Method and device for hierarchical complementary configuration of installed capacity of integrated wind-solar-thermal-storage energy system

Abstract

This application relates to a method and device for complementary configuration of installed capacities of a comprehensive wind-solar-thermal-storage energy system. The specific solution is as follows: multi-time-scale hierarchical complementarity based on the complementary characteristics of the hourly average output of wind power and photovoltaic power throughout the whole time period, the complementary characteristics of the daily output of wind power, photovoltaic power, and thermal power, and the hourly-level characteristics of wind power, photovoltaic power, thermal power, and electricity storage; using a similarity factor function to evaluate the similarity between the hourly average output curves of wind power, photovoltaic power, and thermal power throughout the whole time period and the hourly average power transmission curve of the direct current throughout the whole time period, and further evaluating the complementary effect of the hourly average output characteristics of wind power and photovoltaic power throughout the whole time period; combining with the time-series production simulation method, using the curve fitting goodness function to evaluate the peak shaving demand of the base, and combining with the proportion of new energy electricity and the annual net income to determine the optimal configuration combination of the installed capacities of wind power, photovoltaic power, and thermal power. This application realizes the mutual complementarity and coordinated mutual assistance of the outputs of different types of power sources such as thermal power, wind power, and photovoltaic power, and improves the economy of power supply.

Description

Technical Field

[0001] The present application relates to the technical field of integrated energy power generation, and particularly to a method and device for hierarchical complementary configuration of the installed capacity of a wind-solar-thermal-storage integrated energy system. Background Art

[0002] In the related art, the comprehensive efficiency of the power system is not high, and deep-seated contradictions such as insufficient coordination among the power grid, load, and other links, and insufficient complementarity and mutual assistance among various power sources are becoming increasingly prominent. There is an urgent need for overall optimization to improve the utilization level of clean energy and the operating efficiency of the power system, and to better guide the planning and development of the sending-end power source base and the coordinated interaction among the power grid, load, and storage. The multi-energy complementary characteristic means that the power outputs of different types of power sources such as thermal power, wind power, and photovoltaic power can complement each other and coordinate with each other. Under the background of building a new power system, it is of greater significance to develop multi-energy complementarity to significantly increase the proportion of the power supply of new energy power. Summary of the Invention

[0003] Therefore, the present application provides a method and device for hierarchical complementary configuration of the installed capacity of a wind-solar-thermal-storage integrated energy system. The technical solution of the present application is as follows:

[0004] According to the first aspect of the embodiments of the present application, a method for hierarchical complementary configuration of the installed capacity of wind power, photovoltaic power, and thermal power is provided. A method and device for hierarchical complementary configuration of the installed capacity of a wind-solar-thermal-storage integrated energy system, the method includes:

[0005] Obtain multiple wind power installed capacity data, multiple photovoltaic power installed capacity data, and multiple thermal power installed capacity data respectively;

[0006] Combine the multiple wind power installed capacity data, multiple photovoltaic power installed capacity data, and multiple thermal power installed capacity data to obtain N combinations; each of the N combinations includes one wind power installed capacity data, one photovoltaic power installed capacity data, and one thermal power installed capacity data; N is an integer greater than 0;

[0007] For the kth combination, obtain the full-time output data of wind power, photovoltaic power, and thermal power corresponding to the kth combination; based on the full-time output data of wind power, photovoltaic power, and thermal power corresponding to the kth combination, determine the full-time average output curve of wind power, photovoltaic power, and thermal power corresponding to the kth combination; obtain the DC full-time power transmission curve, and based on the DC full-time power transmission curve, determine the DC full-time average power transmission curve; k is an integer greater than 0 and less than N;

[0008] Determine the similarity factor between the full-time average output curve of wind power, photovoltaic power, and thermal power corresponding to the kth combination and the DC full-time average power transmission curve;

[0009] Determine the combinations corresponding to each of the M similarity factors that meet the preset conditions as the target combinations according to the similarity factors of the N combinations respectively; M is an integer greater than 0 and less than N;

[0010] Comprehensively evaluate each of the M target combinations according to a plurality of preset evaluation indicators to obtain the comprehensive evaluation indicator values of the target combinations respectively;

[0011] Based on the comprehensive evaluation indicator values of the target combinations respectively, determine the optimal combination, and determine the optimal combination as the installed capacity configuration of wind power, photovoltaic power, and thermal power;

[0012] Use the energy storage power supply to compensate for the difference between the full-time output curves of wind power, photovoltaic power, and thermal power of the installed capacity configuration of the optimal combination and the full-time DC power transmission curve, so that the full-time output curves of wind power, photovoltaic power, and thermal power are close to the full-time DC power transmission curve.

[0013] According to an embodiment of the present application, the step of determining the combinations corresponding to each of the M similarity factors that meet the preset conditions as the target combinations according to the similarity factors of the N combinations respectively includes:

[0014] Obtain a first threshold;

[0015] Compare the similarity factors of the N combinations respectively with the first threshold to obtain comparison results;

[0016] For the j-th similarity factor, in response to the comparison result that the j-th similarity factor is greater than or equal to the first threshold, determine that the j-th similarity factor meets the preset conditions; j is an integer greater than 0 and less than M;

[0017] Determine the combinations corresponding to each of the M similarity factors that meet the preset conditions as the target combinations.

[0018] According to an embodiment of the present application, the plurality of preset evaluation indicators include the annual net income index value of the base, the goodness-of-fit index value, and the new energy proportion index value; the step of comprehensively evaluating each of the M target combinations according to a plurality of preset evaluation indicators to obtain the comprehensive evaluation indicator values of the target combinations respectively includes:

[0019] For the k-th combination, based on the wind power installed capacity data, photovoltaic power installed capacity data, and thermal power installed capacity data in the k-th combination, as well as the pre-constructed objective function and constraint conditions, determine the wind power output function, photovoltaic power output function, and thermal power output function respectively;

[0020] Based on the wind power output function, photovoltaic power output function, and thermal power output function, determine the annual net income index value of the base, the goodness-of-fit index value, and the new energy proportion index value of the k-th combination respectively;

[0021] Obtain the respective preset weight values of the annual net income index value, goodness-of-fit index value, and new energy proportion index value of the base respectively;

[0022] According to an embodiment of the present application, the energy storage power supply is used to compensate the full-time output curves of wind power, photovoltaic power, and thermal power, so that the full-time output curves of wind power, photovoltaic power, and thermal power are close to the full-time DC power transmission curve

[0023] Determine the output differences between the full-time output curves of wind power, photovoltaic power, and thermal power and the full-time output curves of wind power, photovoltaic power, and thermal power at each same time period respectively;

[0024] Compensate each of the output differences at each same time period through the energy storage power supply respectively, so that the Electricity, Photovoltaic, Thermal Power output value of each time period in the full-time output curve is close to the output value of the same time period in the full-time DC power transmission curve. According to the second aspect of the embodiments of the present application, a method and device for complementary configuration of the installed capacity of a wind-solar-thermal-storage integrated energy system are provided. The device includes:

[0025] An acquisition module, configured to respectively acquire a plurality of wind power installed capacity data, a plurality of photovoltaic installed capacity data, and a plurality of thermal power installed capacity data;

[0026] A combination module, configured to combine the plurality of wind power installed capacity data, the plurality of photovoltaic installed capacity data, and the plurality of thermal power installed capacity data to obtain N combinations; each of the N combinations includes one wind power installed capacity data, one photovoltaic installed capacity data, and one thermal power installed capacity data; N is an integer greater than 0;

[0027] A first determination module, configured to, for the kth combination, acquire the full-time output data of wind power, photovoltaic power, and thermal power corresponding to the kth combination; based on the full-time output data of wind power, photovoltaic power, and thermal power corresponding to the kth combination, determine the full-time average output curve of wind power, photovoltaic power, and thermal power corresponding to the kth combination; acquire the full-time DC power transmission curve, and determine the full-time average power transmission curve based on the full-time DC power transmission curve; k is an integer greater than 0 and less than N;

[0028] A second determination module, configured to determine the similarity factor between the full-time average output curve of wind power, photovoltaic power, and thermal power corresponding to the kth combination and the full-time average power transmission curve of the DC;

[0029] A third determination module, configured to determine, according to the similarity factors of the N combinations respectively, that the combinations corresponding to M similarity factors that meet the preset conditions are target combinations; M is an integer greater than 0 and less than N;

[0030] An evaluation module for comprehensively evaluating each of the M combinations according to multiple preset evaluation indicators to obtain the comprehensive evaluation index values of the combinations corresponding to the multiple similarity factors that meet the preset conditions;

[0031] A fourth determination module for determining an optimal combination based on the comprehensive evaluation index values of the combinations corresponding to the target combinations, and determining the optimal combination as the installed capacity configuration of wind power, photovoltaic power, and thermal power;

[0032] A compensation module for compensating the full-time output curves of the wind power, photovoltaic power, and thermal power with the energy storage power supply to make the full-time output curves of the wind power, photovoltaic power, and thermal power close to the full-time DC power transmission curve.

[0033] An evaluation module for comprehensively evaluating each of the M target combinations according to multiple preset evaluation indicators to obtain the comprehensive evaluation index values of the combinations corresponding to the multiple similarity factors that meet the preset conditions;

[0034] A fourth determination module for determining an optimal combination based on the comprehensive evaluation index values of the combinations corresponding to the target combinations, and determining the optimal combination as the installed capacity configuration of wind power, photovoltaic power, and thermal power;

[0035] A compensation module for compensating the full-time output curves of the wind power, photovoltaic power, and thermal power with the energy storage power supply to make the full-time output curves of the wind power, photovoltaic power, and thermal power close to the full-time DC power transmission curve.

[0036] According to an embodiment of the present application, the third determination module is specifically configured to:

[0037] Obtain a first threshold;

[0038] Compare the similarity factors of the N combinations with the first threshold respectively to obtain a comparison result;

[0039] For the j-th similarity factor, in response to the comparison result that the j-th similarity factor is greater than or equal to the first threshold, determine that the j-th similarity factor meets the preset conditions; j is an integer greater than 0 and less than M;

[0040] Determine the combinations corresponding to the M similarity factors that meet the preset conditions.

[0041] According to an embodiment of the present application, the multiple preset evaluation indicators include the base annual net income index value, the goodness-of-fit index value, and the new energy ratio index value; the evaluation module is specifically configured to:

[0042] For the k-th combination, based on the wind power installed capacity data, photovoltaic installed capacity data, and thermal power installed capacity data in the k-th combination, as well as the pre-constructed objective function and constraint conditions, determine the wind power output function, photovoltaic output function, and thermal power output function respectively;

[0043] Based on the wind power output function, photovoltaic output function, and thermal power output function, determine the annual net income index value, goodness-of-fit index value, and new energy proportion index value of the base for the k-th combination respectively;

[0044] Obtain the preset weight values of the annual net income index value, goodness-of-fit index value, and new energy proportion index value of the base respectively;

[0045] Based on the annual net income index value, goodness-of-fit index value, and new energy proportion index value of the base for the k-th combination and their respective preset weight values, determine the comprehensive index values of the multiple combinations respectively.

[0046] According to an embodiment of the present application, the compensation module is specifically used for:

[0047] Determine the output differences between the full-time output curves of the wind power, photovoltaic power, and thermal power and the output of the wind power, photovoltaic power, and thermal power at each same time period respectively;

[0048] Compensate each of the output differences at each same time period through the energy storage power supply amount, so that the output value of each time period in the full-time output curves of the wind power, photovoltaic power, and thermal power is close to the output value of the same time period in the DC full-time power transmission curve.

[0049] According to a third aspect of the embodiments of the present application, an electronic device is provided, including: a processor, and a memory communicatively connected to the processor;

[0050] The memory stores computer execution instructions;

[0051] The processor executes the computer execution instructions stored in the memory to implement the method as described in any one of the first aspects.

[0052] According to a fourth aspect of the embodiments of the present application, a computer-readable storage medium is provided, characterized in that computer execution instructions are stored in the computer-readable storage medium, and when the computer execution instructions are executed by a processor, they are used to implement the method as described in any one of the first aspects.

[0053] The technical solutions provided by the embodiments of the present application at least bring the following beneficial effects:

[0054] Through multi-time-scale hierarchical complementarity based on the complementary characteristics of the hourly average output of wind power and photovoltaic power throughout the whole time period, the complementary characteristics of wind power, photovoltaic power, and thermal power within a day, and the hourly-level complementary characteristics of wind power, photovoltaic power, thermal power, and energy storage; using a similarity factor function to evaluate the similarity between the average output curves of wind power, photovoltaic power, and thermal power throughout the whole time period and the average power transmission curve of the DC throughout the whole time period, and then evaluating the complementary effect of the hourly average output characteristics of wind and light throughout the whole time period; combining the time-series production simulation method and using the curve fitting goodness function to evaluate the peak shaving demand of the base, and combining the proportion of new energy power and the annual net income to evaluate the complementary effect of the characteristics of wind, light, and thermal power within a day. According to the evaluation results, the optimal configuration combination of the installed capacities of wind power, photovoltaic power, and thermal power is determined, realizing the mutual complementarity and coordinated mutual assistance of the outputs of different types of power sources such as thermal power, wind power, and photovoltaic power, and improving the economy of power supply.

[0055] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and do not limit this application. Brief Description of the Drawings

[0056] The drawings herein are incorporated into the specification and form a part of this specification, showing embodiments consistent with this application, and are used together with the specification to explain the principles of this application, and do not constitute an improper limitation to this application.

[0057] Figure 1 It is a flowchart of a method for hierarchical complementary allocation of the installed capacities of wind power, photovoltaic power, and thermal power in an embodiment of this application;

[0058] Figure 2 It is a structural block diagram of a device for hierarchical complementary allocation of the installed capacities of wind power, photovoltaic power, and thermal power in an embodiment of this application;

[0059] Figure 3 It is a block diagram of an electronic device in an embodiment of this application. Detailed Description of the Embodiments

[0060] In order to enable those of ordinary skill in the art to better understand the technical solutions of this application, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the drawings.

[0061] It should be noted that the terms "first", "second", etc. in the specification and claims of this application and the above drawings are used to distinguish similar objects, and do not necessarily need to describe a specific order or sequence. It should be understood that such used data can be interchanged under appropriate circumstances so that the embodiments of this application described here can be implemented in an order other than those illustrated or described here. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. On the contrary, they are only examples of devices and methods consistent with some aspects of this application as detailed in the appended claims.

[0062] It should be noted that in the related technologies, the comprehensive efficiency of the power system is not high, and deep-seated contradictions such as insufficient coordination among the power generation, grid, and load links and insufficient complementarity and mutual assistance among various power sources are becoming increasingly prominent. There is an urgent need for overall optimization to improve the utilization level of clean energy and the operating efficiency of the power system, and to better guide the planning and development of the power source bases at the sending end and the coordinated interaction among the power generation, grid, load, and energy storage. The multi-energy complementary characteristic means that the power outputs of different types of power sources such as thermal power, wind power, and photovoltaic power can complement each other and coordinate with each other. Under the background of the construction of a new power system, to greatly increase the proportion of the power supply of new energy power, multi-energy complementary development is of even greater significance.

[0063] Based on the above problems, the present application proposes a method and device for complementary configuration of the installed capacities of a wind-solar-thermal-energy-storage integrated energy system. Through multi-time-scale hierarchical complementarity based on the complementary characteristics of the hourly average power outputs of wind power and photovoltaic power throughout the day, the intra-day characteristics of wind power, photovoltaic power, and thermal power, and the hourly characteristics of wind power, photovoltaic power, thermal power, and energy storage; using a similarity factor function to evaluate the similarity between the hourly average power output curves of wind power, photovoltaic power, and thermal power throughout the day and the DC hourly average power transmission curve throughout the day, and then evaluating the complementary effect of the hourly average power output characteristics of wind and solar power throughout the day; combining with the chronological production simulation method and using a curve fitting goodness function to evaluate the peak shaving demand of the base, and combining with the proportion of new energy power and the annual net income to evaluate the intra-day complementary effect of wind-solar-thermal power. According to the evaluation results, the optimal configuration combination of the installed capacities of wind power, photovoltaic power, and thermal power is determined, realizing that the power outputs of different types of power sources such as thermal power, wind power, and photovoltaic power can complement each other and coordinate with each other, and improving the economy of power supply.

[0064] It should be noted that the DC curve usually takes into account the power sources of the sending-end system and the load conditions of the receiving-end system. Referring to the power transmission curve of the already put into operation UHV DC, the DC curve has certain seasonal characteristics and shows the characteristics of being high during the day and low at night. The wind power output is mainly affected by factors such as wind speed, and has certain seasonal characteristics and intra-day fluctuation characteristics, but generally shows a trend of being high at night and low at noon. The photovoltaic power output is mainly affected by factors such as light intensity and temperature, and also has certain seasonal characteristics and intra-day volatility characteristics, but generally shows a trend of being low at night and high at noon. Therefore, by analyzing and adjusting the complementary characteristics of the hourly average power output of wind and solar power throughout the day, the overall power output characteristics of the base (the comprehensive processing characteristics of wind power, photovoltaic power, and thermal power) can be made similar to the trend of the DC curve, meeting the overall power demand of the DC curve for the energy base, and determining the overall installed capacity of the energy base and the preliminary power source configuration.

[0065] Figure 1 It is a flowchart of a method for complementary configuration of the installed capacities of wind power, photovoltaic power, and thermal power in an embodiment of the present application.

[0066] As Figure 1As shown, the method and device for the hierarchical complementary configuration of the installed capacity of the integrated wind-solar-thermal-energy storage system include:

[0067] Step 110, respectively obtain multiple wind power installed capacity data, multiple photovoltaic installed capacity data, and multiple thermal power installed capacity data.

[0068] Step 120, combine the multiple wind power installed capacity data, multiple photovoltaic installed capacity data, and multiple thermal power installed capacity data to obtain N combinations.

[0069] Among them, in the embodiments of the present application, the N combinations respectively include one wind power installed capacity data, one photovoltaic installed capacity data, and one thermal power installed capacity data; N is an integer greater than 0.

[0070] Step 130, for the kth combination, obtain the full-time output data of wind power, photovoltaic power, and thermal power corresponding to the kth combination; based on the full-time output data of wind power, photovoltaic power, and thermal power corresponding to the kth combination, determine the full-time average output curve of wind power, photovoltaic power, and thermal power corresponding to the kth combination; obtain the full-time DC power transmission curve, and determine the full-time average DC power transmission curve based on the full-time DC power transmission curve; k is an integer greater than 0 and less than N.

[0071] Among them, in the embodiments of the present application, k is an integer greater than 0 and less than N.

[0072] As a possible example, the 8760-hour (annual) output data of wind power and photovoltaic power under the specified installed capacity can be obtained according to the wind measurement and light measurement data of the kth combination, and the full-time average output curves of wind power and photovoltaic power after accumulating the output per hour throughout the year can be calculated; add the full-time average output curves of wind power and photovoltaic power to the average output curve of the thermal power unit to obtain the full-time average output curve of wind power, photovoltaic power, and thermal power (i.e., the full-time average output curve of the energy base), and obtain the pre-calculated full-time average DC power transmission curve.

[0073] Optionally, the 8760-hour output curves of wind power and photovoltaic power under the given installed capacity can be obtained according to the 8760-hour wind measurement data of the wind measurement tower in the planned area and the 8760-hour light measurement data of the light measurement station, combined with the power curves of wind turbines and photovoltaic generators. This curve is the above-mentioned full-time output data of wind power, photovoltaic power, and thermal power. It can be understood that the 8760-hour output data of wind power and photovoltaic power under the specified installed capacity can be obtained according to the wind measurement and light measurement data, and the average value after accumulating the output per hour throughout the year can be calculated to obtain the full-time average output curves of wind power and photovoltaic power; considering the average output of the thermal power unit, the full-time average output curve of thermal power can be obtained.

[0074] Step 140: Determine the similarity factor between the full-time average output curves of wind power, photovoltaic power, and thermal power and the full-time average power transmission curve of direct current corresponding to the k-th combination.

[0075] As a possible example, the similarity factor F2 is a curve similarity comparison parameter of a simple model-independent method. By calculating the differences between two curves at each time point, it measures the similarity between the two curves. Its principle is based on the basic assumption of curve equivalence, and the equivalence evaluation is carried out with the minimum sum of the squares of the cumulative errors. The higher the value of the similarity factor F2, the more similar the two curves are. When the two curves coincide, F2 is the limit value of 100. The specific expression formula is:

[0076]

[0077] In the formula, n is the number of sampling time points, and the value is 24. R t is the data value of the reference curve (the full-time average power transmission curve of direct current) at time t, and T t is the data value of the curve to be compared (the full-time average output curves of wind power, photovoltaic power, and thermal power, that is, the full-time average output curve of the energy base) at time t.

[0078] For example, under different installed capacities of wind, light, and fire, according to the 8760-hour output data of wind power and photovoltaic power, and considering 50% of the installed capacity for the average output of thermal power units, the similarity factor F2 between the full-time average output curve of the energy base and the full-time average power transmission curve of direct current is calculated as shown in Table 1.

[0079] Table 1 Similarity factor between the full-time average output curves of the energy base and direct current power transmission

[0080]

[0081]

[0082] From the analysis of the similarity factor results in Table 1, the overall installed capacity of the energy base and the preliminary power source configuration are as follows: the installed capacity of thermal power is 2000 MW, and the total installed capacity of new energy (that is, the sum of the installed capacity of wind power and photovoltaic power) is approximately in the range of 5000 MW - 7000 MW. Among them, when the installed capacity of wind power is greater than that of photovoltaic power, a better matching effect will be achieved.

[0083] Step 150: According to the similarity factors of each of the N combinations, determine that the combinations corresponding to M similarity factors that meet the preset conditions are the target combinations.

[0084] In some embodiments of the present application, step 105 includes:

[0085] Step 151: Obtain the first threshold.

[0086] It can be understood that the first threshold can be a preset threshold and can be determined according to actual requirements.

[0087] Step 152: Compare the similarity factors of each of the N combinations with the first threshold respectively to obtain a comparison result.

[0088] Step 153: For the j-th similarity factor, in response to the comparison result that the j-th similarity factor is greater than or equal to the obtained first threshold, determine that the j-th similarity factor meets the preset condition; j is an integer greater than 0 and less than M.

[0089] As an example of a possible implementation, if the comparison result is that the j-th similarity factor is greater than or equal to the obtained first threshold, it indicates that the full-time average output curves of wind power, photovoltaic power, and thermal power have a relatively high similarity with the full-time average power transmission curve of DC, and the overall satisfaction degree of the energy base for the power transmission electricity quantity of the DC curve is relatively high; if the comparison result is that the j-th similarity factor is less than the obtained first threshold, it indicates that the full-time average output curves of wind power, photovoltaic power, and thermal power have a relatively low similarity with the full-time average power transmission curve of DC, and the overall satisfaction degree of the energy base for the power transmission electricity quantity of the DC curve is relatively low.

[0090] Step 154: Determine the combinations corresponding to each of the M similarity factors that meet the preset condition as the target combinations.

[0091] Wherein, in the embodiments of the present application, M is an integer greater than 0 and less than N.

[0092] It can be understood that the similarity factors are solved for each of the N combinations, and the similarity factors of M combinations among the N combinations meet the preset condition.

[0093] Step 160: Conduct a comprehensive evaluation of each of the M target combinations according to multiple preset evaluation indicators to obtain the comprehensive evaluation index values corresponding to each of the target combinations.

[0094] In some embodiments of the present application, the multiple preset evaluation indicators include the annual net income index value of the base, the goodness-of-fit index value, and the new energy proportion index value. Step 160 includes:

[0095] Step 161: For the k-th combination, respectively determine the wind power output function, the photovoltaic power output function, and the thermal power output function based on the wind power installed capacity data, the photovoltaic power installed capacity data, and the thermal power installed capacity data in the k-th combination, as well as the pre-constructed objective function and constraint conditions.

[0096] Step 162: Based on the wind power output function, the photovoltaic power output function, and the thermal power output function, respectively determine the annual net income index value of the base, the goodness-of-fit index value, and the new energy proportion index value of the k-th combination.

[0097] Among them, in the embodiments of the present application, the goodness-of-fit index value is used to evaluate the goodness of fit between the total function obtained by adding the wind power output function, the photovoltaic power output function, and the thermal power output function and the DC full-time average power transmission curve. The larger the goodness-of-fit value, the better the fitting degree between the above total function and the DC full-time average power transmission curve.

[0098] Among them, in the embodiments of the present application, the new energy proportion index value is used to evaluate the proportion of wind power and photovoltaic power output in the total output of wind power, photovoltaic power, and thermal power. The larger the proportion, the higher the economy of the combination.

[0099] As a possible example, under the specified installed capacity of wind, light, and fire, time-series production simulation is carried out according to the 8760-hour output data of wind power, photovoltaic power, and DC transmission curves:

[0100] Step a: With the goal of maximizing the consumption of new energy power, construct an objective function:

[0101]

[0102] Among them: T represents the total length of the simulation sequence time; t is the simulation time step; P w (t) is the wind power output function at time period t, and P pv (t) is the photovoltaic power output function at time period t.

[0103] Step b: Set the constraint conditions of the objective function:

[0104] (1) Power balance constraint

[0105]

[0106] Among them, P t (t) is the DC curve outgoing power function at time period t; P g,i (t) is the output function of the i-th thermal power unit in the base at time period t, and I is the number of all thermal power units in the base; Δe(t) is the power exchanged between the base and the AC power grid at time period t.

[0107] (2) Thermal power unit operation constraint

[0108] β i P g,i,max ≤P g,i ≤95%P g,i,max

[0109] -R g,i,down *ΔT≤P g,i,t+1 -P g,i,t ≤R g,i,up *ΔT

[0110] Among them, P g,i,maxis the maximum output of the \(i\)-th thermal power unit; \(\beta\) i is the peak shaving depth of the \(i\)-th thermal power unit; \(P\) g,i,t+1 , \(P\) g,i,t are the outputs of the \(i\)-th thermal power unit at the \((t + 1)\)-th moment and the \(t\)-th moment respectively, \(R\) g,i,down , \(R\) g,i,up are the maximum downward and upward ramping rates per unit time of the \(i\)-th thermal power unit respectively.

[0111] (3) New energy output constraint

[0112] \(0\leq P\) w (t)\(\leq P\) w * (t)

[0113] \(0\leq P\) pv (t)\(\leq P\) pv * (t)

[0114] Among them, \(P\) w * (t) is the wind power time series output function when the installed capacity is constant in period \(t\); \(P\) pv * (t) is the photovoltaic time series output function when the installed capacity is constant in period \(t\).

[0115] Step c: Determine the annual net income index value, goodness-of-fit index value and new energy proportion index value of the \(k\)-th combination respectively:

[0116] (1) Calculate the annual net income GAIN of the base.

[0117]

[0118]

[0119]

[0120]

[0121] Among them, \(G_2\) is the annual power generation income, \(G_1\) is the annual cost; \(\Omega\) is the benchmark on-grid price of coal-fired power generation, and the wind power, photovoltaic power and thermal power supporting the UHVDC base adopt unified electricity price accounting; \(A\) w is the annual unit capacity cost of wind power, \(G\) w is the installed capacity of wind power; \(A\) pv is the annual unit capacity cost of photovoltaic power, \(G\) pv is the installed capacity of photovoltaic power; \(A\) t is the annual unit capacity cost of thermal power units, \(G\) t is the total installed capacity of thermal power units; \(C\) i,cois the fuel cost of the i-th thermal power unit, and a, b, and c are the cost coefficients of the thermal power unit; C i,cl is the ramping cost of the i-th thermal power unit, and γ is the ramping cost factor of the thermal power unit.

[0122] (2) Evaluate the ability of the base's total output to track the DC curve in the 8760-hour sequence.

[0123] The goodness of fit of the curve is used for evaluation. The goodness of fit refers to the degree of fitting of the regression line to the observed values. The larger the goodness-of-fit value, the better the degree of fitting of the regression line to the observed values. The goodness of fit R 2 The expression is:

[0124]

[0125] In the formula, is the average value of the power transmitted by the DC curve in the simulated time series.

[0126] (3) Calculate the proportion of new energy.

[0127]

[0128] Step 163: Obtain the preset weight values of the annual net income index value, goodness-of-fit index value, and new energy proportion index value of the base respectively.

[0129] It can be understood that the preset weight values of the annual net income index value, goodness-of-fit index value, and new energy proportion index value of the base can be preset according to actual needs.

[0130] Step 164: Based on the annual net income index value, goodness-of-fit index value, and new energy proportion index value of the k-th combination and their respective preset weight values, determine the comprehensive index values of each of the multiple combinations.

[0131] As a possible example, multiply the annual net income index value, goodness-of-fit index value, and new energy proportion index value of the k combinations by their respective preset weight values and then add them up to obtain the comprehensive index values of each of the multiple combinations.

[0132] Step 170: Based on the comprehensive evaluation index values corresponding to the target combinations, determine the optimal combination, and determine the optimal combination as the installed capacity configuration of wind power, photovoltaic power, and thermal power.

[0133] As a possible example, select the combination with the largest comprehensive index value among the comprehensive index values of the multiple combinations, determine the combination as the optimal combination, and determine the optimal combination as the installed capacity configuration of wind power, photovoltaic power, and thermal power.

[0134] Step 180: Compensate the full-time output curves of the wind power, photovoltaic power, and thermal power with the energy storage power supply to make the full-time output curves of the wind power, photovoltaic power, and thermal power close to the full-time DC power transmission curve.

[0135] In some embodiments of the present application, Step 180 includes:

[0136] Respectively determine the output differences between the full-time output curves of the wind power, photovoltaic power, and thermal power at each same time period; compensate each of the output differences at each same time period with the energy storage power supply respectively, so that the output value of each time period in the full-time output curves of the wind power, photovoltaic power, and thermal power is close to the output value of the same time period in the full-time DC power transmission curve. It can be understood that after determining the optimal combined installed capacity of wind power, photovoltaic power, and thermal power, utilize the flexible adjustment ability of the energy storage to smooth the volatility of the output curves of wind power and photovoltaic power, and realize the complementarity between the comprehensive output of wind power, photovoltaic power, and thermal power and the adjustable characteristics of the energy storage. According to the energy storage investment cost and the power generation benefits brought by the energy storage, comprehensively weigh to obtain the configured power and capacity of the energy storage.

[0137] For example, the installed capacity of thermal power in one of the M combinations is configured as 2000 MW, the deep peak shaving capacity is set to 25%, the up and down adjustment rate of thermal power is set to 1.5% of the installed capacity per minute, the installed capacity of wind power is configured as 4500 MW, and the installed capacity of photovoltaic power is configured as 1500 MW. Conduct time-series production simulation. During the period of large-scale new energy generation, try to reduce the output of thermal power units as much as possible. During the period of small-scale new energy generation, thermal power units provide the maximum power generation capacity support.

[0138] Consider different combinations of installed capacities of wind, light, and fire for time-series production simulation. Only relying on the comprehensive output of wind, light, and fire under various combinations cannot fully fit the full-time DC average power transmission curve in the 8760-hour time series, and there are certain phenomena of wind abandonment and power shortage. By calculating the goodness of fit, the proportion of new energy power, and the annual net income of the full-time output curves of wind power, photovoltaic power, and thermal power in the 8760-hour time series and the full-time DC average power transmission curve, it is finally determined that when the total installed capacity of new energy is 6000 MW and the wind-light ratio is in the range of 1.0 to 3, it has better comprehensive effects. Therefore, for this full-time DC average power transmission curve, the recommended optimal planned installed capacity is 4000 MW for the installed capacity of wind power, 2000 MW for the installed capacity of photovoltaic power, and 2000 MW for the installed capacity of thermal power.

[0139] According to the method and device for hierarchical complementary configuration of the installed capacity of a wind-solar-thermal-storage integrated energy system according to an embodiment of the present application, through multi-time-scale hierarchical complementarity based on the complementary characteristics of the hourly average output of wind power and photovoltaic power throughout the whole time period, the complementary characteristics of wind power, photovoltaic power, and thermal power within a day, and the hourly characteristics of wind power, photovoltaic power, thermal power, and energy storage; using a similarity factor function to evaluate the similarity between the full-time average output curves of wind power, photovoltaic power, and thermal power and the full-time average power transmission curve of direct current, and then evaluating the complementary effect of the hourly average output characteristics of wind power and photovoltaic power throughout the whole time period; combining the time-series production simulation method and using a curve fitting goodness function to evaluate the peak shaving demand of the base, and combining the proportion of new energy electricity and the annual net income to evaluate the complementary effect of the within-day characteristics of wind power, photovoltaic power, and thermal power. According to the evaluation results, the optimal configuration combination of the installed capacities of wind power, photovoltaic power, and thermal power is determined, realizing the mutual complementarity and coordinated mutual assistance of the outputs of different types of power sources such as thermal power, wind power, and photovoltaic power, and improving the economy of power supply.

[0140] Figure 2 It is a structural block diagram of a device for hierarchical complementary configuration of the installed capacities of wind power, photovoltaic power, and thermal power in an embodiment of the present application.

[0141] As Figure 2 shown, a method and device for hierarchical complementary configuration of the installed capacity of a wind-solar-thermal-storage integrated energy system include:

[0142] An acquisition module 201, configured to respectively acquire a plurality of wind power installed capacity data, a plurality of photovoltaic power installed capacity data, and a plurality of thermal power installed capacity data;

[0143] A combination module 202, configured to combine the plurality of wind power installed capacity data, the plurality of photovoltaic power installed capacity data, and the plurality of thermal power installed capacity data to obtain N combinations; each of the N combinations includes one wind power installed capacity data, one photovoltaic power installed capacity data, and one thermal power installed capacity data; N is an integer greater than 0;

[0144] A first determination module 203, configured to, for the kth combination, acquire the full-time output data of wind power, photovoltaic power, and thermal power corresponding to the kth combination, and respectively determine the full-time historical average output curve and the full-time output curve of wind power, photovoltaic power, and thermal power corresponding to the kth combination; acquire the full-time power transmission curve of direct current, and determine the full-time average power transmission curve based on the full-time power transmission curve of direct current; k is an integer greater than 0 and less than N;

[0145] A second determination module 204, configured to determine the similarity factor between the full-time average output curves of wind power, photovoltaic power, and thermal power corresponding to the kth combination and the full-time average power transmission curve of direct current;

[0146] The third determination module 205 is configured to determine, according to the similarity factors of the N combinations respectively, that the combinations corresponding to the M similarity factors meeting the preset conditions are target combinations; M is an integer greater than 0 and less than N;

[0147] The evaluation module 206 is configured to comprehensively evaluate the M target combinations respectively according to a plurality of preset evaluation indexes, so as to obtain the comprehensive evaluation index values of the target combinations respectively;

[0148] The fourth determination module 207 is configured to determine an optimal combination based on the comprehensive evaluation index values of the combinations corresponding to the target combinations respectively, and determine the optimal combination as the installed capacity configuration of wind power, photovoltaic power and thermal power;

[0149] The compensation module 208 is configured to compensate the full-time output curves of the wind power, photovoltaic power and thermal power by using the energy storage power supply amount, so that the full-time output curves of the wind power, photovoltaic power and thermal power are close to the full-time DC power transmission curve. In some embodiments of the present application, the third determination module 205 is specifically configured to: obtain a first threshold; compare the similarity factors of the N combinations respectively with the first threshold to obtain comparison results; for the jth similarity factor, in response to the comparison result that the jth similarity factor is greater than or equal to the obtained first threshold, determine that the jth similarity factor meets the preset conditions; j is an integer greater than 0 and less than M; determine the combinations corresponding to the M similarity factors meeting the preset conditions as target combinations.

[0150] In some embodiments of the present application, the plurality of preset evaluation indexes include the base annual net income index value, the goodness-of-fit index value and the new energy proportion index value; the evaluation module 206 is specifically configured to: for the kth combination, based on the wind power installed capacity data, photovoltaic power installed capacity data and thermal power installed capacity data in the kth combination, as well as the pre-constructed objective function and constraint conditions, determine the wind power output function, photovoltaic power output function and thermal power output function respectively; based on the wind power output function, photovoltaic power output function and thermal power output function, determine the base annual net income index value, goodness-of-fit index value and new energy proportion index value of the kth combination respectively; obtain the preset weight values of the base annual net income index value, goodness-of-fit index value and new energy proportion index value respectively; determine the comprehensive index values of the plurality of combinations based on the base annual net income index value, goodness-of-fit index value and new energy proportion index value of the kth combination and their respective preset weight values.

[0151] In some embodiments of the present application, the compensation module 208 is specifically configured to:

[0152] Determine the full-time output curves of wind power, photovoltaic power, and thermal power respectively, as well as the output differences of the full-time output curves of wind power, photovoltaic power, and thermal power in each same time period; compensate each output difference in each same time period by the energy storage power supply respectively, so that the output value of each time period in the full-time output curves of wind power, photovoltaic power, and thermal power is close to the output value of the same time period in the full-time DC power transmission curve.

[0153] According to the wind power, photovoltaic power, and thermal power installed capacity echelon complementary matching device of the embodiment of the present application, through multi-time scale echelon complementary based on the complementary of the full-time hourly average output characteristics of wind power and photovoltaic power, the complementary of the intraday characteristics of wind power, photovoltaic power, and thermal power, and the complementary of the hourly characteristics of wind power, photovoltaic power, thermal power, and electricity storage; use the similarity factor function to evaluate the similarity between the full-time average output curves of wind power, photovoltaic power, and thermal power and the full-time average power transmission curve of DC, and then evaluate the complementary effect of the full-time hourly average output characteristics of wind and light; combined with the time series production simulation method, use the curve fitting goodness function to evaluate the base peak shaving demand, and combined with the new energy electricity proportion and the annual net income, evaluate the complementary effect of the intraday characteristics of wind, light, and fire. According to the evaluation results, determine the optimal configuration combination of wind power, photovoltaic power, and thermal power installed capacity, realizing the mutual complementation and coordinated mutual assistance of the output of different types of power sources such as thermal power, wind power, and photovoltaic power, and improving the economy of power supply.

[0154] Figure 3 It is a block diagram of an electronic device in the embodiment of the present application. As Figure 3 shown, the electronic device may include: a transceiver 31, a processor 32, and a memory 33.

[0155] The processor 32 executes the computer execution instructions stored in the memory, so that the processor 32 executes the solutions in the above embodiments. The processor 32 may be a general-purpose processor, including a central processing unit CPU, a network processor (NP), etc.; it may also be a digital signal processor DSP, an application specific integrated circuit ASIC, a field programmable gate array FPGA or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0156] The memory 33 is connected to the processor 32 through the system bus and completes the communication between each other. The memory 33 is used to store computer program instructions.

[0157] The transceiver 31 may be used to obtain the task to be run and the configuration information of the task to be run.

[0158] The system bus can be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The system bus can be divided into an address bus, a data bus, a control bus, etc. For the sake of simplicity, only a thick line is used in the figure to represent it, but it does not mean that there is only one bus or one type of bus. The transceiver is used to implement communication between the database access device and other computers (such as clients, read-write libraries, and read-only libraries). The memory may include Random Access Memory (RAM), and may also include non-volatile memory.

[0159] The electronic device provided by the embodiments of this application can be the terminal device of the above embodiments.

[0160] The embodiments of this application also provide a chip for running instructions. The chip is used to execute the technical solutions of the message processing method in the above embodiments.

[0161] The embodiments of this application also provide a computer-readable storage medium. Computer instructions are stored in the computer-readable storage medium. When the computer instructions run on a computer, the computer is made to execute the technical solutions of the message processing method in the above embodiments.

[0162] The embodiments of this application also provide a computer program product. The computer program product includes a computer program, which is stored in a computer-readable storage medium. At least one processor can read the computer program from the computer-readable storage medium. When at least one processor executes the computer program, the technical solutions of the message processing method in the above embodiments can be implemented.

[0163] Those skilled in the art will readily conceive of other embodiments of this application after considering the specification and practicing the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application, which follow the general principles of this application and include common general knowledge or conventional technical means in the technical field not disclosed in this application. The specification and embodiments are only regarded as exemplary, and the true scope and spirit of this application are pointed out by the following claims.

[0164] It should be understood that this application is not limited to the exact structures described above and shown in the drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is only limited by the appended claims.

Claims

1. A method for hierarchical complementary configuration of installed capacity of a wind-solar-thermal-storage integrated energy system, characterized in that The method includes: Obtaining multiple wind power installed capacity data, multiple photovoltaic installed capacity data, and multiple thermal power installed capacity data respectively; Combining the multiple wind power installed capacity data, multiple photovoltaic installed capacity data, and multiple thermal power installed capacity data to obtain N combinations; each of the N combinations includes one wind power installed capacity data, one photovoltaic installed capacity data, and one thermal power installed capacity data; N is an integer greater than 0; For the kth combination, obtaining the full-time output data of wind power, photovoltaic power, and thermal power corresponding to the kth combination; based on the full-time output data of wind power, photovoltaic power, and thermal power corresponding to the kth combination, determining the full-time average output curve of wind power, photovoltaic power, and thermal power corresponding to the kth combination; obtaining the full-time DC power transmission curve, and determining the full-time average DC power transmission curve based on the full-time DC power transmission curve; k is an integer greater than 0 and less than N; Determining the similarity factor between the full-time average output curve of wind power, photovoltaic power, and thermal power corresponding to the kth combination and the full-time average DC power transmission curve; Comparing the similarity factors of the N combinations with a first threshold respectively to obtain comparison results; for the jth similarity factor, in response to the comparison result that the jth similarity factor is greater than or equal to the first threshold, determining that the jth similarity factor meets a preset condition; determining the combinations corresponding to the M similarity factors that meet the preset condition as target combinations; where M is an integer greater than 0 and less than N, and j is an integer greater than 0 and less than M; Comprehensively evaluating the M target combinations according to multiple preset evaluation indicators respectively to obtain the comprehensive evaluation index values of the target combinations; Based on the comprehensive evaluation index values of the target combinations, determining the optimal combination, and determining the optimal combination as the installed capacity configuration of wind power, photovoltaic power, and thermal power; Compensating the full-time output curves of wind power, photovoltaic power, and thermal power with the energy storage power supply amount to make the full-time output curves of wind power, photovoltaic power, and thermal power close to the full-time DC power transmission curve.

2. The method according to claim 1, characterized in that, The multiple preset evaluation indicators include the base annual net income index value, the goodness-of-fit index value, and the new energy proportion index value; the comprehensively evaluating the M target combinations according to multiple preset evaluation indicators respectively to obtain the comprehensive evaluation index values of the target combinations includes: For the jth combination, based on the wind power installed capacity data, photovoltaic power installed capacity data, and thermal power installed capacity data in the jth combination, and a pre-constructed objective function and constraint conditions, determining the wind power output function, photovoltaic power output function, and thermal power output function respectively; Based on the wind power output function, photovoltaic power output function, and thermal power output function, determining the base annual net income index value, the goodness-of-fit index value, and the new energy proportion index value of the jth combination respectively; Obtaining the preset weight values of the base annual net income index value, the goodness-of-fit index value, and the new energy proportion index value respectively; Based on the base annual net income index value, goodness-of-fit index value, and new energy proportion index value of the j-th combination, as well as their respective preset weight values, determine the comprehensive index value of each of the multiple combinations.

3. The method according to claim 1, characterized in that, The use of the energy storage power supply to compensate the full-time output curves of wind power, photovoltaic power, and thermal power, so that the full-time output curves of wind power, photovoltaic power, and thermal power are close to the full-time DC power transmission curve, includes: Respectively determine the output differences between the full-time output curves of wind power, photovoltaic power, and thermal power and the full-time output curve of DC power at each same time period; Use the energy storage power supply to compensate the output differences at each same time period one by one, so that the output value of each time period in the full-time output curves of wind power, photovoltaic power, and thermal power is close to the output value of the same time period in the full-time DC power transmission curve.

4. A device for hierarchical complementary configuration of installed capacities of a wind-solar-thermal-storage integrated energy system, characterized in that, The device includes: An acquisition module, configured to respectively acquire a plurality of wind power installed capacity data, a plurality of photovoltaic installed capacity data, and a plurality of thermal power installed capacity data; A combination module, configured to combine the plurality of wind power installed capacity data, the plurality of photovoltaic installed capacity data, and the plurality of thermal power installed capacity data to obtain N combinations; each of the N combinations respectively includes one wind power installed capacity data, one photovoltaic installed capacity data, and one thermal power installed capacity data; N is an integer greater than 0; A first determination module, configured to, for the k-th combination, acquire the full-time output data of wind power, photovoltaic power, and thermal power corresponding to the k-th combination; based on the full-time output data of wind power, photovoltaic power, and thermal power corresponding to the k-th combination, determine the full-time average output curves of wind power, photovoltaic power, and thermal power corresponding to the k-th combination; acquire the full-time DC power transmission curve, and determine the full-time average power transmission curve based on the full-time DC power transmission curve; k is an integer greater than 0 and less than N; A second determination module, configured to determine the similarity factor between the full-time average output curves of wind power, photovoltaic power, and thermal power corresponding to the k-th combination and the full-time average power transmission curve of DC power; A third determination module, configured to compare the similarity factors of each of the N combinations with a first threshold respectively to obtain a comparison result; for the j-th similarity factor, in response to the comparison result that the j-th similarity factor is greater than or equal to the first threshold, determine that the j-th similarity factor meets the preset condition; determine the combinations corresponding to the M similarity factors that meet the preset condition as target combinations; wherein, M is an integer greater than 0 and less than N, and j is an integer greater than 0 and less than M; An evaluation module, configured to respectively perform a comprehensive evaluation on the M target combinations according to a plurality of preset evaluation indicators to obtain the comprehensive evaluation index values of the combinations corresponding to the plurality of similarity factors that meet the preset condition; A fourth determination module, configured to determine the optimal combination based on the comprehensive evaluation index values of the combinations corresponding to the target combinations respectively, and determine the optimal combination as the installed capacity configuration of wind power, photovoltaic power, and thermal power; A compensation module, which is used to compensate the full-time output curves of the wind power, photovoltaic power, and thermal power with the energy storage power supply, so that the full-time output curves of the wind power, photovoltaic power, and thermal power are close to the full-time DC power transmission curve.

5. The device according to claim 4, characterized in that, The multiple preset evaluation indicators include the annual net income index value of the base, the goodness-of-fit index value, and the new energy proportion index value; the evaluation module is specifically used for: For the j-th combination, based on the wind power installed capacity data, photovoltaic installed capacity data, and thermal power installed capacity data in the j-th combination, as well as the pre-constructed objective function and constraint conditions, determine the wind power output function, photovoltaic output function, and thermal power output function respectively; Based on the wind power output function, photovoltaic output function, and thermal power output function, determine the annual net income index value of the base, the goodness-of-fit index value, and the new energy proportion index value of the j-th combination respectively; Obtain the preset weight values of the annual net income index value of the base, the goodness-of-fit index value, and the new energy proportion index value respectively; Based on the annual net income index value of the base, the goodness-of-fit index value, and the new energy proportion index value of the j-th combination and their respective preset weight values, determine the comprehensive index values of the multiple combinations respectively.

6. The device according to claim 4, characterized in that The compensation module is specifically used for: Determine the output differences between the full-time output curves of the wind power, photovoltaic power, and thermal power and the full-time output curve of the DC power at each same time period respectively; Compensate each of the output differences at each same time period with the energy storage power supply one by one, so that the output value of each time period in the full-time output curves of the wind power, photovoltaic power, and thermal power is close to the output value of the same time period in the full-time DC power transmission curve.

7. An electronic device, characterized in that, It includes: A processor and a memory communicatively connected to the processor; The memory stores computer execution instructions; The processor executes the computer execution instructions stored in the memory to implement the method according to any one of claims 1-3.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer execution instructions, and when the computer execution instructions are executed by the processor, they are used to implement the method according to any one of claims 1-3.

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