106 results about "Electrovalency" patented technology

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 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 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 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 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 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 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.

The present invention relates to the technical field of power dispatching, and specifically to an intelligent dispatching method and system for electric power resources in construction projects, which includes the following steps: obtaining the instantaneous power demand data of electrical equipment in the construction area, calculating the load density value of each area according to the power consumption of the equipment in each construction area, and obtaining the regional load density data. In the present invention, by using the instantaneous power demand data of electrical equipment in the construction area, calculating the load density value of each area, and combining the current charging state and the dischargeable power of the energy storage unit, the discharge power of the energy storage device is adjusted, so that the energy storage device can dynamically adapt to the fluctuation characteristics of the construction load, improve the power supply stability during peak power consumption periods, and combine the peak-valley electricity price floating value and the load state of the energy storage device to set the charge-discharge switching threshold of the energy storage device, making the electric energy regulation during peak-valley periods more flexible, reducing the peak power purchase cost, and improving the economy of energy dispatching.

The invention relates to the technical field of new energy hydrogen production and chemical coupling application, and discloses a natural gas hydrogen-doped pipeline conveying system which comprises an energy supply layer, a chemical production layer, a digital integrated platform and a dispatching control module. The energy supply layer integrates photovoltaic power, wind power, nuclear power and a power grid standby power supply through a direct-current micro-grid, is matched with a sodium ion flow battery energy storage system, and supplies energy to the water electrolysis hydrogen production system of the non-noble metal catalyst and porous electrode structure. In the chemical production layer, pipeline steel or double-layer alloy steel is selected as a hydrogen-doped pipeline according to the proportion, a hydrogen concentration monitoring and sound wave leakage detection system is arranged, the hydrogen-doped safety upper limit of high pressure of 10% and low pressure of 30% is set, and a chemical hydrogen using system is connected through a gas distribution valve set and adjusted by an intelligent module. The digital platform is based on monitoring of the Internet of Things, hydrogen doping is optimized by means of a fuzzy PID algorithm and digital twinning, and risks are early warned. The scheduling module combines wind and light prediction and real-time electricity price, optimizes the start and stop of the electrolytic cell, the hydrogen doping ratio and the conveying pressure, and achieves efficient and stable conveying.

The invention relates to an installed capacity analysis method for an energy storage system, and the method comprises the steps: obtaining the local electricity price data, the power utilization data of a user in the last year, and the capacity Q change of a transformer, and presetting two groups of charging and discharging parameters of the energy storage system; calculating an output monthly mean value, a monthly charge and discharge factor mean value and a total annual discharge amount of the two groups of charge and discharge parameters under the constraint of an anti-countercurrent protection mechanism and an anti-overcapacity protection mechanism, and respectively obtaining an output monthly mean value instance set, a monthly charge and discharge factor mean value instance set and a total annual discharge amount instance set; and comparing the data in the same instance set, and if the comparison result is that one charging and discharging parameter has two data larger than the other charging and discharging parameter, taking the charging and discharging parameter as an optimal preset scheme. According to the invention, the appropriate machine type can be more accurately selected through multiple comparison, and the anti-backflow and anti-super-capacity mechanism is set, so that the user demand can be better responded.

The present application relates to the field of electrical engineering technology, and provides a method and system for optimizing and scheduling an electric energy storage system based on reinforcement learning, in order to solve the problem that it is difficult to effectively evaluate and control the risk of battery aging during frequent charging and discharging, and it is difficult to meet the real-time scheduling requirements in the low computing power environment on the edge side. The method of the present application includes: obtaining the battery charging status and health status data of the electric energy storage system and the grid load and grid electricity price data of the industrial and commercial park to generate a state input data set; using a reinforcement learning agent to obtain charging and discharging scheduling instructions; allocating power to the electric energy storage system, the multi-port converter power interface and the park load to generate multi-source collaborative power flow data; combining historical operating data, using a reinforcement learning agent to optimize the charging and discharging scheduling instructions; and optimizing and scheduling the electric energy storage system according to the optimized instructions. The present invention realizes efficient, intelligent and adaptive optimization scheduling of the electric energy storage system in the industrial and commercial park.

The invention provides an optical storage park micro-grid regulation and control method and device, electronic equipment and a storage medium, and belongs to the technical field of energy management, the method is applied to an optical storage park micro-grid system, the optical storage park micro-grid system comprises an energy storage system and a micro-grid controller, the energy storage system is in communication connection with the micro-grid controller, and the energy storage system is connected with a power grid in parallel. The method is executed by a micro-grid controller, and comprises the following steps: acquiring the electrical load power and the power grid incoming line power of the optical storage park; and if the power of the electrical load is greater than a preset power grid incoming line power threshold value and the current time period belongs to an electricity price flat peak time period, determining a first regulation and control threshold value, and when the power grid incoming line power is greater than the first regulation and control threshold value, controlling the energy storage system to discharge to the electrical load. The light storage park micro-grid regulation and control method provided by the invention can improve the refinement degree of light storage park micro-grid regulation and control.

The invention belongs to the technical field of energy storage joint optimization, and provides a multi-region heterogeneous energy storage joint optimization method based on model predictive control, which adopts slow time domain rolling optimization on an upper layer to realize joint scheduling of economy and service life. Fast time domain distributed power distribution and intra-group consistency control are adopted at the lower layer to realize fast frequency response and SOC balance; the upper layer cost function merges the operation loss cost, the time-of-use electricity price income and the degradation cost of unified monetization into the same target, and takes the energy storage unit as the dynamic adjustment basis of the degradation unit price to protect the aging unit; and the lower layer dynamically activates the power type and energy type energy storage units based on a disturbance severity index, formulates a charging and discharging group division and switching strategy, and adopts a distributed consistency algorithm to realize power distribution of the minimum communication overhead in the group so as to balance the SOC, so that the instantaneous frequency performance, the long-term economy and the equipment life are considered under the realizable engineering condition.

The invention provides a charging and discharging control method and device for an energy storage system, electronic equipment and a storage medium, and relates to the technical field of electric energy storage, and the method comprises the steps: determining a control objective function based on a future predicted power load, a future predicted electricity price and operation cost; determining a charge-discharge power constraint condition and a charge state constraint condition; the charge state constraint condition comprises an adjustment parameter, and the adjustment parameter is used for adjusting the charge state value so as to reduce the change speed of the charge state value; and performing charge and discharge control on the energy storage system according to the control objective function, the charge and discharge power constraint condition and the charge state constraint condition. In the embodiment of the invention, charging and discharging control is performed on the energy storage system according to the control objective function, the charging and discharging power constraint condition and the state-of-charge constraint condition, and the state-of-charge value is adjusted through the adjustment parameter in the state-of-charge constraint condition, so that the change speed of the state-of-charge value is reduced; the problem of incomplete charging and discharging of the energy storage system is avoided to a certain extent, and earnings are increased.

The present invention provides a household optical energy storage system and related products. The control method of the household optical energy storage system includes: collecting the measurement data of the electric energy metering device, the power of the energy storage battery, and the electricity price information; determining the difference between the power generation power of the microgrid power generation device and the load power of the electrical equipment according to the measurement data to obtain the power difference; obtaining a pre-configured energy regulation model, and using the power difference, the power of the energy storage battery, and the electricity price information to perform matching in the energy regulation model to determine the charging and discharging strategy of the energy storage battery and the operation adjustment strategy of the electrical equipment; using the power conversion device to execute the charging and discharging strategy and sending an adjustment instruction corresponding to the operation adjustment strategy to the electrical equipment. This solution intelligently determines the charging and discharging strategy of the energy storage battery and the operation adjustment strategy of the electrical equipment, realizes simple and efficient coordination of the work of the electrical equipment, enables the coordination of power generation, power storage, and power consumption, and forms a good household energy coordination mechanism.

The invention discloses a visual monitoring and shooting and intelligent identification external damage early warning method and system, and relates to the field of power transmission line safety monitoring. The method comprises the following steps: acquiring external damage accident information; reversely tracing from the power grid topology database based on the accident occurrence position to determine an affected user list; constructing a causal inference model, and carrying out anti-factual estimation on the power consumption of the affected user when no external damage is assumed to occur in the accident influence time period based on the power consumption characteristic data of the affected user in the historical accident-free time period; acquiring actual electricity consumption of a user; determining an electric quantity loss causal effect value according to a difference value between the actual electricity consumption and the anti-factual electricity consumption; and according to the effect value and user electricity price information obtained from the marketing system, generating an external damage follow-up loss list containing the electricity loss cost. According to the method, accurate accounting of the electric quantity loss is realized through a causal inference technology, and a full-link closed-loop system from pre-event early warning to post-event follow-up is constructed in combination with power grid topology analysis and multi-system data fusion.

This application discloses a method and apparatus for optimizing energy consumption by prosumers that considers energy storage life loss, including: obtaining the electricity purchase price and electricity sales price of the prosumer from the power grid; obtaining the electricity cost of the prosumer based on the electricity purchase price, electricity sales price, and the power purchased and sold by the prosumer from the power grid; constructing a total operating cost function for the prosumer based on the electricity cost, the comfort loss cost caused by energy consumption changes, the energy storage life loss cost, and the photovoltaic system operation and maintenance cost; solving the total operating cost function for the prosumer based on total energy consumption optimization constraints, energy storage system constraints, interruptible load constraints, transferable load constraints, and power balance constraints to determine the prosumer's energy consumption strategy. By incorporating the energy storage life loss cost into the construction of the total operating cost function for the prosumer and solving it, the prosumer's energy consumption optimization strategy obtained is accurate and feasible while considering the full life cycle cost of the energy storage equipment.

The present application relates to the technical field of power system optimization operation, and in particular to a method, device, electronic device and storage medium for conservative collaborative control of energy storage resources, wherein the method comprises: judging whether the sum of the energy storage charging capacity and the load power consumption in the charging period before the continuous discharge period in the energy storage pre-dispatching plan is greater than the preset contract amount; when it is greater than the preset contract amount, generating the energy storage physical allocable interval according to the preset energy storage charge state curve, and generating the energy storage economic allocable interval according to the peak and valley electricity price peak; constructing the optimized allocable interval for energy storage pre-dispatching redistribution according to the intersection of the energy storage physical allocable interval and the economic allocable interval, and calculating the remaining capacity at each time point of the allocable interval according to the contract amount of the optimized allocable interval, and allocating the energy storage charging capacity at each time point according to the ratio of the remaining capacity at each time point. Thus, the problem of high penalty fees caused by the inability to avoid energy storage executing the pre-dispatching plan for charging operations in the related technology is solved.