Capacity-load ratio selection method and device considering distributed power supply, and medium

Abstract

The invention relates to a capacity-load ratio selection method and device considering a distributed power supply, and a medium, and the method comprises the steps: collecting a real-time monitoring system and an actual planning target through an existing power system database, and obtaining the load data of each node of a power system and the output data of a new energy distributed power supply; and obtaining the capacity-load ratio based on the improved calculation method through the load data. The method comprises the following steps of: obtaining a distributed power supply coincidence rate g1, a distributed power supply average power factor g2, a distributed power supply installed capacity acceleration g3, a distributed power supply planning confidence capacity proportion eta i, a distributed power supply installed capacity proportion and a ratio rho of the maximum output of the distributed power supply to the maximum annual network supply load of a planning region through output data of a new energy distributed power supply; and further obtaining the credible capacity-generation ratio Rg considering the distributed power supply factor. And obtaining a new capacity-load ratio according to the capacity-load ratio in the S2 and the credible capacity-load ratio Rg in the S3. Under the condition that the distributed power supply is applied to the power system, the new capacity-load ratio under the conditions that the new energy proportion is large and the new energy power generation speed increase and the load development speed are unbalanced can be efficiently and reliably selected and obtained. Compared with the prior art, the method has the advantages of high efficiency, reliability, wide application range and the like.

Description

Technical Field

[0001] The present invention relates to the field of power systems, and in particular to a method, device and medium for selecting a capacity-load ratio taking into account distributed power sources. Background Art

[0002] With the continuous economic growth and the continuous advancement of urbanization, the demand for electricity is growing. And with the increasing prominence of environmental problems and the urgent need for sustainable development, the development and utilization of distributed power sources such as solar energy, wind energy, and hydropower have received attention. Due to the development of distributed power sources, the utilization pattern of power systems has been constantly changing, and distributed power sources have become a key force in promoting energy transformation. Traditional power systems mainly rely on fossil energy power generation, and their planning and design are usually based on relatively stable power supply characteristics. However, distributed power sources have the characteristics of intermittency, volatility, and uncertainty, which brings huge challenges to the stable operation and planning of power systems.

[0003] As an important indicator to measure the power supply capacity and planning rationality of the power system, the capacity load ratio plays an important role in the overall planning of the traditional power system. However, with the large-scale access of distributed power sources, the original method for determining the capacity load ratio can no longer fully adapt to the new situation. On the one hand, the unstable output of distributed power sources may cause the power system to have insufficient or excessive power supply in certain periods, which puts higher requirements on the compliance of the capacity load ratio value with the actual working conditions. On the other hand, the access of distributed power sources has changed the power flow distribution and load characteristics of the power system, and it is necessary to re-examine the role of the capacity load ratio in ensuring the reliability and economy of the system. Therefore, how to select the value of the power system capacity load ratio in a more suitable way for the actual working conditions of adding distributed power sources and improve the reliability and resource utilization of the power system is a technical problem that needs to be solved. Summary of the invention

[0004] The purpose of the present invention is to overcome the defects of the above-mentioned prior art and to provide a method, device and medium for selecting the capacity-load ratio taking into account distributed power sources. Through the existing power system database, real-time monitoring system and actual planning goals, and considering the distributed power sources to select the capacity-load ratio, the selected capacity-load ratio is more in line with the actual operating conditions of the power system in which distributed power sources are planned.

[0005] The purpose of the present invention can be achieved by the following technical solutions: According to one aspect of the present invention, a method for selecting a capacity-load ratio taking into account distributed power sources is provided, and the specific steps include: S1. Obtain the load data of each node in the power system and the output data of distributed power sources through the existing power system database, real-time monitoring system and actual planning targets, and use them as input; S2. Obtaining a capacity-load ratio based on an improved calculation method according to the input load data; S3. According to the input distributed power output data, the distributed power simultaneous rate is obtained. g 1 , average power factor of distributed power supply g 2 , Growth rate of installed capacity of distributed power generation g 3 , Distributed power planning confidence capacity ratio or i , Proportion of installed capacity of distributed power generation s i The ratio of the maximum output of distributed generation to the maximum annual grid load in the planned area r , and further obtain the credible capacity ratio considering distributed power factors R g ; S4. Obtain a new load-to-capacity ratio according to the load-to-capacity ratio in S2 and the trusted transmission ratio Rg in S3, and output the new load-to-capacity ratio.

[0006] Furthermore, in S3, based on the annual maximum output of distributed power sources in the statistical period in the region and the sum of the maximum output values ​​of all distributed power sources, the distributed power generation simultaneous rate is obtained. g 1 , the expression is: , in, P gmax is the annual maximum output of distributed power generation, ∑ P igmax It is the sum of the maximum output values ​​of all distributed power sources during the statistical period.

[0007] Furthermore, the average power factor of the distributed power generation in S3 is g 2 The expression is: , in, P g is the active power of distributed generation, S g is the apparent power of distributed power source, which is obtained from the collected data.

[0008] Furthermore, the growth rate of the installed capacity of distributed power generation in S3 is g 3 The expression is: g 3 = (1 +q ) p , in, q is the growth rate of distributed generation installed capacity, p It is the capacity reserve period.

[0009] Furthermore, the improved algorithm in S2 includes the transformer operation rate k ’ 3 The improvement of is expressed as: k ’ 3 = αk 3 (1-△ U ), in, α To reflect the low voltage side outgoing line of the substation N -1 line ratio; △ U is the voltage deviation coefficient; k 3 is the operating rate of the traditional transformer.

[0010] Furthermore, the improved algorithm in S2 includes the reserve coefficient k ’ 3 The improvement of is expressed as: , in, s The actual load density for detailed planning; s 0 is the average load density of the region, obtained from the existing power system database; r H is the load growth rate of the high solution; r M is the load growth rate of the medium solution; k 4 is the traditional reserve factor.

[0011] Furthermore, the Trusted Capacity Ratio Considering Distributed Generation Factors in S3 R g The expression is: , in, or i For the i The proportion of planning confidence capacity of the distributed generation considered in planning; d i For the i The proportion of the installed capacity of distributed power generation in the total installed capacity of distributed power generation; rIt is the ratio of the annual maximum output of distributed generation to the annual maximum load of the planned area, with an upper limit of 1; g 1 is the distributed power generation simultaneity rate; g 2 is the average power factor of distributed power source; g 3 The growth rate of installed capacity of distributed power generation; k 3 is the operating rate of the traditional transformer. i The planning confidence capacity ratio of distributed generation considered in planning or i It is derived from the annual maximum load, the annual maximum net load and the total installed capacity of distributed power sources, and the specific steps are: input the load and output data obtained from the power system database; obtain the annual net load curve and the annual output curve of distributed new energy in the planning area; superimpose the annual net load curve and the annual output curve of distributed new energy to obtain the annual load curve; calculate the difference between the annual maximum load without considering distributed new energy and the annual maximum net load considering distributed new energy as the first difference, calculate the ratio of the first difference to the installed capacity of distributed new energy; output the first difference. i The planning confidence capacity ratio of distributed generation considered in planning or i .

[0012] According to a second aspect of the present invention, there is provided an electronic device, comprising a memory and a processor, wherein a computer program is stored in the memory, and the method described above is implemented when the processor executes the program.

[0013] According to a third aspect of the present invention, there is provided a computer-readable storage medium having a computer program stored thereon, wherein the program implements the method described above when executed by a processor.

[0014] Compared with the prior art, the present invention has the following beneficial effects:

[0015] (1) Improving the efficiency and reliability of the power system: By comprehensively considering and quantifying the planning of distributed generation in the selection of the capacity-to-load ratio, the planning of the power system is made more efficient. By comprehensively considering the characteristics of distributed generation, the load demand of the power system, the reliability requirements and the development reserve and other factors, the selection of the capacity-to-load ratio is more in line with the actual working conditions, making the power system more reliable and stable. When a large number of distributed generation are configured in a region, the capacity-to-load ratio calculated by this method can avoid the problem of low utilization rate when the power output is less than the load demand, which leads to a decrease in the economic efficiency of the power grid operation, and can also avoid the situation where the power output far exceeds the load demand and causes equipment overload. It solves the problem that the distributed generation cannot clearly provide how much power supply capacity it can provide due to the volatility and randomness of the output during planning. At the same time, a reliable capacity-to-load ratio is defined. By calculating the reliable capacity-to-load ratio, part of the demand for the capacity-to-load ratio can be offset to improve the economy.

[0016] (2) Taking into account the possible imbalance in the growth rate of load and photovoltaic development, k 4 The reserve factor and g 3 The growth rate of distributed power generation installed capacity is taken into account in the calculation of capacity-load ratio and trusted capacity-generation ratio respectively. Since the development speed of photovoltaic power generation is faster than the load growth speed, when only the trusted capacity is calculated, it is generally used for short-term and ultra-short-term predictions, which cannot cover the long-term situation where the growth rates of load and power generation are different.

[0017] (3) Increase the scope of application: It is suitable for the planning of various types of distributed power sources. It can output relevant parameters according to the actual working conditions, so as to accurately obtain the capacity-load ratio that needs to be selected in different situations, thereby increasing the scope of application of the selection. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 A flow chart of a method for selecting a capacity-load ratio taking into account distributed power sources; Specific implementation

[0019] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0020] Example 1

[0021] like Figure 1 As shown in FIG. 1 , a method for selecting a capacity-load ratio taking into account distributed power sources is shown, and the specific steps include: S1. Obtain the load data and new energy power output data of each node in the power system through the existing power system database, real-time monitoring system and actual planning targets, and use them as input; S2. Obtaining a capacity-load ratio based on an improved calculation method according to the input load data; S3. According to the input distributed power output data, the distributed power simultaneous rate is obtained. g 1 , average power factor of distributed power supply g 2 , Growth rate of installed capacity of distributed power generation g 3 , Distributed power planning confidence capacity ratio or i , Proportion of installed capacity of distributed power generation s i The ratio of the maximum output of distributed generation to the maximum annual grid load in the planned area r , and further obtain the credible capacity ratio considering distributed power factors R g ; S4, based on the capacity ratio in S2 and the trusted capacity ratio in S3 R g The new capacity-load ratio is obtained and output. The load distribution coefficient in S2 is expressed as: , in, It is the sum of the maximum loads of each transformer, which is collected from the load data of each node by the real-time monitoring system; P max It is the maximum load of the grid, which is obtained from the historical data in the regional power system database.

[0022] The average power factor expression of S2 is: , in, P is the active power, S is the apparent power, which is obtained from the power system database.

[0023] The transformer operation rate expression of S2 is: k ’ 3 = αk 3 (1-△ U ), in, α To reflect the low voltage side outgoing line of the substation N -1 line ratio; △ U is the voltage deviation coefficient;k 3 is the traditional transformer operation rate, and the expression is: , in, K H is the short-time allowable overload rate of the transformer; N is the total number of transformers in the substation, which is determined by the actual situation of substations in the planning area and the planning objectives.

[0024] Load forecasting is generally based on growth rate. ),middle( ),Low( ) to cope with the uncertainty of load. In actual planning, the middle ( ) scheme. Uncertain reserve parameters for load development Used for detailed planning, based on the forecast plan and The specific calculation formula is as follows: ， When the predicted growth rate is low, the reserve coefficient should also have a lower limit as a development margin, which can be 1.15.

[0025] The reserve coefficient expression of S2 is: , in, s The actual load density for detailed planning; s 0 is the average load density of the region, which can be obtained from the existing power system database; the value of 1.15 is the lower limit of the reserve factor; r H A high scenario for load forecasting; r M It is the middle solution for load forecasting; k 4 is the traditional reserve coefficient, and its expression is: k 4 =h (1 +r ) p , in, r is the load growth rate, obtained by the load forecasting method; p The capacity reserve period; h is the load forecast correction factor, which is obtained by the deviation ratio between the load forecast growth rate and the actual growth rate.

[0026] The credible capacity ratio Rg of S3 taking into account distributed power generation factors: , in, or i For the i The proportion of planning confidence capacity of the distributed generation considered in planning; d i For the i The proportion of the installed capacity of distributed power generation in the total installed capacity of distributed power generation; r It is the ratio of the annual maximum output of distributed generation to the annual maximum load of the planned area, with an upper limit of 1; g 1 is the distributed power generation simultaneity rate; g 2 is the average power factor of distributed power source; g 3 The growth rate of installed capacity of distributed power generation; k 3 is the operation rate of the traditional transformer. Based on the annual maximum output of the distributed power source in the statistical period in the region and the sum of the maximum output values ​​of all distributed power sources, the distributed power source simultaneous rate is obtained. g 1 , the expression is: , in, P gmax is the annual maximum output of distributed power generation, ∑ P igmax It is the sum of the maximum output values ​​of all distributed power sources during the statistical period.

[0027] Average power factor of distributed power generation g 2 The expression is: , in, P g is the active power of distributed generation, S g is the apparent power of distributed power source, which is obtained from the collected data.

[0028] Growth rate of installed capacity of distributed power generation The expression is: = (1 +q ) p , in, q is the growth rate of distributed generation installed capacity, p It is the capacity reserve period.

[0029] No. iThe planning confidence capacity ratio of distributed generation considered in planning or i It is derived from the annual maximum load, annual maximum net load and total installed capacity of distributed power sources. The specific steps are: input the load and output data obtained from the power system database; obtain the annual net load curve and the annual output curve of distributed new energy in the planning area; superimpose the annual net load curve and the annual output curve of distributed new energy to obtain the annual load curve; calculate the difference between the annual maximum load without considering distributed new energy and the annual maximum net load considering distributed new energy as the first difference, calculate the ratio of the first difference to the installed capacity of distributed new energy; output the first difference. i The planning confidence capacity ratio of distributed generation considered in planning or i .

[0030] Distributed power generation confidence capacity ratio or i You can also use the Monte Carlo simulation method to calculate, the steps include: According to different renewable energy generation, the probability distribution function of the output power of distributed power generation is determined: When the renewable energy power generation is wind power, its output power usually obeys the Weibull distribution, and the probability density function is: , in, x is the normalized wind power, k is the shape parameter, λ is the scale parameter; When the renewable energy power generation is photovoltaic power generation, the output power obeys the Beta distribution, and the probability density function is, , in, x is the normalized photovoltaic output power, α and β are the parameters of the Beta distribution, C is the gamma function; Perform random sampling according to the probability distribution function of the output power of the distributed power source; Draw samples from a Weibull distribution X The formula is:

[0031] For the Beta distribution, sampling is done through a random number generator.

[0032] After each sampling, the sampled distributed power samples are substituted into the power system flow calculation, and the system load loss probability ( LOL The load of the system is L t, the conventional power capacity is C , the output power of the distributed power supply is P DG,t i , if the following holds: , A load loss event is considered to have occurred. N In the sampling, the number of load failures is n LOLP , then the load loss probability is: , According to the system reliability requirements, such as requiring the load loss probability to be less than a certain value (such as , It is usually a smaller value, and the specific value is set according to the actual indicator requirements). The confidence capacity of the distributed power supply is determined by statistically analyzing the sampling results.

[0033] Under the condition of meeting the reliability requirements, the capacity of conventional power supply that can be replaced by distributed power generation is , we can gradually increase the capacity assumptions of distributed power sources and re-run Monte Carlo simulation and system status assessment until the reliability requirements are met. For example, starting from a smaller distributed power capacity, increase the step size each time and perform simulation calculations. At this time, is the confidence capacity of the distributed power supply. Its calculation formula can be expressed as: , The ratio of the distributed power confidence capacity to the total capacity is the planned confidence capacity ratio. or i .

[0034] The total capacity ratio expression selected by S4 is: , in, k 1 is the load distribution coefficient; k 2 is the average power factor; k ’ 3 For improved transformer operation rate; k ’ 4 is the improved reserve factor; R g The replaceable partial capacity load ratio is the credible capacity-generation ratio that takes into account the impact of distributed power sources.

[0035] Table 1 shows the selected values ​​of the capacity-load ratio obtained by the traditional method, and Table 2 shows the selected values ​​of the new capacity-load ratio obtained in this embodiment. From the comparison between Table 1 and Table 2, it can be seen that the recommended capacity-load ratio of this embodiment is more in line with the actual working conditions and has stronger stability, reliability and economy.

[0036] Table 1 Selected values ​​of capacity-load ratio obtained by traditional methods

[0037] Table 2 Selected values ​​of capacity-load ratio obtained by the method of this embodiment

[0038] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the described module can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here. Example 2

[0039] The electronic device of the present invention includes a central processing unit (CPU), which can perform various appropriate actions and processes according to computer program instructions stored in a read-only memory (ROM) or loaded from a storage unit into a random access memory (RAM). In the RAM, various programs and data required for the operation of the device can also be stored. The CPU, ROM and RAM are connected to each other through a bus. An input / output (I / O) interface is also connected to the bus.

[0040] Multiple components in the device are connected to the I / O interface, including: input units, such as keyboards, mice, etc.; output units, such as various types of displays, speakers, etc.; storage units, such as disks, optical disks, etc.; and communication units, such as network cards, modems, wireless communication transceivers, etc. The communication unit allows the device to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunication networks. The processing unit performs the various methods and processes described above, such as the method of the present invention. For example, in some embodiments, the method of the present invention may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit. In some embodiments, part or all of the computer program may be loaded and / or installed on the device via ROM and / or a communication unit. When the computer program is loaded into RAM and executed by the CPU, one or more steps of the method of the present invention described above may be performed. Alternatively, in other embodiments, the CPU may be configured to perform the method of the present invention in any other appropriate manner (e.g., by means of firmware).

[0041] The functions described above herein may be performed at least in part by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), and the like.

[0042] The program code for implementing the method of the present invention can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code can be executed entirely on the machine, partially on the machine, partially on the machine as a stand-alone software package and partially on a remote machine, or entirely on a remote machine or server.

[0043] In the context of the present invention, a machine-readable medium may be a tangible medium that may contain or store a program for use by an instruction execution system, device or equipment or used in combination with an instruction execution system, device or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0044] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed by the present invention, and these modifications or replacements should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A method for selecting a capacity-load ratio taking into account distributed power sources, characterized in that: The specific steps include: S1. Obtain the load data of each node in the power system and the output data of distributed power sources through the existing power system database, real-time monitoring system and actual planning targets, and use them as input; S2. Obtaining a capacity-load ratio based on an improved calculation method according to the input load data; S3. According to the input distributed power output data, the distributed power simultaneous rate is obtained. g 1 , average power factor of distributed power supply g 2 , Growth rate of installed capacity of distributed power generation g 3 , Distributed power planning confidence capacity ratio η i , Proportion of installed capacity of distributed power generation σ i The ratio of the maximum output of distributed generation to the maximum load of the planned regional grid supply in an annual period ρ , and further obtain the credible capacity ratio considering distributed power factors R g ; S4, based on the capacity ratio in S2 and the trusted capacity ratio in S3 R g Get the new capacity ratio and output the new capacity ratio.

2. A method for selecting a capacity-load ratio taking into account distributed power sources according to claim 1, characterized in that: In S3, based on the annual maximum output of distributed power sources in the statistical period in the region and the sum of the maximum output values ​​of all distributed power sources, the distributed power generation simultaneous rate is obtained. g 1 , the expression is: ， in, P gmax is the annual maximum output of distributed power generation, ∑ P igmax It is the sum of the maximum output values ​​of all distributed power sources during the statistical period.

3. A method for selecting a capacity-load ratio taking into account distributed power sources according to claim 1, characterized in that: The average power factor of the distributed power supply in S3 g 2 The expression is: ， in, P g is the active power of distributed generation, S g is the apparent power of distributed power source, which is obtained from the collected data.

4. A method for selecting a capacity-load ratio taking into account distributed power sources according to claim 1, characterized in that: The growth rate of distributed generation installed capacity in S3 g 3 The expression is: g 3 = (1 +q ) p ， in, q is the growth rate of distributed generation installed capacity, p It is the capacity reserve period.

5. The method for selecting a capacity-load ratio taking into account distributed power sources according to claim 1, characterized in that: The improved algorithm in S2 includes the following steps: k ’ 3 The improvement of is expressed as: k ’ 3 = αk 3 (1-△ U )， in, α To reflect the low voltage side outgoing line of the substation N -1 line ratio; △ U is the voltage deviation coefficient; k 3 is the operating rate of the traditional transformer.

6. A method for selecting a capacity-load ratio taking into account distributed power sources according to claim 1, characterized in that: The improved algorithm in S2 includes the following steps: k ’ 4 The improvement of is expressed as: ， in, σ The actual load density for detailed planning; σ 0 is the average load density of the region, obtained from the existing power system database; r H is the load growth rate of the high solution; r M is the load growth rate of the medium solution; k 4 is the traditional reserve factor.

7. A method for selecting a capacity-load ratio taking into account distributed power sources according to claim 1, characterized in that: The credible capacity ratio of S3 taking into account the distributed power generation factor R g The expression is: ， in, η i For the i The proportion of planning confidence capacity of the distributed generation considered in planning; δ i For the i The proportion of the installed capacity of distributed power generation in the total installed capacity of distributed power generation; ρ It is the ratio of the annual maximum output of distributed generation to the annual maximum load of the planned area, with an upper limit of 1; g 1 is the distributed power generation simultaneity rate; g 2 is the average power factor of distributed power source; g 3 The growth rate of installed capacity of distributed power generation; k 3 is the operating rate of the traditional transformer.

8. A method for selecting a capacity-load ratio taking into account distributed power sources according to claim 7, characterized in that: The said i The planning confidence capacity ratio of distributed generation considered in planning η i It is derived from the annual maximum load, annual maximum net load and total installed capacity of distributed generation. The specific steps are: Input the load and output data obtained from the power system database; obtain the annual net load curve and the annual output curve of distributed new energy in the planning area; superimpose the annual net load curve and the annual output curve of distributed new energy to obtain the annual load curve; calculate the difference between the annual maximum load without considering the distributed new energy and the annual maximum net load considering the distributed new energy as the first difference, and calculate the ratio of the first difference to the installed capacity of distributed new energy; Output i The planning confidence capacity ratio of distributed generation considered in planning η i .

9. An electronic device comprising a memory and a processor, wherein a computer program is stored in the memory, wherein: When the processor executes the program, the method according to any one of claims 1 to 8 is implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 8 is implemented.

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