47 results about "Grid operator" patented technology

Provided is a method of operating a hybrid power plant, including energy generating units including a wind park and at least one unit of another type of renewable energy source and including an energy storage system, the method including: creating a power production schedule based on an actual forecast of power production, an actual forecast of energy price and actual hybrid power plant status, the power production schedule including at least scheduled power for points in time in the future; and controlling, during the points in time in the future the energy generating units and the energy storage system based on the power production schedule, the hybrid power plant status at the points in time in the future, in particular energy storage system status, such as to dispatch power according to the power production schedule, but complying with any grid operator reference at the points in time in the future.

The invention relates to the technical field of power supply and demand interaction, in order to realize efficient and economical power dispatching, a micro-grid master-slave game optimization dispatching method considering user flexible load demand response comprises the following steps: step 1, establishing a micro-grid day-ahead supply and demand interaction scene in which a single micro-grid operator participates with a plurality of users; 2, constructing an MGO leader optimization scheduling model considering the uncertainty of the user response power; step 3, constructing a user follower demand response model taking maximized participation DR income as a target function; 4, converting the chance constraint into a deterministic linear constraint and a second-order cone constraint which can be solved; and 5, solving the MGO and the master-slave game model of each user by adopting an analytic expression solving method. The method is mainly applied to power dispatching occasions.

The invention relates to the technical field of multi-virtual power plant optimization scheduling, and discloses a multi-virtual power plant mixed game optimization method and system considering wind and light uncertainty, and the method comprises the steps: building a joint model combining a master-slave game with a cooperative game based on the game relation of a power grid operator and a virtual power plant alliance; aiming at the output uncertainty of the wind and light generator set, through a data-driven two-stage distributed robust optimization method, a typical wind and light generator set output scene is selected, a discrete scene distribution value is calculated, the probability distribution of the wind and light generator set output scene is calculated in combination with historical data and a confidence coefficient formula, and a wind and light uncertainty probability model is constructed; based on the joint model and the wind-solar uncertainty probability model, the total cost and carbon emission of the virtual power plant alliance are reduced through collaborative optimization scheduling. According to the invention, the responsiveness to the carbon trading market is enhanced, and powerful support is provided for promoting low-carbon transformation and realizing the purposes of energy conservation and emission reduction.

The invention belongs to the technical field of photovoltaic micro-grids, and particularly relates to a photovoltaic micro-grid cooperative scheduling method based on multiple subjects. In order to solve the problem that EV user benefits, EV dynamic characteristics and the satisfaction degree of users to charging cost are not fully considered, the method is based on a prediction error and user sensitivity-based master-slave game scheduling strategy, firstly, a single-leader and multi-follower master-slave game model is established, a photovoltaic micro-grid operator serves as a leader in the master-slave game, and the photovoltaic micro-grid operator serves as the leader in the master-slave game; an EV aggregator and a vehicle owner serve as followers in a master-slave game, a game model is solved through mixed integer linear programming, an EV charging load prediction error and user sensitivity are considered during solving, a real-time dynamic electricity price correction mechanism is established by using an EV charging load historical prediction error and user sensitivity, a game feasible region is effectively optimized, and a real-time dynamic electricity price correction mechanism is established. Therefore, the EV user actively responds to the electricity price issued by the operator and carries out the charging behavior in order, thereby improving the photovoltaic local consumption.

According to the intelligent compatible and efficient charging control system and the application method thereof, a management system combined with a cloud platform is provided, and a more intelligent, convenient and reliable charging control system is provided for a user by integrating the latest information technology, automation technology and artificial intelligence technology. Charging strategies suitable for various vehicle types are dynamically generated through the cloud strategy management platform, the edge computing node executes a lightweight charging control model, the multi-mode sensing module collects battery state data in real time, and the federal learning framework is connected with vehicle enterprises, power grid operators and charging facility data. The system solves the problems of poor compatibility and insufficient data collaboration of a traditional charging system, improves the charging efficiency, guarantees the safety of a battery, achieves the personalized adjustment of a charging strategy, and will show huge market potential and social value in the future along with the rapid growth of the intelligent equipment and electric vehicle market.

The invention relates to a port micro-grid energy control strategy considering incomplete information, and the strategy is technically characterized in that the time-of-use electricity price of a power grid, the parameters of a micro-grid operator and the like are set, and a data source is determined; scene sampling is carried out, and uncertain information in micro-grid operation is converted into a computable deterministic scene; establishing a Bayesian-Stackelberg game model under incomplete information by taking a power transaction agent as a main body and a micro-grid operator as a slave body; a follower model constraint is established by considering port berth distribution, and a KKT condition is established for a follower model so that the double-layer game model can be converted into a single-layer optimization model; and solving the model by using a CPLEX solver to obtain an optimal electricity price and an energy control strategy of each scene. According to the method, the uncertainty of port micro-grid information is considered, port operation constraints, berth distribution strategies and the like are comprehensively considered, the economy of micro-grid operation is considered while the port logistics transportation efficiency is ensured, and a port micro-grid energy control strategy considering incomplete information is provided.

The application discloses a multi-time scale hierarchical scheduling method for a combined heat and power system containing electric vehicles, and the system comprises a micro gas turbine unit, an absorption refrigeration unit, a ground source heat pump unit, a wind turbine unit, photovoltaic, a battery, a super capacitor and a heat storage device. The optimization method contains two time scales. In the day-ahead stage, economic scheduling is carried out according to the day-ahead predicted power value of wind power and photovoltaic and the day-ahead predicted value of load power in the system, and a target function and optimization constraint condition are established, and the result is used as a reference for the day-ahead optimization. In the day-ahead stage, a two-layer rolling optimization model is considered, a target function and a constraint are established, and a model predictive control (MPC) rolling optimization layer corrects the result of the upper layer according to real-time predicted power information and non-planned behavior of the electric vehicle (EV). The application adopts a multi-time scale hierarchical optimization strategy, real-time tracks the optimal scheduling strategy of the combined heat and power system containing electric vehicles, and realizes a win-win situation between the electric vehicle owner and the micro-grid operator.

Computer implemented systems and methods for providing an uncertainty platform for an energy grid controller that (1) receives risk inputs including (a) one or more load forecasts, (b) one or more wind forecasts, (c) one or more solar forecasts, (d) one or more generator availability risk forecasts, (e) one or more generator fail-to-start or fail-to-run predictions, (f) one or more net scheduled interchange forecasts, and / or (g) one or more transmission congestion forecasts; (2) determines net uncertainty for a predetermined time period based on the risk inputs; and (3) provides dynamic risk outputs including forecast scenarios, reserve requirements and / or reserve margin thresholds based on the determination of net uncertainty.

The present invention discloses a multi-objective game scheduling method and system for a distribution network operator. The method includes the following steps: obtaining power consumption data; establishing a distribution network operator model with the goal of minimizing the grid operation cost; establishing a load aggregator cost model for a load aggregator composed of flexible resource users with economy as the goal; taking the established distribution network operator model as the upper-layer model and the established load aggregator cost model as the lower-layer model to construct a master-slave game model, and using an improved grey wolf algorithm to solve the master-slave game model to obtain the optimal time-of-use electricity price result for the distribution network operator's day-ahead scheduling. By modeling flexible resource users and the grid operator, establishing a day-ahead scheduling problem with economy as the goal, and using an improved grey wolf algorithm for solution to obtain the optimal day-ahead time-of-use electricity price, the present invention can improve the power management level on the flexible resource user side and has good practical significance.

Systems, methods and apparatus for power management in an electric power grid are disclosed. A power flow to a plurality of power consuming devices in the electric power grid is enabled and disabled by a plurality of controllable devices under the control of one or more client devices. An apparatus receives a power control command and select at least one client device to which to issue a power reduction message. The power reduction message comprises an amount of electric power to be reduced to at least one of the plurality of power consuming devices for a predetermined time. A database stores information relating to power consumed by the plurality of power consuming devices based on measurement and verification.

The invention relates to the technical field of photovoltaic voltage regulation, in particular to a photovoltaic energy storage cluster collaborative voltage regulation method and device based on adaptive gaming, and the device comprises a voltage out-of-limit judgment unit which judges whether the node voltage of a power distribution network is out-of-limit or not; the voltage response unit responds and judges whether the energy storage SOC of the power distribution network is sufficient or not; the voltage regulation unit responds to the adaptive game voltage regulation strategy and outputs the regulated node voltage of the power distribution network; the voltage recovery judgment unit is used for judging whether the adjusted node voltage of the power distribution network is recovered or not; a result output unit; according to the method, a'master-slave + evolution + cooperation 'three-layer fusion game framework is constructed, a power grid operator sets excitation signals, photovoltaic energy storage units serve as a group, dynamic response excitation is achieved through evolutionary game, respective output is optimized in a collaborative mode, and finally the equilibrium state of voltage qualification and the lowest cost is taken into consideration. The adaptive game optimization can adjust the strategy in real time in different operation scenes, and has good robustness and adaptability.

The invention relates to the technical field of smart power grids and information security, in particular to a PUF (Physical Unclonable Function)-based certificateless proxy signature smart power grid distributed energy transaction method, which comprises the following steps of: constructing a PUF-based certificateless proxy signature smart power grid distributed energy transaction system, transaction is carried out based on the certificateless proxy signature smart power grid distributed energy transaction system; the system comprises a power grid operator, an energy manufacturer, an agent, PUF equipment and a block chain, the transaction process comprises an initialization stage, an identity authentication stage and a transaction stage; according to the method, the unique key of the equipment is generated through the PUF, the problems of complex certificate management and key escrow are avoided by adopting a certificateless mechanism, decentralized evidence storage and non-tampering of transaction data are ensured based on the block chain, the problems of insufficient security, low efficiency and weak anti-attack ability of a traditional scheme can be effectively solved, and the method is adaptive to the resource-limited Internet of Things equipment and has the advantages of high security and high reliability. And efficient and credible safety guarantee is provided for distributed energy transaction of the smart power grid.

The invention provides a village-level micro-grid cooperative operation method and device considering optical storage and charging grid load coupling, and belongs to the technical field of power system operation. The method comprises the steps that a village-level micro-grid light-storage-charging-grid-load collaborative model is established under multiple scenes, and photovoltaic, energy storage, charging piles, a grid frame and loads of the village-level micro-grid are considered in the collaborative model; based on the collaborative model, taking a village-level micro-grid operator and a load aggregator as participants of a game, and constructing a village-level micro-grid complete information dynamic game model; and solving the game model to realize cooperative operation of the village-level micro-grid under Nash equilibrium. According to the method, the deep coupling relation of light-storage-charging-grid-load is considered, efficient utilization of large-scale distributed resources can be achieved, self-consistent operation of the village-level micro-grid in a source-load fluctuation scene is guaranteed, photovoltaic construction of the whole county of the country is facilitated, and the friendly access capability of the micro-grid is greatly improved.

This application provides an integrated planning method and related equipment for smart distribution network infrastructure. The method includes: constructing a co-construction and sharing actor network by treating network operators, grid operators, decision-makers, and power infrastructure as actors; constructing a co-construction and sharing initiative model based on the decision-makers' decisions, and implementing the co-construction and sharing initiative model based on the co-construction and sharing actor network; dividing the smart distribution network and implementing coordinated planning strategies for the power supply layer and power supply zones respectively; and constructing an optimization configuration strategy based on the analysis of resources and information in the smart distribution network to optimize the infrastructure in the smart distribution network. It is evident that this method, based on the co-construction and sharing initiative model of power infrastructure, solves the initiative problem under co-construction and sharing tasks in different scenarios, avoids ignoring the initiative of actors, and reflects the interactive relationship between the communication network and the smart distribution network infrastructure. It is applicable to complex smart distribution network business scenarios.

The invention discloses a shared game benefit allocation method and system for clean energy and carbon resource multistage utilization, and the method provided by the invention forms a cooperative game through the mutual connection of a plurality of IESs through energy sharing and carbon transfer, achieves the mutual benefit and win-win of resource sharing and benefit allocation, and achieves the mutual benefit and win-win of a micro-grid operator. The MGO can supply energy to each IES and form a Stackelberg game, and analysis and verification are carried out by taking a certain industrial park as an example, so that the advancement of the method is shown, the carbon emission of the system can be reduced for the problems of indirect promotion of increasingly prominent low-carbon importance by a market mechanism, multi-stage utilization of carbon resources and the like, and the effects of flexible management of the carbon resources and the like are achieved.

A system for automating matching of energy load with energy generation for energy consumers, utilities, and gird operators, comprising a processor and a memory containing instructions configuring the processor to collect, from a grid network connecting load centers and generation sources, energy datasets including energy attribute records and energy load data, match each load center to the generation sources based on the energy datasets, matching further comprises generating actionable energy models, each one of the actionable energy models representing a configurable allocation of the energy attribute records, based on the energy datasets, and matching the load centers and generation sources as a function of at least one actionable energy model, populate an allocation report for each load center, and transmit the allocation report to an external device in communication with the processor.

The invention discloses a sending-end power system capacity demand evaluation method and system considering frequency safety, and the method comprises the steps: obtaining the basic data of a sending-end power system, and the basic data comprises the multi-type adjustable resource parameters, tie line parameters and source and load prediction data of the sending-end power system; according to the basic data, based on the flexibility resource frequency dynamic response model, constructing a frequency modulation standby model of multiple types of flexibility resources; deriving a system frequency safety index model based on the frequency modulation standby model; establishing a system regulation capacity demand evaluation model according to the system frequency safety index model and the conventional state system supply and demand balance; and solving the system regulation capacity demand evaluation model based on an NSGA-II algorithm to obtain a minimum capacity demand result. According to the method, a power grid operator can be helped to effectively identify multi-type resource capacity requirements and various resource capacity combination schemes of the system under the frequency safety of guaranteeing supply and demand balance and anticipated disturbance in a certain stage in the future.

The embodiment of the invention discloses a layered and distributed optimal scheduling method for a micro-grid system considering psychological factors of a user. On the basis of considering benefit demands of a micro-grid operator and users participating in demand response, a micro-grid double-layer scheduling model based on a master-slave game is constructed, a user side load model serving as a follower model depicts the influence of psychological factors of the users on the demand response, and a user side load model serving as a follower model depicts the influence of the psychological factors of the users on the demand response. The micro-grid operator model as the leader model optimizes the operation of each device and formulates the excitation price of the demand response, so as to achieve the balance of supply and demand and pursue the maximization of benefits. And layered and distributed optimization solution is performed on the microgrid double-layer scheduling model by adopting an alternating direction multiplier method, so that user side participation demand response can be effectively mined, and resources such as wind power, light and the like in the microgrid system can be fully absorbed. Therefore, on the basis of pursuing optimal operation economy of the micro-grid system and giving consideration to the benefits of the user side, multi-party benefit balance in the micro-grid system is realized.

The present invention belongs to the field of power system dispatching, and relates to a multi-microgrid collaborative dispatching method based on master-slave cooperative game and objective cascading analysis. By using the collaborative dispatching problem of power resources and carbon emissions in a multi-microgrid system, a two-layer master-slave cooperative game framework is constructed: the upper-layer grid operator coordinates the power dispatching and operation strategies of the microgrid alliance based on power flow analysis, voltage regulation, and carbon emission control; each microgrid in the lower-layer microgrid alliance realizes power trading and resource sharing through cooperative game; based on the objective cascading analysis algorithm, the Anderson acceleration method is introduced to dynamically adjust the tie-line power, and the augmented Lagrangian penalty function is combined to handle the constraints, optimizing the decoupled iterative process of the upper and lower layers and accelerating the convergence; effectively solving the problem of low efficiency of multi-agent collaborative optimization, ensuring the stability of system power and the reasonable allocation of electric energy resources, and providing technical support for the operation of the multi-microgrid system.

The invention relates to a computer-implemented method and system for optimizing a baseline when electrical power is drawn by devices of a subscriber connected to a grid connection point on a power supply network operated by a network operator, comprising the steps of: receiving an announcement message from the network operator by an energy management system of the subscriber regarding an upcoming load management event, which indicates the extent to which an electrical load by devices of the subscriber is to be reduced or increased during the load management event in a load adjustment;Determining an optimal baseline for the electrical power consumption of a subscriber's devices in a time interval prior to the announced load management event, such that the load adjustment requested in the notification is optimally balanced in advance with respect to a predefined optimization criterion, taking into account specified constraints; controlling the subscriber's devices by the subscriber's energy management system to achieve the determined optimal baseline during the time interval prior to the announced load management event; and adjusting the electrical load at the subscriber's grid connection point by the subscriber's energy management system according to the information in the notification received from the grid operator regarding the required load adjustment by controlling the subscriber's devices.

A communication system (10) according to the invention for improving the grid stability of electricity grid operators (12) comprises at least one electricity grid operator (12), at least one motor vehicle charging point operator (14) and at least one motor vehicle user (18) of a motor vehicle (16) with an electrical energy storage device, which are functionally connected to each other via a communication medium.In the event of an impending or already active critical power grid condition, an active communication option is enabled for the power grid operator (12) to contact the at least one motor vehicle user (18) regarding the active provision of electrical energy, and the at least one motor vehicle charging point operator (14) enables the at least one motor vehicle user (18) to provide electrical energy from the electrical energy storage of his motor vehicle (16) to the power grid operator (12).

The invention relates to a method for determining a flexibility capability for a power grid (2) within a time range by means of an energy system (1) having a plurality of installations (11) which can be operated flexibly with respect to the generation and / or consumption processes carried out by the installations, wherein the energy system (1) comprises a central control device (12), with respect to the installations (11), for controlling the operation of the installations (11). The method is characterized in that current capability values of the installations (11) are detected and transmitted to the control device (12), the flexibility capability that can be provided being determined by the control device (12) by comparing the detected current capability values with reference data relating to a reference operation of the installations (11). The invention also relates to a method for operating an electrical grid by means of a grid operator (3).

Operation of an electric vehicle (EV) is monitored and controlled to enable operation in a vehicle to grid (V2G) configuration. During bidirectional power transfer, energy stored in batteries onboard the electric vehicle can be transferred to the grid. During a period of high energy input into the grid, e.g., energy sourced from wind turbines / solar, the energy can be stored in the onboard batteries. During low energy input, the energy stored in the batteries can be transferred to the grid. V2G operation is conducted in accordance with a grid code(s) implemented at the grid. Grid codes can be forwarded from respective grid operators to a central system (remotely located from the EV), and subsequently forwarded for implementation to the EV. Based on EV location, the central system can control which grid code is forwarded to the EV and also whether the EV can perform V2G operation(s).

The invention discloses a key branch adaptive screening method based on incremental learning in different operation states, and relates to the technical field of power system key branch identification, and the method comprises the steps: constructing a safety boundary preliminary fitting model in different load states through unsupervised clustering historical operation data; fitting corresponding security boundaries according to the state data to generate a security boundary set of the whole network; training an incremental learning model by using historical operation state data and the fitted security boundary, and outputting a plurality of out-of-limit branches; and judging whether the security boundary of the branch is included into the sample pool based on the confidence score. According to the method, the incremental learning and the online key branch identification technology are combined, so that real-time generation and self-adaptive updating of the safety boundary of the power system are realized. The self-adaptive updating mechanism enables the model to be continuously optimized in a complex operation state, accurately identifies key branches which may be out-of-limit, and helps a power grid operator to predict and prevent safety risks in advance, thereby improving the safety, reliability and scheduling efficiency of a power grid.

The invention discloses a micro-grid-multi-EV aggregator mixed game optimization method considering low-carbon economic operation. The method comprises the following steps: constructing a single EV slow charge capacity boundary model considering user travel uncertainty; constructing a carbon transaction model considering a certificate-carbon fusion mechanism; an operation model is optimized based on a mixed game: an optimal energy selling price strategy of a regional user aggregator is determined through a master-slave game, and a micro-grid operator solves an equilibrium solution for minimizing the comprehensive cost of the two parties based on a pricing boundary; and secondly, each aggregator obtains electric energy transaction payment in the alliance through cooperative game solution based on the transaction power determined in the previous stage, allocates interests of each user according to asymmetric Nash negotiations with different user contribution degrees, and finally forms a multi-agent cooperation mechanism giving consideration to market benefits and environmental benefits.

A method for controlling an electricity distribution grid having a nominal grid voltage, in particular in a critical grid situation, wherein a grid control center is provided for controlling the electricity distribution grid and the electricity distribution grid has at least one control region that comprises a plurality of mutually geographically separate wind farms, comprising the steps of: querying power outputs available from the wind farms, in particular on the basis of a weather forecast; defining a control node within the control region, in particular on the basis of the queried available power out-puts, preferably performed by the grid operator; combining a number of wind farms at the calculated control node to form a wind power plant on the basis of the queried available power outputs and / or a probability distribution of the available power output; controlling the wind power plant, in particular through the grid control center, by way of a wind power plant control unit, such that a required voltage quality and / or frequency stability and / or uninterrupted availability is provided in the control region.

This invention discloses a method, apparatus, equipment, and medium for collaborative optimization decision-making involving a fleet of vehicles in demand response. The method involves: receiving V2G demand response event signals from a grid operator, including demand power, response time period, and real-time electricity price; secondly, acquiring in real-time the location, battery state of charge (SoC), and task status of each autonomous electric vehicle in the fleet, as well as the location information of V2G charging stations; then, using a resource-task network (RTN) model to uniformly model vehicle resources, charging station resources, passenger service resources, and grid demand resources, constructing all potential task sequences, and quantifying resource consumption and task benefits; next, with the objective of maximizing the total profit of the fleet, performing optimization solutions under conditions such as battery SoC boundaries, charging station power constraints, and minimum grid response power, generating task sequences, path planning, and charging / discharging plans for each vehicle; finally, distributing the optimization decision results to the fleet for automatic execution.

The application discloses a power supply guarantee type light storage micro-grid operation method, system, equipment and medium based on multi-party game, and comprises the following steps: acquiring network parameters and equipment parameters of the power supply guarantee type light storage micro-grid; constructing a new incentive benefit model and a power supply guarantee subsidy model of the power supply guarantee type light storage micro-grid according to the network parameters and the equipment parameters of the power supply guarantee type light storage micro-grid; constructing a net income model of an investment subject; constructing a light-storage-grid cooperation game model; solving the light-storage-grid cooperation game model through an NSGA-II algorithm to obtain a Nash equilibrium point of the light-storage-grid cooperation game model, and obtaining and outputting an optimal operation strategy. The application considers the cooperation game of a photovoltaic investor, an energy storage investor and a micro-grid operator, realizes the emergency power supply guarantee of the micro-grid by using the photovoltaic and the energy storage, and maximizes the economic benefits of the three subjects.

The invention discloses a hydroelectric generating set all-condition simulation modeling method and system, and relates to the related technical field of hydroelectric generating sets, and the method comprises the steps: fusing multiple characteristics, and building a set first twin model and an all-condition label matrix; a registration error is analyzed through a multi-scale grid operator, and cross-scale reconstruction is carried out to generate a second twinborn model of the unit; performing inversion accident tracing by using the all-condition label matrix to construct a tracing graph network, and performing fault simulation factoring by combining the fault label matrix to establish a factoring graph network; and cooperatively fusing the all-condition inversion tracing graph network and the fidelity abnormal factorial graph network, and optimizing to generate a unit third twinborn model with higher fidelity. The technical problems that in the prior art, a hydroelectric generating set digital twinborn model is insufficient in fidelity, poor in all-working-condition coverage and dynamic inversion capacity and low in fault simulation and abnormal factorization accuracy are solved, and the technical effects that the hydroelectric generating set digital twinborn model with all-working-condition coverage is constructed, and the fidelity, interpretability and cross-scale consistency are improved are achieved.