23 results about "Energy performance" patented technology

The invention relates to the technical field of intelligent power grids, in particular to an optical storage agricultural micro-grid operation optimization method and system, and the method comprises the steps: constructing an optical storage agricultural greenhouse micro-grid, and constructing a robust optimization scheduling model under the photovoltaic output uncertainty to carry out robust optimization scheduling; based on the scheduling scheme of robust optimization scheduling, constructing a micro-grid load model for the light storage agricultural greenhouse; on the basis of the load demand in the micro-grid load model, a cost-benefit optimization model under two operation modes of autonomous investment construction and energy performance contract is constructed, and the cost-benefit is calculated on the basis of the cost-benefit optimization model under the actual operation mode, so that the energy storage capacity configuration and the operation strategy are subjected to collaborative optimization. And constructing an energy storage system capacity configuration and operation optimization model, and finally determining an energy storage configuration scheme and a multi-time scale scheduling strategy. According to the invention, the problems of photovoltaic output uncertainty, single investment operation mode and insufficient economical efficiency optimization of the existing system are effectively solved.

The invention discloses an automatic fault detection and diagnosis system and method based on an artificial intelligence optimization operation system and a function library, and belongs to the technical field of intelligent building and industrial equipment operation and maintenance. The system comprises a data acquisition and preprocessing layer, a fault detection layer, a fault diagnosis layer, an intelligent recommendation layer and a visual display layer. The method comprises the following steps: collecting equipment data in real time and preprocessing; performing anomaly detection and performance trend analysis in combination with statistical process control and a machine learning algorithm; performing root cause diagnosis by using a Bayesian reasoning model; classifying faults according to an energy performance type, a controllability type and a thermal comfort correlation type, and evaluating priorities through a multi-dimensional weighted scoring model; and intelligently generating a solution and updating the knowledge base. According to the method, whole-process automation from early warning, diagnosis, classification to recommendation is achieved, the equipment reliability, the energy efficiency and the operation and maintenance intelligent level are improved, and the method is suitable for application scenes such as artificial intelligence middleware and computer visual and auditory software.

The present disclosure relates to improving the energy performance of CO2 capture. [Solution] A system for capturing carbon dioxide (CO2) from a CO2-containing gas stream, comprising an absorber for contacting the CO2-containing gas stream with an adsorbent, the adsorbent operable to capture CO2 from the CO2-containing gas stream in a first temperature range and release the CO2 in a second temperature range, a desorber for releasing the CO2 from the adsorbent, first and second heat pumps configured to recover heat for the desorber from both a condenser and at least one other point in the system, and the condenser temperature selected to maximize both the heat content of the condensate and the combined coefficient of performance of the first and second heat pumps to minimize the input energy requirements of the heat pump system.

A method for evaluating the energy performance of a pumping unit includes the steps of: obtaining a first value associated with at least one pair of parameters of the pumping unit, the at least one pair of parameters being measured during testing of the pumping unit, the first value indicating the optimal operating state of the pumping unit. The method further includes the step of: obtaining a second value associated with at least one pair of parameters of the pumping unit, the at least one pair of parameters being measured during initial verification of the operation of the pumping unit in a system where it is intended to be used, the second value indicating the initial operation of the pumping unit in the system.

Various aspects of the present disclosure relate to a network entity for a wireless communication network, the network entity comprising: at least one memory; and at least one processor coupled with the at least one memory and configured to cause the network entity to: receive, from an analytics consumer, a first request message comprising a first request for an energy performance of a portion of the wireless communication network; receive, from the wireless communication network, data related to the energy performance of the portion of the wireless communication network; analyze the data related to the energy performance of the portion of the wireless communication network to determine the energy performance of the portion of the wireless communication network; and transmit, to the analytics consumer, a report message comprising the energy performance of the portion of the wireless communication network.

A whole building or campus entity, energy management and energy control optimization, data presentation and visualization dashboard system including a computer processor service provider system, wherein the computer processor service provider system comprises a cloud-based computer processor service provider system comprising: at least one application server comprising the whole building or campus entity, energy management and energy control optimization system executing in the cloud-based computer processor service provider system; and an onsite energy controller coupled to the cloud-based computer processor service provider system by an electronic communications network; wherein said onsite energy controller comprises: at least one electronic computer processor; and at least one electronic computer memory coupled to said at least one electronic computer processor; wherein said at least one electronic computer processor of said onsite energy controller is configured to: reduce energy and demand costs through whole building or campus entity energy management of a building or campus entity load including by being configured to at least one or more of: optimize energy usage; optimize energy generation; maximize demand reduction and utility savings through optimal control of: the energy usage, and the energy generation, or reduce energy costs; and use of at least one energy storage system device; simulate said building or campus entity load by use of at least one or more of: predictive analytics; or receive user inputs of an event schedule that impacts said building or campus entity load; perform optimization at the start of the billing cycle to establish a demand reduction target achievable with the at least one energy storage system device implemented; set a periodic schedule for discharge of the at least one energy storage system device and allocate a portion of energy storage capacity to a reserve to be used in the event of volatility in said building or campus entity load; determine whether there is unused capacity of the at least one energy storage system device at an end of a period, and responsive to the determination, redistribute any of the unused capacity to a remaining period of the periodic schedule; and reset the demand reduction target for each time-of-use period to what was achieved in the previous period for the same billing period; and wherein said at least one electronic computer processor of said onsite energy controller is configured to: display output interactively via an electronic dashboard graphical user interface (GUI) comprising at least one GUI element enabling interactive user receipt of input and provision of output relating to at least one or more of the following: a heat map; a financial energy savings calculation; a color coding of energy production depicting at least one or more of: actual energy production, weather normalized energy production, or predicted energy production; or a color coding of energy usage performance based upon an automatically calculated comparison of expected energy production to actual energy production; a color coded representation of monetization comprising at least one or more of: multi-colored lines on a graphically displayed chart metaphor GUI element; or multiple revenue streams; visual comparison of data between different time periods; or artificial intelligence (AI)-enabled data showing at least one or more of: anticipated production data or anticipated consumption data.

Methods and systems for remediating impaired devices in a deployment are disclosed. The devices may be remediated by repairing or replacing the devices. Whether to repair or replace the devices may depend on the operational and performance costs of running the impaired devices in the deployment. Operational costs may include the retail price of the device and any energy requirements to run the impaired device. Performance costs may include effects of the output of the impaired device on other devices along the pathway of devices. If the integrated costs of the operational costs and performance costs outweigh the sum of the individual operational costs and performance costs, then the device may be replaced; otherwise, the device may be repaired.

To provide a design support system capable of improving design efficiency by supporting selection of outer skin design and facility equipment necessary for achieving energy performance targeted by a building.SOLUTION: The design support system 1 executes a first calculation step of calculating a target design primary energy consumption amount Et of a building, a second calculation step (S112) of deriving a relationship between a design primary energy consumption amount and an air conditioning capacity by using a property database DB for a plurality of existing buildings and calculating a target air conditioning capacity Q t or Qta corresponding to the target design primary energy consumption amount E t as a design target value on the basis of the relationship, and a third calculation step (S15) of calculating a thermal load of the building and a design air conditioning capacity Q d corresponding to the thermal load from the skin information. The design air conditioning capacity Qd and the target air conditioning capacity Qt or Qta are displayed.SELECTED DRAWING: Figure 10

An energy management system and method designed to analyze the energy consumption of a building or cluster of buildings is provided. The system includes a user device and a controller. The controller includes a building energy audit analysis level, an energy demand-supply management level, and a heat and mass balance simulation level. The system integrates energy consumer-type users, energy server-type users, and energy developer-type users on one single platform. The energy management system provides a single platform for the sustainable management of energy data, integrates the users, inputs energy data, analyzes the data, and outputs energy performance and energy efficiency data based on the analyzed data.

The present disclosure relates to improving the energy performance of CO2 capture. [Solution] A system for capturing carbon dioxide (CO2) from a CO2-containing gas stream, comprising: an absorber for contacting the CO2-containing gas stream with an adsorbent; a desorber for releasing CO2 from the adsorbent; a lean return stream for returning the adsorbent from the desorber to the absorber; a main heat exchanger between the desorber and the absorber, the main heat exchanger removing heat from the lean return stream and adding heat to a rich adsorbent stream; at least one additional heat exchanger adding heat to either the lean return stream after the main heat exchanger or the rich stream before the main heat exchanger to produce a high-temperature lean return stream; and a heat pump system configured to remove heat from the high-temperature lean return stream and supply heat to a heating means.

Provide a system. 【Solution means】 Means for obtaining environmental data from sensors in real time, Means for initially processing the received data and detecting abnormal values, Means for generating an energy usage plan based on a generative artificial intelligence model, Means for referring to regulatory information and modifying the energy usage plan based on regulations, Means for automatically executing the plan and performing equipment control, Means for monitoring energy performance and adjusting it in real time, Means for recording data and using it for the next plan generation, A real-time energy management system including the above.

The invention discloses a control method and system for a steam-electricity double-drive air compressor system, and belongs to the technical field of industrial compressed air systems, and the control method comprises the steps that a current dew point demand set value, a temperature safety margin and a load environment correction function are obtained; according to the current dew point demand set value, the temperature safety margin and the load environment correction function, the optimal exhaust temperature set value under the current dew point demand set value is calculated; and according to the optimal exhaust air temperature set value, the exhaust air temperature of the air compressor system is adjusted. According to the method, the optimal exhaust temperature set value under the current dew point demand set value can be calculated through the current dew point demand set value, the temperature safety margin and the load environment correction function, so that the maximum gas production rate is realized on the premise of guaranteeing the dew point of the zero-gas-consumption blast heat dryer; and the compressed air station energy performance evaluation standard can realize the first-level energy efficiency.

This invention provides a method and system for detecting the density of concrete structures within bridges, relating to the field of concrete density detection technology. By differentially processing the echo signal, this invention effectively suppresses background noise in concrete box girders; furthermore, by performing modal decomposition to identify and eliminate high-frequency noise, it significantly reduces interference from the reinforcing steel frame, achieving signal purification. Moreover, by employing an identification method combining energy intensity and phase characteristics, it reduces the impact of signal attenuation on the evaluation results, enabling the differentiation and identification of echo signals from deep dense areas and shallow defect areas, which are easily confused in terms of energy performance. This distinguishes between corrugated pipes and voids, enhancing the overall detection accuracy of the system and its ability to combat false alarms and missed alarms.

The invention discloses a compressor cluster distributed cooperative scheduling method based on contract energy management, and particularly relates to the technical field of industrial energy conservation, and the method comprises the steps: firstly carrying out the distributed node division of a compressor cluster, and constructing a distributed cooperative scheduling network; then, operating parameters of each compressor intelligent node are collected in real time through a built-in sensor, a compressor energy consumption model is built, and predicted energy consumption of the intelligent nodes is obtained; a distributed optimization algorithm is adopted to obtain a load distribution result and regional total energy consumption of each intelligent node; and finally, through an income accounting rule in the contract energy management system, a compressor global energy-saving accounting result is obtained, and summarization and feedback are carried out. Through distributed cooperative scheduling, optimized operation of the compressors can be achieved according to the real-time operation state and the local load requirement of each compressor, and therefore the energy utilization efficiency of the whole compressor cluster is improved.

A system for capturing carbon dioxide, comprising: an absorber for bringing a CO2-containing gas stream into contact with an absorbent; a desorber for releasing CO2 from the absorbent and heating the absorbent to raise its temperature from a first temperature to a second temperature; a condenser; a lean return stream for returning the absorbent from the desorber to the absorber; a flash vessel for reducing the pressure and temperature of the lean return stream and generating a flash vapor stream; a compressor for receiving the flash vapor stream and compressing it to generate a high-temperature flash vapor stream; and a controller for controlling the temperature of the high-temperature flash vapor stream and injecting the high-temperature flash vapor stream into the desorber at a temperature below a threshold.

The present disclosure relates to improving the energy performance of CO2 capture. [Solution] A system for capturing carbon dioxide (CO2) from a CO2-containing gas stream, comprising: an absorber that contacts the CO2-containing gas stream with an adsorbent; a desorber that releases the CO2 from the adsorbent; and an exhaust conduit having a first condenser and a second condenser for cooling the exhaust stream to remove at least a portion of the vapor from the exhaust stream as a condensate and returning the condensate to the desorber, wherein the first condenser is configured to cool the exhaust stream to a third temperature range, and the second condenser is configured to cool the exhaust stream to a fourth temperature range lower than the third temperature range, and the third temperature range is selected so that 71% to 88% of the condensate is condensed in the first condenser.

The application discloses a machine learning magnesium-air battery composite system preparation method and device and the composite system. The method comprises the following steps: obtaining material performance data set; constructing a physically driven product type derived feature and forming a feature matrix; training multiple regression models, screening an optimal prediction model of anode corrosion performance and cathode energy performance; using an explainability analysis to decouple the independent contribution of alloy elements to corrosion kinetics and thermodynamic indexes, and formulating a differentiated component regulation strategy; performing multi-objective high-throughput screening on candidate cathode materials; preparing anodes according to the strategy and coating gel electrolyte paste, matching water evaporation and polymer chain segment relaxation kinetics through multi-stage gradient step vacuum drying, forming a dense defect-free gel electrolyte layer; and assembling a magnesium-air battery composite system. The application solves the problems of low efficiency, low anode utilization and gel layer defects in traditional trial and error by using machine learning to drive design and precise drying process, and significantly improves the discharge performance of the battery.

The invention discloses an old urban area energy performance-spatial form mutual feedback mechanism and intelligent decision-making method based on remote sensing data, and the method comprises the steps: fusing multi-source remote sensing data with ground observation data, and achieving the high-temporal-spatial-resolution ground surface thermal field measurement through a Kalman filtering and deep learning model; accurately positioning a thermal field gradient typical section; integrating LiDAR point cloud and building energy consumption data to construct a three-dimensional model and a database, and mining key built-up environment factors influencing energy performance based on a clustering algorithm and machine learning; revealing and establishing a mutual feedback mechanism of an environment form and energy performance by combining multi-scale analysis and time sequence causal inference; a staged updating mode is provided, and a platform integrating visualization, intelligent evaluation and intelligent management and control functions is built based on a Django framework and a MySQL system. According to the method, the thermal field positioning precision and factor association analysis capability of the old urban area are improved, accurate optimization and scientific management and control of energy performance are realized, and technical support is provided for urban updating and a dual-carbon target.

A disclosed system for dynamically controlling energy performance operations in a facility includes: energy sources, energy sources controllers, and a centralized controller. The centralized controlle

The present disclosure relates to improving the energy performance of CO2 capture. [Solution] A system for capturing carbon dioxide (CO2) from a CO2-containing gas stream, comprising an absorber for contacting the CO2-containing gas stream with an adsorbent, a desorber for releasing the CO2 from the adsorbent, and a heat pump system configured to remove heat from the absorber and supply heat to the desorber, wherein the absorption rate is maintained above a threshold value by controlling the absorber temperature.

The invention relates to the technical field of electric energy measurement, in particular to an electric energy quality detection method for an intelligent electric meter, which comprises the following steps of: calculating channel energy expression and calibrating an abnormal channel by using the intelligent electric meter, analyzing spectral form drift to generate a harmonic combination result, detecting and classifying abnormal events, and evaluating an electric energy quality grade. And screening a trend consistent period section, predicting quality change, and generating trend modeling data. According to the method, periodic energy expression is calculated, sampling abnormal channels are marked, spectral form drifting is recognized by combining frequency band combination features between harmonic amplitudes, periodic overlapping behaviors are further analyzed in abnormal event detection, the abnormal degree of a periodic section is quantified, and a multi-parameter classification result is constructed through event type aggregation. And recognizing a repeated abnormal rule in the time sequence, constructing a dense score according to the repeated abnormal rule, and extracting an input period with consistent trend by combining the variation trend of voltage fluctuation, frequency change and harmonic amplitude, so as to realize power quality trend prediction.

The present application relates to the technical field of electric energy measurement, in particular to a power quality detection method of smart meter, comprising the following steps: calculating channel energy performance and calibrating abnormal channels by smart meter, analyzing spectral shape drift to generate harmonic combination results, detecting abnormal events and classifying, evaluating power quality level, screening consistent trend period segments and predicting quality change, and generating trend modeling data.In the present application, the period energy performance is calculated and the sampling abnormal channel is marked, the spectral shape drift is identified in combination with the harmonic amplitude inter-frequency band combination characteristics, the period overlap behavior is further analyzed in the abnormal event detection, and the abnormal degree of the period segment is quantified, the multi-parameter classification results are constructed by event type aggregation, the repeated abnormal rules in the time sequence are identified and the dense score is constructed accordingly, the input period segments with consistent trend are extracted in combination with the voltage fluctuation, frequency change and harmonic amplitude change trend, and the power quality trend prediction is realized.