21 results about "Operational energy" patented technology

The invention relates to the technical field of indoor environment control, in particular to an energy efficiency optimization and intelligent energy-saving control method and device for an AI five-constant system, and provides the following scheme that indoor and outdoor environment parameters and personnel detection information obtained by a sensing module are combined with an indoor space three-dimensional geometric model, and an energy efficiency optimization and intelligent energy-saving control method and device for the AI five-constant system are obtained. An indoor space is dynamically divided into a target microclimate area and a non-target microclimate area which are formed around people. By respectively determining a five-constant control target parameter set and a differential allowable fluctuation range of the two types of regions, the regulation and control precision is concentrated in the region where the human body is located, and an energy consumption regulation space is reserved in a non-key region. And an energy consumption model is further utilized to construct an operation energy consumption target function, the five-constant-error constraint and the equipment operation constraint are jointly introduced into a multi-target optimization framework, target air supply parameters of the partitioned air supply structure and indoor unit operation parameters are solved, and coordinated regulation and control of the air temperature, humidity, cleanliness, oxygen content and noise are achieved.

This invention discloses a modular data center container collaborative communication method and system, including receiving uploaded 3D drawings, identifying container categories and constructing digital twin models; collecting data from each container in real time, and updating the state of the digital twin model in real time based on the container data; predicting the future state of the container based on the real-time updated digital twin model; performing global optimization adjustments based on the container category and the predicted future state; issuing and executing global optimization commands, and repeating the above steps. The system includes a central digital twin system, edge computing nodes deployed in each container, and a communication network. By constructing a global digital twin model and combining it with a model predictive control framework, this invention achieves advanced prediction of IT load and cooling demand, as well as multi-objective global optimization scheduling, effectively solving the problems of control lag and low energy efficiency in existing container systems, and improving the overall operational energy efficiency and security of modular data centers.

The invention discloses a cross-shaped core tube design method suitable for a super high-rise building, belongs to the field of building design, and aims to solve the problems that due to lack of intensive layout, the building area is wasted, and the use amount of building materials and operation energy consumption are increased. A building system, a structure system, an electromechanical system, an elevator system and other systems are subjected to coupling optimization design, and the plane service capacity of the core tube is improved; by adopting the crossed arrangement of the cross-shaped elevator halls, the traffic area of the core tube can be saved by about 10m < 2 > on each floor, and the use space of more than 500m < 2 > is totally saved according to 50 floors; waste of building area is reduced, and the plane utilization rate can be increased to 78%-80% and is increased by about 2%-5% compared with traditional parallel arrangement; by adopting the cross-shaped elevator hall arrangement scheme, the uniformity of the plane can be obviously improved, the problem of plane detour is avoided, and the streamline distance from the core tube to each shop under the same plane layout can be shortened by about 25-30% compared with a parallel arrangement scheme.

This application provides a distributed building design data collaborative optimization method and system based on federated learning, relating to the fields of intelligent building and data collaboration technology. Specifically, this application first acquires operational energy consumption data, environmental monitoring data, and high-precision point cloud data to construct a semantic spatial structure map. Then, it inputs the operational energy consumption data, environmental monitoring data, and semantic spatial structure map into a joint encoding network to obtain latent variable representations. Subsequently, it uses these latent variable representations to train a local energy consumption analysis model and uploads it to a collaborative center to form an updated global optimization model. Finally, it uses the updated global optimization model to process the latent variable representations to generate optimized operational strategies. The technical solution provided by this application not only achieves collaborative sharing of training experience across multiple buildings and global model iteration but also improves the accuracy and operational efficiency of building energy consumption management.

An energy-saving scheduling method and system for automated dry bulk cargo terminals, considering dynamic switching of conveyor belts, belongs to the field of port operation scheduling. First, it collects characteristic data of the automated dry bulk cargo terminal's yard, information on stacking and reclaiming operations, and parameter information of the operating equipment. Second, it constructs an energy-saving scheduling optimization model for the automated dry bulk cargo terminal considering dynamic switching of conveyor belts. Finally, it solves the energy-saving scheduling optimization model and generates an operation scheduling plan for the planning period based on the solution results. This invention enables integrated optimization of yard location allocation, task transportation route selection, and conveyor belt start-up and shutdown sequence in multi-task, multi-transportation-path scenarios; effectively reducing idle operation and repeated start-ups and shutdowns, significantly reducing operational energy consumption while ensuring operational efficiency, and providing technical support for the intelligent collaboration and green, efficient operation of dry bulk cargo terminals.

This invention discloses a method and system for energy consumption analysis of highway power equipment based on smart gateways. The method includes: acquiring power equipment operation data collected by smart gateways deployed at multiple nodes along the highway; identifying operational energy consumption correlation characteristics corresponding to each smart gateway based on a preset correlation model; predicting the gateway area risk corresponding to each smart gateway based on the operational energy consumption correlation characteristics using a prediction model; and performing energy consumption structure analysis on the highway and identifying abnormal energy consumption data based on the gateway area risk, thereby outputting operational management suggestions for the power equipment. Therefore, this invention can achieve digital monitoring and risk warning of the operational status of highway power infrastructure, thus providing scientific decision-making suggestions and data support for the precise operation and management of power equipment.

This invention relates to solid waste resource utilization technology and discloses a solid waste recycling device for furfurylic acid processing, comprising an anaerobic pyrolysis carbonization furnace and a protective gas flow adaptive adjustment system. The adjustment system includes: a safety risk assessment module, which obtains a safety monitoring coefficient based on combustible gas concentration and temperature gradient; a processing load sensing module, which obtains a load coefficient based on feed rate and gas production flow; a comprehensive demand decision module, which obtains a comprehensive demand coefficient based on the load coefficient, safety monitoring coefficient, waste moisture content, and particle size; an operational stability monitoring module, which obtains a stability coefficient based on multi-point oxygen concentration and furnace pressure; and a flow precision control module, which calculates the target nitrogen flow rate based on the larger value of the comprehensive demand coefficient and the stability coefficient and adjusts it in real time. This invention achieves dynamic and precise control of the protective gas flow rate through multi-source parameter fusion and nonlinear decision-making, optimizing operational energy consumption and pyrolysis efficiency while ensuring the safety of the anaerobic environment.

This invention discloses a predictive control method and system for energy conservation in urban rail transit electromechanical systems based on an adaptive model, belonging to the field of energy conservation control technology for urban rail transit. Existing control methods for ventilation and air conditioning systems in subway stations struggle to balance environmental comfort and operational energy consumption. Online simulation is time-consuming, online strategy trial-and-error carries significant risks, and real-time adaptive adjustment is difficult. This method deploys an offline-trained neural network proxy model and a control strategy model on edge computing devices in subway stations. The neural network proxy model outputs predicted temperature field distribution data and equipment energy consumption data for multiple areas of the station based on outdoor environmental parameters, passenger flow parameters, and equipment operating parameters. The control strategy model uses this proxy model as an interactive environment to construct a reward function based on thermal comfort and equipment energy consumption indicators for reinforcement learning pre-training. This invention is primarily used for energy-saving optimization control of ventilation and air conditioning systems in subway stations.

The present application relates to the technical field of fluid mixing. Disclosed is a fluid-mixing device. The device comprises: a main support, a movable support, a plurality of microporous tubes, a vibration mechanism and a fluid-pushing mechanism, wherein the movable support is movably connected to the main support and is provided with a fluid intake structure; the plurality of microporous tubes are arranged on the movable support and are in communication with the fluid intake structure; the vibration mechanism comprises a vibration device connected to the movable support so as to drive the plurality of microporous tubes to vibrate; and the fluid-pushing mechanism comprises a liquid pump and a fluid-spraying structure in communication with a liquid discharge end of the liquid pump, the fluid-spraying structure is provided with a liquid-spraying opening, and the fluid-pushing mechanism can drive, by means of the liquid pump, a liquid to be sprayed from the liquid-spraying opening towards the tops of the plurality of microporous tubes. The fluid-mixing device of the present application can realize micronization of fluids and improve the mixing effect between fluids, and the fluid-mixing device has extremely low levels of operational energy consumption, thereby facilitating saving on production costs.

The application discloses an artificial intelligence-based power distribution box operation energy efficiency analysis system, comprising: a data processing module for collecting and preprocessing operation data of the power distribution box; a state evolution module for constructing a continuous state evolution trajectory and generating a state change path; a parameter modeling module for constructing a state embedded flow and performing parameterized modeling; a residual sharing module for inputting a state evolution tensor into a multi-channel A3C architecture; a strategy aggregation module for performing independent strategy updating and constructing a cross-channel attention graph; a record control module for controlling power distribution box load on-off logic and generating energy efficiency behavior records with timing labels; and an asynchronous updating module for inputting asynchronous gradients into a shared parameter pool for synchronous updating. The application realizes continuous modeling of the power distribution box operation state and closed-loop optimization of intelligent control decisions, significantly improving the accuracy and real-time performance of energy efficiency management.

This invention discloses an underwater cavern data center based on an island layout, along with its construction and operation methods, belonging to the technical field of cavern-type data centers. The underwater cavern data center includes two parallel transport caverns located within an island, connected by several connecting caverns. Several underwater data storage caverns are located below the sides of these connecting caverns within the island, situated below the water surface of the island's surrounding waters. Each underwater data storage cavern houses a data train, and the connecting caverns contain data train traction equipment. This traction equipment passes through vertical lifting caverns at both ends of its respective connecting cavern before connecting to both ends of the data train within the underwater data storage cavern. The data compartments within the data train undergo immersion cooling within the underwater data storage caverns, improving cooling efficiency and reducing operational energy consumption.

An example of an apparatus to connect to a utility-scale power distribution network is provided. The apparatus includes a first energy storage unit to store a first amount of energy at a utility-scale to be provided to a power distribution network. Also, the apparatus includes a first inverter to connect the first energy storage unit to the power distribution network. The apparatus further includes a second energy storage unit to store a second amount of energy at the utility-scale to be provided to the power distribution network. The apparatus also includes a second inverter to connect the second energy storage unit to the power distribution network. Furthermore, the apparatus includes a switch disposed between the first energy storage unit and the second energy storage unit, wherein the switch converts the first energy storage unit and the second energy storage unit between a line interactive state and an online state.

This invention relates to a method and system for monitoring the operation of electric agricultural machinery based on the Internet of Things (IoT), belonging to the field of intelligent monitoring and IoT technology for agricultural equipment. The invention addresses the problem of complex hardware configurations in existing methods that rely on multiple dedicated sensors to monitor the operational status of agricultural machinery. The method includes: collecting multi-source data to construct an agricultural machinery operation status vector, and then preprocessing it to obtain an agricultural machinery operation feature vector; pre-determining the agricultural machinery's no-load speed range and no-load reference power to determine the final operational status of the agricultural machinery; accumulating the actual operational time of the agricultural machinery based on the final operational status; calculating the actual operational energy consumption; statistically analyzing the set of actual operational trajectory points; calculating the operational coverage area based on the final operational status and the set of actual operational trajectory points; calculating the actual operational intensity based on the actual operational energy consumption and actual operational time; and simultaneously calculating the corresponding operational load response and operational load stability based on the final operational status, thereby achieving agricultural machinery operation monitoring. This invention is used for monitoring the operational status of agricultural machinery.

A detector system may include a sensing element including a substrate, sensing electrodes supported by the substrate, sensing material over the sensing electrodes, and a multi-energy-delivering element. The multi-energy-delivering element may be coupled to the sensing material and may deliver different types of energy to the gas sensing material. The detector system may include excitation and detection circuitry coupled to the sensing electrodes and the multi-energy-delivering element, and a controller coupled to the excitation and detection circuitry. The controller may cause the excitation and detection circuitry to achieve multi-gas differentiation with one-, two-, or higher-dimensional detection by applying an alternating current through the sensing electrodes at one or more operational frequencies for excitation of the sensing material, and applying at least one type of operational energy to the gas sensing material via the multi-energy-delivering element, wherein at least one type of operational energy has at least two levels.

This invention discloses a method and system for simulating and regulating irrigation district water resources with dual control of quantity and quality, belonging to the field of water resource management technology. This invention acquires multi-source basic data from the irrigation district, constructs a water quantity-quality coupled simulation model with a hybrid architecture of mechanism and deep learning, establishes a multi-objective optimization regulation model based on the simulation results, dynamically updates model parameters through Bayesian online learning, and distributes the regulation scheme to the execution unit to form a closed-loop regulation. The system includes a data perception layer, a transmission and storage layer, a simulation calculation layer, a decision application layer, and an execution control layer. This invention adopts a dual-driven mechanism-data approach and multi-timescale adaptive correction, significantly improving simulation efficiency and prediction accuracy, achieving total water quantity control, water quality threshold management, and precise water allocation execution. It can effectively reduce irrigation water shortage rate, water quality exceeding standards risk, and operational energy consumption, and is suitable for intelligent water resource scheduling in large irrigation districts, possessing good engineering practicality.

This invention provides a method for evaluating the operational energy efficiency of hydropower units based on multi-dimensional data comparison of hydropower stations. The method includes: S1, collecting data information on hydropower units in the hydropower station, including basic data and historical operating data; S2, evaluating the current energy efficiency status of the units, the energy efficiency improvement after technical upgrades, and the demand for and adaptability of new energy complementarity; S3, combining the evaluation of the current energy efficiency status and the evaluation of the energy efficiency improvement after technical upgrades, and performing a comprehensive energy efficiency score for the units, using the comprehensive energy efficiency score as the basis for determining whether to upgrade the hydropower station units. This invention allows for the evaluation of the operational energy efficiency of hydropower units of different models and reservoir capacities from multiple dimensions, including hydropower station hydrological parameters, hydropower unit design parameters, operating parameters, and the demand for and adaptability of new energy complementarity. It forms a quantifiable evaluation method, facilitating horizontal comparisons between different types of power stations.

The present invention relates to a method (10) for determining the operational energy loss (Df, Ds) over time intervals for a liquefied gas carrier equipped with a liquefaction system, the method comprising: (12) calculating the amount of energy consumed by the ship's energy consumption devices; (14) calculating the energy fluctuation (D2) as a function of temperature fluctuations of the liquefied gas; (16) adding the energy fluctuation (D2) to the amount of energy consumed (D1) to generate the actual operational energy loss (Df); and, if the liquefaction system is operating over time intervals, the method comprising: (18) calculating the amount of energy saved by the liquefaction system; and (20) adding the energy saved (D3) to the actual operational energy loss (Df) to generate the estimated operational energy loss (Ds) that would have been observed if the liquefaction system had not been operating.

The present invention relates to the technical field of energy consumption analysis in rail transit engineering processes, and specifically relates to a method and system for determining operational energy efficiency of railway freight cars under formation. The method comprises: acquiring operational data of railway freight cars on a line; extracting, from the operational data, a time and corresponding energy consumption required for the railway freight cars to travel a distance S, and using the product of the time and the corresponding energy consumption as a numerator of operational energy efficiency; extracting, from the operational data, the square of the travel distance S and the cumulative value of payloads of the railway freight cars, and using the product of the square of the travel distance S and the cumulative value of the payloads of the railway freight cars as a denominator of the operational energy efficiency; and the ratio of the numerator to the denominator being the operational energy efficiency of the railway freight cars on the line under formulation. Energy efficiency calculation can be dynamically performed in real time, and key factors such as an operating time, operational energy consumption, a travel distance, and a cargo weight are comprehensively considered in a multi-dimensional manner; instantaneous operational energy efficiency can be calculated, average energy efficiency over a period of operation can be calculated, and post-operational energy efficiency calculation can be performed as in the prior art.

A novel renewable energy system is disclosed. The renewable energy system combines second life electric vehicle batteries to form an energy storage system. The energy storage system may compensate for large variations in operational energy and power requirements. The energy storage system is enabled through reuse of unopened electric vehicle batteries after their end first life use (e.g., in automotive use). The energy storage system within the renewable storage system may include a plurality of second life electric vehicle batteries, which may be configured to controllably store and provide power for a variety of applications. In some embodiments, the energy storage system may be operably coupled to one or more photovoltaics, fast chargers, or other variable loads that operate on DC currents. In various embodiments, the renewable energy system containing the energy storage system may require only one bidirectional inverter, which may be connected to a grid.

The invention discloses an intelligent fermentation tail gas treatment system, and relates to the technical field of biological fermentation engineering, and the system comprises a data acquisition module which obtains fermentation tank biological metabolism parameters, gas inlet mass flow, a tail gas component spectrum and a tail gas treatment unit operation state in real time, and establishes a fermentation process-tail gas treatment complete period space-time synchronization industrial database; the health state prediction module learns different fermentation process batch pollution production characteristic rules, generates a process pollution production characteristic digital portrait, establishes a tail gas treatment system digital twinborn model, and predicts tail gas load fluctuation, a pollutant removal efficiency attenuation track and a treatment unit health state; and the stable up-to-standard emission module dynamically generates an optimal control instruction set based on the predicted tail gas load fluctuation, the pollutant removal efficiency attenuation track and the health state of the processing unit in combination with the process-pollutant production characteristic digital portrait, so that stable up-to-standard emission of the tail gas is ensured with the lowest energy consumption. The operation energy efficiency is improved.

This invention relates to the field of multi-split air conditioning technology, and provides a method for predicting energy-saving performance of multi-split air conditioning systems based on air humidity, as well as a multi-split air conditioning system itself. The method includes: collecting relative humidity data of the indoor environment in the room where each indoor unit is located using humidity sensors in each indoor unit; transmitting the relative humidity data from the indoor unit to the outdoor unit, and then uploading it from the outdoor unit to a centralized control device; determining humidity characteristic parameters based on the relative humidity data of each indoor unit; comparing the humidity characteristic parameters with parameters of a preset humidity scenario model to obtain a humidity comparison result; determining the current indoor environmental conditions based on the humidity comparison result; and generating energy-saving reminder information based on the current indoor conditions. This invention enables automatic diagnosis and targeted guidance of the root causes of inefficient operation of multi-split air conditioning systems, effectively improving the operational energy efficiency and intelligent management level of multi-split air conditioning systems.