128 results about "Smart power" patented technology

The invention relates to the technical field of smart power grids, in particular to a hybrid game-based virtual power plant optimization operation method under multiple markets, and the method comprises the steps: building an electricity-certificate-carbon multi-market coupling transaction framework, deeply analyzing a master-slave game relationship between a virtual power plant operation platform and a VPP alliance, and building a price guidance-based double-layer interaction mechanism; according to the method, research is carried out aiming at the condition that a virtual power plant belongs to different interest subjects, a resource complementation-based alliance cooperation model is proposed, and a VPP alliance cooperation optimization framework considering demand side load elasticity is established by introducing a refined model of a flexible load; and establishing a virtual power plant operation platform and VPP alliance mixed game optimization model. Solving a master-slave game stage by adopting a double-layer iterative algorithm; and solving a cooperative game stage in combination with an alternating direction multiplier method. The virtual power plant is guided to participate in multi-market cooperative regulation and control through a mixed game mechanism, safe and stable operation of the power system is ensured, and the operation economy and environmental protection property are improved.

The invention discloses an electricity consumption anomaly detection method, system and device based on an environmental perception graph convolutional network and a medium, and belongs to the technical field of smart power grids. The method comprises the steps that historical electricity consumption of a power grid area unit and external environmental factors are acquired to construct a multi-dimensional space-time association graph; a periodic trend component and environment-related residual fluctuation are separated through the multi-dimensional space-time correlation diagram, and a two-channel diagram convolution feature is obtained; in combination with the convolution features of the two-channel graph, feature space decoupling of a periodic channel and a residual channel is realized, and decoupling features are obtained; and extracting a historical residual fluctuation sequence based on the decoupling features, and constructing an environmental state sensitive probability density function. According to the method, the historical electricity consumption and the external environment factors such as temperature, humidity or weather events are closely fused by constructing the multi-dimensional space-time association diagram, so that the space-time dependence of the electricity consumption behavior is effectively captured, and misjudgment caused by ignoring environment dynamics in a traditional method is avoided.

The invention provides a spare power automatic switching risk prediction method and system for a smart power grid, and relates to the technical field of smart power grids, and the method comprises the steps: collecting and screening an initial feature set of the smart power grid, and generating a dynamic feature set; outputting a conventional risk probability based on a time sequence feature through a random forest model, identifying a sudden abnormal mode based on a frequency domain feature through an XGBoost model, and synchronously generating a feature importance matrix; determining a power grid state by combining the time sequence characteristics and the frequency domain characteristics, dynamically fusing output results of the models according to fusion weights of the models determined by the power grid state, and generating a comprehensive risk level; inputting the comprehensive risk level and the dynamic feature set into a reinforcement learning environment model, and solving a multi-objective function generated by the model to obtain a spare power automatic switching execution strategy; and executing the spare power automatic switching execution strategy, and dynamically adjusting the sliding window for feature acquisition until the execution result meets the preset condition, so that the accuracy of spare power automatic switching risk prediction and the adaptability of the strategy are remarkably improved.

The invention relates to the technical field of data early warning, in particular to an intelligent power plant safety early warning method based on multi-data coupling. The method comprises the following steps: acquiring multi-source coupling data including power plant production operation data, key equipment state monitoring data, environment monitoring data and historical accident records, and calculating acquisition time intervals and synchronous delays between data sources; defining the ratio of the acquisition time interval to the topological distance between the corresponding nodes of the key equipment as a coupling propagation rate; constructing a time sequence-topology association window based on the coupling propagation rate, and judging the state type of the key equipment according to the time sequence-topology association window; a key equipment risk parameter is obtained by quantifying the state type; according to the method, key equipment risk parameter quantification and potential risk marking are realized through multi-source coupling data and time sequence-topology correlation analysis, so that dynamic grading early warning is supported, and the operation safety and early warning real-time performance of a power plant are improved.

The invention discloses an electric vehicle charging method, device and equipment based on time-of-use electricity price, and a medium, and relates to the field of smart power grids, and the method comprises the steps: generating a target power data set according to the load data of a power grid side, the charging data of a target charging pile, and a preset time-of-use electricity price parameter; performing power grid load curve prediction based on the target power data set through a preset prediction model, and performing peak-valley period division on a predicted target prediction power grid load curve to obtain divided periods; generating a time-of-use electricity price signal according to the divided time periods, and constructing a charging strategy function according to the target power data set and the time-of-use electricity price signal; and solving the charging strategy function to obtain a corresponding target solution set, scoring a plurality of solutions in the target solution set through a preset weight, and generating a charging strategy based on the target solution with the highest score, so that the electric vehicle can be charged based on the charging strategy. Therefore, the electric vehicle charging cost of the user can be reduced while the intra-day load peak-valley difference is reduced.

The invention relates to the technical field of intelligent power distribution network safety detection and fault processing, in particular to a multi-source coupling leakage current accurate traceability and cooperative suppression method and system for a power distribution network, and the method comprises the steps: collecting leakage current, voltage phase and power fluctuation data through a synchronous phasor measurement device; based on the collected data, constructing a four-dimensional feature library, carrying out decoupling processing on leakage current signals, and then realizing accurate traceability positioning of the leakage current according to a matching result of the leakage current signals and the four-dimensional feature library and a time difference between sensors; data are uploaded to a distribution network dispatching center, leakage current is evaluated based on a dynamically adjusted safety threshold value, and then operation states of a photovoltaic inverter, an energy storage converter and a charging pile are cooperatively controlled to realize active suppression of the leakage current; and performing preliminary diagnosis on the leakage current at the edge side, uploading a result to a cloud end, and determining a final diagnosis conclusion. According to the invention, the accuracy of multi-source coupling leakage current tracing and the accuracy of cooperative suppression of the power distribution network are improved.

The invention relates to the technical field of intelligent power plants, in particular to a robot inspection control method and system for an intelligent power plant. Comprising the steps that an inspection equipment library and a power plant monitoring model are established, and the power plant monitoring model is used for generating a risk thermodynamic diagram; generating an inspection demand package according to the risk thermodynamic diagram, and generating a primary inspection strategy according to a preset inspection model and the inspection demand package; obtaining a feedback data packet of each inspection sub-device according to a preset feedback time node, and judging whether to generate an operation correction instruction or not according to the feedback data packet; the method comprises the following steps: periodically predicting power plant equipment, constructing a corresponding risk thermodynamic diagram, screening first-level risk points according to the risk thermodynamic diagram, performing path optimization based on position parameters of each first-level risk point according to an inspection model, generating corresponding inspection sub-paths, and completing an inspection task by matching the optimal inspection sub-equipment. The inspection efficiency and fault early warning efficiency of the power plant are improved, and safe operation of the power plant is ensured.

The invention discloses a block chain enabling smart power grid transaction system based on a game theory, and relates to the technical field of regional chains, and the system comprises a strategy management module which is used for making a buying and selling strategy based on the optimal utility through the game theory according to the electric meter storage space of a user, power utilization historical information and transaction record information, the electric equipment of the whole network is dispatched through the block chain; the transaction contract module is used for creating and updating a transaction contract based on the operation strategy formulated by the strategy management module; and the user management module is used for managing the information of the power users and the historical electricity utilization records. According to the invention, an efficient, fair and transparent power transaction mode is constructed by using the security of the block chain technology and the real-time response characteristic of the smart power grid, and the method aims at fully utilizing the distributed power storage units to achieve power utilization peak regulation so as to reduce the energy loss.

The invention discloses an intelligent power utilization data acquisition control method and system based on edge calculation. The method comprises the following steps: acquiring acquisition task information of a master station; the acquisition task information of the master station is divided into a plurality of sub-acquisition tasks according to regions; sending the sub-collection tasks to collectors and concentrators in the corresponding areas for storage; based on the sub-collection task, the collector collects user-side electric energy meter data and verifies the data to obtain first collection data; based on the concurrent reading command, the concentrator reads the first aggregated data in the collector to obtain second aggregated data; and based on the set requirement of the master station, the master station extracts the corresponding electric energy meter data in the collector. According to the invention, local collection of a user side is completed by reading meter data storage through the collector, minute-level high-frequency collection and power failure active reporting of data such as voltage, current and electric energy of the electric energy meter can be realized, and a data basis is provided for services such as power supply line aging trend analysis, power grid voltage quality monitoring and load monitoring analysis.

The invention relates to an automatic pre-warning system after equipment failure for a smart power plant. The automatic pre-warning system comprises a data acquisition unit, a fault point judgment unit, a fault propagation relationship network establishment unit, a shutdown risk assessment unit and a pre-warning unit. The method has the beneficial effects that through cooperative work of data acquisition, fault point judgment, fault propagation relationship network modeling, shutdown risk assessment and an early warning unit, fault propagation chain reaction is dynamically quantified, and the shutdown risk probability of the whole plant is generated, so that the defects of incomplete path analysis and lagging risk calculation in a multi-equipment fault scene in a traditional method are overcome; the accuracy of fault early warning is improved, so that an effective emergency response basis is provided for operation and maintenance personnel of an intelligent power plant; the propagation probability matrix generation module corrects the final propagation probability according to the actual fault propagation mark value, and the final propagation probability is corrected in each fault propagation event, so that prediction becomes more and more accurate along with system operation.

The invention provides a dynamic cooperative control method and system for a smart power plant with few people on duty, relates to the field of power plant operation control, and solves the technical problem of insufficient adaptive ability of a control strategy in a few people on duty environment in the prior art. The method comprises the following steps: adjusting a weight coefficient of a global optimization objective function by utilizing a meta-cognitive optimization model based on historical and real-time operation data; generating an optimal control strategy in a pre-constructed digital twinborn model through a reinforcement learning algorithm by using the adjusted global optimization objective function; performing distributed negotiation on each sub-region through a potential game mechanism according to the optimal control strategy to obtain a cooperative control strategy of each sub-region; and performing simulation verification on the cooperative control strategy by using a pre-constructed digital twinborn model, and performing risk assessment and strategy decision in combination with a risk assessment model.

The invention relates to the technical field of industrial big data, in particular to an Internet of Things sensing and data monitoring integrated system, which comprises an Internet of Things sensing module used for acquiring a sensing parameter set of a distributed simulation unit of an intelligent power plant and a historical performance evolution trend reflecting a dynamic evolution rule; the twin mapping module is used for realizing signal space-time synchronization by utilizing a time service protocol, calling a multi-physics field evolution model to calculate thermal stress offset so as to execute numerical compensation, and generating a high-fidelity physical feature vector; the collaborative decision-making module shares observation information by using a multi-agent distributed collaborative architecture, identifies an electromagnetic-dynamic coupling response mode through a joint reward function and outputs a collaborative optimization strategy; and the execution module is used for generating an evaluation result by calculating the numerical deviation between the physical feature vector and the design envelope, and adjusting the excitation control variable according to a strategy until the system converges to a target equilibrium value. According to the method, the steady state monitoring of the power system is realized through twin mapping and collaborative decision.

The invention discloses a renewable energy power grid voltage control method, device and system based on machine learning and a medium, and aims to solve the problems of power grid voltage fluctuation and out-of-limit caused by high-permeability renewable energy access. The method comprises the following steps: firstly, collecting power grid operation parameters, denoising, complementing and standardizing through Kalman filtering; constructing and training a GNN model in combination with power grid topology to realize real-time prediction of voltage deviation; then, an MARL decision framework with stable voltage, low consumption and high efficiency as targets is built, and an intelligent agent is trained to complete decentralized collaborative decision; driving a voltage regulating device to execute regulation based on a GNN prediction result and an MARL optimal strategy, and adapting to the dynamic change of the power grid through an interactive feedback mechanism; and finally, continuously monitoring the state of the power grid, and triggering iterative optimization of the model and the strategy. Through multi-module cooperation and dynamic iterative optimization, the power grid voltage stability is effectively maintained, the voltage fluctuation is suppressed, and the operation reliability and the electric energy quality of the smart power grid are improved while the efficient consumption of renewable energy sources is ensured.

The invention provides an automatic power generation dispatching control method and device of a thermal power generating unit, and relates to the technical field of intelligent power grids, and the method comprises the steps: collecting multi-source observation data of an electric side and a hearth combustion side, and extracting a hearth negative pressure fluctuation amplitude, a flame centroid jitter amplitude and a sound pressure fluctuation amplitude to construct a sound-combustion coupling stability index; establishing a coal consumption cost function and an emission cost function in combination with historical unit operation data; dividing an acoustic-fuel coupling stability domain according to an acoustic-fuel coupling stability index, monitoring a rising trend, and taking an acoustic-fuel coupling risk as a scheduling constraint triggering condition; a scheduling optimization model is reconstructed in a risk dominant scene, active power output, a coal mill combination and air distribution parameters are used as decision variables, an optimal track is solved with physical limits, power grid side constraints and a stability domain as limiting conditions, and finally the optimal track is issued to a coordination control layer. According to the method, the output curve can be actively deviated in the acoustic-fuel coupling instability risk rising stage to avoid acoustic resonance, and therefore the dynamic dispatching capacity of the unit is guaranteed.

The invention discloses an active power distribution network multi-mode electric vehicle charging and discharging bearing capacity evaluation method, which belongs to the technical field of smart power grids, and comprises the following steps: firstly, aiming at the behavior randomness of an electric vehicle, constructing a time sequence scene containing arrival time, departure time and an initial charge state, and establishing three types of charging and discharging mode constraints; generating a time sequence demand curve through Latin hypercube sampling; establishing each-phase voltage and current steady-state constraint and distributed power supply constraint by taking the maximum bearing capacity as a target and combining the characteristics of the power distribution network, and constructing an evaluation model; and finally, solving by adopting mixed integer linear programming, and linearizing the nonlinear constraint to obtain a linear model capable of being efficiently solved, so as to realize evaluation of the bearing capacity of the electric vehicle. The method focuses on the core demand of large-scale electric vehicle bearing capacity evaluation, overcomes the limitation that a traditional model is difficult to adapt to complex characteristics of a three-phase unbalanced active power distribution network, and realizes collaborative optimization of the electric vehicle bearing capacity and safe and stable operation of the power distribution network.

The application provides an anti-theft intelligent metering box suitable for smart power grids, which comprises a metering box body and a closing door. The inside of the metering box body is an installation cavity. The front of the metering box body is provided with an opening. The closing door is slidably connected with the front of the metering box body in the horizontal direction. The upper and lower sides of the front of the metering box body are both provided with horizontal sliding grooves. The back of the closing door is provided with two sliding assemblies. The two sliding assemblies are slidably connected with the two sliding grooves respectively. A camera is arranged in the installation cavity. The application further comprises a protective cover which is horizontally and rotatably arranged in the installation cavity. A driving assembly is arranged between the installation cavity and the back of the closing door. The driving assembly is used to drive the protective cover to be sleeved on the camera or to drive the protective cover to be away from the camera. The application solves the problems that the camera in the electric energy metering box is easily exposed, the protective cover is not responsive to the opening and cannot timely shoot the facial features of the person who opens the door in the prior art.

The invention relates to the technical field of smart power grid information security and privacy protection, and discloses a smart power grid P2P electric energy transaction differential privacy method comprising the following steps: setting related parameters according to a P2P electric energy transaction platform; constructing an attack evaluation module to obtain a quantified current privacy disclosure risk score; a differential privacy noise adaptive deployment problem is formalized into a Markov decision model; the optimal or near-optimal strategy of the candidate noise injection position and intensity is output in a self-adaptive mode; after noise parameters are generated and a noise injection decision is obtained through a set differential privacy noise mechanism, noise is injected and liquidation is executed at a specified position, a market liquidation result is issued, and meanwhile, corresponding privacy budget is deducted from global privacy budget parameters; and the attack evaluation module is used for carrying out privacy risk re-evaluation on the released market liquidation result, and carrying out online adaptation and rolling updating on the strategy network model. The privacy protection strategy can be dynamically adjusted according to the market state and the privacy risk.

The application relates to the field of data processing, and relates to a power consumption prediction method and system based on a smart electric energy meter. The method comprises the following steps: acquiring an average temperature prediction value of a next date; acquiring a planned running duration of production equipment of the next date; acquiring real power consumption values of a continuous preset number of days by using the smart electric energy meter; inputting the average temperature prediction value of the next date and the planned running duration into a preset power consumption prediction model, so that a power consumption prediction value of the next date of the enterprise is obtained. The method can improve the accuracy of the power consumption prediction result of the enterprise.

This invention discloses a method and system for configuring and restoring flexible resources and mobile energy storage in a power distribution network, belonging to the field of smart power distribution network technology. Based on a typhoon wind field and wind and rain load model, this invention constructs a time-varying failure rate for power lines and uses Latin hypercube sampling to generate a set of failure scenarios. Typical scenarios are obtained through scenario reduction. Based on the failure scenarios, in the pre-disaster stage, the invention identifies the deployment locations of smart soft switches (SOPs) and mobile energy storage systems (MESSs) that minimize the sum of pre-disaster investment costs and post-disaster recovery period weighted load shedding costs. In the post-disaster stage, time-varying accessibility constraints are constructed based on road travel time preprocessing results, establishing a collaborative recovery model that includes SOP operation, network reconfiguration, and MESS time-varying scheduling. This invention, based on the collaborative configuration and post-disaster control of flexible resources and mobile energy storage, effectively reduces the configuration cost of the power distribution network while improving its support and recovery capabilities in the face of extreme disasters such as typhoons.

The invention provides an energy router for an intelligent power distribution area, and relates to the technical field of power systems, and the energy router comprises a three-phase power supply, a high-voltage side main winding, a three-phase load, a low-voltage side main winding, a first voltage source converter, a second voltage source converter and a third voltage source converter. The high-voltage side main winding comprises a first high-voltage winding, a second high-voltage winding and a third high-voltage winding which are connected end to end; the low-voltage side main winding comprises a low-voltage small winding and a low-voltage winding; the low-voltage small windings comprise a first low-voltage small winding, a second low-voltage small winding and a third low-voltage small winding; the first low-voltage small winding, the second low-voltage small winding and the third low-voltage small winding are in star connection; the low-voltage winding comprises a first low-voltage winding, a second low-voltage winding and a third low-voltage winding which are connected end to end, and the low-voltage winding forms a three-phase series loop and is connected to the alternating current output terminal of the second voltage source converter.

The invention relates to the technical field of distribution boxes, and particularly discloses a waterproof comprehensive distribution box special for a smart power grid, which comprises a main box body, a cable chamber is fixedly connected to the bottom of the inner wall of the main box body, a sealing gasket is fixedly connected to the side surface of the main box body, a box door is rotatably connected to the side surface of the main box body, and a connecting groove is formed in the side surface of the box door. The sealing gasket is matched with the connecting groove in shape and size, an inclined rain baffle is fixedly connected to the top of the main box body, an air treatment box is fixedly connected to the part, located in the inclined rain baffle, of the top of the main box body, a drying device is fixedly connected to the top of the air treatment box, and a temperature adjusting chamber is fixedly connected to the top of the inner wall of the main box body; according to the comprehensive distribution box special for the waterproof intelligent power grid, damage caused by frosting of electrical components in winter can be avoided through the arrangement of the temperature adjusting chamber, air entering the distribution box can be dried through the arrangement of the drying device, and the electrical components in the distribution box are prevented from being damaged by moisture in the air.

The application relates to the technical field of smart power grids, and discloses a power distribution cabinet for electrical equipment, which comprises a power distribution cabinet, a zero line row arranged in the power distribution cabinet and electrically connected with the branch line, a conductive pin in sustained conductive contact with the zero line row, a pressing assembly comprising a pressing ring capable of being sleeved on the conductive pin, and a heat-sensitive trigger piece which releases the pressing effect of the pressing ring when the temperature of the conductive pin exceeds a threshold value, so that the contact piece instantaneously releases the zero line row and forms a repair gap therebetween, and then re-closes. When the temperature exceeds the threshold value, the heat-sensitive trigger piece instantaneously releases the pressing force of the pressing ring, so that a controllable repair gap is formed between the contact piece and the zero line row, and under the shearing action, the silver powder and the reducing agent are released by breaking the microcapsules, then the silver powder is sintered by Joule heat to form a dense conductive layer and reduce the oxidation layer, so that the effects of automatically repairing electrochemical corrosion, restoring low contact resistance and avoiding continuous high-temperature fire are achieved.

The present application belongs to the field of network type energy storage cabinet, especially relates to a kind of intelligent power consumption optimization method and system for network type energy storage, the method is by real-time acquisition operating state data, external dispatching instruction and system operation mode, constructs dynamic hypergraph model to integrally represent the coupling relationship between power scheduling task, heat load demand and heat management energy consumption;Further, with the minimum system total operating energy consumption as the goal, based on the model collaborative optimization solution, generate the joint operation strategy of power scheduling and heat management control in future period;Finally, execute the strategy on digital twin energy storage cabinet, realize the closed-loop joint control of power conversion and heat management subsystem, thereby solve the energy efficiency bottleneck problem caused by the split optimization of electric heating system, improve overall operation economy and safety.

Embodiments of the present disclosure relate to a smart power mode management inertial measurement system and a smart power mode management method. An embodiment inertial measurement system includes at least one motion sensor that outputs motion data having output data rate (ODR) periods and a control unit coupled to the motion sensor to control operation of the control unit based on power mode switching of the motion sensor, each ODR period including, according to the power mode switching, a first phase in which the motion sensor is controlled in a low power consumption state and a subsequent measurement phase in which the motion sensor is controlled to perform a measurement of generation of measurement data. Based on at least one check related to the measurement data generated in the measurement phase, the control unit adaptively adjusts a duration of the ODR period.

The invention relates to the technical field of smart power plants, and discloses a smart operation platform of a smart power plant, and compared with a traditional power plant management mode, the smart power plant system is higher in automation degree, can dynamically collect and process equipment data, can evaluate and optimize equipment and system protocols in real time, and improves the system reliability. And delay and cost increase caused by equipment incompatibility are eliminated. On the basis of the existing technical means, the platform further enhances the intelligence, automation and adaptability of the system through deep data analysis and protocol calibration, and improves the response speed, interconnection and intercommunication capability and overall operation efficiency of the power plant. Through automatic protocol conversion and real-time data feedback, the platform provides accurate decision support for operation of the power plant, energy management and resource configuration are optimized, and the power plant can quickly respond to changes and requirements of equipment protocols.

The invention relates to a ring main unit with a protection function, which relates to the technical field of intelligent power grids and comprises a box body and two box doors rotatably mounted on two edges of the front side of the box body. The top surface of the box body is rotatably connected with a protection plate, the protection plate can be overturned towards the direction close to the box door to be in a horizontal maintenance state attached to the top surface of the box body and can be overturned towards the direction away from the box door to be in a horizontal application state attached to the top surface of the box body, and the box body is provided with a rotating part for overturning and switching the two states of the protection plate; the protection plate can protrude out of the top face of the box body when in the horizontal maintenance state, and the protruding part of the protection plate can protect workers at the moment. According to the tool, workers are effectively prevented from being wetted, do not need to hold an umbrella, and can freely operate the tool with two hands for maintenance action.

The invention discloses an intelligent power distribution environment monitoring and sampling device, which comprises a sampling and monitoring unit, a power distribution environment monitoring unit and a power distribution environment monitoring unit, the parameter signals at least comprise a state parameter of a UPS storage battery pack, a machine room temperature and humidity parameter, a fresh air system operation state parameter, a harmful gas concentration parameter, an electrical parameter of a power distribution array cabinet, an illegal intrusion detection signal, a precise air conditioner operation parameter, a machine room water leakage detection signal and a fire-fighting monitoring signal. A data island formed by a traditional independent sensor is thoroughly broken through, an edge calculation module is arranged in the server to carry out on-site real-time cleaning, fusion and deep analysis processing on multi-source heterogeneous data, a multi-stage early warning mechanism is combined, the intelligent level of the system is remarkably improved, a machine room three-dimensional temperature field can be constructed, precise temperature control is achieved, and the service life of the system is prolonged. On-line diagnosis of the mechanical state of the switch does not depend on manual disassembly and maintenance, and high-frequency CT access can be directly supported to realize extra-peripheral-free detection of partial discharge.

The invention relates to the technical field of insulation protection equipment, in particular to an outdoor primary and secondary fusion ring main unit for an intelligent power grid, which comprises a box body and a sealing box, and is characterized in that a pressure relief assembly for protecting a circuit is arranged outside the sealing box; the pressure relief assembly comprises a trigger structure arranged in the sealing box, two gas outlet pipes used for discharging high-temperature gas and two arc extinguishing structures used for extinguishing electric arcs generated during switch-off. By arranging the trigger structure and the gas outlet pipe, when faults such as short circuit occur in the sealing box, the gas outlet pipe can be quickly opened for pressure relief, and more serious problems such as explosion caused by too high gas temperature and gas pressure in the sealing box are avoided; besides, through the arrangement of the arc extinguishing structure, when the sealing box is short-circuited and switched off, arc extinguishing processing is carried out on an electric arc generated by switching off, and more serious damage caused by the electric arc is avoided.

The invention relates to the technical field of smart power grids and energy transaction, and discloses a micro-grid P2P electric energy transaction bidding and matching optimization method, which comprises the following steps of: constructing a micro-grid bilateral P2P electric energy transaction market model, defining a buyer, a consumer, as an energy-deficient micro-grid and a seller, as an energy-rich micro-grid, and establishing a micro-grid bilateral P2P electric energy transaction market model; designing a transaction matching and settlement mechanism based on the second price auction mechanism; modeling a transaction environment in the market model as a Markov decision process, introducing a multi-agent reinforcement learning algorithm under a Markov decision process framework, and learning and generating a dynamic bidding strategy oriented to multiple rounds of transactions; in the market matching stage, the dynamic bidding strategy of the producer and the consumer is input into the microgrid bilateral P2P electric energy trading market model, a settlement list is output, the problems that the bidding strategy is static and the market efficiency is low in a traditional trading method are solved, and the method has high adaptability and generalization ability and is suitable for scenes such as intelligent power grid demand side management and energy internet.

The invention relates to the technical field of electric energy meters, in particular to a detachable combined modular electric energy metering box adaptive to an intelligent power grid, which comprises a cabinet body and a partition plate fixed in the cabinet body, and a cabinet door is rotationally mounted on the cabinet body; the electric energy meter is placed in the cabinet body, a switch is rotationally installed on the electric energy meter, and a positioning assembly connected with the electric energy meter is arranged on the partition plate; the elastic supporting mechanism is arranged in the cabinet body and connected with the electric energy meter, a locking mechanism connected with the electric energy meter is arranged on the partition plate, when the electric energy meter is assembled, the positioning assembly can limit the position of the electric energy meter, and under the action of the locking mechanism and the elastic supporting mechanism, position locking of a switch is released firstly, and then the electric energy meter is assembled. And when the electric energy meter needs to be disassembled, the locking mechanism can control the switch to be in an off state, so that the effect of safe disassembly and assembly during assembly and disassembly is ensured.