117 results about "Energy sharing" patented technology

The invention provides a remote control method and system for a new energy vehicle charging pile, and the method comprises the steps: collecting a vehicle battery state, a user demand, and the operation information of a power grid and the charging pile, and integrating the information into a standardized comprehensive state variable; dynamically adjusting the initial charging power of the single user according to the health state of the vehicle battery to obtain adjusted charging power; calculating the charging priority of the user by combining the distributed power with a dynamic weight adjustment model based on time decay; receiving a multi-user distribution strategy, and constructing a real-time adjustment variable set in combination with the operation information of the charging pile; and the power grid load change is monitored in real time. According to the invention, on one hand, a flexible solution is provided for personalized demands of users, and on the other hand, efficient utilization and active management of system resources are realized through energy sharing and remote dynamic control, so that main defects in the prior art are overcome, and the system has important technical value and application prospect.

A multi-virtual power plant collaborative optimization scheduling method considering energy sharing comprises the steps of constructing a master-slave game model, constructing an upper-layer game leader scheduling center model, constructing a lower-layer game follower multi-virtual power plant collaborative optimization scheduling model and a multi-virtual power plant income distribution model, and solving the models by adopting a particle swarm optimization algorithm and a Cplex solver. According to the invention, the scheduling center based on energy sharing and the master-slave game model of the multiple virtual power plants are provided, the scheduling center is used as a superior game leader, and the multiple virtual power plants are guided to perform optimal scheduling by dynamically adjusting the electricity price, so that energy sharing among the multiple virtual power plants is stimulated; effective interaction between the multiple virtual power plants and an upper-layer mechanism is achieved through electricity price adjustment; according to the method, the benefit relationship among the multiple virtual power plants is deeply studied, and the problem of benefit damage of part of main bodies in the collaborative operation process is solved based on the multi-virtual power plant collaborative operation benefit distribution model of the Shapley value method, so that the collaborative operation relationship of the multiple virtual power plants can be stably maintained.

The invention relates to the technical field of energy management, in particular to a smart park energy consumption equipment operation management system based on a block chain, and the system comprises a data authentication module, a smart contract module, a credit scoring module, a collaborative management module, a renewable energy access module and a performance evaluation module. According to the invention, through the block chain technology, it is ensured that the data of the energy-consuming equipment is not tampered in the transmission and storage process, the credit score of the equipment is adjusted through real-time monitoring, the actual operation condition of the equipment can be continuously reflected, potential faults of the equipment can be timely identified, the maintenance and replacement efficiency can be improved, and cross-park and cross-park management can be realized. The energy consumption difference between the devices is optimized and coordinated through data analysis, energy sharing and efficient utilization between the parks are further promoted, when renewable energy sources are accessed, supply data of wind power and solar energy can be obtained in real time, the requirements of the renewable energy sources and traditional energy sources are balanced, and energy efficiency management of the parks is more accurate and continuous.

A digital twin-based converged village-level microgrid operation system and method according to an embodiment analyze power patterns of power generation sources and loads in type-specific villages or complexes having different peak time zones, thereby enabling energy use efficiency and stability to be improved. In addition, through an embodiment, power operation and surplus power for each type of empirical site according to a peak load and energy saving analysis can be shared, and thus power purchase costs can be reduced and a power operation between type-specific empirical complexes can be linked. In addition, through an embodiment, provided are digital twin-based microgrid operation advancement methods such as those for energy utilization improvement and power grid stabilization contribution by using an internal power operation of a small-scale empirical site and energy sharing between type-specific complexes.

According to the data center cluster two-stage energy sharing method based on the multi-element load comprehensive demand response, the first stage is a day-ahead optimization stage, uncertainty probability distribution of wind power, photovoltaic power generation and loads is fully considered in the stage, and a shared energy storage (SES) optimization scheduling method based on a conditional worst-at-risk value (WCVaR) is constructed. The second stage is a real-time optimization stage: firstly, designing a novel point-to-point (P2P) transaction mechanism based on an electricity and heat supply-demand ratio so as to realize joint sharing of electricity and heat between DCPs; then, a refined IDR model is provided, the model considers the space-time transferability of data loads and the flexibility, the thermal hysteresis effect and the thermal comfort of the household appliances, and indexes such as the efficiency improvement ratio are introduced to evaluate the IDR model; and finally, constructing a benefit function of the DCCO and the DCPs.

The invention relates to the technical field of multi-park integrated energy system scheduling, in particular to a low-carbon scheduling method and system for a multi-park integrated energy system, and the method comprises the steps: obtaining renewable energy historical output data and historical meteorological parameters of each park, and generating a renewable energy generation power prediction sequence through a pre-trained generative adversarial network; constructing a comprehensive energy optimization model, inputting a renewable energy power generation power prediction sequence, and outputting an equipment scheduling instruction and an energy interaction strategy of each park; executing the equipment scheduling instruction, monitoring actual renewable energy power generation power data, and calculating a renewable energy power generation power prediction deviation; and calculating the energy interaction cost and the energy sharing income of each park, and calculating the actual marginal contribution value of each park by adopting an improved Shapley value algorithm based on the renewable energy power generation power prediction deviation, the energy interaction cost and the energy sharing income. According to the invention, prediction precision and scheduling reliability can be improved, cost and carbon emission are optimized, and earnings are distributed fairly.

The invention provides a maintenance rescue interface system, a vehicle energy system, a child-mother vehicle energy sharing system and a vehicle state control method, and relates to the field of new energy vehicles. The maintenance and rescue interface system is arranged on any one of a child vehicle and a mother vehicle and comprises a maintenance and rescue change-over switch, a maintenance and rescue controller and a maintenance and rescue interface, wherein the maintenance and rescue change-over switch and the maintenance and rescue controller are arranged in the vehicle, and the maintenance and rescue interface is arranged outside the vehicle; the maintenance and rescue change-over switch is connected with a maintenance and rescue controller, the maintenance and rescue controller and a power battery system on the vehicle are both in communication connection with a vehicle control unit on the vehicle, and the power battery system and the maintenance and rescue controller are connected with a high-voltage power supply interface and a low-voltage communication interface of the maintenance and rescue interface respectively; and the high-voltage power supply interface and the low-voltage communication interface of the maintenance rescue interface are respectively used for connecting high-voltage power supply interfaces and low-voltage communication interfaces on maintenance rescue interfaces of other vehicles. Therefore, energy sharing of the two vehicles can be rapidly achieved, and the method is suitable for diversified scenes.

The invention provides an energy management optimization method and system for producers and diasters, and the method comprises the steps: constructing an energy storage sharing energy management framework, quantifying the energy storage standby demands, and adjusting and optimizing the energy storage resource configuration; the energy storage sharing energy management framework comprises a production and disappearing person group and an energy management control center; based on an energy storage sharing energy management framework, constructing a target function by taking the lowest operation cost of a producer as a target, and based on energy storage sharing matching, constructing a producer energy management optimization model; a local community clearing model is constructed based on a producer energy management optimization model, distributed clearing solving is carried out by using an alternating direction multiplier method ADMM, and energy sharing and transaction are carried out among producers by solving an energy-reserve sharing problem of producers. The technical problems that an energy management scheme is difficult to popularize on a large scale and the electric energy sharing effect is poor due to low energy management efficiency, insufficient flexibility, high investment cost, extensive management and low utilization rate are solved.

The invention provides a child-mother vehicle energy sharing system, a control method and a child-mother vehicle system, and relates to the technical field of charging control. The child-mother vehicle energy sharing system comprises an energy transmission system, a mother vehicle power battery system, a mother vehicle fuel cell system, a mother vehicle electric driving system, a mother vehicle whole vehicle controller, a child vehicle power battery system, a child vehicle fuel cell system and a child vehicle whole vehicle controller. The mother vehicle fuel cell system is electrically connected with the mother vehicle power cell system, and the mother vehicle fuel cell system and the mother vehicle power cell system are electrically connected with the mother vehicle electric driving system to provide energy for the mother vehicle electric driving system; the secondary vehicle fuel cell system is electrically connected with the secondary vehicle power cell system to charge the secondary vehicle power cell system, and the energy transmission system is electrically connected with the primary vehicle power cell system, the primary vehicle electric driving system and the secondary vehicle power cell system to transmit energy in the primary vehicle and the secondary vehicle. According to the invention, the fuel cell, the power cell and the child-mother vehicle can be combined for energy sharing.

The invention provides a distributed scheduling method for railway traction stations and peripheral micro-energy grids, and belongs to the technical field of energy supply of micro-energy grid groups containing the railway traction stations, and the method comprises the steps: building a micro-energy grid sharing mutual aid grid structure containing the railway traction stations, obtaining a power model of each railway traction station, and optimally configuring energy storage equipment, obtaining operation constraints of the energy storage equipment; constructing an energy sharing benefit function by taking each micro-energy network agent as a game main body and taking individual benefit maximization as a target, setting constraint conditions, and establishing an energy sharing non-cooperative game model; and solving the energy sharing non-cooperative game model by adopting an alternating direction multiplier algorithm to obtain a distributed energy transaction behavior result and a price result. According to the method, distributed solution is carried out on the micro-energy network energy sharing non-cooperative game model based on the alternating direction multiplier method, original centralized optimization is converted into coupling optimization among a plurality of micro-energy network agents through interactive variables, the efficiency of the whole iteration process is guaranteed, and the privacy of each energy network is protected.

The invention belongs to the technical field of power transmission line erection equipment, and particularly relates to a stretching system. The stretching system comprises a plurality of traction devices and a plurality of tension devices, the traction devices and the tension devices are each provided with a driving power source, due to the fact that the capacities of the driving power sources are different and the power consumption of the electric devices is different, the driving power sources of the electric devices can have different electric quantity conditions, and even part of the driving power sources can have a power lack state. Therefore, the operation efficiency of the electric equipment with the driving power supply in the power-deficient state is reduced. In the application, mutual charging is realized through the power supply modules of the electric devices, so that energy sharing of the electric devices in the stretching system is realized, the electric devices can maintain normal operation efficiency for a long time, reasonable utilization of energy is further realized, the operation efficiency of the stretching system is improved, and the purposes of saving energy and reducing consumption are achieved.

The invention discloses an unmanned aerial vehicle assisted emergency communication network performance optimization method and system. The method covers communication link optimization based on environment perception, information is collected through multiple sensors, an environment model is established by applying a machine learning algorithm, and the flight attitude and the communication frequency are dynamically adjusted according to the environment model. The distributed resource allocation utilizes a distributed algorithm and a game theory, takes a utility function Ui = w1Qi + w2Ri-w3Ei as a decision basis, and reaches Nash equilibrium through an iterative game; efficient energy management improves endurance by means of devices such as a solar panel and a wind energy collector in combination with an intelligent algorithm and an energy sharing mechanism. The system comprises a plurality of unmanned aerial vehicles equipped with various modules and corresponding control modules. The stability, the resource utilization rate and the cruising ability of the emergency communication network are effectively improved, and powerful communication guarantee is provided for emergency rescue.

The invention relates to the technical field of energy sharing management, and discloses a vehicle electric cabinet collaborative energy sharing management system, which comprises a vehicle electric cabinet management module, an environment monitoring module, a battery charging information module and an analysis unit, and is characterized in that each vehicle electric cabinet in a target area is numbered; acquiring environment information data of each vehicle electric cabinet through an environment monitoring module; acquiring charging information data of each battery in a past preset time period through a battery charging information module; and finally, performing analysis according to the environment monitoring information data and the charging information data through an analysis unit to obtain a state index of each battery, performing state rating on each battery according to the state index of each battery, and judging a charging mode of each battery according to the state rating of each battery. According to the invention, the automatic evaluation of the battery state is realized, and the corresponding charging mode is automatically matched, so that the utilization rate of the vehicle electric cabinet is improved to the greatest extent, the service life of the battery is effectively prolonged, and the potential safety risk is reduced.

The invention discloses a ship energy sharing management method based on multi-mode adaptive droop control. The ship energy sharing management method comprises the following steps: acquiring shipborne micro-grid data; connecting a plurality of electric ships in parallel with a direct-current micro-grid, and constructing a direct-current micro-grid cluster by using the obtained shipborne micro-grid data; and performing multi-mode adaptive droop control on the constructed DC micro-grid cluster, and coordinating a power control strategy of the whole DC micro-grid cluster. And establishing a small-signal analysis model for the direct-current micro-grid cluster to judge the stability of the system. According to the ship energy sharing management method, decentralized power sharing of a micro-grid cluster based on a plurality of electric ship parallel DC micro-grids is realized through multi-mode adaptive droop control, and a power control strategy of the whole micro-grid cluster is coordinated, so that the micro-grids can operate independently and can also provide power support mutually.

The invention relates to the technical field of hybrid energy storage, in particular to a flywheel energy storage and storage battery hybrid UPS comprehensive evaluation method, which comprises the following steps: analyzing the variation trend of key parameters of a flywheel energy storage unit and a storage battery based on a UPS uninterruptible power supply system, identifying synchronous abrupt change and abnormal combination, and judging the synchronous fluctuation and sharing relationship between parameters, and combining the temperature rise speed and the energy distribution state, dynamically adjusting the output proportion, and obtaining a parameter sensitivity distribution index. According to the invention, through dynamic linkage analysis of operation data of the flywheel energy storage unit and the storage battery, synchronous identification is carried out for parameter change trend, fluctuation amplitude and sudden change behaviors, and coupling judgment is carried out on multi-source parameters, so that a feature group showing linkage abnormity can be screened out in real time; dynamic changes of key links such as energy sharing, temperature rise and discharge rate are accurately described in all stages of operation of the UPS system, and UPS system state interval division is performed according to the parameter response direction and number, so that the boundary of a risk area is clear.

The invention belongs to the field of cloud energy storage power dispatching, and discloses a multi-microgrid cloud energy storage dispatching method in an energy sharing mode, which comprises the following steps: acquiring data and preprocessing the data; constructing a user side cloud energy storage charging and discharging optimization decision model; constructing a cloud energy storage operator charging and discharging optimization decision model; the micro-grid internal power balance model serves as an upper-layer model, user income serves as a main optimization target, upper-layer and lower-layer public decision variables are transmitted into a lower-layer model after solving, the lower-layer model is a multi-micro-grid combined operation optimization model, micro-grid overall income serves as a main optimization target, and an optimal scheduling strategy is output after solving. According to the invention, the problem that the income is biased to the user without the photovoltaic system by taking the overall benefit as the main target based on the traditional cloud energy storage mode is solved, the benefit of the user with the photovoltaic system is ensured, and the electricity utilization satisfaction degree of the photovoltaic users participating in the mode is improved.

The invention discloses a distributed energy sharing method and system based on a hybrid game model, and relates to the field of economic operation of a power distribution network, and the method comprises the steps: taking upper-layer power distribution network income maximization as an objective function, considering power distribution network price constraints and power distribution network operation constraints, and building a power distribution network-aggregator master-slave game model; and minimizing the operation cost of the lower-layer optical storage all-in-one machine aggregator alliance as a target function, considering the operation constraint of the aggregator, establishing an aggregator alliance cooperative game model, and forming a power distribution network-aggregator mixed game model by the cooperative game model and a master-slave game model. Solving the power distribution network-aggregator mixed game model to obtain a power distribution network-aggregator distributed energy sharing optimal result; the hybrid game model is considered in the distribution network-aggregator distributed energy sharing, so that the overall benefit of the aggregator cluster and the rationality of the transaction are effectively improved, and the benefit of the aggregator in the alliance can be guaranteed.

The invention discloses a hydrogen production and hydrogenation integrated station electric energy-peak regulation combined market transaction method considering hydrogen load demand response. The method comprises the following steps: 1) constructing a hydrogen production and hydrogenation integrated station day-ahead electric energy-peak regulation combined market transaction mechanism and framework; 2) constructing a cost model of the hydrogen production and hydrogenation integrated station for regulating and controlling multi-type hydrogen load demand response; 3) considering uncertainty factors such as hydrogenation load of the hydrogen fuel cell vehicle, and proposing a hydrogen production and hydrogenation integrated station market transaction model with maximum operation income as a target based on distribution robustness; 4) constructing a day-ahead electric energy-peak regulation combined market clearing model containing the hydrogen production and hydrogenation integrated station by taking social welfare maximization as a target; and 5) proposing a market transaction strategy solving method based on a differential privacy-consistent alternating direction multiplier method (DP-C-ADMM). According to the invention, a cooperative transaction mechanism in which the hydrogen production and hydrogenation integrated station participates in multiple markets is constructed, and a transaction model based on distributed robustness and a transaction strategy solving method considering privacy protection are proposing.

The invention belongs to the technical field of power systems, and particularly relates to a direct-current micro-grid group power protection scheduling method based on mobile energy storage transfer frequency modeling. Comprising the following steps: constructing a mobile energy storage MES model; during the peak period of power demand, the MES flexibly moves through charging and discharging to realize energy scheduling among DCMG groups; a scheduling objective function is constructed, and a scheduling strategy with the purpose of minimizing the total operation cost is achieved; constructing a space-time transfer model of the mobile energy storage MES, and defining transfer time, residence time and frequency constraints; the nonlinear constraint is converted into a mixed integer linear programming problem, and the problem is solved through a commercial solver. According to the method, energy sharing among the DCMGs is realized through the MES, and the DC micro-grid group energy scheduling model integrating the MES under the power limiting condition is established, so that the load interruption cost during the power limiting period is reduced, and the overall elasticity of the micro-grid group is improved.

The invention relates to the technical field of battery health management, in particular to a battery energy storage health management method and system based on energy sharing, and the method comprises the steps that an aggregator obtains the current charging and discharging data of energy storage equipment of all user sides in real time, and obtains the current battery health state of the energy storage equipment according to the current charging and discharging data and initial data; the aggregator inputs the current battery health state of the energy storage equipment into the equivalent circuit model to obtain the current system efficiency and power capacity of the energy storage equipment; and the aggregator performs energy sharing on all the energy storage devices based on a preset health awareness energy management strategy according to the current battery health states, efficiencies and power capacities of all the energy storage devices, generates an energy scheduling scheme corresponding to each user side and sends the energy scheduling scheme to the corresponding user side. The system has the beneficial effects that energy sharing in a large range is realized on the basis of sensing the health state of the battery in real time, so that unnecessary cost and energy waste are reduced.

The present invention discloses an optimization method and system for the energy consumption load management of chain parks based on a clustering algorithm, which relates to the technical field of load management optimization. The method includes collecting data of multiple chain parks, constructing a load characteristic vector through a multi-source feature fusion technology; based on the load similarity and geographical distribution characteristics among chain parks, using a graph structure model to model the energy interaction and correlation characteristics among chain park nodes, forming a collaborative load network; aiming at the time-dependent characteristics of the energy consumption load of chain parks, segmenting the load curve according to time sequence and introducing a time weighting coefficient for clustering; designing a multi-objective collaborative optimization clustering algorithm, combining load clustering with optimization objectives to solve the optimal clustering scheme under different scenarios; and generating a distributed scheduling strategy adaptable to scenario changes according to the clustering results and the load collaboration relationship among chain parks. The present invention realizes energy sharing and load balancing among chain parks, and greatly improves the economy and environmental benefits of the regional energy system.

The invention discloses a vehicle energy sharing system and a control method. The vehicle energy sharing system is applied to a child-mother vehicle, and the child-mother vehicle comprises a child vehicle and a mother vehicle. The vehicle energy sharing system comprises a power source sharing controller, a child vehicle power supply conversion control module, a child vehicle power supply conversion switch module, a mother vehicle power supply conversion control module and a mother vehicle power supply conversion switch module. The power source sharing controller sends power supply conversion control signals to the child vehicle power supply conversion control module and the mother vehicle power supply conversion control module, and the child vehicle power supply conversion control module controls the on-off state of the child vehicle power supply conversion switch module according to the power supply conversion control signals. The mother vehicle power supply conversion control module controls the on-off state of the mother vehicle power supply conversion switch module according to the power supply conversion control signal, and energy sharing is achieved. According to the technical scheme, the child vehicle can charge the mother vehicle, the child vehicle does not need to be parked at a fixed charging device for charging, charging convenience is improved, the utilization rate of a power source is increased, and then cost is reduced.

The invention discloses an energy sharing mutual aid benefit balanced distribution mechanism among multiple micro-energy networks, which belongs to the field of multi-micro-energy network system operation scheduling, and comprises the following steps: S1, dividing micro-energy network groups and combined pairing according to a matching index of a comprehensive curve form and a distance of micro-energy network source and load data, and constructing a micro-energy network benefit objective function; s2, introducing contribution, cost and risk factors into a traditional Shapley value method model, and constructing an improved Shapley value method model; and S3, performing distributed optimization solution on the micro-energy network cooperation alliance based on an ADMM algorithm, and realizing benefit balanced distribution by adopting a cooperation game strategy of an improved Shapley value method model. According to the method, the interaction efficiency is improved by dividing the group through source load matching, the information privacy is protected by using the ADMM algorithm, fair distribution is realized by improving the Shapley value method model, and the method is suitable for collaborative optimization operation of a multi-micro energy network system.

The invention provides a big data industrial park multi-type building group electric energy sharing method and device, and belongs to the technical field of building group electric energy sharing optimization. The method comprises the steps that a big data industrial park electric energy sharing framework is built, and three typical building group optimization operation models of a data center building group, an office building group and a residential building group in a big data industrial park are built by considering the space-time adjustable characteristics of different loads; constructing a multi-building-group asymmetric Nash negotiation model by considering the contribution degree of each building group during electric energy sharing, and equivalently converting the multi-building-group asymmetric Nash negotiation model into a first-stage interaction power decision optimization problem and a second-stage transaction price decision optimization problem; a two-stage decision optimization problem is solved in a distributed manner by adopting an enhanced adaptive algorithm, so that the convergence speed of the model is accelerated. The method can assist the big data industrial park to realize efficient utilization of electric energy and cost saving, and has a wide application prospect.

The application provides a multi-output DC-DC converter based on shared DC capacitor, comprising a power conversion unit, an energy sharing regulation unit and an output unit; the power conversion unit is arranged between a power supply end and the output unit, and comprises a plurality of flying capacitors and a plurality of power switching tubes, thereby forming a flying capacitor switching network; the energy sharing regulation unit is connected with the power conversion unit, and comprises a DC capacitor and a plurality of power switching tubes, thereby forming a DC capacitor switching network; the output unit comprises a plurality of inductors and a plurality of output capacitors, thereby forming an inductor-capacitor output network, and the output unit has a plurality of output ends; the charging and discharging of the flying capacitor and the charging and discharging of the inductor are controlled by controlling the on-off of the power switching tubes in the power conversion unit and the energy sharing regulation unit, so that the output ends provide energy for loads, the DC capacitor is charged and discharged to store energy and provide energy for the output ends, and independent regulation of the output ends is realized.

The invention is suitable for the technical field of micro-grids, and provides a multi-micro-grid energy sharing method based on a vehicle-mounted mobile energy storage system, and the method comprises the steps: obtaining the real-time power vacancy or power redundancy data of each micro-grid in a multi-micro-grid system; constructing a multi-microgrid system energy sharing optimization model; solving the multi-microgrid system energy sharing optimization model to obtain the optimal transaction power of each microgrid and the vehicle-mounted mobile energy storage system; based on an asymmetric Nash bargaining model, generating a cooperative profit distribution scheme according to the optimal transaction power; sending to an energy transport operator, receiving an executable scheduling scheme fed back by the vehicle-mounted mobile energy storage system, and generating a target energy scheduling instruction according to the executable scheduling scheme; and controlling the vehicle-mounted mobile energy storage system to execute charging and discharging operation and mobile operation based on the target energy scheduling instruction. The utilization rate of mobile energy storage is effectively improved, and the problem that mobile energy storage refuses to execute remote area scheduling due to insufficient economic excitation is avoided.

The invention provides a capacitor energy equalization system and method for a modular multilevel converter. The system comprises a modular multilevel converter access module, an average capacitor voltage controller and a circulating current controller, the modular multilevel converter access module is used for generating a circulating current and inputting the circulating current to the circulating current controller; the average capacitor voltage controller is used for controlling the average value of the capacitor voltages of the sub-modules in the phase units to track a preset voltage reference value, generating a circulating current control reference current and inputting the circulating current control reference current to the circulating current controller; and the circulating current controller is used for receiving the circulating current and the circulating current control reference current, generating a compensating current which is opposite to the double-frequency circulating current in phase, and adjusting the circulating current through the compensating current so as to equally divide the capacitance energy. According to the invention, the loop current controller is added to suppress the frequency doubling loop current, and the operation reliability of the modular multilevel converter is improved.

The present invention relates to the technical field of photovoltaic energy storage, and in particular relates to a green energy sharing system and management method based on a photovoltaic energy storage system. The green energy sharing system comprises: a photovoltaic energy storage system; customer power generation systems, which are configured at all or some customers and are configured to connect to customer load circuits; an energy router, which is configured at each customer; and a system cloud platform, which is used for generating a scheduling instruction on the basis of the power generation of the photovoltaic energy storage system, the power generation of each customer power generation system and the power consumption of each customer load circuit. The management method is used for realizing energy scheduling on the basis of the green energy sharing system. The present invention provides a new solution for the application of new energy in different environments.

The application discloses a dynamic distributed energy storage and energy sharing allocation method based on energy exchange fusion, which comprises the following steps: a client continuously acquires power battery information and real-time position information at a fixed sampling frequency during vehicle operation and uploads the information to a server; according to the state of charge of the power battery, the client is divided into energy supply clients and energy demand clients; the energy demand clients send energy demand requests to the server; the server sends confirmation requests to the energy supply clients and the energy demand clients in turn, and generates an energy sharing allocation session after confirmation by both parties; the energy transmission is performed by respectively controlling the discharging device and the charging device through the in-vehicle bus; and in the energy transmission process, any party can actively terminate and notify the server that the energy transmission is over. The application can realize real-time, accurate and efficient allocation of energy between vehicles and is suitable for the urban road network dynamic distributed energy storage scene based on the long-range energy storage battery of an electric vehicle.

The invention discloses a park centralized and decentralized regulation and control method suitable for high-proportion photovoltaic consumption, and the method comprises the steps: building interactive energy sharing transaction mechanism mathematical models between market operators and parks and between a plurality of parks, building a non-cooperative game power distribution network and a target function of a plurality of park optimization regulation and control models, the market electricity price constraint, the electric quantity balance constraint and the electric energy supply and demand balance of the park are used as constraints; and solving a game model based on a Kriging meta-model algorithm. According to the method, a clear mathematical optimization model is adopted, a scheduling decision is determined by a clear objective function and constraint conditions, the whole scheduling process is transparent and traceable, and the interpretability is greatly enhanced. According to the method, electricity purchase and sale prices formulated by the power distribution network, all cost coefficients and a small number of parameters of the PSO algorithm are mainly adjusted, the structure enables the parameter space to be greatly reduced, parameter adjustment has more physical significance, and debugging is easy.