Research on the Demand and Business Prospect of Informatization Based Digital Energy Use Service in Parks

. With the in-depth development of digital technologies such as informatization, networking, big data, intelligence and intelligence, the digital management of energy consumption in the park has become the development direction of intelligent parks in the future. This paper analyzes the energy consumption and digital service demand of enterprises in the park, analyzes and prospects the business prospect of energy consumption digital service in the park, and puts forward suggestions from the perspective of market operation mode and technology, in order to provide reference for the development of energy consumption digital service in the park in the future.


Introduction
As a world-class brand, State Grid Corporation of China (SGCC) has the world's largest grid assets and strong technology, talent and customer resources advantages, and has the strength to become stronger, better and bigger in the enterprise's energy digital service business. It has huge advantages in infrastructure, basic capacity, brand, users, technical force, personnel team, practical experience and data. In particular, the State Grid Corporation has formed software, platform and massive data in various fields such as planning and design, dispatching and operation, energy management, smart power use, which are the basis of innovative digital products for the energy market in the park. The in-depth development of digital service for power consumption in the park has great advantages and potential in helping users save energy costs, improve energy efficiency, and promote low-carbon energy consumption, which is bound to occupy an important position in the future energy market [1][2][3].

Analysis ideas of digital service demand and business prospect of energy consumption in the park
According to the market of digital services in the park and the changing trend of energy demand of enterprises, this paper selects typical parks and enterprises in the field to conduct research, master the concerns of energy services in the park, carry out the demand and business prospect analysis of energy digital services in the park from the perspective of informatization, and put forward the business model and key market strategies of enterprise level energy digital services suitable for State Grid ecommerce companies, so as to promote the upgrading of State Grid e-commerce companies to energy Internet services. First, according to case analysis and research, carry out accurate portrait of target customers, and clarify the energy consumption and digital service needs of enterprises in the park. The second is to propose a set of enterprise level digital energy service business model in line with the State Grid e-commerce company [4].

Literature review method -use for reference to carry out leading practice case analysis
The literature research method runs through the whole process of the project, and studies, analyzes and summarizes the project data obtained at any time. Through data retrieval, literature reading and other methods, the concept, connotation and theoretical review of energy big data serving regional economy are sorted out and summarized, and the leading practices and cases at home and abroad are interpreted [5].

Interview research method -carry out research on internal and external advanced units
The methods of interview, observation and questionnaire are mainly used to evaluate the current situation of the company's big data construction. The purpose is to accurately identify the problems, shortcomings and causes of the company's work organization, business process, operation mechanism and other aspects. Carry out on-site investigation, expert interview and communication with relevant management personnel of domestic government agencies, Energy Bureau, Ministry of industry and information technology, China electricity Union, typical parks and other institutions, and master the management ideas, methods and demands of ecosystem construction of the project.

Problem clustering analysis -customer pain point clustering analysis develop products and services
Cluster analysis, also known as group analysis, mainly includes direct clustering, shortest distance clustering and longest distance clustering. According to the principle of "birds of a feather flock together", it is a multivariate statistical analysis method to classify samples or indicators. The object of their discussion is a large number of samples, which are required to be reasonably classified according to their respective characteristics. There is no model for reference or follow, that is, it is carried out without prior knowledge. Clustering comes from many fields, including mathematics, computer science, statistics, biology and economics. The process of classifying data into different classes or clusters, so objects in the same cluster are very similar, while objects in different clusters are very different.

Energy demand analysis of enterprises in the park
At present, most of the industrial parks implemented in China emphasize the cluster effect of similar industries.
The key industries to be developed in typical industrial parks in China include equipment manufacturing, petrochemical refining, pulp and paper, power industry, non-ferrous industry, tobacco and alcohol industry, iron and steel metallurgy industry, building materials industry, coal industry, medicine, food processing, tourism commodity characteristic industry, sewage treatment, electronic information, new materials, biotechnology, energy conservation and environmental protection, new energy and other emerging industries. Therefore, according to the industrial planning layout of the industrial park, the industries in the park can be roughly classified into three types: discrete manufacturing, process industry and emerging R & D industry. The energy demand of three types of industrial enterprises is analyzed as follows.

Energy demand analysis of discrete manufacturing industry
Discrete manufacturing industry mainly includes communication facilities, aerospace, electronic equipment, machine tools, automobiles, various types of household appliances, toy manufacturing, clothing and other industrial types. Most of its products are assembled by parts and components and have certain functions. The energy consumed is mainly the power consumed by production and processing equipment, and mainly consumes electric energy; However, the heating and air conditioning of plants in this type of industrial park often account for a large proportion of the total energy consumption. The energy consumption characteristics of the production rooms in the above parks are basically similar to those of the building terminals. Among them, the energy consumption of electricity accounts for about 14% of the total energy consumption, and the energy consumption of heating, air conditioning and hot water supply accounts for about 80%. In northern China, the thermal power ratio of terminal energy demand is about 5.7. In the southern region, if the steam lithium bromide absorption refrigeration and electric refrigeration of waste heat boiler and low-temperature waste heat heating water are used at the same time, the thermal power ratio of its energy demand will be far greater than 3.

Energy demand analysis of process industry
Process industries include electric power, metallurgy, chemical industry, building materials, papermaking, food, medicine and other industrial types, and their raw materials and products are generally materials or materials with specific functions and properties. In fact, in China's industrial structure, the total energy consumption of the process industry is far greater than that of the discrete manufacturing industry, and the industrial energy demand accounts for more than 40% of China's total energy consumption. However, in the composition of terminal energy consumption in process industry, the proportion of electricity consumption in the total energy consumption is small, and its thermoelectric ratio is generally greater than 3. Taking the oil refining industry as an example, the thermal power ratio including steam demand and heat demand is generally greater than 3.

Energy demand analysis of emerging R & D industries
For emerging R & D industries such as electronic information, new materials, biotechnology, energy conservation and environmental protection, and new energy in the park, the probability of using steam for production is small. Even if there is steam load for production, the steam user points will be very scattered, and the steam consumption of each heat user is estimated not to be too large. Considering the economy of steam production and transmission, dispersed steam users can adopt small heat sources such as gas and electricity. Therefore, most of the heat and cold demand in the industrial park can be produced and provided through electric energy technology.

Digital service demand for energy consumption of enterprises in the park
The digital services of energy consuming enterprises in the park need to be reflected in the two levels of Industrial Park and enterprise. The Industrial Park hopes to provide energy consuming digital services to improve the attraction of the industrial park, while enterprises expect to reduce power consumption and costs by using digital management and technology. This requires online monitoring of the dynamic process of production energy consumption of enterprises, collecting a large number of scattered power and energy consumption data in the production process, providing real-time and historical data analysis and comparison functions, so as to find the problems in the process and structure of energy consumption, and guide enterprises to implement corresponding energy-saving transformation measures. First, show the energy consumption of enterprises. It mainly shows the quantity and composition, distribution and flow direction of energy consumption. The second is to understand the energy consumption level of enterprises. Understand the loss of energy utilization, equipment efficiency and energy utilization rate through the energy consumption of the enterprise. Third, it reflects the energy consumption of enterprises. On the basis of understanding the energy consumption level of the enterprise, the problem of energy waste in management, equipment and process operation is found. Fourth, check the energysaving effect of enterprises. By comparing the energy consumption data before and after the transformation, the economic benefits of technical improvement, equipment renewal and process reform are calculated. Fifth, clarify the direction of enterprise energy conservation. After understanding the effects before and after the transformation of the enterprise, it is necessary to clarify the energy-saving transformation of the enterprise process and products, and formulate technical transformation plans and measures. Sixth, power related financial services. By providing banks or third-party payment companies with power and payment history data information, we can innovate power related financial service products.

Business model of digital service of energy consumption in parks
At this stage, the main obstacle to the development of energy services in the park lies in the weak initiative of users' participation. The root cause of the problem is that users generally do not understand and recognize the value of energy services. The construction and operation parties and project owners (users) of most domestic energy service pilot projects belong to the same enterprise, so there is no market transaction problem, let alone business model. In the context of energy Internet, the business models of relevant market players have richer connotations, including not only the traditional energy supply and marketing service model, but also the energy asset service model, energy value-added service model, energy equipment service model and energy information service model. Therefore, identifying the value foothold of various types of market players and building a business model corresponding to their market functions are the basic guarantee for realizing the virtuous circle development of the energy industry chain.

Prospect of the business model of digital energy service in the park
According to the prediction of the International Renewable Energy Agency, under the situation of clean, low-carbon and intelligent development of energy, the proportion of electric energy in terminal energy consumption will gradually increase, and it is expected to reach 50% by 2050. The grid will further highlight its position as a basic hub in the energy revolution. According to incomplete calculation, by the end of the "14th five year plan", the output value of the domestic comprehensive energy service industry is expected to exceed 8trillion yuan. China is in a critical period of energy transformation, and the problem of high energy costs is very serious. By providing new digital services for energy use in the park, on the one hand, reduce the energy consumption and service costs of enterprises, on the other hand, enrich the comprehensive energy service product line of the State Grid. For example, Edison upgraded 140000 street lights in Illinois to intelligent street lighting, enabling it to achieve self-regulation by collecting data on brightness and object activity. It is estimated that Chicago alone will save about 10million dollars per year.
In addition, as the cost of various energy technologies drops, more and more new digital business models for energy use of enterprises continue to emerge, and technology development and business models are iterative and continuous development. Stem, which was born in Silicon Valley, has built a business model for energy storage operation. It controls the participation of energy storage batteries in demand side response through realtime analysis of power supply and demand data to earn peak valley price difference. The development of business model with digital energy service as the core has the potential of cross-border innovation, and has a broad space to play. The future energy business model will be driven by data and digital technology, and will continue to develop in a clean, efficient and distributed way.

Conclusion
Although power grid enterprises themselves have carried out successful exploration of digital transformation, realized the integration of industry technology and digital technology, and have advanced practical experience in data perception and operation optimization, the value mining of energy service data resources is still at a relatively preliminary stage, digital culture is still the main constraint, and there is still much room for imagination in business model innovation. In general, in order to give full play to the role of energy Internet in promoting the digital service of energy consumption in the park, it is necessary to realize the full interaction, mutual benefit and win-win between the market participants and users in the market operation mode; At the technical level, more advanced information processing and data mining technologies are introduced to achieve a wider and deeper interaction between information flow, energy flow and business flow; At the policy level, we should improve various mechanisms and norms as soon as possible to promote the