61 results about "Grid friendly" patented technology

The invention provides a wind power plant AGC optimization control method and system based on model prediction control, and relates to the technical field of model control, and the method comprises the steps: building an adaptive prediction model, carrying out the online identification of parameters through a recursive least square method, constructing an active power optimization objective function, solving a control instruction sequence, designing a feedback compensator, and correcting a control instruction. And finally, issuing to each fan to execute and realize closed-loop control. According to the method, the AGC control precision of the wind power plant can be improved, the power fluctuation is reduced, and the power grid friendliness and the adaptability of an AGC control system are enhanced.

The invention relates to the technical field of wind-solar storage power station operation control, and discloses a wind-solar storage multi-energy complementary power station cooperative operation method and system. The method comprises the following steps: constructing a wind-light fluctuation rate phase plane, defining a coupling stable elliptical region and generating a multi-source coupling state tag; an energy storage response performance plane is constructed, a dynamic dead zone threshold parameter is calculated, a dynamic respiration hexagonal boundary is established, and the penetration depth is calculated to generate an energy storage effective action instruction; and constructing a virtual energy gravitational potential energy field by utilizing an energy storage effective action instruction, calculating virtual potential energy heights of independent physical nodes and nonlinear flow resistance characteristics of a virtual energy transmission pipeline, and analyzing a virtual potential energy height difference and a virtual energy flow velocity to obtain a final power distribution scheme. Precise classification of fluctuation modes is achieved through geometric topology, the dynamic breathing hexagon is utilized to consider battery life and stability control requirements, the problem of lagging of multi-target optimization calculation is solved based on the physics field theory, and the operation efficiency of a power station and the friendliness of a power grid are remarkably improved.

The invention discloses a photovoltaic cluster flexible grid-connected regulation and control method and system, and the method comprises the steps: collecting the state data of a power distribution network node and a photovoltaic cluster, carrying out the data cleaning and timestamp alignment preprocessing, and obtaining a system state comprehensive data flow; constructing a multi-target optimization model containing power grid friendliness and photovoltaic power generation benefits based on the system state comprehensive data flow, and solving by utilizing a reinforcement learning algorithm to obtain a control strategy of a photovoltaic inverter and an energy storage unit; according to the control strategy, active power output and reactive power output of the photovoltaic inverter and charging and discharging power of the energy storage unit are controlled in a coordinated mode, and flexible grid connection of the photovoltaic cluster is achieved; and based on system response data, optimizing a control strategy by adopting an optimal decision tree algorithm, updating the reinforcement learning model, and establishing an optimized experience knowledge base. According to the invention, efficient flexible grid-connected regulation and control of the photovoltaic cluster are realized, and the problems of voltage out-of-limit, reverse power transmission and the like when large-scale photovoltaic access to the power distribution network are solved.

The invention discloses a charging control method and device, equipment and a storage medium, and the charging control method comprises the steps: obtaining the pile demand power of each charging pile when charging station limitation information sent by a far-end control platform is received; determining a charging adjustment coefficient of each charging pile according to the pile demand power of each charging pile, the rated work information corresponding to each charging pile and the charging station limitation information; and performing charging control on each charging pile in the charging station according to the charging adjustment coefficient of each charging pile. Through the above mode, the adjustment coefficient of each charging pile is dynamically calculated, power distribution is optimized to avoid overload, the method adapts to complex environments such as large-scale charging stations and district distributed pile groups, multi-scene dynamic adaptation and localization reliable control are realized, the system deployment complexity is significantly reduced, the resource utilization rate and the power grid friendliness are improved, and the method is suitable for large-scale charging stations, district distributed pile groups and other complex environments. And while the charging efficiency of the user is ensured, the power grid dispatching requirement is met, and the dependence on a centralized background is reduced.

The invention discloses a power grid friendly light storage direct current integrated grid-connected control method and device. The method comprises the following steps: acquiring a power grid dispatching instruction, a common connection point voltage / frequency deviation, the maximum power of a photovoltaic unit, the charge state of an energy storage unit and a power limit value in real time; calculating a total active / reactive power target value required to be injected into the power grid by the grid-connected converter based on the power grid dispatching instruction and the common connection point voltage / frequency deviation; generating a photovoltaic power / energy storage power dynamic adjustment coefficient in real time according to the power grid frequency deviation amplitude, the voltage out-of-limit grade and the charge state of the energy storage unit, and decomposing the total active power target value into photovoltaic unit / energy storage unit instruction power; adjusting the direct-current bus voltage based on the total active / reactive power target value in a grid-connected converter control layer to realize a power grid supporting function; in a local unit control layer, photovoltaic unit instruction power is tracked through a photovoltaic unit DC / DC converter, and energy storage unit instruction power is tracked through an energy storage unit bidirectional DC / DC converter.

The invention belongs to the technical field of power grid control, and particularly relates to a dynamic balance control method for a power grid-friendly electro-hydrogen fusion energy hub, which comprises the following steps of: acquiring multi-source data in real time, including a power grid frequency deviation value, wind-solar power generation power, an energy storage device charge state, a hydrogen storage tank pressure, an electrolytic hydrogen production device input power and a fuel cell output power; forming a multi-dimensional operation parameter set; according to the amplitude and duration of the power grid frequency deviation, an energy storage device, an electrolytic hydrogen production device and a fuel cell device are called in a layered manner for cooperative adjustment; the wind generating set is controlled to release kinetic energy of a rotor, and meanwhile the electrolytic hydrogen production device is adjusted to serve as an interruptible load to provide virtual inertia support; the energy storage device, the electrolytic hydrogen production device and the fuel cell device are called according to the priority for power compensation, and dynamic balance of the electricity-hydrogen fusion energy system is achieved. According to the method, the power grid frequency stability is remarkably improved, the energy storage configuration requirement is reduced, and the hydrogen energy utilization efficiency and the new energy consumption capability are improved.

The invention belongs to the technical field of power systems, and particularly relates to a day-ahead scheduling method for a building light storage direct-flexible energy microgrid with friendly power exchange. Comprising the steps that a mathematical model of the negative carbon building light storage direct-flexible energy microgrid is constructed, so that the complex operation characteristics of the negative carbon building light storage direct-flexible energy microgrid are converted into quantifiable optimization problems; wherein the mathematical model comprises a power generation constraint model, a power balance constraint model, a peak-valley difference and volatility constraint model, a storage battery constraint model, a phase change heat storage system operation constraint model and a water supply system operation constraint model; constructing a target function of an optimal scheduling model by taking the minimum total operation cost of the negative carbon building light-storage direct-flexible energy microgrid in a scheduling period as a target; wherein the total operation cost comprises an economic cost item, an environmental cost item and a power grid interaction optimization demand cost item. After the heat and water storage system is introduced, except for the friendly cost of a power grid, other costs are remarkably reduced.

The invention discloses a centralized charging station rolling optimization scheduling method and a centralized charging station rolling optimization scheduling system considering distribution network bearing capacity, and aims to improve the operation economy and the service capability of a charging station under the condition of meeting the safety constraint condition of a power distribution network. According to the method, based on a platform-station control two-stage cooperative control architecture, photovoltaic power generation, an energy storage device and an electric vehicle charging load are subjected to multi-energy cooperative optimization control, and power distribution network bearing capacity boundary constraint and differentiated charging demand modeling are introduced; and real-time optimization of charging power distribution, energy storage charging and discharging and power grid electricity purchasing and selling decision is realized through a rolling optimization algorithm. Through variable time scale scheduling combining fine granularity and coarse granularity, the short-term regulation and control precision is improved, the model complexity is reduced, the operation income and the charging service level of the charging station can be remarkably improved, and the power grid friendliness is improved. The method is suitable for various centralized electric vehicle charging stations containing distributed photovoltaic and energy storage, and particularly has outstanding advantages in the scene that the power supply capacity of a power distribution network is limited or dynamically changes.

The invention relates to a direct current side coupling type super capacitor-battery hybrid energy storage system. According to the energy storage system, a super-capacitor module and a battery module are directly connected on the direct current side through a bidirectional DC / DC converter, the super-capacitor module is connected with a power grid through a current source type converter, the battery module is connected with the power grid through a voltage source type converter, and a modularized and extensible topological structure is formed. The system has multiple differentiated working modes, cooperative efficient operation of the super-capacitor and the battery can be achieved according to working conditions, high-frequency / short-time power is preferentially borne by the super-capacitor, and the battery is responsible for steady-state energy adjustment. And meanwhile, by virtue of the boosting capability of the current source type converter, the super capacitor can support the power grid in a short time and strong manner in a deep discharging manner. And the battery module charges the super capacitor module through the bidirectional DC / DC converter, so that the influence of frequent charging of the super capacitor on the grid-side electric energy quality is reduced. The method can effectively reduce the aging loss of the battery, improves the energy storage utilization efficiency and the power grid friendliness, assists the new energy consumption and the safe and stable operation of the power grid, and has economic and social benefits.

The invention provides an electric energy quality adjusting method and system for a light storage coupling inverter, and the method comprises the steps: collecting the electrical parameters of a grid-connected point in real time, calculating the electric energy quality parameters, judging whether the parameters exceed the standard or not, generating a cooperative control strategy through integrating the photovoltaic real-time output, the energy storage charge state and the problem type, and finally controlling the inverter to execute compensation operation. The electric energy quality adjusting system comprises a monitoring module, a calculation and analysis module, a cooperative control decision module and an inverter control module, relates to the technical field of new energy power generation, can realize comprehensive treatment of various electric energy quality problems without additional special equipment and reuse of existing hardware resources, improves system economy and power grid friendliness, and is suitable for large-scale popularization and application. The method is suitable for a distributed optical storage grid-connected system.

The invention provides a multi-device cooperative charging system and method based on a W algorithm, and relates to the technical field of cooperative charging. Comprising a charging data collection module for collecting charging data; the weight assignment module is used for analyzing key factors influencing a charging and changing decision and assigning a weight by using a W algorithm; the comprehensive evaluation module is used for calculating a component matrix of each vehicle and each station, and carrying out weight distribution on each component matrix according to a qualified weight table; the charging and battery replacement distribution decision module distributes each vehicle to the station with the maximum evaluation value and updates the use state of the charging pile; and the real-time monitoring module monitors the station state and the vehicle progress in real time during energy supplementation, judges whether a change event occurs or not, and adjusts the matching of the vehicle and the station if the change event occurs. According to the invention, a pile-station cooperative intelligent charging network is constructed, the weight adaptive algorithm is driven through real-time data, vehicle distribution is dynamically optimized, and energy complementation scheduling with highest global efficiency, fastest response and friendly power grid is realized.

The invention relates to the technical field of energy supply control, in particular to a multi-mode energy supply control system and an optimization method thereof, and the system comprises an energy supply module, a main transmission channel, a main regulator, a plurality of parallel energy distribution branches, and a control regulation module. The energy distribution branch comprises a branch control node and an energy utilization outlet; the control regulation module periodically acquires energy demand data, calculates a global demand fluctuation index, and compares a threshold interval to generate an energy supply mode switching instruction; in the priority mode, the branch with the highest demand at present is dynamically appointed as a virtual main channel, and energy priority distribution is realized by adjusting equivalent impedance of the branch. According to the method, the global demand fluctuation index is used as a quantitative perceptron, a'balance-priority-emergency 'multi-stage mode is constructed, a dynamic virtual main channel and closed-loop feedback calibration are combined, conversion from static energy distribution to dynamic routing is achieved, and the system operation efficiency, the energy supply reliability, the power distribution network friend performance and the economical efficiency are improved.

The embodiment of the invention provides a PLC (Programmable Logic Controller)-based high-power wind turbine generator control method and a PLC-based high-power wind turbine generator control system, which are used for carrying out short-time prediction on future wind speed on the basis of a time sequence model and generating a feed-forward compensation pitch angle in combination with system delay so as to actively cope with upcoming wind speed disturbance, so that the reactive defects of traditional control are fundamentally overcome. According to the prospective control mode, the response speed and the control precision of the variable pitch system can be remarkably improved, the power and rotating speed overshoot caused by the large inertia characteristic is effectively restrained, the output power is smooth, and therefore the overall operation life of a unit is prolonged, and the power generation efficiency and the power grid friendliness are improved.

The invention discloses a micro-grid energy optimization configuration method under a direct current micro-grid layered droop control strategy, and belongs to the technical field of power system operation and control, and the method comprises the steps: taking the lowest system operation cost as a target, constructing a direct current micro-grid rolling optimization model, and formulating the minute-level optimal economic operation reference of each unit in the micro-grid in real time; constructing a layered droop control strategy, and determining participation states and response modes of an energy storage pile, a charging pile and a power grid in different areas by dividing an operation area corresponding to a bus voltage deviation degree; and establishing a scheduling-control integrated coordination mechanism, quantifying a standby demand of bottom-layer dynamic droop control for transient power, and embedding the standby demand as a robust constraint into an upper-layer rolling optimization model. According to the method, the problem that an economic target and a voltage safety target are mutually separated in traditional microgrid energy management is solved, and an effective method is provided for realizing safe, economic and power-grid-friendly operation of the high-proportion new energy direct-current microgrid.

A kind of combined grid-friendly photovoltaic confluence system for 5G base station, including confluence unit, sensing unit, photovoltaic power generation system is accessed to direct current bus through confluence unit;Sensing unit collects distribution network voltage information and is transmitted to confluence unit in real time;Confluence unit according to distribution network voltage and direct current bus voltage, dynamically adjusts output power.Confluence unit includes: main power circuit, auxiliary power supply circuit, sampling circuit, drive circuit, control module, protection circuit, first wireless communication module.Sensing unit includes: single-chip microcomputer, wireless communication module, ac power grid power quality monitoring unit, auxiliary power supply.The utility model discloses a kind of combined grid-friendly photovoltaic confluence system for 5G base station, to be able to cope with 5G base station inside direct current bus overvoltage problem, simultaneously can according to the distribution network voltage of surrounding node, dynamically adjust power output, improve the stability of power supply system.

The application discloses an orderly charging control method for an electric vehicle charging station, comprising the following steps: data acquisition; constructing a double-layer Stackelberg game framework of an upper-layer aggregator and a lower-layer individual user; constructing a user bounded rationality behavior model coupled with a prospect theory, a range anxiety and individual heterogeneity; solving by using a customized SAC algorithm to generate a charging and discharging incentive price and a power instruction; executing feedback and dynamic adjustment; and realizing closed-loop regulation and control of data set updating and model iterative solving through a deviation threshold determination. The application is suitable for power spot market fluctuation environment, has strong algorithm robustness and accurate scheduling, and can improve the operation efficiency of the charging station and the power grid friendliness.

The invention discloses a distributed optimal scheduling method based on a power grid friendly rural comprehensive energy system, which relates to the field of power grids and comprises the steps of establishing a power grid rural energy sensing network, summarizing collected rural comprehensive energy information, scheduling rural comprehensive energy and predicting the demand quantity of the rural comprehensive energy. Real-time scheduling is carried out on rural comprehensive energy, an electric power price optimization algorithm is established, a user participation incentive mechanism is established, self-scheduling and load management of users are promoted through price levers and reward measures, and analysis and summarization are carried out on rural comprehensive energy system optimization scheduling. According to the distributed optimization scheduling method based on the power grid friendly rural comprehensive energy system, efficient scheduling of rural energy is achieved by establishing a power grid rural energy sensing network, collecting and analyzing rural comprehensive energy use information and combining economical, energy-saving, sustainable development and people-benefiting constraint conditions.

The invention is suitable for the technical field of charging optimization, and provides a shared electric bicycle battery health prediction and off-peak charging optimization method based on big data, and the method comprises the steps: inputting obtained battery operation data into a pre-trained battery health prediction model, and outputting a health state prediction value of a battery; constructing a multi-target optimization model aiming at reducing the overall operation cost of the shared electric bicycle fleet, prolonging the overall service life of a battery pack of the fleet and stabilizing the regional power grid load; based on the determined health state prediction value, the time-of-use electricity price data, the power grid load data and the charging demand data, a genetic algorithm is adopted for solving, and a peak shifting charging scheduling scheme is obtained; and issuing the off-peak charging scheduling scheme to a charging control terminal of the shared electric bicycle operation platform so as to execute centralized off-peak charging operation. The method solves the problems of inaccurate prediction, uneconomical scheduling and disjunction of a power grid and actual operation in the prior art, and realizes collaborative optimization of operation efficiency, battery life and power grid friendliness.

The present invention discloses a grid-friendly rural virtual power plant auxiliary frequency control system and method, which realizes the control of solar energy and biomass energy according to the frequency control target model. The biomass energy production biogas module produces biogas through biomass energy and the heat generated by the solar energy utilization module, and stores it in the gas storage tank of the energy storage module. The biogas generator set of the biogas cogeneration module uses the stored biogas to generate electricity. At the same time, the biogas-fired boiler uses the biogas to generate heat and transfers the heat to the heat load and the biomass energy production biogas module. The excess heat is stored in the heat storage device. The photovoltaic power generation equipment of the solar energy utilization module uses solar energy to generate electricity and transfers it to the power load. At the same time, the excess electricity is stored in a battery or converted into heat through a heat pump. The scheme of the present invention couples solar energy and biomass energy, fully utilizes the synergistic relationship between rural photovoltaic and biogas, and forms a grid-friendly virtual power plant in the countryside that can realize auxiliary frequency regulation. It has important practical significance for promoting the effective use of clean energy, improving the stability and reliability of the power system, reducing frequency regulation costs, and helping rural revitalization.

The invention discloses a building power grid friendly multi-dimensional evaluation index evaluation method and device and a medium, and the method comprises the steps: constructing a multi-dimensional evaluation index system based on a green building evaluation standard, carrying out the expert scoring, constructing a judgment matrix, carrying out the dual validity detection through employing the individual consistency detection and group consistency detection, and obtaining an effective judgment matrix, based on statistical characteristics of a weight sample set of the effective judgment matrix, performing inversion calculation on the basic weight and the divergence degree of the indexes in the effective judgment matrix, correcting the weight model, and based on the corrected weight, performing comprehensive scoring on the multi-dimensional evaluation index system by adopting coupling coordination. By constructing a three-in-one multi-dimensional evaluation index system and adopting dual validity inspection of individual consistency inspection and group consistency inspection, the problem of evaluation system distortion caused by extreme deviation of individual experts is effectively avoided, the weight is corrected through the basic weight and the divergence degree, fine tuning is performed, and the evaluation accuracy is improved. And the evaluation precision of index scoring is improved.

The present invention provides a grid-friendly interactive building energy flexible management system, comprising: a data acquisition module (10), a calculation module (20) and a control module (30). The data acquisition module is capable of acquiring the real-time electricity price curve and the weather forecast data for the next day. The calculation module is connected to the data acquisition module by signal and is capable of: generating a first predicted power generation curve, a first predicted power consumption curve and a full-day predicted electricity price curve for the next day based on the weather forecast data for the next day, the historical power consumption curve and the real-time electricity price curve for the next day; comparing the first predicted power generation and the first predicted power consumption on the next day; generating different strategies based on the comparison results and adjusting the full-day predicted electricity price curve in real time; and acquiring real-time operation data for training. The control module is connected to the calculation module by signal to receive each strategy and is capable of controlling the operation of the building energy system. A building energy flexible management method is also provided.

The invention discloses an energy storage type electric heat supply method and system based on multi-period heat storage and load regulation, and the method comprises the steps: responding to an operation signal of a power grid in a valley electricity period or a power consumption period, executing an electricity-heat conversion and heat storage process which comprises heat energy grade management operation aiming at a medium in a heat storage device, the availability of high-grade heat energy is improved; before releasing heat to the heat supply network, selectively executing a heat energy grade enhanced heat release mode based on the evaluation of the heat energy grade state in the current heat storage device and the demand of the heat supply network; and when the heat energy grade enhanced heat release mode is selected to be executed, dynamic shunting based on real-time grade judgment is carried out on the heating medium extracted from the heat storage device, and the part which is judged to be a low-grade heating medium is guided into the electric-heat conversion unit to carry out heat energy grade improvement. Through collaborative optimization design of the whole chain of the energy storage type electric heat supply system, the unification of guaranteeing the heat supply quality, improving the operation economy and enhancing the power grid friendliness is realized.

The embodiment of the invention provides a self-adaptive fan variable pitch controller and a method thereof, which are used for carrying out dynamic self-adaptive adjustment on weights of targets such as power tracking and load suppression in a model predictive control cost function through a power grid event level and a unit load level which are monitored in real time. Through the method, the controller can autonomously switch and optimize the control priority according to the actual working condition, the power response is preferentially guaranteed when the power grid needs to be supported, the load is actively inhibited when the load is too large, and the emphasis is emphasized on generating capacity maximization under the conventional working condition; and finally, the optimal balance of the power generation efficiency, the structural safety and the power grid friendliness of the fan under the complex operation condition is realized, and the intelligent level and the comprehensive performance of the unit are remarkably improved.

The application discloses an artificial intelligence charging equipment power adaptive control method and system, after a to-be-charged object is connected, the state of charge, the battery pack temperature, the single cell voltage difference, the allowed charging current, the charging module temperature, the interface temperature, the station end remaining capacity, the power grid voltage drop amount and the environment temperature are acquired according to a sampling period to form a charging state time sequence matrix; the charging state time sequence matrix is input into a trained improved multi-scale causal convolution-KAN double-branch model to output recommended power, temperature rise response trend and voltage drop response trend; a trusted power envelope is formed according to the battery, the equipment and the power grid constraints, and power perturbation is executed within the envelope, and the battery, the interface, the module temperature rise change rate and the power grid voltage recovery time before and after the perturbation are checked for model response consistency; if the model response is consistent, the recommended power is adjusted, and if the model response is inconsistent, the envelope is contracted and the power is reduced. The application improves charging efficiency, safety and power grid friendliness.

The present invention discloses a control method for a virtual synchronous PEM electrolytic water hydrogen production module, and also discloses a device with the control method for the virtual synchronous PEM electrolytic water hydrogen production module. In the existing PEM hydrogen production device, the control method integrates a PWM three-phase converter with a load virtual synchronous control function for control, enabling the existing PEM electrolytic water hydrogen production module to have the autonomous operation and active management functions of active power - frequency and reactive power - voltage output at various time scales, and endowing the device with the operating external characteristics such as the inertia, damping characteristics, active power frequency modulation, and reactive power voltage regulation of a synchronous generator set, which can respond to the adjustment of the grid voltage / frequency and provide active and reactive power support for the grid. It promotes the friendly interaction between the PEM hydrogen production module and the power grid, and helps to improve the active power balance and voltage stability.

The invention discloses an intelligent photovoltaic grid-connected regulation and control method and system, relates to the field of photovoltaic grid-connected regulation and control, abandons expensive external observation equipment, and constructs a power map capable of intuitively reflecting the position and intensity of a cloud shadow by aggregating and normalizing a real-time power data flow. Based on the time sequence analysis of the map, the moving track of the power trough (namely cloud shadow) is detected and tracked, so that a cloud motion vector field model is established, and the accurate prediction of future power impact is realized. The active prediction mechanism solves the control hysteresis problem of a traditional scheme. Finally, through global space-time optimization scheduling, the predicted centralized power impact is smoothly allocated to inverters in different areas in a power station in advance, the problem of space inconsistency is effectively solved, the transformation from passive lag compensation to active prediction cooperative regulation is realized, and the power grid friendliness is greatly improved.

This invention discloses a method for optimizing energy allocation in a DC microgrid under a hierarchical droop control strategy, belonging to the field of power system operation and control technology. The method includes: constructing a rolling optimization model for the DC microgrid with the goal of minimizing system operating costs, and establishing minute-level optimal economic operating benchmarks for each unit in the microgrid in real time; constructing a hierarchical droop control strategy, determining the participation status and response mode of energy storage, charging piles, and the power grid in different regions by dividing the operating areas corresponding to the degree of bus voltage deviation; establishing an integrated scheduling-control coordination mechanism, quantifying the reserve demand of the underlying dynamic droop control for transient power, and embedding this reserve demand as a robust constraint into the upper-level rolling optimization model. This invention solves the problem of the separation between economic objectives and voltage safety objectives in traditional microgrid energy management, providing an effective method for achieving safe, economical, and grid-friendly operation of high-proportion renewable energy DC microgrids.

The invention relates to the technical field of data acquisition control, in particular to an electric power control method and device for alkaline water electrolysis hydrogen production equipment, and the method comprises the following steps: collecting the input and output voltage, current, power and DC bus ripple data of a rectifier of the alkaline water electrolysis hydrogen production equipment under a preset working condition; according to the method, the voltage, the current, the power and the direct-current bus ripple value of the input and output end of the rectifier of the alkaline electrolytic water hydrogen production equipment under the preset working condition are collected, the multi-dimensional statistical control limit is constructed, and during real-time data projection and analysis, accurate calculation of the real-time power offset metric value and dynamic comparison of the threshold value are combined, so that the real-time power offset metric value is obtained. The judgment of the real-time power offset state signal is more sensitive and accurate; meanwhile, by obtaining the actual parameters of the electrolytic cell cluster in the aspect of power response speed, the power grid friendliness subentry index set is further refined, so that the construction process of the power grid friendliness comprehensive index is more comprehensive, and the coordination ability between the power grid and equipment is enhanced.

The invention provides an air conditioner comprehensive efficiency quantitative evaluation method based on friendly interaction of a power grid. The air conditioner comprehensive efficiency quantitative evaluation method can be applied to the cross technical field of power system optimization operation and building flexible resource fine management. The method comprises the following steps: processing target flexible adjustment potential data of the air conditioner in a demand response period according to quantitative correlation models corresponding to a plurality of recovery strategies to obtain estimated rebound effect data corresponding to the plurality of recovery strategies, the demand response time period represents a time period when the electric appliance temperature of the air conditioner is increased from the baseline temperature based on the power saving demand, and the target flexible adjustment potential data represents power reduction data generated in the temperature adjustment process based on the demand response time period; and according to difference values between the target flexible adjustment potential data and the multiple pieces of estimated rebound effect data, multiple estimated load efficiency net values are determined, and the multiple estimated load efficiency net values are used for determining a target recovery strategy from multiple recovery strategies so as to execute temperature down-regulation operation for the air conditioner.

The present application belongs to the technical field of power grid control, and particularly relates to a dynamic balance control method for a power grid-friendly electric-hydrogen integrated energy hub, which comprises the following steps: collecting multi-source data in real time, including power grid frequency deviation value, wind and light power generation, energy storage device state of charge, hydrogen storage tank pressure, electrolytic hydrogen production device input power and fuel cell output power, to form a multi-dimensional operating parameter set; according to the amplitude and duration of the power grid frequency deviation, hierarchically calling the energy storage device, electrolytic hydrogen production device and fuel cell device for collaborative regulation; controlling the wind turbine generator to release rotor kinetic energy, while adjusting the electrolytic hydrogen production device as an interruptible load to provide virtual inertia support; calling the energy storage device, electrolytic hydrogen production device and fuel cell device according to priority for power compensation, to realize dynamic balance of the electric-hydrogen integrated energy system. The present application significantly improves the power grid frequency stability, reduces the energy storage configuration demand, and improves the hydrogen energy utilization efficiency and new energy consumption capacity.