356 results about "Pv power" patented technology

The invention discloses a power distribution network photovoltaic and energy storage configuration method considering island division and network reconstruction. The method comprises the following steps: collecting basic information of a power distribution network; monitoring output change and load fluctuation of a photovoltaic power supply in real time, constructing a photovoltaic power supply output model and a load time-varying model, and predicting photovoltaic output data and load demand data in the fault duration; determining an island range by using a breadth-first search algorithm by taking a load node directly supplied with power by the photovoltaic power supply as a starting point; based on an island division result, identifying residual load nodes of which the power supply is not recovered and network lines connected with the load nodes; the lowest comprehensive cost is determined as an optimization target, an electrical constraint condition is converted into a second-order cone constraint form, the optimization target and the electrical constraint condition are used for solving a network reconstruction problem for the fault duration, and a switch operation strategy is determined; power supply of the fault area is recovered; and performing configuration optimization on the photovoltaic power supply according to the load operation state in the island during the fault period of the power distribution network.

The invention discloses an optimal scheduling method for grid connection of a power distribution network and a distributed power supply, and particularly relates to the technical field of optimal scheduling, which comprises the following steps of: determining employment performance information during grid connection of the distributed photovoltaic power supply according to the difference between real-time and historical solar photovoltaic output models; based on charge state data of an energy storage system connected with the distributed photovoltaic power supply, determining energy storage performance information during grid connection of the distributed photovoltaic power supply, determining a grid connection strategy of the distributed photovoltaic power supply, and determining a grid connection strategy of the distributed photovoltaic power supply based on consideration of a node system topology connection relation of the power distribution network and related data of nodes and branches; possible risks existing in distributed photovoltaic power grid-connected nodes in the power distribution network are simulated, grid-connected risk information of the power distribution network is determined, the matching degree of output power and required power of the distributed photovoltaic power is considered, grid-connected load matching information of the power distribution network is determined, and the overall grid-connected performance of the power distribution network is quantified. According to the invention, stable operation of the power distribution network can be ensured.

The invention provides an active power distribution network double-layer collaborative voltage regulation and control method based on an LSTM neural network. According to the method, self-adaptive partition of the active power distribution network is realized by using a community division algorithm, an active power distribution network double-layer cooperation and photovoltaic power supply descending order control model is established, and rapid regulation and control of off-limit voltage of the power distribution network are realized through a reactive compensation / active power reduction two-stage control mode. The universality of centralized voltage control and the rapidity of cluster voltage control can be considered at the same time, and efficient regulation and control of distributed photovoltaic high-proportion access power distribution network voltage are achieved.

The invention discloses a photovoltaic power generation intelligent control system of photovoltaic panels in an optical storage direct flexible system, and relates to the technical field of photovoltaic power generation, the intelligent control system comprises a plurality of photovoltaic panel assemblies, the plurality of photovoltaic panel assemblies comprise main node assemblies, one main node assembly is arranged every 5-10 groups of photovoltaic panel assemblies, and the main node assemblies are connected with the photovoltaic panel assemblies; the master node assembly is configured with a high-precision double-axis sun sensor and an edge calculation module and is responsible for collecting a solar azimuth angle, a current inclination angle of the assembly and environment temperature and humidity data in real time, and the slave node assembly is configured with a single-axis inclination angle sensor and adjusts a tracking angle by receiving a master node instruction. Specifically, a master-slave node heterogeneous design is adopted, the slave node only needs a single-axis tilt angle sensor and a wireless communication module, the hardware configuration number is reduced, and cost control is achieved. According to the method for photovoltaic panel tracking optimization, the control instruction quantity of the system is reduced, the central control pressure is remarkably reduced, and the problems of cost and complexity during large-scale application of photovoltaic panel tracking are solved.

The invention provides a new energy field station AGC distribution method for power distribution, and the method comprises the steps: obtaining the characteristic information of a target photovoltaic power station, and the characteristic information at least comprises the grid-connected point voltage value of the photovoltaic power station, the environment temperature of the photovoltaic power station, and the solar irradiance task profile data; based on the characteristic information, an improved droop control strategy is adopted to calculate the reactive power of the photovoltaic power station; obtaining a reactive power regulation margin based on the reactive power of the photovoltaic power station; generating an active power distribution instruction based on the reactive power regulation margin, the distribution instruction being used for distributing active power; a photovoltaic power supply fatigue loss model is established, a photovoltaic power supply fatigue loss result is obtained, and photovoltaic power supply loss at least comprises IGBT loss and capacitor loss; based on the photovoltaic power supply fatigue loss result, a photovoltaic reactive power optimal distribution model is established, and based on the photovoltaic reactive power optimal distribution model, a distribution strategy is generated, and the distribution strategy is used for distributing reactive power.

The invention relates to the field of power systems, and discloses an optimized operation method and system for an active power distribution network containing a photovoltaic power supply. The method comprises the steps that an SVG reactive power compensation device is additionally installed in a power distribution network, and the node voltage of the power distribution network is adjusted; (2) introducing an OLTC on-load tap-changing transformer at a power grid balance node, and changing the transformation ratio of the transformer by adjusting the position of a tap of the OLTC on-load tap-changing transformer so as to adjust the voltage; (3) a multi-target optimization idea is adopted to reduce the network loss, reduce the voltage fluctuation and improve the photovoltaic consumption rate as optimization targets; (4) introducing a particle swarm algorithm and improving the particle swarm algorithm into a multi-target particle swarm algorithm; and (5) establishing an IEEE33 node power distribution network model containing a photovoltaic power supply on an MATLAB platform, setting related parameters and constraint conditions for simulation, and verifying the feasibility of an optimization strategy. According to the technical scheme, the problems of stability, reliability, economical efficiency and the like caused by the fact that the photovoltaic power source is connected into the active power distribution network can be solved, and optimized operation of the power distribution network is achieved.

The invention discloses a networked photovoltaic power generation energy storage system, relates to the technical field of photovoltaic energy storage, and is used for charging control of a rechargeable battery, overcurrent protection during charging control of the rechargeable battery and automatic voltage stabilization through a feedback pin. The demodulator is used for transmitting demodulated data to the charging controller for processing; the control module is used for controlling the voltage regulation precision and the voltage regulation range of the voltage regulation module, processing a receiving power request fed back by the demodulation module in time, and outputting a control signal to the voltage regulation module according to requirements, so as to realize multi-gear voltage precise regulation; the load power detection module and the load voltage and current detection circuit are additionally arranged at the load, the load power and the voltage and current are uploaded to the monitoring system, it is ensured that the output of the inverter does not exceed the limit value, then the output power of the photovoltaic power supply is ensured, countercurrent is effectively avoided, and energy is saved.

The invention discloses a deep learning photovoltaic power generation long-term prediction method fusing domain knowledge, and the method comprises the following steps: constructing a meteorological feature fine classification module, carrying out the classification processing of original meteorological data, and generating discrete weather category labels; carrying out embedded representation on discrete weather category labels, and splicing the discrete weather category labels with original continuous meteorological features to form an enhanced input sequence; the enhanced input sequence is input into a Fusionform model, and photovoltaic power generation power prediction is carried out; introducing a theoretical power modeling module based on a photovoltaic physical mechanism, and calculating theoretical power generation power according to photovoltaic system parameters and meteorological data; performing weighted fusion on the output of the Fusionformer model and the theoretical generated power to obtain a final prediction result; according to the method, the physical consistency and interpretability are improved while the precision is ensured, and high-precision long-term prediction support is provided for power grid dispatching.

The invention discloses a wall-mounted base, a charging and discharging device and a control method and system. The wall-mounted base comprises a mains supply interface, a photovoltaic interface, a charging pile interface, a switching circuit and a control unit, the commercial power interface is used for being connected with a commercial power supply, the photovoltaic interface is used for being connected with a photovoltaic power supply, and the charging pile interface is used for being detachably connected with a portable charging pile; one end of the switching circuit is connected with the commercial power interface or the photovoltaic interface, and the other end of the switching circuit is connected with the charging pile interface; and the control unit is connected with the switching circuit and is used for controlling the switching circuit to connect a target power supply and the portable charging pile and carrying out charging and discharging control. The wall-mounted base can be used in cooperation with the portable charging pile, the photovoltaic power source and the commercial power source which are connected can conduct charging and discharging interaction with the portable charging pile or a charging and discharging device connected with the portable charging pile, photovoltaic charging, power storage and power supplement to a commercial power grid can be completed, and the wall-mounted base can adapt to optical storage and charging application scenes in an all-around mode.

1. The name of the product of this design: Power adapter extension cable (8 to 2). 2. Purpose of this design product: used for electrical connection between components of photovoltaic power system. 3. The design key point of this appearance design product lies in the shape. 4. The picture or photo that best illustrates the design points: three-dimensional picture.

1. The name of the product of this design: Graphical user interface for displaying the operating status of energy storage inverter for electronic equipment (ph1100 three-phase). 2. Purpose of this design product: for use in an electronic device. 3. The design key point of this appearance design product lies in the pattern. 4. The picture or photo that best illustrates the key points of the design: Main view of Design 1. 5. Designate Design 1 as the base design. 6.Purpose of the graphical user interface: It is used to display on electronic devices to show users the working status of the inverter and the input and output parameters of the inverter. Users can interact with the computer through touch screens, buttons or other communication methods to facilitate display and function settings. 7. Description of the changing states of the graphical user interface: Design 1 is the full icon display interface, Design 2 is the interface when the inverter is turned off, Design 3 is the interface when the grid-connected PV is running at 100%, Design 4 is the interface when the grid-connected power grid is running at 100%, Design 5 is the interface when the off-grid generator is running, Design 6 is the interface when the off-grid battery is powered, Design 7 is the interface when the off-grid PV is generating electricity, and Design 8 is the interface when the grid is connected to bypass.

The invention discloses a particle swarm optimization-based power distribution area energy storage and reactive compensation coordinated optimization method, which comprises the following steps of: constructing a power distribution area power flow model, and setting operation constraint strips of an energy storage device, a reactive compensation device and a photovoltaic power supply; according to the method, the problem of maximizing the photovoltaic consumption capacity of the power distribution area is converted into the problem of minimizing the photovoltaic overflow power when light is not abandoned, constraint conditions and safe operation boundaries of elements of the power distribution area are considered, the minimum total network loss of a system and the minimum total photovoltaic overflow amount in a period of time are taken as objective functions, a coordinated optimization model is established, and the optimal power consumption of the power distribution area is reduced. The particle swarm optimization algorithm is adopted to optimize the charging and discharging amount of the energy storage device and the compensation amount of the reactive power compensation device in the time period, solving of the optimal operation scheme of the power distribution area is achieved, and on the premise that safe and stable operation of the power distribution area is guaranteed, the network loss can be reduced, the photovoltaic permeability is improved, and the energy consumption is reduced. And the operation safety and economy of the power distribution area are improved.

The invention provides a photovoltaic output scene clustering method. High-frequency noise of an original photovoltaic output time sequence is suppressed through self-adaptive smoothing processing, fluctuation characteristics of the high-frequency noise are extracted, it is ensured that target time sequence data accurately reflect photovoltaic power generation working conditions, and high-quality input is provided for subsequent clustering; the target clustering number is determined based on joint optimization parameters (fusing local dynamic characteristics and global distribution characteristics), and scene division deviation caused by subjective setting of the clustering number is avoided; the clustering center is updated by iteratively optimizing the clustering objective function, and it is ensured that the typical scene center truly reflects the mainstream output mode. Therefore, scene representativeness is improved in the aspects of data preprocessing, clustering number decision making and central optimization of a whole link, and generalization ability of a power grid dispatching strategy is remarkably enhanced.

The invention relates to a water-light-storage integrated micro-grid system and a control method thereof. The system comprises a distributed hydroelectric power supply, a distributed photovoltaic power supply, an energy storage system, a medium-voltage AC-DC flexible interconnection device, a micro-grid energy management system and a load. The medium-voltage AC / DC flexible interconnection device is connected in series between a grid-connected point of the micro-grid and a superior power distribution network, an AC port of the medium-voltage AC / DC flexible interconnection device is used for realizing flexible power flow mutual aid between the micro-grid and the superior power distribution network, and a DC port of the medium-voltage AC / DC flexible interconnection device is used for being connected with an energy storage system; and the micro-grid energy management system is in communication connection with the distributed hydroelectric power supply, the distributed photovoltaic power supply, the energy storage system and the medium-voltage AC / DC flexible interconnection device, and is used for collecting system operation data, executing an optimization control strategy and realizing autonomous operation of the micro-grid and cooperative control of the micro-grid and a superior power distribution network. The system can effectively cope with seasonal load peaks, greatly improve the local consumption rate of distributed water and light resources, and enhance the power supply reliability and operation flexibility of a local power grid.

The invention belongs to the technical field of new energy, and particularly discloses an optical storage micro-grid system for large-scale photovoltaic water lifting in remote mountainous areas, which comprises a plurality of photovoltaic power supplies, a booster station, a grid-forming type energy storage module, a pump station power distribution module and a source grid load storage control module, the plurality of photovoltaic power supplies are electrically connected with the bus through the booster station, the grid-forming energy storage module is electrically connected with the bus, the bus is electrically connected with the pump station power distribution module through the power transmission line, and the voltage grade of the power transmission line is determined based on the length of the power transmission line and the installed power of the pump station; the network-forming type energy storage module is in a voltage source mode or a power source mode; and the source grid load storage control module is used for controlling grid-connected or off-grid switching and controlling the working mode of the grid-forming type energy storage module. According to the invention, for photovoltaic water lifting in remote mountainous areas, the scale of photovoltaic water lifting is effectively improved, and the operation efficiency of the water pump is guaranteed.

The present disclosure provides a device, a method, and a medium for charging. The device for charging includes a first sensor, a second sensor, a third sensor, a charging pile, and a processor. The first sensor obtains first sensing information from a battery connected with the charging pile. The second sensor obtains second sensing information from a photovoltaic system connected with the charging pile. The third sensor obtains third sensing information from a power grid connected with the charging pile. The charging pile transmits power to a target object. The processor is configured to determine power storage information of the battery, photovoltaic power supply information of the photovoltaic system, and power grid power supply information of the power grid, respectively; determine the target object to be charged based on the power pile; determine a source object, and, control the charging pile to transmit power to the target object.

The invention relates to a new energy power distribution network collaborative optimization system based on a distributed regulation and control framework. The system comprises a cluster module, a virtual power plant module, a power distribution network module and an optimization module. The cluster module gathers a plurality of small-capacity dispersedly accessed photovoltaic power supplies to form a plurality of photovoltaic power supply clusters; the virtual power plant modules form a plurality of virtual power plants, each virtual power plant comprises a high-capacity photovoltaic power station, an energy storage device and a load, and the virtual power plants serve as an optimization main body to supply power to the internal load and reversely transmit electric quantity to the power distribution network module so as to generate benefits; and the power distribution network module is used for connecting a plurality of photovoltaic power supply clusters and a plurality of virtual power plants. The invention relates to the technical field of new energy power distribution networks. Dispersed small-capacity photovoltaic power supplies are divided into photovoltaic clusters, large-capacity photovoltaic power stations are combined with energy storage and loads to form a virtual power plant, it is guaranteed that the photovoltaic power supplies connected in different forms fully participate in collaborative optimization, and the adverse effect of photovoltaic power generation intermittency and randomness on a power distribution network is reduced.

The invention relates to the technical field of photovoltaic power generation, in particular to a regional autonomous regulation and control method and system for distributed photovoltaic groups and user side energy storage. The method comprises the following steps: obtaining photovoltaic group output data and user side load data; performing energy balance evaluation according to the photovoltaic group output data and the user side load data to determine a regional energy gap; performing energy storage autonomous adjustment analysis based on the regional energy gap to obtain energy storage autonomous adjustment data; performing peak clipping and valley filling identification based on the energy storage autonomous adjustment data to obtain peak clipping and valley filling data; positioning an energy mutual aid path by using peak clipping and valley filling data; performing power grid stability detection based on the energy mutual aid path to obtain power grid stability data; predicting a critical instability state according to the power grid stability data; and adjusting energy storage parameters according to the critical instability state to obtain energy storage adjustment parameters. Based on the photovoltaic power generation technology, the energy dispatching precision and the power grid operation stability of the regional photovoltaic and energy storage system are improved.

A DC microgrid has increased DC bus voltage inertia without adding large physical capacitors. A Virtual Inertia Enhancement Controller (VIEC) of a DC-DC converter emulates a DC machine's mechanical inertia characteristics through a virtual capacitor which compensates for a power imbalance causing DC bus voltage fluctuations. When a battery charges and generated photovoltaic (PV) power is more than the load power, VIEC controls the PV's DC-DC converter to the DC bus. When the battery discharges and generated PV power is less than load power, VIEC controls the battery's DC-DC converter to the DC bus. VIEC controls both the PV's DC-DC converter and battery's DC-DC converter to the DC bus when generated PV power is more than the load power and battery is fully charged. VIEC emulates an additional virtual capacitance in parallel with DC link capacitors. DC bus voltage fluctuations are significantly reduced by the VIEC emulating virtual capacitors.

The invention relates to the technical field of power distribution of a power system, in particular to a grid interconnection light storage direct-flexible building power distribution structure method and system, and the system comprises an AC power distribution room, a public V2G charging pile, a building outdoor energy storage unit, an emergency power distribution area and a floor power distribution area, the AC power distribution room supplies power to the public V2G charging pile, the building outdoor energy storage unit and the emergency power distribution area, and the floor power distribution area supplies power to the building outdoor energy storage unit and the emergency power distribution area. And a converter is connected with a direct current bus in the building to supply power to the divided floor power distribution areas. Self-governance of partial areas in the building is realized, mutual power complementation and mutual supply can be realized among power distribution areas of all floors, flexible adjustment of power flow of a power distribution system in the building when a high-proportion distributed photovoltaic power supply is connected into the power distribution system of the building is realized, and local consumption of new energy is effectively realized; uncertainty and volatility caused by a large number of distributed power supplies in the power distribution system can be dealt with, and the power supply reliability of the system is enhanced.

The invention discloses a power distribution network photovoltaic power supply power distribution method based on online power flow feedback optimization. Firstly, system parameter initialization and data acquisition are performed to provide a basis for subsequent calculation. And constructing a power flow matrix, analyzing the result, and adjusting the output of the photovoltaic power supply in real time through online power flow feedback so as to maintain the stability of the power grid. On the basis, a power distribution model is constructed, various constraint conditions are incorporated, and an interior point method is adopted to solve and obtain an optimal or satisfactory scheme. Finally, the scheme is issued to a controller, initial power adjustment is carried out firstly, then secondary adjustment is carried out based on voltage feedback, and voltage safety is ensured. According to the method, fair power distribution is realized, and the utilization efficiency of a photovoltaic power supply is improved; various operation constraints are strictly followed, and power grid stability is guaranteed; the real-time dynamic adjustment capability is realized, and the power grid adaptability is enhanced; and moreover, continuous optimization is controlled through closed-loop feedback, so that the problem existing in power distribution of the photovoltaic power supply of the existing power distribution network is effectively solved.

A photovoltaic (PV) power prediction method based on an inverted Transformer combined with weighted decomposition consists of an inverted Transformer architecture, a weighted series decomposition module, and a probabilistic sparse attention mechanism. Step 1: The inverted Transformer architecture captures the complex nonlinear and volatile characteristics of PV power data, thereby improving the model's ability to learn multivariate correlations. Step 2: The weighted series decomposition module extracts the temporal characteristics and periodicity of PV data and introduces weights consistent with the actual PV power output variation pattern to constrain the model's output. Step 3: The probabilistic sparse attention mechanism combined with the inverted architecture enables the prediction method to maintain high computational efficiency when processing long-sequence data, enhancing model performance. Step 4: A two-stage structure is constructed to process different characteristics of PV data separately to improve prediction accuracy, robustness, and computational efficiency. Step 5: PV power prediction is performed through the prediction layer.

A DC microgrid has increased DC bus voltage inertia without adding large physical capacitors. A Virtual Inertia Enhancement Controller (VIEC) of a DC-DC converter emulates a DC machine's mechanical inertia characteristics through a virtual capacitor which compensates for a power imbalance causing DC bus voltage fluctuations. When a battery charges and generated photovoltaic (PV) power is more than the load power, VIEC controls the PV's DC-DC converter to the DC bus. When the battery discharges and generated PV power is less than load power, VIEC controls the battery's DC-DC converter to the DC bus. VIEC controls both the PV's DC-DC converter and battery's DC-DC converter to the DC bus when generated PV power is more than the load power and battery is fully charged. VIEC emulates an additional virtual capacitance in parallel with DC link capacitors. DC bus voltage fluctuations are significantly reduced by the VIEC emulating virtual capacitors.

The invention relates to the technical field of residual current protection, in particular to a power distribution network residual current protection method and system based on a distributed photovoltaic power supply, and the method comprises the following steps: obtaining a zero-sequence current waveform in a disturbance period, recognizing an abrupt change node, analyzing the fluctuation rhythm and trend, and constructing a response structure; the method comprises the following steps: extracting a sequence relationship between abrupt change nodes and fluctuation rhythms, constructing a response fragment set with trend consistency and rhythm coherence, screening response fragments capable of triggering protection, adjusting a starting point and a sequence, completing action triggering rhythm merging, and generating a residual current protection strategy, in the method, through sequence relationship extraction between the abrupt change nodes and the fluctuation rhythms, constructing a response fragment set with trend consistency and rhythm coherence, and combining a change cooperation relationship between sections; key paragraphs capable of triggering protection are screened out, the triggering sequence and the starting point position are adjusted according to trend continuity, the starting time sequence matching degree is improved, behavior stability is judged through trend coherence, rhythmic merging of response structures is achieved, action strategies with directivity and continuity are output, and the precise control capacity of protection response under variable disturbance is enhanced.

The invention discloses a fault property identification method utilizing active injection signals of a distributed photovoltaic power inverter, which belongs to the field of distributed photovoltaic, and comprises the following steps: when a power distribution line has a fault, a line protection device completes fault removal and fault phase selection; the line protection device sends the protection action information and the phase selection signal to the distributed photovoltaic power supply through a 5G network; after the distributed photovoltaic power supply receives the protection action information and the phase selection signal, the working mode of the inverter is changed, the pilot frequency signal is injected, the impedance identification calculation of the distribution line is carried out, and the effective discrimination of the fault property is realized, so that an additional device is not needed, and the fault identification reliability, stability and rapidity of the distributed photovoltaic power supply inverter are improved.

The invention relates to the technical field of power distribution networks, in particular to a power distribution network photovoltaic power supply power fair distribution method based on a game model. The method comprises the following steps: firstly, deploying a sensor in a power distribution network to collect the position information of photovoltaic power supplies, dividing sub-regions containing a certain number of photovoltaic power supplies through a K-Means algorithm, and counting the quantity of schedulable resources; secondly, participants, a strategy space and a revenue function are defined to construct a game model, and a Nash equilibrium solution method is used for obtaining a plurality of power distribution schemes through multiple iterations; and finally, performing NSGA-II algorithm initial population on the schemes, performing non-dominated sorting, crowding degree calculation, selection crossover mutation operation and population iteration updating, and selecting an optimal resource allocation scheme from Pareto optimal solutions according to the preference of a decision maker, thereby realizing fair distribution of the power of the photovoltaic power supply of the power distribution network, improving the stability of the power grid, the power generation efficiency and the cost effectiveness, and improving the economic benefit of the power distribution network. And reasonable utilization of resources is promoted.

The invention relates to a reactive power and active power comprehensive control method based on a photovoltaic grid-connected inverter. The method comprises the following steps: calculating the influence of a photovoltaic grid-connected inverter on the voltage of a power distribution network; calculating a voltage out-of-limit problem caused when a plurality of photovoltaic power supplies are connected to the power distribution network according to the influence of one photovoltaic grid-connected power supply on the voltage of the power distribution network; aiming at the voltage out-of-limit problem, on the premise of not changing the line structure of the power distribution network, not adding a reactive power compensation device and not using an on-load tap changer, a reactive power and active power comprehensive control strategy is constructed by taking the low-voltage power distribution network as a management node; the inverter is used for absorbing reactive power, unnecessary active loss is avoided, and the voltage of the power distribution network is reduced by cutting off part of active power. According to the invention, active power adjustment is added on the basis of reactive power adjustment. And when the reactive power cannot adjust the voltage to a specified range, the active power is increased to enable the voltage to reach the standard.

The invention provides a grid-connected frequency modulation control strategy based on photovoltaic power prediction so as to solve the problems of stability and safety of a power system under high-proportion photovoltaic grid connection. According to the strategy, new parameters representing characteristics of a traditional synchronous generator set and a photovoltaic system are introduced, and a control strategy of a power grid side inverter is improved based on actual grid-connected working conditions. Meanwhile, a frequency dynamic response model considering the photovoltaic penetration influence is established, and the inertia response of the synchronous generator set is accurately simulated by introducing the dynamic characteristics of a power grid side direct current capacitor. And by adjusting the virtual inertia and the adjustment factor, the anti-disturbance capability of the photovoltaic system is enhanced. In combination with historical photovoltaic power generation data, the photovoltaic power is predicted by adopting data normalization, feature selection, SOM clustering analysis, singular spectrum analysis and a full-connection network model, and the prediction accuracy is improved. And the control strategy is combined with the power prediction result to realize efficient and stable frequency modulation control of the grid-connected photovoltaic system.

The invention provides an intelligent monitoring system for catastrophe of a prestressed prefabricated segment assembled pier. The system comprises a monitoring module and a control module, wherein the monitoring module is made of high-strength and high-sensitivity fine aggregate concrete, a galvanized copper mesh electrode is arranged on the bottom surface of the high-strength and high-sensitivity fine aggregate concrete, and a direct-current power supply system is configured to be connected with the galvanized copper mesh electrode to form a loop and is used for monitoring deformation of the bridge pier under the action of a dynamic load in real time; the control module is composed of a shape memory alloy beam, a controller and a photovoltaic power source energy input and storage device connected with the controller and used for starting the energy recovery process when the bridge pier deforms greatly. According to the invention, important characteristics of two intelligent materials are combined and utilized to form the intelligent monitoring system for catastrophe of the prestressed prefabricated segment assembled pier. And in combination with a semi-active control theory, the control force can be automatically adjusted under the action of a dynamic load, and good effects are achieved in the aspects of energy consumption and recovery.

The invention discloses an ultra-short-term photovoltaic output prediction method based on multi-modal data and adaptive weights, and belongs to the technical field of electric power and artificial intelligence. Historical photovoltaic output data of a photovoltaic power station and sky image data at corresponding moments are acquired through measurement equipment, and a multi-modal photovoltaic prediction data set is constructed; respectively constructing an original sequence, a primary difference sequence and a secondary difference sequence for the historical photovoltaic output data, carrying out feature extraction, and carrying out feature extraction on the sky image sequence; a cross-modal attention mechanism is introduced, and interactive fusion between photovoltaic time sequence features and sky image features is realized; a fusion weight is generated based on sky image features, and adaptive weighted fusion is carried out on the multi-path features; and training an ultra-short-term photovoltaic output prediction model by using the fusion features, and predicting the photovoltaic output in real time. The method can improve the accuracy and stability of photovoltaic output ultra-short-term prediction, and is especially suitable for a novel power system operation scene with high-proportion photovoltaic access.