A medium- and long-term scheduling method and system for multi-energy complementarity based on short-term fluctuation risk control

Abstract

This invention discloses a medium- and long-term scheduling method and system for multi-energy complementarity based on short-term fluctuation risk control. The method includes: analyzing the complementary relationship between photovoltaic fluctuation amplitude and hydropower regulation capacity from the perspective of output shape and power quantity based on historical operating data of the multi-energy complementarity system, thereby formulating a fluctuation risk control strategy for the short-term multi-energy complementarity power generation process. Based on this, a nested optimization scheduling model is constructed, coupling an outer layer of medium- and long-term hydropower decision search with an inner layer of short-term fluctuation risk control. This method further coordinates the effectiveness of hydropower in compensating for photovoltaic fluctuations. Fluctuation risk control effectively balances energy consumption and grid-connected power quality, responding to the stability requirements of high-voltage direct current transmission in multi-energy complementarity bundled grid connection, and providing application guidance for the coordinated operation of complementary systems and power systems.

Description

Technical Field

[0001] The present invention relates to a multi-energy complementary power generation technology, and in particular to a multi-energy complementary medium- and long-term scheduling method and system based on short-term fluctuation risk control. Background Art

[0002] my country's western region is rich in resources. Electricity is transmitted to the eastern power grid through the "West-to-East Power Transmission" transmission channel for consumption and utilization. Whether the region's clean energy can be rationally utilized will not only have a significant impact on the construction of clean energy bases, but will also make a huge contribution to the local high-quality economic development. The superposition of current harmonics caused by output fluctuations during power generation and transmission will increase the pressure on the power grid. The zigzag output of photovoltaic power, which is affected by weather, has a significant adverse impact. In this case, the problem of single energy consumption needs to be extended to the comprehensive problem of volatility risk control. At the same time, the traditional multi-energy complementary process lacks a comprehensive consideration of the medium- and long-term consumption of power generation and the short-term consumption and fluctuation of transmission channels. How to coordinate hydropower to cope with the local and overall volatility of photovoltaic output, and how this coordination mechanism influences and regulates the medium- and long-term scheduling decisions of the multi-energy complementary system, requires further research. Summary of the Invention

[0003] Purpose of the invention: The purpose of the present invention is to provide a medium- and long-term scheduling method for multi-energy complementarity based on short-term fluctuation risk control, aiming to take into account the short-term fluctuation risk of multi-energy complementary system power generation in the medium- and long-term scheduling process, and on this basis achieve the effective connection between long-term electricity consumption and short-term electricity grid connection, thereby improving the efficiency of multi-energy utilization.

[0004] Another object of the present invention is to provide a multi-energy complementary medium- and long-term scheduling system based on short-term fluctuation risk control.

[0005] Technical solution: The present invention provides a mid- to long-term scheduling method for multi-energy complementarity based on short-term fluctuation risk control, comprising the following steps:

[0006] S1. Collect historical operating data of the multi-energy complementary system, including a hydropower station and a photovoltaic power station, to obtain photovoltaic output process, hydropower regulation capacity, and transmission channel capacity;

[0007] S2. Based on the short-term photovoltaic output process and hydropower regulation capacity, the transmission channel capacity is divided into a hydropower guarantee area, a photovoltaic consumption area, and a fluctuation control area. The fluctuation control area is compensated by hydropower, while smoothing the local and overall fluctuations of the photovoltaic output process. On this basis, a fluctuation risk control strategy is formed in the short-term multi-energy complementary power generation process;

[0008] S3. Construct a medium- and long-term scheduling model for multi-energy complementarity, including: establishing an objective function for medium- and long-term scheduling with the goal of optimizing the amount of electricity consumed by the multi-energy complementarity system, transforming short-term fluctuation risk control into constraints, and thereby constructing a nested optimization scheduling model that couples medium- and long-term hydropower decision-making search with short-term fluctuation risk control;

[0009] S4. Use intelligent algorithms to solve the medium- and long-term scheduling model of multi-energy complementary systems and obtain the medium- and long-term optimal scheduling method of the multi-energy complementary systems.

[0010] Furthermore, in step S2, the hydropower guarantee area is the transmission channel space required to meet the lower limit of hydropower output; the photovoltaic consumption area is the transmission channel space further occupied by the photovoltaic output process on the basis of the hydropower guarantee area, specifically:

[0011]

[0012]

[0013]

[0014] in, are the capacities of the hydropower guarantee area and photovoltaic consumption area in stage n respectively; is the lower limit of short-term hydropower output in stage n; P g is the grid channel capacity; are respectively the short-term photovoltaic output and the short-term photovoltaic output in the t-th period of the n-th phase. represents the maximum photovoltaic output that the transmission channel can absorb, t is the short-term period, t = 1…T, T is the number of short-term periods, n is the medium- and long-term stage variable, n = 1…N, N is the total number of medium- and long-term stages, and Δt is the short-term step size;

[0015] The fluctuation control area is: based on the photovoltaic consumption area, the hydropower electricity compensates for the transmission channel space occupied by the volatility of the photovoltaic output process; according to the hydropower electricity compensation method, the fluctuation control area is divided into local fluctuation control area and overall fluctuation control area.

[0016] Furthermore, the outer boundary of the local fluctuation control area is able to accommodate The minimum trapezoidal outline, the upper boundary of the trapezoidal outline is The highest point remains the same, and the trapezoidal outline is divided into two right-angled trapezoids on the left and right through this point. The trapezoidal outline search method is as follows:

[0017]

[0018]

[0019] minA1=f(l1),minA2=f(l2)

[0020] in, is the spatial capacity of the local fluctuation control area in stage n; is the initial fluctuation area of ​​the nth stage, indicating the area between the boundary of the local fluctuation control area and the boundary of the photovoltaic absorption area; A1 and A2 are the areas of the left and right right trapezoids respectively, l1 and l2 are the hypotenuses of the left and right right trapezoids respectively, and f is the area function of the right trapezoid; traverse and connect the time nodes on the upper and lower boundaries of the trapezoid outline in sequence to form the hypotenuse l1 or l2, calculate A1 and A2 by f, if the side Located inside the hypotenuse and meeting the minimum area requirement, the boundary of the local fluctuation control area is obtained It represents the minimum trapezoidal profile that can fully accommodate the photovoltaic output process.

[0021] Furthermore, the outer boundary of the overall fluctuation control area is the outline of the transmission channel that can absorb the hydropower, specifically:

[0022]

[0023]

[0024]

[0025]

[0026] in, is the spatial capacity of the overall fluctuation control zone in stage n; is the overall fluctuation control area in stage n, which represents the area between the maximum capacity of the transmission channel and the boundary of the local fluctuation control area; is the boundary of the overall fluctuation control area in stage n; The expected output of hydropower in stage n; P z for hydropower installed capacity; It is the upper limit of hydropower output in stage n.

[0027] Furthermore, in step S2, the volatility risk control strategy in the local volatility control area is:

[0028] Step 1: Initial volatility area The position is represented by a short-term period t, t = 1…T;

[0029] Step 2: Identify the fluctuation area Fluctuation intensity at each position Where k represents the number of cycles;

[0030] Step 3: Assign local fluctuation parameter ΔS to guide hydropower compensation output Compensate and smooth out fluctuating areas Fluctuation intensity at each position

[0031] Step 4: Construct a new volatility area If the fluctuation area The volatility intensity at each position is no higher than the local volatility parameter ΔS, and the volatility risk control process is completed. Otherwise, return to step 2, specifically:

[0032]

[0033]

[0034]

[0035]

[0036]

[0037] in, are the fluctuation area size, fluctuation intensity, and hydropower compensation output at the fluctuation area position t during the k-th fluctuation risk control process; are the fluctuation area size and hydropower compensation output at location t after the fluctuation risk control meets the requirements; ΔS is the local fluctuation parameter; is the local balance electricity of hydropower; represents the hydropower electricity demanded in the process of compensating the local fluctuation control area, where ΔS is the only variable, and the function f1 is introduced to represent When ΔS=0, the fluctuation range is fully compensated. disappear completely.

[0038] Furthermore, in step S2, the volatility risk control strategy in the overall volatility control area is:

[0039] Step 1: Overall Fluctuation Control Area The position is represented by a short-term period t, t = 1…T;

[0040] Step 2: Assign the overall fluctuation parameter ΔR to guide hydropower consumption output Along the rising boundary of the horizontal plane Compensation for overall fluctuation control area Specifically:

[0041]

[0042]

[0043]

[0044] in, is the rising boundary of the horizontal plane, is the hydropower consumption output at position t in the overall fluctuation control area; The overall balance of hydropower electricity, in the process of compensating the overall balance area, ΔR is the overall fluctuation parameter, which is the only variable. The function f2 is introduced to express

[0045] After the hydropower electricity compensation in the local fluctuation control area is completed, the remaining hydropower electricity rises along the horizontal plane within the overall fluctuation control area, cooperating with the local fluctuation control area to smooth the overall volatility of the multi-energy complementary system's power generation, so that the peak-to-valley difference in the multi-energy complementary system's power generation process is further reduced.

[0046] Furthermore, in step S3, the nested optimization scheduling model that couples the mid- and long-term hydropower decision search with the short-term fluctuation risk control is:

[0047] S31. In the medium and long term, the goal is to maximize the amount of electricity consumed. The scheduling period is one month and the scheduling step is one day. Specifically:

[0048]

[0049]

[0050] Among them, W is the medium and long-term power consumption, W n is the short-term power consumption in the nth stage, is the short-term hydropower consumption in stage n, is the short-term photovoltaic power consumption in the nth stage, which is obtained by calculating the water level node and runoff in the current stage;

[0051] S32. Constraints include: water balance constraints, reservoir capacity constraints, discharge flow constraints, and short-term fluctuation risk control constraints, specifically:

[0052]

[0053]

[0054] in, It is the hydropower guarantee area for the nth phase; are the hydropower electricity used by the local fluctuation control area and the overall fluctuation control area in the nth stage, ΔS and ΔR are vectors composed of multiple local fluctuation parameters and overall fluctuation parameters, respectively, where 0 represents the highest requirement for fluctuation control;

[0055] The constraints also include short-term power curtailment risk control constraints, specifically:

[0056]

[0057]

[0058] in, It is the maximum consumption space of short-term hydropower in the nth stage.

[0059] The present invention provides a multi-energy complementary medium- and long-term scheduling system based on short-term fluctuation risk control, comprising:

[0060] Data acquisition module, used to collect historical operation data of the multi-energy complementary system;

[0061] The short-term fluctuation risk control module randomly selects one day based on the historical operating data of the hydropower-photovoltaic complementary power generation system to formulate a fluctuation risk control strategy for the short-term multi-energy complementary power generation process. It also extracts complementary power information during the short-term complementary process, including: short-term photovoltaic power consumption, short-term hydropower power consumption, hydropower power called up by the local fluctuation control area, hydropower power called up by the overall fluctuation control area, and the maximum short-term hydropower power consumption space.

[0062] The long-term hydropower-solar complementary scheduling module, based on the complementary power information output by the short-term fluctuation risk control module, further constructs a nested optimization scheduling model that couples medium- and long-term hydropower decision-making search with short-term fluctuation risk control.

[0063] The model solving module uses intelligent algorithms to solve the medium- and long-term scheduling model and obtain the medium- and long-term optimal scheduling method of the multi-energy complementary system.

[0064] A device of the present invention includes a memory and a processor, wherein:

[0065] a memory for storing computer programs capable of running on the processor;

[0066] The processor is used to execute the steps of the above-mentioned multi-energy complementary medium- and long-term scheduling method based on short-term fluctuation risk control when running the computer program.

[0067] A storage medium of the present invention stores a computer program, which, when executed by at least one processor, implements the steps of the above-mentioned multi-energy complementary medium- and long-term scheduling method based on short-term fluctuation risk control.

[0068] Beneficial effects: Compared with the existing technology, the method of the present invention ensures the guaranteed output of hydropower and maximizes the absorption degree of photovoltaic output by reasonably dividing the capacity of transmission channels; on this basis, local and overall fluctuation parameters are introduced to guide the hydropower electricity in the local fluctuation control area and the overall fluctuation control area respectively, and implement compensation and smoothing for the local volatility and overall volatility of the power generation process of the multi-energy complementary system, thereby realizing a short-term fluctuation risk control strategy; at the same time, the electricity complementarity information is transmitted to the medium- and long-term scheduling process, effectively coordinating the medium- and long-term power generation absorption and short-term fluctuation risk control and power abandonment, improving the medium- and long-term power generation absorption level of the multi-energy complementary system, and effectively smoothing the fluctuation risk of the power generation process in the short term, thereby improving the comprehensive benefits of the multi-energy complementary system and the power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] Figure 1 It is a flow chart of the method of the present invention;

[0070] Figure 2 It is a schematic diagram of the capacity division of transmission channels;

[0071] Figure 3 It is a schematic diagram of the volatility risk control process in the local volatility control area;

[0072] Figure 4 It is a schematic diagram of the volatility risk control process in the overall volatility control area;

[0073] Figure 5 This is a schematic diagram of the mid- to long-term optimization scheduling results of the volatility risk control solution.

[0074] Figure 6 This is a schematic diagram of the mid- to long-term optimization scheduling results of the second volatility risk control scheme;

[0075] Figure 7 This is a schematic diagram of the mid- to long-term optimization scheduling results of the volatility risk control plan three;

[0076] Figure 8 It is a schematic diagram of the fluctuation area of ​​the three schemes in the local fluctuation control area;

[0077] Figure 9 This is a schematic diagram of the peak-to-valley difference of the three schemes in the overall fluctuation control area. DETAILED DESCRIPTION

[0078] The present invention will be described in further detail below in conjunction with the accompanying drawings and specific examples. The following examples are used to illustrate the present invention but are not intended to limit the scope of the present invention.

[0079] For this example, we selected a multi-energy complementary system with 9.525 million kW of installed hydropower capacity and 12 million kW of installed photovoltaic capacity, transmitting power through a 10 million kW transmission channel. Given the stable interannual total photovoltaic power generation, we used the photovoltaic output process in June of a typical year for this example calculation.

[0080] Table 1 Scale parameters of cascade hydropower stations

[0081]

[0082] like Figure 1 As shown, the present invention provides a multi-energy complementary medium- and long-term scheduling method based on short-term fluctuation risk control, comprising the following steps:

[0083] S1. Collect historical operating data of the multi-energy complementary system to obtain the photovoltaic output process, hydropower regulation capacity, and transmission channel capacity within the scheduling period;

[0084] The multi-energy complementary system includes hydropower stations and photovoltaic power stations. The photovoltaic output process mainly presents local fluctuations and overall fluctuations of "daytime power generation and nighttime rest". The hydropower regulation capacity mainly includes the upper limit and lower limit of hydropower output.

[0085] S2. Divide the transmission channel capacity into a hydropower guarantee zone, a photovoltaic consumption zone, and a fluctuation control zone based on the short-term photovoltaic output process and hydropower regulation capacity. The fluctuation control zone is compensated by hydropower, while simultaneously smoothing the local and overall fluctuations of the photovoltaic output process. On this basis, a fluctuation risk control strategy is formed during the short-term multi-energy complementary power generation process.

[0086] like Figure 2 As shown in the figure, the hydropower guarantee area is the transmission channel space required for the lower limit of hydropower output; the photovoltaic consumption area is the transmission channel space further occupied by the photovoltaic output process on the basis of the hydropower guarantee area, specifically:

[0087]

[0088]

[0089]

[0090] Where, are the capacities of the hydropower guarantee area and photovoltaic consumption area in stage n respectively; is the lower limit of short-term hydropower output in stage n; P g is the transmission channel capacity; is the short-term photovoltaic output consumed in the tth period of the nth stage, indicating the photovoltaic output that the transmission channel can consume to the maximum extent. is the short-term photovoltaic output in the t-th period of the n-th stage; t is the short-term period, t=1…T, T is the number of short-term periods, n is the medium- and long-term period variable, n=1…N, N represents the total number of medium- and long-term periods, and Δt is the short-term step size.

[0091] The fluctuation control area is: based on the photovoltaic consumption area, the hydropower electricity compensates for the transmission channel space occupied by the volatility of the photovoltaic output process; according to the hydropower electricity compensation method, the fluctuation control area is divided into local fluctuation control area and overall fluctuation control area.

[0092] The outer boundary of the local fluctuation control area is the area that can accommodate The minimum trapezoidal outline, the upper boundary of the trapezoidal outline is The highest point remains consistent, and the trapezoidal outline is divided into two stepped polygons on the left and right through this point. Specifically, it can be expressed as a standard right-angled trapezoid or triangle. This process aims to improve the search efficiency of the outer boundary of the local fluctuation control area, i.e., the trapezoidal outline, through the efficient area function integral operation of the right-angled trapezoid or triangle (the calculation form of the two expressions of the right-angled trapezoid or triangle is the same, because the photovoltaic absorption area is a fixed area, and the calculation of the minimum area of ​​A1 and A2 is actually the calculation of the minimum area of ​​the local fluctuation control area in the above expression). The trapezoidal outline search method is specifically as follows:

[0093]

[0094]

[0095] minA1=f(l1),minA2=f(l2)

[0096] Where, is the spatial capacity of the local fluctuation control area in stage n; is the initial fluctuation area of ​​the nth stage, indicating the area between the boundary of the local fluctuation control area and the boundary of the photovoltaic absorption area; A1 and A2 are the areas of the left and right stepped polygons (i.e., right-angled trapezoids), l1 and l2 are the hypotenuses of the left and right stepped polygons (i.e., right-angled trapezoids), and f is the area function of the stepped polygon (i.e., right-angled trapezoid); traverse and connect the time nodes on the upper and lower boundaries of the trapezoidal outline in sequence to form the hypotenuse l1 or l2, calculate A1 and A2 through f, if the side Located inside the hypotenuse and meeting the minimum area requirement, the boundary of the local fluctuation control area can be obtained It represents the minimum trapezoidal profile that can fully accommodate the photovoltaic output process.

[0097] The outer boundary of the overall fluctuation control area is the outline of the transmission channel that can absorb the hydropower, specifically:

[0098]

[0099]

[0100]

[0101]

[0102] Where, is the spatial capacity of the overall fluctuation control zone in stage n; is the overall fluctuation control area in stage n, which represents the area between the maximum capacity of the transmission channel and the boundary of the local fluctuation control area; is the boundary of the overall fluctuation control area in stage n; The expected output of hydropower in stage n; P z for hydropower installed capacity; It is the upper limit of hydropower output in stage n.

[0103] like Figure 3 As shown in Figure 2, the volatility risk control strategy in the local volatility control area is:

[0104] Step 1: Initial volatility area The position is represented by a short-term period t, t = 1…T;

[0105] Step 2: Identify the fluctuation area Fluctuation intensity at each position Where k represents the number of cycles;

[0106] Step 3: Assign local fluctuation parameter ΔS to guide hydropower compensation output Compensate and smooth out fluctuating areas Fluctuation intensity at each position

[0107] Step 4: Construct a new volatility area If the fluctuation area The volatility intensity at each position is no higher than the local volatility parameter ΔS, and the volatility risk control process is completed. Otherwise, return to step 2, specifically:

[0108]

[0109]

[0110]

[0111]

[0112]

[0113] Where, are the fluctuation area size, fluctuation intensity, and hydropower compensation output at the fluctuation area position t during the k-th fluctuation risk control process; are the fluctuation area size and hydropower compensation output at location t after the fluctuation risk control meets the requirements; ΔS is the local fluctuation parameter; is the local balance electricity of hydropower; represents the hydropower electricity demanded in the process of compensating the local fluctuation control area, where ΔS is the only variable, and the function f1 is introduced to represent When ΔS=0, the fluctuation range is fully compensated. disappear completely.

[0114] For example Figure 3 Hydropower Compensation Output I represents the hydropower compensation output process in the fluctuating area when ΔS = 400,000 kW, and Hydropower Compensation Output II represents the hydropower compensation output process in the fluctuating area when ΔS = 100,000 kW. Obviously, as ΔS decreases, the hydropower compensation output increases, and the compensation and smoothing effect on the fluctuating area is improved. If ΔS = 0,000 kW, hydropower can fully compensate for the fluctuating area. This process aims to smooth the local fluctuations in the power generation of the multi-energy complementary system, so that the power generation process of the multi-energy complementary system gradually approaches the trapezoidal profile power transmission form, ensuring the local stability of the transmission process.

[0115] like Figure 4 As shown in Figure 2, the volatility risk control strategy in the overall volatility control area is:

[0116] Step 1: Overall Fluctuation Control Area The position is represented by a short-term period t, t = 1…T;

[0117] Step 2: Assign the overall fluctuation parameter ΔR to guide hydropower consumption output Along the rising boundary of the horizontal plane Compensation for overall fluctuation control area Specifically:

[0118]

[0119]

[0120]

[0121] Where, is the rising boundary of the horizontal plane, is the hydropower consumption output at position t in the overall fluctuation control area; The overall balance of hydropower electricity, in the process of compensating the overall balance area, △R is the overall fluctuation parameter, which is the only variable, and the function f2 is introduced to express

[0122] After the hydropower electricity in the local fluctuation control area is compensated, the remaining hydropower electricity rises along the horizontal plane in the overall fluctuation control area, e.g. Figure 4 Hydropower Compensation Output III represents the hydropower compensation output process in the overall fluctuation control zone when ΔR = 2 million kW, while Hydropower Compensation Output IV represents the hydropower compensation output process in the overall fluctuation control zone when ΔR = 5 million kW. Clearly, as ΔR increases, the hydropower compensation output increases accordingly, improving the compensation and smoothing effect on the overall fluctuation control zone. This process is designed to cooperate with local fluctuation control zones to further smooth the overall fluctuation of the multi-energy complementary system's power generation, further reducing the peak-to-valley difference in the multi-energy complementary system's power generation process and ensuring the overall stability of the transmission process.

[0123] In summary, the goal of establishing a fluctuation control zone based on short-term photovoltaic output and compensating for it with hydropower is to smooth the fluctuations in the multi-energy complementary system's transmission process. Because the hydropower compensation capacity is constrained by multiple factors, the fluctuation control zone is further divided into a local fluctuation control zone and an overall fluctuation control zone. When hydropower compensation capacity is weak, the local fluctuation control zone is compensated according to the local fluctuation parameters, minimizing the multi-energy complementary system's power generation process to a trapezoidal transmission profile and ensuring local stability. When hydropower compensation capacity is strong, the hydropower first compensates the local fluctuation control zone, then compensates the overall fluctuation control zone according to the overall fluctuation parameters, minimizing the peak-to-valley difference in the multi-energy complementary system's power generation process and ensuring overall stability. On this basis, a short-term, flexible and controllable fluctuation risk control strategy is developed based on long-term multi-energy complementary system scheduling decisions.

[0124] S3. Construct a medium- and long-term scheduling model for multi-energy complementarity, including establishing a medium- and long-term scheduling objective function and constraints. The objective function for medium- and long-term scheduling is to optimize the amount of electricity consumed by the multi-energy complementarity system, and to transform short-term fluctuation risk control into constraints. This allows for the construction of a nested optimization scheduling model that couples medium- and long-term hydropower decision-making search with short-term fluctuation risk control, i.e., a medium- and long-term scheduling model for multi-energy complementarity.

[0125] S31. In the medium and long term, the goal is to maximize the amount of electricity consumed. The scheduling period is one month and the scheduling step is one day. Specifically:

[0126]

[0127]

[0128] Where W is the medium and long-term power consumption, W n is the short-term power consumption in the nth stage, is the short-term hydropower consumption in stage n, is the short-term photovoltaic power consumption in the nth stage, which is obtained by calculating the water level node and runoff in the current stage;

[0129] S32. Constraints include: water balance constraints, reservoir capacity constraints, discharge flow constraints, and short-term fluctuation risk control constraints, specifically:

[0130]

[0131]

[0132] Where, It is the hydropower guarantee area for the nth phase; are the hydropower electricity used in the local fluctuation control area and the overall fluctuation control area in the nth stage, respectively. ΔS and ΔR are vectors composed of multiple local fluctuation parameters and overall fluctuation parameters, where 0 represents the highest requirement for fluctuation control.

[0133] The constraints also include short-term power curtailment risk control constraints, specifically:

[0134]

[0135]

[0136] Where, It is the maximum consumption space of short-term hydropower in the nth stage.

[0137] S4. Use intelligent algorithms to solve the medium- and long-term scheduling model of multi-energy complementary systems and obtain the medium- and long-term optimal scheduling method of the multi-energy complementary systems.

[0138] A multi-energy complementary medium- and long-term scheduling system based on short-term fluctuation risk control, comprising:

[0139] Data acquisition module, used to collect historical operation data of the multi-energy complementary system;

[0140] The short-term fluctuation risk control module randomly selects one day based on the historical operation data of the multi-energy complementary system to formulate a fluctuation risk control strategy in the short-term multi-energy complementary power generation process and extract the complementary power information in the short-term complementary process, including: Extracting the complementary power information in the short-term complementary process, including: The capacity of the hydropower guarantee area Capacity of photovoltaic consumption area Local balance of hydropower Overall balance of hydropower Maximum capacity for absorbing hydropower

[0141] The long-term hydropower-solar complementary scheduling module, based on the complementary power information output by the short-term fluctuation risk control module, further constructs a nested optimization scheduling model that couples medium- and long-term hydropower decision-making search with short-term fluctuation risk control.

[0142] The model solving module uses intelligent algorithms to solve the medium- and long-term scheduling model and obtain the medium- and long-term optimal scheduling method of the multi-energy complementary system.

[0143] A device of the present invention includes a memory and a processor, wherein:

[0144] a memory for storing computer programs capable of running on the processor;

[0145] The processor is used to execute the steps of the multi-energy complementary medium- and long-term scheduling method based on short-term fluctuation risk control when running the computer program, and can achieve the technical effect consistent with the above method.

[0146] A storage medium of the present invention stores a computer program, which, when executed by at least one processor, implements the steps of a multi-energy complementary medium- and long-term scheduling method based on short-term fluctuation risk control, and can achieve technical effects consistent with the above method.

[0147] like Figures 5 to 7 As shown, the average runoff flow in June is 1070m 3 / s as an example, combined with the photovoltaic output process, three groups of schemes are set: ΔS = [200, 20, 0]; ΔR = [1000, 1000, 500]. The dynamic programming algorithm is used to solve the multi-energy complementary medium- and long-term scheduling model. The hydropower consumption in each stage in the medium and long term has changed significantly. The reason is that, guided by the local fluctuation parameters and the overall fluctuation parameters, a part of the hydropower needs to be called in each stage to control the local and overall fluctuations of the photovoltaic output process. The smaller the local fluctuation parameters and the overall fluctuation parameters, the more obvious the control effect is, and the more hydropower needs to be called. The specific effect of fluctuation risk control is as follows:

[0148] like Figure 8 As shown, the local fluctuation parameter of Scheme 1 is 2 million kW, the local fluctuation parameter of Scheme 2 is 200,000 kW, and the local fluctuation parameter of Scheme 3 is 0 kW. After controlling the short-term fluctuation risk, the sawtooth fluctuation amplitude of photovoltaic output in adjacent periods of the fluctuation area in the local fluctuation control area is significantly alleviated. When △S = 0 MW, the fluctuation area drops to 0 and presents a horizontal straight line, indicating that the photovoltaic elevator contour is fully compensated. The power transmitted by the complementary system presents a stepped straight line, meeting the requirements of the segmented stable power transmission method. It can effectively reduce the operating pressure of the power system.

[0149] like Figure 9As shown, the overall fluctuation parameter of Scheme 1 is 10 million kW, the overall fluctuation parameter of Scheme 2 is 10 million kW, and the overall fluctuation parameter of Scheme 3 is 5 million kW. After short-term fluctuation risk control, the peak-to-valley difference in Scheme 3 is reduced to below 500kW, and the fluctuation risk control effect is obvious.

[0150] The above analysis shows that controlling short-term fluctuation risks significantly impacts medium- and long-term dispatch and distribution of electricity, and significantly regulates both the local and overall grid-connected quality of electricity at each stage. This improves medium- and long-term electricity consumption, effectively mitigates short-term fluctuation risks in power generation, and enhances the overall benefits of the multi-energy complementary system and the power system.

Claims

1. A mid- to long-term scheduling method for multi-energy complementarity based on short-term fluctuation risk control, characterized in that: The following steps are involved: S1. Collect historical operating data of the multi-energy complementary system, including hydropower stations and photovoltaic power stations, to obtain the photovoltaic output process, hydropower regulation capacity, and transmission channel capacity within the scheduling period; S2. Based on the short-term photovoltaic output process and hydropower regulation capacity, the transmission channel capacity is divided into a hydropower guarantee area, a photovoltaic consumption area, and a fluctuation control area. The fluctuation control area is compensated by hydropower, while smoothing the local and overall fluctuations of the photovoltaic output process. On this basis, a fluctuation risk control strategy is formed in the short-term multi-energy complementary power generation process; The fluctuation control area is the transmission channel space occupied by hydropower to compensate for the fluctuation of photovoltaic output in the photovoltaic consumption area. Based on the hydropower compensation method, the fluctuation control area is divided into local fluctuation control area and overall fluctuation control area. The outer boundary of the local fluctuation control area is the area that can accommodate The minimum trapezoidal outline, the upper boundary of the trapezoidal outline is The highest point remains the same, and the trapezoidal outline is divided into two stepped polygons on the left and right through this point. The specific search method for the stepped polygon outline is: minA1=f(l1),minA2=f(l2) in, is the spatial capacity of the local fluctuation control area in stage n; is the initial fluctuation area of ​​the nth stage, indicating the area between the boundary of the local fluctuation control area and the boundary of the photovoltaic consumption area; t is the short-term period, t = 1…T, T is the number of short-term periods, Δt is the short-term step length, is the short-term photovoltaic output consumed in the tth period of the nth stage, indicating the photovoltaic output that the transmission channel can consume to the greatest extent; A1 and A2 are the areas of the left and right stepped polygons, respectively; l1 and l2 are the hypotenuses of the left and right stepped polygons, respectively; f is the area function of the stepped polygon; traverse and connect the time nodes on the upper and lower boundaries of the trapezoidal outline in sequence to form the hypotenuse l1 or l2, and calculate A1 and A2 through f. If the side Located inside the hypotenuse and meeting the minimum area requirement, the boundary of the local fluctuation control area is obtained Indicates the minimum trapezoidal profile that can fully accommodate the photovoltaic output process; S3. Construct a medium- and long-term scheduling model for multi-energy complementarity, including: establishing an objective function for medium- and long-term scheduling with the goal of optimizing the amount of electricity consumed by the multi-energy complementarity system, transforming short-term fluctuation risk control into constraints, and thereby constructing a nested optimization scheduling model that couples medium- and long-term hydropower decision-making search with short-term fluctuation risk control, namely the medium- and long-term scheduling model for multi-energy complementarity; S4. Use intelligent algorithms to solve the medium- and long-term scheduling model of multi-energy complementary systems and obtain the medium- and long-term optimal scheduling method of the multi-energy complementary systems.

2. The method for mid- to long-term scheduling of multi-energy complementarity based on short-term fluctuation risk control according to claim 1, characterized in that: In step S2, the hydropower guarantee area is the transmission channel space required to meet the lower limit of hydropower output; the photovoltaic consumption area is the transmission channel space further occupied by the photovoltaic output process on the basis of the hydropower guarantee area, specifically: in, are the capacities of the hydropower guarantee area and photovoltaic consumption area in stage n respectively; is the lower limit of short-term hydropower output in stage n; P g is the transmission channel capacity; is the short-term photovoltaic output absorbed in the tth period of the nth stage, indicating the photovoltaic output that the transmission channel can absorb to the maximum extent; is the short-term photovoltaic output in the t-th period of the n-th stage; t is the short-term period, t=1…T, T is the number of short-term periods, n is the medium- and long-term period variable, n=1…N, N represents the total number of medium- and long-term periods, and Δt is the short-term step size.

3. The method for mid- to long-term scheduling of multi-energy complementary energy based on short-term fluctuation risk control according to claim 2, characterized in that: The outer boundary of the overall fluctuation control area is the outline of the transmission channel that can absorb the hydropower, specifically: in, is the spatial capacity of the overall fluctuation control zone in stage n; is the overall fluctuation control area in stage n, which represents the area between the maximum capacity of the transmission channel and the boundary of the local fluctuation control area; is the boundary of the overall fluctuation control area in stage n; The expected output of hydropower in stage n; P z for hydropower installed capacity; It is the upper limit of hydropower output in stage n.

4. The method for mid- to long-term scheduling of multi-energy complementarity based on short-term fluctuation risk control according to claim 1, characterized in that: In step S2, the volatility risk control strategy in the local volatility control area is: Step 1: Initial volatility area The position is represented by a short-term period t, t = 1…T; Step 2: Identify the fluctuation area Fluctuation intensity at each position Where k represents the number of cycles; Step 3: Assign local fluctuation parameter ΔS to guide hydropower compensation output Compensate and smooth out fluctuating areas Fluctuation intensity at each position Step 4: Construct a new volatility area If the fluctuation area The volatility intensity at each position is no higher than the local volatility parameter ΔS, and the volatility risk control process is completed. Otherwise, return to step 2, specifically: in, are the fluctuation area size, fluctuation intensity, and hydropower compensation output at the fluctuation area position t during the k-th fluctuation risk control process; are the fluctuation area size and hydropower compensation output at location t after the fluctuation risk control meets the requirements; ΔS is the local fluctuation parameter; is the local balance electricity of hydropower; represents the hydropower electricity demanded in the process of compensating the local fluctuation control area, where ΔS is the only variable, and the function f1 is introduced to represent When ΔS=0, the fluctuation range is fully compensated. disappear completely.

5. The method for mid- to long-term scheduling of multi-energy complementary energy based on short-term fluctuation risk control according to claim 1, characterized in that: In step S2, the volatility risk control strategy in the overall volatility control area is: Step 1: Overall Fluctuation Control Area The position is represented by a short-term period t, t = 1…T; is the overall fluctuation control area in stage n, which represents the area between the maximum capacity of the transmission channel and the boundary of the local fluctuation control area; Step 2: Assign the overall fluctuation parameter ΔR to guide hydropower consumption output Along the rising boundary of the horizontal plane Compensation for overall fluctuation control area Specifically: in, is the rising boundary of the horizontal plane, is the hydropower consumption output at position t in the overall fluctuation control area, is the boundary of the overall fluctuation control area in stage n; is the short-term photovoltaic output absorbed in the tth period of the nth stage, indicating the photovoltaic output that the transmission channel can absorb to the maximum extent; is the lower limit of short-term hydropower output in stage n; The overall balance of hydropower electricity, in the process of compensating the overall balance area, ΔR is the overall fluctuation parameter, which is the only variable. The function f2 is introduced to express After the hydropower electricity compensation in the local fluctuation control area is completed, the remaining hydropower electricity rises along the horizontal plane within the overall fluctuation control area, cooperating with the local fluctuation control area to smooth the overall volatility of the multi-energy complementary system's power generation, so that the peak-to-valley difference in the multi-energy complementary system's power generation process is further reduced.

6. A system for the multi-energy complementary medium- and long-term scheduling method based on short-term fluctuation risk control according to any one of claims 1 to 5, characterized in that the system include: Data acquisition module, used to collect historical operation data of the multi-energy complementary system; The short-term fluctuation risk control module randomly selects one day based on the historical operating data of the multi-energy complementary system to formulate a fluctuation risk control strategy for the short-term multi-energy complementary power generation process and extracts complementary power information in the short-term complementary process, including: short-term photovoltaic power consumption, short-term hydropower power consumption, hydropower power called by the local fluctuation control area, hydropower power called by the overall fluctuation control area, and the maximum short-term hydropower power consumption space; The long-term hydropower-solar complementary scheduling module, based on the complementary power information output by the short-term fluctuation risk control module, further constructs a nested optimization scheduling model that couples medium- and long-term hydropower decision-making search with short-term fluctuation risk control. The model solving module uses intelligent algorithms to solve the medium- and long-term scheduling model and obtain the medium- and long-term optimal scheduling method of the multi-energy complementary system.

7. A device, characterized in that: comprising a memory and a processor, wherein: a memory for storing computer programs capable of running on the processor; A processor is configured to execute the steps of a multi-energy complementary medium- and long-term scheduling method based on short-term fluctuation risk control as described in any one of claims 1 to 5 when running the computer program.

8. A storage medium, characterized in that: The storage medium stores a computer program, which, when executed by at least one processor, implements the steps of a multi-energy complementary medium- and long-term scheduling method based on short-term fluctuation risk control as described in any one of claims 1 to 5.

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