13 results about "Demand load" patented technology

The invention discloses a hydrothermal coupling dynamic simulation method and system for sudden supply and demand change of a long-distance heat supply pipe network, and belongs to the technical field of central heating, and the technical scheme is as follows: obtaining topological structure parameters, elevation, pipeline structure parameters, thermal insulation layer structure parameters and environmental parameters of the heat supply pipe network; constructing a node incidence matrix, and setting a heat source parameter, a physical property parameter, an abrupt change working condition parameter and a space step length; initial hydraulic calculation is conducted, and flow of all pipe sections and pressure distribution of all nodes of the heat supply pipe network are obtained; time-marching calculation is carried out on a temperature field in the pipe network when supply and demand loads suddenly change, heat supply medium physical property parameters and a pipe network hydraulic state are synchronously updated in the temperature field calculation process, and hydraulic and thermal coupling dynamic simulation is achieved; and on the basis of coupling dynamic simulation, the heat storage or heat release process of the heat supply pipe network under the supply and demand load sudden change working condition is analyzed. The dynamic simulation method and system for the supply and demand sudden change hydrothermal coupling of the long-distance heat supply pipe network have the beneficial effect that the dynamic simulation method and system for the supply and demand sudden change hydrothermal coupling are provided.

The invention relates to the technical field of power system frequency regulation, in particular to a virtual power plant frequency regulation method and system based on supply-demand collaboration, and the method comprises the steps: obtaining the demand load, voltage data and power supply quantity data of a power grid in real time; according to the fluctuation characteristics of the power supply quantity data in each detection time period, the correlation degree between the power supply quantity data and the demand load and the peak-valley value time synchronization degree, the supply-demand stability coefficient of each detection time period is obtained, and the deformation degree of the voltage data in each detection time period is combined; and according to the difference between the voltage peak-valley value when the power supply amount fluctuates and the voltage peak-valley values at other moments, and the discrete degree of the voltage peak-valley value when the power supply amount fluctuates, obtaining a frequency retention coefficient of each detection time period, thereby obtaining a droop coefficient of each detection time period, and adjusting the frequency of the next detection time period. According to the method, the droop coefficient of each detection time period is adaptively acquired, so that the frequency regulation effect of the virtual power plant is improved.

The application discloses a kind of long supply and demand mutation water-heat coupling dynamic simulation method and system of heat supply pipe network, belong to central heating technical field, technical scheme is, obtaining heat supply pipe network topological structure parameter, elevation, pipe structure parameter, insulation layer structure parameter and environmental parameter;Matrix is constructed to node association, sets heat source parameter, physical property parameter, mutation working condition parameter and space step;Initial hydraulic calculation is carried out, and the flow of each pipe section of heat supply pipe network and the pressure distribution of each node are obtained;Temperature field in pipe network is calculated when supply and demand load mutation occurs Time advancing, and heat medium physical property parameter and pipe network hydraulic state are updated synchronously in temperature field calculation process, the coupling dynamic simulation of water and heat is realized;On the basis of coupling dynamic simulation, the heat storage or heat release process of heat supply pipe network under supply and demand load mutation working condition is analyzed.The beneficial effects of the application are: provide a kind of long supply and demand mutation water-heat coupling dynamic simulation method and system of heat supply pipe network.

This application provides a joint planning method for power systems, including establishing a shared energy storage joint planning model based on the power system's topology, and using a two-level optimization method to solve the shared energy storage joint planning model to obtain the energy storage system's operation plan. The optimization objective is to optimize the overall economic performance of the power system at the upper level, and the operational performance of the energy storage system in a typical scenario is used as the lower level optimization objective. The shared energy storage joint planning model uses a fuzzy chance-constrained programming method to describe the source-side model of wind turbine output, the load-side model describing the impact of price incentives on user demand load response, and the storage-side model considering the lifespan of the energy storage power station. This application considers the randomness and uncertainty of the power system's source-side and load-side operation, thereby achieving power system dispatch balance, improving energy utilization efficiency, and reducing overall system cost.

The multi-split system comprises an outdoor unit and at least two indoor units, the outdoor unit comprises an outdoor temperature detection module, and when the indoor units operate in a refrigeration mode, refrigeration load parameters of rooms corresponding to the indoor units are determined; the expected indoor temperature at each moment is determined; according to the refrigeration load parameter, the difference between the indoor temperature at the current moment and the expected indoor temperature, the difference between the outdoor temperature and the indoor temperature and the control period, the real-time demand load is determined; and determining the target evaporation temperature according to the real-time demand load, and determining the compressor frequency according to the target evaporation temperature. The frequency of the compressor can be matched with the real-time demand load, the under-regulation problem of a large-load and small-temperature-difference scene and the over-regulation problem of a small-load and large-temperature-difference scene are solved, the air conditioner capacity is matched with the building load, room temperature fluctuation is reduced in medium and small loads, power consumption increase caused by frequent starting and stopping is avoided, and the indoor unit capacity is improved in the large load; the room temperature change speed is accelerated; and the user comfort is improved.

The application discloses a control method and air conditioning unit of a multi-connected air conditioner based on load self-adaption, relates to the technical field of air conditioner control, and solves the technical problems of frequent start and stop of the unit, room temperature fluctuation and user discomfort caused by the mismatch between output capacity and demand load, passive control mode and insufficient self-adaptive adjustment of the multi-connected air conditioner when running at night under small load. In the application, each indoor unit is independently controlled, a load self-adaptive matching algorithm is adopted, room load is calculated in real time, the matched output capacity load is generated according to the real-time load change in each room, and independent control logic is generated; the outdoor unit calculates the supply capacity according to the parameter change of each indoor unit, realizes load self-adaptive adjustment based on the combination control of the compressor frequency and the fan rotating speed, and realizes the real-time supply-demand matching of the load in each room by the real-time matching and automatic optimization iteration of the output capacity of the outdoor unit and the room load without increasing hardware.

The application relates to a kind of intelligent micro-grid frequency modulation peak shaving and power distribution methods based on photovoltaic power generation, and relates to the field of intelligent micro-grid, comprising: obtaining predicted fluctuation degree and energy supply deviation amplitude by analysis, obtaining fluctuation degree by combining predicted fluctuation degree and historical fluctuation degree, obtaining frequency modulation coefficient and peak shaving distribution coefficient according to fluctuation degree and energy supply deviation amplitude configuration; randomly generate power distribution scheme, according to predicted photovoltaic power generation power sequence and predicted demand load power sequence, carry out peak shaving and frequency modulation analysis, calculate distribution fitness according to frequency modulation coefficient and peak shaving distribution coefficient, carry out iterative optimization evaluation, obtain optimal distribution scheme to carry out power distribution. Through the application, the technical problems that traditional methods cannot efficiently cope with load fluctuation and photovoltaic power generation deficiency, and it is difficult to ensure that energy storage units can respond in time and provide stable and accurate power support, resulting in that micro-grid has large operation fluctuation and high frequency modulation and peak shaving difficulty during high load period can be solved.

A multi-split air conditioner installation verification system includes a processing module configured to: identify hardware configuration; determine the corresponding detection path; calculate the target verification frequency of the compressor based on the current environment and demand load, and configure a detection scenario corresponding to the current environmental load and demand load; calculate the theoretical expected temperature change value of the test point based on an attenuation model under the detection scenario; detect the real-time temperature corresponding to the test point; determine whether the real-time temperature meets the preset theoretical tolerance range based on the theoretical expected temperature; and identify the pipe connection error corresponding to the test point when the preset theoretical tolerance range is exceeded. The multi-split air conditioner installation verification system provided in this application, through dynamic modeling and multi-mode collaboration, transforms manual acceptance into an automated pipe verification system based on dynamic thermodynamic feedback, and is particularly suitable for identifying cross-connection or misconnection problems that are prone to occur in four-pipe multi-split air conditioners in complex industrial environments.

The application relates to the technical field of power system frequency regulation, in particular to a virtual power plant frequency regulation method and system based on supply-demand cooperation, which comprises the following steps: acquiring the demand load, voltage data and power supply data of a power grid in real time; acquiring the supply-demand stability coefficient of each detection period according to the fluctuation characteristics of the power supply data, the correlation degree between the power supply data and the demand load and the time synchronization degree of peak-valley values, combining the deformation degree of the voltage data in each detection period, the difference between the voltage peak-valley value during power supply fluctuation and the voltage peak-valley value at other time, and the discrete degree of the voltage peak-valley value during power supply fluctuation, acquiring the frequency retention coefficient of each detection period, and acquiring the droop coefficient of each detection period to regulate the frequency of the next detection period. The application adaptively acquires the droop coefficient of each detection period, thereby improving the frequency regulation effect of the virtual power plant.

Embodiments of the present application disclose a kind of autonomous planning method, system and medium for giant heterogeneous constellation observation task;The method comprises: after receiving the original task set information of upper injection in the first satellite in heterogeneous constellation, the satellite that meets the task type and demand load in the first satellite network corresponding to itself sends task commission information;Wherein, the first satellite network includes at least one satellite of each load category in the heterogeneous constellation The second satellite that receives task commission information in the first satellite network constructs the second satellite network based on the load category of itself, which is the same as the load category in the heterogeneous constellation Satellite;The second satellite decomposes task according to the task commission information, to obtain meta task set;The second satellite determines the task execution satellite for the meta task set in the second satellite network based on the set contract bidding strategy, so that the task execution satellite executes the original task set.

The multi-split system comprises an outdoor unit and at least two indoor units, the outdoor unit comprises an outdoor temperature detection module, and when the indoor units operate in a heating mode, heating load parameters of rooms corresponding to the indoor units are determined; the expected indoor temperature at each moment is determined; according to the heating load parameter, the difference between the expected indoor temperature and the indoor temperature at the current moment, the difference between the indoor temperature and the outdoor temperature and the control period, the real-time demand load is determined; and determining a target condensation temperature according to the real-time demand load, and determining a compressor frequency according to the target condensation temperature. The frequency of the compressor can be matched with the real-time demand load, the under-regulation problem of a large-load and small-temperature-difference scene and the over-regulation problem of a small-load and large-temperature-difference scene are solved, the air conditioner capacity is matched with the building load, room temperature fluctuation is reduced in medium and small loads, power consumption increase caused by frequent starting and stopping is avoided, and the indoor unit capacity is improved in the large load; the room temperature change speed is accelerated; and the user comfort is improved.

The invention discloses a control method of an air conditioning system, which comprises the following steps of: learning a refrigeration load parameter of a room corresponding to an indoor unit according to historical learning data of the indoor unit and a load characteristic learning model, and obtaining the refrigeration load parameter through self-learning; and according to the expected indoor temperature, the refrigeration load parameter, the indoor temperature, the outdoor temperature and the control period at the current moment, the demand load at the current moment is determined, and operation parameters of the air conditioning system are controlled according to the demand load. The refrigeration load parameters obtained through self-learning can reflect the current load state of the room more truly, and the determined demand load at the current moment can be matched with the real-time load of the room corresponding to the indoor unit, so that the operation parameters of the air conditioning system are controlled through the real-time demand load of the room, and the operation efficiency of the air conditioning system is improved. Therefore, the operation state of the air conditioning system can be matched with the real-time demand load of the room, load following is achieved, control is conducted, and the problems of under-regulation, over-regulation and room temperature fluctuation are avoided.

The invention relates to a direct-current micro-grid dispatching method, device and system. The method comprises the following steps: acquiring a cost parameter, electricity price information and an initial demand load capacity of the DC micro-grid; inputting the cost parameter, the electricity price information and the initial demand load into a pre-constructed scheduling model; the scheduling model comprises a cost model, a load demand response model and an electricity price optimization model; the cost model is used for optimizing the total cost, the load demand response model is used for constraining the incidence relation between the scheduling load rate and the electricity price, and the load demand response model is used for optimizing the load scheduling rate; based on a preset constraint condition, solving the scheduling model to obtain a load scheduling scheme; the load scheduling scheme comprises a target load scheduling rate and a target scheduling time period; the target load scheduling rate is used for indicating that part of the demand load capacity in the initial demand load capacity is scheduled to the target scheduling period. According to the scheme, the power utilization cost of a user is reduced.