Construction environment influence evaluation method and system based on internet of things distributed energy storage power station

Abstract

A kind of method and system for evaluating environmental impact of construction of distributed energy storage power station based on Internet of Things, the method comprises the following steps: S1, the initial value of the environment of several site selection areas before the construction of distributed energy storage power station is collected;S2, according to the bill of materials and engineering scope of constructing distributed energy storage power station, the first environmental impact factor of the construction process of distributed energy storage power station in several site selection areas is estimated;S3, the second environmental impact factor of distributed energy storage power station in use in several site selection areas is estimated;S4, an environmental impact assessment model is constructed, the first environmental impact factor and the second environmental impact factor are combined, the environmental impact assessment score of several site selection areas is estimated, and the suitable site selection area is selected for construction.The present application selects the site selection of suitable pumped storage distributed energy storage power station for construction and use through the screening process of scoring, reduces the short-term impact and long-term impact on the environment.

Description

Technical Field

[0001] This invention relates to environmental impact assessment methods, belonging to the field of environmental impact assessment technology for energy storage power stations, and particularly to a method and system for environmental impact assessment of construction of distributed energy storage power stations based on the Internet of Things. Background Technology

[0002] The environmental impact of power grid construction has long been limited to power transmission, tower installation, and noise pollution around substations. However, energy storage power stations continuously impact the surrounding environment during site selection, construction, operation, and maintenance, affecting and even persisting throughout the entire lifecycle of the energy storage power station.

[0003] The construction and operation phases have both temporary and long-term environmental impacts. To assess the environmental impact of distributed energy storage power stations, especially pumped-storage distributed energy storage power stations, it is necessary to sample lifecycle carbon emissions and, in conjunction with the energy storage-generation capacity of distributed energy storage power stations, construct an IoT-based environmental impact assessment method for the construction of distributed energy storage power stations. This method can quickly estimate carbon emissions during site selection and long-term operation, and thus evaluate the environmental impact of distributed energy storage power stations. Summary of the Invention

[0004] In view of this, the present invention proposes an environmental impact assessment method and system for the construction of distributed energy storage power stations based on the Internet of Things, which can acquire changes in the environmental conditions at the planned site in real time, estimate permanent and continuous carbon emissions during the construction and long-term operation, and then assess the environmental friendliness of the energy storage power station.

[0005] To achieve the above objectives, the technical solution of this invention is: a method for environmental impact assessment of the construction of a distributed energy storage power station based on the Internet of Things, comprising:

[0006] S1. Collect initial environmental values ​​for several site selection areas before the construction of distributed energy storage power stations;

[0007] S2. Based on the bill of materials and scope of work for the construction of distributed energy storage power stations, estimate the first environmental impact factor during the construction process of distributed energy storage power stations in several site selection areas.

[0008] S3. Estimate the second environmental impact factor of distributed energy storage power stations in several site selection areas during use;

[0009] S4. Construct an environmental impact assessment model, combine the first environmental impact factor and the second environmental impact factor, estimate the environmental impact assessment scores of several site selection areas, and select suitable site selection areas for construction.

[0010] Preferably, step S2 specifically includes:

[0011] S21. Obtain the types and quantities of materials required for the construction of the distributed energy storage power station from the bill of materials, and consider the processing margin;

[0012] S22. Calculate the carbon emissions E generated during the production process of various materials required for the construction of several site selection areas. manu ;

[0013] S23. Calculate the carbon emissions E generated during the transportation of various materials to several site selection areas. tran ;

[0014] S24. Calculate the carbon emissions E generated by the energy consumed during the construction of a distributed energy storage power station. cons And the carbon emissions E generated during the recycling of excess materials after construction. recl ;

[0015] S25. Calculate the carbon emissions ΔW and ΔF caused by the permanent change in the area of ​​the adjacent water body and the change in vegetation cover after the completion of the construction of the distributed energy storage power station.

[0016] S26. Based on the carbon emissions generated from the production, transportation, construction, recycling, permanent changes in water area, and changes in vegetation cover of the above-mentioned distributed energy storage power station, the first environmental impact factor EII1 is obtained.

[0017] More preferably, in step S26, the first environmental impact factor EII1 is calculated as follows:

[0018] EII1=E mamu +E tran +E cons +E recl +ΔW+ΔF;

[0019] The carbon emissions generated during the production process of various materials are as follows:

[0020]

[0021] Where: M i This represents the amount of material i used, where i = 1, 2, ..., n;

[0022] The carbon emissions generated during the transportation of various materials to several site areas are as follows:

[0023]

[0024] in: Let D be the carbon emission factor of the i-th material transported from the production site to the site selection area. i Let be the distance that the i-th material is transported from the production site to the selected site.

[0025] The carbon emissions generated by the energy consumed during the construction of distributed energy storage power stations are:

[0026]

[0027] Among them: E j Let j be the power corresponding to the energy used during construction, j = 1, 2, ..., m, m < n; Carbon emission factors of energy used during construction;

[0028] The carbon emissions generated during the recycling of excess materials after construction are:

[0029]

[0030] Where: R k Let n be the weight of the k-th material recycled, where k = 1, 2, ..., K, and K ≤ n; To account for the carbon emission factor generated during the recycling and transportation of the k-th material, d k The distance from the selected site to the recycling point. The carbon emission reduction factor when recycling the k-th material.

[0031] Furthermore, the carbon emissions resulting from permanent changes in the area of ​​adjacent water bodies are as follows:

[0032]

[0033] Where: ΔA p The permanent change in the area of ​​water body p caused by the construction of the distributed energy storage power station; Let r1 be the carbon emission factor of water body p; r1 is the correction factor for water body p, r1 = (a × e) -b×h )×(e T-20 )×β, a and b are empirical parameters, h is the average water depth of water area p, and T is the average ambient temperature; adjustment coefficient β∈(0,1); water area p is the water area within a circular area with radius R and the geometric center of the distributed energy storage power station, or the water area connected to the circular area.

[0034] Furthermore, the carbon emissions generated by changes in vegetation cover are:

[0035]

[0036] Where: ΔA s This represents the change in vegetation cover area. To reduce the carbon emission factor increased per unit area of ​​vegetation, r2 is the vegetation correction factor.

[0037] More preferably, step S3 specifically includes:

[0038] S31. Estimate the change in carbon emissions E(OP) from waste generated during the daily operation of a distributed energy storage power station over its life cycle;

[0039] S32. Based on the changes in soil pH during the daily operation of the distributed energy storage power station throughout its life cycle, estimate the change in carbon emissions E(pH) caused by the change in soil pH.

[0040] S33. Estimate the change in carbon emissions E(h) caused by the periodic storage or drainage of lakes during the debt life of a distributed energy storage power station.

[0041] S34. Taking into account the daily operation, soil pH changes, and carbon emission changes from periodic lake water storage or drainage during the above life cycle, the second environmental impact factor EII2 is obtained.

[0042] More preferably, the formula for calculating the second environmental impact factor EII2 is as follows:

[0043] EII2=E(OP)+E(pH)+E(h);

[0044] Among them, the change in carbon emissions from waste generated during daily operation is as follows:

[0045]

[0046] Where: L is the expected lifespan of the distributed energy storage power station, l = 1, 2, 3, ..., L; g pl The mass of waste generated per person per day on operating days; n pl τ represents the average number of employees per day on a given operating day. l The number of operating days per year; EF op Carbon emission factor of waste generated on operating days;

[0047] The change in carbon emissions caused by changes in soil pH is as follows:

[0048]

[0049] Where: N0 is the initial value of total soil nitrogen content within a circular area with radius R and the geometric center of the distributed energy storage power station; pH1 is the optimal pH value for nitrogen utilization; M0 is the standardization coefficient; pH2 is the critical pH value for heavy metal dissolution; EF ph Carbon emission factors are introduced to adjust the current soil pH to the initial value; P0 is the initial pH value after the construction of the distributed energy storage power station is completed, and pH3 is the median pH value of microbial activity; α, δ, γ and ε are all adjustment coefficients in the (0,1) interval.

[0050] The changes in carbon emissions caused by the periodic storage or drainage of water in lakes are as follows:

[0051] E(h)=Δh×ΔA′ p ×e -εLati ×[1+β(TT ref )]×EF h ;

[0052] Where: Δh is the average value of the lake height variation; ΔA′ p The lake's average area corresponds to the range of altitude variation; Lati is the lake's latitude deviation from the equator, 0 ≤ Lati < 90; T ref The average temperature of lakes at the same latitude; EF h Carbon emissions from the process of storing or draining water from lakes.

[0053] In a further preferred embodiment, step S4 specifically includes:

[0054] The expression for the environmental impact assessment model is:

[0055]

[0056] Where: k1 and k2 are proportional factors, k1,k2≥1; W is the power generation of the distributed energy storage power station throughout its entire life cycle; Score is the environmental impact assessment score, used to measure the amount of carbon emissions corresponding to each megawatt-hour of power generated during the entire life cycle of the distributed energy storage power station.

[0057] Preferably, an environmental impact assessment system for the construction of an IoT-based distributed energy storage power station is provided, which is applied to the above-mentioned method. The system includes:

[0058] The environmental data acquisition unit is used to collect initial environmental values ​​of several site selection areas before the construction of the distributed energy storage power station.

[0059] The first environmental impact factor acquisition unit is used to estimate the first environmental impact factor during the construction of distributed energy storage power stations in several site selection areas based on the bill of materials and engineering scope of the construction of distributed energy storage power stations.

[0060] The second environmental impact factor acquisition unit is used to estimate the second environmental impact factor of distributed energy storage power stations in several site areas during use.

[0061] An environmental impact assessment unit is used to construct an environmental impact assessment model, combine the first environmental impact factor and the second environmental impact factor, estimate the environmental impact assessment scores of several site selection areas, and select suitable site selection areas for construction.

[0062] Preferably, an environmental impact assessment device for the construction of an IoT-based distributed energy storage power station includes a processor and a memory.

[0063] The memory is used to store computer program code and to transmit the computer program code to the processor;

[0064] The processor is used to execute the above-mentioned environmental impact assessment method for construction of IoT-based distributed energy storage power stations according to the instructions in the computer program code.

[0065] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0066] This invention discloses an environmental impact assessment method and system for the construction of distributed energy storage power stations based on the Internet of Things (IoT). The method constructs a primary environmental impact factor during the construction of the distributed energy storage power station in the selected site area, designs the production, computation, construction, and recycling environment of related materials, and considers the permanent changes in water area and vegetation coverage resulting from the construction process. This facilitates accurate calculation of the overall carbon emissions during the construction phase. Furthermore, it incorporates the long-term impacts of waste generated by human activities, soil pH, and the cumulative effects of periodic storage and drainage on the environment during actual use. Combined with the power generation volume over the lifecycle of the distributed energy storage power station, the method quantitatively assesses the environmental impact of the construction and operation phases of the distributed energy storage power station, providing data support for better evaluating the energy-saving level and recommendation of the energy storage power station. Attached Figure Description

[0067] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0068] Figure 1 This is a flowchart of the method steps of the present invention.

[0069] Figure 2 This is a schematic diagram of the system structure of the present invention.

[0070] Figure 3 This is a schematic diagram of the device structure of the present invention.

[0071] In the figure: Environmental data acquisition unit 1, first environmental impact factor acquisition unit 2, second environmental impact factor acquisition unit 3, environmental impact assessment unit 4, processor 5, memory 6, computer program code 61. Detailed Implementation

[0072] The technical solutions of the present invention will be clearly and completely described below with reference to the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0073] Example 1:

[0074] like Figure 1 As shown, this invention provides a method for environmental impact assessment of the construction of an IoT-based distributed energy storage power station, comprising the following steps:

[0075] S1. Collect initial environmental values ​​for several site selection areas before the construction of distributed energy storage power stations;

[0076] Step S1 involves configuring an IoT-based distributed environmental acquisition unit to obtain ambient temperature, initial soil pH, initial water area, and initial vegetation cover for several selected sites. The IoT-based distributed environmental acquisition unit mainly includes sensing devices such as temperature sensors and pH sensors. The initial water area and initial vegetation cover can be obtained by image recognition from satellite images of the selected sites.

[0077] Once the location of the water body is determined, the number of pixels in the outline of the water body is confirmed based on the pixel resolution. If the pixels correspond to the actual size of 10m×10m or 15m×15m in the world coordinate system, the initial water body area can be obtained by accumulating the number of pixels in the outline of the water body.

[0078] Similarly, the initial vegetation coverage before construction is obtained by identifying the pixel area of ​​(vegetation-covered pixel area) / the neighborhood of the site selection area on the image of the site selection area.

[0079] The initial site selection requirements are to minimize the occupation of land in sensitive ecological areas, restore the ecology in a timely manner, and use environmentally friendly construction technologies and materials.

[0080] S2. Based on the bill of materials and scope of work for the construction of distributed energy storage power stations, estimate the first environmental impact factor during the construction process of distributed energy storage power stations in several site selection areas.

[0081] Step S2 specifically includes:

[0082] S21. Obtain the types and quantities of materials required for the construction of the distributed energy storage power station from the bill of materials, and appropriately consider a certain processing margin. The types and quantities of materials can be obtained from the BOM. Of course, depending on the size of the quantity, an appropriate 5%-10% material margin can be added to cope with temporary engineering changes.

[0083] S22. Calculate the carbon emissions E generated during the production process of various materials required for the construction of several site selection areas. manu The materials required for construction, such as concrete, cement, steel bars, metal structures, cables, sand and gravel, and tap water, as well as energy sources such as fuel oil or electricity, all involve significant energy consumption during production, and each material's production process generates corresponding carbon emissions. Carbon emission factor data for common materials can be obtained by consulting literature, such as 0.094 tCO2e / ton for concrete; 0.73 tCO2e / ton for cement; 2.1 tCO2e / ton for steel bars; 3.67 tCO2e / ton for diesel fuel; and 3.5 tCO2e / ton for gasoline, etc.

[0084] S23. Calculate the carbon emissions E generated during the transportation of various materials to several site selection areas. tran During the calculation, considering that the distance from the production site to the selected area is not exactly the same, and the means of transportation used are also not exactly the same, the weight of the material, the calculation distance, and the carbon emission factor corresponding to the fuel consumption per ton of material per kilometer are all taken into account. The carbon emissions E generated during the transportation process are obtained by summing them up. tran .

[0085] S24. Calculate the carbon emissions E generated by the energy consumed during the construction of a distributed energy storage power station. cons And the carbon emissions E generated during the recycling of excess materials after construction. recl The construction process mainly involves earthwork excavation, concrete pouring, and structure assembly, requiring the use of energy sources such as fuel, tap water, and electricity. Each energy source has a different carbon emission factor. If there are surplus engineering materials, and the demand for spare parts is met, the surplus materials can be recycled. When recycling, it is necessary to comprehensively consider the increased carbon emissions from transportation and the reduced carbon emissions from recycling the materials.

[0086] S25. Calculate the carbon emissions ΔW and ΔF caused by the permanent change in the area of ​​the adjacent water body and the change in vegetation cover after the completion of the construction of the distributed energy storage power station. During the construction of the distributed energy storage power station, the boundary of the water body and the vegetation cover may be permanently affected. Therefore, the permanent increase in carbon emissions caused by the change in the water body boundary and the change in vegetation cover is also calculated for such cases.

[0087] S26. Based on the carbon emissions generated from the production, transportation, construction, recycling, permanent changes in water area, and changes in vegetation cover of the above-mentioned distributed energy storage power station, the first environmental impact factor EII1 is obtained.

[0088] Specifically, the calculation method for the first environmental impact factor EII1 is as follows:

[0089] EII1=E mamu +E tran +E cons +E recl +ΔW+ΔF;

[0090] The carbon emissions generated during the production process of various materials are as follows:

[0091]

[0092] Where: M i This represents the amount of material i used (in tons), where i = 1, 2, ..., n; The carbon emission factor (unit: tCO2e / ton) for the production of the i-th material;

[0093] The carbon emissions generated during the transportation of various materials to several site areas are as follows:

[0094]

[0095] in: Let D be the carbon emission factor (unit: tCO2e / (km × ton)) of the i-th material transported from the production site to the site selection area. i The distance (in kilometers) for transporting the i-th material from the production site to the selected site.

[0096] The carbon emissions generated by the energy consumed during the construction of distributed energy storage power stations are:

[0097]

[0098] Among them: E j The energy used during construction has a power rating (in kilowatt-hours), and the energy type is j = 1, 2, ..., m, where m < n; The carbon emission factor (unit: tCO2e / kWh) of the energy used during construction; here, for the sake of uniform calculation, different energy sources are uniformly converted into power form.

[0099] The carbon emissions generated during the recycling of excess materials after construction are:

[0100]

[0101] Where: R k Let n be the weight (in tons) of the k-th material recovered, where k = 1, 2, ..., K, and K ≥ n; The carbon emission factor (in tCO2e / km) generated during the recycling and transportation of the k-th material, d k The distance (in kilometers) from the selected site to the recycling point. The carbon emission reduction factor (in tCO2e / ton) when recycling the kth material.

[0102] In one embodiment, the carbon emissions resulting from permanent changes in the area of ​​adjacent water bodies are calculated using the following formula:

[0103]

[0104] Where: ΔA p The permanent change in the area of ​​water body p caused by the construction of distributed energy storage power stations (unit: square kilometers); Let p be the carbon emission factor of the water body (unit: tCO2e / km²); r1 is the correction factor for p, r1 = (a × e) / km². -b×h )×(e T-20 )×β, a and b are empirical parameters, h is the average water depth of water area p, and T is the average ambient temperature; adjustment coefficient β∈(0,1); water area p is the water area within a circular area with radius R and the geometric center of the distributed energy storage power station, or the water area connected to the circular area.

[0105] Changes in lake area have an impact on carbon emissions, primarily based on the carbon storage and release process. Lakes store atmospheric carbon in their sediments by depositing organic matter. As lake area changes, the area of ​​organic sediments may shift, affecting carbon storage capacity and potentially increasing the probability of releasing carbon stored in the water. The correction factor r1 for the water area p is non-linear; if the lake area decreases, the adjustment factor β increases; conversely, if the lake area increases, the adjustment factor β decreases.

[0106] In one embodiment, the carbon emissions resulting from changes in vegetation cover are calculated using the following formula:

[0107]

[0108] Where: ΔA s This represents the change in vegetation cover area (unit: square kilometers). To reduce the carbon emission factor (tCO2e / km²) per unit area of ​​vegetation, r2 is the vegetation correction factor. The value range of the vegetation correction factor r2 is r2∈[0.5, 3].

[0109] The vegetation correction factor r² can be further subdivided into low and high ranges. The low range (r² = 0.5, 1.5) indicates that vegetation change has a relatively small impact on carbon emissions and will not significantly increase them. The high range (r² = 1.2, 3) indicates that vegetation change will significantly increase carbon emissions. Since vegetation has the ability to absorb and store carbon, changes in vegetation area can lead to carbon release or reduced carbon absorption. Changes in vegetation cover area can be identified from the images of the aforementioned site selection area.

[0110] Step S3 specifically includes:

[0111] S31. Estimate the change in carbon emissions E(OP) from waste generated during the daily operation of a distributed energy storage power station throughout its life cycle. This part involves different types of waste continuously generated by human activities, such as household waste, materials used to manufacture waste, and the carbon emissions generated from the disposal of such waste. Moreover, the amount of carbon emissions is directly proportional to the design life of the distributed energy storage power station, the number of personnel, and the annual operating time.

[0112] S32. Based on the changes in soil pH during the daily operation of the distributed energy storage power station throughout its life cycle, estimate the change in carbon emissions E(pH) caused by changes in soil pH. The relationship between fluctuations in soil pH and environmental impact is a complex issue involving multiple environmental factors, such as nutrient activity, heavy metal solubility, microbial activity, and soil erosion. In this invention, soil pH is selected to evaluate three aspects: nutrient availability, heavy metal solubility, plant growth stimulation, and microbial activity.

[0113] S33. Estimate the change in carbon emissions E(h) caused by the periodic storage or drainage of lakes during the debt life of a distributed energy storage power station. Here, the periodic changes in lake storage volume are taken into account, and the interaction between carbon emissions and lake volume, lake latitude and temperature is used to construct the relationship between carbon emissions E(h) during the storage and drainage stages.

[0114] S34. Taking into account the daily operation, soil pH changes, and carbon emission changes from periodic lake water storage or drainage during the above life cycle, the second environmental impact factor EII2 is obtained.

[0115] The formula for calculating the second environmental impact factor EII2 is as follows:

[0116] EII2=E(OP)+E(pH)+E(h);

[0117] Among them, the change in carbon emissions from waste generated during daily operation is as follows:

[0118]

[0119] Where: L is the expected lifespan of the distributed energy storage power station, l = 1, 2, 3, ..., L; g pl The mass of waste generated per person per day on operating days (unit: tons / (person·day)); n pl τ is the average number of employees (per person) per day on the operating day; l The number of operating days per year (in days); EF op Carbon emission factor of waste generated per operating day (unit: tCO2e / ton);

[0120] The change in carbon emissions caused by the change in soil pH is as follows:

[0121]

[0122] Where: N0 is the initial value of total soil nitrogen content within a circular area with radius R and the geometric center of the distributed energy storage power station; pH1 is the optimal pH value for nitrogen utilization, with an empirical pH value of 5.8; M0 is the standardization coefficient; pH2 is the critical pH value for heavy metal dissolution, with the critical pH value for heavy metal dissolution ranging from [9, 12]; EF ph Carbon emission factors are introduced to adjust the current soil pH to the initial value; P0 is the initial pH value after the construction of the distributed energy storage power station is completed; pH3 is the median pH value of microbial activity, with a value range of [5.0, 9.0]; α, δ, γ and ε are all adjustment coefficients in the (0, 1) interval.

[0123] The changes in carbon emissions caused by the periodic storage or drainage of water in lakes are as follows:

[0124] E(h)=Δh×ΔA′ p ×e -εLati ×[1+β(TT ref )]×EF h ;

[0125] Where: Δh is the average value of the lake height variation; ΔA′ p The lake's average area corresponds to the range of altitude variation; Lati is the lake's latitude deviation from the equator, 0 ≤ Lati < 90; T ref The average temperature of lakes at the same latitude; EF h E(h) represents the carbon emission factor (tCO2e / m³) during the lake's water storage or drainage process. v is an adjustment coefficient in the (0,1) interval; the smaller the value of Lati, the smaller the value of ε. It should be noted that E(h) is a cumulative value, and each water storage-drainage process needs to be calculated separately and accumulated.

[0126] S4. Construct an environmental impact assessment model, combine the first environmental impact factor and the second environmental impact factor, estimate the environmental impact assessment scores of several site selection areas, and select suitable site selection areas for construction.

[0127] In a further preferred embodiment, step S4 specifically includes:

[0128] The expression for the environmental impact assessment model is:

[0129]

[0130] Wherein: k1 and k2 are proportional factors, k1, k2≥1. The default value of k1 and k2 is 1. If the actual service life exceeds the design service life, the size of k1 and k2 is adjusted according to the ratio of the actual service life to the design service life to better calculate the first environmental impact factor and the second environmental impact factor accurately.

[0131] W represents the total power generation (in megawatt-hours) over the entire lifecycle of the distributed energy storage power station; Score represents the environmental impact assessment score (in tCO2e / megawatt-hour), used to measure the carbon emissions corresponding to one megawatt-hour of power generation over the entire lifecycle of the distributed energy storage power station. Different environmental impact assessment scores are given based on different intervals of the calculation results, as follows:

[0132]

[0133] The evaluation criteria are as follows: a positive evaluation indicates that the distributed energy storage power station has low carbon emissions per megawatt of power generation, demonstrating significant clean energy properties, and is therefore suitable for construction in the selected site. A negative evaluation indicates that the distributed energy storage power station has high carbon emissions per megawatt of power generation, and construction in the selected site is not recommended. A neutral evaluation falls between the positive and negative evaluations. Therefore, based on the calculation results, sites with a positive evaluation are prioritized for the construction of distributed energy storage power stations.

[0134] This method is applicable not only to distributed pumped storage power stations, but also to distributed photovoltaic power stations or distributed wind power stations. However, the contents of the first and second environmental impact factors considered in the specific construction and operation processes are not exactly the same.

[0135] Example 2:

[0136] See Figure 2 An environmental impact assessment system for the construction of an IoT-based distributed energy storage power station is provided. This system is applied to the method described in Example 1, and the system includes:

[0137] Environmental data acquisition unit 1 is used to collect initial environmental values ​​of several site selection areas before the construction of the distributed energy storage power station;

[0138] Furthermore, the initial environmental values ​​acquired by the environmental data acquisition unit 1 include: ambient temperature, initial soil pH value of several site selection areas, initial water area and initial vegetation coverage.

[0139] The first environmental impact factor acquisition unit 2 is used to estimate the first environmental impact factor in the construction process of distributed energy storage power stations in several site selection areas based on the bill of materials and engineering scope of the construction of distributed energy storage power stations.

[0140] Furthermore, the first environmental impact factor acquisition unit 2 acquires the first environmental impact factor according to the following steps:

[0141] S21. Obtain the types and quantities of materials required for the construction of the distributed energy storage power station from the bill of materials, and consider the processing margin;

[0142] S22. Calculate the carbon emissions E generated during the production process of various materials required for the construction of several site selection areas. manu ;

[0143] S23. Calculate the carbon emissions E generated during the transportation of various materials to several site selection areas. tran ;

[0144] S24. Calculate the carbon emissions E generated by the energy consumed during the construction of a distributed energy storage power station. cons And the carbon emissions E generated during the recycling of excess materials after construction. recl ;

[0145] S25. Calculate the carbon emissions ΔW and ΔF caused by the permanent change in the area of ​​the adjacent water body and the change in vegetation cover after the completion of the construction of the distributed energy storage power station.

[0146] S26. Based on the carbon emissions generated from the production, transportation, construction, recycling, permanent changes in water area, and changes in vegetation cover of the above-mentioned distributed energy storage power station, the first environmental impact factor EII1 is obtained.

[0147] The calculation method for the first environmental impact factor EII1 is as follows:

[0148] EII1=E mamu +E tran +E cons +E recl +ΔW+ΔF;

[0149] The carbon emissions generated during the production process of various materials are as follows:

[0150]

[0151] Where: M i This represents the amount of material i used, where i = 1, 2, ..., n; The carbon emission factor for producing the i-th material;

[0152] The carbon emissions generated during the transportation of various materials to several site areas are as follows:

[0153]

[0154] in: Let D be the carbon emission factor of the i-th material transported from the production site to the site selection area. i Let be the distance that the i-th material is transported from the production site to the selected site.

[0155] The carbon emissions generated by the energy consumed during the construction of distributed energy storage power stations are:

[0156]

[0157] Among them: E j Let j be the power corresponding to the energy used during construction, where j = 1, 2, ..., m, m < n; Carbon emission factors of energy used during construction;

[0158] The carbon emissions generated during the recycling of excess materials after construction are:

[0159]

[0160] Where: R k Let n be the weight of the k-th material recycled, where k = 1, 2, ..., K, and K ≤ n; To account for the carbon emission factor generated during the recycling and transportation of the k-th material, d k The distance from the selected site to the recycling point. The carbon emission reduction factor when recycling the k-th material.

[0161] The carbon emissions resulting from the permanent change in the area of ​​the adjacent water body are:

[0162]

[0163] Where: ΔA p The permanent change in the area of ​​water body p caused by the construction of the distributed energy storage power station; Let r1 be the carbon emission factor of water body p; r1 is the correction factor for water body p, r1 = (a × e) -b×h )×(e T-20)×β, a and b are empirical parameters, h is the average water depth of water area p, and T is the average ambient temperature; adjustment coefficient β∈(0,1); water area p is the water area within a circular area with radius R and the geometric center of the distributed energy storage power station, or the water area connected to the circular area.

[0164] The carbon emissions generated by the change in vegetation cover are:

[0165]

[0166] Where: ΔA s This represents the change in vegetation cover area. To reduce the carbon emission factor increased per unit area of ​​vegetation, r2 is the vegetation correction factor.

[0167] The second environmental impact factor acquisition unit 3 is used to estimate the second environmental impact factor of distributed energy storage power stations in several site areas during use.

[0168] Furthermore, the second environmental impact factor acquisition unit 3 acquires the second environmental impact factor according to the following steps:

[0169] S31. Estimate the change in carbon emissions E(OP) from waste generated during the daily operation of a distributed energy storage power station over its life cycle;

[0170] S32. Based on the changes in soil pH during the daily operation of the distributed energy storage power station throughout its life cycle, estimate the change in carbon emissions E(pH) caused by the change in soil pH.

[0171] S33. Estimate the change in carbon emissions E(h) caused by the periodic storage or drainage of lakes during the debt life of a distributed energy storage power station.

[0172] S34. Taking into account the daily operation, soil pH changes, and carbon emission changes from periodic lake water storage or drainage during the above life cycle, the second environmental impact factor EII2 is obtained.

[0173] The formula for calculating the second environmental impact factor EII2 is as follows:

[0174] EII2=E(OP)+E(pH)+E(h);

[0175] Among them, the change in carbon emissions from waste generated during daily operation is as follows:

[0176]

[0177] Where: L is the expected lifespan of the distributed energy storage power station, l = 1, 2, 3, ..., L; g pl The mass of waste generated per person per day on operating days; npl τ represents the average number of employees per day on a given operating day. l The number of operating days per year; EF op Carbon emission factor of waste generated on operating days;

[0178] The change in carbon emissions caused by changes in soil pH is as follows:

[0179]

[0180] Where: N0 is the initial value of total soil nitrogen content within a circular area with radius R and the geometric center of the distributed energy storage power station; pH1 is the optimal pH value for nitrogen utilization; M0 is the standardization coefficient; pH2 is the critical pH value for heavy metal dissolution; EF ph Carbon emission factors are introduced to adjust the current soil pH to the initial value; P0 is the initial pH value after the construction of the distributed energy storage power station is completed, and pH3 is the median pH value of microbial activity; α, δ, γ and ε are all adjustment coefficients in the (0,1) interval.

[0181] The changes in carbon emissions caused by the periodic storage or drainage of water in lakes are as follows:

[0182] E(h)=Δh×ΔA′ p ×e -εLati ×[1+β(TT ref )]×EF h ;

[0183] Where: Δh is the average value of the lake height variation; ΔA′ p The lake's average area corresponds to the range of altitude variation; Lati is the lake's latitude deviation from the equator, 0 ≤ Lati < 90; T ref The average temperature of lakes at the same latitude; EF h Carbon emissions from the process of storing or draining water from lakes.

[0184] Environmental impact assessment unit 4 is used to construct an environmental impact assessment model, combine the first environmental impact factor and the second environmental impact factor, estimate the environmental impact assessment scores of several site selection areas, and select suitable site selection areas for construction.

[0185] Furthermore, the environmental impact assessment model constructed by the environmental impact assessment unit 4 is as follows:

[0186]

[0187] Where: k1 and k2 are proportional factors, k1, k2≥1; W is the power generation of the distributed energy storage power station throughout its entire life cycle; Score is the environmental impact assessment score, used to measure the amount of carbon emissions corresponding to each megawatt-hour of power generated during the entire life cycle of the distributed energy storage power station.

[0188] Example 3:

[0189] See Figure 3 An environmental impact assessment device for the construction of a distributed energy storage power station based on the Internet of Things, the device including a processor 5 and a memory 6;

[0190] The memory 6 is used to store computer program code 61 and transmit the computer program code 61 to the processor 5;

[0191] The processor 5 is used to execute the environmental impact assessment method for construction of IoT-based distributed energy storage power stations as described in Embodiment 1, according to the instructions in the computer program code 61.

[0192] Although embodiments of the present invention have been shown and described above, it should be understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.

Claims

1. A method for environmental impact assessment of construction of distributed energy storage power stations based on the Internet of Things, characterized in that, include: S1. Collect initial environmental values ​​for several site selection areas before the construction of distributed energy storage power stations; S2. Based on the bill of materials and scope of work for the construction of distributed energy storage power stations, estimate the first environmental impact factor during the construction process of distributed energy storage power stations in several site selection areas. The first environmental impact factor includes carbon emissions from the production, transportation, construction, and recycling processes of the distributed energy storage power station, permanent changes in the area of ​​adjacent water bodies, and changes in vegetation cover. The carbon emissions resulting from the permanent change in the area of ​​the adjacent water body are: ； in: Water areas caused by the construction of distributed energy storage power stations The permanent change in area; For water area Carbon emission factors; For water area The correction factor , and These are empirical parameters. For water area Average water depth, The ambient average temperature; adjustment factor water area The distributed energy storage power station is centered on a circle with a radius of . The water area within the circular region or the water area connected to the circular region; S3. Estimate the second environmental impact factor of distributed energy storage power stations in several site selection areas during use; S4. Construct an environmental impact assessment model, combine the first environmental impact factor and the second environmental impact factor, estimate the environmental impact assessment scores of several site selection areas, and select suitable site selection areas for construction.

2. The method for environmental impact assessment of construction of a distributed energy storage power station based on the Internet of Things as described in claim 1, characterized in that: Step S2 specifically includes: S21. Obtain the types and quantities of materials required for the construction of the distributed energy storage power station from the bill of materials, and consider the processing margin; S22. Calculate the carbon emissions generated during the production process of various materials required for the construction of several site selection areas. ; S23. Calculate the carbon emissions generated during the transportation of various materials to several site selection areas. ; S24. Calculate the carbon emissions generated by the energy consumed during the construction of a distributed energy storage power station. And the carbon emissions generated during the recycling of excess materials after construction. ; S25. Calculate the carbon emissions resulting from the permanent change in the area of ​​the adjacent water body after the completion of the distributed energy storage power station construction. Carbon emissions from changes in vegetation cover ; S26. Taking into account the carbon emissions generated from the production, transportation, construction, and recycling processes of the distributed energy storage power station, as well as permanent changes in water area and vegetation cover, the first environmental impact factor is obtained. .

3. The method for environmental impact assessment of construction of a distributed energy storage power station based on the Internet of Things as described in claim 2, characterized in that: In step S26, the first environmental impact factor The calculation method is as follows: ； The carbon emissions generated during the production process of various materials are as follows: ； in: Indicates the first The amount of this material used ; For the production of the first Carbon emission factor of the material; The carbon emissions generated during the transportation of various materials to several site areas are as follows: ； in: For the first Carbon emissions from transporting materials from the production site to the site selection area For the first The distance the material is transported from the production site to the selected site; The carbon emissions generated by the energy consumed during the construction of distributed energy storage power stations are: ； in: The power output and energy type corresponding to the energy used during construction. , ; Carbon emission factors of energy used during construction; The carbon emissions generated during the recycling of excess materials after construction are: ； in: For the first The weight of recycled excess materials, , ; For the recovery and transportation of the first Carbon emissions generated when planting excess materials The distance from the selected site to the recycling point. To recycle the first The carbon emission factor is reduced when there is excess material.

4. The method for environmental impact assessment of construction of a distributed energy storage power station based on the Internet of Things as described in claim 3, characterized in that: The carbon emissions generated by the change in vegetation cover are: ； in: This represents the change in vegetation cover area. To reduce the carbon emission factors per unit area caused by vegetation, It is a vegetation correction factor.

5. The method for environmental impact assessment of construction of a distributed energy storage power station based on the Internet of Things as described in claim 3, characterized in that: Step S3 specifically includes: S31. Estimate the changes in carbon emissions from waste generated during the daily operation of a distributed energy storage power station throughout its lifecycle. ; S32. Based on the changes in soil pH during the daily operation of the distributed energy storage power station throughout its life cycle, estimate the changes in carbon emissions caused by changes in soil pH. ; S33. Estimate the changes in carbon emissions caused by the periodic storage or drainage of lakes during the debt lifecycle of a distributed energy storage power station. ; S34. Taking into account the daily operation, soil pH changes, and carbon emission changes from periodic lake water storage or drainage throughout the above life cycle, the second environmental impact factor is obtained. .

6. The method for environmental impact assessment of construction of a distributed energy storage power station based on the Internet of Things as described in claim 5, characterized in that: Second environmental impact factor The calculation formula is: ； Among them, the change in carbon emissions from waste generated during daily operation is as follows: ； in: For the expected lifespan of distributed energy storage power stations, ; The amount of waste generated per person per day on operating days; This represents the average number of employees per operating day. The number of operating days per year; Carbon emission factor of waste generated on operating days; The change in carbon emissions caused by changes in soil pH is as follows: ； in: It is the initial value of the total nitrogen content in the soil within a circular area with radius R, centered on the geometric center of the distributed energy storage power station. The optimal pH value for nitrogen utilization; These are the standardized coefficients; This is the critical pH value for the dissolution of heavy metals; Carbon emission factors introduced to adjust the current soil pH to its initial value; This refers to the initial pH value after the completion of construction of the distributed energy storage power station. The median pH value for microbial activity; , , All Adjustment factor for the interval; The changes in carbon emissions caused by the periodic storage or drainage of water in lakes are as follows: ； in: This represents the average value of the lake's height variation; The average area of ​​the lake corresponding to the range of lake height variation; This represents the latitude of the lake relative to the equator. ; The average temperature of lakes at the same latitude; Carbon emission factors during lake water storage or drainage processes; for Adjustment factor for the interval.

7. The method for environmental impact assessment of construction of a distributed energy storage power station based on the Internet of Things as described in claim 6, characterized in that: Step S4 specifically includes: The expression for the environmental impact assessment model is: ； in: and As a scaling factor, ; This refers to the total power generation of a distributed energy storage power station throughout its entire lifecycle. The environmental impact assessment score is used to measure the amount of carbon emissions corresponding to one megawatt-hour of electricity generated throughout the entire life cycle of a distributed energy storage power station.

8. An environmental impact assessment system for the construction of a distributed energy storage power station based on the Internet of Things, characterized in that: The system is applied to the method according to any one of claims 1-7, the system comprising: Environmental data acquisition unit (1) is used to collect initial environmental values ​​of several site selection areas before the construction of distributed energy storage power stations; The first environmental impact factor acquisition unit (2) is used to estimate the first environmental impact factor in the construction process of distributed energy storage power stations in several site selection areas based on the bill of materials and engineering scope of the construction of distributed energy storage power stations. The first environmental impact factor includes carbon emissions from the production, transportation, construction, and recycling processes of the distributed energy storage power station, permanent changes in the area of ​​adjacent water bodies, and changes in vegetation cover. The carbon emissions resulting from the permanent change in the area of ​​the adjacent water body are: ； in: Water areas caused by the construction of distributed energy storage power stations The permanent change in area; For water area Carbon emission factors; For water area The correction factor , and These are empirical parameters. For water area Average water depth, The ambient average temperature; adjustment factor water area The distributed energy storage power station is centered on a circle with a radius of . The water area within the circular region or the water area connected to the circular region; The second environmental impact factor acquisition unit (3) is used to estimate the second environmental impact factor of distributed energy storage power stations in several site selection areas during use. Environmental impact assessment unit (4) is used to construct an environmental impact assessment model, combine the first environmental impact factor and the second environmental impact factor, estimate the environmental impact assessment scores of several site selection areas, and select suitable site selection areas for construction.

9. An environmental impact assessment device for the construction of an IoT-based distributed energy storage power station, characterized in that: The device includes a processor (5) and a memory (6); The memory (6) is used to store computer program code (61) and to transmit the computer program code (61) to the processor (5). The processor (5) is used to execute the construction environmental impact assessment method for any one of claims 1-7 based on the Internet of Things distributed energy storage power station according to the instructions in the computer program code (61).

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