Evaluation method and device of wind and light energy storage system based on carbon emission reduction

Abstract

The invention provides a method and a device for evaluating a wind and light energy storage system based on carbon emission reduction, and belongs to the field of wind and light energy storage systems. The method comprises the following steps: acquiring electrical parameters of a to-be-evaluated wind and light energy storage system; the electrical parameters comprise installed capacity, power grid parameters and working parameters, the installed capacity comprises wind power installed capacity, photovoltaic installed capacity and energy storage capacity, and the power grid parameters comprise wind power generation data and photovoltaic power generation data in a target historical time period; the working parameters comprise the average power of photovoltaic power generation in a target historical time period, the average power of wind power generation in the target historical time period, the load demand in the target historical time period, the output power of energy storage in the target historical time period and the consumption in the target historical time period; and inputting the electrical parameters into a pre-constructed evaluation model to obtain an evaluation result of the to-be-evaluated wind and light energy storage system. According to the method, the wind-solar energy storage system can be accurately evaluated.

Description

Technical Field

[0001] The present invention relates to the technical field of wind-solar energy storage systems, and particularly to an evaluation method and device for a wind-solar energy storage system based on carbon emission reduction. Background Art

[0002] With the continuous strengthening of people's awareness of environmental protection, new energy power generation such as wind power generation and photovoltaic power generation has the characteristics of rich resources, cleanliness, renewable and low carbon, and has received extensive attention.

[0003] The overall goal of the development of the wind-solar energy storage system is to improve the new energy utilization rate, reliability and economy of the wind-solar energy storage system through the complementary coordination between wind power, solar power and energy storage, so as to achieve the maximum utilization of clean energy. However, the proportion of the wind-solar energy storage system in the power grid is increasing continuously, and the highly uncertain wind power generation and photovoltaic power generation pose great challenges to energy security at various time and space scales.

[0004] At present, although there are also evaluations of the wind-solar energy storage system, the existing evaluation methods mainly focus on the evaluation carried out for maximizing benefits, and do not consider the overall performance of the integrated operation of wind-solar energy storage, resulting in the existing evaluation methods being unable to meet the current evaluation requirements. Summary of the Invention

[0005] Embodiments of the present invention provide an evaluation method and device for a wind-solar energy storage system based on carbon emission reduction to solve the problem that the current evaluation method is inaccurate.

[0006] In a first aspect, embodiments of the present invention provide an evaluation method for a wind-solar energy storage system based on carbon emission reduction, including:

[0007] Obtain the electrical parameters of the wind-solar energy storage system to be evaluated; wherein, the electrical parameters include installed capacity, grid parameters and operating parameters, the installed capacity includes wind power installed capacity, photovoltaic installed capacity and energy storage capacity, the grid parameters include wind power generation data and photovoltaic power generation data within a target historical period, and the operating parameters include the average power of photovoltaic power generation within a target historical period, the average power of wind power generation within a target historical period, the load demand within a target historical period, the output power of the energy storage within a target historical period, and the accommodation within a target historical period;

[0008] Input the electrical parameters into a pre-constructed evaluation model to obtain an evaluation result of the wind-solar energy storage system to be evaluated; wherein, the evaluation model includes a carbon emission reduction calculation module, a system load power outage rate calculation module, a system peak shaving performance calculation module and an output volatility calculation module.

[0009] In a possible implementation manner, the output volatility calculation module determines an output volatility score based on the wind power installed capacity, the photovoltaic installed capacity, the wind power generation data and the photovoltaic power generation data within a target historical period.

[0010] The system load power shortage rate calculation module determines the power shortage rate score based on the average power of photovoltaic power generation, the average power of wind power generation, and the load demand within the target historical period.

[0011] The system peak shaving performance calculation module determines the peak shaving performance score based on the wind power installed capacity, the photovoltaic power installed capacity, the energy storage capacity, the per-unit value of photovoltaic output, the per-unit value of wind power output, the output power of the energy storage, and the consumption within the target historical period.

[0012] The carbon emission reduction amount calculation module determines the carbon emission reduction score based on the photovoltaic power generation data, the photovoltaic power generation carbon emission reduction factor, the wind power generation data, and the wind power generation carbon emission reduction factor within the target historical period.

[0013] In a possible implementation, the photovoltaic power generation carbon emission reduction factor is determined based on the photovoltaic power generation carbon emission factor and the grid carbon emission factor in the photovoltaic power generation installation area.

[0014] The wind power generation carbon emission reduction factor is determined based on the wind power generation carbon emission factor and the grid carbon emission factor in the wind power generation installation area.

[0015] In a possible implementation, the output fluctuation calculation module converts the wind power generation data and the photovoltaic power generation data within the target historical period into a wind power output sequence L W and a photovoltaic output sequence L G , and the output fluctuation score F 1 is:

[0016] F 1 = std(N) + X(N);

[0017] where N = αL W + βL G , α + β = 1, α is the wind power installation ratio, β is the photovoltaic power installation ratio, std(N) is the standard deviation of sequence N, and X(N) is the range of sequence N.

[0018] The power shortage rate score F 2 is:

[0019] F 2 = (T 需 - T 风 - T 光 )Δt;

[0020] where T 需 is the load demand in the target historical period t, T 风 is the average power of wind power generation in the target historical period t, T光 The average power of photovoltaic power generation in the target historical period t, and Δt is the sampling frequency within the statistical time;

[0021] The peak shaving performance score F 3 is:

[0022]

[0023] where C WG = M×(αP W +βP G ), C WG is the total output of wind and light in the target historical period t, P 2 is the output power of the energy storage in the target historical period t, C X is the accommodation in the target historical period t, M is the total installed capacity of wind and light, α + β = 1, α is the proportion of wind power installed capacity, β is the proportion of photovoltaic power installed capacity, P W is the per-unit value of wind power output in the target historical period t, P G is the per-unit value of photovoltaic power output in the target historical period t.

[0024] In a possible implementation, the carbon emission reduction score F 4 is:

[0025] F 4 = εT 1 +θT 2 ;

[0026] where ε is the carbon emission reduction factor of photovoltaic power generation, θ is the carbon emission reduction factor of wind power generation, T 1 is the photovoltaic power generation amount in the target historical period, T 2 is the wind power generation amount in the target historical period.

[0027] In a possible implementation, input the electrical parameters into a pre-constructed evaluation model to obtain the evaluation result of the wind-light energy storage system to be evaluated, including:

[0028] Input the electrical parameters into the evaluation model, and output the scores of the wind-light energy storage system to be evaluated; among them, each score respectively includes the carbon emission reduction score, the power outage rate score, the peak shaving performance score, and the output fluctuation score;

[0029] Based on each score and the preset evaluation criteria, determine the evaluation result of the wind-light energy storage system to be evaluated; among them, the preset evaluation criteria include the carbon emission reduction evaluation criteria, the power outage rate evaluation criteria, the peak shaving performance evaluation criteria, and the output fluctuation evaluation criteria.

[0030] In a possible implementation, based on each score and the preset evaluation criteria, determine the evaluation result of the wind-light energy storage system to be evaluated, including:

[0031] Based on the carbon emission reduction score and the carbon emission reduction evaluation criteria, determine the carbon emission reduction score value;

[0032] Based on the power shortage rate score and the power shortage rate evaluation criteria, determine the power shortage rate score value;

[0033] Based on the peak shaving performance score and the peak shaving performance evaluation criteria, determine the peak shaving performance score value;

[0034] Based on the output power fluctuation score and the output power fluctuation evaluation criteria, determine the output power fluctuation score value;

[0035] Based on the carbon emission reduction score value, the power shortage rate score value, the peak shaving performance score value and the output power fluctuation score value, determine the evaluation result of the wind-solar energy storage system to be evaluated.

[0036] In a possible implementation manner, each calculation module in the evaluation model is correspondingly provided with a preset weight;

[0037] Input the electrical parameters into the pre-constructed evaluation model to obtain the evaluation result of the wind-solar energy storage system to be evaluated, including:

[0038] Input the electrical parameters into the evaluation model, and based on the first results of each calculation module and the preset weights of each calculation module, obtain the evaluation result of the wind-solar energy storage system to be evaluated; wherein, the first result is the result obtained after normalizing the output results of all calculation modules.

[0039] In a second aspect, an embodiment of the present invention provides an evaluation device for a wind-solar energy storage system based on carbon emission reduction, including:

[0040] An acquisition module, configured to acquire the electrical parameters of the wind-solar energy storage system to be evaluated; wherein, the electrical parameters include the installed capacity, grid parameters and working parameters, the installed capacity includes the installed capacity of wind power, the installed capacity of photovoltaic power and the energy storage capacity, the grid parameters include the wind power generation data and photovoltaic power generation data within the target historical period, and the working parameters include the average power of photovoltaic power generation within the target historical period, the average power of wind power generation within the target historical period, the load demand within the target historical period, the output power of the energy storage within the target historical period, and the consumption within the target historical period;

[0041] An evaluation module, configured to input the electrical parameters into the pre-constructed evaluation model to obtain the evaluation result of the wind-solar energy storage system to be evaluated; wherein, the evaluation model includes a carbon emission reduction amount calculation module, a system load power shortage rate calculation module, a system peak shaving performance calculation module and an output power volatility calculation module.

[0042] In a possible implementation manner, the output power volatility calculation module determines the output power fluctuation score based on the installed capacity of wind power, the installed capacity of photovoltaic power, the wind power generation data and photovoltaic power generation data within the target historical period;

[0043] The system load power shortage rate calculation module determines the power shortage rate score based on the average power of photovoltaic power generation, the average power of wind power generation, and the load demand during the target historical period.

[0044] The system peak shaving performance calculation module determines the peak shaving performance score based on the installed capacity of wind power, the installed capacity of photovoltaic power, the energy storage capacity, the per-unit value of photovoltaic output, the per-unit value of wind power output, the output power of the energy storage during the target historical period, and the accommodation during the target historical period.

[0045] The carbon emission reduction calculation module determines the carbon emission reduction score based on the photovoltaic power generation data, the photovoltaic power generation carbon emission reduction factor, the wind power generation data, and the wind power generation carbon emission reduction factor during the target historical period.

[0046] An embodiment of the present invention provides an evaluation method for a wind-solar energy storage system based on carbon emission reduction. By obtaining the electrical parameters of the wind-solar energy storage system to be evaluated, and in order to accurately and comprehensively evaluate the wind-solar energy storage system, the obtained electrical parameters include the installed capacity, grid parameters, and working parameters. After obtaining the electrical parameters, the electrical parameters can be input into a pre-constructed evaluation model to obtain the evaluation result of the wind-solar energy storage system to be evaluated. Among them, the evaluation model includes a carbon emission reduction calculation module, a system load power shortage rate calculation module, a system peak shaving performance calculation module, and an output fluctuation calculation module. The evaluation model comprehensively and accurately evaluates the wind-solar energy storage system to be evaluated from four aspects: carbon emission reduction, system load power shortage rate, system peak shaving performance, and output fluctuation, and the evaluation is more comprehensive, thus realizing the accurate evaluation of the wind-solar energy storage system. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for use in the embodiments or the description of the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0048] Figure 1 is the implementation flowchart of the evaluation method for the wind-solar energy storage system based on carbon emission reduction provided by the embodiment of the present invention;

[0049] Figure 2 is the structural schematic diagram of the evaluation device for the wind-solar energy storage system based on carbon emission reduction provided by the embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0050] In the following description, specific details such as specific system architectures and technologies are presented for the purpose of illustration rather than limitation, so as to thoroughly understand the embodiments of the present invention. However, those skilled in the art should clearly understand that the present invention can also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid unnecessary details from interfering with the description of the present invention.

[0051] To make the objectives, technical solutions, and advantages of the present invention clearer, the following will be described through specific embodiments in conjunction with the accompanying drawings.

[0052] With the rapid development of new energy, the installed capacity of the wind-solar energy storage system is also continuously expanding. As a result, the balancing difficulty of the wind-solar energy storage system and the adjustment cost of the system are also continuously rising. How to accurately evaluate the wind-solar energy storage system has become an urgent problem to be solved currently.

[0053] Figure 1 The implementation flowchart of the evaluation method for the wind-solar energy storage system based on carbon emission reduction provided by the embodiments of the present invention is described in detail as follows:

[0054] S110. Obtain the electrical parameters of the wind-solar energy storage system to be evaluated.

[0055] Among them, the electrical parameters include installed capacity, grid parameters, and operating parameters. The installed capacity includes wind power installed capacity, photovoltaic installed capacity, and energy storage capacity. The grid parameters include wind power generation data and photovoltaic power generation data within a target historical period. The operating parameters include the average power of photovoltaic power generation within a target historical period, the average power of wind power generation within a target historical period, the load demand within a target historical period, the output power of the energy storage within a target historical period, and the consumption within a target historical period.

[0056] The installed capacity can be determined according to the installed capacity at the time of the construction of the wind-solar energy storage system.

[0057] The grid parameters can be obtained from the monitoring platform of the wind-solar energy storage system for the wind power generation data and photovoltaic power generation data within a target historical period.

[0058] The operating parameters can also be obtained from the monitoring platform of the wind-solar energy storage system for the average power of photovoltaic power generation within a target historical period, the average power of wind power generation within a target historical period, the load demand within a target historical period, the output power of the energy storage within a target historical period, and the consumption within a target historical period.

[0059] S120. Input the electrical parameters into a pre-constructed evaluation model to obtain the evaluation result of the wind-solar energy storage system to be evaluated.

[0060] The evaluation model includes a carbon emission reduction calculation module, a system load power outage rate calculation module, a system peak shaving performance calculation module, and an output volatility calculation module.

[0061] In some embodiments, the output volatility calculation module may determine an output volatility score based on the wind power installed capacity, the photovoltaic power installed capacity, the wind power generation data, and the photovoltaic power generation data within a target historical period.

[0062] The system load power outage rate calculation module determines a power outage rate score based on the average power of photovoltaic power generation, the average power of wind power generation, and the load demand within a target historical period.

[0063] The system peak shaving performance calculation module determines a peak shaving performance score based on the wind power installed capacity, the photovoltaic power installed capacity, the energy storage capacity, the per-unit value of photovoltaic output, the per-unit value of wind power output, the output power of the energy storage, and the consumption within a target historical period.

[0064] The carbon emission reduction calculation module determines a carbon emission reduction score based on the photovoltaic power generation data, the photovoltaic power generation carbon emission reduction factor, the wind power generation data, and the wind power generation carbon emission reduction factor within a target historical period.

[0065] In this embodiment, the photovoltaic power generation carbon emission reduction factor is determined based on the photovoltaic power generation carbon emission factor and the grid carbon emission factor of the photovoltaic power generation installation area.

[0066] The wind power generation carbon emission reduction factor is determined based on the wind power generation carbon emission factor and the grid carbon emission factor of the wind power generation installation area.

[0067] Specifically, the photovoltaic power generation carbon emission reduction factor can be calculated based on the calculation formula of the photovoltaic power generation carbon emission reduction factor, the photovoltaic power generation carbon emission factor, and the grid carbon emission factor of the installation area.

[0068] The calculation formula for the photovoltaic power generation carbon emission reduction factor is:

[0069]

[0070] Among them, α is the photovoltaic power generation carbon emission reduction factor of the installation area, F 1 is the grid carbon emission factor of the installation area, P 1 is the proportion of photovoltaic power generation in the total power generation of the installation area, F 2 is the photovoltaic power generation carbon emission factor, F 3 is the carbon emission generated by photovoltaic power generation, F 4 is the photovoltaic power generation amount.

[0071] Specifically, the carbon emission reduction factor of wind power generation can be calculated based on the calculation formula of the carbon emission reduction factor of wind power generation, the carbon emission factor of wind power generation, and the carbon emission factor of the power grid in the installation area.

[0072] The calculation formula for the carbon emission reduction factor of wind power generation is:

[0073]

[0074] Among them, β is the carbon emission reduction factor of wind power generation in the installation area, F 1 is the carbon emission factor of the power grid in the installation area, P 2 is the proportion of wind power generation in the total power generation in the installation area, F 5 is the carbon emission factor of wind power generation, F 6 is the carbon emission amount generated by wind power generation, F 7 is the wind power generation.

[0075] In some embodiments, the output volatility calculation module converts the wind power generation data and photovoltaic power generation data in the target historical period into a wind power output sequence L W and a photovoltaic output sequence L G , and the output fluctuation score F 1 is:

[0076] F 1 = std(N) + X(N);

[0077] Among them, N = αL W + βL 1 , α + β = 1, α is the wind power installation ratio, β is the photovoltaic installation ratio, std(N) is the standard deviation of the sequence N, and X(N) is the range of the sequence N. N is the wind-solar output sequence converted based on the wind-solar power generation characteristic curves of typical days in each season during the historical period, L W is the output sequence converted based on the wind power generation characteristic curves of typical days in each season during the historical period, L G is the output sequence converted based on the photovoltaic power generation characteristic curves of typical days in each season during the historical period, and std(N) is the standard deviation of the sequence N.

[0078] The power shortage rate score F 2 is:

[0079] F 2 = (T 需 - T 风 - T 光 )Δt;

[0080] Among them, T 需 is the load demand at time t in the target historical period, T 风 is the average power of wind power generation at time t in the target historical period, T光 The average power of photovoltaic power generation in the target historical period t, and Δt is the sampling frequency within the statistical time.

[0081] Peaking performance score F 3 is:

[0082]

[0083] where C WG = M×(αP W +βP G ), C WG is the total output of wind and light in the target historical period t, P 2 is the output power of the energy storage in the target historical period t, C X is the accommodation in the target historical period t, M is the total installed capacity of wind and light, α + β = 1, α is the proportion of wind power installed capacity, β is the proportion of photovoltaic power installed capacity, P W is the per-unit value of wind power output in the target historical period t, P G is the per-unit value of photovoltaic power output in the target historical period t.

[0084] Carbon emission reduction score F 4 is:

[0085] F 4 = εT 1 + θT 2 ;

[0086] where ε is the carbon emission reduction factor of photovoltaic power generation, θ is the carbon emission reduction factor of wind power generation, T 1 is the photovoltaic power generation amount in the target historical period, T 2 is the wind power generation amount in the target historical period.

[0087] In some embodiments, first, electrical parameters can be input into the evaluation model to output the scores of the wind-solar energy storage system to be evaluated. Among them, the scores respectively include the carbon emission reduction score, the power outage rate score, the peaking performance score, and the output fluctuation score. Then, based on the scores and the preset evaluation criteria, the evaluation result of the wind-solar energy storage system to be evaluated is determined. Among them, the preset evaluation criteria include the carbon emission reduction evaluation criteria, the power outage rate evaluation criteria, the peaking performance evaluation criteria, and the output fluctuation evaluation criteria.

[0088] In this embodiment, the carbon emission reduction score can be determined based on the carbon emission reduction score and the carbon emission reduction evaluation criteria, the power outage rate score can be determined based on the power outage rate score and the power outage rate evaluation criteria, the peaking performance score can be determined based on the peaking performance score and the peaking performance evaluation criteria, the output fluctuation score can be determined based on the output fluctuation score and the output fluctuation evaluation criteria, and the evaluation result of the wind-solar energy storage system to be evaluated can be determined based on the carbon emission reduction score, the power outage rate score, the peaking performance score, and the output fluctuation score.

[0089] Specifically, after obtaining the electrical parameters, based on the relevant parameters obtained, according to the calculation formula of the carbon emission reduction factor for photovoltaic power generation and calculate the carbon emission reduction factor α for photovoltaic power generation. In addition, according to the calculation formula of the carbon emission reduction factor for wind power generation and calculate the carbon emission reduction factor β for wind power generation.

[0090] Next, the output volatility calculation module will convert the wind power generation data and photovoltaic power generation data in the target historical period into the wind power output sequence L W and the photovoltaic power output sequence L G respectively based on the obtained wind power installed capacity, photovoltaic installed capacity, wind power generation data and photovoltaic power generation data in the target historical period. Then, according to the calculation formula of the output fluctuation score F 1 F 1 = std(N) + X(N), the output fluctuation score F 1 can be determined.

[0091] Secondly, the system load power shortage rate calculation module will be based on the average power of photovoltaic power generation, the average power of wind power generation, and the load demand in the target historical period obtained, and according to the calculation formula of the power shortage rate score F 2 F 2 = (T 需 - T 风 - T 光 )Δt, the power shortage rate score F 2 can be determined.

[0092] Again, the system peak shaving performance calculation module will be based on the obtained wind power installed capacity, photovoltaic installed capacity, energy storage capacity, per-unit value of photovoltaic power output, per-unit value of wind power output, output power of energy storage in the target historical period, and consumption in the target historical period, and according to the calculation formula of the peak shaving performance score F 3 C C WG = M×(αP W + βP G ), the carbon emission reduction factor α for photovoltaic power generation and the carbon emission reduction factor β for wind power generation, calculate the peak shaving performance score F 3 can be determined.

[0093] Next, the carbon emission reduction amount calculation module will be based on the obtained photovoltaic power generation data, carbon emission reduction factor for photovoltaic power generation, wind power generation data, carbon emission reduction factor for wind power generation in the target historical period, and the carbon emission reduction score F 4Calculation formula of F 4 = εT 1 + θT 2 , and the carbon emission reduction score F is calculated 4 .

[0094] Finally, according to the carbon emission reduction score F 4 and the carbon emission reduction evaluation criteria, the carbon emission reduction score value is determined. Based on the power shortage rate score F 2 and the power shortage rate evaluation criteria, the power shortage rate score value is determined. Based on the peak shaving performance score F 3 and the peak shaving performance evaluation criteria, the peak shaving performance score value is determined. Based on the output power fluctuation score F 1 and the output power fluctuation evaluation criteria, the output power fluctuation score value is determined. Finally, the evaluation model will determine the evaluation result of the wind-solar energy storage system to be evaluated based on the carbon emission reduction score value, the power shortage rate score value, the peak shaving performance score value, and the output power fluctuation score value.

[0095] In some embodiments, each calculation module in the evaluation model is correspondingly provided with a preset weight. The setting of the preset weight can be determined according to the importance of the carbon emission reduction amount calculation module, the system load power shortage rate calculation module, the system peak shaving performance calculation module, and the output power fluctuation calculation module in the evaluation model.

[0096] In this embodiment, the electrical parameters can be input into the evaluation model, and based on the first results of each calculation module and the preset weights of each calculation module, the evaluation result of the wind-solar energy storage system to be evaluated is obtained. Among them, the first result is the result obtained after normalizing the output results of all calculation modules.

[0097] Specifically, in this embodiment, the carbon emission reduction factor α of photovoltaic power generation, the carbon emission reduction factor β of wind power generation, the output power fluctuation score F 1 , the power shortage rate score F 2 , the peak shaving performance score F 3 and the carbon emission reduction score F 4 are all the same as the above calculation methods. After obtaining the output power fluctuation score F 1 , the power shortage rate score F 2 , the peak shaving performance score F 3 and the carbon emission reduction score F 4 , the output power fluctuation score F 1 , the power shortage rate score F 2 , the peak shaving performance score F 3 and the carbon emission reduction score F 4 are normalized to obtain the first results of each calculation module.

[0098] Finally, the evaluation model will obtain the evaluation result of the wind-solar energy storage system to be evaluated based on the preset weights of the carbon emission reduction calculation module, the system load power shortage rate calculation module, the system peak shaving performance calculation module, and the output power fluctuation calculation module, as well as the first result corresponding to each calculation module.

[0099] The evaluation method provided by the present invention obtains the electrical parameters of the wind-solar energy storage system to be evaluated. In order to accurately and comprehensively evaluate the wind-solar energy storage system, the obtained electrical parameters include installed capacity, grid parameters, and operating parameters. After obtaining the electrical parameters, the electrical parameters can be input into a pre-constructed evaluation model to obtain the evaluation result of the wind-solar energy storage system to be evaluated. Among them, the evaluation model includes a carbon emission reduction calculation module, a system load power shortage rate calculation module, a system peak shaving performance calculation module, and an output power fluctuation calculation module. The evaluation model comprehensively and accurately evaluates the wind-solar energy storage system to be evaluated from four aspects: carbon emission reduction, system load power shortage rate, system peak shaving performance, and output power fluctuation, and the evaluation is more comprehensive, thus realizing the accurate evaluation of the wind-solar energy storage system.

[0100] It should be understood that the magnitudes of the sequence numbers of the steps in the above embodiments do not mean the order of execution. The execution order of each process should be determined according to its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.

[0101] The following is an apparatus embodiment of the present invention. For the details not described in detail therein, reference may be made to the corresponding method embodiment above.

[0102] Figure 2 The structural schematic diagram of the evaluation apparatus for a wind-solar energy storage system based on carbon emission reduction provided by an embodiment of the present invention is shown. For the sake of convenience of description, only the parts related to the embodiment of the present invention are shown and are described in detail as follows:

[0103] As Figure 2 shown, the evaluation apparatus 200 for a wind-solar energy storage system based on carbon emission reduction includes:

[0104] An acquisition module 210, configured to acquire the electrical parameters of the wind-solar energy storage system to be evaluated; wherein, the electrical parameters include installed capacity, grid parameters, and operating parameters. The installed capacity includes wind power installed capacity, photovoltaic installed capacity, and energy storage capacity. The grid parameters include wind power generation data and photovoltaic power generation data within a target historical period. The operating parameters include the average power of photovoltaic power generation within a target historical period, the average power of wind power generation within a target historical period, the load demand within a target historical period, the output power of the energy storage within a target historical period, and the accommodation within a target historical period;

[0105] An evaluation module 220 is configured to input electrical parameters into a pre-constructed evaluation model to obtain an evaluation result of the wind-solar energy storage system to be evaluated; wherein, the evaluation model includes a carbon emission reduction calculation module, a system load power shortage rate calculation module, a system peak shaving performance calculation module, and an output volatility calculation module.

[0106] In a possible implementation manner, the output volatility calculation module determines an output volatility score based on the wind power installed capacity, the photovoltaic installed capacity, the wind power generation data, and the photovoltaic power generation data within a target historical period.

[0107] The system load power shortage rate calculation module determines a power shortage rate score based on the average power of photovoltaic power generation, the average power of wind power generation, and the load demand within a target historical period.

[0108] The system peak shaving performance calculation module determines a peak shaving performance score based on the wind power installed capacity, the photovoltaic installed capacity, the energy storage capacity, the per-unit value of photovoltaic output, the per-unit value of wind power output, the output power of the energy storage, and the consumption within a target historical period.

[0109] The carbon emission reduction calculation module determines a carbon emission reduction score based on the photovoltaic power generation data, the photovoltaic power generation carbon emission reduction factor, the wind power generation data, and the wind power generation carbon emission reduction factor within a target historical period.

[0110] In a possible implementation manner, the photovoltaic power generation carbon emission reduction factor is determined based on the photovoltaic power generation carbon emission factor and the power grid carbon emission factor of the photovoltaic power generation installation area.

[0111] The wind power generation carbon emission reduction factor is determined based on the wind power generation carbon emission factor and the power grid carbon emission factor of the wind power generation installation area.

[0112] In a possible implementation manner, the output volatility calculation module respectively converts the wind power generation data and the photovoltaic power generation data within a target historical period into a wind power output sequence L W and a photovoltaic output sequence L G , and the output volatility score F 1 is:

[0113] F 1 = std(N) + X(N);

[0114] wherein, N = αL W + βL G , α + β = 1, α is the wind power installation ratio, β is the photovoltaic installation ratio, std(N) is the standard deviation of the sequence N, and X(N) is the range of the sequence N.

[0115] The power shortage rate score F2 is:

[0116] F 2 =(T 需 - T 风 - T 光 )Δt;

[0117] Wherein, T 需 is the load demand of the target historical period t, T 风 is the average power of wind power generation in the target historical period t, T 光 is the average power of photovoltaic power generation in the target historical period t, and Δt is the sampling frequency within the statistical time;

[0118] The peak shaving performance score F 3 is:

[0119]

[0120] Wherein, C WG = M×(αP W + βP G ), C WG is the total output of wind and light in the target historical period t, P 2 is the output power of the energy storage in the target historical period t, C X is the accommodation in the target historical period t, M is the total installed capacity of wind and light, α + β = 1, α is the proportion of wind power installed capacity, β is the proportion of photovoltaic installed capacity, P W is the per-unit value of wind power output in the target historical period t, P G is the per-unit value of photovoltaic power output in the target historical period t.

[0121] In a possible implementation, the carbon emission reduction score F 4 is:

[0122] F 4 = εT 1 + θT 2 ;

[0123] Wherein, ε is the carbon emission reduction factor of photovoltaic power generation, θ is the carbon emission reduction factor of wind power generation, T 1 is the photovoltaic power generation amount in the target historical period, T 2 is the wind power generation amount in the target historical period.

[0124] In a possible implementation, the evaluation module 220 is configured to input electrical parameters into an evaluation model and output various scores of the wind-solar energy storage system to be evaluated; wherein, the various scores respectively include a carbon emission reduction score, a power outage rate score, a peak shaving performance score, and an output fluctuation score;

[0125] Based on each score and the preset evaluation criteria, determine the evaluation result of the wind-solar energy storage system to be evaluated; wherein, the preset evaluation criteria include carbon emission reduction evaluation criteria, power outage rate evaluation criteria, peak shaving performance evaluation criteria, and output fluctuation evaluation criteria.

[0126] In a possible implementation manner, the evaluation module 220 is configured to determine a carbon emission reduction score based on the carbon emission reduction score and the carbon emission reduction evaluation criteria;

[0127] Determine a power outage rate score based on the power outage rate score and the power outage rate evaluation criteria;

[0128] Determine a peak shaving performance score based on the peak shaving performance score and the peak shaving performance evaluation criteria;

[0129] Determine an output fluctuation score based on the output fluctuation score and the output fluctuation evaluation criteria;

[0130] Based on the carbon emission reduction score, the power outage rate score, the peak shaving performance score, and the output fluctuation score, determine the evaluation result of the wind-solar energy storage system to be evaluated.

[0131] In a possible implementation manner, each calculation module in the evaluation model is correspondingly provided with a preset weight;

[0132] The evaluation module 220 is configured to input electrical parameters into the evaluation model, and obtain the evaluation result of the wind-solar energy storage system to be evaluated based on the first results of each calculation module and the preset weights of each calculation module; wherein, the first result is the result obtained after normalizing the output results of all calculation modules.

[0133] In the above embodiments, the descriptions of each embodiment have their own focuses. For the parts not detailed or recorded in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0134] Those of ordinary skill in the art can realize that, in combination with the templates, units, and algorithm steps of the examples described in the embodiments disclosed herein, they can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present invention.

[0135] If the module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, to implement all or part of the processes in the above-described embodiment methods of the present invention, it can also be completed by a computer program instructing relevant hardware. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, the steps of the above-described various embodiments of the evaluation method of the wind-solar energy storage system based on carbon emission reduction can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in the form of source code, object code, executable file, or some intermediate form, etc. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disc, computer memory, read-only memory, random access memory, electrical carrier signal, telecommunication signal, and software distribution medium, etc.

[0136] The above-described embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the various embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. An evaluation method for a wind-solar-energy storage system based on carbon emission reduction, characterized in that: include: Obtaining electrical parameters of the wind-solar-energy storage system to be evaluated; wherein the electrical parameters include installed capacity, grid parameters and operating parameters; the installed capacity includes wind power installed capacity, photovoltaic installed capacity and energy storage capacity; the grid parameters include wind power generation data and photovoltaic power generation data within the target historical period; the operating parameters include the average power of photovoltaic power generation within the target historical period, the average power of wind power generation within the target historical period, the load demand within the target historical period, the output power of energy storage within the target historical period, and the consumption within the target historical period; The electrical parameters are input into a pre-built evaluation model to obtain the evaluation results of the wind-solar-energy storage system to be evaluated; wherein the evaluation model includes a carbon emission reduction calculation module, a system load power shortage rate calculation module, a system peak-shaving performance calculation module and an output volatility calculation module.

2. The evaluation method for wind-solar energy storage system based on carbon emission reduction according to claim 1 is characterized in that: The output volatility calculation module determines an output volatility score based on the wind power installed capacity, the photovoltaic installed capacity, the wind power generation data and the photovoltaic power generation data in the target historical period; The system load power shortage rate calculation module determines the power shortage rate score based on the average power of photovoltaic power generation in the target historical period, the average power of wind power generation in the target historical period, and the load demand in the target historical period; The system peak-shaving performance calculation module determines the peak-shaving performance score based on the wind power installed capacity, photovoltaic installed capacity, energy storage capacity, photovoltaic output per unit value within the target historical period, wind power output per unit value within the target historical period, output power of energy storage within the target historical period, and consumption within the target historical period; The carbon emission reduction calculation module determines the carbon emission reduction score based on the photovoltaic power generation data and the photovoltaic power generation carbon emission reduction factor within the target historical period, and the wind power generation data and the wind power generation carbon emission reduction factor within the target historical period.

3. The evaluation method for wind-solar-energy storage system based on carbon emission reduction according to claim 2 is characterized in that: The photovoltaic power generation carbon emission reduction factor is determined based on the photovoltaic power generation carbon emission factor and the power grid carbon emission factor of the photovoltaic power generation installed area; The wind power generation carbon emission reduction factor is determined based on the wind power generation carbon emission factor and the power grid carbon emission factor of the wind power generation installed area.

4. The evaluation method for wind-solar-energy storage system based on carbon emission reduction according to claim 2 is characterized in that: The output fluctuation calculation module converts the wind power generation data and photovoltaic power generation data in the target historical period into wind power output sequence L W and photovoltaic output sequence L G , the output fluctuation score F1 is: F1 = std(N) + X(N); Where N = αL W +βL G , α+β=1, α is the proportion of wind power installed capacity, β is the proportion of photovoltaic installed capacity, std(N) is the standard deviation of sequence N, and X(N) is the range of sequence N; The power failure rate score F2 is: F2=(T 需 -T 风 -T 光 )Δt; Among them, T 需 is the load demand in the target historical period t, T 风 is the average power of wind power generation in the target historical period t, T 光 The average power of photovoltaic power generation in the target historical period t, Δt is the sampling frequency within the statistical time; The peak load performance score F3 is: Among them, C WG =M×(αP W +βP G ), C WG is the total wind and solar power output in the target historical period t, P2 is the output power of energy storage in the target historical period t, C X is the consumption of the target historical period t, M is the total installed capacity of wind and solar power, α+β=1, α is the proportion of wind power installed capacity, β is the proportion of photovoltaic installed capacity, P W is the wind power output per unit value in the target historical period t, P G is the per unit value of photovoltaic output in the target historical period t.

5. The evaluation method for wind-solar-energy storage system based on carbon emission reduction according to claim 2 is characterized in that: The carbon reduction score F4 is: F4=εT1+θT2; Among them, ε is the carbon emission reduction factor of photovoltaic power generation, θ is the carbon emission reduction factor of wind power generation, T1 is the photovoltaic power generation in the target historical period, and T2 is the wind power generation in the target historical period.

6. The evaluation method for wind-solar-energy storage system based on carbon emission reduction according to claim 1 is characterized in that: The step of inputting the electrical parameters into a pre-built evaluation model to obtain an evaluation result of the wind-solar energy storage system to be evaluated includes: Input the electrical parameters into the evaluation model, and output various scores of the wind-solar-energy storage system to be evaluated; wherein the various scores include carbon emission reduction score, power shortage rate score, peak load performance score and output fluctuation score; Based on the scores and preset evaluation criteria, the evaluation results of the wind-solar-energy storage system to be evaluated are determined; wherein the preset evaluation criteria include carbon emission reduction evaluation criteria, power shortage rate evaluation criteria, peak load performance evaluation criteria and output fluctuation evaluation criteria.

7. The evaluation method for wind-solar-energy storage system based on carbon emission reduction according to claim 6 is characterized in that: The step of determining the evaluation result of the wind-solar-energy storage system to be evaluated based on the scores and the preset evaluation criteria includes: Determining a carbon emission reduction score based on the carbon emission reduction score and the carbon emission reduction evaluation standard; Determining a power shortage rate score based on the power shortage rate score and the power shortage rate evaluation standard; Determining a peak shaving performance score based on the peak shaving performance score and the peak shaving performance evaluation standard; Determining an output fluctuation score based on the output fluctuation score and the output fluctuation evaluation standard; Based on the carbon emission reduction score, the power shortage rate score, the peak load performance score and the output fluctuation score, an evaluation result of the wind-solar-energy storage system to be evaluated is determined.

8. The evaluation method for wind-solar-energy storage system based on carbon emission reduction according to claim 1 is characterized in that: Each calculation module in the evaluation model is correspondingly provided with a preset weight; The step of inputting the electrical parameters into a pre-built evaluation model to obtain an evaluation result of the wind-solar energy storage system to be evaluated includes: The electrical parameters are input into the evaluation model, and based on the first results of each calculation module and the preset weights of each calculation module, the evaluation results of the wind-solar-energy storage system to be evaluated are obtained; wherein the first result is the result obtained after normalizing the output results of all the calculation modules.

9. An evaluation device for a wind-solar energy storage system based on carbon emission reduction, characterized in that: include: An acquisition module is used to acquire electrical parameters of the wind-solar-energy storage system to be evaluated; wherein the electrical parameters include installed capacity, grid parameters and working parameters, the installed capacity includes wind power installed capacity, photovoltaic installed capacity and energy storage capacity, the grid parameters include wind power generation data and photovoltaic power generation data within the target historical period, and the working parameters include the average power of photovoltaic power generation within the target historical period, the average power of wind power generation within the target historical period, the load demand within the target historical period, the output power of energy storage within the target historical period, and the consumption within the target historical period; An evaluation module is used to input the electrical parameters into a pre-built evaluation model to obtain the evaluation results of the wind-solar-energy storage system to be evaluated; wherein the evaluation model includes a carbon emission reduction calculation module, a system load power shortage rate calculation module, a system peak-shaving performance calculation module and an output volatility calculation module.

10. The evaluation device for a wind-solar-energy storage system based on carbon emission reduction according to claim 9, characterized in that: The output volatility calculation module determines an output volatility score based on the wind power installed capacity, the photovoltaic installed capacity, the wind power generation data and the photovoltaic power generation data in the target historical period; The system load power shortage rate calculation module determines the power shortage rate score based on the average power of photovoltaic power generation in the target historical period, the average power of wind power generation in the target historical period, and the load demand in the target historical period; The system peak-shaving performance calculation module determines the peak-shaving performance score based on the wind power installed capacity, photovoltaic installed capacity, energy storage capacity, photovoltaic output per unit value within the target historical period, wind power output per unit value within the target historical period, output power of energy storage within the target historical period, and consumption within the target historical period; The carbon emission reduction calculation module determines the carbon emission reduction score based on the photovoltaic power generation data and the photovoltaic power generation carbon emission reduction factor within the target historical period, and the wind power generation data and the wind power generation carbon emission reduction factor within the target historical period.

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