential.

4.3.7 Energy consumption prediction

By analyzing the energy consumption of production processes and equipment in enterprises, establishing an energy consumption calculation model, and modifying the data and model based on artificial intelligence algorithms, effective decision-making basis is provided for energy conservation.

4.3.8 Operation Monitoring

The system collects data on energy consumption of regions, sections, and equipment, monitors the operating status of equipment and processes, such as temperature, humidity, flow rate, pressure, speed, etc., and supports one-time operation monitoring of power distribution systems. You can quickly browse the managed energy consumption data directly from the dynamic monitoring plan, and support querying related energy consumption by energy type, workshop, section, time and other dimensions.

4.3.9 Analysis Report

By conducting comprehensive statistical analysis on the energy utilization, line losses, equipment operation, and maintenance of enterprises on a yearly, monthly, and daily basis, users can gain a comprehensive understanding of the system's operation and provide a data foundation for them to discover equipment abnormalities, identify improvement points, and explore energy-saving potential based on energy consumption.

4.3.10 Event Alarm

Continuously monitor the operation of equipment and systems, issue alarms for communication failures, data anomalies, quota exceeding limits, abnormal process parameter exceeding limits, equipment abnormalities or failures, remind enterprises to pay attention and search for problems, and form alarm logs.

4.3.11 Mobile Support

The APP supports Android and iOS operating systems, making it convenient for users to grasp enterprise energy consumption, efficiency analysis, month on month analysis, energy consumption conversion, energy consumption prediction, operation monitoring, abnormal alarm, etc. from different dimensions such as energy classification, region, workshop, process, team, and equipment.

4.4 On site equipment selection

5 Conclusion

The energy control of industrial parks often includes energy production systems, energy transmission systems, or energy utilization systems, which require the establishment of a fully integrated energy management system through information technology, the introduction of intelligent analysis and optimization methods, and the achievement of the overall energy conservation and emission reduction goals of the park. This article presents an intelligent energy management and control platform designed and established for the Lingang Heavy Equipment Industrial Park. With the help of information technology, an online monitoring and statistical analysis system for multi-level, multi view, and multi-dimensional energy supply and consumption data has been implemented; Based on the standard processing energy consumption and processing time library, the optimization of production planning and energy scheduling has been completed, achieving the goal of reducing ineffective energy consumption and unit output energy consumption in the production process; A closed-loop energy management model has been established for the interaction between energy supply and consumption, which not only considers "energy supply oriented", but also "energy consumption oriented", improves the utilization rate of energy supply equipment and production equipment, and reduces the energy consumption per unit output value of the park.