63 results about "Piecewise linearization" patented technology

The invention relates to the technical field of sensors, and discloses a temperature compensation method based on a silicon resonance pressure sensor. According to the method, real-time temperature drift data is collected through a sliding time window, and a temperature sensitive area and a temperature non-sensitive area are accurately identified; establishing a coupling model of zero drift and full scale drift in the temperature sensitive area; then, piecewise linearization processing is conducted on the coupling model through a dynamic weight distribution strategy, and high-precision temperature compensation parameters are generated; and finally, according to the environment temperature value detected in real time, automatically calling the temperature compensation parameter of the corresponding segment, and carrying out real-time dynamic correction on the original output value of the sensor. According to the method, through region identification and model coupling of temperature drift characteristics, fine division and adaptive matching of a compensation strategy are realized, and the measurement precision and long-term stability of the silicon resonance pressure sensor in a wide temperature range are improved.

The invention discloses an offshore wind power plant micro-siting optimization method considering regular layout. The method comprises the following steps: firstly, obtaining wind data, wind power plant parameters, fan parameters and wake flow parameters; performing multi-angle rotation on the wind power plant based on an equivalent rotation coordinate method, constructing a gridding mixed integer quadratic programming model, and performing rotation rule layout optimization (RRLO-1) to obtain an initial fan layout; on the basis of the initial layout, a hybrid algorithm (GA-ISSA) of a genetic algorithm and a sparrow search algorithm is adopted, the position of a draught fan and the rotation angle of the wind power plant are finely adjusted, and fine rule layout optimization (RRLO-2) is completed; and finally, the wake flow influence is calculated through a Cosine wake flow model and a quadratic sum superposition model, a fan power curve is processed in a piecewise linearization mode, and the final layout is output by taking the maximization of the total generating capacity as the target. According to the method, a fan position configuration scheme meeting the engineering rule layout requirement is provided for early-stage planning of the offshore wind plant, the wake effect is reduced, the power generation efficiency is improved, and development of the offshore wind power industry and low-carbon target implementation are facilitated.

The invention relates to the technical field of power system automation, in particular to a climbing-frequency modulation coordinated optimization method and system considering energy storage capacity uncertainty, and the method comprises the steps: building an opportunity constraint model of an energy storage system based on the capacity uncertainty, and enabling the opportunity constraint model to be used for describing a reliable feasible region under the deviation of energy storage electric quantity; establishing an energy storage system linearization model considering a climbing-frequency modulation power unified constraint, and realizing power coupling and sharing constraint description of two types of adjustment services; aiming at the nonlinear characteristic of the gradeability of the thermal power generating unit, establishing a piecewise linearization model of the gradeability by adopting a piecewise linearization method; and establishing a thermal power-energy storage combined climbing-frequency modulation coordinated optimization model, and solving the optimization model by adopting a quadratic programming method to obtain the climbing power and frequency modulation reserve capacity of the thermal power generating unit and energy storage. According to the method, the actual available range of the energy storage system capacity can be dynamically reflected, the electric quantity out-of-limit risk caused by the uncertainty of the energy storage capacity is avoided, and the reliability of the scheduling result is improved.

The ELM-based frequency safety constraint linearization optimization scheduling method comprises the following steps: establishing a fire-wind-light multi-energy complementary frequency dynamic response model, and deducing a time domain analytical expression of a frequency safety index by taking a frequency maximum change rate and a frequency maximum deviation as the frequency safety index of a system; considering a frequency lowest point security constraint and a frequency maximum change rate security constraint, and establishing a frequency security constraint-containing optimization scheduling model; a maximum bearable disturbance power linearization mapping method based on ELM is provided, nonlinear frequency security constraints are converted into a series of linear constraint sets, and linearization processing of the frequency security constraints is achieved; and piecewise linearization is carried out on quadratic terms in the established objective function containing the frequency security constraint optimization scheduling model, the overall model is converted into a mixed integer linear model, and a Gurobi solver is used to solve the linearly processed model. The scheduling method can ensure that the system frequency is safe and stable, so that the established optimal scheduling model gives consideration to both economy and frequency safety.

The invention discloses a virtual power plant source load interaction optimization scheduling model based on low-carbon response and a solving algorithm, and belongs to the technical field of power system optimization scheduling. A low-carbon scheduling framework containing a distributed power supply, energy storage, a flexible load and a carbon transaction mechanism is constructed, the carbon emission intensity of each link is quantified to form a carbon flow scheduling signal, and a dynamic carbon emission factor and energy cost are coupled. A multi-objective optimization model is established, a complex function is processed by piecewise linearization, and a hybrid algorithm of an improved genetic algorithm and a commercial solver is designed to improve the solving efficiency. The prediction error is dynamically corrected through a'prediction-optimization-feedback 'closed loop, and the strategy is adjusted. According to the scheme, low-carbon and economic collaborative optimization is realized, renewable energy consumption and system stability are enhanced, user satisfaction and real-time scheduling are considered, and a solution is provided for low-carbon intelligent operation of the power distribution network.

The invention discloses an offshore wind power plant regular layout optimization method considering submarine topography and turbulence intensity, and the method comprises the steps: carrying out the grid discretization of a target region, and defining a layout rotation angle; a mixed integer linear fractional programming model with the minimum leveling cost per kilowatt-hour as the target is constructed, a wake flow model based on an axisymmetric cosine function and a turbulence model based on an axisymmetric double-Gaussian function are comprehensively integrated, and piecewise linearization is conducted on a turbulence nonlinear term; the method comprises the following steps: pre-defining a layout mode and regular layout constraints, and matching with engineering constraints such as fan number, power and safety distance; and a bounded Dinkelbach algorithm is adopted to carry out iterative solution on the sub-problems decomposed according to angles, and a global optimal layout is obtained. According to the method, wake flow loss, turbulence fatigue and terrain-related cost can be effectively and synergistically optimized, and an economical and efficient layout scheme is provided for offshore wind plant planning.

A lateral–vertical dynamics coordinated control method for a distributed drive electric vehicle, and a related device. The lateral–vertical dynamics coordinated control method for a distributed drive electric vehicle comprises the following steps: creating a fourteen-degree-of-freedom full vehicle model which considers unbalanced magnetic force in an in-wheel motor, so as to accurately represent a state response of a vehicle under different inputs; a three-dimensional piecewise affine tire model performing piecewise linearization of a lateral force of a tire under different side slip angles and vertical loads, so that nonlinear features of the tire can be described under extreme operating conditions; creating an active front-wheel steering controller on the basis of hybrid model predictive control, obtaining a reference center of mass side slip angle and a yaw rate by means of a bicycle model, and then calculating an additional steering angle of the vehicle, thereby ensuring vehicle stability; and designing a multi-constraint input and multi-constraint output active suspension controller based on dual-model predictive control by using roll stability and ride comfort, that is, a tire dynamic load, a vehicle body acceleration, and an in-wheel motor stator-rotor eccentricity, as suspension design control targets.

This invention relates to an optimization method for an electric-gas coupled system based on adaptive piecewise linearization. This invention considers the coordinated operation of the power system and the natural gas system, and can improve the overall efficiency of the energy system through multi-energy complementarity, promote the absorption of new energy sources, and simultaneously improve the safe and reliable supply of electricity and natural gas. In the calculation process, the number of segments in the linearized pipeline airflow equation obtained through piecewise linearization is adaptively determined. Specifically, the number of segments and segmentation points are dynamically divided using an iterative method, gradually increasing the number of segments and segmentation points. This approach, while ensuring computational accuracy, introduces the minimum number of segmentation intervals and determines the optimal segmentation point location. This transforms the optimal energy flow calculation of the electric-gas coupled system into a mixed-integer linear programming model, achieving an effective trade-off between solution accuracy and computational efficiency. Ultimately, it provides a feasible and efficient technical means for the optimal energy flow analysis of electric-gas coupled systems.

The present application relates to the technical field of bus charging, in particular to a bus fast charging station orderly charging method based on a data-driven energy efficiency model; first, the power demand meeting the operation of a bus line is determined, and then a relationship between charging energy conversion efficiency and the actual charging power of a vehicle-mounted energy storage system is established; taking the minimum actual power consumption of the charging station in a day or the minimum actual electricity cost of the charging station in a day as an objective function, wherein the charging energy conversion efficiency is considered, a nonlinear optimization objective function model is established with the power demand of the electric bus line operation, the continuity of the electric bus charging time as constraint conditions, then the nonlinear optimization objective function model is converted into a mixed integer convex programming problem using piecewise linearization, and the optimal charging plan is obtained by solving the mixed integer convex programming problem; the present scheme can further improve the energy conversion efficiency of charging on the basis of traditional orderly charging, reduce the power consumption cost of the charging station operator and the charging cost of the electric bus, and improve the economy.

A voltage sag management optimization configuration method considering differentiated economic losses of sensitive users, comprising: constructing a parameterized voltage tolerance boundary function; establishing an economic loss model of sensitive users under a single fault event, which continuously changes from a lossless area, a quality loss area to a complete interruption area; constructing a residual voltage recovery model after management under the synergistic action of a static synchronous compensator (STATCOM) and a dynamic voltage restorer (DVR); constructing a collaborative optimization configuration model of management equipment, taking the sum of the investment cost of management equipment, the annual operation and maintenance cost and the annual comprehensive economic loss after management as the target; performing piecewise linearization processing on the voltage sag economic loss function and the equipment cost function, converting the collaborative optimization configuration model of management equipment into a mixed integer linear programming model, and then obtaining the optimal installation node and configuration capacity of the management equipment. The method can better match the protection needs of different sensitive users and effectively reduce the comprehensive economic loss caused by voltage sag in the distribution network.

The invention discloses a voltage control target adaptive generation method and system for high-proportion new energy power, and relates to the technical field of new energy voltage regulation and control, and the method comprises the steps: dividing operation modes based on a multi-dimensional operation characteristic database of a new energy station; introducing a piecewise linearization function to convert the ideal voltage control range; calculating and issuing a reactive power control reference quantity of the new energy station; and analyzing the reactive power control reference quantity limit. According to the method, typical working conditions such as a photovoltaic duck curve are accurately sensed, the precision, response speed and robustness of high-proportion new energy power grid voltage control are improved, the prominent problems of midday voltage rise, sudden drop at dusk and the like are inhibited, waste of adjustment resources and voltage out-of-limit risks are avoided, and the method is suitable for large-scale popularization and application. The method improves the new energy consumption capability and the power grid operation safety, and has a good application prospect and popularization value.

The application provides a bus fast-charging station orderly charging method considering battery dynamic charging loss, comprising: determining the power demand meeting bus line operation according to the operation time of the charging station, equipment power limit, quantity limit and bus departure plan; establishing a battery heat loss model and the relationship between charging energy conversion efficiency and the actual charging power of the vehicle-mounted energy storage system based on a first-order RC circuit model; taking the minimum actual power consumption of the charging station in a day or the minimum actual electricity cost of the charging station in a day as an objective function, wherein the battery heat loss is considered, and an optimization model is established with the charging station operation time, charging pile number, charging pile maximum power, power distribution capacity, electric bus travel power demand, electric bus charging time continuity as constraint conditions; using piecewise linearization to convert the nonlinear optimization objective function model into a mixed integer convex programming problem, and solving the mixed integer convex programming problem to obtain the optimal charging plan, including the optimal charging time and corresponding charging power of each vehicle. The method improves the charging energy conversion efficiency, reduces the battery heat loss and prolongs the service life of the battery, reduces the charging cost of the bus while improving the charging energy conversion efficiency, and improves the economy.

The invention belongs to the technical field of post-disaster power distribution network power supply recovery, and particularly relates to a post-disaster power distribution network power supply recovery method based on satellite communication vehicle scheduling. Comprising the steps that a satellite communication vehicle is scheduled to move in a power distribution network area, communication gears are switched according to load requirements, and first-class loads and second-class loads are activated through the communication coverage area of the satellite communication vehicle; constructing a day-ahead scheduling model with the minimum daily operation cost of the post-disaster power distribution network as a target; processing nonlinear constraints by adopting an adaptive piecewise linearization method so as to solve the day-ahead scheduling model; and controlling a moving path, gear switching and a load activation strategy of the satellite communication vehicle according to a solving result of the day-ahead scheduling model. The load is flexibly activated through the satellite communication vehicle, and the system toughness is improved; by distinguishing load types and optimizing communication resource utilization, the total operation cost of the system is reduced, and the post-disaster power supply recovery efficiency is improved.

The application provides an IES scheduling method, system and medium, the method comprising: modeling electrochemical processes and thermal processes of cell units and SOFC auxiliary equipment in the SOFC respectively, and simultaneously obtaining a SOFC nonlinear output characteristic model to represent the relationship between the output electric power, thermal power and working state of the SOFC; based on the degradation effect of the SOFC under different working states, establishing a SOFC nonlinear degradation cost model to count the asset loss caused by the degradation process into the cost; constructing an ETC model according to the SOFC nonlinear output characteristic model and the SOFC nonlinear degradation cost model, and describing the operation and degradation effect of the SOFC; further, adopting a piecewise linearization method to linearize the ETC model, so as to facilitate the solution of the IES optimization scheduling problem. The application facilitates the scheduling personnel of the IES to formulate a safe and economic SOFC operation strategy.

This invention relates to the field of power system automation technology, and particularly to a method and system for coordinated optimization of ramp-frequency regulation considering the uncertainty of energy storage capacity. The method includes: establishing an opportunity constraint model of the energy storage system based on capacity uncertainty to describe the reliable feasible region under energy storage power deviation; establishing a linearized model of the energy storage system considering unified power constraints for ramp-frequency regulation, realizing the power coupling and shared constraint description of the two types of regulation services; establishing a piecewise linearization model of ramp capacity using a piecewise linearization method to address the nonlinear characteristics of the ramp capacity of thermal power units; establishing a joint ramp-frequency regulation coordination optimization model of thermal power and energy storage, and solving the optimization model using a quadratic programming method to obtain the ramp power and frequency regulation reserve capacity of the thermal power units and energy storage. This invention can dynamically reflect the actual available range of the energy storage system capacity, avoid the risk of power exceeding limits due to energy storage capacity uncertainty, and improve the reliability of dispatch results.

The application belongs to the technical field of power systems, and relates to a carbon emission flow constraint linearization method for low-carbon scheduling of power systems. The method comprises the following steps: establishing a power carbon emission flow model based on power flow direction decomposition to obtain power flow direction constraints and node carbon flow balance constraints for coupling carbon flow calculation; introducing auxiliary state variables and processing the power flow direction constraints by using a large M method; constructing a carbon flow balance equation simplification model based on piecewise linearization and a large M relaxation method; based on the power flow direction constraint and node carbon flow balance constraint linearization method, establishing a low-carbon economic scheduling model of the power system coupled with carbon flow calculation, and converting the model into a linear optimization problem for solving. The application converts the original nonlinear problem into a linear optimization programming problem, improves the solving universality of the low-carbon economic scheduling method of the power system containing carbon flow calculation, can guarantee good carbon accounting accuracy, and significantly improves the model solving efficiency.

The invention discloses a multi-objective mixed integer programming layout optimization method based on intelligent orthogonal constraint, and relates to the technical field of component layout optimization, comprising: establishing a multi-objective layout optimization model based on mixed integer linear programming; decomposing the multi-objective layout optimization model into two single-objective optimization models, and respectively solving the two single-objective optimization models by using a mixed integer programming algorithm; solving results of the two single-target optimization models are processed by using an intelligent orthogonal constraint method, and an intelligent Pareto solution set corresponding to the multi-target layout optimization model is obtained; wherein when the multi-target layout optimization model is established, a finite rectangle method is adopted to decompose a non-rectangular component into a plurality of orthogonal rectangular components, and for a square term in rotational inertia, a piecewise linearization technology is adopted to carry out approximate processing on the square term. According to the method, the multi-target layout optimization problem can be embedded into the mixed integer linear programming framework, and the component layout optimization solving efficiency and the engineering practicability are greatly improved.

The invention discloses an optical storage direct-flexible system long-period adaptive optimization regulation and control method considering source load uncertainty, and the method comprises the steps: designing an optimization scheduling objective function of an optical storage direct-flexible system, and minimizing the total operation cost of the system in a total optimization time scale on the premise of guaranteeing the safe operation of the optical storage direct-flexible system; a system power balance constraint, a power transmission line capacity limitation constraint and a reserve capacity requirement constraint are comprehensively considered, and a day-ahead unit regulation and control strategy with the aim of minimizing the total operation cost of the system is solved based on an external approximation method and a piecewise linearization method; a Markov decision process is constructed by considering the source load uncertainty and the overall optimization regulation and control efficiency under the long-period time scale; and taking the day-ahead unit regulation and control strategy as an initial unit regulation and control strategy under a long-period scale, and realizing self-adaptive adjustment of the long-period unit regulation and control strategy of the optical storage direct-flexible system by adopting a near-end strategy optimization algorithm. According to the method, the adaptive strategy optimization of the controllable unit under the long-period source load uncertainty can be realized.

This invention discloses a modular simulation method for a direct-drive variable-speed pumped-storage unit, belonging to the field of hydropower storage technology. A piecewise linearized control block diagram for the direct-drive pumped-storage unit is established. The pump-turbine in the pumped-storage unit operates under two modes: power generation and motoring. Since the simulation analysis methods for power generation and motoring are largely similar, only the power generation mode is used as an example to establish the control block diagram. The value ranges of the PI regulation parameters for the power closed-loop and power multi-state modules are solved. After obtaining the value ranges, the Bode plot analysis method is used to design the power closed-loop regulation parameters. Simulation analysis under the power generation mode is performed based on the designed parameters to verify the effectiveness of the piecewise linear simulation method. The simulation method of this invention combines the simplicity of traditional fixed-parameter PID regulation with the adaptability of novel PID regulation to multiple operating modes in the new energy power grid, effectively suppressing fluctuations in the new energy power grid.

The embodiment of the application discloses a method for determining the exit time of frequency modulation of a fan, which comprises the following steps: establishing a system model comprising a hydroelectric generator model, a wind turbine model and a frequency response model based on a state space method; obtaining a piecewise linearization model based on a preset transformation and rewriting method; determining system frequency expressions of a frequency modulation stage and a speed recovery stage according to the piecewise linearization model, and determining the lowest frequency values corresponding to the two stages and the time corresponding to the lowest frequency values according to the two system frequency expressions; establishing an optimization model based on the time range of the system frequency modulation stage with the second lowest frequency value corresponding to the second frequency drop as the target; and determining the optimal exit time according to the optimization model. By establishing the system model and the optimization model, the optimal exit time of the fan frequency modulation is determined, so that the influence on the normal operation of the system can be reduced when the fan exits the frequency modulation at the optimal exit time, and the safe operation of the system is facilitated.

This invention relates to the field of electrical testing technology, specifically to a method and system for detecting anomalies in electricity meters. The method includes: activating a wideband programmable power source to apply a composite excitation signal to the electricity meter under test; acquiring electrical parameters such as discrete current and voltage sequences to generate a heterogeneous operating condition dataset; generating a physical field correction tensor through a thermomagnetic dynamic correction model, performing physical field mapping operations on the discrete current and voltage sequences to generate an environmental hysteresis loop trajectory; receiving the environmental hysteresis loop trajectory, performing piecewise linearization analysis to generate a core depth saturation distortion index; and projecting the core depth saturation distortion index onto a metering error tolerance evaluation interval to generate a magnetic saturation metering anomaly signal. This invention, by constructing a strong coupling mechanism between environment, physics, and geometry, ensures that the anomaly judgment logic no longer relies solely on electrical thresholds, resulting in more accurate judgments of minor metering deviations induced by environmental factors.

The present application relates to the technical field of comprehensive energy system application, in particular to a wind-solar-thermal-pumped distributed robust optimization scheduling method considering variable working condition characteristics of pumped storage units. In view of the problems that system power balance is difficult under high proportion of new energy access, and traditional model is difficult to accurately solve the non-convex nonlinear characteristics of pumped storage units, the present application firstly generates typical scenarios and initial probability based on clustering; the core lies in introducing a model linearization processing strategy, processing the water level-storage capacity curve by piecewise linearization, and using McCormick envelope method to convex relaxation the head-flow-power coupling characteristics of the unit, and constructing a mixed integer linear distributed robust optimization model based on comprehensive norm fuzzy set. On this basis, by using column and constraint generation algorithm for solving, the optimal balance of system operation cost minimization and scheduling robustness is realized while coping with source and load uncertainty.

This invention discloses a multi-objective mixed-integer programming layout optimization method based on intelligent orthogonal constraints, relating to the field of component layout optimization technology. The method includes: establishing a multi-objective layout optimization model based on mixed-integer linear programming; decomposing the multi-objective layout optimization model into two single-objective optimization models, and solving the two single-objective optimization models using mixed-integer programming algorithms respectively; processing the solution results of the two single-objective optimization models using an intelligent orthogonal constraint method to obtain the intelligent Pareto solution set corresponding to the multi-objective layout optimization model; wherein, when establishing the multi-objective layout optimization model, the finite rectangle method is used to decompose non-rectangular components into multiple orthogonal rectangular components, and for the square term in the moment of inertia, a piecewise linearization technique is used to approximate the square term. This invention can embed the multi-objective layout optimization problem into a mixed-integer linear programming framework, significantly improving the solution efficiency and engineering practicality of component layout optimization.

The invention discloses a new energy port-oriented hydrogen production-hydrogen storage-power generation integrated modeling and cooperative operation method, which comprises the following steps of: analyzing a dynamic coupling relationship between electrolytic voltage and current density, and establishing a nonlinear electrolytic cell hydrogen production model reflecting a correlation mechanism among input power, hydrogen production rate and energy efficiency; piecewise linearization processing is carried out on the hydrogen production model to obtain a multi-stage hydrogen production model, and hydrogen production characteristics and start-stop characteristics are integrated to establish a complete electric hydrogen production unit operation model, hydrogen storage energy is utilized to replace part of electrochemical storage energy, electric energy is stored through electric hydrogen production in an energy consumption surplus period, and power is generated through a fuel cell in an energy consumption shortage period. According to the scheme, peak clipping and valley filling of the port power load can be achieved by building a hydrogen energy long-time storage mechanism, dynamic fluctuation of the load is effectively dealt with, the energy consumption cost is reduced, the overall energy utilization efficiency of the port is improved, and technical support is provided for port decarburization.

The invention discloses a new energy power system monthly unit combination method considering a short-time extreme weather event, and the method comprises the steps: firstly, employing a multi-parameter screening method combining first-order difference and scene description based on historical meteorological data and corresponding new energy output power fluctuation characteristics; identifying and extracting a short-time extreme weather event set and a corresponding new energy output set; then, constructing a dual-time scale constraint of a monthly unit combination; and finally, based on the constructed dual-time scale constraint, combining a short-time extreme weather event set, utilizing a power generation cost function as a total objective function, obtaining an optimization problem by adopting a two-stage random optimization framework, simplifying the optimization problem by adopting a piecewise linearization thought and a sample estimation mathematical expectation, and then solving the optimization problem. And obtaining a new energy power system monthly unit combination strategy considering the short-time extreme weather event.

The invention discloses an offshore wind turbine generator yaw control optimization method based on a physical information neural network, and the method comprises the steps: generating a series of power output data at different yaw angles based on an FLORIS simulation model, and constructing a data set; taking the data set as a training set, training a proxy network between the yaw angle and power output based on DNN, and obtaining a yaw angle-power proxy network model; establishing an optimization problem of yaw control through a yaw angle-power proxy network model; based on ReLU piecewise linearization, MILP reconstruction is carried out on the optimization problem of yaw control; and the optimization problem after MILP reconstruction is solved through a linear optimization solver, and a global optimal wind turbine generator yaw angle combination is obtained. Through combination of the agent model and the optimization algorithm, the optimal yaw angle combination can be rapidly calculated under different wind speed and wind direction conditions, and real-time optimization of wind power plant yaw control is realized.

The invention discloses an accurate control method and system for an overhead working truck based on a proportional valve, and the method comprises the steps: inputting a preset control parameter in a control device, and operating the control device to output an initial current signal; collecting current signals in real time, converting the current signals into digital signals, and transmitting the digital signals to the ARM processor; sequentially performing filtering, piecewise linearization processing and PID dynamic compensation adjustment on the converted digital signal to generate a high-precision current instruction; based on the high-precision current instruction, a control signal is calculated and generated by combining a preset segmentation mapping relation between current and the opening degree of the proportional valve and is output to the driving module; the driving module analyzes the signal duty ratio, converts the signal duty ratio into driving current matched with a proportional valve coil, and inputs the driving current into the proportional valve coil to accurately adjust the opening and closing degree of the proportional valve; the proportional valve controls the high-altitude operation vehicle to move accurately, and meanwhile, the monitoring and protecting module automatically locks the proportional valve when monitoring abnormity, and opening and closing degree adjustment is stopped. Accurate control over the overhead working truck is achieved, and operation stability, accuracy and safety are improved.

The invention discloses an independent energy storage power station spot market bidding decision optimization method fusing an electrochemical mechanism, and relates to the field of energy storage, and the method comprises the steps: firstly building a battery first-order equivalent circuit model to represent the internal physical characteristics of an energy storage battery, and building a system-level energy storage power station model based on the model; when a bidding decision optimization model is constructed, the benefit maximization is taken as a target, current constraints including charge and discharge state mutual exclusion and upper and lower limits of current are comprehensively considered, SOC constraints including upper and lower limits of safe operation are set, and through voltage constraints for performing piecewise linearization processing on a nonlinear relation between open-circuit voltage and SOC, a bidding decision optimization model is constructed. Performing linearization processing on the current and voltage product term and setting power constraints of upper and lower limits of power output; and finally, solving the constructed decision optimization model to generate an optimal bidding strategy. According to the method, the internal mechanism and the physical characteristics of the electrochemical battery are comprehensively considered, the nonlinear dynamic characteristics of the electrochemical battery are converted into linear constraints to be embedded into the optimization model, and accurate description and economical efficiency improvement of the operation characteristics of the energy storage system are achieved.

A wind turbine gearbox anomaly detection method considering the similarity of multi-unit operating states, based on the piecewise linear time series similarity evaluation method, evaluates a single state variable; considering the similarity of multiple state variables, the wind turbine operating state spatiotemporal similarity quantification method evaluates the similarity of each wind turbine and the operating state of the unit to be detected; a state estimation LSTM model is constructed, different LSTM models are trained; the accuracy and adaptability of different LSTM model performances are verified; select several LSTM models that perform well in performance verification, construct a combined state estimation model CPEM through weighted combination; estimate the target variable of the unit to be detected, calculate the residual error between the estimated value and the true value, and based on the residual effective value comparison and residual information entropy comparison, identify the anomaly. This method detects the operating state of the gearbox based on the historical operating data of the wind turbine, without the need for maintenance personnel to conduct on-site detection, reducing the operating and maintenance costs of the wind turbine.

The invention discloses an opportunity constraint economic dispatching method considering wind curtailment and load curtailment. The opportunity constraint economic dispatching method comprises the steps of obtaining a total operation cost function of an economic dispatching model under high permeability of new energy; reducing the standby demand of economic dispatching of the system through a wind curtailment and load curtailment plan, wherein the wind curtailment and load curtailment plan comprises setting a planned output upper limit of a wind power plant and a load curtailment upper limit of a load aggregate; performing linearization processing on the opportunity constraint through a conditional risk value CVaR, a risk value VaR and a piecewise linearization method; setting the standby constraint as an opportunity constraint, enabling standby scheduling to meet a constraint requirement with a preset confidence coefficient, and allowing a standby insufficiency condition with a preset probability; an energy storage unit is integrated, the wind curtailment amount is reduced through charging and discharging operation, the standby requirement is relieved, and peak load shifting is achieved. According to the invention, through an innovative opportunity constraint economic dispatching model, the wind and load abandoning phenomenon is significantly reduced, and the risk of insufficient reserve is effectively relieved.