8results about How to "Balanced energy consumption" patented technology

The application relates to a kind of distributed unmanned aerial vehicle ad hoc network routing methods based on deep reinforcement learning, comprising;According to Markov decision process, the deep reinforcement learning architecture of unmanned aerial vehicle communication network is built;Running Dijkstra algorithm sends original data packet from source node to destination node and generates original training data according to the routing process of original data packet to pre-train the deep reinforcement learning architecture;The coordinates of the destination node D of target data packet are input, the next hop node B of current node A is obtained using the pre-trained deep reinforcement learning architecture, and target training data is generated, and the deep reinforcement learning architecture is retrained according to the original training data and target training data;Next hop node B is used as starting node, until the next hop node is the destination node, the routing of target data packet is completed, and the application can enhance the robustness of network and improve the life of unmanned aerial vehicle communication network.

The utility model discloses a multilayer combined filter structure of desulfurization dust remover, including tower body, at least one layer composite filler layer is arranged in the tower body, the composite filler layer is multilayer structure, and the regular shaped filler area, transition flow guide area, bulk packing area and support grating from top to bottom include successively, the regular shaped filler area and bulk packing area outside all are provided with fixed frame, the regular shaped filler area and bulk packing area are filled in the corresponding fixed frame respectively, through the high specific surface area of bulk packing, can effectively strengthen gas liquid contact in bulk packing area, improve mass transfer rate, and the low resistance characteristic of regular shaped filler can avoid partial pressure drop surge in regular shaped filler area, realizes the balance of desulfurization efficiency and energy consumption, reduces operating energy consumption while guaranteeing desulfurization effect.

The application provides an environment monitoring method and device based on wireless sensor network joint self-learning, and relates to the field of Internet of Things monitoring.The method comprises the following steps: acquiring an original time sequence and determining the total iteration number of each edge node;at each edge node, the original time sequence is normalized, segmented, aggregated and approximately calculated, and symbolized according to the total iteration number, to generate a discrete finite symbol sequence;the discrete finite symbol sequence is subjected to abnormal probability calculation to generate a single local anomaly detection threshold;at the convergence node, the single local anomaly detection threshold is subjected to weighted fusion to obtain a weighted threshold;the single local anomaly detection threshold is updated through the weighted threshold until the iteration ends, the local anomaly detection threshold is output, and the anomaly detection of the environment is completed.The scheme effectively reduces the storage and calculation costs, realizes the communication between nodes, balances the energy consumption of the edge nodes, and improves the detection accuracy.

The application discloses a kind of building energy consumption regulation and control optimization method, system, terminal and medium, it is related to energy consumption regulation and control technical field, its technical scheme main point is: obtaining the output fluctuation data of generator set and the power load fluctuation data of target building;Determine the upper limit value and lower limit value of power load of target building at corresponding target time;Determine the dispatching optimization interval of target building at corresponding time;With the sum of all target buildings control optimization value minimum as optimization goal to establish control optimization model;Solving obtains the energy consumption regulation and control strategy of each target building.The application uses power load control, both considers the fluctuation trend brought by the randomness and uncertainty of new energy in power system in generation side, also considers the demand change trend of each building in power consumption side, can realize the balanced distribution of each building energy consumption under the demand intensity of each building with small error.

This invention relates to the field of air conditioning control technology, and in particular to a control method, device, equipment, and storage medium for a dual-outlet wall-mounted air conditioner. The method, based on a structure of dual independent air outlets and dual independent air ducts, solves the technical problems of traditional single-outlet wall-mounted air conditioners, such as direct cold air blowing, reduced cooling capacity due to reduced airflow speed, and poor scene adaptability, through control rules that fix the initial air outlet mode upon startup, determine real-time parameters, and execute three modes in a graded manner. Specifically, the forced execution of the front air outlet mode upon startup can quickly establish indoor cooling capacity to match the user's immediate cooling needs. Based on real-time operating parameters, it achieves unattended confirmation of the pending execution mode, reducing user operating costs. The three modes—front air outlet, bottom air outlet, and dual air outlet—correspond to conventional cooling, anti-direct-blow dehumidification, and rapid temperature adjustment in large spaces, respectively. Through the opening and closing of the air outlets and the coordinated adjustment of core components, it improves user comfort while ensuring cooling efficiency, balancing cooling effect, energy consumption, and user experience.

This application discloses a method, apparatus, equipment, storage medium, and product for balancing energy consumption in a pumping unit well group, relating to the fields of industrial automation and energy efficiency optimization technology. The method includes: acquiring pumping unit electrical parameter data based on IoT devices and an oilfield database; calculating the power parameters and system efficiency data of each pumping unit based on the electrical parameter data; and accurately reflecting the operating status and power consumption of each pumping unit through real-time electrical parameter data acquired from IoT devices and the oilfield database. By inputting the power parameters and system efficiency data of each pumping unit into a pre-constructed pumping unit well system model, the corresponding target motor frequency is obtained. The pumping unit power is adjusted in real-time according to the target motor frequency, enabling dynamic calculation and optimization of the motor frequency, thereby achieving energy balance in the well group. By adjusting the motor frequency in real-time, it is ensured that the pumping units always operate at their optimal operating points, improving the control stability of the well group.

The utility model discloses a cooling system of integrated compressor relates to compressor technical field, wherein, the cooling system of integrated compressor includes compressor body, inverter module, rectifier module, refrigerant pipeline and controller component, and the refrigerant of refrigerant pipeline is in series and flows through inverter module, rectifier module and compressor body. Through above -mentioned technical scheme, the optimization integration of cooling flow channel is realized, and the pipeline redundancy caused by multiple independent cooling systems is eliminated. The heat of different components is absorbed in series flow channel in turn, and the refrigerant utilization efficiency is improved. Modular flow channel design makes the system can quickly adapt to different models compressor, reduces the equipment transformation cost. The controller grading regulation function of refrigerant flow effectively balances the cooling efficiency and energy consumption index, reduces the refrigerant consumption while maintaining the component working temperature.

The application discloses a post-disaster unmanned aerial vehicle deployment method based on a worst-case flexible strategy evaluation, and comprises the following steps: acquiring the current position of an unmanned aerial vehicle cluster, a task target position, residual energy, communication energy consumption, flight energy consumption and the maximum communication distance of the unmanned aerial vehicle; constructing an energy consumption model of the unmanned aerial vehicle cluster based on the communication energy consumption and the flight energy consumption, and constructing a channel model based on the current position of the unmanned aerial vehicle cluster, the task target position and the maximum communication distance of the unmanned aerial vehicle; setting an optimization constraint target of the unmanned aerial vehicle cluster; and based on the energy consumption model, the channel model and the residual energy of the unmanned aerial vehicle cluster, the optimization constraint target is used to optimize the unmanned aerial vehicle cluster, so that the optimal flight strategy of the unmanned aerial vehicle cluster is acquired. The application can effectively avoid high-risk flight positions, and finally achieve the balance between coverage and energy consumption.