643 results about "Energy storage efficiency" patented technology

The invention relates to an intelligent charging method and system based on light and wind complementation and intelligent energy storage. According to the method, dynamic optimized charging is realized through multi-source data collaborative decision, and the method comprises the following steps: firstly, collecting real-time data such as light-wind power generation, energy storage SOC, charging load and commercial power supply, analyzing a wind-solar power generation complementary relationship and calculating a real-time complementary coefficient; a dynamic weight distribution scheme of light wind and commercial power is generated in combination with the commercial power state, and an energy storage charging and discharging instruction is generated by fusing peak and valley electricity prices and energy storage efficiency optimization; and based on the adjusted energy storage output power, comprehensively considering the charging demand and the vehicle battery state, and dynamically distributing the power of the charging pile through the charging priority. By adopting the method, energy complementation, economic scheduling and charging demand management can be combined, the utilization rate of renewable energy sources is effectively improved, and the charging cost is reduced.

The invention discloses a circulating type gravity energy storage transportation system which comprises a master controller, an annular rail, a high-position storage yard and a low-position storage yard, a transportation train is composed of a plurality of carriages which are flexibly connected and arranged on the annular rail, a low-position running rail is arranged on the annular rail, the high-position running rail is provided with a linear loading and unloading section, and the low-position running rail is provided with a linear loading and unloading section. A plurality of grabbing parts are arranged on the high-position storage yard and the low-position storage yard and move back and forth between the loading and unloading section and the stacking area, and the hoisting device is electrically connected with the master controller. By means of the double-circulation design of train circulation operation and heavy block rapid loading and unloading, the core pain points that an existing gravity energy storage system is not coherent in operation and low in efficiency are effectively solved, and the energy storage efficiency is improved. And a reliable system solution is provided for realizing large-scale, high-efficiency and fast-response gravity energy storage commercialized application.

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.

The invention discloses a park energy storage intelligent scheduling system and method based on big data, and relates to the technical field of big data park energy storage intelligent scheduling, and the method comprises the following steps: S100, collecting the real-time operation data of multiple types of energy systems in a park, constructing a time sequence database, and carrying out the preprocessing; s200, predicting load change based on an energy demand scene, and constructing a polymorphic energy storage model in combination with dynamic characteristics of energy storage equipment; s300, defining a multi-objective optimization function taking energy loss, renewable energy utilization rate and energy storage efficiency as cores, establishing a total energy balance model, and setting constraint conditions of charging and discharging and heat and cold storage power of energy storage equipment; and S400, updating the load demand and the energy storage state by using the real-time data, calculating the load deviation and correcting the target function, and readjusting the charging and discharging of the energy storage equipment and the heat storage and cold storage power distribution according to the corrected target function.

The invention relates to the technical field of supercritical compressed carbon dioxide energy storage, in particular to an adiabatic supercritical compressed carbon dioxide energy storage system. An expansion unit; during energy storage, the heat storage tank stores compression heat of the supercritical carbon dioxide in the high-temperature and high-pressure state, and the supercritical carbon dioxide in the high-temperature and high-pressure state is cooled to the temperature the same as that of the high-pressure gas storage chamber; during energy release, the heat storage tank heats the low-temperature high-pressure supercritical carbon dioxide discharged from the high-pressure gas storage chamber; the temperature control system adjusts the flow of the cooling medium in the second heat exchanger, controls the inlet temperature of the compressor and further adjusts the inlet temperature of each stage of expansion machine, it is guaranteed that the carbon dioxide temperature of the inlet position of each stage of expansion machine is not lower than the liquefaction critical temperature, and the large-area liquefaction phenomenon does not occur. According to the temperature control system, the phenomenon that in the prior art, when carbon dioxide is at low temperature, carbon dioxide is liquefied, and large-area condensation occurs in the expansion machine can be effectively overcome, and then the operation efficiency and the energy storage efficiency of the system are guaranteed.

The invention belongs to the technical field of energy storage, and particularly relates to a vertical circulation type gravity energy storage system based on a linear motor, the vertical circulation type gravity energy storage system comprises a circulation shaft, a carrying platform system and an energy storage system, the circulation shaft comprises a heavy object shaft, a no-load shaft and a horizontal channel, and a secondary switching disc is arranged at the joint of the heavy object shaft and the horizontal channel and the joint of the no-load shaft and the horizontal channel; the heavy well, the no-load well, the horizontal channel and the secondary switching disc are each provided with a secondary driving side, and each secondary driving side comprises a first rail set and a linear motor secondary; the platform deck system comprises a plurality of platform decks, the platform decks are used for bearing heavy objects, primary switching discs are arranged on the side faces of the platform decks, primary driving sides are arranged on the platform decks and the primary switching discs, and each primary driving side comprises a second track set and a linear motor primary; the energy storage system includes an upper storage bin, a lower storage bin, and a loading and unloading zone. The energy storage capacity expansion mode is simple, the expansion cost is low, the energy storage capacity configuration is flexible, and the energy storage efficiency is high.

The invention discloses an intelligent distributed photovoltaic power station optimal scheduling and operation and maintenance management method and system, and relates to the technical field of optimal scheduling. Historical power generation data, real-time meteorological data and future weather forecast of a photovoltaic power station are acquired; according to the historical power generation data, the real-time meteorological data and the future weather forecast, inputting the historical power generation data, the real-time meteorological data and the future weather forecast into a pre-trained power generation prediction model to obtain a photovoltaic power generation prediction value in a future time period; and obtaining the power grid demand power of the photovoltaic power station, and planning the charging and discharging strategy of the energy storage system according to the absolute value of the difference between the power grid demand power and the photovoltaic power generation prediction value. The difference between the power grid demand power and the photovoltaic generating capacity prediction value is analyzed, the output power of the photovoltaic power station and the charging and discharging mode of the energy storage system are adjusted according to the difference, the completion degree of the charging and discharging strategy is judged through the charging and discharging time of the energy storage system, the adjusting function of the energy storage system is fully played, and the energy storage efficiency is improved. And the reliability and continuity of power supply are improved.

The invention discloses an energy storage efficiency improvement method and system combined with energy management, and relates to the technical field of intelligent power grids, and the method comprises the steps: collecting the state data, environment data and load data of an energy storage unit through a sensor network, obtaining the information of a power grid through the Internet, and carrying out the real-time processing; constructing a prediction model based on the multi-level memory network, and predicting future load demands and electric energy supply conditions; according to the prediction result, combining the real-time state of the energy storage unit and the power grid information, generating a preliminary charging and discharging instruction, and sending the instruction to an edge node; performing preliminary decision on the preliminary charging and discharging instruction at the edge node, generating a local charging and discharging plan, and uploading the local charging and discharging plan to a cloud server; the cloud server gathers the local charging and discharging plans, carries out global optimization, generates a final charging and discharging instruction, and issues the final charging and discharging instruction to the energy storage unit; through the prediction model constructed based on the multi-level memory network, the prediction precision is remarkably improved, and meanwhile, through a physical constraint embedding mechanism, the credibility of a prediction result is ensured.

The invention relates to the technical field of phase change heat storage, in particular to a test method of a composite nanoparticle latent heat system based on a Fibonacci fractal tree-shaped fin. The test method comprises the following steps: firstly, establishing a physical model of a nanoparticle three-sleeve vertical latent heat system based on the Fibonacci fractal tree-shaped fin; secondly, performing two-dimensional simulation analysis on the physical model by adopting a two-dimensional model, simulating the melting and solidification process of the PCM, analyzing the heat transfer performance and energy storage efficiency of the system, building an experimental device of a nano-particle three-sleeve vertical latent heat system based on the Fibonacci fractal tree-shaped fins, selecting proper PCM and nano-particles, simulating different working conditions, and establishing a three-sleeve vertical latent heat system based on the nano-particle three-sleeve vertical latent heat system based on the Fibonacci fractal tree-shaped fins. And finally, comparing a simulation result with an experimental result, adjusting parameters of a simulation model, improving the accuracy of the simulation result, analyzing the influence of different fin bifurcation angles, nanoparticle types, wall surface temperatures and fin materials on the heat transfer performance and energy storage efficiency of the system, and providing guidance for optimal design of the system.

The invention relates to the technical field of intelligent monitoring, in particular to an intelligent monitoring type photovoltaic power generation system, which converts light energy into electric energy through a photovoltaic module and stores the electric energy, and changes the thermal compensation condition of the temperature of each area of an energy storage battery according to the actual situation. The temperature of different areas of the energy storage battery is monitored through the monitor, the electric energy parameters of the energy storage battery are obtained, historical data monitored by the monitor are stored through the prior analyzer, and a severe influence period and a gentle influence period are distinguished through the photovoltaic controller based on temperature influence tendency characterization values corresponding to different temperature influence periods. And monitoring the energy storage battery, determining an energy conversion characterization parameter to predict whether the energy storage effect of the energy storage battery meets a predetermined standard or not so as to determine whether the thermal compensation device is started or not, and adaptively intervening the thermal compensation device by considering the influence of the temperature difference of the energy storage battery on the energy storage efficiency in the operation process of the photovoltaic system. Therefore, the energy storage efficiency and the power generation efficiency of the photovoltaic system are ensured.

The invention relates to the technical field of information, in particular to a control method and system for an intelligent photovoltaic charging pile in the technical field of automobile charging piles, and the method comprises the steps: obtaining the charging demands and residual electric quantity information of a plurality of electric automobiles, dynamically adjusting the charging power of each automobile through combining with an electric power distribution algorithm, and guaranteeing the reasonable distribution of electric power resources; acquiring real-time load data through a power grid load monitoring system, predicting a future power grid load change trend in combination with a historical load curve, and judging whether a charging strategy needs to be adjusted or not; according to historical data and real-time data, cooperative working parameters of photovoltaic power generation and storage battery power storage are optimized by adopting a machine learning algorithm, and the overall efficiency of the system is improved; a cooperative working mode of photovoltaic power generation, storage battery power storage and power grid power supply is dynamically adjusted through an intelligent optimization algorithm; if the illumination fluctuation is large, a standby power supply is started to supplement power supply, it is ensured that the charging process is not affected, meanwhile, the energy storage efficiency is optimized, and power resource waste is reduced.

The invention relates to the technical field of energy storage systems, and provides a capacity configuration method for a multi-power hybrid energy storage system, which comprises the following steps: S1, analyzing load requirements in different application scenes in detail, and accurately determining energy storage requirements and formulating differentiated capacity configuration strategies by analyzing the load requirements in the application scenes and characteristics of a power grid and new energy in detail; the hybrid system is constructed by combining various energy storage technologies, effective complementation of energy and power is realized, meanwhile, based on a multi-target optimization model and an advanced optimization algorithm, an optimal solution can be found under complex constraints, the energy storage economy is improved, the power state of an energy storage unit is estimated in real time by adopting a recursive least square method, and the energy storage efficiency is improved. The self-adaptive energy management strategy is designed in combination with the rolling optimization concept, the accuracy of power estimation is improved, efficient energy management of the energy storage system is achieved, the service life of equipment is prolonged, energy loss is reduced, and the problem of insufficient energy storage economy in the prior art is solved through the technical scheme.

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 discloses an energy storage cabinet temperature control method based on a cloud platform and a temperature control energy storage cabinet, and relates to the technical field of electric energy storage, the energy storage cabinet comprises a cabinet body, an energy storage module, a data acquisition module, a communication module and a temperature control module, and the temperature control method comprises the following steps: S1, acquiring environmental parameters and battery state data; s2, determining a temperature adjustment factor of the energy storage cabinet through the battery state data; s3, generating a composite temperature index based on the environmental parameters and the temperature adjustment factor; s4, performing region division on the energy storage cabinet, determining temperature requirements of different regions according to the composite temperature index, and formulating an energy storage cabinet temperature control strategy based on the temperature requirements in combination with the environment prediction temperature; s5, the cloud platform generates a control instruction based on the temperature control strategy and issues the control instruction to the energy storage cabinet to execute the control instruction; accurate control over the temperature in the energy storage cabinet can be achieved, it is ensured that energy storage equipment operates within the optimal temperature range, the energy storage efficiency is improved, and the service life of the equipment is prolonged.

The invention discloses an optical storage layered collaborative optimization control method coupling photovoltaic priority absorption and time-of-use electricity price, and relates to the technical field of new energy power system optimization control. The method comprises the following steps: taking a photovoltaic generating capacity prediction value, a load electricity consumption prediction value and peak and valley electricity price information as input data; carrying out rolling optimization by utilizing a model prediction control framework, and generating a light storage plan table; and calculating a photovoltaic output regulation value and energy storage charging and discharging power based on the generated light storage plan table in combination with the photovoltaic power generation power and the load power consumption power which are acquired in real time, executing corresponding energy storage charging and discharging and photovoltaic output processing by applying a decision tree control mechanism, and optimizing light storage control according to a processing result. According to the method, the photovoltaic preferential consumption strategy is executed, the light abandoning amount is reduced, the photovoltaic consumption rate is improved, the time-of-use electricity price dynamic response mechanism and the energy storage efficiency compensation and light abandoning punishment mechanism are combined, peak-valley arbitrage is maximized, meanwhile, the comprehensive electricity utilization cost is reduced, and the power purchase demand of a power grid is reduced.

The invention relates to a dynamic network reconstruction strategy of a digital electric power energy storage system in the technical field of electric power energy storage. The strategy comprises the following steps: S1, building an energy storage system; the system consists of an intelligent layer, a control layer and a data layer, s2, modeling an energy storage network; learning an optimal control strategy of the energy storage network by adopting a graph capsule neural network; s3, dynamic network reconstruction; generating a fault emergency response model based on a Markov decision process; by systematically optimizing a topological structure and an optimal control strategy of the energy storage network, rapid isolation of a fault area and dynamic adjustment and reconfiguration of working modes of energy storage equipment and load equipment are realized, the energy storage network is ensured to still operate stably in a fault situation, and the energy storage efficiency is improved. The flexibility and elasticity (fault tolerance) of the energy storage system in a dynamic environment are improved; by reducing the energy loss in the transmission process, balancing the network load and preventing local faults, the technical problems existing in the prior art are solved, and the sustainable development of a novel renewable energy system is promoted.

The invention belongs to the technical field of energy storage, and particularly relates to a vertical circulation type single-well gravity energy storage system based on a linear motor, the vertical circulation type single-well gravity energy storage system comprises a weight storage system, an energy storage unit, a transportation system and a power system, and the weight storage system comprises an upper-layer energy storage chamber and a lower-layer energy storage chamber which are arranged up and down; the energy storage unit comprises a plurality of energy boxes and a plurality of weights arranged in the upper-layer energy storage chamber and the lower-layer energy storage chamber; the transportation system comprises a transportation track penetrating through the upper-layer energy storage chamber and the lower-layer energy storage chamber, and the transportation track is used for transporting the energy box; the power system comprises a secondary linear motor arranged on the conveying rail and a primary linear motor arranged on the energy box and is used for providing power for the energy box. The energy storage capacity expansion mode is simple, the expansion cost is low, the energy storage efficiency is high, the continuity of output or input power can be realized, and the fault tolerance performance is high.

The invention relates to the technical field of energy storage modules, in particular to a direct-current power supply energy storage system suitable for various household appliances. According to the method, the current change value and the power fluctuation range of the energy storage unit are analyzed, statistics of the power change amplitude and the time interval is combined, the work cycle rule of the energy storage unit is defined, the power difference between the partitions is extracted through the Markov chain model, and real-time balance of the partition power supply state is achieved by gradually optimizing path distribution. And resource waste caused by power fluctuation is effectively reduced. Through gradual correction of a real-time output power value and a target power value, dynamic power matching of an energy storage unit is realized, the flexibility and accuracy of energy distribution are improved, voltage fluctuation trend is monitored and adjusted through a variational mode decomposition technology, voltage stability control of an energy storage module is realized, the reliability of an energy storage system is optimized, and the energy storage efficiency is improved. And the overall stability and the energy utilization efficiency are improved by matching the output power and the frequency adjustment range.

The invention belongs to the technical field of aluminum alloy extrusion profiles, and relates to a high-strength 3-series aluminum alloy extrusion profile, a preparation method thereof and application of the high-strength 3-series aluminum alloy extrusion profile in an energy storage device. According to the high-performance 3-series aluminum alloy and the profile preparation method thereof, when the relation that Mn + Si + Zr + Sn is larger than or equal to 1.70 wt% and smaller than or equal to 2.5 wt% is met, the tensile strength Rm of the whole 3-series aluminum alloy is larger than or equal to 150 MPa, the yield strength Rp0.2 is larger than or equal to 110 MPa, the ductility A50 is larger than or equal to 10%, remarkable technical progress is brought to the energy storage industry, the problems existing in a traditional process are solved, and the energy storage efficiency is improved. And the requirements of the industry for light weight, high strength and corrosion resistance are met, and the development of the energy storage industry is promoted.

The invention relates to the technical field of dielectric materials, and discloses polyimide, a polyimide film and a preparation method and application thereof, the polyimide is obtained by a polymerization reaction of a dianhydride monomer and a diamine monomer, the diamine monomer comprises a methylene bridging group and a phenyl group with a substituent group, and the methylene bridging group is a phenyl group with a substituent group. The substituent group at least comprises one methyl group. The molecular twisted conformation lock structure provided by the invention not only can improve the tolerance of polyimide, but also can doubly inhibit intrachain and inter-chain charge migration of the dielectric film, so that the dielectric film still has extremely high energy storage density and energy storage efficiency at a service temperature close to a glass-transition temperature.

The invention discloses an air conditioner energy storage system based on intelligent control and a peak-valley electricity price utilization method, and relates to the technical field of air conditioner control. Comprising an energy storage module, an air conditioner module and an intelligent control module. And the intelligent control module is set to dynamically solve an optimal control sequence through a model prediction control algorithm based on predicted environmental parameters, electricity price information and user requirements in a future time period by taking the lowest operation cost as a target, and to control the start, stop and power of the valve, the refrigeration host and the associated water pump, so that the optimal control sequence is obtained. Therefore, the system preferentially charges the energy storage module in the electricity price valley section and preferentially utilizes the energy storage module to supply energy in the electricity price peak section, the load can be accurately predicted, the energy storage state can be sensed in real time, the air conditioner host and the energy storage device can be dynamically and intelligently coordinated in the whole operation period based on a multi-target optimization algorithm, and the energy storage efficiency is improved. Therefore, the peak-valley price difference is utilized to the maximum extent on the premise of ensuring the comfort of the user.

The invention relates to a pumped storage and compressed air energy storage coupled scheduling method, which comprises the following steps of: establishing a multi-stage data system based on input data of multiple time scales; constructing a multi-time scale scheduling model; when the load of the pumped storage mixed compressed air energy storage power station is lower than a first preset threshold value, electricity is abandoned preferentially, water pumping and compression are conducted, and when the load is larger than a second preset threshold value, the pumped storage mixed compressed air energy storage power station is controlled to conduct combined energy release. The nonlinear relation between the pumped storage efficiency and the water level and the nonlinear relation between the compressed air energy storage power and the pressure are converted into linear constraints, solving is conducted by dividing the water level interval and the pressure level, and a scheduling strategy is obtained. Therefore, the problems of relatively low energy storage efficiency, insufficient scheduling refinement, relatively high system standby cost and the like caused by the problems that pumped storage water scheduling and CAES energy management are separated, a standby capacity coordination mechanism is lacked and the like in a hybrid system scheduling method in related technologies are solved.

The invention discloses a constant-pressure type compressed air energy storage system and method combined with pumping and storage, and belongs to the technical field of electric energy physical energy storage systems, and the constant-pressure type energy storage system comprises a pumped storage subsystem, a turbine expansion power generation subsystem, a compressed air energy storage subsystem and a water-gas common-capacity cabin constant-pressure subsystem. By flexibly controlling the operation modes of the subsystems and the on-off states of valves among the subsystems, the system can achieve independent energy storage and power generation operation among the pumped storage subsystem, the air compression subsystem and the turbine expansion subsystem. The design not only improves the flexibility and reliability of the system, but also enables the system to carry out optimal configuration and operation according to actual demands, thereby further improving the energy storage efficiency and economic benefits.

The invention provides a distributed photovoltaic energy storage method and system based on a deep learning model, and the system comprises a data collection and preprocessing module, a deep learning model construction module, a model training and optimization module, an energy storage control strategy module, a cooperative work and optimization module, and a system monitoring and feedback module. A deep learning model can accurately predict photovoltaic power generation capacity and load requirements, realizes optimized charge and discharge control of energy storage equipment, maximally utilizes photovoltaic energy and reduces energy waste, and meanwhile, the deep learning model can quickly learn and adapt to a new operation scene and a data mode, so that the energy storage efficiency is improved. The system can cope with various complex and changeable environments and load conditions, and through accurate prediction and an intelligent control strategy, the fluctuation of photovoltaic power generation is effectively stabilized, the stable power supply of the micro-grid under different working conditions is ensured, and the fluctuation of voltage and frequency is reduced.

The invention discloses an energy storage monitoring method and system, electronic equipment and a storage medium, and relates to the technical field of energy storage. The method comprises the following steps: acquiring voltage data and temperature data of a plurality of different types of battery units; generating a voltage response curve of the corresponding battery unit based on each voltage data, and generating a temperature response curve of the corresponding battery unit based on each temperature data; dividing each battery unit into a plurality of battery packs with different charging and discharging characteristics according to each voltage response curve and each temperature response curve, and calculating the residual electric quantity value of each battery unit in each battery pack; in each battery pack, determining an electric quantity difference value between the battery units in combination with the residual electric quantity value of each battery unit, and taking each battery unit of which the electric quantity difference value is greater than an electric quantity threshold value as a target battery pair; and performing concurrent equalization adjustment on the power parameters of each target battery pair until the electric quantity difference value of each target battery pair is smaller than the electric quantity threshold value. By implementing the technical scheme provided by the invention, the overall energy storage efficiency can be improved.

According to the high-low-temperature double-tank photovoltaic abandoned electricity coupling binary fused salt heat storage and exchange system and the operation method thereof, binary fused salt heat storage is adopted, light condensation heat storage and power generation load dynamic decoupling are achieved through independent heat storage of a cold salt tank and a hot salt tank and two-stage fused salt path control, and the power generation stability is improved. According to the system, photovoltaic abandoned electricity is utilized to drive a 25MW fused salt electric heater, fused salt is heated from 290 DEG C + / -10 DEG C to 550 DEG C + / -10 DEG C, the energy storage efficiency is larger than or equal to 93%, and the abandoned electricity is effectively absorbed. An intelligent salt dredging system is arranged, gravity self-flowing and compressed air assistance are combined, the emptying rate within 30 minutes + / -2 minutes reaches 99.5% + / -0.3%, and the risk of molten salt residue is reduced. The annular distribution pipe and the variable frequency pump are cooperatively controlled, so that the temperature stratification of the hot salt tank is less than or equal to 3 DEG C + / -0.5 DEG C, and the heat efficiency is improved by 8-12%. And the anti-condensation energy consumption of the storage tank is controlled to be smaller than or equal to 15 MWh / day through circulating anti-condensation of the MI heat tracing cable and the temperature adjusting pump, and the advantages of efficient heat storage, flexible peak regulation, high reliability and the like are achieved.

The invention discloses a Carnot cell system based on reversible cascade organic Rankine cycle and two-stage heat release. Comprising a bottom organic Rankine heat pump circulation loop, a top organic Rankine heat pump circulation loop, a top organic Rankine power generation circulation loop, a bottom organic Rankine power generation circulation loop, a heat storage water heat charging loop, a heat storage water first-stage heat release loop and a heat storage water second-stage heat release loop. The cascade organic Rankine cycle adopts a dry organic working medium, so that the problems of high vacuum compression, high compression ratio and high superheat degree of a compressor and wet expansion, liquid impact, corrosion and the like of a last-stage blade of a steam turbine can be effectively avoided; and through the efficient integrated structural design of a large-temperature-drop two-stage heat release system of the cascade organic Rankine cycle and the heat storage water, high-degree integration of the organic working medium Rankine heat pump cycle and the organic working medium Rankine power generation cycle loop is achieved, and meanwhile the energy storage efficiency and the round-trip efficiency of the system are improved.

The invention discloses a photovoltaic power generation system energy storage management method based on dynamic regulation and control and computer equipment. The method comprises the following steps: S1, obtaining and preliminarily analyzing power grid load data; s2, constructing a power grid cost dynamic scheduling model; s3, calculating and optimizing the number of the energy storage units; s4, constructing an optimal dynamic scheduling model; and S5, historical data matching and strategy optimization are carried out. In order to solve the problem that power output is unstable due to the fact that photovoltaic power generation is influenced by weather and day and night changes in the prior art, power grid load data, photovoltaic power generation historical data, the number of energy storage units and other information are obtained, decision making is conducted through the historical data and a load prediction model, it is ensured that an energy storage management strategy is more scientific and reasonable, and the energy storage efficiency is improved. The method aims at optimizing energy storage management, improving the utilization rate and the economic benefit of photovoltaic power generation, and remarkably improving the economical efficiency and the stability of a photovoltaic power generation system through an effective energy storage management method.

The invention discloses a user side energy storage method for improving the flexibility of a power grid, and relates to the technical field of intelligent power grids and energy storage, and the method comprises the steps: collecting the power load data and electricity price data of user side power equipment, building a load prediction model according to the power load data, and obtaining a power load prediction value; calculating a charging and discharging time window of the energy storage system based on the electricity price data and the electricity load prediction value; generating an optimal scheduling instruction of the energy storage system according to the charging and discharging time window in combination with the capacity constraint of the energy storage system; and controlling the energy storage system to perform charging and discharging operation according to the optimal scheduling instruction. Through intelligent prediction and accurate scheduling, the energy storage system can discharge for peak clipping in the peak period of the load and charge for valley filling in the valley period of the load, load fluctuation is effectively stabilized, the peak regulation capability of the power grid is enhanced, the energy storage system can quickly respond to the fluctuation of the power grid through real-time monitoring in cooperation with dynamic regulation of the ramp rate and SOC constraint, and the energy storage efficiency is improved. And flexible power support is provided.

The present invention relates to the technical field of thermal airflow power generation equipment, and provides an energy storage peak-shaving device to solve the defects of high energy storage cost and low efficiency of the power grid in the prior art, including a power generation mechanism; a heat collection mechanism, the heat collection mechanism includes a heat storage component and a thermal airflow power generation component, the power generation mechanism is connected to the heat storage component, the heat storage component is used to transport the thermal airflow to the thermal airflow power generation component, the thermal airflow power generation component is used to connect to the input end of the power grid, and the heat storage component is used to connect to the output end of the power grid. The present invention provides electric energy to the thermal storage component through the power generation mechanism to heat the airflow and store the electric energy to form a thermal airflow, the thermal airflow power generation component uses the thermal airflow to generate electricity, and transmits the electric energy to the power grid to meet the peak power demand, and in the power trough stage, the power grid can directly supply power to the thermal storage component to realize power storage and energy storage, and then realize energy storage peak-shaving, ensure the reliability of power supply and operational stability, reduce costs, realize energy storage peak-shaving of electricity, and improve energy storage efficiency.