137 results about "Electrovalency" patented technology

The invention provides an optical energy storage regulation and control method and system based on multi-time scale rolling optimization in the technical field of energy storage regulation and control, and the method comprises the steps: S1, inputting a 24-hour electricity price prediction curve, a 24-hour photovoltaic output prediction curve, a 24-hour load prediction curve and an initial SOC into a day-ahead prediction model, a 24-hour SOC reference trajectory and a standard charging and discharging plan are obtained; s2, collecting feedback data, and inputting the 24-hour SOC reference trajectory, the standard charging and discharging plan and the feedback data into the intra-day prediction model to obtain a corrected charging and discharging plan; and S3, setting an SOC dynamic limit value, collecting a real-time electricity price and real-time photovoltaic output, and inputting the corrected charging and discharging plan, the SOC dynamic limit value, the real-time electricity price, the real-time photovoltaic output and the actual SOC into the real-time prediction model to obtain a charging and discharging instruction and frequency modulation output power. The method has the advantages that the precision, economical efficiency and power grid adaptability of energy storage regulation and control are greatly improved, and the attenuation speed of the service life of the battery is greatly delayed.

The invention discloses a multi-user energy storage power station charging and discharging control method and system based on electricity price, and the method comprises the steps: arranging a monitoring terminal at energy storage equipment, and collecting the load data of each energy storage equipment; carrying out data preprocessing on the collected load data; constructing a cascade neural network prediction model, training the model by using the preprocessed load data, and generating a regional total load demand prediction value in a future time period; designing a deep reinforcement learning model DRL by using the regional total load demand predicted value to obtain a preliminary power adjustment amount; designing a target function considering the battery aging cost by using the initial power adjustment amount, and determining an initial value range of a coefficient in the target function of the optimization model according to a constraint condition; and a multi-objective optimization problem is considered, a Pareto optimal solution set is obtained based on the initial value range, and a final power distribution scheme is determined. The method can accurately predict the load, optimize the charging and discharging strategy, reduce the power consumption and operation cost, balance the service life of the battery and the economic benefit, and improve the intelligent and efficient level of the energy storage power station.

The invention discloses an integrated energy system real-time regulation and control method and system considering spot market electricity price, and belongs to the technical field of integrated energy system operation regulation and control optimization. The method comprises the following steps: solving output power, electrochemical energy storage charging power, electrochemical energy storage discharging power and to-be-adjusted load capacity of a CCHP unit at a moment t according to a dynamic electricity price of an electric power spot market at a moment t-1, and solving power generation cost, power transmission blocking cost and marginal cost of loss of the unit; and summing the auxiliary service cost constructed according to the auxiliary service demand fluctuation quantity at the moment t to obtain the dynamic electricity price of the electric power spot market at the moment t, constructing a real-time optimization regulation and control model of the integrated energy system, and solving the model in combination with a model prediction control theory and a machine learning algorithm to obtain an optimal regulation and control strategy of the integrated energy system. The economical efficiency, the reliability, the timeliness and the accuracy of regulation and control of the comprehensive energy system in the electric power spot market are improved, and the response will of a user is improved.

The invention discloses a charging and discharging control method and device for an elevator energy storage system, a medium and a product, and relates to the field of data processing. The method comprises the steps that real-time operation data such as the position and the load capacity of an elevator car are obtained, and the instantaneous power generation power and the power change rate of a traction machine are determined accordingly; determining a power change predicted value in a future preset time period based on the parameters, and obtaining the total amount of power generation energy required to be stored by the energy storage system through zero setting of a positive value, integral operation and efficiency compensation; according to the power change rate, the state of the energy storage unit and the power grid electricity price time period, the charging and discharging priorities fed back by the super capacitor, the lithium battery and the power grid are determined; controlling the bidirectional DC / DC circuit to switch charging and discharging modes according to the priority, and adjusting the PWM duty ratio of the brake resistor; and based on the charging and discharging mode and the duty ratio, charging and discharging control over the elevator energy storage system is achieved. According to the method, the problem of inaccurate real-time matching of the dynamic load and the energy fluctuation of the current elevator energy storage system can be relieved.

The invention discloses an electric energy metering method under power grid waveform distortion, and particularly relates to the technical field of electric energy metering. The problems of false triggering of an energy compensation mechanism, metering deviation and electricity price settlement risks caused by zero-sequence current or false phase drift easily generated in a multipoint grounding or grounding fault power system in the prior art are solved. According to the anomaly identification and control method integrating zero-sequence current frequency domain characteristic analysis and three-phase phase deviation trend consistency judgment, the false phase deviation state is accurately identified through synchronous sampling, frequency domain analysis and trend consistency evaluation of three-phase voltage, three-phase current and neutral line current, and the false phase deviation state is accurately identified. The error compensation behavior is shielded in real time, the fundamental wave power metering mode is switched to, the electric energy metering accuracy is guaranteed through an error backtracking correction mechanism after recovery, and the anti-interference capability and metering reliability of the electric meter under complex working conditions are effectively improved.

The invention discloses an energy storage equipment power balance dynamic load automatic regulation and control method and system, and the method comprises the steps: building a charging power optimization model based on an electricity price policy divided in peak and valley time periods, combining historical electricity demand data, and obtaining the optimal charging power in each time period; the method comprises the following steps: constructing a discharge power dynamic adjustment model through operation state parameters acquired by a real-time environment parameter acquisition device in combination with real-time electricity demand data, and acquiring optimal discharge power in each time period; parameters of the two models are optimized, and the load state based on the optimal charging and discharging power is balanced; based on the historical regulation and control data, the overload condition under the abnormal factors is predicted; and on the basis of a power imbalance condition, preferentially ensuring power supply of a key load according to a power distribution priority and executing energy storage equipment state self-checking. The method has the advantages that the charging power and the discharging power are optimized in combination with the electricity price and the real-time requirement, so that the load state is balanced, the energy cost is reduced, and the equipment overload risk is avoided.

The invention discloses a micro-grid park integrated energy system planning method and device, a terminal and a medium. The method comprises the following steps: acquiring energy demand data, time-of-use electricity price information, natural gas price and meteorological information of a park to be planned, and equipment parameters, equipment investment cost and equipment maintenance cost in an integrated energy system of the park to be planned; the influence of temperature change on thermodynamic characteristics of steam is considered, and equivalent energy storage of a steam heat accumulator of the microgrid park is modeled by considering valley electricity heat storage; setting constraint conditions of a planning model according to the acquired data information, and taking the minimum comprehensive cost as an objective function, thereby constructing a cold-hot electro-optical storage and charging integrated microgrid park planning model considering electric power-steam multi-energy complementation; and solving the planning model, and outputting a planning scheme about whether each device in the integrated energy system is configured, the configuration capacity and the operation output curve of each configured device. According to the invention, the energy structure of the park is optimized, the resource utilization efficiency is improved, and the stability of the system is enhanced.

The invention discloses a distributed photovoltaic power distribution network shared energy storage optimization method, and relates to the technical field of energy storage system optimization, and the method comprises the following steps: inputting the current electricity price of an electricity market into a preset electricity price prediction model, and obtaining a current rolling cycle electricity price prediction sequence, constructing a rolling optimization model based on the current rolling cycle electricity price prediction sequence, the energy storage system battery real-time charge state and the energy storage system operation constraint condition, taking the maximum energy storage system net income as an objective function, taking the battery life attenuation cost as a correction parameter, and obtaining an optimal charge and discharge power sequence, and controlling the charging and discharging actions of the energy storage system, monitoring an electricity price prediction deviation index in real time, optimizing and calibrating an electricity price prediction model, updating an optimal charging and discharging power sequence, adjusting the charging and discharging actions when the electricity price prediction deviation index is greater than a preset deviation threshold value, and repeating the steps at the beginning of a next rolling period, so that the benefits of the energy storage system are improved, and the battery loss is reduced.

The invention relates to the technical field of power grid interaction, in particular to a two-way energy control method and intelligent equipment, and aims to solve the problem of how to perform charging and discharging control on two-way energy equipment according to power grid load information and peak and valley electricity prices on the basis of an optimal cost principle. The method comprises the steps that the initial electric quantity of an energy storage module is acquired; acquiring historical electrical load information of a set time period; and predicting a power control curve of a set time period according to the initial electric quantity, the historical electric load information and the expected electric quantity based on a cost optimal principle. On the basis of the predicted power control curve, charging and discharging control is performed on the energy storage module through the bidirectional energy equipment, so that the stability of the power grid can be enhanced, the power supply condition of the power grid can be optimized, the electric charge expenditure of the user can be reduced, the user experience can be improved, income can be brought to the user, and the return on investment of the user can be improved. And by adopting a dynamic programming algorithm, the operation speed is improved, and engineering realization is more convenient.

The invention relates to the technical field of photovoltaic power generation, and discloses a photovoltaic energy storage cooperative power generation system and method.The photovoltaic energy storage cooperative power generation system comprises a photovoltaic assembly, an intelligent string structure, an energy storage system and an intelligent controller, and the photovoltaic assembly comprises an east assembly and a west assembly and is connected to the direct current end of the same inverter to balance the morning and evening power generation peak values. The group string structure adopts a fixed group string and a switchable group string to be connected in parallel, and the group strings are dynamically switched to be connected and disconnected through an intelligent switch to adapt to irradiation fluctuation. The energy storage system comprises an energy storage battery and a bidirectional converter, a direct current end is connected with the battery, an alternating current end is connected with a grid through an intelligent switch, and charging and discharging scheduling under a peak-valley electricity price strategy is supported. The intelligent controller integrates a power prediction module, an economic dispatching module and an equipment protection module, monitors photovoltaic output, an energy storage SOC and a power grid state in real time, and dynamically optimizes string switching, energy storage charging and discharging and inverter operation parameters. Through east-west assembly power balance, flexible string reconstruction and energy storage intelligent scheduling, power generation income maximization and equipment service life prolonging are realized.

The invention discloses an electric vehicle V2G regulation potential evaluation method based on electricity price regulation, particularly relates to the technical field of electric energy storage cooperative control, and is used for solving the problems of power grid resonance risk and battery life loss caused by power synchronism in existing V2G centralized scheduling. Through real-time fusion of a dynamic electricity price time period division signal and a power grid frequency deviation value, carrying out dual constraint on a charging and discharging power range in combination with a battery health state attenuation coefficient, and generating an initial instruction set; a power grid resonant frequency distribution interval is further extracted based on a frequency sweep test, an asymmetric phase disturbance rule is generated for a dominant resonant frequency point, and a harmonic superposition effect of power output is destroyed through differential time sequence offset; in the instruction execution stage, the phase disturbance amplitude is dynamically adjusted to adapt to the power grid frequency fluctuation and the battery aging degree, a closed-loop control mechanism is formed, collaborative optimization of the power grid stability and the equipment service life is achieved, and the safety of the electric vehicle cluster participating in power grid adjustment is improved.

The invention relates to the technical field of power grid energy storage, in particular to a voltage fluctuation rapid suppression method based on a composite energy storage system, which realizes targeted response to voltage fluctuation of different frequencies by setting a dual-time scale power distribution strategy, improves the improvement efficiency of the energy storage system, and improves the suppression efficiency of the composite energy storage system. Through a composite control structure of an adaptive PI controller and a feedforward compensation link, the voltage control precision and the harmonic suppression rate are improved, and according to peak-valley electricity price characteristics and load fluctuation rules of different scenes, the power grid line voltage fluctuation type is monitored in real time, and a dynamic parameter library and an online identification algorithm are combined. The system can automatically adapt to factors such as hardware aging and environment change, a long-term control effect is maintained, and the charging and discharging frequency of the lithium iron battery is reduced by setting the high-frequency power buffer effect of the super capacitor, so that the cycle life of the lithium iron battery is prolonged; meanwhile, the overall energy conversion efficiency of the system is improved through cooperative control of the modular multilevel converter topology and the double energy storage elements.

The invention provides a new energy configuration, construction and energy storage combined operation optimization system and method, and relates to the technical field of new energy configuration and energy storage. According to electricity price prediction data, a single wind power station output prediction result, a single photovoltaic power station output prediction result, an AGC active power instruction and new energy real-time active power, overall income maximization is taken as a target function, new energy output constraint and energy storage operation cost are considered, and a new energy output prediction result is obtained according to a general principle of low-price charging and high-price discharging. And an energy storage charging and discharging strategy in a future period is given, the charging and discharging strategy is issued to the energy storage EMS, and automatic charging and discharging are controlled by the energy storage EMS. By predicting the node electricity price, the energy storage charging and discharging time is reasonably planned, the energy storage charging and discharging actions are automatically controlled, and the utilization rate of new energy distribution and storage is improved. By predicting the node electricity price, the energy storage charging and discharging time is reasonably planned, the energy storage charging and discharging actions are automatically controlled, and the utilization rate of new energy distribution and storage is improved.

The invention relates to an energy system configuration optimization method considering equipment variable working condition characteristics and energy storage life attenuation, which comprises the following steps: establishing a mathematical model of an energy system, and calculating equipment cycle aging indexes in the mathematical model of power storage equipment by considering the energy storage life attenuation, in mathematical models of the cold-heat-electricity combined supply system, the gas-fired boiler and the electric refrigerating unit, the corresponding efficiency is calculated by considering the variable working condition characteristics of the equipment; and based on the established mathematical model, resource configuration optimization of the energy system is carried out by using a double-layer optimization method, the upper layer optimizes equipment capacity design by taking minimization of annual cost as a target, and the lower layer carries out operation optimization by taking the sum of minimization of operation cost, battery life degradation cost and demand electricity price as a target. The battery life degradation cost is calculated based on the equipment cycle aging index. Compared with the prior art, battery life attenuation and equipment variable working condition operation are considered at the same time, and the overall efficiency and reliability of the system are improved.

The invention relates to the field of multi-energy collaborative scheduling of an electric power system, and particularly discloses a wind-light-fire-hydrogen coupling system electric quantity balance method considering an electric power price factor, which is realized based on an optimization model construction module, a scene generation module, a scene reduction module, a dynamic adjustment module and a solving module. Comprising the steps that S1, a wind-light-fire-hydrogen multi-energy coupling system joint optimization hydrogen storage model is constructed, and a dynamic electricity-hydrogen conversion and virtual bidding arbitrage mechanism is combined; s2, an initial scene set is generated through Latin hypercube sampling according to photovoltaic Beta distribution, wind power Weibull distribution and real-time electricity price logarithmic normal distribution; s3, performing staged mixed reduction to extract a typical scene set; s4, executing two strategies to adjust the bidding scale and the electricity purchasing and selling behavior; and S5, converting a KKT condition by using a nonlinear complementary function, and solving a Nash equilibrium solution to realize market clearing. According to the method, price fluctuation is effectively stabilized, the new energy consumption capability is improved, and an efficient and stable electric quantity balance solution is provided for a high-proportion new energy power system.

The invention relates to the technical field of box-type substations, in particular to a prefabricated intelligent box-type substation which comprises a substation body and an edge control system. According to the method, multi-source data such as the vibration acceleration mean value and the stress cycle damage proportion are fused in real time through a vibration characteristic and structural damage two-dimensional grading mechanism, and the trigger level is accurately judged. Based on cooperative linkage of a hydraulic damping assembly and a rubber shock insulation layer, full-process active control from pre-starting adjustment to emergency power-off is achieved, and the limitation that a traditional transformer substation can only conduct passive early warning is broken through. Through real-time analysis based on an electricity price fluctuation curve and a load curve, a high-low level trend proportion model is constructed, and a load output strategy of the transformer substation is dynamically adjusted. By matching the real-time electricity price with the load demand, the economic mode of full-power operation in the valley period and energy storage supplement in the peak period is realized, and the defect that a traditional strategy is not combined with the market electricity price is overcome.

The invention is suitable for the technical field of electrochemical energy storage, and provides a multi-source cooperative control method and device, computer equipment and a computer program product, and the method comprises the steps: obtaining basic parameters of a power grid, a hybrid energy storage system and a new energy power generation system; obtaining prediction parameters of the electric power energy system based on the historical working conditions and the prediction model; according to the preset initial investment amount, the cycle life of the hybrid energy storage system and the basic parameters and working conditions of the electric power energy system, calculating the unit energy charging and discharging cost of the hybrid energy storage system; based on the unit energy charging and discharging cost, the time step length, the power grid billing time-of-use electricity price and the prediction parameters of the hybrid energy storage system and the planned charging and discharging power of the hybrid energy storage system, an objective function with the optimal economical efficiency as an objective is constructed, the objective function is solved, and the optimal planned charging and discharging power of the hybrid energy storage system in each time period is obtained. According to the method, multi-dimensional data is combined, an objective function with the optimal economical efficiency is constructed and solved, and a hybrid energy storage charging and discharging strategy is automatically obtained.

The invention relates to the technical field of refrigeration energy efficiency monitoring of refrigeration houses, in particular to a dynamic monitoring system and method for refrigeration energy efficiency of a refrigeration house. A multi-objective optimization scheme analysis module in the system is used for analyzing the refrigeration energy efficiency of the refrigeration house based on the running state of each temperature zone of the current refrigeration house, the heat state of stored goods and an external electricity price signal; and by taking the minimization of the total operation energy consumption of the refrigeration house and the minimization of the temperature fluctuation of each temperature zone as optimization objectives, constructing a multi-objective optimization function, and generating at least one candidate energy-saving operation scheme in a future time window of a preset duration. According to the method, through multi-dimensional data perception, a digital twinborn model for specific characteristics of goods and refrigeration house scenes is established; a multi-objective optimization function with the lowest total energy consumption, the lowest temperature difference fluctuation of the temperature zone and the highest energy efficiency ratio of the system as the core is constructed; and a plurality of candidate energy-saving schemes are dynamically generated by using the function, and an optimal scheme is screened out through a normalized comprehensive evaluation system, so that clear energy efficiency data and optimization suggestions are provided for managers, and invalid energy consumption is avoided.

The invention belongs to the technical field of supply and demand interaction in high-heat and high-humidity areas, and discloses a high-heat and high-humidity area flexible resource random robust optimization regulation and control method and system so as to solve the regulation and control problem of a regional energy system in a high-heat and high-humidity environment. The method comprises the following steps: collecting flexible resource data, power grid data and meteorological data; a deterministic optimization model is constructed, and minimization of the daily operation total cost of the micro-grid in the target region is taken as a target; on the basis of the deterministic optimization model, introducing an uncertainty set of photovoltaic output and load power and Monte Carlo simulation of real-time electricity price, constructing a random robust optimization model, and performing iterative solution through a column constraint generation algorithm to generate a collaborative regulation and control strategy; and issuing the cooperative regulation and control strategy to the building group, the electric vehicle and the energy storage equipment for execution, monitoring the execution effect in real time, and dynamically adjusting the strategy. According to the invention, the energy utilization efficiency is improved, the carbon emission is reduced, and the stable and reliable operation of the system in a high-heat and high-humidity environment is guaranteed.

The invention discloses an electric charge abnormity error processing method and system based on intelligent verification, and relates to the technical field of electric power billing, and the method comprises the steps: obtaining electric charge abnormity first data, carrying out the abnormity detection of electric charge calculation based on a neural network algorithm, and enabling the electric charge abnormity first data to comprise an electricity price feature, a force adjustment standard feature and a definite proportion feature; when the electric charge calculation is abnormal, correcting the electric quantity based on load flow calculation and an energy balance algorithm, retrieving historical electricity price information of a user, performing consistency verification on the historical electricity price information and current electricity price information, judging and updating the electricity price of the user, and recalculating the electric charge; real-time updating three-color labeling display is performed on an electric charge correction calculation result based on a visualization technology, contribution degrees of input parameters to electric charges are obtained based on a local sensitivity method, and importance ranking is performed on the input parameters according to the contribution degrees; according to the invention, through accurate correction of the key parameters of electricity charge calculation, the efficiency and accuracy of electricity charge error processing are effectively improved, the working pressure of basic units is reduced, and the customer satisfaction is improved.

The invention discloses a multi-time-scale optical storage charging and discharging integrated energy management method and device, a medium and a product, and relates to the field of power scheduling, and the method comprises the steps: determining the earnings of an optical storage charging and discharging multifunctional integrated energy management system according to the day-ahead operation data; constructing an upper-layer control model; according to the upper layer control model, determining the load scheduling power of the zero-carbon park; power deviation is determined according to the real-time operation parameters and zero-carbon park load dispatching power, and a lower-layer control model is constructed; determining adjustment power according to the power deviation and a lower-layer control model; the load scheduling of the zero-carbon park is adjusted; and in combination with the real-time electricity price, the power utilization load, the charging pile load and the energy storage charging and discharging power of the zero-carbon park are adjusted and optimized in real time on the intra-day scale. According to the method, the time sequence coupling characteristics of the energy storage and the charging pile can be considered, so that the method better adapts to the time uncertainty of the user side load and the energy storage.

The invention discloses an intelligent soft switching and multilayer electro-hydrogen hybrid energy storage two-stage space-time decoupling configuration method and system. The method comprises the following steps: inputting basic data and initializing network basic parameters; in the first stage of constructing the two-stage MEH-SOP model, the power / capacity of each device of the MEH is optimally configured on the basis of annual 8760h time sequence operation simulation considering time-of-use electricity price; constructing a second stage of the two-stage MEH-SOP model, extracting typical scenes of MEH full-year high-power charging / discharging and power distribution network full-year voltage serious out-of-limit, and optimally configuring SOP multi-port capacity; and solving the constructed two-stage MEH-SOP model, and outputting an optimal configuration result. According to the invention, a multi-level energy storage system covering from the day to the week is constructed, and the multi-port SOP direct current side is connected in a modularized manner, so that the structural flexibility and the operation flexibility of the power distribution network are remarkably enhanced.

A distributed photovoltaic energy storage system configuration method based on depth feature clustering and robust double-layer optimization comprises the steps of performing normalization processing on multi-source historical data such as photovoltaic output, load, electricity price and weather, and generating a typical operation scene capable of representing uncertainty by adopting a depth embedded feature extraction and clustering algorithm; constructing a double-layer optimization configuration model: in the upper-layer planning optimization model, taking annual comprehensive cost, carbon emission cost, node voltage deviation and renewable energy consumption rate as multi-objective functions, and determining the access position, capacity and rated power of photovoltaic and energy storage; in the lower-layer operation optimization model, the charging and discharging strategy and reactive power output of the energy storage system are optimized with the daily operation cost, the voltage deviation, the electric energy quality index and the auxiliary service income as optimization targets; and an improved NSGA-II algorithm based on an elitist strategy is adopted to realize closed-loop optimization of planning and operation. According to the method, economy, low-carbon property and electric energy quality can be considered while uncertainty is considered, and the comprehensive performance of operation of the power distribution network is improved.

The invention discloses a base station energy storage device and a control method thereof, and belongs to the technical field of new energy. The equipment comprises a power supply module, a detection module, three switches, a rectifier, an inverter, an energy storage device, a charging power supply and a controller, wherein the controller is used for controlling the charging and discharging states of the energy storage device according to the operation state and the electricity price of a power grid and switching the power supply source of the inverter so as to supply power to a base station by using the inverter; the detection module is connected with the controller through a second switch and a third switch which are connected in series, the control end of the second switch is used for receiving output signals of the detection module, the detection module is connected with the input end of the rectifier through the first switch, and the output ends of the rectifier and the energy accumulator are connected with the inverter. The equipment can solve the technical problems that in the prior art, a base station needs to be transformed, the construction difficulty is large, the energy storage coverage rate is not high, and anti-islanding protection measures need to be taken when a power grid is powered off.

The invention discloses an energy storage adjusting method and device of a virtual power plant, a storage medium and electronic equipment, and belongs to the technical field of power systems.The method comprises the steps that an adjusting model and constraint conditions for an energy storage system are established, and the adjusting model takes the minimum capacity of the energy storage system as an objective function; the constraint condition comprises a power balance constraint condition of the virtual power plant, and a variable in the power balance constraint condition comprises a power purchase deviation value between power grid input power of a real-time market and power grid input power of a day-ahead market; constructing a deviation constraint condition and a deviation standard-exceeding constraint condition aiming at the electricity purchasing deviation value; and determining the energy storage adjustment data of the energy storage system according to the adjustment model, the deviation constraint condition and the deviation standard-exceeding constraint condition, thereby effectively avoiding the capacity waste of the energy storage system caused by low-probability extreme weather, and controlling the increase of the electricity price cost caused by the deviation electric quantity. And the electricity price cost in the operation process of the power grid and the construction cost in the planning process achieve a better balance.

The invention provides an adjustable resource real-time control method suitable for a port shore power energy system. The method comprises the following steps: step (1), modeling a key energy sub-module in the system; (2) constructing a prediction model by adopting a generalized regression neural network; (3) an economic layer is used for dynamically constructing an economic cost optimization model according to the real-time electricity price, the battery state and the photovoltaic output condition after the short-term prediction load curve is obtained, and generating an optimal reference charging and discharging track of the energy storage system; and step (4), a control layer is an execution layer in the energy management system, a model prediction control method is adopted, an optimal control strategy is calculated in real time according to the optimal state generated by the economic layer, and accurate tracking and power balance adjustment of the state of the energy storage system are realized. The invention provides the adjustable resource real-time control method suitable for the port shore power energy system, and the method has good prediction precision, economic optimization capability and control responsiveness.

The invention relates to the technical field of photovoltaic energy storage charging, and particularly provides a photovoltaic energy storage intelligent management method and device, and the method comprises the steps: querying a pre-constructed mapping relation table about the power grid electricity price and a discharge depth coefficient according to the real-time electricity price information of a power grid, so as to obtain a first discharge depth coefficient, under the condition that the residual electricity storage quantity information is greater than or equal to a preset electricity storage quantity lower limit value, calculating the maximum discharge quantity according to the electricity storage quantity information and a first discharge depth coefficient; controlling the energy storage assembly to supply power to the charging pile according to the charging power demand until the discharge capacity of the energy storage assembly reaches the maximum discharge capacity or the charging power demand is reduced to 0; when the discharge capacity of the energy storage assembly reaches the maximum discharge capacity and the charging power demand is not zero, the commercial power supply adjusting assembly is controlled to supply power to the charging pile according to the charging power demand; according to the method, the discharge capacity of the energy storage assembly in the peak period of electricity price can be increased, and the situation of deep discharge of the energy storage assembly is avoided.

The invention provides an intelligent refrigeration system utilizing electro-thermal conversion and phase change energy storage, the intelligent refrigeration system comprises a phase change structure and an intelligent temperature control system, the phase change structure is arranged on a building body, and the temperature of the phase change structure during phase change is the phase change temperature; the intelligent temperature control system comprises a temperature detection device, an intelligent control system and a refrigeration device; the temperature detection device is connected with the intelligent control system, and the intelligent control system is electrically connected with the refrigeration device; the temperature detection device is used for measuring the indoor real-time temperature, the intelligent control system is used for receiving the measured real-time temperature and comparing the measured real-time temperature with the phase change temperature, and when the real-time temperature is larger than the phase change temperature, the intelligent control system controls the refrigeration device to be started. According to the intelligent refrigeration system, the phase change temperature of the phase change structure serves as the control temperature, the refrigeration system can be started to conduct mild cooling and enable the phase change structure to release heat when the electricity price is low, and the phase change structure absorbs heat to slowly rise the temperature after the refrigeration system is closed when the electricity price is high.

The invention discloses a multi-time scale coupled source-storage collaborative economic dispatching method and system, relates to the field of power system dispatching, and solves the problem of low dispatching economy of a power system dispatching scheme. According to the day-ahead scheduling optimization in the embodiment of the invention, the hidden cost of deep peak regulation and high-frequency charging and discharging can be quantified through the deep peak regulation coal consumption function of the thermal power generating unit and the charging and discharging depth-service life attenuation mapping table of the energy storage equipment; the intra-day rolling optimization dynamically adjusts the energy storage behavior based on the real-time electricity price, so that the scheduling plan can be matched with the market fluctuation, and the energy storage income is improved; by combining the two points, the operation characteristics of the power system under the complex working condition can be reflected more accurately, and the scheduling economy of the finally obtained optimal scheduling scheme is improved.

The invention discloses a new energy electric power spot transaction auxiliary decision-making system, and relates to the technical field of auxiliary decision-making. The system accurately measures and calculates initial charging and discharging power in each time period through an initial power determination module, optimizes power according to an electricity price time period and a wind power processing constraint by means of a power optimization decision module, and generates compliance declaration electric quantity based on a power-electric quantity conversion relation, a minimum unit and fluctuation limitation through a compliance declaration adaptation module. Transaction failure caused by non-compliance is avoided; a feedback regulation and control module carries out deviation judgment and correction on the optimized power and the compliance declaration electric quantity, it is guaranteed that transaction data is accurately matched with actual operation, and finally the transaction decision-making efficiency, the energy storage operation stability and the overall economic and environmental protection benefits are improved; the problems that in new energy electric power spot transaction, it is difficult to determine the energy storage initial power by combining the real-time cycle index and the charging and discharging depth, power optimization does not adapt to electricity price and wind power constraints, declaration electric quantity is not compliant, and the power and the electric quantity are prone to deviation are solved.