107 results about "Energy service" patented technology

The invention discloses an urban energy network intelligent allocation method and system, and the method comprises the steps: obtaining building energy consumption data and energy supply network topology information, building a supply and demand matching reference, recognizing a load peak value dense time period and a peak clipping and valley filling potential region, and exporting transferable load data to form a regional supply and demand distribution diagram; generating a peak shifting adjustment space in combination with the user response delay duration and the equipment start-stop period; performing gap matching analysis on the regional supply and demand distribution map and the peak shifting adjustment space, creating a hierarchical regulation instruction set, and differentially generating an instant response instruction and a delay response instruction; a regulation and control coordination parameter is formed through coordination configuration of the peak shifting revenue coefficient and the instant response instruction; finally, a regulation and control execution range is determined, cost benefit evaluation is implemented, an urban-level energy scheduling execution scheme is formed, accurate matching and efficient scheduling of urban energy supply and demand are achieved, and comprehensive and efficient scheduling decision support can be provided for application scenes such as an intelligent power grid, regional heat supply and comprehensive energy service.

The invention relates to the technical field of electric power data transaction, in particular to an integrated energy service electric power transaction method and system. The method comprises the following steps: acquiring power use data; performing consumer behavior pattern graph construction on the power use data to generate a consumer energy use behavior pattern graph; performing comprehensive energy demand prediction on the standard power use data through the consumer energy use behavior mode map to generate consumer comprehensive energy demand prediction data; and building a block chain energy transaction platform based on the comprehensive energy demand prediction data of the consumer, and generating a block chain energy transaction contract. According to the invention, through personalized energy demand prediction, block chain transaction platform construction, electric energy type analysis, fluctuation response strategy, automatic transaction monitoring and data visualization, the flexibility and efficiency of electric power transaction are improved.

The invention discloses an energy robot-oriented model training method, and relates to the technical field of energy digitization, and the method comprises the steps: synchronizing a business database to a local metadata knowledge base, and carrying out the business feature labeling of a metadata table in the metadata knowledge base according to the business logic; establishing a business problem knowledge base based on the business requirements; constructing a semantic map model of the robot based on the metadata knowledge base; generating mixed data features based on the labeled metadata knowledge base and the business problem knowledge base, and performing multi-model cooperative training of robot intention recognition, intelligent dialogue and intelligent table splicing according to the mixed data features in combination with a semantic map model; performing distributed incremental training on each model of the robot in response to the user session log, and performing model migration according to containerization to complete deployment of the robot; the intention recognition ability and data retrieval and query efficiency of the robot on the text input by the user are improved, then the question-answer response efficiency of the robot is improved, and efficient business question-answer is achieved.

The invention discloses an electricity customer credit rating management method and system based on a differentiated service strategy, particularly relates to the field of energy service, and solves the problem of cold start user credit evaluation deviation and power service resource dynamic adaptation optimization. Seamless migration of credit scoring parameters and smooth transition of user portraits are realized by introducing multi-dimensional feature similarity analysis of virtual data and real data and a time-driven weight attenuation strategy, and continuity and adaptive optimization capability of an evaluation system are ensured; meanwhile, an intelligent service matching network is constructed based on the credit rating updated in real time, and a closed-loop service management and control system driven by data feedback is formed by dynamically adjusting a prepayment mode threshold value and an electric charge overdraft elastic interval strategy, so that the credit value of a user is deeply associated with the power resource configuration efficiency, and the user experience is improved. The operation risk and the service cost of a power grid enterprise are reduced, and finally collaborative optimization ecology considering energy safety management and user behavior guidance is established.

The invention discloses a commercial building electricity comprehensive energy-saving control device, and relates to the technical field of building energy management, the commercial building electricity comprehensive energy-saving control device comprises a comprehensive energy service cloud platform, an air conditioner energy router and an intelligent terminal, the comprehensive energy service cloud platform is in signal connection with the intelligent terminal through the air conditioner energy router; the integrated energy service cloud platform is communicated with the air conditioner energy router through the Ethernet, 4G and NBIOT; the air conditioner energy router is used for providing a traditional gateway data forwarding function and undertaking local data storage, fusion and terminal equipment management. From the perspective of energy efficiency, firstly, a perfect energy efficiency index of the central air-conditioning system is put forward, on this basis, a specific energy consumption optimization strategy is researched from links such as a cold and heat source system, a water system and a terminal system, and finally, from the whole building, operation mode adjustment based on self-learning optimization is achieved in combination with a load prediction model. And comprehensive energy-saving control of electricity utilization of commercial buildings is realized.

The invention belongs to the technical field of energy service scheduling, and particularly discloses an operation management platform for automobile charging service, which comprises a data acquisition module used for acquiring service data; the queue estimation module is used for calculating expected waiting time in a future time period through the constructed prediction model; the pricing and demand mapping module is used for constructing a relation curve of listing prices and time slots; the vehicle owner sensitivity learning module is used for constructing a vehicle owner utility function and pushing and updating an index influencing a service mode selected by the vehicle owner to the mobile terminal of the vehicle owner; the dynamic adjusting module is used for updating service data according to the service mode reported by the vehicle owner and judging whether a charging queue threshold value is triggered or not; if yes, the listing price is adjusted, and updating is broadcasted; the iterative convergence coordination module is used for judging whether the updated listed price and the expected waiting time are in an equilibrium solution or not in each time slot; the method has the following advantages: dynamic coupling of supply and demand, rapid price adjustment, accurate flow control, smooth queuing, and synchronous optimization of income and load are realized.

The invention discloses a cost calculation method and system for an integrated energy service system, and belongs to the field of integrated energy service. According to the method, the comprehensive energy service system is analyzed, physical boundaries and elements of the comprehensive energy service system are determined, and a corresponding cost benefit model is constructed. The elements comprise wind power, photovoltaic and cooling and heating systems on a source load side, a comprehensive energy service management and control platform on a power grid side, electrochemical energy storage on an energy storage side and an electric vehicle V2G. And then the business modes of the comprehensive energy service system are divided into four classes, and the scientific calculation of the overall cost benefit of the comprehensive energy service system is realized by combining the cost benefit models of different elements.

The invention discloses an integrated energy system real-time scheduling method considering price fluctuation under multiple subjects, and the method comprises the following steps: S1, determining all subjects of an integrated energy system and an energy consumption mode of the subjects, and introducing a reward and punishment stepped carbon transaction mechanism to restrain a model of system carbon emission; s2, taking the comprehensive energy service provider as a leader and the other subjects as followers, and establishing a multi-subject transaction model; s3, based on the optimization target, the constraint condition and the price fluctuation, constructing an economic optimization scheduling model of the integrated energy system; and S4, calling a CPLEX toolbox in MATLAB software to solve the economic optimization scheduling model, and obtaining a real-time scheduling optimal strategy of the integrated energy system. According to the method, the minimum total operation cost of the system is taken as a target, the effectiveness of the proposed method is verified by setting an example, flexible demand response resources under real-time scheduling can be fully excavated, and balance of benefits of all subjects and economic and low-carbon operation of the system are realized.

The invention relates to the technical field of energy control, in particular to a comprehensive energy service optimization control system based on multi-energy flow coupling. Three energy coupling supply modes of the air source heat pump, the electric boiler and the heat storage water tank are adopted to provide heat loads for the park winter user side, the operation states of the air source heat pump unit, the electric boiler and the heat storage water tank are controlled in a coordinated mode according to the park user side heat load demand change condition, multi-energy complementation and on-demand energy supply are achieved, and the energy utilization rate is increased. Meanwhile, the advantage of high energy efficiency of the air source heat pump unit is fully played, economical operation is achieved, and the comprehensive operation cost of the whole thermodynamic system in the park is reduced; according to the invention, a multi-coupling energy supply hierarchical coordination control strategy is adopted, the comprehensive energy management and control platform is divided into an intelligent central application layer, a control layer and an equipment layer, and a hierarchical coordination control strategy of park system hierarchical management and park system centralized coordination is adopted, so that integration and intellectualization of the whole park energy system are realized; and safe and economical operation of the park comprehensive energy system is ensured.

The present invention relates to the field of natural gas management technology, and in particular provides a distributed energy pipeline natural gas demand management method, system and medium, the method comprising: determining a commercial change sequence; determining a civil change sequence; determining a demand sequence based on the civil change sequence, the commercial change sequence and historical usage data; constructing a micro-pipeline network map; determining a gas storage coverage rate and a gas supply priority; determining a gas storage adjustment parameter based on the gas storage coverage rate and the gas supply priority; and generating a gas storage adjustment instruction based on the gas storage adjustment parameter. The system comprises a distributed energy perception control platform, a distributed energy sensor network platform, a distributed energy demand management platform, a distributed energy service platform and a distributed energy user platform. The method can be run after being read by a computer instruction stored in a computer-readable storage medium. The method can ensure the normal supply of gas in the gas supply area without affecting the normal production and life of gas users.

The invention discloses a green low-carbon energy consumption service management system, which belongs to the technical field of energy consumption management and comprises a platform end and a user end. The platform end is used and managed by a platform party and comprises a monitoring analysis module; the monitoring analysis module is used for performing monitoring reserve analysis, setting a plurality of energy consumption estimation models and configuring corresponding energy consumption estimation models for the user side; the user side comprises a monitoring module, a display module and an energy-saving analysis module; the monitoring module is used for monitoring energy consumption data of each energy consumption device in an enterprise in real time, and merging and classifying the energy consumption devices to obtain a plurality of representative classifications and independent devices; monitoring equipment is arranged according to the representative classification and the independent equipment; performing real-time energy consumption monitoring on the representative classification and the independent equipment according to the energy consumption estimation model to obtain energy consumption monitoring data of the energy consumption equipment; the display module is used for monitoring and displaying; and the energy-saving analysis module is used for performing real-time energy-saving analysis according to the energy consumption simulation model to obtain a corresponding emission reduction scheme.

The present invention provides a dynamic aggregation method for integrated energy service providers that considers node load yields. The method constructs an IESP operating structure based on the IEDN. The operating structure includes a network infrastructure and EH within the service provider's jurisdiction. The network infrastructure is centered on the distribution network, and the IEDN couples the gas and heat distribution networks through the EH. The present invention also constructs an EH input-output model, performs aggregation based on the IESP aggregation principle of node yields, obtains the aggregated yield of node resources based on the initial aggregation incentive, constructs a node yield calculation model, establishes a dynamic correction model for the aggregation incentive, and uses the correction model to establish a node load aggregation potential calculation model. Finally, an IESP aggregation yield maximization model is established to obtain a method for dynamic node load aggregation. The present invention fully aggregates the electricity, gas, and heat resources within the IEDN, quantifies the real-time contribution during the aggregation process, identifies key nodes that contribute to improved efficiency, and increases aggregation yield.

The invention discloses a user energy efficiency optimization strategy generation method and system based on deep learning, particularly relates to the field of comprehensive energy service, and is used for solving the problem of strategy instability caused by frequent jump of current user portraits. Constructing a group structure chart to identify leading customers and target customers to mark response features, generating a strategy candidate set by the group structure chart and a trigger queue, translating the strategy candidate set into an action script, setting a write-back suppression coefficient and a cooling period threshold, and calculating write-back control parameters to constrain write-back amplitude and rhythm; and outputting a resource release plan, collecting and executing a return certificate, and updating the dynamic portrait set and the group structure chart according to a write-back control parameter, thereby effectively maintaining the stability of the portrait, and realizing a stable closed loop of user energy efficiency optimization.

The present invention relates to a multi-agent optimal compromise scheduling method for a multi-agent hydrogen-containing integrated energy system. For the multi-agent hydrogen-containing integrated energy system optimization scheduling model, a multi-agent reinforcement learning model consisting of a hydrogen-containing integrated energy service provider agent, an electric load aggregator agent, a thermal load aggregator agent, and a hydrogen load aggregator agent is constructed, and the solution is obtained through a multi-agent proximal strategy optimization algorithm and an approximate ideal solution sorting method. The present invention enhances state space collaboration by incorporating action information of adjacent agents, and constructs a multi-scheme evaluation mechanism based on the approximate ideal solution sorting method to screen the action combination of the optimal compromise solution, forming a multi-agent optimal compromise reinforcement learning algorithm, thereby improving the collaboration and solution efficiency between agents.

The invention relates to a multi-agent optimal compromise scheduling method for a multi-agent hydrogen-containing comprehensive energy system. A multi-agent reinforcement learning model composed of a hydrogen-containing comprehensive energy service provider agent, an electrical load aggregator agent, a thermal load aggregator agent and a hydrogen load aggregator agent is constructed for a multi-agent hydrogen-containing comprehensive energy system optimization scheduling model. Solving is carried out through a multi-agent near-end strategy optimization algorithm and an ideal solution approaching sorting method; according to the multi-agent optimal compromise reinforcement learning method, the state space cooperation is enhanced by fusing the action information of the adjacent agents, a multi-scheme evaluation mechanism is constructed based on the approximate ideal solution sorting method, the action combination of the optimal compromise solution is screened, the multi-agent optimal compromise reinforcement learning algorithm is formed, and the cooperation and solving efficiency between the agents is improved.

The application provides a kind of comprehensive energy point-to-point transaction system based on blockchain, it is related to comprehensive energy technical field, the system includes: energy supply subsystem, terminal subsystem, regulating subsystem and feedback subsystem.Wherein, energy supply subsystem is used to input energy to comprehensive energy service system;Terminal subsystem includes supplier and receiver, for providing energy or receiving and consuming energy;Regulating subsystem is used to delete all other subsystem nodes in transaction information after each transaction process, record transaction information in regulating subsystem;Feedback subsystem is used to ask transaction parties whether information deletion can be carried out with regulating subsystem.The application uses regulating subsystem to carry out information storage management of the whole system, realizes the unified integration of each node storage information after transaction, deletes redundant transaction information, reduces information storage pressure and guarantees the stability of point-to-point transaction process.

The application relates to an industry chain early warning method and an energy service SaaS operation and maintenance management platform. The method comprises the following steps: acquiring basic power consumption data groups of all terminals of an enterprise, each terminal corresponding to a basic power consumption data group; cleaning the basic power consumption data groups to obtain analysis power consumption data groups; constructing power consumption analysis curves by using the analysis power consumption data groups; acquiring behavior data of the terminals and segmenting the power consumption analysis curves according to the behavior data to obtain multiple sub-power consumption analysis curves; correlating and analyzing the sub-power consumption analysis curves and a comparison reference curve according to the behavior data to obtain analysis results; and giving a judgment result according to the analysis results, wherein the judgment result comprises normal power consumption behavior and abnormal power consumption behavior. The industry chain early warning method and the energy service SaaS operation and maintenance management platform disclosed by the application can discover the relationship between equipment operation behavior and power consumption by analyzing collected data, thereby providing data support for subsequent equipment maintenance and power consumption optimization.

The utility model discloses a cloud computing smart energy server device installed in a distributed mode, and belongs to the technical field of server installation. A cloud computing smart energy server device installed in a distributed mode comprises two sets of installing bases and a server body, the installing bases are arranged in parallel, connecting assemblies are arranged in the installing bases, the server body is installed at the tops of the connecting assemblies, and heat dissipation holes are formed in the surface of the server body. Connecting clamps are arranged between the server bodies, transverse frames are arranged between the transverse connecting assemblies, vertical frames are arranged between the vertical connecting assemblies, and the server bodies are in lap joint with the surfaces of the transverse frames and the surfaces of the vertical frames. The utility model aims to solve the problems that the installation structure of a server in the prior art is more compact, the heat dissipation performance of the server installed in an array mode is poorer, and the disassembly, assembly and maintenance of unit servers are more tedious.

The invention discloses a comprehensive energy service system for a thermal power plant combined with hydrogen energy application. The outlet of a fuel system of the thermal power plant is sequentially connected to a burner on a boiler via a pulverizing system, the steam outlet of the boiler is connected to an inlet of a steam turbine, the exhaust steam outlet of the steam turbine is connected to industrial steam equipment, absorption refrigeration equipment and a heat release side of a heat exchanger; the output end of the steam turbine is connected to a driving shaft of a generator, the output end of the generator is connected to a public power grid and a plant power grid, the plant power grid is connected to an electrolytic hydrogen production device, an air separation device, a public gas preparation device, a compression refrigeration device and a compression heat pump, the output end of a distributed photovoltaic system is connected to a power supply interface of an electrolytic hydrogen production device, the hydrogen outlet of the electrolytic hydrogen production device and the nitrogen outlet of the air separation device are connected to the inlet of an ammonia reactor, and the outlet of the ammonia reactor is connected to an ammonia burner on the boiler. The system can realize the combination of comprehensive energy services and hydrogen energy.

An energy service apparatus which includes a memory that stores information associated with a plurality of devices connected via a smart home network or information associated with a device providing an energy service associated with at least one of a power consumption or a power-saving mode. The energy service apparatus includes a processor that identify a target device selected through a user terminal, requests first information associated with a device providing an energy service, based on information associated with the target device not being included in the first information, requests second information, and based on the second information and information of a management file, identify whether the target device is the device providing the energy service, wherein the information of the management file includes information which is registered by an administrator and associated with the device that provides the energy service.

The invention discloses a public institution energy efficiency improvement and transformation strategy selection method based on a three-party evolutionary game, and the method comprises the following steps: S1, deeply considering three-party benefits and decisions based on an interaction mechanism formed by the mutual influence of a government, an integrated energy service provider and a public institution in facing a public institution energy efficiency improvement and transformation project, income and expenditure parameters of all parties are determined, and a three-party evolutionary game model with the government, the comprehensive energy service provider and the public institution as the main body is established. According to the invention, the three-party dynamic game model of the government, the comprehensive energy service provider and the public institution is constructed, the income cost parameters of all parties are quantitatively analyzed, and evolution paths of different strategy combinations are revealed by using a duplicated dynamic equation and stability analysis, so that a dynamic strategy framework based on benefit balance is provided for improving the energy efficiency of the public institution; therefore, an effective method is provided for selecting the energy efficiency improvement strategy of the public institution.

This invention provides a method and system for constructing a corpus database. The method includes: decomposing multi-source heterogeneous corpora obtained based on energy service business processes to obtain multiple business process nodes and corresponding initial corpora; extracting association features from the initial corpora of any two adjacent business process nodes to obtain co-occurrence association features; for each business process node, dividing the initial corpora into scenario corpora and associated corpora based on business scenario tags and co-occurrence association features; mapping the associated corpora of each business process node to the scenario corpora or associated corpora of other corresponding nodes based on the sequential order of the business process nodes to construct association links; and storing all corpora based on the paths from the scenario corpora and associated corpora to the associated node corpora and the association links. This invention meets the needs of energy service businesses for efficient and accurate data support.

The invention discloses a multi-source data fusion processing platform and method supporting energy business collaboration, and relates to the technical field of data processing, and the method comprises the steps: connecting a multi-source data end side, and recognizing a first group of mapping data sources of the energy business collaboration; identifying a historical data source failure probability of the first group of mapping data sources to obtain a first group of failure probabilities, and inputting the first group of failure probabilities into a data fusion influence degree identification model for analysis to obtain a data fusion influence degree index; when the data fusion influence degree index is greater than a preset influence degree threshold value, identifying a second group of mapping data sources of energy business collaboration, and configuring the second group of mapping data sources as equivalent data pairs of the first group of mapping data sources; and performing data fusion processing on the multi-source data pairs based on the equivalent data pairs to obtain a fusion database. The technical problems that in the prior art, due to insufficient reliability of multi-source data, the fusion result deviates, and the energy service cooperation stability cannot be guaranteed are solved, and the technical effect of guaranteeing the fusion data stability and the service cooperation continuity is achieved.

The invention provides a corpus database construction method and system, and the method comprises the steps: carrying out the disassembly of an obtained multi-source heterogeneous corpus based on an energy service business process, and obtaining a plurality of business process nodes and corresponding initial corpora; performing associated feature extraction based on the initial corpora of any two adjacent business process nodes to obtain co-occurrence associated features; aiming at each business process node, dividing the initial corpus into a scene corpus and an associated corpus based on a business scene label in combination with a co-occurrence associated feature; mapping the associated corpus of each business process node with the scene corpus or associated corpus of the corresponding other nodes based on the sequence of the business process nodes, and constructing an associated link; and storing all corpora based on the scene corpora, the path of the associated corpora pointing to the associated node corpora and the associated link. According to the invention, the requirement of energy service business on efficient and accurate data support is met.

There is provided an energy transaction platform to facilitate a wholesale↔distribution↔DER owner marketplace for DER-based energy products, including contracting, delivery, and settlement, for example, based on blockchain technology. The platform provides components to enrol and verify DER owners having a DER device. Platform components define and communicate contracts for energy services for bidding by DER owners to facilitate e.g. EV charging, GHG reduction, or demand response goals. Contracts are cleared in response to bidding, for example, by DER owners. The platform triggers contract delivery, which delivery is monitored and confirmed. Settlement is made between contract parties according to confirmed participation. Participation rewards and / or credit tokens are transferrable to DER owners, which can be further transferred. DER owner credibility measures can encourage participation and assist with clearing contracts. The platform can use blockchain smart contracts for events and store data to the blockchain.

The invention discloses an energy service task-oriented equipment maintenance personnel automatic selection method and system, and relates to the technical field of data processing, and the method comprises the steps: setting segmented selection configuration parameters according to maintenance task demand parameters and personnel qualification access conditions of energy service equipment; setting a correction coefficient based on the semantic matching characteristics of the maintenance resources and task execution efficiency parameters; reversely analyzing the optimized selection configuration parameters, and generating a personnel automatic selection execution scheme; and acquiring task matching influence area data in real time, and dynamically refreshing and optimizing the selection configuration parameters according to a preset matching threshold value and an adaptive deviation. The technical problems that an existing equipment maintenance personnel selection method cannot dynamically adapt to task demand changes, and personnel selection precision and efficiency are low are solved, and the technical effect of improving personnel selection precision and response speed through automatic selection and dynamic optimization based on task demands and real-time data is achieved.

The utility model provides a transcritical cycle-based multi-energy combined supply system. The transcritical cycle-based multi-energy combined supply system comprises a clean energy utilization system, an energy storage system, a supercritical medium power generation system, a supercritical medium refrigeration system, a combined heat and power generation system and a control system, the supercritical medium power generation system comprises a first gas-liquid separator, a compressor and a high-pressure turbine; the output end of the heat storage system is connected with the input end of the first gas-liquid separator, the energy storage medium output end of the first gas-liquid separator is connected with the input end of the combined heat and power generation system, the supercritical medium output end of the first gas-liquid separator is connected with the first input end of the compressor, and the first output end of the compressor is connected with the input end of the high-pressure turbine. The second output end of the compressor is connected with the supercritical medium input end of the cold storage system. According to the scheme, through coupling application of a supercritical medium technology and an energy storage medium heat storage technology, a comprehensive energy service system integrating efficient energy conversion, flexible energy storage adjustment and multifunctional cooling, heating and power supply is constructed.

The invention discloses an oil-gas-hydrogen-electricity comprehensive energy service station coupling modeling method and related equipment, and relates to the field of energy internet, and the method comprises the steps: taking operation and price parameters of an electrolytic cell, a compressor, a storage tank, terminal supply, electric energy storage, a gas turbine, a photovoltaic power grid, a superior power grid and the like; based on time-sharing demands of vehicles (fuel oil, natural gas, hydrogen fuel cells and electric vehicles) and single-machine capacity and number of terminal supply equipment, time-sharing electric power balance of a supply end and a power utilization end, hydrogen / gas storage cross-period inventory continuity, electric energy storage charging and discharging and SOC constraint are established, and scale matching and the maximum installation number are set. An optimization model is constructed and solved by taking energy sales income operation and maintenance reduction cost, light abandoning cost and energy purchasing cost as objective functions, time-sharing equipment output, electricity purchasing quantity, oil / gas / hydrogen flow and electric energy storage state are output, and a basis is provided for station-level scheduling and planning.

This invention belongs to the field of integrated energy service systems and discloses a method and system for optimizing an integrated energy service system based on carbon trading. The method comprises: obtaining operational data of the integrated energy service system to calculate the system's carbon emissions; constructing a two-layer model for a power-carbon P2P joint market, comprising an upper-layer model for power-carbon P2P trading and a lower-layer model for distribution system operators; inputting carbon emissions into the upper-layer model to obtain the results of power-carbon P2P trading; the lower-layer model for distribution system operators calculates and updates the carbon emissions of the integrated energy service system based on the results of power-carbon P2P trading; and iteratively solving the two-layer model to obtain an optimization strategy for the integrated energy service system. This invention utilizes dynamic carbon flow tracking technology to achieve real-time calculation of carbon emissions through continuous iterative calculations, addressing the difficulty of balancing data security and global coordination in traditional centralized optimization.

The present invention discloses a management method, device and equipment for displaying information in an integrated energy service platform. The method includes: receiving a login request from a platform user, responding to the login of the platform user, and determining the user type of the platform user; if the user type of the platform user is an enterprise-level user, then according to the enterprise type to which the enterprise-level user belongs, combined with a pre-built service data pool, determining the matching platform homepage display information; if the user type of the platform user is an individual-level user, then according to a pre-set general display information screening logic, obtaining the platform homepage display information to be displayed from the service data pool; extracting the service display information corresponding to each homepage service display item from the determined platform display information, and presenting the corresponding information display area. The platform provides differentiated information display according to different users, and users can more simply and quickly obtain the required information with a higher degree of matching, thereby improving the user experience of the integrated energy service platform.