1279 results about "Power Fluctuation" patented technology

A tracking and adaptive compensation method for power fluctuation of a pulse load of a ship is provided. The method includes: based on a microgrid topology model of the ship, a pulse load model of the pulse load, and an interharmonic power and pulse parameter relationship model, performing power fluctuation tracking, frequency selection and a power spectrum analysis to obtain filtering parameters of a low-pass filter and filtering parameters of a band-pass filter; performing waveform adaptation to eliminate a phase delay caused by the low-pass filter and the band-pass filter, and obtaining a control command for a power compensation strategy; and generating, by a power loop, a pulse width modulation (PWM) signal to control a switching tube in a bidirectional direct current (DC) / DC converter of each of an energy storage battery pack and a supercapacitor of a hybrid energy storage system.

The invention relates to the technical field of operation prediction, in particular to an optical storage flexible direct current operation prediction method based on deep learning, and the method achieves the precise evaluation of photovoltaic power fluctuation through the analysis of historical operation data and the combination of a power state conversion matrix, guarantees that the energy storage charging and discharging rate can be matched with the load demand distribution, and improves the prediction precision. Power scheduling is optimized, topology analysis and power flow path identification are carried out, topology weight calculation is carried out by using a graph convolutional network, power flow can be dynamically adjusted, the adaptability of an operation mode is improved, the influence of power fluctuation on system stability is reduced, power matching is carried out by adopting an adversarial generative network, photovoltaic output is optimized, and the system stability is improved. The energy storage release path is more reasonable, the power loss is reduced, the overall power distribution efficiency is improved, and the load compensation strategy is optimized through short-period fluctuation detection and long-period trend fitting. And variable correction is performed based on error calculation and anomaly detection, so that the reliability of regulation and control response is improved.

The invention discloses a distributed power supply access-oriented power distribution network fault distance measurement method and system, and relates to the technical field of power systems, and the method comprises the steps: collecting the electrical parameters and operation states of distributed power supply access nodes in a power distribution network in real time, building a dynamic manifold model based on an ecological niche theory, and carrying out the calculation of the dynamic manifold model; adaptively adjusting manifold learning neighborhood parameters according to power fluctuation data included in the electrical parameters, and updating node ecological niches to reconstruct a dynamic manifold model; based on the reconstructed dynamic manifold model, fault features are extracted from three scales of a current harmonic component, a feed line inter-harmonic propagation path and whole network voltage influence, and a three-dimensional feature vector is generated through fusion of a graph correlation algorithm; based on the expanded fault sample library and the power fluctuation data, constructing a fault transfer relation model to predict a ground fault and a short circuit risk area; a fault source is modeled by adopting a topological neural network, and a fault point distance measurement value is output through state prediction and strategy deduction.

The invention relates to the technical field of new energy power station control, and particularly discloses a new energy power station perception control method and system, and the method comprises the steps: S1, data collection, S2, state perception, S3, monitoring and early warning, S4, decision and optimization control, S5, execution and feedback, S6, intelligent operation and maintenance, and S7, self-healing scheduling. The deep neural network DNN is utilized to process a large amount of sensor data, so that the system can learn modes from complex historical data, accurately identify conditions such as power fluctuation and voltage abnormity, and timely discover potential abnormity through real-time updating of the model, so that the possibility of misinformation and missing report is reduced, and the reliability of the system is improved. The system monitors the operation state of the power station in real time, can quickly recognize and classify abnormal conditions, provides instant data support for decision making, can take measures in advance through abnormal prediction, prevents problems from being further expanded, and can recognize equipment needing to be maintained and prevents faults from being expanded through patrol inspection and prediction analysis of the unmanned aerial vehicle.

The invention relates to the technical field of power electronics, in particular to a photovoltaic off-grid inverter control method and system, and the method comprises the following steps: applying a test signal to identify an output interaction characteristic parameter, predicting the power generation power through combining with weather and attenuation, calculating the power fluctuation, and adjusting a current control parameter set. And calculating voltage and reactive power compensation parameters to generate an inverter control instruction, and combining a temperature load prediction trend to adjust a power allowable value to obtain a predictive power calibration coefficient. According to the invention, by analyzing the output interaction characteristics, enhancing the perception capability of the inverter to the actual operation environment, combining with the prediction of the photovoltaic power generation amount, realizing the prediction and influence evaluation of the power fluctuation, improving the adaptive adjustment capability of the current control parameters, improving the output voltage and reactive power control precision by utilizing the interaction characteristics, and optimizing the electric energy quality; and through thermal management of multi-point temperature and load prediction, the operation safety is improved, the service life of equipment is prolonged, and the operation performance of the photovoltaic off-grid system in a complex environment is improved.

The invention belongs to the technical field of wind-solar power generation power monitoring, and particularly relates to a new energy wind-solar power data monitoring system and method. According to the method, power fluctuation characteristics and equipment state correlation indexes are extracted through abnormal value detection and time sequence analysis, so that the precision and efficiency of data processing are improved, and in the aspect of prediction, dynamic comparison between a historical operation data set and the current power fluctuation characteristics is utilized, and environmental parameter change trends are combined. A power prediction curve and a confidence interval are generated, so that the system can recognize potential abnormal operation in advance, decision support time is provided for operation and maintenance personnel, in addition, the system has corresponding fault diagnosis and optimization capabilities, when the prediction deviation degree exceeds a preset threshold value, an early warning mechanism is automatically triggered, a fault source is positioned through a fault diagnosis process, and the fault diagnosis efficiency is improved. And finally, according to a fault diagnosis result, a power prediction curve is corrected and optimized to form a closed-loop optimization mechanism, and the prediction precision and the operation efficiency of the system are continuously improved.

The invention provides a virtual synchronous generator adaptive control method based on line impedance identification, and relates to the technical field of power system control. The line impedance identification-based adaptive control method for the virtual synchronous generator comprises the steps of dynamically adjusting the virtual inertia J, the damping coefficient D and the droop coefficient K of the virtual synchronous generator through a multivariable constraint optimization algorithm according to the impedance-frequency coupling model, and realizing real-time matching between the output power of the virtual synchronous generator and the impedance of a power grid. By collecting power grid signals in real time and extracting impedance characteristics, the dynamic change of power grid impedance can be timely and accurately mastered, and a reliable basis is provided for subsequent control strategy adjustment, so that real-time matching of the output power of the virtual synchronous generator and the power grid impedance is realized, power fluctuation is effectively reduced, and the stability of a power grid is improved; according to the invention, a self-adaptive modulation strategy and a multi-resonant controller are adopted, harmonic oscillation can be effectively suppressed, and the quality of output electric energy of the inverter is improved.

The invention provides an intelligent management method and system for photovoltaic energy storage equipment, and the method comprises the steps: analyzing the power fluctuation trend through monitoring the output power and environment parameters of the photovoltaic energy storage equipment in real time, and pre-judging the power fluctuation characteristics; according to the operation state parameters of the supercapacitor and the vanadium redox flow battery and the power fluctuation pre-judgment result, the power distribution proportion and the cooperative working mode of the energy storage element are determined; based on industrial load demand characteristics, an energy storage element is controlled to be flexibly switched between an active adjustment mode and a reactive compensation mode; and voltage regulation and harmonic compensation are realized by monitoring electric energy quality indexes of parallel connection points. According to the invention, the rapid response capability of the photovoltaic energy storage system to the industrial load can be effectively improved, the power supply stability and the electric energy quality are remarkably improved, the system power fluctuation is reduced, the utilization efficiency of the energy storage equipment is improved, and reliable clean energy support is provided for industrial users.

The invention relates to the technical field of energy storage scheduling, and discloses a distributed energy storage power system optimization scheduling method and system. The method comprises the following steps: collecting system operation data, performing normalization processing and anomaly detection, and predicting 24-hour load demand and new energy output in combination with standardized data; performing cost calculation and constraint analysis according to the prediction data, and generating a day-ahead scheduling plan; the operation state is updated according to the 15-minute cycle, and the output data is adjusted; performing multi-time-scale hierarchical processing on the power fluctuation; based on this, the energy storage capacity is optimally configured and the life characteristic is evaluated; and parameter optimization and updating are realized through operation index monitoring and analysis. According to the invention, through multi-dimensional performance evaluation and parameter optimization, efficient utilization and service life prolonging of the energy storage system are realized.

A virtual synchronization method for an energy storage system and a radial-flow water turbine generator set, said method comprising: analyzing characteristics of a radial-flow water turbine generator set, and designing a suitable energy storage system so as to smooth the power fluctuation of the radial-flow water turbine generator set (S1); acquiring characteristic parameters of the radial-flow water turbine generator set, on the basis of the characteristic parameters, designing a virtual rotor model, and establishing a machinery dynamics equation (S2); on the basis of the virtual rotor model, designing a virtual synchronization controller, constructing a closed-loop control system, and implementing charging and discharging control for the energy storage system (S3); establishing a simulation model for coupling the energy storage system and the radial-flow water turbine generator set, and optimizing parameters of the controller (S4); and, on a test platform of an actual radial-flow water turbine generator set, implementing a proposed virtual synchronous control policy, and carrying out experiment verification and result analysis (S5).

The invention relates to the technical field of network load prediction, and particularly discloses a power supply energy saving system and method based on a load prediction intelligent dormancy strategy, and the method comprises the steps: collecting base station service load and power supply power data, and employing a neural network to accurately fit the nonlinear relation between the two for adjusting the power; constructing a multi-mode service load prediction model, generating a power supply power adjustment instruction in advance, and adjusting the power in time when the load prediction deviation exceeds a threshold value; frequent power fluctuation is avoided through a dynamic threshold mechanism based on hysteresis comparison; a sleep and wake-up strategy and a buffer mechanism are established to ensure that the state of the power supply is switched only when the load changes continuously, so that the switching accuracy and stability are improved; self-adaptive sleep duration and progressive wake-up adjustment are introduced, so that smooth transition and intelligent energy conservation of power supply operation are realized; the method can improve the energy efficiency of the power supply and reduce the energy consumption.

The invention discloses a generator non-inductive access grid-connected method, device and equipment, and provides a reliable data basis for subsequent operation by collecting a power grid state and generator operation monitoring parameters in real time. Power grid frequency is calculated at multiple time points, and a real-time frequency curve is constructed and used for analyzing stability, predicting changes, comparing generator current output frequencies to identify frequency differences and evaluating coordination. Frequency synchronization is realized by using minimum difference time point detection, the time point is marked to optimize frequency control, and grid-connected stability and safety are guaranteed by combining dynamic frequency adjustment and synchronous frequency error estimation. In the aspect of power control, power fluctuation is reduced through transient power suppression optimization, and the adaptability of the generator is enhanced through dynamic feed-forward compensation control. In addition, manual intervention is reduced through intelligent non-inductive grid-connected optimization, an intelligent grid-connected engine is constructed, seamless butt joint of a generator and a power grid is achieved, grid-connected efficiency and safety are comprehensively improved, and system complexity and risks are reduced.

The invention relates to the technical field of wind energy control systems, and discloses a wind power energy-saving control method and system based on big data analysis, and the system comprises a data collection and transmission layer, a data storage and management layer, a data analysis and prediction layer, an intelligent control layer, and an equipment full life cycle management layer. The data acquisition and transmission layer further comprises multi-source data acquisition system construction, edge computing data preprocessing and data transmission network construction. According to the intelligent control strategy, by means of a distributed cooperative control algorithm and an intelligent variable-pitch variable-speed control algorithm, the fan blade angle, the rotating speed and the power output are dynamically adjusted according to the real-time meteorological data, the power grid load requirement and the fan running state, wind power output is smoother through accurate regulation and control, and the wind power output efficiency is improved. The impact on the power grid caused by power fluctuation is effectively reduced, the wind power acceptance capability of the power grid is remarkably improved, and the stability and reliability of the operation of the power grid are guaranteed.

The invention provides a virtual power plant planning method and system based on flexibility vacancy partition evaluation. The method comprises the steps that node flexibility supply and power fluctuation quantity are calculated; determining tie line transmission capability constraints, and constructing a flexibility mutual aid scheme optimization model; solving the model to obtain a flexibility mutual aid scheme; calculating the adjustment demand of each partition in combination with a node flexibility supply and demand and flexibility mutual aid scheme; constructing a controllable resource physical characteristic model, simulating a resource operation state and an adjustment capability, and calculating a proportional relation between the adjustment capability and the capacity based on a simulation result; obtaining different aggregation modes and aggregation difficulties, calculating a unit capacity aggregation cost coefficient, and constructing a virtual power plant cost model; and constructing an optimal configuration model by taking meeting of adjustment requirements of each partition as a constraint and taking the minimum total aggregation cost as a target, and solving to obtain the virtual power plant aggregation resource type and capacity of each partition. Based on the method, the invention also provides a virtual power plant planning system. According to the invention, rapid and accurate optimization planning of the virtual power plant is realized.

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 discloses an energy storage system cooperative control method and system for power grid frequency modulation, belongs to the field of power grid control, and particularly relates to power grid frequency control, and the method comprises the steps: collecting power output time sequence data of each energy storage system in a target power grid in response to a power grid frequency modulation instruction through data monitoring equipment, to identify a timing misalignment event due to communication delay or response difference; acquiring output power data of each time sequence dislocation event so as to judge whether a cooperative failure condition occurs among the energy storage systems or not; if it is determined that a cooperative failure condition occurs, generating a frequency modulation power task redistribution instruction with smooth power grid power fluctuation as a target according to the output power data, and obtaining delay data to generate a communication time sequence adjustment instruction synchronized with power distribution, so as to adjust the frequency modulation power task according to the communication time sequence adjustment instruction; and cooperative control of each energy storage system in the target power grid is realized. The stability of power frequency modulation of the power grid can be improved through cooperative control of the energy storage system in the power grid.

The invention discloses a multi-electrolytic cell collaborative optimization control method suitable for wide-range power fluctuation, and belongs to the technical field of new energy. According to the method, an optimization framework is adopted for collaborative optimization of hydrogen production power supply power, electrolytic cell power, electric energy storage power and electrolytic cell time sequence production state, a finite time domain rolling solving method is adopted in optimization, the rolling time domain length is hour level, the sampling time is minute level or hour level, an optimization objective function and a constraint model are established respectively, and the optimization objective function and the constraint model are optimized. And solving the optimization model by adopting a mathematical programming or heuristic algorithm to obtain the operation power of each device of the multi-electrolytic cell hydrogen production system and the electrolytic cell state. According to the method, under the wide-range power fluctuation working condition, battery energy storage weakening of frequent starting and stopping of the electrolytic cell is achieved, under the narrow-range power fluctuation working condition, battery energy storage is achieved, it is guaranteed that the electrolytic hydrogen production system operates at the optimal efficiency, and maximum energy utilization and efficient operation of the system are guaranteed; and a new method is provided for collaborative optimization control of the multi-electrolytic-bath hydrogen production system.

The invention relates to the technical field of distributed energy voltage regulation, and discloses a distributed energy cluster voltage regulation control method, system and device, and the method comprises the steps: obtaining all distributed energy nodes in a power distribution network; performing group division on all the distributed energy nodes based on the sensitivity of the voltage of the distributed energy nodes to power change in combination with a K-means clustering algorithm to form a plurality of clusters; respectively establishing an adjustment control model for each cluster, wherein the adjustment control model comprises an objective function taking reduction of power fluctuation and voltage deviation as an optimization objective and a constraint condition taking safe operation of the power distribution network as a premise; and solving the regulation control model corresponding to each cluster through an improved particle swarm algorithm, thereby obtaining a control strategy for voltage regulation of each distributed energy node in each cluster. Quantitative evaluation indexes are established to evaluate the node voltage stability, a method for improving calculation precision is combined, power grid changes are quickly responded, and the voltage is accurately adjusted.

The invention relates to the technical field of AC / DC module control, and discloses an intelligent control method and system for multi-mode switching of an AC / DC module. According to the method, a dynamic topology mapping model is constructed according to an impedance spectrum matrix, and a physical connection relation is converted into a node admittance relation network; generating an energy distribution state sequence based on the power fluctuation vector, and analyzing migration constraint conditions among different operation modes by adopting an association rule mining algorithm; when an operation mode switching instruction is detected, activating a node admittance relation network in the dynamic topology mapping model, and inputting a current energy distribution state sequence to an association rule mining algorithm; according to a real-time matching result of the node admittance relation network and the migration constraint condition, generating a switching control instruction containing an impedance adjustment gradient and a power distribution weight; and the power semiconductor execution unit transmits the switching control instruction to the AC / DC module. According to the method, multi-mode intelligent switching control of the alternating-current and direct-current module can be realized.

The invention relates to the technical field of photovoltaic energy storage systems, and discloses a power regulation method, device and equipment for a photovoltaic energy storage system and a storage medium, and the method comprises the steps: carrying out the real-time collection and wavelet decomposition of voltage and current parameters of a photovoltaic array, and obtaining power fluctuation components and power trigger signals of different frequencies; executing power vector analysis to obtain an oscillation mode characteristic parameter set and an oscillation suppression strategy; constructing a photovoltaic side feedforward trigger channel and an energy storage side feedback trigger channel, and obtaining a coordination trigger instruction of the photovoltaic side and the energy storage side; and performing multi-objective optimization decomposition and slope limitation processing on the coordination triggering instruction to obtain a voltage reference value of the photovoltaic MPPT controller and a current reference value of the battery charging and discharging controller, thereby realizing accurate identification and prediction of different frequency power fluctuation components, realizing collaborative cooperation of photovoltaic side feed-forward and energy storage side feedback, and improving the reliability of the system. And the power oscillation risk caused by control mode switching is avoided.

The invention provides an active-disturbance-rejection full-wind-speed power smoothing method based on kinetic energy of a fan rotor, and belongs to the technical field of wind power control. The technical problem that the output power of a traditional wind turbine generator is unstable due to random fluctuation of the wind speed is solved. According to the technical scheme, the method comprises the following steps that S1, rotor kinetic energy is calculated based on a wind turbine kinetic model, and the effect of the rotor kinetic energy in power fluctuation stabilization is analyzed; s2, designing a first-order linear active disturbance rejection controller for rotating speed loop control; s3, designing a second-order linear active disturbance rejection controller for variable pitch control; and S4, dynamically generating an active power reference value by combining the kinetic energy of the rotor and an active disturbance rejection control technology, and controlling by coordinating a rotating speed ring and a variable pitch. The method has the beneficial effects that power fluctuation can be remarkably reduced under wind speed fluctuation and complex working conditions, the smoothness of power output is improved, meanwhile, the anti-interference capability and the dynamic stability of the system are enhanced, and efficient and stable operation of the wind driven generator system is ensured.

The invention discloses an expressway slope photovoltaic grid-connected power generation system for cross energy fusion, and relates to the technical field of expressway slope photovoltaic grid-connected power generation. Comprising a main power grid dispatching sensing module, a reverse power transmission characteristic data acquisition module, an impact strength evaluation and classification module, a graded power regulation and control execution module and a self-adaptive regulation and control feedback module, the reverse power transmission characteristic data acquisition module is used for acquiring electrical characteristic data and power fluctuation characteristic data of the photovoltaic grid-connected point in real time and constructing a reverse power transmission evaluation data set when the judgment result is that the photovoltaic grid-connected point encounters transient reverse power transmission; and the impact strength evaluation and classification module determines the impact strength of the reverse current when the photovoltaic grid-connected point encounters transient reverse power transmission based on the constructed reverse power transmission evaluation data set, and classifies the impact strength. According to the invention, the problem that the photovoltaic grid-connected point cannot be dynamically regulated and controlled under the impact of transient reverse power transmission is solved, and the self-adaptive power regulation and control effect of impact strength identification and grading response is realized.

The invention relates to the technical field of new energy power system control, and relates to a power decoupling method for cooperative control of voltage feed-forward compensation and adaptive virtual impedance. The method comprises the following steps: acquiring a power grid current and a power grid voltage, and calculating a reactive power measured value and an active power measured value of a power grid; virtual synchronous machine control is carried out, and a voltage feed-forward pre-compensation item is introduced into a reactive power control loop; calculating a reactive power control loop after VSG compensation, and obtaining VSG output side voltage and instantaneous angular frequency; self-adaptive virtual impedance control is adopted, a self-adaptive virtual impedance reference value is calculated, line impedance is dynamically adjusted, and a voltage loop input instruction voltage is calculated according to the line impedance; and adjusting the output performance of the inverter according to the instruction voltage. According to the invention, the problem of power fluctuation caused by VSG output voltage amplitude variation is effectively solved, and the dynamic influence of a power coupling item is weakened.

The invention discloses a method for preventing power reverse peak regulation by coupling primary frequency modulation and virtual inertia of a network-forming type fan, and the method effectively prevents power reverse peak regulation by dynamically decoupling the coupling effect of primary frequency modulation and virtual inertia and adjusting an amplitude limiting threshold value based on a real-time working condition. The adaptive amplitude limiting control strategy adjusts an amplitude limiting threshold value in real time according to parameters such as power grid frequency deviation, frequency change rate and fan operation state, optimizes fan power output, and avoids excessive power fluctuation. The virtual inertia compensation module simulates inertia response of a traditional generator set, provides extra inertia support and stabilizes frequency fluctuation of a power grid. The hierarchical control architecture realizes the balance of virtual inertia and frequency modulation control through the synergistic effect of an upper decision layer and a bottom execution layer, and avoids the phenomenon of reverse peak regulation of power. The control strategy not only improves the frequency modulation response speed and precision, but also enhances the adaptive capacity of the fan to the frequency fluctuation of the power grid, and has important application value and wide market prospect.

The invention discloses a grid-connected power fluctuation active stabilization control method and system for multi-source new energy, and relates to the technical field of grid-connected power control, and the method comprises the steps: reading equipment data after a multi-source new energy management device is connected; executing data acquisition of environment data, establishing a time sequence environment data set, performing environment prediction, and establishing an environment prediction result; performing collaborative relation identification based on an active identification complementary window, and establishing a collaborative relation identification result; executing initialization of the dynamic response virtual collaboration body; obtaining a time sequence load demand task, and generating a collaborative scheduling result; and carrying out active stabilization control management on grid-connected power fluctuation by utilizing the collaborative scheduling result. The technical problems that in the prior art, during multi-source new energy grid connection, power fluctuation is large, and the stability and reliability of a grid connection system are low are solved, and the technical effects that active stabilizing control over multi-source new energy grid connection power fluctuation is achieved, and the stability and reliability of the grid connection system are improved are achieved.

The invention discloses a wind and light storage and charging micro-grid distribution optimization method and system. The method comprises the following steps: acquiring parameter data of each node in a micro-grid in real time; constructing a load demand prediction model, and automatically adjusting the scheduling weight coefficient of the wind and light storage and charging equipment according to the weather type; based on a model output result, establishing a matching relationship between the line impedance and the load emergency degree, generating a power supply path set, and creating a power path selection mechanism based on a dynamic planning algorithm; calculating real-time charge-discharge efficiency based on the equivalent resistance parameter of the power supply path, and dynamically adjusting a charge-discharge rate threshold according to a prediction error; acquiring a real-time monitoring load curve, calculating the similarity between the load curve and historical data, and matching and identifying a potential sudden change risk; and according to a distributed negotiation protocol, each node achieves a scheduling consensus through a priority broadcasting mechanism. The method has the advantages that through load prediction and dynamic scheduling, optimal scheduling, power fluctuation stabilization and sudden change risk identification of the wind and light storage and charging equipment are realized.

The invention provides an optimization scheduling method and system for power distribution of an electrolytic cell group under a wind power fluctuation condition, and relates to the technical field of wind power grid-connected power generation control, and the method comprises the steps: collecting wind power plant power data and electrolytic cell operation parameters, carrying out the adaptive segmentation processing of the power data, constructing a fluctuation feature space, predicting the fluctuation risk, and carrying out the optimization scheduling of the power distribution of the electrolytic cell group. And an electrolytic cell regulation capability evaluation system is established and dynamically grouped, and a power regulation matrix is constructed to calculate an optimal power distribution proportion, so that coordinated regulation of wind power fluctuation by the electrolytic cell group is realized, and the system operation stability and the energy utilization efficiency are improved.

The invention provides a photovoltaic energy storage inverter power coordination control method based on an adaptive algorithm, and relates to the technical field of data processing, and the method comprises the steps: collecting the output power data of a photovoltaic module, the state data of an energy storage device, and the load demand data of a grid connection point, and carrying out the normalization processing of the data; calculating to obtain an initial power distribution parameter of the current period; respectively calculating a load change trend factor and a power fluctuation trend factor based on the load demand data and the output power data of the historical period, and coupling the load change trend factor and the power fluctuation trend factor to form a trend coupling factor; carrying out self-adaptive repair through a trend coupling factor; combining real-time grid-connected point load demand data with energy storage device state data to generate a target power distribution instruction and an energy storage charging and discharging adjustment instruction, and respectively issuing the instructions to an inverter control unit and an energy storage device control unit; according to the invention, the accuracy of the photovoltaic energy storage inverter power coordination control method is improved.

The invention provides a micro-grid control method, a program product and a readable storage medium. The micro-grid control method comprises the following steps: acquiring operation data of a micro-grid and each piece of network-forming equipment thereof, and environment data of an environment where the micro-grid is located; performing multi-source feature fusion processing on the collected operation data and environment data, and predicting the energy output, load demand and power fluctuation amplitude of the microgrid in a future preset time period based on the fused features; based on the prediction result and the current state of each piece of network construction type equipment, optimizing the voltage parameter and the frequency parameter of each piece of network construction type equipment; and issuing the optimized voltage parameters and frequency parameters serving as parameter adjustment instructions to the corresponding network construction type devices, so that the network construction type devices operate based on the issued parameter adjustment instructions. The method has the advantages that the voltage parameter and the frequency parameter of each piece of network construction equipment can be optimized, and a key foundation is laid for stable and efficient operation of the micro-grid.

The invention, which relates to the technical field of power grid electrical equipment monitoring, discloses an electrical equipment abnormal power state monitoring system comprising a data acquisition module, a data processing module, a monitoring analysis module and a management module. The monitoring analysis module comprises a power reference offset sub-module, a power fluctuation sub-module and a comprehensive abnormal power risk sub-module, the abnormal power state monitoring effect of the electrical equipment can be remarkably improved, the influence of multiple factors on power reference offset is considered by the system, the power reference can be accurately corrected, and power grid interaction factors can be effectively improved. Therefore, the abnormal power risk can be comprehensively and accurately assessed based on the power reference offset, the power fluctuation stability and multiple factors, so that the safe and stable operation of a smart power grid and a large-scale power grid can be powerfully ensured.