525results about "Selective ac load connection arrangements" patented technology

The invention discloses an optical storage and charging integrated micro-grid energy management system, which relates to the related technical field of micro-grids and comprises an electric energy collection layer, a digital twinborn layer, a collaborative optimization layer, an application execution layer, a photovoltaic power generation unit, an energy storage unit, a charging load unit and a distributed measurement and control terminal. The invention further discloses an energy management method of the photovoltaic, storage and charging integrated micro-grid. The energy management method comprises the steps of data acquisition, digital twin modeling, multi-target strategy generation and optimization, strategy evaluation and screening, strategy issuing and execution and closed-loop feedback and dynamic correction. According to the invention, through short-term prediction of a digital twinborn layer and real-time generation of a charging and discharging strategy by a collaborative optimization layer, fluctuating renewable energy sources are preferentially consumed, the light abandoning rate is reduced, energy storage charging is automatically triggered in an illumination peak period, and power overflow is avoided; based on the simulation result of the digital twinborn model, the power distribution of energy storage and load is dynamically adjusted, so that the photovoltaic utilization rate is improved, and the dependence on a traditional power grid is reduced.

The invention discloses a virtual power plant-based power distribution area collaborative governance system and method, and relates to the technical field of power system automation and intelligent power distribution networks, and the system comprises a dynamic autonomous partition governance unit which is used for dividing a power distribution area node into a plurality of subunits, correcting abnormal states in the subunits based on a power mutual aid strategy between adjacent subunits; the multi-time-scale collaborative optimization unit is used for constructing a second-level, minute-level and hour-level multi-time-scale collaborative mechanism and coordinating control targets of the power distribution area at different time scales; the edge-cloud collaborative decision-making unit is used for complementing the edge side real-time control strategy and the cloud global strategy; and the elastic resource pool unit is used for calculating the elastic contribution degree of the resources and formulating priorities, and calling the resources according to the priorities to meet load requirements. By integrating the virtual power plant technology, the edge calculation, the digital twinning and the multi-time scale optimization strategy, the intelligent and efficient treatment of the power distribution area is realized.

The invention relates to a power equipment state self-healing operation and maintenance method, and belongs to the field of power equipment operation and maintenance, and the method comprises the steps: obtaining the real-time operation state data of a power supply in a current multi-source power supply system, collecting the data through a preset sampling frequency, and constructing a power supply state matrix; a conversion time constraint condition is set in advance, a zero-delay switching decision tree is constructed and a power supply switching decision is output in combination with a main power supply fault risk assessment result, and if the main power supply fault risk assessment result is abnormal, the standby power supplies are switched according to the determined switching priorities of the standby power supplies and the power supply switching decision; after the switching is completed, monitoring the power supply continuity index of the power equipment in real time, and if the power supply fluctuation time or the phase jump amplitude exceeds a preset allowable value, smoothing the power supply fluctuation by adopting the rapid power compensation function of the energy storage device; the stability and reliability of the multi-source power supply system are improved, and intelligent power supply switching and self-healing disaster recovery are realized.

The invention relates to the technical field of automation and intelligent operation and maintenance of a power system, in particular to a knowledge graph-fused reinforcement learning switching operation anti-error verification method, which systematically extracts a multi-dimensional anti-error rule covering an operation sequence, an equipment state and an electrical safety distance by constructing an operation ticket knowledge graph, and improves the accuracy of the operation ticket knowledge graph. The defect that a traditional single-station anti-error system is incomplete in rule coverage is overcome, meanwhile, in combination with deep mining of a reinforcement learning model on historical operation data, implicit anti-error rules can be automatically extracted, illegal scenes which are not covered by a traditional rule base are supplemented, overall-process and multi-level accurate verification of switching operation is achieved, and the verification efficiency is improved. And the risks of misoperation and missing detection are greatly reduced.

The present teachings relate to an electrical device (100) comprising: a first electrical power input (101) connectable to receive electrical power from a first power source; a second electrical power input (102) connectable to receive electrical power from a second power source different from the first power source; at least one electrical power output (121, 122, 123) , each electrical power output being connectable to supply electrical power to an individual electrical power consumer; a switching circuit (105) operable to route electrical power from the first electrical input to at least one of the electrical power outputs; a sense circuit operable to detect a depletion signal indicating an interruption in the electrical power which is being provided at the first electrical input; a controller (110) operable to control the switching circuit to switch from the first electrical power input to the second electrical power input in response to the depletion signal, thereby routing electrical power from the second electrical input to at least one of the electrical power outputs. Related methods are also disclosed.

Disclosed in the present invention are an optimization-based regulation and control method and apparatus for distributed energy storage, a device, and a storage medium. The method comprises: on the basis of current weather parameters, constructing an extreme weather model; determining a plurality of faulted and out-of-service elements in which faults will occur in a power distribution network; then on the basis of the faulted and out-of-service elements, system parameters of a distributed energy storage system, and an operation parameter of the power distribution network, constructing a dual-objective optimization model taking load loss minimization and power failure time minimization as objectives; and finally, solving for the dual-objective optimization model to generate an optimal regulation and control scheme applied to the distributed energy storage system. Therefore, when a fault has occurred in the power distribution network, the distributed energy storage system is regulated and controlled by means of the optimal regulation and control scheme, such that power supply of the power distribution network is restored as soon as possible in extreme typhoon weather, and the transient power deficit of the power distribution network is made up promptly. Therefore, the present invention can effectively guarantee the safe operation of power distribution networks under the condition of extreme typhoon weather.

An electrical device (100), such as an automatic transfer switch or an electrical power distributor, comprises: a first electrical power input (101); a second electrical power input (102); an electrical power output (121, 122, 123); a switching circuit (105) operable to route electrical power from the electrical power inputs to the electrical power output; the switching circuit comprising: a first switching element (111) to allow, when enabled, power flow from the first electrical power input to the electrical power output; and a second switching element (112) to allow, when enabled, power flow from the second electrical power input to the electrical power output; a controller (110) operable to control the switching circuit to switch to the first electrical power input or the second electrical power input for selecting which of said electrical power inputs is to supply electrical power at the electrical power output; wherein the electrical device is operable to determine a timing sequence of switching between the first electrical power input and the second electrical power input.

An electrical line selection system comprising a circuit module configured to connect energy sources with multiple line outputs. The circuit module has a number of inputs configured to connect to energy sources, including rechargeable battery systems, and a number of outputs configured to connect with other electrical systems such as other battery systems, loads, charging sources, and various AC or DC power supplies. A switching circuit is contained by the circuit module and a controller manages the switching circuit based on desired connections and strategies for managing power supplies and current sinks.

Responsive to a voltage across a capacitor being greater than a voltage across a traction battery, a controller may open switches such that charge current from a DC charger flows through a diode to the traction battery without following through coils of an electric machine and without flowing through an inverter.

The invention discloses a flexible resource distributed optimization scheduling method and system considering wind power uncertainty, and the method comprises the steps: constructing a distribution robust opportunity constraint according to a wind power prediction error fuzzy set, and carrying out the convex approximation of the distribution robust opportunity constraint through introducing a conditional value-at-risk, carrying out linearization processing on the distribution robust opportunity constraint after convex approximation; based on the distribution robust opportunity constraint subjected to linear processing, multi-element flexible resource differentiation operation characteristics of an energy storage system, an electric vehicle and an adjustable load are considered, and a flexible resource collaborative scheduling model considering the wind power uncertainty distribution robust opportunity constraint is constructed; adopting a consensus alternating direction multiplier algorithm to reconstruct the flexible resource collaborative scheduling model considering the wind power uncertainty distribution robust opportunity constraint into a distributed optimal scheduling model; and improving a consensus alternating direction multiplier method through a branch and bound method, processing an adjustable load discrete variable, and solving the distributed optimization scheduling model to obtain a flexible resource distributed optimization scheduling strategy.

The invention relates to the technical field of safe operation of a power system, in particular to a power distribution network information physical system fault collaborative recovery method, which comprises the following steps of: acquiring basic operation data of a communication layer and a physical layer, and respectively constructing fault recovery models of the communication layer and the physical layer; the communication layer takes optimal link performance as a target and applies constraints such as link capacity and connectivity, the physical layer takes multiple parameters such as load recovery as an optimization target and applies constraints such as network topology and power flow, and a double-layer optimization model, an upper layer optimization communication recovery strategy and a lower layer optimization physical recovery strategy are constructed for concurrent faults; and solving by using a double-layer optimization objective function to realize power distribution network fault collaborative recovery. According to the method, the interaction between the communication layer and the physical layer is comprehensively considered, so that the fault point can be more accurately positioned, the fault area can be quickly identified, the optimal recovery strategy is formulated, the power supply reliability is improved, and the healthy development of the smart power grid is promoted.

The invention discloses a power distribution network flexible mutual supply control method considering load uncertainty, and relates to the technical field of power system control. The method includes: acquiring historical operation data of a power distribution network, and establishing a robust optimization model; based on the robust optimization model, a flexible mutual supply control strategy is designed, and an adaptive control mechanism is introduced; evaluating a system state, and performing distributed coordination control based on the evaluated system state; carrying out robust stability analysis according to the characteristics of the distributed control system; and evaluating the index system. According to the invention, the robust optimization model is established to effectively cope with load fluctuation; a flexible mutual supply control strategy is designed based on the model, power distribution is optimized by combining a hierarchical architecture and a self-adaptive control mechanism, and the response capability of the system to sudden changes is enhanced; an improved Kalman filtering algorithm is used for evaluating the system state, distributed coordination control is implemented, and the communication cost is reduced; a Lyapunov direct method is adopted to carry out robust stability analysis, and stable operation of the system is ensured.

The embodiment of the invention provides a virtual power plant cooperative control method and system and electronic equipment, and relates to the technical field of power distribution Internet of Things. The method comprises the steps of obtaining a control target; calculating a fluctuation coefficient according to historical data of the global state parameters, and determining an uncertain set; establishing a robust optimization model based on the uncertainty set, and solving the robust optimization model to obtain an optimal solution of a robust objective function; training a Bayesian deep reinforcement learning model by using the historical data; inputting the current state data of the global state parameters into a trained Bayesian deep reinforcement learning model, generating an optimal action, and calculating a corresponding confidence coefficient; and selecting one of the optimal action and the optimal solution of the robust objective function to generate a first control instruction according to the relationship between the confidence coefficient and a preset confidence coefficient threshold value, and issuing the first control instruction to a low-layer intelligent agent. According to the implementation mode provided by the invention, the virtual power plant can be promoted to develop in a more refined, intelligent and autonomous direction.

The present disclosure describes systems for providing electrical power that are modular, upgradable, and customizable. Systems described herein can be used to create modular, upgradable, and customizable charging stations for charging electric vehicles. In one example, a sub panel module can be electrically connected to a main input line that provides an alternating current power supply, and includes a plurality of electrical outlets, and a plurality of breaker switches Each breaker switch is electrically connected to one or more of the plurality of electrical outlets and can be electrically connected to the main input line.

The invention relates to the technical field of load segmented transfer, in particular to a 10kV distribution line load segmented transfer method and device based on an electric energy meter and a storage medium. Comprising the steps that S1, electrical parameters of key nodes of a 10kV distribution line are monitored in real time based on an intelligent electric energy meter, and the electrical parameters at least comprise voltage, current and a power factor; s2, mapping the monitored electrical parameters to a predefined fuzzy set by using a fuzzy logic algorithm, and reasoning and quantitatively evaluating the overload degree of the equipment based on a fuzzy rule; selecting a to-be-transferred load path based on a Dijkstra algorithm; and after it is confirmed that the load verification of the to-be-transferred path is passed, carrying out load transfer. According to the method, the electrical parameters on the key nodes are monitored in real time, overload evaluation is carried out in combination with the fuzzy logic algorithm and the optimized defuzzification algorithm, and the overload condition can be recognized more accurately even under the condition that current and power factors fluctuate sharply due to frequent starting and stopping of large industrial equipment.

An electrical device (100), such as an automatic transfer switch or an electrical power distributor, comprises: a first electrical power input (101); a second electrical power input (102); an electrical power output (121, 122, 123); a switching circuit (105) operable to route electrical power from the electrical power inputs to the electrical power output; the switching circuit comprising: a first switching element (111) to allow, when enabled, power flow from the first electrical power input to the electrical power output; and a second switching element (112) to allow, when enabled, power flow from the second electrical power input to the electrical power output; a controller (110) operable to control the switching circuit to switch to the first electrical power input or the second electrical power input for selecting which of said electrical power inputs is to supply electrical power at the electrical power output; wherein the electrical device is operable to determine a timing sequence of switching between the first electrical power input and the second electrical power input.

The invention discloses a power supply framework, a power supply method, a power supply device and a readable storage medium. The power supply framework comprises a mains supply end, a power supply system, to-be-powered equipment, a first mains supply end and a second mains supply end, the power supply system comprises a plurality of first power supply circuits and second power supply circuits with the same number as the first power supply circuits, the high-voltage ends of the first power supply circuits are electrically connected with a first mains supply end, and the high-voltage ends of the second power supply circuits are electrically connected with a second mains supply end. The low-voltage ends of the plurality of first power supply circuits and the low-voltage ends of the plurality of second power supply circuits are in one-to-one correspondence with low-voltage buscouple; the number of the to-be-powered devices is the same as that of the first power supply circuits, each to-be-powered device is electrically connected with the low-voltage end of one first power supply circuit and the low-voltage end of one second power supply circuit, and the first power supply circuit and the second power supply circuit which are in mutual low-voltage bus connection are electrically connected to two different to-be-powered devices. According to the power supply architecture, two power supply circuits of the same to-be-powered device are completely independent.

A dual power switching system selects a first power source or a second power source to supply power to a load coupled to an inductive device. The dual power switching system includes a first thyristor, a second thyristor, a third thyristor, a fourth thyristor, and a controller. The controller calculates a total magnetic flux according to a current magnetic flux of the inductive device and an expected magnetic flux of the second power source. When the power-supplying source is switched, the controller turns off the first thyristor and the second thyristor, and determines whether a commutable time is reached according to a power parameter of the first static transfer switch and the second static transfer switch. When the commutable time is reached, the controller correspondingly turns on at least one of the third thyristor and the fourth thyristor according to the total magnetic flux being less than a threshold.

The invention discloses a solar hybrid energy supply system for unmanned area monitoring and a dynamic adjustment strategy method. The system integrates a solar energy collection module, an energy storage module, a wind power / fuel oil auxiliary energy supply module and a monitoring load module, and realizes power supply guarantee through a multi-energy collaborative architecture. The dynamic adjustment strategy is based on real-time data acquisition, solar energy and wind energy are preferentially scheduled by utilizing a machine learning prediction model and a multi-objective optimization algorithm, and a'prediction-scheduling-fault tolerance 'closed-loop management is formed in combination with an energy storage battery buffer and fuel generator standby mechanism. The problems of unstable energy and high operation and maintenance cost in a traditional energy supply mode in a depopulated area are solved, 7 * 24-hour continuous power supply is realized, the utilization rate of renewable energy sources is remarkably improved, and the system has fault self-repairing and remote monitoring functions and is suitable for long-term monitoring scenes in an extreme environment.

A power management device for intelligently splitting and controlling a high power outlet is described. The device includes a housing, power input, outlets, power sensor, and a controller. The housing has an internal compartment configured to hold components of the device and an exterior surface. The device has a plurality of outlets on the exterior surface of the housing. Each outlet is configured to connect to an appliance. Each outlet has a power sensor configured to sense current draw and / or power use at the outlet. The controller of the device is contained within the internal compartment of the housing and monitors the usage of each outlet via readings from the power sensors. The controller determines, based on the monitored usage and appliance parameters, one or more outlets to provide current to, and causes current to be provided to the determined outlet(s).

The invention relates to a power equipment load scheduling optimization method and device. The method comprises the following steps: carrying out load operation data acquisition through monitoring units deployed in power equipment to obtain a distributed load operation data set, and obtaining strategy game relationship network data between the equipment based on the distributed load operation data set; obtaining initial load adjustment intention intensity data of each power device according to the policy game relationship network data between the devices; sending the initial load adjustment intention intensity data and the global collaborative scheduling optimization target to a distributed negotiation chain to obtain final load adjustment strategy data after negotiation consensus; and obtaining an optimized distributed load scheduling model according to the final load adjustment strategy data after negotiation of the consensus, distributing the optimized distributed load scheduling model to each power device, and executing decentralized power device load scheduling optimization. By adopting the method, the load scheduling of the power equipment can be optimized.

The present teachings relate to an electrical device comprising: a first electrical power input connectable to receive electrical power from a first power source; a second electrical power input connectable to receive electrical power from a second power source different from the first power source; at least one electrical power output, each electrical power output being connectable to supply electrical power to an individual electrical power consumer; a switching circuit operable to route electrical power from the first electrical input to at least one of the electrical power outputs; a sense circuit operable to detect a depletion signal indicating an interruption in the electrical power which is being provided at the first electrical input; a controller operable to control the switching circuit to switch from the first electrical power input to the second electrical power input in response to the depletion signal, thereby routing electrical power from the second electrical input to at least one of the electrical power outputs. Related methods and software products are also disclosed.

The invention discloses a transformer area intelligent interconnection device with a fast charging function and a control method thereof. The device mainly comprises a first current transformation module, a second current transformation module, an all-solid-state energy storage battery, a direct current charging module and a collaborative energy manager (EMS). The DC sides of the two converter modules, the energy storage battery and the input end of the charging module are all connected to a common DC bus, and the AC sides are respectively connected to the low-voltage sides of different distribution transformers. Through uniform control of the EMS, three core functions are realized: 1, during normal operation, the two converter modules are controlled to carry out power mutual assistance and reactive power regulation, the transformer load is balanced, and the voltage of the transformer area is optimized; secondly, the direct current charging module is used for rapidly charging the electric vehicle, and an energy storage battery is used for stabilizing charging power impact; and 3, when the power grid fails, switching the converter module to a grid construction mode, and establishing an island micro-grid in cooperation with the energy storage battery to guarantee power supply of a key load. According to the invention, the integration level is high, and intelligent cooperation and autonomous operation of source-network-load-storage-charging of the transformer area are realized.

The invention discloses an integrated power supply system and a scheduling method thereof, and belongs to the technical field of power supply systems, and the method comprises the steps: collecting the operation state data of a micro-grid in real time; establishing a storage battery stress factor table, identifying an effective charge-discharge cycle, calculating a life loss value, and converting the life loss value into life loss cost; the method comprises the following steps of: constructing an optimization model containing life loss cost by taking minimization of total operation cost as a target, and generating an optimal scheduling instruction set in each scheduling period by adopting a model prediction control framework and an improved particle swarm optimization algorithm. According to the invention, through real-time quantitative evaluation and optimal scheduling of the service life of the storage battery, the economy and reliability of the whole life cycle of the system are improved.

In one aspect, a transfer switch configured to operate in different transfer modes is provided. The transfer switch includes first and second inputs, first and second contactors, an output, first and second power stages, and a controller. The first and second inputs are configured to couple with first and second power sources, respectively. The first and second contactors are configured to selectively couple with the first and second inputs, respectively. The output is configured to couple with a load. The first and second power stages are configured to conduct electrical power when active. The controller is configured to determine whether a trigger condition has occurred while the first power stage is active, and in response thereto, to open the first contactor and activate the second power stage to transfer the load from the first power source to the second power source.

A connector, a power supply system, and a control method are provided. The power supply system includes multiple power supply devices and a connector. The connector includes a load connection terminal and a selection unit. The load connection terminal is configured to be connected to a load. The selection unit includes an output terminal and multiple input terminals. Each of the power supply devices is connected to a corresponding one of the input terminals. The input terminals are electrically insulated from each other. The output terminal is connected to the load connection terminal. The selection unit enables a selection of at most one of the input terminals to be electrically connected to the output terminal, to cause at most one of the power supply devices to supply power to the load through the selection unit.

The invention provides an intelligent monitoring and regulation and control method and system based on a distributed power supply access unit, and relates to a distributed power supply intelligent regulation and control technology. The method comprises the following steps: collecting and processing power grid load and power output data to obtain a load fluctuation trend and an output characteristic deviation; establishing a prediction model by using a support vector machine, and identifying dynamic mismatching points; when the mismatching points exceed the limit, parameter variation is analyzed through a neural network, and an adjustment coefficient is calculated; generating a regulation and control instruction by adopting a particle swarm optimization algorithm, and calibrating the output characteristics of the power supply; key synchronization points are extracted for matching judgment, and stable access configuration is obtained; performing risk assessment through a feedback mechanism, and updating the regulation and control model according to the risk assessment; and finally realizing balanced distribution of the power grid pressure. The system correspondingly comprises a data acquisition module, a dynamic analysis module, an instruction generation module, a configuration and evaluation module, an optimization balancing module and the like. According to the invention, accurate monitoring and adaptive regulation and control of distributed power supply access are realized, and the stability and efficiency of power grid operation are improved.

A power distribution system includes a macrogrid controller configured to control one or more first loads associated with a macrogrid, wherein the one or more first loads include a microgrid comprising one or more second loads and a plurality of energy resource systems; and a microgrid controller configured to receive one or more control signals from the macrogrid controller and control a power connection of the microgrid to the macrogrid based on the one or more control signals. The microgrid controller is configurable in a grid-connected mode, during which the microgrid is connected to the macrogrid, and a stand-alone mode, during which the microgrid is disconnected from the macrogrid, and wherein the microgrid controller is configured to operate in the grid-connected mode or in the stand-alone mode based on the one or more control signals.

A server manages power balancing resources electrically connected to a power network. The server includes a processor. In response to receipt of input of a travel schedule including a date and time of travel, a departure point, and a destination point from a user of the vehicle, the processor predicts a power supply and demand balance on the power network for the date and time of travel, based on power supply and demand performance information of the power network. In response to prediction that the power supply and demand balance is going to be adjusted on the date and time of travel, the processor provides the user suggestion to keep the vehicle connected to the power equipment on the date and time of travel and a reward for the vehicle responding to a request to adjust the power supply and demand balance.

The invention provides a multi-source data fusion digital twinborn platform construction method. The method comprises the following steps: acquiring real-time multi-source monitoring data streams of power equipment and preprocessing the real-time multi-source monitoring data streams; determining an analysis time period according to the preprocessed data, and extracting a data calculation equipment state label in the time period to represent an operation risk level; if the tag is a high-risk tag, generating an optimization strategy in combination with the current control strategy; if the label is a low-risk label, generating a maintenance strategy; and regulating and controlling the equipment according to the strategy information. Through dynamic analysis time period determination, state index calculation and a hierarchical response mechanism, accurate assessment and adaptive control of power equipment risks are realized, intelligent regulation and control based on a state prediction model and a decision tree are supported, and safe and stable operation of equipment is ensured. According to the invention, accurate monitoring and adaptive optimization control of the operation state of the power equipment can be realized, and the safety and operation and maintenance efficiency of the equipment are improved.