Power system investment decision evaluation method, system, medium and equipment

Abstract

The invention discloses an electric power system investment decision evaluation method and system, a medium and equipment, and the method comprises the steps: carrying out the curve fitting of a power grid development stage through taking the per capita power consumption as an index, and analyzing the change trend of the power grid development level along with time t; analyzing the influence of the novel power system on the power supply side investment structure, the power grid side investment structure, the load side investment structure and the energy storage side investment structure, and respectively constructing power supply side investment demand systems, power grid side investment demand systems, load side investment demand systems and energy storage side investment demand systems which adapt to the novel power system; the investment capacity is measured and calculated, and the investment scale and the power grid investment boundary and range are determined by combining the recent-year investment scale and based on the investment capacity coefficient and the price checking investment coefficient, overall planning the investment capacity, the investment demand, the planning investment, the price checking investment and the electric quantity benefit constraint; a multi-scene power grid investment evaluation index system is formed according to different scenes, a novel power system multi-scene power grid investment effect evaluation model is established, and power grid investment effect dynamic deduction is carried out for typical scenes under the construction of the novel power system.

Description

Background Art

[0002] High-quality energy and power supply is an important part of the supply system and the core goal of the energy revolution. In the face of growing electricity demand, it is necessary to continuously increase grid investment and promote high-quality development of the grid. Grid investment serves the development of the national economy and is the backbone and main force of stable investment and stable growth. Investment is a means and process to achieve resource allocation. Grid investment strategy is an important means for the high-quality development of the grid itself and the grid company. Research on grid investment strategy decision support technology is an urgent need to cope with the complex and changing internal and external environment of grid companies. Facing the new power system, the scenarios faced by grid investment are more complex and need to provide systematic support. Grid investment decisions face new and higher requirements such as investment demand, investment strategy, and investment results. In terms of investment demand, it is necessary to meet the needs of high-quality economic and social development and the needs of rapid development of new energy; in terms of investment strategy, it is necessary to face the constraints of limited investment capacity and the pressure of rising system costs; in terms of investment results, it is necessary to ensure the efficiency and benefits of grid investment and consider the impact of changes in different factors on results.

[0003] At present, the defects and shortcomings of the existing technology are as follows:

[0004] 1) In the process of power grid construction, there are many types of projects to be invested in, and the number is large. The traditional project optimization method uses the same set of indicators to conduct a comprehensive evaluation of all types of projects, ignoring the attribute characteristics and attribute importance of the project, which is somewhat unreasonable.

[0005] 2) It is currently difficult to extract the key influencing factors of the evolution of the investment function of the new power system, and it is difficult to conduct a scientific analysis of the evolution of the investment function demand of the power grid.

[0006] 3) Existing research lacks the objective and comprehensive selection of key indicators and the use of appropriate methods to conduct comprehensive evaluations and then analyze the investment category structure and investment project timing arrangements.

[0007] 4) In view of the research difficulties such as the uncertainty of the variables of key influencing factors in the power grid investment process changing with the internal and external environment over time, considering that the current research lacks a system for comprehensive evaluation of its economic benefits, social and environmental benefits, and a systematic study of dynamic deduction. Summary of the invention

[0008] The technical problem to be solved by the present invention is to provide a method, system, medium and equipment for evaluating investment decisions in an electric power system in view of the deficiencies in the above-mentioned prior art, so as to solve the technical problems that the classification and logic of the investment functional demand system has not yet been formed under the type power system, the project optimization decision in the power grid investment strategy optimization ignores the attribute characteristics and attribute importance of the project, the construction of the index system is imperfect, the qualitative limitations of the traditional power grid investment evaluation and the lack of systematic analysis.

[0009] The present invention adopts the following technical solutions:

[0010] A power system investment decision evaluation method comprises the following steps:

[0011] Based on the Logistic model, the power grid development stage is fitted with a curve using per capita electricity consumption as an indicator, and the trend of power grid development level over time t is analyzed to obtain the results of the power grid development stage assessment.

[0012] According to the results of the grid development stage research, the impact of the new power system on the investment structure of the power supply side, grid side, load side and energy storage side is analyzed. Considering the changes in the investment function requirements of the power supply side, grid side, load side and energy storage side, the investment demand system of the power supply side, grid side, load side and energy storage side that adapt to the new power system is constructed respectively;

[0013] The investment capacity is calculated based on the investment demand system for the power supply side, grid side, load side and energy storage side that is adapted to the new power system. Combined with the investment scale in recent years, based on the investment capacity coefficient and the price-based investment coefficient, the investment capacity, investment demand, planned investment, price-based investment and electricity efficiency constraints are coordinated to determine the investment scale, as well as the boundaries and scope of grid investment;

[0014] Determine the constraints and objective function of the grid investment strategy optimization model based on the investment scale results and the grid investment boundary and scope;

[0015] Based on the constraints and objective function of the grid investment strategy optimization model, a multi-scenario grid investment evaluation index system is formed according to different scenarios, and a multi-scenario grid investment effectiveness evaluation model for a new power system is established. The grid investment effectiveness is dynamically deduced for typical scenarios under the construction of a new power system.

[0016] Preferably, the changing trend of the power grid development level over time t is as follows:

[0017]

[0018] Among them, U(t) is the development level of the power grid; c is the saturation value of the power grid development; a and b are the parameters to be estimated; and t is time.

[0019] Preferably, the power supply side investment demand system is as follows:

[0020] C=C fb +C jz

[0021] Among them, C is the total investment on the power supply side; C fb is the total investment of distributed power generation; C jz Invest in centralized power supply.

[0022] Preferably, the grid-side investment demand system is as follows:

[0023] T=β×T 基 +Δ

[0024] Among them, T is the power grid investment demand, β is the investment demand index, T 基 is the benchmark value of investment demand, and Δ is the number of new major projects.

[0025] Preferably, the load-side investment demand system is as follows:

[0026] L=L cb -L gxt -L zxt -L dxt

[0027] Among them, L cb is the demand response cost; L is the load side investment scale; L gxt Save investment for high voltage substation; L zxt Save investment for medium voltage equipment; L dxt Save investment for low-voltage equipment.

[0028] Preferably, the energy storage investment demand system is as follows:

[0029] W=W1-W2-W3

[0030] Among them, W is the total investment cost of the energy storage system; W1 is the cost of the energy storage system; W2 is the peak-valley arbitrage income of energy storage; and W3 is the subsidy cost on the energy storage side.

[0031] Preferably, the investment scale is calculated as follows:

[0032] I cGD =R c -Z J -Q c +FZ-FZ S

[0033] Among them, I cGD Represents the fixed asset investment capacity of the enterprise during the forecast period; R c represents the annual net profit during the forecast period, Z J represents the depreciation expense during the forecast period, Q crepresents the equity investment received during the forecast period; FZ represents the total liabilities during the forecast period; FZ S Represents the total liabilities in the previous year of the forecast period.

[0034] In a second aspect, an embodiment of the present invention provides a power system investment decision evaluation system, including:

[0035] The trend module, based on the Logistic model, uses per capita electricity consumption as an indicator to perform curve fitting on the power grid development stage, analyzes the changing trend of the power grid development level over time t, and obtains the results of the power grid development stage assessment;

[0036] System module: Analyze the impact of the new power system on the investment structure of the power supply side, grid side, load side and energy storage side according to the results of the grid development stage assessment, consider the changes in the investment function requirements of the power supply side, grid side, load side and energy storage side, and build the investment demand system of the power supply side, grid side, load side and energy storage side that adapt to the new power system;

[0037] The calculation module calculates the investment capacity based on the investment demand system for the power supply side, grid side, load side and energy storage side that is adapted to the new power system. Combined with the investment scale in recent years, based on the investment capacity coefficient and the price-based investment coefficient, it coordinates the investment capacity, investment demand, planned investment, price-based investment and electricity efficiency constraints to determine the investment scale, as well as the boundaries and scope of grid investment.

[0038] The construction module determines the constraints and objective function of the grid investment strategy optimization model based on the investment scale results and the grid investment boundary and scope;

[0039] The evaluation module, based on the constraints and objective function of the power grid investment strategy optimization model, forms a multi-scenario power grid investment evaluation index system according to different scenarios, establishes a multi-scenario power grid investment effectiveness evaluation model for a new power system, and dynamically deduces the effectiveness of power grid investment for typical scenarios under the construction of a new power system.

[0040] In a third aspect, a computer device comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above-mentioned power system investment decision evaluation method when executing the computer program.

[0041] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, including a computer program, which, when executed by a processor, implements the steps of the above-mentioned power system investment decision evaluation method.

[0042] Compared with the prior art, the present invention has at least the following beneficial effects:

[0043] A method for evaluating power system investment decisions forms a systematic functional classification by analyzing changes in investment function requirements from four aspects: source, network, load and storage. It improves the project evaluation index system, improves the investment strategy optimization method, adds investment effectiveness evaluation index dimensions for new power systems, quantitatively analyzes investment effectiveness, and makes power grid investment analysis more in-depth and comprehensive.

[0044] Furthermore, considering the changes in the functional requirements of grid investment, a grid investment demand system that adapts to the new power system is constructed to focus on the construction of the new power system. The stage of grid development is accurately located based on the Logistic model, laying the foundation for investment demand analysis.

[0045] Furthermore, by considering the access standards of lines and distribution transformers for distributed power sources, an investment demand system for new energy access power sources that takes into account safety and economy is proposed, making the solution process more scientific and reasonable.

[0046] Furthermore, by combining the impact of macroeconomic factors on grid investment, a grid-side investment demand system that adapts to the new power system is constructed, and grid investment decisions are more in line with the economic environment of the region where the grid company is located.

[0047] Furthermore, considering the peak shaving of energy storage, a load-side investment scale calculation model is proposed which takes into account the benefits of slow construction of distribution network.

[0048] Furthermore, considering the power generation data of new energy, a total cost calculation model for energy storage system investment is proposed, which takes into account the cost of energy storage system, peak-valley arbitrage income, and storage-side subsidy costs, so as to improve the accuracy of investment demand.

[0049] Furthermore, combined with the investment scale in recent years, based on the investment capacity coefficient and the price-based investment coefficient, the investment capacity, investment demand, planned investment, price-based investment and electricity efficiency are comprehensively considered to determine the recommended investment scale. The power grid investment strategy formulation method proposed in this invention is closely linked to the current power grid development environment and has a certain reference value for guiding power grid planning work.

[0050] It can be understood that the beneficial effects of the second to fourth aspects mentioned above can be found in the relevant description of the first aspect mentioned above, and will not be repeated here.

[0051] In summary, the present invention constructs an investment demand estimation model for the four sides of source, grid, load and storage based on the investment direction, and estimates the investment scale in a scenario-based manner; constructs a power grid investment strategy optimization model according to the attribute characteristics and attribute importance of the project to obtain the optimal investment project portfolio under the constraint of the total investment amount; constructs a new power system multi-scenario power grid investment effectiveness evaluation model from the provincial, municipal and county levels, and puts forward new power system investment recommendations. This can then achieve investment scale estimation, project optimization, and effectiveness deduction, and improve the company's internal investment and project management efficiency. It avoids decision-making errors caused by ignoring changes in the economic environment based solely on time series, and the proposed estimation model is highly instructive and universal for power grid companies.

[0052] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 Analyze the trend of power grid development level over time t for the Logistic growth model;

[0054] Figure 2 Calculate the logic diagram for the investment demand on the power supply side;

[0055] Figure 3 Calculate the logic diagram for grid-side investment demand;

[0056] Figure 4 Calculate the logic diagram for load-side investment demand;

[0057] Figure 5 Calculate the logic diagram for energy storage investment demand;

[0058] Figure 6 Optimize the logic diagram for investment projects;

[0059] Figure 7 A schematic diagram of a computer device provided by an embodiment of the present invention;

[0060] Figure 8 A block diagram of an electronic device provided according to an embodiment of the present invention;

[0061] Fig. 9 This is the analysis result of the development stage of Province A. DETAILED DESCRIPTION

[0062] 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 are within the scope of protection of the present invention.

[0063] In the description of the present invention, it should be understood that the terms “include” and “comprises” indicate the presence of described features, wholes, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or collections thereof.

[0064] It should also be understood that the terms used in the present specification are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the present specification and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0065] It should be further understood that the term "and / or" used in the present specification and the appended claims refers to any combination of one or more of the associated listed items and all possible combinations, and includes these combinations. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in the present invention generally indicates that the associated objects are in an "or" relationship.

[0066] The word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrases "if it is determined" or "if (stated condition or event) is detected" may be interpreted as "when it is determined" or "in response to determining" or "when detecting (stated condition or event)" or "in response to detecting (stated condition or event)", depending on the context.

[0067] Various structural schematic diagrams of the embodiments disclosed in the present invention are shown in the accompanying drawings. These figures are not drawn to scale, and some details are magnified and some details may be omitted for the purpose of clear expression. The shapes of various regions and layers shown in the figures and the relative sizes and positional relationships therebetween are only exemplary, and may deviate in practice due to manufacturing tolerances or technical limitations, and those skilled in the art may additionally design regions / layers with different shapes, sizes, and relative positions according to actual needs.

[0068] The present invention provides a method for evaluating investment decisions of a power system. In view of the lack of scientific analysis of the evolution of power grid investment function requirements in the prior art, the inability to objectively and comprehensively select key indicators and adopt appropriate methods to comprehensively evaluate them and then analyze the investment category structure and the timing arrangement of investment projects, and the lack of a system for comprehensively evaluating its economic benefits, social and environmental benefits, etc., the present invention considers the changes in power grid investment function requirements and constructs a power grid investment demand system that adapts to the new power system; considering the conditions that the power grid development level and the economic and social development level have certain differences, based on the high-quality development evaluation index system of the State Grid Corporation, etc., selects key indicators and adopts intelligent algorithms to construct a power grid investment strategy optimization model to optimize investment categories; from multiple dimensions such as economy and society, comprehensively considers the characteristics of regional power grid investment, studies the power grid investment evaluation index system, and constructs an investment effectiveness evaluation model, based on the dynamic changes of evaluation indicators, quantifies the degree of change in power grid investment effectiveness. Clarify the future direction of power grid investment, provide theoretical support for scientific decision-making on power grid investment, help the high-quality development of power grids, and achieve investment efficiency and benefits.

[0069] The present invention provides a power system investment decision evaluation method, comprising the following steps:

[0070] S1. Based on the Logistic model, analyze the development characteristics of the power grid and the development trend of the new power system, consider the main characteristics of the new power system, study the changes in the investment function requirements of the power grid under the new power system, and then study the changes in the investment function requirements of the power supply side, the power grid side, the load side and the energy storage side;

[0071] See also Figure 1 , the Logistic growth model is used to analyze the changing trend of the power grid development level over time t, as follows:

[0072]

[0073] Among them, U(t) is the development level of the power grid; c is the saturation value of the power grid development; a and b are the parameters to be estimated; and t is time.

[0074] S2. Analyze the impact of the new power system on the power supply side investment structure, study the evolution trend of the power supply side investment structure under the new power system, consider the changes in the power supply side investment function requirements, and build a power supply side investment demand system that adapts to the new power system;

[0075] See also Figure 2 , the total investment scale on the power supply side is the sum of centralized photovoltaic investment and distributed photovoltaic investment, and the calculation formula is as follows:

[0076] C=C fb ×C jz

[0077] Among them, C is the total investment on the power supply side, RMB 10,000; C fb is the total investment of distributed power source, RMB 10,000; C jz The investment in centralized power supply is RMB 10,000.

[0078] The calculation formula for distributed power generation investment is as follows:

[0079] C fb =C1+C2+C3+C4+C5

[0080] Among them, C fb C is the investment in distributed power source, RMB 10,000; C1 is the investment in new 10kV line, RMB 10,000; C2 is the investment in transformation of 10kV line, RMB 10,000; C3 is the investment in new distribution transformer, RMB 10,000; C4 is the investment in transformation of distribution transformer, RMB 10,000; C5 is the investment in distributed power source access project, RMB 10,000.

[0081] The calculation formula for centralized power supply investment is as follows:

[0082] C jz =C5+C6

[0083] Among them, C jz C is the investment in centralized power supply, RMB 10,000; C5 is the investment in supporting transmission projects of 110kV and above, RMB 10,000; C6 is the investment in new construction and renovation of 110kV and above, RMB 10,000.

[0084] S3. Analyze the impact of the new power system on the grid-side investment structure, study the evolution trend of the grid-side investment structure under the new power system, consider the changes in the grid-side investment function requirements, and build a grid-side investment demand system that adapts to the new power system;

[0085] See also Figure 3 , coordinate the implementation status and planning as well as the factors affecting the investment demand on the grid side, such as load growth, and build a grid side investment demand estimation model.

[0086] 1) Coordinate the implementation and planning of investment demand benchmarks

[0087] Average from 2016 to 2020 = (2016 fixed assets (excluding UHV) + 2017 fixed assets (excluding UHV) + 2018 fixed assets (excluding UHV) + 2019 fixed assets (excluding UHV) + 2020 fixed assets (excluding UHV)) / 5

[0088] The remaining average of the plan from 2021 to 2025 = (plan from 2021 to 2025 - completion in 2021 - completion in 2022 - plan in 2023) / 3

[0089] Investment demand = average annual amount from 2016 to 2020*0.1+completed amount in 2021*0.15+completed amount in 2022*0.25+planned amount in 2023*0.25+average annual amount of remaining plan from 2021 to 2025*0.25

[0090] 2) Calculate investment demand by comprehensively considering factors that affect investment demand

[0091] Taking into account the central policies, economic and social development, energy transformation, institutional reform and stable operation, we analyze the needs of power grid development, identify the key factors affecting the investment demand calculation, form an indicator system, quantify the development of indicators and the degree of impact on investment, form an investment demand index, and then adjust the basic value of the investment scale. In combination with new major projects, we build an investment demand calculation model to calculate investment demand.

[0092] ① Central policy

[0093] The central government's policy mainly considers the service level of the new power system. Among them, the proportion of electricity in terminal consumption is evaluated by benchmarking method, and the calculation formula is:

[0094] G 电能在终端消费中的比重 =The proportion of electricity in terminal consumption × 100

[0095] The proportion of new energy in total installed capacity, the level of grid intelligence and the calculation principle of the digital development index are the same as the proportion of electricity in terminal consumption.

[0096] However, for the power demand response capability index, the lower the index score, the more investment is needed. The benchmarking method is used to evaluate it, and the calculation formula is:

[0097] G 电力需求响应能力指数 =100-power demand response capability index×100

[0098] The calculation principle of the source-grid-load-storage collaborative service index is the same as that of the electricity demand response capability index.

[0099] The calculation formula at the central policy level is:

[0100] G 中央政策 =ω 电能在终端消费中的比重 ×G 电能在终端消费中的比重 +ω 新能源占总装机的比重 ×G 新能源占总装机的比重 +

[0101] ω 电力需求响应能力指数 ×G 电力需求响应能力指数 +ω 源网荷储协同服务指数 ×G 源网荷储协同服务指数 +

[0102] ω 电网智能化水平 ×G 电网智能化水平 +ω数字化发展指数 ×G 数字化发展指数

[0103] ②Economic and social

[0104] The economic level mainly considers the impact of GDP on investment demand. The GDP growth rate is evaluated using the benchmarking method, and the calculation formula is:

[0105]

[0106] Therefore, the economic level calculation formula is:

[0107] G 经济 =ω GDP增速 ×G GDP增速

[0108] The social level mainly considers the impact of urbanization rate, total social electricity consumption and total social maximum load on investment demand. Among them, the urbanization rate is evaluated using the benchmarking method, and the calculation formula is:

[0109] G 城镇化率 =60+(100-60)×(this year's urbanization rate - the minimum value of this indicator for each unit) /

[0110] (The maximum value of the indicator in each unit - the minimum value of the indicator in each unit)

[0111] The growth rate of total electricity consumption and the growth rate of total maximum load in society are calculated based on the same principle as the GDP growth rate.

[0112] Therefore, the social level calculation formula is:

[0113] G 社会 =ω 城镇化率 ×G 城镇化率 +ω 全社会用电量 ×G 全社会用电量 +ω 全社会最大负荷 ×G 全社会最大负荷

[0114] The calculation formula for the economic and social level is:

[0115] G 经济社会 =ω 经济 ×G 经济 +ω 社会 ×G 社会

[0116] ③Energy transformation

[0117] Energy transformation mainly considers the service "carbon reduction" level. Among them, the increase in wind and solar grid-connected installed capacity and the increase in electricity substitution are evaluated by benchmark targeting method, and the calculation principle is the same as the urbanization rate in economic and social indicators. The wind power utilization rate and photovoltaic utilization rate are calculated in the same principle as the power demand response capability index. Therefore, the calculation formula at the energy transformation level is:

[0118] G 能源转型 =ω 风光并网装机 ×G 风光并网装机 +ω 电能替代电量 ×G 电能替代电量

[0119] +ω 风电利用率 ×G 风电利用率 +ω 光伏利用率 ×G 光伏利用率

[0120] ④Institutional reform

[0121] The system reform mainly considers the proposed "two increases, one control and three improvements" goals and tasks. The total profit and net profit are calculated using the benchmarking method, which is the same as the calculation principle of the urbanization rate in the economic and social indicators. The asset-liability ratio is evaluated using the industry benchmarking method, and the asset-liability ratio is used as the basic control indicator to classify and manage state-owned enterprises of different industry types, and implement dynamic adjustments. According to the established standards, the asset-liability ratio warning line of state-owned industrial enterprises is 65%, and the key supervision line is 70%. Therefore, the asset-liability ratio calculation formula is:

[0122]

[0123] The calculation formula at the institutional reform level is:

[0124] G 体制改革 =ω 利润总额 ×G 利润总额 +ω 净利润 ×G 净利润 +ω 资产负债率 ×G 资产负债率

[0125] ⑤Steady operation

[0126] The stable operation mainly considers the operating efficiency and power supply capacity. In terms of operating efficiency, the load increase per unit of grid investment is evaluated by the benchmarking method, and the calculation formula is:

[0127]

[0128] The increase in electricity sales per unit of investment, market share and operating income are all evaluated using the benchmarking method. The calculation principle of the increase in electricity sales per unit of investment is the same as the increase in load per unit of grid investment, the calculation principle of market share is the same as the proportion of electricity in terminal consumption, and the increase in operating income is the same as the calculation principle of urbanization rate in economic and social indicators. Therefore, the calculation formula at the operating efficiency level is:

[0129] G 经营效益 =ω 单位电网投资增供负荷 ×G 单位电网投资增供负荷 +ω 单位电网投资增售电量 ×G 单位电网投资增售电量

[0130] +ω 市场占有率 ×G 市场占有率 +ω 营业收入 ×G 营业收入

[0131] At the power supply capacity level, the N-1 pass rate, the main transformer (distribution transformer) heavy overload rate, the line heavy overload rate, and the proportion of old equipment are all evaluated using the benchmark targeting method. The calculation principle is the same as the proportion of electricity in terminal consumption. The capacity load ratio is evaluated using the industry benchmarking method. According to the "State Grid Corporation of China Urban Power Grid Planning and Design Guidelines", if the capacity load ratio of each voltage level is within the requirements of the guidelines or higher than the upper limit of the guidelines, the score is 0, otherwise it is 100 points. The average load rate is evaluated using the benchmark targeting method, and the calculation formula is:

[0132]

[0133] The maximum load rate is evaluated by the benchmarking method, and the calculation formula is:

[0134]

[0135] Therefore, the calculation formula for power supply capacity is:

[0136] G 供电能力 =ω N-1通过率 ×G N-1通过率 +ω 容载比 ×G 容载比

[0137] +ω 主变(配变)重过载率 ×G 主变(配变)重过载率

[0138] +ω 老旧主变(配变)占比 ×G 老旧主变(配变)占比

[0139] +ω 老旧线路占比 ×G 老旧线路占比

[0140] +ω 主变(配变)平均负载率 ×G 主变(配变)平均负载率

[0141] +ω 线路平均负载率 ×G 线路平均负载率

[0142] +ω 主变(配变)最大负载率 ×G 主变(配变)最大负载率

[0143] +ω 线路最大负载率 ×G 线路最大负载率

[0144] The calculation formula for the stable operation level is:

[0145] G 稳健经营 =ω 经营效益 ×G 经营效益 +ω 供电能力 ×G 供电能力

[0146] Among them, s n is the weight of the nth indicator.

[0147] Therefore, the formula for calculating the comprehensive score of each unit is:

[0148] G=ω 中央政策 ×G 中央政策 +ω 经济社会 ×G 经济社会

[0149] +ω 经济社会 ×G 经济社会 +ω 体制改革 ×G 体制改革 +ω 稳健经营 ×G 稳健经营

[0150] Finally, the development input index β is determined based on the comprehensive score G of each unit, and the investment demand benchmark is adjusted using the investment index. In addition, the investment demand is calculated based on the newly added major projects. The calculation formula is:

[0151] T=β×T 基 +Δ

[0152] Among them, T is the power grid investment demand, β is the investment demand index, T 基 is the benchmark value of investment demand, and Δ is the number of new major projects.

[0153] S4. Analyze the impact of the new power system on the load-side investment structure, study the evolution trend of the load-side investment structure under the new power system, consider the changes in the functional requirements of the load-side investment, and build a load-side investment demand system that adapts to the new power system;

[0154] See also Figure 4 , considering energy storage peak shaving, and studying the load-side investment demand calculation model taking into account the benefits of distribution network slow construction.

[0155] Since the power demand in the grid-side investment demand has excluded the power consumed locally by distributed power sources, the investment saved by energy storage for peak load shifting and valley filling can be excluded from the investment related to distributed power source construction. The calculation formula is as follows:

[0156] The calculation formula for the load-side investment scale is as follows:

[0157] L=L cb -L xt

[0158] Wherein, L is the investment scale on the load side, ten thousand yuan; L xt Save investment of 10,000 yuan for energy storage to reduce peak load and fill valley.

[0159] L xt =L cb -L gxt -L zxt -L dxt

[0160] Among them, L cb is the demand response cost, 10,000 yuan; L gxt Save investment for high-voltage substation, 10,000 yuan; L zxt Save investment in medium voltage equipment, RMB 10,000; L dxt Save investment of tens of thousands of yuan for low-voltage equipment.

[0161] S5. Analyze the impact of the new power system on the investment structure of energy storage, study the evolution trend of the investment structure of energy storage under the new power system, consider the changes in the functional requirements of energy storage investment, and build an energy storage investment demand system that adapts to the new power system;

[0162] See also Figure 5 At present, energy storage application scenarios are mainly divided into power supply side, grid side and user side. In theory, grid-side energy storage is invested by grid companies, but under the current policy, companies do not invest in grid-side energy storage for the time being. If grid companies still do not invest in grid-side energy storage in the future, there will be no investment in energy storage; if grid companies and social capital invest in grid-side energy storage at 50% each in the future, the total investment cost of the energy storage system will be 0.5W. If grid companies invest in grid-side energy storage in full in the future, the total investment cost of the energy storage system will be W.

[0163] The total investment cost calculation model formula of energy storage system is as follows:

[0164] W=W1-W2-W3

[0165] Among them, W is the total investment cost of the energy storage system, RMB 10,000; W1 is the cost of the energy storage system, RMB 10,000; W2 is the peak-valley arbitrage income of energy storage, RMB 10,000; W3 is the subsidy cost on the energy storage side, RMB 10,000.

[0166] 1) Energy storage system cost:

[0167] W1=E N P RL

[0168] Among them, E N Configure the capacity for energy storage, kWh; P RL is the unit capacity cost, RMB / kWh.

[0169] 2) Energy storage peak-valley arbitrage benefits:

[0170] Under the premise of charging and discharging twice a day, the main benefits of the energy storage project are peak-valley price difference and peak-flat price difference arbitrage.

[0171] Assuming two charges and two discharges per day, ignoring the peak electricity price under special circumstances, and only considering the peak, flat and valley electricity prices, the daily charging and discharging income is calculated as shown in the formula:

[0172] I tl =P f -P c

[0173] P c =E N η(p m +p l )

[0174] P f =2E N ηp h

[0175] Among them, I tl is the peak-to-valley arbitrage income; P f is the discharge gain; P c P is the charging cost; h is the peak electricity price; p m is the flat-term electricity price; p l is the valley electricity price; η is the charge and discharge efficiency, which is 90%.

[0176] 3) Energy storage subsidy costs

[0177] During the transition period, peak load regulation projects (with annual utilization hours of no less than 600 hours) will be compensated for their capacity, with the compensation standard declining year by year, and the subsidy period is tentatively set at 3 years (at 200, 180, and 170 yuan / kW / year). For demonstration projects of frequency regulation of combined thermal power units, those with a Kpd value greater than 0.9 will be given a certain coal consumption quota of 200,000 kWh / MW per month for frequency regulation based on energy storage capacity.

[0178] S6. Calculate investment capacity, combine the investment scale in recent years, and determine the recommended investment scale based on the investment capacity coefficient and the price-based investment coefficient, taking into account the constraints of investment capacity, investment demand, planned investment, price-based investment and electricity efficiency; determine the boundary and scope of grid investment by comprehensively considering the investment capacity and the increase in system costs brought about by the development of new energy;

[0179] Investment capacity is a comprehensive reflection of the level of an enterprise's operating activities. It refers to the ability of the net cash flow created through operating activities and financing activities to meet the cash needs of investment activities. The most important influencing factors are the cash flow generated by operating activities, investment activities, financing activities and the minimum safety reserve amount.

[0180] The formula for calculating fixed asset investment capacity is:

[0181] I cGD =R c -Z J -Q c +FZ-FZ S

[0182] Among them, I cGD Represents the fixed asset investment capacity of the enterprise during the forecast period; R c represents the annual net profit during the forecast period, Z J represents the depreciation expense during the forecast period, Q c Indicates the equity investment received during the forecast period (fiscal funds, capital injection from headquarters, etc.); FZ indicates the total liabilities during the forecast period; FZ S Represents the total liabilities in the previous year of the forecast period.

[0183] S7. Determine the constraints and objective function of the power grid investment strategy optimization model, build the power grid investment strategy optimization model, and study the optimal combination of investment categories and the timing arrangement of investment projects under multiple constraints;

[0184] See also Figure 6 In the process of power grid construction, there are many types and large number of projects to be invested. The traditional project optimization method uses the same set of indicators to conduct a comprehensive evaluation of all types of projects, ignoring the attribute characteristics and attribute importance of the project, which is somewhat unreasonable.

[0185] First, the projects are divided into five categories according to their importance, among which Category 1 / 2 projects are priority projects and can be selected without considering their benefits; Category 3 / 4 / 5 projects are classified according to their attributes, and an evaluation index system is established for the characteristics of each attribute to prioritize similar projects, and the release plan for each type of project is determined under the constraints of the investment scale of each attribute, ultimately obtaining the optimal investment project portfolio under the constraints of the total investment amount, effectively improving investment accuracy.

[0186] S8. Taking into account the characteristics of regional power grid investment from multiple dimensions such as safety, economy, and low carbon, the power grid investment evaluation index system is studied from multiple levels of provinces, cities, and counties. A multi-scenario power grid investment evaluation index system is formed according to different scenarios, and a multi-scenario power grid investment effectiveness evaluation model for new power systems is established. By analyzing the connotation and characteristics of the new power system, the power grid investment evaluation index system is studied from multiple levels of provinces, cities, and counties. A multi-scenario power grid investment evaluation index system is formed according to different scenarios, and a multi-scenario power grid investment effectiveness evaluation model for new power systems is studied.

[0187] Typical scenarios under power system construction, dynamic simulation of grid investment effectiveness.

[0188] Evaluation indicators for effective asset investment performance of provincial, municipal and county companies

[0189]

[0190]

[0191] (2) Power grid investment effectiveness evaluation model

[0192] Starting from the statistical characteristics of the effective asset evaluation indicators of the power grid, combined with the business characteristics of the power grid, application scenarios, and conventional data, this paper analyzes and gives suggestions on the quantification methods of indicators, laying the foundation for the selection of quantification methods of indicators in various subsequent application models. At present, there are many quantification methods for related indicators, involving linear scaling method, fuzzy membership method, exponential logarithmic scaling method, etc. The optimal quantification methods are different for different indicator types, different data characteristics, and different application scenarios. In addition, the data quality and data level of each company vary greatly, and there is no unified and clear optimal quantification method, which needs to be determined according to the actual situation.

[0193] 1) Index score calculation logic

[0194] ①Linear scaling method

[0195] First, set the maximum and minimum business values ​​of the evaluation object. The maximum and minimum values ​​can be set manually according to the business situation, or the maximum and minimum values ​​of the sample data can be taken. Secondly, the original data is linearly transformed to make the result fall into the [0,1] interval. When the maximum and minimum business values ​​are manually set, sample data that exceeds the maximum value is processed as the maximum value, and sample data that is less than the minimum value is processed as the minimum value.

[0196] ②n quantile method

[0197] The quantile value is one of the characteristic numbers of a random variable. Divide the area enclosed by the random variable distribution curve and the x-axis into n equal parts, and get n-1 values ​​(x1, x2...x n-1), these values ​​are called n-quantiles. Use these quantiles to process the data and find the expected and predicted intervals; evenly set the scores between the n equal partitions, and then calculate the actual score of the data based on the expected and predicted intervals.

[0198] ③Exponential scaling method

[0199] Set parameter a and use the exponential function conversion method with a as the base to achieve exponential scaling. The formula is as follows: (x i is the original input value, y i is the value after exponential scaling)

[0200]

[0201] ④Logarithmic scaling method

[0202] Set parameter a and use the logarithmic function conversion method with a as the base to achieve logarithmic scaling. The formula is as follows: (x i is the original input value, y i is the value after logarithmic scaling)

[0203]

[0204] 2) Index weight calculation logic

[0205] The indicator weights in the model are determined by combining the Delphi weighting method with the coefficient of variation weighting method.

[0206] ① Delphi method

[0207] The Delphi method, also known as the expert survey method, is a method in which a company forms a special forecasting organization, including several experts and corporate forecast organizers, and in accordance with the prescribed procedures, back-to-back solicits the opinions or judgments of experts on the future market, and then makes forecasts. Its essence is a feedback anonymous letter inquiry method.

[0208] The process is: after obtaining the opinions of experts on the weights of the indicators to be predicted, they are sorted, summarized, and counted, and then anonymously fed back to the experts, and their opinions are sought again, concentrated again, and fed back again until a consensus is reached.

[0209] ② Coefficient of variation method

[0210] The coefficient of variation, also known as the "standard deviation rate", is a statistic that measures the degree of variation of each observation value of the evaluation object. When comparing the degree of variation of two or more objects, if the measurement unit of each indicator is the same as the average, the standard deviation can be used directly for comparison, and the size of the standard deviation of each evaluation indicator is used as the basis for weight calculation.

[0211] That is, the standard deviation:

[0212]

[0213] Indicator weight:

[0214]

[0215] Here, μ is the arithmetic mean.

[0216] If the indicator units and (or) mean values ​​are different, the standard deviation cannot be used to compare their degree of variation. Instead, the ratio of the standard deviation to the mean (relative value) must be used for comparison.

[0217] That is, the indicator weight:

[0218]

[0219] In the evaluation index system, indicators with greater differences in value are more difficult to achieve and can better reflect the gap between the evaluated objects.

[0220] It will be appreciated by those skilled in the art that various aspects of the present invention may be implemented as systems, methods or program products. Therefore, various aspects of the present invention may be specifically implemented in the following forms, namely: complete hardware implementation, complete software implementation (including firmware, microcode, etc.), or a combination of hardware and software implementations, which may be collectively referred to herein as "circuits", "modules" or "platforms".

[0221] In another embodiment of the present invention, there is provided an electric power system investment decision evaluation system, which can be used to implement the above-mentioned electric power system investment decision evaluation method. Specifically, the electric power system investment decision evaluation system includes a trend module, a system module, a measurement module, a construction module and an evaluation module.

[0222] Among them, the trend module, based on the Logistic model, uses per capita electricity consumption as an indicator to perform curve fitting on the power grid development stage, analyzes the changing trend of the power grid development level over time t, and obtains the results of the power grid development stage assessment;

[0223] System module: Analyze the impact of the new power system on the investment structure of the power supply side, grid side, load side and energy storage side according to the results of the grid development stage assessment, consider the changes in the investment function requirements of the power supply side, grid side, load side and energy storage side, and build the investment demand system of the power supply side, grid side, load side and energy storage side that adapt to the new power system;

[0224] The calculation module calculates the investment capacity based on the investment demand system for the power supply side, grid side, load side and energy storage side that is adapted to the new power system. Combined with the investment scale in recent years, based on the investment capacity coefficient and the price-based investment coefficient, it coordinates the investment capacity, investment demand, planned investment, price-based investment and electricity efficiency constraints to determine the investment scale, as well as the boundaries and scope of grid investment.

[0225] The construction module determines the constraints and objective function of the grid investment strategy optimization model based on the investment scale results and the grid investment boundary and scope;

[0226] The evaluation module, based on the constraints and objective function of the power grid investment strategy optimization model, forms a multi-scenario power grid investment evaluation index system according to different scenarios, establishes a multi-scenario power grid investment effectiveness evaluation model for a new power system, and dynamically deduces the effectiveness of power grid investment for typical scenarios under the construction of a new power system.

[0227] In another embodiment of the present invention, a terminal device is provided, which includes a processor and a memory, wherein the memory is used to store a computer program, the computer program includes program instructions, and the processor is used to execute the program instructions stored in the computer storage medium. The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, which is suitable for implementing one or more instructions, and is specifically suitable for loading and executing one or more instructions to implement the corresponding method flow or corresponding function; the processor described in the embodiment of the present invention can be used for the operation of the power system investment decision evaluation method, including:

[0228] Based on the Logistic model, the curve fitting of the power grid development stage is carried out with per capita electricity consumption as an indicator, and the changing trend of the power grid development level over time t is analyzed to obtain the results of the power grid development stage assessment; according to the results of the power grid development stage assessment, the impact of the new power system on the investment structure of the power supply side, grid side, load side and energy storage side is analyzed, and the changes in the investment function requirements of the power supply side, grid side, load side and energy storage side are considered to construct the power supply side, grid side, load side and energy storage side investment demand system that adapts to the new power system; based on the constructed power supply side, grid side, load side and energy storage side investment demand system that adapts to the new power system, the investment capacity is calculated , combined with the investment scale in recent years, based on the investment capacity coefficient and the nuclear price investment coefficient, coordinate the investment capacity, investment demand, planned investment, nuclear price investment and electricity benefit constraints to determine the investment scale, as well as the boundary and scope of the power grid investment; determine the constraints and objective function of the power grid investment strategy optimization model based on the investment scale results and the boundary and scope of the power grid investment; based on the constraints and objective function of the power grid investment strategy optimization model, a multi-scenario power grid investment evaluation index system is formed according to different scenarios, and a multi-scenario power grid investment effectiveness evaluation model for a new power system is established. For typical scenarios under the construction of a new power system, a dynamic deduction of the power grid investment effectiveness is carried out.

[0229] In another embodiment of the present invention, the present invention also provides a storage medium, specifically a computer-readable storage medium (Memory), which is a memory device in a terminal device for storing programs and data. It is understandable that the computer-readable storage medium here can include both the built-in storage medium in the terminal device and the extended storage medium supported by the terminal device, and can be any tangible medium containing or storing a program, which can be used by an instruction execution system, device or device or used in combination with it. The computer-readable storage medium provides a storage space, which stores the operating system of the terminal. In addition, one or more instructions suitable for being loaded and executed by the processor are also stored in the storage space, and these instructions can be one or more computer programs (including program codes). It should be noted that more specific examples (non-exhaustive list) of the computer-readable storage medium here include: an electrical connection with one or more wires, a portable 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 above.

[0230] Computer readable storage media also include data signals propagated in baseband or as part of a carrier wave, which carry readable program codes. Such propagated data signals can take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The readable storage medium can also be any readable medium other than a readable storage medium, which can send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, device, or device. The program code contained on the readable storage medium can be transmitted using any appropriate medium, including but not limited to wireless, wired, optical cable, RF, etc., or any suitable combination of the above.

[0231] Program code for performing the operations of the present invention may be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, etc., and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as a separate software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (e.g., through the Internet using an Internet service provider).

[0232] The processor may load and execute one or more instructions stored in a computer-readable storage medium to implement the corresponding steps of the power system investment decision evaluation method in the above embodiment; the processor may load and execute the following steps:

[0233] Based on the Logistic model, the curve fitting of the power grid development stage is carried out with per capita electricity consumption as an indicator, and the changing trend of the power grid development level over time t is analyzed to obtain the results of the power grid development stage assessment; according to the results of the power grid development stage assessment, the impact of the new power system on the investment structure of the power supply side, grid side, load side and energy storage side is analyzed, and the changes in the investment function requirements of the power supply side, grid side, load side and energy storage side are considered to construct the power supply side, grid side, load side and energy storage side investment demand system that adapts to the new power system; based on the constructed power supply side, grid side, load side and energy storage side investment demand system that adapts to the new power system, the investment capacity is calculated , combined with the investment scale in recent years, based on the investment capacity coefficient and the nuclear price investment coefficient, coordinate the investment capacity, investment demand, planned investment, nuclear price investment and electricity benefit constraints to determine the investment scale, as well as the boundary and scope of the power grid investment; determine the constraints and objective function of the power grid investment strategy optimization model based on the investment scale results and the boundary and scope of the power grid investment; based on the constraints and objective function of the power grid investment strategy optimization model, a multi-scenario power grid investment evaluation index system is formed according to different scenarios, and a multi-scenario power grid investment effectiveness evaluation model for a new power system is established. For typical scenarios under the construction of a new power system, a dynamic deduction of the power grid investment effectiveness is carried out.

[0234] See also Figure 7 , the terminal device is a computer device, and the computer device 60 of this embodiment includes: a processor 61, a memory 62, and a computer program 63 stored in the memory 62 and executable on the processor 61. When the computer program 63 is executed by the processor 61, the power system investment decision evaluation method in the embodiment is implemented. To avoid repetition, it is not described one by one here. Alternatively, when the computer program 63 is executed by the processor 61, the functions of each model / unit in the power system investment decision evaluation system in the embodiment are implemented. To avoid repetition, it is not described one by one here.

[0235] The computer device 60 may be a computing device such as a desktop computer, a notebook, a PDA, or a cloud server. The computer device 60 may include, but is not limited to, a processor 61 and a memory 62. Those skilled in the art will appreciate that Figure 7 This is only an example of the computer device 60 and does not constitute a limitation of the computer device 60. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the computer device may also include input and output devices, network access devices, buses, etc.

[0236] The processor 61 may be a central processing unit (CPU), or other general-purpose processors, central processing units, graphics processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, data processing logic based on quantum computing, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may be any conventional processor, etc.

[0237] The memory 62 may be an internal storage unit of the computer device 60, such as a hard disk or memory of the computer device 60. The memory 62 may also be an external storage device of the computer device 60, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc., equipped on the computer device 60.

[0238] Furthermore, the memory 62 may include both an internal storage unit of the computer device 60 and an external storage device. The memory 62 is used to store computer programs and other programs and data required by the computer device. The memory 62 may also be used to temporarily store data that has been output or is to be output.

[0239] Any reference to memory, database or other media used in the embodiments provided in the present application may include at least one of non-volatile and volatile memory. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory may include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM may be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0240] The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. The non-relational database may include a distributed database based on blockchain, etc., but is not limited thereto. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but is not limited thereto.

[0241] See also Figure 8 The terminal device 600 is an electronic device, and the electronic device is in the form of a general computing device. The components of the electronic device may include but are not limited to: at least one processing unit 610, at least one storage unit 620, a bus 630 connecting different platform components (including the storage unit 620 and the processing unit 610), a display unit 640, etc.

[0242] The storage unit stores program codes, which can be executed by the processing unit 610, so that the processing unit 610 executes the steps according to various exemplary embodiments of the present invention described in the above method part of this specification.

[0243] The storage unit 620 may include a readable medium in the form of a volatile storage unit, such as a random access memory unit (RAM) 6201 and / or a cache memory unit 6202 , and may further include a read-only memory unit (ROM) 6203 .

[0244] The storage unit 620 may also include a program / utility 6204 having a set (at least one) of program modules 6205, such program modules 6205 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.

[0245] Bus 630 may represent one or more of several types of bus structures, including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

[0246] The electronic device 600 may also communicate with one or more external devices 700 (e.g., keyboards, pointing devices, Bluetooth devices, etc.), may also communicate with one or more devices that enable a user to interact with the electronic device 600, and / or communicate with any device that enables the electronic device 600 to communicate with one or more other computing devices (e.g., routers, modems, etc.). Such communication may be performed via an input / output (I / O) interface 650. Furthermore, the electronic device 600 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) via a network adapter 660. The network adapter 660 may communicate with other modules of the electronic device 600 via a bus 630. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the electronic device 600, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage platforms, etc.

[0247] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. The components of the embodiments of the present invention described and shown in the drawings here can usually be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0248] For specific implementation, take Province A as an example to calculate the investment decision evaluation results of Province A:

[0249] By fitting the logistic curve of per capita electricity consumption in Province A, the fitting results are as follows: Fig. 9As shown, it shows that the power grid development in Province A is in a rapid development stage.

[0250] Based on the results of the grid development stage and the corresponding investment demand forecasting model, it is calculated that the centralized power supply investment on the power supply side of Province A is 621 million yuan. It is estimated that about 65% of distributed photovoltaics are sent at 380 volts and about 35% are sent at 10 kilovolts. The investment in distributed power sources is 314 million yuan, and the investment on the power supply side is 935 million yuan. The average annual investment in Province A from 2016 to 2020, 2021, 2022, 2023, and the remaining planned years are 92.03, 94.54, 90.99, and 105.88 respectively. , 15.876 billion yuan, and the calculated investment demand benchmark value is 14.882 billion yuan. Taking various factors into consideration, the investment demand index is 1.02, and the investment demand on the grid side is 15.180 billion yuan; Province A saves 326 million yuan on the demand side, of which 211 million yuan is saved on medium-voltage equipment, 125 million yuan is saved on low-voltage equipment, the demand response cost is 551 million yuan, and the investment demand on the load side is 225 million yuan; since there is no grid-side energy storage configuration, there is no investment on the energy storage side. Therefore, the investment demand in Province A is 16.340 billion yuan.

[0251] According to the investment capacity calculation formula, the investment capacity is calculated to be 13.506 billion yuan. The calculation results are shown in Table 1.

[0252] Table 1 Investment Capacity Calculation Table

[0253] years 2023 2024 (forecast) Net profit (100 million yuan) 3.97 4.31 Depreciation (100 million yuan) 91.64 96.89 East-West assistance funds and fiscal funds (100 million yuan) 1.89 1.86 Total assets at the end of the period (100 million yuan) 1186.98 1221.46 End-of-period debt-to-asset ratio (%) 54.25 53.68 Investment capacity (100 million yuan) — 135.06

[0254] The average investment scale in the past three years was 9.714 billion yuan, the investment capacity coefficient was 1.39, and the nuclear price investment was 11.82 billion yuan. The calculated nuclear price investment coefficient was 1.22. Since the investment capacity coefficient and the nuclear price investment coefficient are both greater than 1.1, the investment scale is the smaller value of the investment demand (16.34 billion yuan) and the electricity efficiency (16.826 billion yuan), which is 16.34 billion yuan.

[0255] Taking the 668 newly started projects in Province A as an example, the scores of each project were calculated by comprehensively considering the attributes of each project and the scoring criteria. Under the constraint of maximizing the total investment benefit, a multi-objective optimization solution for the projects was carried out based on the power grid investment strategy optimization model, and 659 projects were selected with a total investment amount of 15.98 billion yuan, which is the investment project portfolio with the greatest power grid investment benefit.

[0256] Taking into account the positioning, connotation and characteristics of the new power system, we set up basic scenarios, new energy development and accelerated electrification scenarios, and calculated the total efficiency of grid investment under different scenarios. The total investment efficiency of each scenario was 0.989, 0.997 and 0.992 respectively. The total investment efficiency of the scenario of rapid development of new energy was the highest. In the future, we should actively open up green channels to ensure the timing matching between the main body of new energy projects and the construction of transmission projects. At the same time, we should continue to provide good new energy grid connection and consumption services to realize large-scale and intensive development of new energy.

[0257] In summary, the present invention provides a power system investment decision evaluation method, system, medium and device, which have the following characteristics:

[0258] 1. Comprehensively consider multiple objectives such as safety and economy, extract the key factors that affect the investment demand of the power system, innovatively construct an analysis model for the evolution of the power grid investment function demand that adapts to the new power system, and clarify the mechanism of the impact of various factors on the change of the power grid investment function. Consider the changes in the power grid investment function demand and construct a power grid investment demand system that adapts to the new power system;

[0259] 2. Considering the differences between the level of power grid development and the level of economic and social development, based on the company's high-quality development evaluation index system, innovatively select key indicators and use intelligent algorithms to build a power grid investment strategy optimization model to select investment categories;

[0260] 3. Taking into account the characteristics of power grid investment from multiple dimensions such as economy and society, innovatively research the power grid investment evaluation index system, and build an investment effectiveness evaluation model to quantify the degree of change in power grid investment effectiveness based on the dynamic changes of evaluation indicators.

[0261] The above contents are only for explaining the technical idea of ​​the present invention and cannot be used to limit the protection scope of the present invention. Any changes made on the basis of the technical solution in accordance with the technical idea proposed by the present invention shall fall within the protection scope of the claims of the present invention.

Claims

1. A method for evaluating power system investment decisions. It is characterized in that The following steps are involved: Based on the Logistic model, the power grid development stage is fitted with a curve using per capita electricity consumption as an indicator, and the trend of power grid development level over time t is analyzed to obtain the results of the power grid development stage assessment. According to the results of the grid development stage research, the impact of the new power system on the investment structure of the power supply side, grid side, load side and energy storage side is analyzed. Considering the changes in the investment function requirements of the power supply side, grid side, load side and energy storage side, the investment demand system of the power supply side, grid side, load side and energy storage side that adapt to the new power system is constructed respectively; The investment capacity is calculated based on the investment demand system for the power supply side, grid side, load side and energy storage side that is adapted to the new power system. Combined with the investment scale in recent years, based on the investment capacity coefficient and the price-based investment coefficient, the investment capacity, investment demand, planned investment, price-based investment and electricity efficiency constraints are coordinated to determine the investment scale, as well as the boundaries and scope of grid investment; Determine the constraints and objective function of the grid investment strategy optimization model based on the investment scale results and the grid investment boundary and scope; Based on the constraints and objective function of the grid investment strategy optimization model, a multi-scenario grid investment evaluation index system is formed according to different scenarios, and a multi-scenario grid investment effectiveness evaluation model for a new power system is established. The grid investment effectiveness is dynamically deduced for typical scenarios under the construction of a new power system.

2. The power system investment decision evaluation method according to claim 1, It is characterized in that The changing trend of the power grid development level over time t is as follows: Among them, U(t) is the development level of the power grid; c is the saturation value of the power grid development; a and b are the parameters to be estimated; and t is time.

3. The power system investment decision evaluation method according to claim 1, It is characterized in that The investment demand system on the power supply side is as follows: C=C fb +C jz Among them, C is the total investment on the power supply side; C fb is the total investment of distributed power generation; C jz Invest in a centralized power supply.

4. The power system investment decision evaluation method according to claim 1, It is characterized in that The grid-side investment demand system is as follows: T=β×T 基 +D Among them, T is the power grid investment demand, β is the investment demand index, T 基 is the benchmark value of investment demand, and Δ is the number of new major projects.

5. The power system investment decision evaluation method according to claim 1, It is characterized in that The load-side investment demand system is as follows: L=L cb -L gxt -L zxt -L dxt Among them, L cb is the demand response cost; L is the load side investment scale; L gxt Save investment for high voltage substation; L zxt Save investment for medium voltage equipment; L dxt Save investment for low-voltage equipment.

6. The power system investment decision evaluation method according to claim 1, It is characterized in that The investment demand system for energy storage is as follows: W=W 1 -IN 2 -IN 3 Where W is the total investment cost of the energy storage system; W 1 is the energy storage system cost; W 2 W is the peak-valley arbitrage income of energy storage; 3 Subsidy cost for energy storage.

7. The power system investment decision evaluation method according to claim 1, It is characterized in that The investment scale is estimated as follows: I cGD =R c -Z J -Q c +FZ-FZ S Among them, I cGD Represents the fixed asset investment capacity of the enterprise during the forecast period; R c Represents the annual net profit during the forecast period, Z J represents the depreciation expense during the forecast period, Q c represents the equity investment received during the forecast period; FZ represents the total liabilities during the forecast period; FZ S Represents the total amount of liabilities in the previous year of the forecast period.

8. A power system investment decision evaluation system, It is characterized in that include: The trend module, based on the Logistic model, uses per capita electricity consumption as an indicator to perform curve fitting on the power grid development stage, analyzes the changing trend of the power grid development level over time t, and obtains the results of the power grid development stage assessment; System module: Analyze the impact of the new power system on the investment structure of the power supply side, grid side, load side and energy storage side according to the results of the grid development stage assessment, consider the changes in the investment function requirements of the power supply side, grid side, load side and energy storage side, and build the investment demand system of the power supply side, grid side, load side and energy storage side that adapt to the new power system; The calculation module calculates the investment capacity based on the investment demand system for the power supply side, grid side, load side and energy storage side that is adapted to the new power system. Combined with the investment scale in recent years, based on the investment capacity coefficient and the price-based investment coefficient, it coordinates the investment capacity, investment demand, planned investment, price-based investment and electricity efficiency constraints to determine the investment scale, as well as the boundaries and scope of grid investment. The construction module determines the constraints and objective function of the grid investment strategy optimization model based on the investment scale results and the grid investment boundary and scope; The evaluation module, based on the constraints and objective function of the power grid investment strategy optimization model, forms a multi-scenario power grid investment evaluation index system according to different scenarios, establishes a multi-scenario power grid investment effectiveness evaluation model for a new power system, and dynamically deduces the effectiveness of power grid investment for typical scenarios under the construction of a new power system.

9. A computer-readable storage medium storing one or more programs, It is characterized in that The one or more programs include instructions, which, when executed by a computing device, cause the computing device to perform the method of any one of claims 1 to 7.

10. A computing device, It is characterized in that include: One or more processors, a memory and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the one or more programs include steps for executing the method according to any one of claims 1 to 7.

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