Abstract: A fully-distributed reactive voltage control method, includes: establishing a power grid reactive voltage optimization model of a power grid; parting the power grid reactive voltage optimization model into a plurality of area reactive voltage optimization models of a plurality of areas of the power grid; converting a power flow equation constraint in each of the plurality of area reactive voltage optimization models to a linear regression model; solving the linear regression model by using a robust recursive regression algorithm to obtain a solution result of the linear regression model; solving each of the plurality of area reactive voltage optimization models by using the solution result of the linear regression model, a gradient projection algorithm, and an alternating direction multiplier algorithm, so as to realize a reactive voltage optimization control of each of the plurality of areas.

Abstract: A data-driven wind farm frequency control method based on dynamic mode decomposition. The method enables a low-dimension nonlinear dynamic feature of a wind power system to perform global capturing in a high-dimension space through a state transition matrix given by a Koopman operator theory, thus fewer data samples are necessary while control requirements are satisfied with respect to a model fitting accuracy. Meanwhile, a pure linear feature of a control model also provides a favorable foundation for fast on-line dynamic response, thereby satisfying response accuracy and speed requirements simultaneously in an actual control step.

Abstract: A method for multi-time scale reactive voltage control based on reinforcement learning in a power distribution network is provided, which relates to the field of power system operation and control. The method includes: constituting an optimization model for multi-time scale reactive voltage control in a power distribution network based on a reactive voltage control object of a slow discrete device and a reactive voltage control object of a fast continuous device in the power distribution network; constructing a hierarchical interaction training framework based on a two-layer Markov decision process based on the model; setting a slow agent for the slow discrete device and setting a fast agent for the fast continuous device; and deciding action values of the controlled devices by each agent based on measurement information inputted, so as to realize the multi-time scale reactive voltage control while the slow agent and the fast agent perform continuous online learning.

Abstract: A method and system for power grid optimization control based on a linear time-varying model is provided. The system model is first estimated offline using historical data combined with a piecewise linear regression method that supports a vector regression model. For online applications, a time-varying linear model prediction control framework based on a piecewise linear model coordinates the optimization control of both fast and slow regulating devices in the power grid. This approach does not require precise system model parameters, instead learning the power grid model from historical data. The method optimizes voltage distribution, reduces operating costs, and addresses issues like bad data and collinearity in the historical data, improving the voltage quality and enabling optimal operation even with incomplete models.

Abstract: A planning method for a power distribution automation system based on a reliability constraint is provided. The method includes: defining installation states of components and principles of a fault isolation, a load transfer and a fault recovery after a branch fault occurs; establishing a reliability evaluation optimization model for a power distribution network based on a mixed integer linear programming, the reliability evaluation optimization model comprising a target function and constraint conditions; solving the reliability evaluation optimization model to obtain an optimum planning scheme; and planning the power distribution automation system based on the optimum planning scheme.

Abstract: The present invention relates to a method of assessing dynamic flexibility for a virtual power plant, which belongs to the technical field of operating and controlling a power system. The method equals a virtual power plant to an equivalent energy storage device and an equivalent generator and decouples a network constraint condition between the two types of devices through a Robust optimization method. Subsequently, by using a two-stage Robust optimization algorithm, parameters of the equivalent energy storage device and the equivalent generator are calculated and finally accurate depiction is realized on adjusting ability of a distributed resource, so as to provide a scientific decision basis for the virtual power plant to participate in grid control, such that it has a great value in an actual application.

Abstract: An online voltage control method for coordinating multi-type reactive power resources is provided. First, a linearized power flow equation of branch reactive power is established, and an online voltage control model of multi-type reactive power resources including an objective function and constraint conditions is constructed. The constraint conditions includes generator reactive power constraints, reactive power compensator constraints, transformer tap position constraints, a nodal reactive power balance constraint, and slack contained nodal voltage constraints. Then, an optimization result of voltage control is obtained by solving the model.

Abstract: The present disclosure provides a method for optimizing transformation of automation equipment in a power distribution network based on reliability, including determining installation states of respective components in the power distribution network and operation criterions for fault isolation, load transfer and fault recovery after a fault occurred in a feeder segment; determining a target function which is a target function for minimizing a total transformation cost of the power distribution network; determining constraint conditions including reliability constraints; establishing an optimization model for evaluating the reliability of the power distribution network based on the reliability constraints in accordance with the target function and the constraints; and solving the established optimization model for evaluating the reliability of the power distribution network based on the reliability constraints to obtain optimal solutions as optimization results of the automation transformation state of the cir

Abstract: A transient stability assessment method for an electric power system is disclosed. Transient stability tags and steady-state data of the electric power system before a failure occurs are collected from transient stability simulation data. Data sets under different predetermined failures are obtained based on a statistical result of the transient stability tags and a maximum-minimum method. A similarity evaluation index between different predetermined failures is constructed based on a Jaccard distance and a Hausdorff distance. Different predetermined failures are clustered based on a clustering algorithm. A parameters-shared siamese neural network is trained for different predetermined failures in each cluster to obtain a multi-task siamese neural network for the transient stability assessment.

Abstract: The disclosure provides power distribution network reliability index calculation method based on mixed integer linear programming. The method includes: establishing a model for optimizing reliability indexes of a power distribution network based on a mixed integer linear programming model, wherein the model comprises an objective function and constraint conditions, the objective function is for minimizing a system average interruption duration index (SAIDI); solving the model based on the objective function and the constraint conditions to obtain reliability indexes of the power distribution network; and controlling operation of the power distribution network based on the reliability indexes.

Abstract: The present disclosure provides a stability criterion for time-delay of cyber-physical power systems under distributed control, which relates to a field of cyber-physical power systems technologies.

Abstract: A method for quantifying and assessing a scheduling risk considering source load fluctuation and rescheduling, and an apparatus for quantifying and assessing a scheduling risk considering source load fluctuation and rescheduling are provided. The method includes establishing a scene set considering a new energy disturbance; establishing and solving a rescheduling optimization model considering the new energy disturbance in each scene based on a preset scheduling plan according to the scene set, so as to obtain a solving result of the rescheduling optimization model; and calculating a risk quantifying and assessing result corresponding to the preset scheduling plan according to the solving result of the rescheduling optimization model.

Abstract: The present disclosure provides a method for planning a distribution network with reliability constraints based on a feeder corridor, including determining installation states of respective elements in the distribution network; determining an objective function, the objective function being an objective function of minimizing a total investment cost of the distribution network; obtaining fault-isolation-and-load-transfer time and fault recovery time in a case where the feeder segment of each feeder line that is contained in each feeder corridor fails; determining constraint conditions including reliability constraints; building a distribution network planning model according to the objective function and the constraints; and solving the distribution network planning model built to obtain optimal solutions as planning states and reliability indexes to plan the distribution network.

Abstract: A reactive power-voltage control method for integrated transmission and distribution networks is provided. The reactive power-voltage control method includes: establishing a reactive power-voltage control model for a power system consisting of a transmission network and a plurality of distribution networks; performing a second order cone relaxation on a non-convex constraint of the plurality of distribution network constraints to obtain the convex-relaxed reactive power-voltage control model; solving the convex-relaxed reactive power-voltage control model to acquire control variables of the transmission network and control variables of each distribution network; and controlling the transmission network based on the control variables of the transmission network and controlling each distribution network based on the control variables of the distribution network, so as to realize coordinated control of the power system.

Abstract: A method for dispatching a power grid is disclosed. The method includes: obtaining a whole power generation interval scheduled for a cluster of renewable energy stations from a power grid dispatching center; establishing a decomposition model that includes an objection function and constraint conditions; decomposing the whole power generation interval with the decomposition model to obtain each power generation interval of each renewable energy station; and controlling each renewable energy station to generate powers based on each power generation interval. The objection function minimizes a total operating cost in the power grid and includes a renewable energy randomness indicating an actual power generation amount of each renewable energy station.

Abstract: A fully-distributed reactive voltage control method, includes: establishing a power grid reactive voltage optimization model of a power grid; parting the power grid reactive voltage optimization model into a plurality of area reactive voltage optimization models of a plurality of areas of the power grid; converting a power flow equation constraint in each of the plurality of area reactive voltage optimization models to a linear regression model; solving the linear regression model by using a robust recursive regression algorithm to obtain a solution result of the linear regression model; solving each of the plurality of area reactive voltage optimization models by using the solution result of the linear regression model, a gradient projection algorithm, and an alternating direction multiplier algorithm, so as to realize a reactive voltage optimization control of each of the plurality of areas.

Abstract: A power grid reactive voltage control model training method. The method comprises: establishing a power grid simulation model; establishing a reactive voltage optimization model, according to a power grid reactive voltage control target; building interactive training environment based on Adversarial Markov Decision Process, in combination with the power grid simulation model and the reactive voltage optimization model; training the power grid reactive voltage control model through a joint adversarial training algorithm; and transferring the trained power grid reactive voltage control model to an online system. The power grid reactive voltage control model trained by using the method according to the present disclosure has transferability as compared with the traditional method, and may be directly used for online power grid reactive voltage control.

Abstract: The disclosure relates to a two-side stochastic dispatching method for a power grid. By analyzing historical data of wind power, the Gaussian mixture distribution is fitted by software. For certain power system parameters, a two-side chance-constrained stochastic dispatching model is established. The hyperbolic tangent function is used to analyze and approximate cumulative distribution functions of random variables in the reserve demand constraint and the power flow constraint, to convert the two-side chance constraint into a deterministic constraint. The disclosure can have the advantage of using the hyperbolic tangent function to convert the two-side chance constraint containing risk levels and random variables into the solvable deterministic convex constraint, effectively improving the solution efficiency of the model, and providing decision makers with a more reasonable dispatching basis.

Abstract: The disclosure provides a method for calculating a parameter changing domain of loads under a case that guarantees a constant locational marginal price in an electricity market, which relates to the electricity market field of the power system. With the method in the disclosure, the clearing model on the locational marginal price in the general form is established, and the safe changing domain of the locational marginal price with respect to the loads may be derived and calculated based on the first-order KKT condition expansion of the clearing model on the locational marginal price in the general form. When the increment of the nodal loads is subordinate to the changing domain, the locational marginal price may remain unchanged. The parameter changing domain of loads in the power system may be used for the comprehensive evaluation of power market clearing results and assisting the operation of the power market.

Abstract: A heat supply network hydraulic circuit modeling method for a comprehensive energy system scheduling is provided. The hydraulic analysis model is unified with the power network model, and the connection between the hydraulic dynamic state and the hydraulic steady state is established. Based on the characteristic equations of thermal pipelines, flow control valves and compressors, this method abstracts hydraulic circuit element models such as hydraulic resistance, hydraulic inductance, and hydraulic pressure source, establishes hydraulic branch characteristics of the heat supply network based on the above hydraulic circuit elements, establishes the hydraulic topology constraints of the heat supply network based on Kirchhoff-like voltage and current laws, and establishes the steady hydraulic network equation by combining the above hydraulic branch characteristics and hydraulic topology constraints.