2070 results about "Optical storage" patented technology

According to the optical storage direct flexible system scheduling method based on multi-objective optimization and an adaptive scheduling strategy, monitoring devices are installed on a photovoltaic array, an energy storage unit and a load side, a data sensing network covering the whole link of'source-storage-load-network 'is constructed, and key data are collected in real time. A multi-objective optimization model with maximization of economical efficiency, reliability and clean energy consumption rate as objectives is established, and a hybrid optimization mechanism of a genetic algorithm and particle swarm optimization is adopted to generate a day-ahead scheduling reference scheme. And designing an adaptive scheduling algorithm and a dynamic parameter adjustment mechanism based on fuzzy logic, and combining a rolling optimization window to realize real-time optical storage coordination control and power real-time balance. According to the invention, the operation efficiency, stability and flexibility of the optical storage direct-flexible system are effectively improved, the capability of coping with emergencies is enhanced, and the optimization of the overall performance of the system is realized.

The invention relates to an optical storage cooperative control optimization method, electronic equipment and a medium. The method comprises the steps of collecting historical energy consumption and photovoltaic data of a park, constructing a photovoltaic electronic model based on the data, performing day-ahead prediction by adopting CNN-BiGRU, and generating a load power and photovoltaic generation power sequence; calculating the electricity consumption and the photovoltaic generating capacity of each time period; setting the capacity of an energy storage module, and calculating the energy storage charging and discharging capacity based on an SOC formula; according to the electricity consumption, the generating capacity and the energy storage capacity, determining a peak section discharge demand; photovoltaic fluctuation constraint is combined, and energy storage charging and discharging power is adjusted to stabilize fluctuation; optimizing load power utilization, photovoltaic power generation and energy storage power scheduling based on the power balance relation; and constructing a revenue maximization objective function, establishing a light storage collaborative optimization model in combination with constraints, and solving an optimal operation scheme of a prediction day. According to the method, photovoltaic power generation errors are reduced, power output is balanced, power grid requirements are met, the photovoltaic consumption rate is improved, healthy operation of the system is guaranteed, and operation benefits are improved.

The invention discloses a light storage and charging energy allocation system based on data driving and a control method, and relates to the technical field of light storage and charging energy allocation, and the method comprises the following steps: carrying out the real-time collection of the real-time power generation amount of a photovoltaic power generation system, the current power state of an energy storage battery, and the power consumption data of a load; and cleaning, normalization processing and time serialization are carried out on the collected data, so that the accuracy and continuity of the input data are ensured. According to the invention, by monitoring the power consumption data of the load in real time, combining with the long-term energy prediction model and dynamically adjusting the energy storage and discharge strategy, excessive discharge in a non-peak period is avoided, sufficient energy storage in a peak period is ensured, the power grid dependence is reduced, and the power consumption cost is reduced. Through load sudden increase detection and an adaptive scheduling algorithm, the system can quickly cope with sudden load changes, preferentially guarantee power supply of key loads, flexibly adjust a discharge mode, improve endurance time and system stability, and maximize green energy utilization efficiency.

The invention discloses an optical storage direct-flexible system power scheduling method based on market model prediction response, which comprises the following steps: determining the composition of an optical storage direct-flexible system, and collecting operation state data and external environment data; constructing a hybrid prediction model, and predicting the market price and the uncertainty interval of the market price in the scheduling period; establishing a power scheduling optimization model, and solving to obtain an optimal power scheduling strategy; according to the optimal power scheduling strategy, a control instruction is issued to each control unit of the optical storage direct flexible system, and cooperative adjustment is carried out through a bidirectional coupling feedback mechanism of voltage and power; the market price and the system operation state are monitored in real time, and when the market price deviation exceeds a price deviation threshold value, scheduling strategy online correction is triggered. According to the robust optimization architecture, traditional power scheduling is converted into a confrontation game structure between the system and the market, and the resistance of the system to extreme price situations is improved while economic benefits are guaranteed.

The invention provides an optical storage and charging cooperative control method and system based on multi-energy complementation. The method comprises the following sub-steps: respectively establishing a photovoltaic power generation model, an energy storage system model and a charging load model; acquiring historical illumination information, charging information and electricity price information, constructing a prediction model based on a neural network, and predicting and outputting illumination intensity, charging load demand power and electricity price in a future time period; constructing a target optimization function by taking the annual net cost and the power deviation rate as optimization targets; according to the method, the cooperative optimization control of the photovoltaic power generation, energy storage and charging system is realized, the annual net cost is reduced, the power deviation is reduced, the energy storage and charging cooperative control strategy is established, the target optimization function is solved by adopting the improved whale optimization algorithm, and the charging and discharging power sequence is generated according to the optimal solution obtained by solving and is input to the system for execution. And the operation efficiency and reliability of the whole system are improved.

The invention discloses a multi-source data fusion-based optical storage load collaborative optimization scheduling system and method, and relates to the technical field of photovoltaic energy storage optimization, and the method comprises the steps: building a photovoltaic power generation scene tree model and a load prediction model through obtaining historical photovoltaic power generation data, load power consumption data and meteorological data; constructing a first optimization target and a second optimization target by considering the operation income and the energy storage aging cost, considering the photovoltaic uncertainty based on the photovoltaic power generation scene tree model, and establishing an adaptive optimization scheduling model in combination with the load demand predicted by the load prediction model; the photovoltaic power generation scene tree model and the load prediction model are embedded into the adaptive optimization scheduling model, and the optimal energy storage charging and discharging strategy of the current time period is solved, so that the robustness and reliability of energy storage scheduling are improved while the economical efficiency of photovoltaic power generation is ensured.

An optical storage system designed to compensate for the water hammer effect in hydropower turbines and its cooperative frequency modulation method are provided. The method involves detecting the water hammer effect and utilizing a pre-established system model integrating a hydropower unit, photovoltaic system, and hybrid energy storage system. Through model predictive control combined with a whale optimization algorithm, the governor parameters of the hydropower unit are optimized. The system then obtains the photovoltaic active power output and the battery's state of charge (SOC) within the hybrid energy storage system. Based on these parameters, a collaborative control strategy for the photovoltaic and hybrid energy storage systems is determined and executed. This strategy enables effective control of the photovoltaic system and / or hybrid energy storage to compensate for reverse power adjustments in the hydropower unit, addressing the water hammer effect and ensuring stable power grid operation.

The invention discloses an optical storage and charging integrated charging station operation optimization system and method, and relates to the technical field of charging stations, and the system comprises an energy storage module, a charging pile module, a photovoltaic module, and an optical storage and charging management platform. The energy storage module comprises a plurality of energy storage battery packs, the charging pile module comprises a plurality of charging piles, the photovoltaic module comprises a plurality of photovoltaic panel groups, the plurality of photovoltaic panel groups form a photovoltaic array, and the photovoltaic storage and charging management platform comprises a data acquisition module, a data processing center and an optimization control module. According to the scheme, by accurately analyzing the power generation power change curve and the power generation efficiency of the photovoltaic module and combining the state of the energy storage module and the requirements of the charging pile, photovoltaic and energy storage cooperative power supply is achieved, photovoltaic power generation can be fully utilized, the light abandoning phenomenon is reduced, meanwhile, the energy storage charging and discharging strategy is optimized, the overall energy utilization rate is increased, and dependence on power grid electric energy is reduced; and energy utilization is more reasonable and efficient.

The invention discloses an optical storage and charging integrated micro-grid energy management system, relates to the technical field of micro-grid energy management, and is used for solving the problems of low energy scheduling efficiency and insufficient stability in an optical storage and charging system. The system comprises a power generation monitoring module, an energy storage management module, a charging load control module and an energy coordination module. The photovoltaic power generation state and environmental parameters are monitored in real time through a multi-type sensor network, and the running state of the photovoltaic module is judged; based on battery monitoring data and photovoltaic output characteristics, a differential energy storage management strategy is formulated; the charging power is dynamically distributed in combination with the energy state to realize charging and discharging intelligent regulation and control; by converging multi-source information, source storage and load interaction is coordinated to cope with different power states; accurate monitoring, intelligent scheduling and efficient cooperation of the photovoltaic, storage and charging integrated micro-grid are realized, and the energy utilization efficiency and the operation stability are remarkably improved.

The invention provides an intelligent scheduling control method for an optical storage charging and discharging integrated power station, and the method constructs a multi-time-scale prediction-optimization-correction three-stage control architecture, and achieves the real-time scheduling of the optical storage charging and discharging integrated power station through the coordinated operation in the upper-layer 24-hour rolling optimization, the middle-layer real-time scheduling and the lower-layer equipment control. And multi-target and multi-time-scale coordinated control optimization of maximization of the photovoltaic consumption rate, minimization of the power grid electricity purchase cost and prolonging of the service life of the energy storage system is realized. And a model prediction control algorithm is combined to dynamically adjust photovoltaic power generation output, an energy storage charging and discharging plan and a charging pile scheduling strategy. In addition, an adaptive parameter adjustment mechanism is introduced, and MPC parameters are adjusted online by using a reinforcement learning algorithm so as to cope with dynamic changes of environmental parameters and equipment states. The method can effectively improve the operation efficiency and economy of the optical storage charging and discharging integrated power station, prolongs the service life of an energy storage system, and is suitable for intelligent scheduling control of various optical storage charging and discharging integrated power stations.

The invention relates to the technical field of data processing, and discloses a cold and hot data exchange method and system based on optical storage and a storage medium. The method comprises the following steps: performing access feature acquisition and analysis on data in the optomagnetic hybrid storage system, calculating an access life cycle factor, generating a logic interval heat evaluation result, performing temperature grading, formulating a cold and hot data placement strategy, generating a data placement mapping table, executing batch migration according to priority, and updating a data position record. According to the method, the problem of how to realize logic interval hot degree accurate identification, temperature grade dynamic grading, storage mapping optimal matching and batch migration task efficient organization under the optomagnetic hybrid architecture is solved.

The invention relates to the technical field of power system engineering, in particular to a power distribution network safety assessment method and system based on an optical storage and charging system, and the method comprises the steps: collecting three types of key data of the optical storage and charging system; based on the three types of key data, establishing a power generation prediction model, constructing an energy storage scheduling strategy, and generating a load characteristic curve; calculating a node voltage deviation value and a branch power loss value of the power distribution network to form a network state evaluation index; performing comparative analysis on the network state evaluation index and a preset safety threshold value, and when the node voltage deviation value or the branch power loss value exceeds the preset safety threshold value, marking an abnormal node position; and for the abnormal nodes, adjusting the charging and discharging power of the energy storage system and the operation mode of the charging facility, and outputting optimized operation parameters of the optical storage and charging system. Through cooperative operation of the photovoltaic power generation system, the energy storage system and the charging facility, accurate evaluation and dynamic regulation and control of the node voltage and the line power loss of the power distribution network are realized, and the operation safety and the energy complementation efficiency of the power distribution network are improved.

The invention discloses a grid-connected inverter grid-following / grid-construction flexible switching method, system and device and a medium, and the method comprises the steps: building a control model of grid-following control and grid-construction control for a grid-connected inverter of an optical storage system; according to the power grid strength, hysteresis switching control is adopted to establish a switching criterion of network following / network construction control; and flexible switching of a phase angle and a dq-axis current reference value in grid-connected inverter control is realized by utilizing an integrator, voltage pre-synchronization and a state follower, so that flexible switching control of grid following / grid construction is realized. According to the stable complementary characteristics of the network following control and the network construction control under different power grid intensities, the stable operation of the optical storage system under the large-range change of the power grid intensity is realized by utilizing the network following / network construction flexible switching control.

The invention discloses an optical storage and charging integrated intelligent management system and method based on a virtual power plant platform, relates to the technical field of optical storage and charging, and aims to solve the problems that in energy storage battery management, long-time storage may cause increase of self-discharge rate of batteries and aggravated capacity attenuation, but an existing system often adopts a unified management strategy, batteries with different storage times are not distinguished, and the energy storage efficiency is poor. According to the optical storage and charging integrated intelligent management system and method based on the virtual power plant platform, the storage time and temperature of the energy storage battery are incorporated into a charging and discharging management strategy, so that the service life of the battery is prolonged; the charging and discharging logic can be dynamically adjusted according to charging requirements and light energy input changes, the adaptability of the system to complex conditions is enhanced, energy waste and charging delay are avoided, and the energy utilization efficiency is improved; the maintenance cost and the downtime are reduced, and the overall reliability and flexibility of the system are improved.

A self-adaptive control technology for rotational inertia and damping coefficient of an optical storage VSG system comprises a grid-connected system overall structure which is provided with an energy storage device, takes photovoltaic as a source end and is controlled by a grid-connected inverter virtual synchronous machine, and the grid-connected system overall structure is formed by electrically connecting a photovoltaic array, the energy storage device, an inverter, a DC / DC (Direct Current / Direct Current), a converter and a filter; the energy storage device is additionally arranged at a direct current bus of the system, the energy storage device and the photovoltaic array form a common direct current bus structure, the inverter is controlled by a virtual synchronous machine, inertial response and frequency adjustment are provided for the optical storage power generation system, and the power shortage between the photovoltaic array and the photovoltaic inverter is made up by adding the energy storage device; and the frequency deviation and the frequency change rate are introduced into VSG parameters, and the inertia and damping parameters of the VSG system are adaptively adjusted, so that the frequency stability of the micro-grid during power sudden change is improved, and the direct-current measurement energy storage power balance is met.

The invention relates to the field of optical storage, and particularly discloses an optical storage system cooperative control method and device, a terminal and a medium, and the method comprises the steps: collecting multi-dimensional data in real time, including photovoltaic array data, user side load data, power grid side information data, meteorological data and weather forecast information; generating a photovoltaic power generation power prediction curve, a user load demand prediction curve and a power grid electricity price prediction curve by using the multi-dimensional data through a machine learning model; and taking the current state of the optical storage system and each prediction curve as input parameters, carrying out optimization problem solving based on a multi-objective optimization function and constraint conditions through a model prediction control algorithm, generating an optimal control sequence in a period of time in the future, and controlling corresponding equipment through the optimal control sequence. According to the method, the response speed to uncertainties such as illumination abrupt change and load fluctuation is increased, source-storage-load-network coordination is realized, the sub-optimal problem of independent control of each unit is avoided, the operation cost is reduced, and renewable energy consumption is improved.

The invention provides an energy management and control platform system and a control method thereof. The method comprises the following steps: extracting a transient fluctuation quantity of electric power during each energy switching of a distribution unit and power distribution information in a stable power distribution state from historical energy distribution data to determine an electric power fluctuation entropy during energy switching of the distribution unit; according to the configuration information of the optical storage capacity in different time periods, determining the electric power unbalance degree when the load changes in the corresponding time period, and determining the capacity compensation cost when the configuration unit configures the optical storage capacity in different time periods according to all the electric power unbalance degrees and the change characteristics of the optical storage capacity configuration; determining an energy allocation predicted quantity, and adjusting the energy allocation predicted quantity through the power fluctuation entropy and all the capacity compensation costs to obtain an energy prediction adjustment value; and performing adaptive regulation and control on the optical storage capacity configuration of the configuration unit based on the energy prediction regulation value. By adopting the scheme of the invention, capacity self-adaptive configuration during transient fluctuation of the light storage energy can be realized, so that the stability of energy allocation is improved.

The invention provides an energy management system based on a cloud and edge integrated optical storage system. The energy management system comprises a cloud module and an edge module, the EMS controller is used for collecting information of the optical storage equipment module and the load module and uniformly sending the collected data to the cloud module; the cloud module predicts future photovoltaic power generation power / electric quantity through a photovoltaic power generation prediction model by receiving data acquired by the EMS controller; predicting a future load through the load prediction model; analyzing peak and valley time periods of the electricity price through the electricity price management model, and sending prediction data to the edge module; and the edge module carries out energy management through the control logic of energy management according to the battery SOC, the chargeable amount, the photovoltaic predicted power and the generating capacity, and superposition peak-valley arbitrage and safe anti-countercurrent logic. Through the arrangement, the whole energy management system has high intelligence and automation levels, energy distribution and use are optimized, and the energy utilization efficiency is improved.

The invention discloses an energy storage capacity configuration method for cluster regulation and control of an optical storage and charging station, relates to the technical field of capacity configuration, and effectively solves the problem of balancing economy and robustness of a traditional method through a hierarchical collaborative energy storage capacity configuration mechanism. The established source-load difference uncertainty model accurately quantifies the space-time coupling characteristics of the photovoltaic output and the charging load, and avoids capacity redundancy caused by deterministic planning; independent energy storage is configured on the basis of sub-cluster differentiation requirements, repeated investment of distributed energy storage is reduced through local fluctuation stabilization, and meanwhile, single-point capacity requirements are reduced by using complementary characteristics in clusters; shared energy storage is introduced and a cross-cluster collaborative optimization model is constructed, so that the overall capacity utilization rate is remarkably improved; on the premise that high-proportion photovoltaic consumption and reliable power supply of a charging load are guaranteed, the adaptability to extreme scenes is enhanced through a layered response mechanism, and an extensible solution is provided for a power system.

The invention discloses a system processing method and device, a storage medium and electronic equipment, and relates to the technical field of optical storage. The method comprises the following steps: acquiring historical generating capacity data of a photovoltaic power generation system, historical state information of an energy storage system and historical consumption data of load equipment; inputting the historical generating capacity data, the historical state information and the historical consumption data into a target prediction model, and predicting to obtain generating capacity data of the photovoltaic power generation system in a first preset time period and load demand data of the load equipment in the first preset time period; generating an initial operation plan according to the generating capacity data and the load demand data; and determining a target operation plan based on the initial operation plan, and adjusting the operation states of the photovoltaic power generation system and the energy storage system according to the target operation plan. According to the invention, the problem that the operation efficiency of the photovoltaic power generation system and the energy storage system is low because the operation state of the photovoltaic and energy storage system is adjusted based on a fixed operation strategy in the prior art is solved.

The invention relates to an optical storage direct flexible park adjustable load orderly energy using method and device and computer equipment. The method comprises the following steps: constructing a micro-grid architecture model of the optical storage direct-current flexible park according to equipment power utilization characteristics and power resource scheduling information of the optical storage direct-current flexible park; constructing an equipment operation model corresponding to each piece of power equipment according to the equipment operation characteristics of each piece of power equipment in the optical storage direct flexible park; according to the micro-grid architecture model and each equipment operation model, constructing an adjustable load ordered energy use objective function of the optical storage direct flexible park and park equipment operation constraint conditions; the park equipment operation constraint condition is used as a limit, an adjustable load ordered energy use target function is solved, and adjustable load ordered energy use adjustment information of the optical storage direct flexible park is obtained; the adjustable load orderly energy utilization adjustment information is used for adjusting the power resource distribution condition of the optical storage direct flexible park. By adopting the method, the satisfaction degree of the user on the regulation and control means of the adjustable load can be improved.

The invention discloses a multi-objective optimization scheduling optical storage and charging integrated coordination control method and system, and the method comprises the steps: analyzing the working characteristics of an optical storage and charging integrated system, and obtaining the operation characteristics of all components; carrying out resource modeling on the light storage and charging integrated system, and establishing a photovoltaic power generation model, an energy storage battery model and an electric vehicle load characteristic model; establishing a multi-target optimization scheduling model taking the lowest electricity purchase cost and the lowest cycle electricity quantity as targets; and solving through a multi-target genetic algorithm to obtain an optimal solution of the scheduling scheme which comprehensively considers the cost and the cyclic electric quantity. According to the multi-objective optimization solution, the importance degrees of the two objective functions can be artificially accepted and rejected, and optimization control strategies under the condition that the objective function results are different are obtained; the algorithm is high in adjustability, and the effectiveness of the optimized scheduling strategy is improved.

The invention discloses a residual capacity harmonic compensation method for a household single-phase optical storage cooperative converter, and belongs to the technical field of converter control. The invention aims to provide a dynamic harmonic compensation method for household single-phase photovoltaic energy storage under limited power capacity and a residual capacity harmonic compensation method for a household single-phase photovoltaic energy storage cooperative converter based on an energy management harmonic priority compensation strategy. The household single-phase optical storage cooperative converter adopts a harmonic current priority compensation strategy, and the core of the harmonic current priority compensation strategy is to increase the residual current margin of a grid-connected inverter by utilizing photovoltaic load shedding and controlling the energy storage charging power, so that harmonic waves are completely compensated. Through a dynamic harmonic current compensation technology, when the output current of the grid-connected inverter exceeds a rated value, the harmonic current value is reduced through a harmonic current compensation factor, so that the output harmonic current value of the inverter is flexibly limited, and the harmonic current is compensated to the maximum extent while the grid-connected inverter works normally.

The invention relates to an optical storage and charging alternating current and direct current hybrid micro-grid construction control method and device and a medium. According to the method, level-to-level management is carried out on an energy storage converter according to an SOC value of an energy storage device. And the converter with the high priority is switched to a VSG mode, and whether the voltage and frequency fluctuation of the micro-grid exceeds an adjustment dead zone or not is detected. When the frequency fluctuation is exceeded, active power output is adjusted through a VSG mode; when the voltage fluctuation is exceeded, the reactive power output is adjusted. And the energy storage equipment is switched to the VSG mode step by step, and when the requirements cannot be met, the photovoltaic equipment and the electric automobile support power grid are put into use in sequence. Before the photovoltaic equipment is connected, the voltage of the photovoltaic equipment is synchronized to be consistent with that of the connected energy storage equipment, and the VSG mode is converted. And if further support is still needed, the electric vehicle is used for feeding by adjusting a charging pile control algorithm. And the voltage and the phase need to be synchronized before the electric vehicle is connected so as to cooperatively support the micro-grid. According to the method, the voltage and frequency stability of the micro-grid system is remarkably improved.

The invention relates to the technical field of photovoltaic power generation energy storage grid connection, and discloses an optical storage VSG control method and system for coordinating power maximum output and energy storage, and the method comprises the steps: building an output power-angular frequency model between the output power of an inverter and the angular frequency of a VSG virtual rotor based on a VSG control principle; establishing a direct current capacitor voltage-output power model; establishing a control model of the proportional relation between the direct current side voltage and the output frequency deviation; simulating droop control between the input power and the rotor speed in the synchronous generator, associating the battery power with the direct current side voltage, establishing a battery droop control strategy, and transferring the battery power change response demand to a direct current side capacitor; active-power control in a traditional photovoltaic energy storage power generation system control principle is optimized, and a battery droop control strategy is established, so that battery power change response demands are transferred to a direct current side capacitor, more photovoltaic energy is utilized, and demands and adverse effects on photovoltaic power generation absorbed by a local battery are reduced.

The invention relates to the technical field of hierarchical storage, in particular to a photo-electromagnetic storage method and system based on hierarchical management, and the method comprises the following steps: collecting read-write speed, error rate, durability and cost data of optical storage and electromagnetic storage media, carrying out the sorting and grading processing of the data according to the read-write speed and the error rate, and carrying out the sorting and grading processing of the data; and performing score calculation on each storage medium to obtain a medium performance score. According to the method and the device, the data is effectively distributed to the most suitable storage medium by accurately scoring the performance of the storage medium and combining specific requirements of the to-be-stored data, so that the data access speed and efficiency are improved, the total storage cost is reduced, and particularly, when a large amount of data is processed, the data compression level and the encoding format are dynamically adjusted, and the data compression efficiency is improved. The storage efficiency of the data is further optimized, data redundancy is reduced, the overall performance of data storage and access is remarkably improved through optimization measures, and meanwhile long-term safety and integrity of the data are ensured.

The invention relates to the technical field of power grid dispatching, and discloses an optical storage direct-current flexible micro-grid multi-target optimization dispatching system, which comprises a photovoltaic power generation module, an energy storage module, a direct-current power supply module, a flexible power supply module and a multi-target optimization dispatching module, and is characterized in that the multi-target optimization dispatching module comprises a monitoring unit used for monitoring each load unit in real time, acquiring basic power utilization information; the prediction unit is used for carrying out load prediction on the load unit at each moment every day according to the power utilization basic information; and the optimal scheduling unit is used for establishing a multi-target model by adopting a multi-target optimization algorithm and by taking the lowest daily operation cost and the maximum photovoltaic consumption rate of the optical storage direct-flexible micro-grid as targets, and solving the multi-target model based on a load prediction result to obtain an energy scheduling scheme of the optical storage direct-flexible micro-grid. According to the invention, the operation state of the micro-grid can be predicted and scheduled more accurately, so that an energy scheduling scheme with a better effect is obtained, and the energy utilization efficiency and the system operation stability are improved.

The invention provides an optical storage parallel network control method, which comprises the following steps: calculating the current load rate percentage of each residual unit according to the connection relation and electrical path information of the residual units after isolation; evaluating the available margin capacity and the frequency regulation bearing capacity of the remaining units, matching the available margin capacity and the frequency regulation bearing capacity with a specific power value and a frequency regulation requirement which need to be compensated, and determining a feasible unit combination scheme for fault recovery; generating a power redistribution list and a frequency adjustment responsibility distribution table according to the direct current bus connection mode of the optimal unit recombination, and obtaining an output power set value and a frequency adjustment parameter of each unit after adjustment; and extracting the continuous power supply time value of the optical storage parallel network, updating the total power supply capacity value of the optical storage parallel network, and maintaining the continuous power output and frequency stability after the fault of the optical storage parallel network.

The invention relates to a reliability evaluation method and system for a flexible AC / DC power distribution network containing an optical storage system in the field of flexible AC / DC power distribution networks. The method comprises the following steps: collecting photovoltaic data, energy storage data, AC / DC bus data and the like in real time; constructing a multi-time scale dynamic topology model, and establishing a failure probability distribution function; load flow calculation based on an improved forward-backward substitution method; adopting an N-1 + N-1-1 composite fault screening strategy to simulate a typical disturbance scene; establishing a vulnerability evaluation matrix to calculate power failure probability and other indexes; designing an optimal scheduling strategy based on model predictive control; multi-time-scale reliability evaluation is carried out; and outputting an evaluation report and a topology reconstruction suggestion. The system comprises a data acquisition unit, a dynamic modeling unit and the like, and an evaluation and analysis unit is internally provided with an algorithm module and is configured with an FPGA acceleration card. The method breaks through the limitation of traditional steady state evaluation in the technology level, improves the load flow calculation speed in the calculation efficiency level, reduces the operation cost in the application value level, improves the energy storage efficiency, and provides support for reliability evaluation of a novel power system.

The invention provides a photovoltaic output prediction method and a distributed optical storage transformer area active / reactive support capability optimization method, and belongs to the technical field of power system automation. Comprising the following steps: constructing a prediction model based on meteorological information, extracting multi-scale features of meteorological data, reducing dimensions through kernel principal component analysis, predicting photovoltaic power through a long-short-term memory network, quantifying the uncertainty of the photovoltaic power, and forming a prediction interval. Based on a photovoltaic power prediction result, a robust nonlinear programming model is established, the sum of absolute values of active / reactive power transmitted to a main power grid by a light storage area is maximized as a target, and linear and nonlinear constraints such as energy storage operation, power balance, equipment capacity and power factors are considered at the same time. The robustness under the photovoltaic output uncertainty is ensured through a budget uncertainty set; the model is solved by adopting a sequential quadratic programming algorithm. According to the method, the photovoltaic power prediction precision is effectively improved, and organic combination of high-precision prediction and robust nonlinear optimization is realized.