Project Background:

This well-known packaging company is currently the largest supplier of reusable logistics packaging for JD.com and SF Express, and is also an important supplier of China Post , its core production process needs to dissolve plastic particles through electric heating, and supply them to the subsequent process through a wire drawing machine. This production process is highly dependent on electric energy, and it is a typical enterprise with high energy consumption and high carbon emissions.

Problems facing:

Insufficient capacity. Because the total rated power of the factory equipment exceeds the capacity of the transformer, and the capacity cannot be increased, tripping or Capacity constraints are common;

High electricity bills. The production process consumes a lot of electricity, and there is a certain load valley period at night. It is more suitable for handling peak and valley electricity bills.

Double carbon indicator. The government has carbon emission quota requirements for large electricity consumers, and needs to reduce carbon emission by 5% every year %.

Photovoltaic waste. Due to holidays, equipment maintenance and shutdown on high temperature days, there is a phenomenon of photovoltaic power abandonment and waste.

There is a lot of room for optimization. Rely on manual meter reading for equipment management, which takes a long time, has large errors, and has data loss problems , the overall energy management effect is not ideal;

■ Solution:

Global energy management

Deploy more than 2,000 data points from 50 measuring points in each energy use link of the factory to collect more than 2,000 data points, and build a factory-wide energy management system to assist Refined energy management. Overall, it meets the refined management needs of factories such as energy cost control, data statistics, energy efficiency analysis, and energy operation and maintenance.

AI energy storage

Based on the actual load data and environmental conditions of the factory, a 500kWp distributed photovoltaic station and a 100kW/200kWh The distributed energy storage system and two 60kW electric vehicle charging piles are used to increase the energy supply and virtual expansion of the factory to meet the operation of the newly added air conditioning system in the workshop, the charging demand of the factory's electric vehicles and the guarantee of peak production load.

 Smart Microgrid

Complete the construction of the "Lego" building block factory intelligent micro-grid system module, combined with artificial intelligence algorithm model and scheduling control technology, the collection market Electricity, production/operating load, photovoltaic, energy storage operation monitoring, air-conditioning system and external policy changes, output prediction and analysis of solar energy storage energy revenue and control strategies, using cloud-edge integrated UES architecture, to achieve full-scale optimization when internal optimization goals change The unmanned intelligent adjustment and optimization of the revenue curve meets the automatic optimal strategy operation of the factory's integration of light, storage and charging, and realizes optimal economic benefits and worry-free management of energy scheduling.

Entropy cloud intelligent control system

Based on energy data analysis and production scene research, the group intelligent control of wire drawing machines, air compressors, and workshop air conditioners is completed.

Item value

Create economic value of more than 7 million yuan and reduce carbon emissions by 2600 tons

The average annual photovoltaic power generation is about 800,000 kWh, equivalent to about 450,000 yuan in electricity bills, and the investment recovery period after the smart microgrid is upgraded From 5.92 years to 5.28 years, the average annual reduction of carbon emissions is about 2,600 tons.

The average annual income of energy storage peak shifting and demand regulation is more than 70,000 yuan, and the investment recovery period after the smart microgrid is upgraded From 5.86 years to 5.4 years.

Due to the virtual capacity increase to meet the air conditioner operating conditions on high temperature days in summer, 15 downtime days are reduced every year, and the production order revenue is increased by about 6 million yuan.

Improve energy management efficiency, reduce the workload of power operation and maintenance personnel, and reduce the cost of one power operation and maintenance personnel by about 80,000 per year.

Energy safety early warning mechanism reduces the proportion of unplanned shutdowns to 40% of the original number, reducing economic losses by about 300,000 yuan per year.

Optimized production intelligent control, reducing energy consumption per unit product by 8%, and reducing product production costs.

Complete the digital transformation of the energy system and create sustainable management value

Build and complete the energy digital management system, complete the energy digital transformation, and improve the human efficiency of energy management.

Complete the construction of factories and dual-carbon smart energy systems, laying the foundation for power trading and carbon trading.

Complete the practice of algorithm-driven energy-saving optimization and improve the factory's intelligent operation capability.

The level of energy safety management is improved and the risk of factory operation is reduced.

Actively respond to energy conservation and emission reduction, and practice corporate social responsibility

Promote energy conservation, emission reduction and green factory construction, and help achieve the goal of carbon neutrality at the peak of carbon emission.

Improve the digital management level of traditional factories, take the initiative to complete the digital transformation of smart transformation, and provide a convenient foundation for the government to link industrial energy consumption supervision.