53results about How to "Optimize operation strategy" patented technology

The invention discloses a control system for measuring the energy consumption of urban rail transit and an evaluation method. The control system comprises a vehicle-mounted energy consumption control unit, a data management unit and a ground energy consumption control unit. The control system has the beneficial effects that the system is a multi-path sampling energyconsumption metering system; drive control is carried out by adopting a permanent-magnet synchronous DC motor; a double-energy control module is built by using a super capacitor and a lithium battery for vehicle-mounted energy conversion control; train force analysis and modeling are not needed; a large quantity of nonlinear analysis or intelligent optimization calculation is not needed; traction energy consumption, regenerative braking energy and auxiliary energy consumption can be measured and monitored by directly utilizing collected voltage and current data; the control system has the functions of real-time storage and display of energy consumption data; the energy consumption data can be uploaded to the ground energy consumption control unit through the data management unit; the labor cost is reduced; the control system has a fault detection function; and the fault can be accurately reported when the system fails.

The invention relates to the technical field of energy-saving scheduling for an air conditioning system, in particular to an energy-saving operation optimization scheduling method for the air conditioning system, which comprises the following steps of: constructing of a total objective function for calculating the minimum total energy consumption; inputting the predicted load Q (i) i ( / i) to be allocated, sequencing the devices according to the priority order of the peak price in the schedule to judge whether the predicted load Q (i) i ( / i) is higher than the minimum starting load of the system and whether the predicted load Q (i) i ( / i) is higher than the minimum output load of the unit; judging whether the air conditioning system is a cold supply mode or a heat supply mode; respectivelyentering a water pump frequency conversion module and a cooling tower module for frequency modulation calculation according to the calculated data; setting a constraint condition of the temperature ofthe inlet and outlet water to judge whether the temperature of the inlet and outlet water meets the constraint condition; calculating the energy consumption of each device. The method comprises respectively calculating the power consumption of equipment such as a water chilling unit, a water pump, a cooling tower, a boiler and the like to arrange the equipment in a large-small sequence, screeningby taking the minimum total power consumption of an air conditioning system as a target to obtain the minimum power consumption, and outputting a corresponding equipment optimization operation strategy.

The invention discloses a public traffic operation service quality evaluating system, which can comprehensively reflect the evaluation on operation service quality by the subject (flee) and object (passengers) of public traffic operation service, provides a new angle of view for public traffic service evaluation on the basis of online and on-file automatic vehicle positioning data, and can provide decision support in optimizing operation policy, improving service level and demonstrating the actual and boundary effects of improvement on service measures on enhancement of service for public traffic operating enterprises and provide a corresponding theory and a corresponding method for controlling the quality of the public traffic operation service for the management department of the public traffic industry to realize the aim of the invention.

The invention discloses a mobile cold-heat-electricity triple generation distributive energy station. The energy station adopts a box type structure; and a micro gas turbine generator set, a smoke afterburning lithium boride air conditioning unit and a cooling tower which are included by the energy station, and a control system, an air conditioner water system, a natural gas system, a smoke system, an electric system, running water, a drainage system and a vibration and noise reducing system of the energy station are all prized on a base, so that the energy station becomes a mobile system.

The invention provides an urban rail transit simulation system. The system comprises a simulation management module and a simulation module; the simulation management module is used for configuring the simulation parameters of a train and outputting a simulation control instruction; and the simulation module is electrically connected with the simulation management module. According to the simulation system, a simulation mode can be selected according to actual requirements; single-system-level and component-level simulation can be achieved, and at the same time, multi-system-level coupling simulation can be achieved. Therefore, the urban rail transit simulation system can meet the application requirements of the multi-disciplinary collaborative optimization design and verification of the multiple systems, single system and components of trains, the reliability and life prediction of the key components of the trains, the optimization of operation strategies, fault simulation and processing and the like.

The invention relates to the technical field of indoor heating and ventilation, in particular to a control method of an intelligent comfortable cooling and heating household air conditioning system. The control method comprises the following steps: in a heating mode, valves of a capillary network and a ground temperature adjusting pipe network are controlled to be opened through a valve controller for heating; in a refrigerating mode, the valves of the capillary network and the ground temperature adjusting pipe network are controlled to be opened, meanwhile, water supply at the set temperature is controlled and provided through a water mixing temperature adjusting controller for cooling; when the control result of the capillary network and the ground temperature adjusting pipe network cannot meet the set requirement, a fan coil is opened in a linkage mode; and when the control result of the capillary network and the ground temperature adjusting pipe network can meet the set requirement, the temperature is controlled by controlling a proportional integral valve through the water mixing temperature adjusting controller in the heating mode, and the temperature is controlled by opening and closing the valves of the capillary network and the ground temperature adjusting pipe network in the refrigerating mode. Radiation temperature adjustment is mainly adopted, the temperature can be rapidly adjusted, the blowing feeling is reduced, and the comfort degree is improved.

The invention relates to an operation system and an operation method based on user behavior data and user portrait data. The system comprises a user behavior data management module, a user portrait data management module, a crowd creation module, a crowd operation plan management module and an operation effect evaluation module. Based on event data which is user behavior data, users are screened by configuring a plurality of events and event attributes as limiting conditions. Based on user portrait data, namely label data, a plurality of labels are configured to serve as limiting conditions tofurther screen users. The crowd list is regularly updated through the crowd operation plan management module, and the crowd is regularly pushed to the target operation system. After an operation taskis completed, operation result data is obtained, the crowd data is associated with the operation batch data, and an operation effect is analyzed. By measuring the user behavior data and the user portrait data, the target user with the high matching degree with the operation target is screened out, and low-cost operation and high-efficiency conversion of the user are achieved.

The invention relates to the technical field of air conditioner energy efficiency detectors, in particular to an air conditioning system energy efficiency on-line detection and diagnosis analyzer. Theair conditioning system energy efficiency on-line detection and diagnosis analyzer comprises an air conditioning unit parameter detecting module used for collecting parameters of a central air conditioner. The air conditioning unit parameter detecting module comprises a sensor unit. The sensor unit is connected with a collecting controller. The collecting controller is connected with a work station by an industrial communication bus. Through adopting the method and structure, the air conditioning system energy efficiency on-line detection and diagnosis can monitor and record the machine roompipeline pressure, temperature, flow amount and the water pump, cooling tower and unit power consumption data in real time. Water pump efficiency, unit energy efficiency ratio and water pump transmission data can be obtained by calculating and analyzing. The analytical data are compared with data related to a similar machine room to analyze the energy cost and the equipment status of the machine room. Factors affecting energy efficiency are analyzed, the system operating strategy is optimized, the system comprehensive energy efficiency is improved, and the operation cost can be reduced.

The invention discloses a modeling method of a reverse osmosis seawater desalination system. The modeling method comprises the following steps: establishing an operation cost model of the reverse osmosis seawater desalination system; constructing a dynamic operation model and an operation boundary condition of the reverse osmosis seawater desalination system; and constructing a model of the reverse osmosis seawater desalination system by taking the lowest operation cost model as an objective function and taking the dynamic operation model and the operation boundary condition as constraint conditions. Constructing a mathematical model of the operation cost of the reverse osmosis seawater desalination system, optimizing the operation strategy of the reverse osmosis seawater desalination system, and reducing the operation cost; factors influencing the operation cost, such as the chemical treatment investment cost, the operation cost of a low-pressure centrifugal pump in the water taking process, the operation cost of equipment in the reverse osmosis process, the fixed investment cost of a reverse osmosis membrane, the system maintenance cost and the labor cost, are integrated in the dynamic optimization model, so that the optimal operation point of the reverse osmosis seawater desalination system can be accurately found.

The invention provides a combined heat and power scheduling method based on convex relaxation, and the method builds a simplified thermodynamic model to describe the water temperature change in a regional heat supply system; non-convex equality constraints and bilinear constraints in the model are relaxed by using cone relaxation and polyhedron relaxation methods, so that a convex CHPD model is obtained, a relaxed solution obtained based on the model is further projected to a feasible solution space, and finally, the CHPD solving quality and calculation performance can be improved. According to the invention, the simplified thermodynamic model about the temperature change of the heat supply network is established, and the mathematical complexity of a node method used in a traditional heatsupply network modeling method is reduced; a convex CHPD model is constructed by utilizing second-order cone relaxation and polyhedron relaxation, and the hydraulic and thermal conditions of DHS are fully simulated. The invention further provides a self-adaptive boundary tightening strategy to improve the quality of the relaxation solution, and the local optimal solution of the combined heat and power scheduling problem can be quickly and effectively found.

The invention relates to the technical field of electric energy service management, in particular to a pneumatic-electric complementary heating demand response control system. The pneumatic-electric complementary heating demand response control system comprises an intelligent heating demand response management main station system, a power grid dispatching system, and at least one user side electric complementary heating control management substation; an output end of the power grid dispatching system is communicated with an input end of the intelligent heating demand response management main station system; and the intelligent heating demand response management main station system is in two-way communication with the user side electric complementary heating control management substation. The pneumatic-electric complementary heating demand response control system realizes the electric boiler control instruction establishment and actuation and the operation data monitoring and analysis through constructing the intelligent heating demand response management main station system and the user side electric complementary heating control management substation, facilitates to control the electric boiler operation, meanwhile, achieves the purpose of absorbing the wind power remained capacity, saves natural gas and petroleum resources, provides the demand response to the power grid peak shaving, and provides auxiliary services to the power grid operation.

The invention relates to the technical field of photo-thermal power generation, in particular to a photo-thermal power station heat collection field power generation efficiency evaluation method and system, which can provide more accurate and real-time power generation efficiency evaluation. The method comprises the steps that design parameters, historical operation data and historical heat collection efficiency of a heat collection field of the photo-thermal power station are collected; according to the design parameters of the heat collection field of the photo-thermal power station, a simulation model of the heat collection field is constructed to simulate the operation condition of the heat collection field of the photo-thermal power station, and the simulation model comprises a minute-level mechanism model and an artificial intelligence correction module; inputting the historical operation data into the simulation model to obtain historical predicted heat collection efficiency; performing deviation analysis on the historical predicted heat collection efficiency and the historical heat collection efficiency to obtain a model correction index; the model correction index is substituted into the simulation model, the model is corrected, and a heat collection efficiency evaluation model is obtained; and acquiring real-time operation data, and inputting the real-time operation data into the heat collection efficiency evaluation model to obtain the power generation efficiency of the heat collection field.

The invention discloses an energy storage system operation method and system for providing multiple services. The method comprises the steps of determining multiple service types provided by an energystorage system; establishing a single value evaluation model corresponding to the single service type; based on the single value evaluation model, establishing a multiple value evaluation model of multiple service types provided by the energy storage system; and optimizing the charging and discharging curve of the energy storage system by taking the maximum benefit as a target according to the multiple value evaluation model of the energy storage system, and obtaining an optimized operation strategy when multiple service types are provided by the energy storage system.

The invention discloses a distributed energy supply cooling, heating and power load prediction model system and method, and the system comprises: a physical layer module which is provided with a plurality of sensing devices, is disposed at each point of an energy supply region of an energy center, and is used for providing real-time onsite data; a data layer module which is used for storing data detected at each point location of the energy supply area of the energy center; a calculation layer module whcih is used for processing the data from the data layer module; and an application layer module whichis used for instructing the energy supply area of the energy center to select the energy storage capacity of the energy storage equipment according to the cold-heat-electricity prediction result. By adopting the technical scheme, the energy center can select the energy storage capacity of the energy storage equipment according to the cold-heat-electricity prediction result, so that accurate prediction of the cold-heat-electricity load is realized, and the operation strategy of the energy storage device of the energy center and the distribution scheme of the cold-heat-electricity loadare optimized.

The invention discloses a product correlation degree quantitative analysis method based on an Amazon platform. The method comprises the steps of obtaining a reverse data link between a source ASIN anda plurality of associated ASINs through a crawler technology, calculating the proximity of the reverse data link corresponding to the associated ASINs under a single dimension, calculating the proximity of the associated ASINs under a plurality of dimensions, and calculating the similarity and relevancy between the source ASIN and the associated ASINs. The method comprises the steps of obtaininga plurality of reverse associated data chains between a source ASIN and a plurality of other associated ASINs through a crawler technology; according to the method, the association degree between thesource ASIN and the plurality of associated ASINs is quantitatively analyzed by establishing the association degree quantitative model, so that a seller can be effectively helped to accurately find the associated products, the operation strategy is optimized, and the product flow is improved.

The invention relates to an optimization method for operating parameters of a fluid heating snow melting system based on a multi-objective programming, and relates to an optimization method for operating parameters of the fluid heating snow melting system. The invention solves the problems that the prior art can not calculate the snow melting effect and the operation cost of the system and can notdetermine the optimal operation parameters. The invention comprises the following steps: 1. Establishing a snow melting effect database of a fluid heating snow melting system; 2, calculate that snowmelting effect of the fluid heat snow melting system under a certain working condition; 3, obtain that operating cost M of the fluid heat snow melting system in the range of the unit area road body according to the heat flux q; IV. Evaluation of M; 5. Establishing the optimization model of the operation strategy of the fluid heating snow melting system by using the method of multi-objective programming; 6, obtaining the optimal operation parameters of the fluid heat snow melting system under a certain working condition; 7, repeat that step 6 to obtain the control chart of the operation parameters of the fluid heat snow melting system under the full working condition. The invention is used in the field of transportation engineering.

The invention provides a water conservancy safety detection method based on AI edge calculation, and the method comprises the steps: deploying a sensor in a water conservancy system according to the installation and coding of the sensor, coding the sensor, and recording the geographic position information and measurement physical quantity of the sensor; setting measurement parameters, and setting a measurement interval value and a threshold value of each sensor; data linkage setting: defining data linkage selection data, and triggering pump IO output when the data reaches a specific interval threshold value; the method comprises the following steps: monitoring sensor data in real time, if the data is abnormal, starting a video AI to check, comparing whether the result is consistent, if the video AI confirms that the sensor data is abnormal, intercepting a real-time video as sample data, sending the sample data to a cloud server, triggering a corresponding alarm according to the abnormal condition, and notifying related personnel to process. The accuracy and timeliness of abnormal condition detection are improved, and a powerful guarantee is provided for safe operation of a water conservancy system.

The invention relates to an offshore wind power plant reactive voltage regulation method based on deep learning, and the method comprises the steps: collecting the historical operation data of an offshore wind power plant, constructing an LSTM neural network model, training the LSTM neural network model through employing the preprocessed historical operation data of the offshore wind power plant, adjusting the weight and bias in a network, and obtaining the reactive voltage of the offshore wind power plant. And obtaining operation data of the offshore wind power plant in real time, inputting the operation data obtained in real time into the trained LSTM neural network model to obtain a predicted value of a reactive power demand and a grid-connected point bus voltage amplitude, and according to the predicted value of the reactive power demand and the grid-connected point bus voltage amplitude, combining an operation constraint and a control objective function of the wind power plant. And dynamically adjusting the reactive voltage by adopting a hybrid optimization algorithm. According to the invention, the time sequence characteristics and dynamic changes of the wind power plant can be accurately captured, so that the reactive power and voltage of the offshore wind power plant can be accurately predicted and adjusted.

The invention relates to the technical field of transformer substations, in particular to a transformer substation multi-node energy consumption prediction method, which comprises the following steps that: a data acquisition and integration module collects energy consumption data, meteorological data and equipment state data from multiple channels of a transformer substation monitoring system, a meteorological system and historical energy consumption records, and integrates the energy consumption data, the meteorological data and the equipment state data; extracting features helpful for energy consumption prediction from the original data; by accurately predicting the energy consumption of each node of the transformer substation, the energy distribution of the electric power system can be better managed, unnecessary energy waste is reduced, the energy utilization efficiency is improved, the energy consumption prediction is beneficial to optimizing the operation strategy of the electric power system, reducing the use of fossil fuel, and further reducing the emission of greenhouse gases. The method has positive influence on environmental protection and climate change coping, energy conservation and emission reduction are achieved, meanwhile, the operation cost of a power system can be reduced, economic benefits are improved, and power waste and economic losses caused by too high energy consumption can be avoided through prediction and optimization.

The invention provides a thermal power coupling battery data monitoring and safe operation optimization method, and relates to the technical field of electric energy monitoring optimization. Comprising the following steps: establishing a combined dynamic simulation model by combining preprocessed historical operation data with real-time operation data, and simulating collaborative operation characteristics of a thermal power generating unit and a battery pack under different load conditions through the combined dynamic simulation model; and analyzing the cooperative operation characteristics of the thermal power generating unit and the battery pack based on the combined dynamic simulation model, determining power distribution, temperature control requirements and response time, and dynamically adjusting the output power of the thermal power generating unit and the charging and discharging power of the battery pack in combination with real-time load data. According to the method, the real-time operation data and the historical operation data of the thermal power generating unit and the battery pack are fused, and the dynamic simulation algorithm is adopted to construct the joint dynamic simulation model, so that accurate description of the cooperative operation characteristics of the thermal power generating unit and the battery pack under different load conditions is realized, and a basis is provided for operation strategy optimization.

The invention relates to the technical field of station management, and particularly provides an intelligent station management system and method based on a data medium station, and the system comprises a data receiving module and a data application module. The data receiving module is used for acquiring application data and production operation data corresponding to a plurality of regional stations; and the data processing module is used for determining the current operation condition of each regional station based on the application data set and the production operation data, and performing data comprehensive analysis and production regulation and control based on the current operation condition. According to the intelligent station management system based on the data medium station, fusion of application data of each regional station in station management and production operation data of the industrial data medium station is realized through the data medium station, a comprehensive view angle is provided for power plant station management, and optimization of an operation strategy and improvement of management efficiency are facilitated.

The invention provides a fan increased generating capacity statistical method and a deicing system. A fan comprises a power generation host, a control processor and a heating device, wherein the heating device is used for deicing fan blades. The method includes the steps that when the fan is switched from a non-icing period state to an icing period state, it is determined that the icing period of the fan starts, wherein the non-icing period state and the icing period state are two working states of the fan; the real-time generating capacity of the fan and the real-time power consumption of the heating device are obtained within the icing period; and according to the real-time generating capacity and the real-time power consumption, the real-time increased generating capacity of the fan in the icing period is counted. According to the fan increased generating capacity statistical method and the deicing system, accurate statistics can be conducted on the total increased generating capacity of the fan with the icing period as the period, income situations of the fan under different working conditions can be accurately known, operation strategies of the fan can be optimized, and therefore the operation benefit of the fan in the icing period is improved.

The invention relates to the technical field of micro-grid communication, in particular to a micro-grid controller and a micro-grid communication method applied by the micro-grid controller, and realizes real-time data acquisition and monitoring of terminal equipment of a micro-grid by integrating a main controller, a micro photovoltaic inverter, a micro energy storage device and a communication module. And the main controller analyzes and processes the collected data, formulates a dynamic load adjustment plan, and optimizes power resource allocation according to the real-time electricity price and supply and demand conditions, and the method introduces an elastic load management mechanism, can automatically adjust the user load according to the real-time condition, and significantly improves the energy utilization efficiency. In addition, by implementing switch control and a feedback mechanism, the system can monitor the flow direction of electric power in real time, and the stability and reliability of power supply are ensured. According to the invention, through intelligent data analysis and decision making, the purpose of improving the overall operation efficiency and the user experience is achieved.

The present invention relates to the technical field of server heat dissipation, and in particular to a method, device and computer storage medium for heat dissipation control of a server. The method comprises: obtaining temperature values, access flow data to be processed and processing speed data; determining the state value of the server; forward displacing the temperature sequence, and performing temperature delay correction according to the correlation between the displaced sequence and the state sequence obtained after the dislocation, to obtain a target sequence; determining the abnormal change moment according to the target sequence and the state sequence, and then determining the temperature change time period, and determining the change extension index of each abnormal change moment according to the numerical distribution of the temperature value in each temperature change time period; determining the heat dissipation power at the current moment according to the change extension index of the abnormal change moment before the current moment, and the state value and temperature value at the current moment. The present invention can reduce the delay effect of temperature control, optimize the operation strategy of heat dissipation, realize active heat dissipation control, and improve energy efficiency.

The invention provides a wind speed-power curve abnormal point identification method and device, and belongs to the technical field of wind power generation. The method comprises the following steps: acquiring a plurality of wind speed-power data points of a wind turbine generator in a preset time period; identifying the plurality of wind speed-power data points by using different curve abnormal value identification methods to obtain wind speed-power abnormal data points under the different curve abnormal value identification methods; and determining the same wind speed-power abnormal data points under different curve abnormal value identification methods as wind speed-power target abnormal data points. According to the method, the density clustering algorithm and the wind speed segmentation algorithm are fused, so that accurate identification of the abnormal points of the wind turbine generator is realized, the operation efficiency is improved, the maintenance cost is reduced, and safe and stable operation of the generator is ensured.

The invention belongs to the technical field of post-processing, and particularly provides a vehicle end DPF passive regeneration performance evaluation method, device and equipment and a storage medium. The method comprises the following steps that original emission data of operation of different vehicles is collected; screening the original emission data to obtain effective data; dividing the effective data into a plurality of sub-data according to the vehicle number; wherein the data of each vehicle number is recorded as subdata; dividing the sub-data into a plurality of sub-data fragments according to the active regeneration state of the vehicle; calculating the increasing rate of the carbon load in each sub-data fragment of each vehicle along with the running time of the engine; calculating a passive regeneration evaluation coefficient according to the increase rate of the carbon loading capacity; and evaluating the passive regeneration performance in the set state according to the passive regeneration evaluation coefficient. By calculating the increasing rate of the carbon load in each sub-data fragment of each vehicle along with the running time of the engine and calculating a passive regeneration evaluation coefficient according to the increasing rate, quantitative evaluation of the passive regeneration performance is realized.

The invention discloses a transformer substation operation management method and system based on super capacitor energy storage, and the system comprises a super capacitor module disposed in a transformer substation, and also comprises a data collection unit, a state monitoring unit, an environment monitoring unit, a DC guarantee unit, an early warning unit and an energy management unit which are disposed in the transformer substation. The data acquisition unit is used for acquiring operation state data of a super capacitor module in the transformer substation, and the operation state data comprises voltage and current data; the state monitoring unit is used for monitoring equipment in the transformer substation in real time; the environment monitoring unit is used for monitoring environment parameters in the substation; the energy management unit is used for adjusting a charging and discharging strategy of the super capacitor module according to a load demand; the direct current guarantee unit is connected with a direct current bus of the transformer substation in parallel and used for charging when alternating current is normal, the direct current guarantee unit is not only used for supplying power to a load, but also used for supplementing electric energy for the super-capacitor module, and the scheme is used for improving the operation efficiency of the super-capacitor module.

The invention relates to the technical field of intelligent parking, in particular to a parking lot package matching method and device, electronic equipment and a storage medium, and the method comprises the steps: receiving parking renting demand information inputted by a user in a user interface, and carrying out the structural processing of the parking renting demand information, and obtaining a user demand feature vector; and extracting a feature vector from at least one package in the parking lot package resource library to obtain a package feature vector corresponding to the package. According to the method, the renting demand of the user and the parking lot package resources are vectorized respectively, and intelligent matching and integrating degree calculation are performed based on the feature vectors, so that conversion from a fixed package to demand driving is realized. According to the method, the single package and the combined package with high integrating degree can be automatically recommended to the user, the matching accuracy of the package and the user demand is improved, the time for the user to select the package is shortened, the selection cost and parking expenditure of the user are reduced, meanwhile, the parking lot is assisted to digest idle resources, and the operation strategy is optimized.

The invention relates to an operating method for a hybrid vehicle which is driven on a circuit. A hybrid vehicle has an internal combustion engine and a coolable electrical system having at least one connectable electrical machine, power electronics and energy store. The electrical machine can be operated as a motor or a generator. The acceleration profiles of the vehicle, power profiles of the electrical system and temperature profiles of the electrical system are recorded and stored during the respective lap that is being driven and, furthermore, the profile of the performance of the electrical system is optimized with respect to the thermal load capacity of the electrical system in the respective next lap. This allows an optimum power profile of the electrical machine during real operation when a circuit is driven around repeatedly.