A grid-connected optimal operation method and system for a wind-solar power consumption grid

Abstract

The application relates to the technical field of power system dispatching optimization, in particular to a grid-connection optimization operation method and system for a wind-solar power consumption power grid, which comprises the following steps: calculating a margin index to quantify the adjustment pressure based on the residual quota and time of monthly energy abandonment and load loss; determining an adjustment tendency coefficient by comparing the difference between the energy abandonment margin and the load loss margin, so as to quantify the output tendency adjustment amount of water, pumped storage and energy storage; setting an adaptive penalty coefficient according to the margin tension degree, constructing a target function with the minimum deviation from the balanced tendency as the target, and supplementing with power balance and other constraints; and generating an output dispatching plan through optimization solving. The application solves the problem of monthly energy abandonment and load loss imbalance caused by traditional dispatching, realizes the dynamic balance of wind-solar power consumption and power supply guarantee, and improves the stability and economy of the wind-solar power consumption power grid operation.

Description

Technical Field

[0001] This application relates to the field of power system dispatch optimization technology, specifically to a grid-connected optimization operation method and system for a wind-solar integrated power grid. Background Technology

[0002] The wind-solar integrated power grid, a new type of power system with wind and solar power as its main power sources, relies on flexible adjustment resources such as cascade hydropower stations, pumped storage power stations, and electrochemical energy storage stations to achieve power balance. Its ultimate goal is to efficiently transmit new energy power into the main grid. The so-called optimized grid-connected operation, in essence, means scientifically scheduling the output timing of various power sources and energy storage devices under the conditions of grid dispatch instructions and the physical capacity limitations of transmission channels. This maximizes the utilization of wind and solar resources while ensuring a stable and reliable power supply to the load.

[0003] Existing methods, when determining the output allocation of each regulating device, only focus on the power balance demand of the current period, lacking a comprehensive consideration of the monthly distribution balance of curtailment and load shedding levels throughout the annual operating cycle. This short-sighted decision-making mechanism leads to the problem that wind and solar resources exhibit significant seasonal imbalances: abundant sunshine in summer and relatively scarce sunshine in winter, abundant wind resources in spring and autumn and often weak winds in midsummer. Traditional dispatching methods fail to incorporate monthly balance targets into the daily dispatching decision-making framework, resulting in concentrated curtailment events during months rich in wind and solar resources, and frequent load shedding events during months with scarce wind and solar resources, reducing the stability and economic efficiency of the grid operation for wind and solar power integration. Summary of the Invention

[0004] To address the aforementioned technical problems, the purpose of this application is to provide a method and system for optimized grid connection operation of wind and solar power grids. The specific technical solution adopted is as follows: In a first aspect, embodiments of this application provide a method for optimizing the grid connection of a wind-solar integrated power grid, the method comprising the following steps: Based on the difference between the total energy curtailment before the current time period in the current cycle and the preset target energy curtailment limit in the current cycle, the difference between the total load shedding and the preset target load shedding limit in the current cycle, and the number of the current time period and the remaining time period after the current cycle in the wind and solar power grid, the energy curtailment margin and load shedding margin of the current time period are determined respectively. Based on the difference between the current load shedding margin and the curtailment margin, the adjustment tendency coefficient for the current period is determined; the difference between the installed capacity of hydropower stations, the upper limit of the power generation of pumped storage power stations and the upper limit of the pumping power in the wind-solar grid, and the rated power of electrochemical energy storage stations are obtained, and combined with the adjustment tendency coefficient, the power output tendency adjustment of hydropower stations, the power output tendency adjustment of pumped storage power stations and the power output tendency adjustment of electrochemical energy storage stations are determined in the current period. The current energy curtailment margin and load shedding margin are compared to determine the penalty coefficient for the current period. The differences between the baseline output of hydropower stations, pumped storage stations, and electrochemical energy storage stations in each sub-segment of the current period and the actual output of hydropower stations, pumped storage stations, and electrochemical energy storage stations in the current period are calculated. Combined with the output tendency adjustment of hydropower stations, pumped storage stations, and electrochemical energy storage stations, as well as the penalty coefficient, the objective function is determined. The objective function is solved to obtain the grid-connected power output scheduling plan for the current period.

[0005] Preferably, the method for determining the energy curtailment margin and load shedding margin for the current time period is as follows: The result of calculating the total number of time periods included in the current period divided by the total number of the current time period and the remaining time periods after the current period is recorded as the time ratio. The minimum value among the preset time factors is recorded as the time correction factor. The product of the normalized value of the difference between the total energy curtailment before the current time period in the current cycle and the preset target energy curtailment limit in the current cycle and the time correction factor, and the product of the difference between the total load shedding before the current time period in the current cycle and the preset target load shedding limit in the current cycle and the time correction factor, are respectively denoted as energy curtailment margin and load shedding margin.

[0006] Preferably, the adjustment tendency coefficient for the current time period is the normalized value of the difference between the load shedding margin and the energy curtailment margin for the current time period.

[0007] Preferably, determining the output tendency adjustment of hydropower stations, pumped storage power stations, and electrochemical energy storage stations within the current time period includes: Current period hydropower station output tendency adjustment The expression for the output tendency adjustment of pumped storage power stations The expression for the output tendency adjustment vector of the electrochemical energy storage station The expressions are as follows: , , In the formula, This represents the propensity to adjust in the current period. Indicates the installed capacity of the hydropower station; , These represent the upper limit of the power generation capacity of the pumped storage power station and the upper limit of the water power capacity of the pumped storage power station, respectively. This indicates the rated power of the electrochemical energy storage station.

[0008] Preferably, the expression for the penalty coefficient of the current time period is: In the formula, This represents the penalty coefficient for the current time period; This indicates the preset baseline penalty coefficient; , represents the current energy curtailment margin and load shedding margin, respectively; min() represents the minimum value function; exp[] represents the exponential function with the natural constant as the base.

[0009] Preferably, determining the objective function includes: Objective function for the current time period The expression is: In the formula, This represents the penalty coefficient for the current time period; This represents the propensity to adjust in the current period. , , Let N represent the baseline output, actual output, and output tendency adjustment of the d-th type of resource regulation station under segment t in the current time period, respectively. The actual output is an unknown variable to be solved. N represents all types of resource regulation stations, including hydropower stations, pumped storage stations, and electrochemical energy storage stations. M represents the number of all segments in the current time period. sign() represents the sign function. max[] represents the maximum value function.

[0010] Preferably, solving the objective function to obtain the grid-connected power output scheduling plan for the current time period includes: Power balance constraints and energy storage state of charge constraints are set separately. Based on the constraints, the objective function is solved by a sequential quadratic programming algorithm to obtain the actual output of hydropower stations, pumped storage stations and electrochemical energy storage stations in each sub-segment under the current time period.

[0011] Preferably, the power balance constraint condition is that the sum of the actual output of the hydropower station, pumped storage station and electrochemical energy storage station in each sub-segment during the current time period is equal to the obtained difference value of the grid-connected power output in the corresponding sub-segment.

[0012] Preferably, the state of charge (SOC) constraint condition for energy storage is that the SOC value of each sub-segment in the next adjacent sub-segment within the current time period is equal to the SOC value of each sub-segment minus the SOC change of the electrochemical energy storage station within a preset period.

[0013] Secondly, embodiments of this application also provide a grid-connected optimization operation system for a wind-solar integrated power grid, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps of any of the above-described methods for the grid-connected optimization operation of a wind-solar integrated power grid.

[0014] This application has at least the following beneficial effects: This application decomposes the macro-level equilibrium objective into daily executable, refined dispatch instructions. It not only quantifies the current slack in remaining energy curtailment and load shedding quotas in real time, but also ensures the forward-looking and fair nature of decision-making by introducing a time correction factor. This effectively guides a dynamic trade-off between wind and solar power consumption and power supply security, fundamentally solving the problem of severe monthly imbalances in energy curtailment and load shedding caused by short-sighted decisions in traditional dispatching. This helps improve the long-term operational stability and economy of the wind and solar power grid. Furthermore, this application constructs a regulation tendency coefficient mapped in the [-1,1] interval by comparing energy curtailment and load shedding margins, intuitively indicating whether current dispatching should prioritize consumption or power supply reliability. Subsequently, this regulation tendency coefficient is combined with the regulation capabilities of each device (such as hydropower station installed capacity, pumped storage total regulation range, and energy storage rated power) and multiplied by a 10% limiting factor to generate specific output tendency adjustment amounts. This decomposes the equilibrium objective into quantitative, mild, and differentiated control instructions for different types of resources such as water, pumped storage, and energy storage, providing guidance for subsequent optimization solutions. Finally, this application quantifies the urgency of the current equilibrium constraint through an adaptive penalty coefficient, ensuring strong correction when margins are tight. Furthermore, an objective function is designed to calculate the cost of any scheduling scheme that deviates from the preset equilibrium tendency, and the physical feasibility of the scheme is ensured through hard constraints such as power balance and energy storage status. The model is solved using mature optimization algorithms, thereby automatically generating an output scheduling scheme that satisfies the current power balance while ensuring the safe operation of the power grid, thus improving the stability and economy of the wind and solar power grid. Attached Figure Description

[0015] To more clearly illustrate the technical solutions and advantages in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 A flowchart illustrating the steps of a grid-connected optimization operation method for a wind-solar integrated power grid, as provided in one embodiment of this application; Figure 2This is a schematic diagram of the output tendency adjustment extraction process provided in one embodiment of this application. Detailed Implementation

[0017] To further illustrate the technical means and effects adopted by this application to achieve the intended purpose of the invention, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a wind-solar integrated power grid optimization operation method and system proposed in this application. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains.

[0019] The following, in conjunction with the accompanying drawings, details the specific scheme of the grid-connected optimization operation method and system for wind and solar power grid integration provided in this application.

[0020] Please see Figure 1 The diagram illustrates a flowchart of a grid-connected optimization operation method for wind and solar power grid integration, according to an embodiment of this application. The method includes the following steps: Step S1: Based on the remaining quota of current energy curtailment and load shedding, determine the adjustment tendency, and calculate the adjustment amount of hydropower station output tendency, pumped storage power station output tendency, and electrochemical energy storage station output tendency.

[0021] The core problem with traditional dispatching methods lies in their passive response and locally optimal decision-making logic, which fails to foresee the long-term impact of current decisions on the future. Specifically, in months with extremely abundant wind and solar resources, the power grid will continuously and massively utilize its flexibility resources to absorb the energy until it reaches its physical or economic limits, thereby rapidly consuming the entire month's curtailment quota. This forces the grid to abandon any additional wind and solar power output in subsequent periods. Conversely, in months with scarce resources, the power grid will excessively consume its regulation margin to fill the power gap, making the power supply at the end of the month extremely vulnerable. This makes the grid highly susceptible to chain-reaction load events caused by forecasting errors or sudden faults, ultimately resulting in a severe imbalance in the distribution of curtailment and load loss over time.

[0022] Therefore, to solve the above problems, this embodiment determines the adjustment tendency based on the remaining quota of current energy curtailment and load shedding, and calculates the adjustment amount of power output tendency for hydropower stations, pumped storage power stations, and electrochemical energy storage stations accordingly. The specific process is as follows: S1.1: Based on the difference between the total curtailed energy before the current time period in the current cycle and the preset target curtailed energy limit in the current cycle, the difference between the total load shedding and the preset target load shedding limit in the current cycle, and the number of the current time period and the remaining time period after the current cycle, the curtailment margin and load shedding margin of the current time period are determined respectively.

[0023] In this embodiment, the result of calculating the total number of time periods included in the current period divided by the total number of the current time period and the remaining time periods after the current period is recorded as the time ratio. The minimum value of the time ratio and the preset time factors is recorded as the time correction factor. The product of the normalized value of the difference between the total energy curtailment before the current time period in the current cycle and the preset target energy curtailment limit in the current cycle and the time correction factor, and the product of the difference between the total load shedding before the current time period in the current cycle and the preset target load shedding limit in the current cycle and the time correction factor, are respectively denoted as energy curtailment margin and load shedding margin.

[0024] To avoid a surge in the time correction factor value, potentially approaching infinity, due to a small denominator at the end of the current cycle (when the remaining time period is small), thus affecting system stability, this embodiment presets the time factor value to 10. Taking the cycle length in this embodiment as an example, the cycle length is 1 month. On the last day, there is only 1 day remaining, so the denominator is 1. Assuming the numerator is 30, the scheduling pressure will be 30 times. However, even if there is only one day left, the scheduling pressure should not be 30 times. 10 times the pressure is sufficient to represent an extreme emergency state. Therefore, the upper limit of the time correction factor is set to 10.

[0025] It should be noted that in this embodiment, the length of one cycle is one month, one period is one day, and one day is divided into 96 segments, each segment being 15 minutes long. The reason for setting each segment to 15 minutes is firstly because the output of wind and solar power, especially photovoltaic power, changes very drastically during critical periods such as sunrise and sunset. A resolution of 15 minutes is sufficient to capture these rapid changes, thereby making more accurate responses and avoiding energy curtailment or load shedding due to scheduling delays. Secondly, the trading cycle of the electricity market and the issuance cycle of grid dispatch instructions are usually also in 15-minute units. Using the same resolution facilitates seamless integration with the market and upper-level dispatch. Finally, for resources such as electrochemical energy storage with response speeds measured in seconds, a 15-minute timescale can fully leverage their rapid adjustment advantages while avoiding the problem of excessively complex models and a surge in computational load due to an excessively short timescale. It is a good balance between accuracy and computational efficiency.

[0026] It should be noted that in this embodiment, the result of subtracting the total energy curtailment before the current time period in the current period from the upper limit of the preset target energy curtailment in the current period is used as the difference between the total energy curtailment before the current time period in the current period and the upper limit of the preset target energy curtailment in the current period. The difference between the load shedding is the same, which is the difference value.

[0027] It should be noted that there are many commonly used normalization methods. In this embodiment, the difference between the total energy curtailment before the current time period in the current cycle and the preset upper limit of energy curtailment in the current cycle is divided by the preset target energy curtailment, and the result is used as the normalized value of the difference. The normalization of the difference between the load shedding is carried out using the same normalization method as the energy curtailment. In actual application, as other implementation methods, implementers may also use other normalization methods such as the maximum and minimum value normalization method according to the specific situation. This embodiment does not impose any special restrictions on the selection of normalization methods.

[0028] The method for obtaining the preset target energy curtailment is as follows: obtain the target power output curve issued by the power grid dispatch center, with the horizontal axis representing the curve and the vertical axis representing the power value that the wind and solar power grid should transmit to the main grid at each time point, i.e., the power output dispatch amount, in MW; in this embodiment, obtain the total power value that the wind and solar power grid should transmit to the main grid in the current time period, i.e., the total power output dispatch amount, and use 1% of the total power output dispatch amount as the preset target energy curtailment limit for the current time period, and use 0.5% of the total power output dispatch amount as the preset target load shedding limit for the current time period.

[0029] Based on the concepts of curtailment margin and load shedding margin, we can understand that curtailment margin characterizes the sufficiency of the remaining curtailment quota for the current period. It reflects the buffer space allowed for wind and solar power curtailment in subsequent scheduling, and its value directly influences whether scheduling decisions favor absorption or conservative control. The calculation logic for curtailment margin is as follows: first, calculate the difference between the monthly target curtailment ceiling and the amount of curtailed electricity (i.e., the remaining quota); then normalize it; finally, multiply it by a time correction factor that averages the remaining quota over the remaining days. Curtailment margin is mainly influenced by the remaining curtailment... The curtailment margin is influenced by two factors: quota and remaining days. When the remaining curtailment quota is larger relative to the total upper limit, meaning fewer curtailments have occurred and more remaining days, the curtailment margin is larger. This indicates that the curtailment pressure this month is small, and wind and solar power can be absorbed boldly, even allowing a small amount of curtailment to be exchanged for other benefits. Conversely, when the remaining curtailment quota is small or even negative, meaning that curtailment has occurred close to or exceeded the monthly target and there are very few remaining days, the curtailment margin is smaller or even negative. This indicates that the curtailment pressure this month is huge, and measures must be taken to reduce new curtailment, even if some economic benefits may be sacrificed.

[0030] Load shedding margin characterizes the safe margin of load shedding allowed in the current cycle at the current time point. It reflects the amount of safety margin available to handle power shortages in subsequent dispatching, and its value directly determines the level of assurance for power supply reliability. The calculation logic of load shedding margin is completely consistent with that of curtailment margin: First, calculate the difference between the monthly target load shedding limit and the amount of load shedding that has occurred (i.e., the remaining load shedding quota), then normalize it, and then multiply it by the time correction factor. Its calculation is mainly affected by two factors: the remaining load shedding quota and the number of remaining days. When the remaining load shedding quota is larger relative to the total limit, that is, the fewer load sheddings have occurred and the more remaining days, the larger the load shedding margin is. This indicates that the pressure on power supply reliability this month is very small, and the reserve capacity can be appropriately reduced to prioritize wind and solar power consumption. Conversely, when the remaining load shedding quota is very small or even negative, that is, the load shedding that has occurred is close to or exceeds the monthly target and the number of remaining days is very small, the load shedding margin is smaller or even negative. This indicates that the power supply reliability this month faces severe challenges, and sufficient adjustment margin must be maintained to prioritize power supply.

[0031] Thus, this embodiment decomposes the macro-level equilibrium objective into daily executable fine-grained scheduling instructions. It not only quantifies the current sufficiency of remaining energy curtailment and load shedding quotas in real time, but also ensures the foresight and fairness of decision-making by introducing a time correction factor. This effectively guides a dynamic trade-off between wind and solar power consumption and power supply security, fundamentally solving the problem of severe imbalance between energy curtailment and load shedding caused by short-sighted decisions in traditional scheduling. This helps improve the long-term operational stability and economy of the wind and solar power grid.

[0032] S1.2: Based on the difference between the current period's load shedding margin and energy curtailment margin, determine the adjustment tendency coefficient for the current period; obtain the difference between the installed capacity of hydropower stations, the upper limit of pumped storage power generation and the upper limit of pumping power in the wind-solar grid, and the rated power of electrochemical energy storage stations, and combine them with the adjustment tendency coefficient to determine the adjustment amount of hydropower station output tendency, pumped storage power station output tendency, and electrochemical energy storage station output tendency in the current period.

[0033] First, based on the difference between the current period's load shedding margin and energy curtailment margin, the adjustment tendency coefficient for the current period is determined, specifically: In this embodiment, the normalized value of the difference between the load shedding margin and the energy curtailment margin in the current period is used as the adjustment tendency coefficient for the current period. In this embodiment, the result of dividing the difference between the load shedding margin and the energy curtailment margin in the current period by the sum of the load shedding margin and the energy curtailment margin is used as the normalized value of the difference between the load shedding margin and the energy curtailment margin in the current period. Finally, the normalized result is mapped to the range of [-1, 1].

[0034] Based on the adjustment tendency coefficient, it can be understood that the adjustment tendency coefficient is used to characterize the trade-off and tilt between the two objectives of reducing energy curtailment and reducing load shedding during the current scheduling cycle. The adjustment tendency coefficient reflects the focus of the current cycle equilibrium contradiction, and its positive or negative sign directly guides the direction of subsequent optimization solutions. The calculation logic of the adjustment tendency coefficient is as follows: the difference between the load shedding margin and the energy curtailment margin is normalized, so that the result is mapped to the interval [-1,1]. It is mainly affected by the relative magnitude of the load shedding margin and the energy curtailment margin. When the load shedding margin is much larger than the energy curtailment margin, the adjustment tendency coefficient will be affected. When the energy margin is high, i.e., the adjustment tendency coefficient is greater than 0, the pressure of energy curtailment is greater. When the adjustment tendency coefficient approaches +1, it indicates that there should be a strong inclination to reduce energy curtailment, i.e., encouraging more charging and less generating to absorb excess wind and solar power. When the energy curtailment margin is much greater than the load shedding margin, i.e., the adjustment tendency coefficient is less than 0, the pressure of load shedding is greater. When the adjustment tendency coefficient approaches -1, it indicates that there should be a strong inclination to reduce load shedding, i.e., encouraging more generating and less charging to preserve regulation capacity. When the two are close, the adjustment tendency coefficient approaches 0, indicating that no special tilt is needed and conventional scheduling strategies can be used.

[0035] Furthermore, the difference between the installed capacity of hydropower stations, the upper limit of pumped storage power generation, and the upper limit of pumping power in the wind-solar grid, as well as the rated power of electrochemical energy storage stations, are obtained. Combined with the aforementioned adjustment tendency coefficient, the adjustment amounts for the output tendency of hydropower stations, pumped storage power stations, and electrochemical energy storage stations are determined for the current time period. Specifically: Current period hydropower station output tendency adjustment The expression for the output tendency adjustment of pumped storage power stations The expression for the output tendency adjustment vector of the electrochemical energy storage station The expressions are as follows: , , In the formula, The current period represents the propensity to adjust coefficient, which is dimensionless. This indicates the installed capacity of the hydropower station (unit: MW). , These represent the upper limit of the power generation capacity of the pumped storage power station and the upper limit of the hydropower capacity of the pumped storage power station, respectively (unit: MW). This indicates the rated power of the electrochemical energy storage station (unit: MW).

[0036] Preferably, the schematic diagram of the output tendency adjustment amount extraction process provided in this embodiment is as follows: Figure 2 As shown.

[0037] It should be noted that when calculating the output tendency adjustment, each expression is multiplied by 0.1. The core purpose is to transform the macro-level monthly equilibrium pressure into a gradual and controllable micro-level adjustment instruction. This 0.1 (i.e., 10%) is an empirical adjustment range limit factor. It ensures that no matter how large the monthly equilibrium pressure, i.e., the adjustment tendency coefficient, is, the adjustment range of any single dispatch for the output plan of any regulating device will not exceed 10% of its own regulating capacity. The benefits of doing so are: on the one hand, it avoids drastic fluctuations in the system's operating status due to excessively large daily adjustment ranges, which may trigger new instability risks or cause severe conflicts with the daily economic targets; on the other hand, it prevents excessively small adjustment ranges, which would make it impossible to effectively correct the cumulative monthly deviation within the remaining days. Therefore, the value of 10% is a balance achieved between "correction effectiveness" and "operational stability".

[0038] Based on the current adjustment amounts for hydropower station output tendency, pumped storage power station output tendency, and electrochemical energy storage power station output tendency, it can be understood that the hydropower station output tendency adjustment is used to characterize the additional or reduced power generation required by the hydropower station in response to the monthly balance target within the current dispatch cycle, on top of the regular dispatch. It reflects the micro-control instructions of the macro-balance target on the specific regulating device of the hydropower station. Its magnitude and sign directly change the hydropower station's output plan. Its calculation logic is: after taking the negative sign of the adjustment tendency coefficient, it is multiplied by the water... The adjustment range is 10% of the installed capacity of the power station. Its calculation is mainly affected by the adjustment tendency coefficient and the installed capacity of the hydropower station. When the adjustment tendency coefficient is positive, the adjustment amount of the hydropower station's output tendency to reduce curtailment is negative, which means that the hydropower station needs to reduce its output to make way for wind and solar power. Moreover, the larger the installed capacity, the greater the absolute power reduction value. Conversely, when the adjustment tendency coefficient is negative, the hydropower station's installed capacity tendency to reduce load shedding is positive, which means that the hydropower station needs to increase its output to undertake the task of ensuring power supply. Moreover, the larger the installed capacity, the greater the absolute power increase value. The output tendency adjustment of pumped storage power stations is used to characterize the additional power value that a pumped storage power station needs to adjust on top of the regular dispatch within the current dispatch cycle in response to the monthly balance target. It reflects the micro-level control instructions from the macro-balance target to this two-way regulating device. Its sign determines whether the power station tends to pump water or generate electricity. The calculation logic is as follows: after taking the negative sign of the tendency coefficient, multiply it by its total regulation range, i.e., 10% of the difference between the upper limit of power generation and the upper limit of pumping water, as the adjustment magnitude. Its calculation is mainly affected by the tendency coefficient and the total regulation capacity of the pumped storage power station. When the tendency coefficient is positive, indicating a tendency to reduce energy curtailment, the output tendency adjustment of the pumped storage power station is negative, meaning the pumped storage power station should enhance its pumping operation to absorb excess wind and solar power. The stronger the regulation capacity of the power station, the greater the absolute power value that needs to be adjusted. Conversely, when the tendency coefficient is negative, indicating a tendency to reduce load shedding, the output tendency adjustment of the pumped storage power station is positive, indicating that the pumped storage power station should enhance its power generation operation to supplement the power gap. The stronger the regulation capacity of the power station, the greater the supporting power it can provide. The output tendency adjustment of electrochemical energy storage stations is used to characterize the additional charging and discharging power that electrochemical energy storage stations need to adjust on top of regular dispatch within the current dispatch cycle in response to the monthly balance target. It reflects the micro-level control instructions of the macro-balance target on energy storage, a fast-response resource. Its sign determines whether the energy storage tends to charge or discharge. The calculation logic is as follows: after taking the negative sign of the adjustment tendency coefficient, it is multiplied by 10% of its rated power as the adjustment range. Its calculation is mainly affected by the adjustment tendency coefficient and the rated power of the energy storage station. When the adjustment tendency coefficient is positive, indicating a tendency to reduce energy curtailment, the output tendency adjustment of the electrochemical energy storage station is negative, indicating that the energy storage station should increase charging power as a flexible supplement to wind and solar power absorption. Moreover, the larger the rated power of the energy storage station, the greater the absolute power value that needs to be adjusted. Conversely, when the adjustment tendency coefficient is negative, indicating a tendency to reduce load shedding, the output tendency adjustment of the electrochemical energy storage station is positive, indicating that the energy storage station should increase discharging power to provide emergency support to the grid. Moreover, the larger the rated power of the energy storage station, the greater the support power it can provide.

[0039] Thus, this embodiment constructs a regulation tendency coefficient mapped in the [-1,1] interval by comparing energy curtailment and load shedding margins, intuitively indicating whether the current dispatch should prioritize ensuring energy absorption or power supply reliability. Subsequently, this regulation tendency coefficient is combined with the regulation capabilities of each device (such as the installed capacity of hydropower stations, the total regulation range of pumped storage, and the rated power of energy storage), and multiplied by a 10% limiting factor to generate specific output tendency adjustment amounts. The equilibrium objective is decomposed into quantitative, mild, and differentiated control instructions for different types of resources such as water, pumped storage, and energy storage, providing guidance for subsequent optimization solutions.

[0040] Step S2: Compare the current energy curtailment margin with the load shedding margin to determine the penalty coefficient for the current period; separately calculate the differences between the baseline output of hydropower stations, pumped storage stations, and electrochemical energy storage stations in each sub-segment of the current period and the actual output of hydropower stations, pumped storage stations, and electrochemical energy storage stations in the current period, and combine the adjustment amount of the output tendency of hydropower stations, the adjustment amount of the output tendency of pumped storage stations, the adjustment amount of the output tendency of electrochemical energy storage stations, and the penalty coefficient to determine the objective function, and solve the objective function to obtain the grid-connected power dispatch plan for the current period.

[0041] Under the premise of ensuring power balance and meeting various operational constraints, a power output scheduling plan that takes into account the balance objective is generated. This embodiment determines the penalty coefficient for the current time period by comparing the curtailment margin and load shedding margin. It then statistically analyzes the differences between the baseline output of hydropower stations, pumped storage stations, and electrochemical energy storage stations in each sub-segment of the current time period and their actual outputs, and combines these differences with the current time period's actual output. Finally, it determines the objective function by combining the hydropower station output tendency adjustment, the pumped storage station output tendency adjustment, the electrochemical energy storage station output tendency adjustment, and the penalty coefficient. Solving the objective function yields the grid-connected power output scheduling plan for the current time period. The specific process is as follows: First, by comparing the current energy curtailment margin with the load shedding margin, the penalty coefficient for the current period is determined. Specifically: As one implementation method, in this embodiment, the penalty coefficient for the current time period... The expression is: In the formula, This indicates the preset baseline penalty coefficient; , represents the current energy curtailment margin and load shedding margin, respectively; min() represents the minimum value function; exp[] represents the exponential function with the natural constant as the base.

[0042] It should be noted that the preset benchmark penalty coefficient is set manually; in this embodiment, the preset benchmark penalty coefficient is set to... In practical applications, as other implementation methods, implementers may also set their own methods according to specific circumstances, and this embodiment does not impose any special restrictions.

[0043] The penalty coefficient, as understood from the diagram, characterizes the severity of the penalty imposed by the optimization model on deviations from the equilibrium objective. It reflects the urgency of the current cyclical equilibrium constraint, and its magnitude directly determines whether the optimization algorithm prioritizes economy or equilibrium during the solution process. The calculation logic for the penalty coefficient is as follows: based on a baseline penalty coefficient, multiplied by a factor... The relevant exponential function is primarily affected by the smaller of the energy curtailment margin and the load shedding margin. When When the value of is large, meaning both the energy curtailment margin and the load shedding margin are very generous, the exponential term approaches 0, and the penalty coefficient is very small. This indicates that the optimization model is allowed to prioritize economic efficiency, and the penalty for deviations from the equilibrium objective is very light; conversely, when , When the value of is very small or even negative, that is, when at least one indicator is already very stressed, the exponential term increases rapidly and the penalty coefficient becomes large, which indicates that the forced optimization model must prioritize satisfying the equilibrium objective.

[0044] Furthermore, the differences between the benchmark output of hydropower stations, pumped storage power stations, and electrochemical energy storage stations in each sub-segment during the current time period and the actual output of hydropower stations, pumped storage power stations, and electrochemical energy storage stations during the current time period are statistically analyzed. These differences are then combined with the adjustment amounts for the output tendency of hydropower stations, pumped storage power stations, and electrochemical energy storage stations, as well as the penalty coefficient, to determine the objective function. Specifically: In this embodiment, the objective function for the current time period The expression is: In the formula, This represents the penalty coefficient for the current time period; This represents the propensity to adjust in the current period. , , Let N represent the baseline output, actual output, and output tendency adjustment of the d-th type of resource regulation station under segment t in the current time period, respectively. The actual output is an unknown variable to be solved. N represents all types of resource regulation stations, including hydropower stations, pumped storage stations, and electrochemical energy storage stations. M represents the number of all segments in the current time period. sign() represents the sign function. max[] represents the maximum value function.

[0045] Based on the objective function, it can be understood that the objective function is used to quantitatively evaluate the extent to which a scheduling scheme deviates from the preset equilibrium adjustment tendency. It reflects the distance between the scheduling plan and the macro-equilibrium target, and the goal of optimization is to minimize this distance. The calculation logic is as follows: iterates through all time periods and all regulating devices throughout the day. When the actual output of a device deviates from the ideal direction indicated by the tendency adjustment, a deviation value is generated. This deviation value is then summed by a weighted sum of squares to obtain the total penalty value. Its calculation is mainly affected by the penalty coefficient μ, the adjustment tendency coefficient, the actual output, and the baseline output. When the penalty coefficient is larger, or the actual output deviates more from the ideal direction, the objective function value is larger, indicating that the scheduling scheme is less satisfied with the equilibrium requirement. Conversely, when the penalty coefficient is smaller, or the actual output closely follows the ideal direction, the objective function value is smaller, indicating that the scheduling scheme is more in line with the equilibrium target. The optimization algorithm finds the solution that minimizes the objective function through adjustments.

[0046] Furthermore, power balance constraints and energy storage state of charge constraints are set separately. Based on the constraints, the objective function is solved using the sequential quadratic programming (SQP) algorithm to obtain the actual output of the hydropower station, pumped storage station and electrochemical energy storage station in each sub-segment under the current time period. The process of solving the objective function using the sequential quadratic programming (SQP) algorithm is a well-known technique and will not be described in detail here.

[0047] The power balance constraint is that the sum of the actual outputs of the hydropower station, pumped storage station, and electrochemical energy storage station in each sub-segment during the current time period is equal to the obtained difference in grid-connected power output for the corresponding sub-segment. The energy storage state of charge constraint is that the SOC value of the next adjacent sub-segment in the current time period is equal to the SOC value of each sub-segment minus the SOC change of the electrochemical energy storage station within a preset period. To facilitate a clearer understanding of the constraints, the specific expression is given below: The equation for the power balance constraint is: In the formula, , , These represent the actual power output of the hydropower station, the actual power output of the pumped storage power station, and the actual power output of the electrochemical energy storage station in segment t during the current time period; This indicates the difference in grid-connected power output under segment t within the current time period.

[0048] The method for obtaining the grid-connected power transmission difference value is as follows: Obtain the wind power output prediction curve output by the wind power prediction system and the photovoltaic power prediction curve output by the photovoltaic power prediction system. The horizontal axis of the wind power output prediction curve is time (in minutes), and the vertical axis is the predicted wind power output value (in MW). The horizontal axis of the photovoltaic power output prediction curve is time (in minutes), and the vertical axis is the predicted photovoltaic output value (in MW). Based on the target power transmission curve obtained above, the total power dispatch amount under each sub-segment in the current time period is obtained by subtracting the total predicted wind power output value and the predicted photovoltaic output value under each sub-segment in turn. This result is used as the grid-connected power transmission difference value under each sub-segment in the current time period, in MW.

[0049] The equation for the energy storage state of charge constraint is: In the formula, , These represent the SOC values ​​for sub-segment t+1 and sub-segment t within the current time period, respectively. This indicates that the electrochemical energy storage station is in the pre-set period. The change in SOC within the period, where, This indicates the actual output of the electrochemical energy storage station under segment t within the current time period; This indicates the rated capacity of the electrochemical energy storage station, expressed in MWh.

[0050] It should be noted that when t=0, the SOC value is set to 50%, which means that the energy storage is in a "half-charged" state. It has both upward adjustment space (discharging to cope with load shedding) and downward adjustment space (charging to cope with energy curtailment), which can respond to the positive and negative changes of "output tendency adjustment amount" in subsequent dispatch instructions to the greatest extent, and has the greatest flexibility.

[0051] It should be noted that the preset period The value is set manually; in this embodiment, the preset period is... The value is set to 0.25h. Setting the length of the preset period Δt to 0.25 hours, or 15 minutes, is to maintain consistency with the time resolution of the entire scheduling model and ensure accurate matching of the model in terms of time and energy, in the energy storage state of charge constraint. This represents the charging and discharging power within the current 15-minute segment. Therefore, it must be multiplied by the same time length of 0.25h to accurately calculate the amount of electricity flowing through the energy storage within these 15 minutes, and thus accurately update the SOC value. If Δt takes other values, it will lead to an error in the conversion relationship between power and electricity, causing the evolution trajectory of SOC to be distorted, ultimately resulting in infeasible or inaccurate optimization results. Therefore, setting 0.25h is a necessary requirement to ensure that the entire optimization model is mathematically consistent and physically correct.

[0052] Thus, this embodiment quantifies the urgency of the current equilibrium constraint through an adaptive penalty coefficient, ensuring strong correction when margins are tight. Furthermore, an objective function is designed to calculate the cost of any scheduling scheme that deviates from the preset equilibrium tendency, and the physical feasibility of the scheme is ensured through hard constraints such as power balance and energy storage status. Finally, the model is solved using a mature optimization algorithm, thereby automatically generating an output scheduling scheme that satisfies the current power balance while ensuring the safe operation of the power grid, thus improving the stability and economy of the wind and solar power grid.

[0053] Based on the same inventive concept as the above method, this application embodiment also provides a grid-connected optimization operation system for wind and solar power grids, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps of any one of the above-described methods for grid-connected optimization operation of wind and solar power grids.

[0054] It should be noted that the order of the embodiments described above is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, specific embodiments of this specification have been described above. Additionally, the processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some implementations, multitasking and parallel processing are possible or may be advantageous.

[0055] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

[0056] The above description is only a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the principles of this application should be included within the protection scope of this application.

Claims

1. A method for optimizing the operation of a wind-solar integrated power grid, characterized in that, The method includes the following steps: Based on the difference between the total energy curtailment before the current time period in the current cycle and the preset target energy curtailment limit in the current cycle, the difference between the total load shedding and the preset target load shedding limit in the current cycle, and the number of the current time period and the remaining time period after the current cycle in the wind and solar power grid, the energy curtailment margin and load shedding margin of the current time period are determined respectively. Based on the difference between the current load shedding margin and the curtailment margin, the adjustment tendency coefficient for the current period is determined; the difference between the installed capacity of hydropower stations, the upper limit of the power generation of pumped storage power stations and the upper limit of the pumping power in the wind-solar grid, and the rated power of electrochemical energy storage stations are obtained, and combined with the adjustment tendency coefficient, the power output tendency adjustment of hydropower stations, the power output tendency adjustment of pumped storage power stations and the power output tendency adjustment of electrochemical energy storage stations are determined in the current period. The current energy curtailment margin and load shedding margin are compared to determine the penalty coefficient for the current period. The differences between the baseline output of hydropower stations, pumped storage stations, and electrochemical energy storage stations in each sub-segment of the current period and the actual output of hydropower stations, pumped storage stations, and electrochemical energy storage stations in the current period are calculated. Combined with the output tendency adjustment of hydropower stations, pumped storage stations, and electrochemical energy storage stations, as well as the penalty coefficient, the objective function is determined. The objective function is solved to obtain the grid-connected power output scheduling plan for the current period.

2. The grid-connected optimized operation method for a wind-solar integrated power grid as described in claim 1, characterized in that, The method for determining the current period's energy curtailment margin and load shedding margin is as follows: The result of calculating the total number of time periods included in the current period divided by the total number of the current time period and the remaining time periods after the current period is recorded as the time ratio. The minimum value among the preset time factors is recorded as the time correction factor. The product of the normalized value of the difference between the total energy curtailment before the current time period in the current cycle and the preset target energy curtailment limit in the current cycle and the time correction factor, and the product of the difference between the total load shedding before the current time period in the current cycle and the preset target load shedding limit in the current cycle and the time correction factor, are respectively denoted as energy curtailment margin and load shedding margin.

3. The grid-connected optimized operation method for a wind-solar integrated power grid as described in claim 1, characterized in that, The adjustment tendency coefficient for the current period is the normalized value of the difference between the load shedding margin and the energy curtailment margin for the current period.

4. The grid-connected optimized operation method for a wind-solar integrated power grid as described in claim 1, characterized in that, The determination of the output tendency adjustment of hydropower stations, pumped storage power stations, and electrochemical energy storage stations within the current time period includes: Current period hydropower station output tendency adjustment The expression for the output tendency adjustment of pumped storage power stations The expression for the output tendency adjustment vector of the electrochemical energy storage station The expressions are as follows: , , In the formula, This represents the propensity to adjust in the current period. Indicates the installed capacity of the hydropower station; , These represent the upper limit of the power generation capacity of the pumped storage power station and the upper limit of the water power capacity of the pumped storage power station, respectively. This indicates the rated power of the electrochemical energy storage station.

5. The grid-connected optimized operation method for a wind-solar integrated power grid as described in claim 1, characterized in that, The expression for the penalty coefficient for the current time period is: In the formula, This represents the penalty coefficient for the current time period; This indicates the preset baseline penalty coefficient; , represents the current energy curtailment margin and load shedding margin, respectively; min() represents the minimum value function; exp[] represents the exponential function with the natural constant as the base.

6. The grid-connected optimized operation method for a wind-solar integrated power grid as described in claim 1, characterized in that, The determination of the objective function includes: Objective function for the current time period The expression is: In the formula, This represents the penalty coefficient for the current time period; This represents the propensity to adjust in the current period. , , Let N represent the baseline output, actual output, and output tendency adjustment of the d-th type of resource regulation station under segment t in the current time period, respectively. The actual output is an unknown variable to be solved. N represents all types of resource regulation stations, including hydropower stations, pumped storage stations, and electrochemical energy storage stations. M represents the number of all segments in the current time period. sign() represents the sign function. max[] represents the maximum value function.

7. The grid-connected optimized operation method for a wind-solar integrated power grid as described in claim 1, characterized in that, Solving the objective function to obtain the grid-connected power output scheduling plan for the current time period includes: Power balance constraints and energy storage state of charge constraints are set separately. Based on the constraints, the objective function is solved by a sequential quadratic programming algorithm to obtain the actual output of hydropower stations, pumped storage stations and electrochemical energy storage stations in each sub-segment under the current time period.

8. The grid-connected optimized operation method for a wind-solar integrated power grid as described in claim 7, characterized in that, The power balance constraint condition is that the sum of the actual output of the hydropower station, pumped storage station and electrochemical energy storage station in each sub-segment during the current time period is equal to the obtained difference in grid-connected power output in the corresponding sub-segment.

9. The grid-connected optimized operation method for a wind-solar integrated power grid as described in claim 7, characterized in that, The state of charge (SOC) constraint for energy storage is that the SOC value of each sub-segment in the current time period is equal to the SOC value of each sub-segment minus the SOC change of the electrochemical energy storage station within a preset period.

10. A grid-connected optimized operation system for wind and solar power grid integration, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the grid-connected optimized operation method for a wind-solar integrated power grid as described in any one of claims 1-9.

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