A method for generating and optimizing layout schemes for productive rooftop renovation

Abstract

The present invention discloses a method for generating and optimizing a layout plan for productive rooftop renovation, comprising the following steps: Step 1, establishing a 3D model of a block; Step 2, picking up a geometric model of the block and a selected renovation roof; Step 3, simulating the physical environment and screening suitable roofs; Step 4, calculating the average annual output per unit area of ​​each suitable roof when applying different production strategies; Step 5, calculating the cost-benefit coefficient of applying different strategies. k ,Step 6, input the cost-benefit coefficient into the multi-objective optimization module in the selection order, and obtain the optimal configuration scheme of the roof renovation strategy. In the optimal configuration scheme, F max 、E max Cost min Step 7: The multi-dimensional evaluation calculation model generates resource indicators, economic indicators, and environmental indicators for each configuration scheme as decision support for optimizing the configuration scheme. This invention can provide comprehensive, rapid, and accurate decision support for rooftop renovations.

Description

Technical Field

[0001] The present invention relates to the field of urban renewal technology, and in particular to a method for generating and optimizing a layout plan for productive rooftop renovation, which is applicable to the planning and design of rooftop renovation in urban blocks. Multiple sets of optimal planning methods can be obtained based on basic site information and design objectives. Background Art

[0002] Urbanization is rapidly advancing. Currently, more than half of the world's population lives in cities, and by 2050, approximately 70% of the world's population is projected to live in cities. This expansion of urban areas will inevitably encroach on suburban land, primarily used for agricultural production, placing enormous pressure on food production and distribution. Furthermore, the spatial distance between agricultural production and consumption is further increasing, leading to increased agricultural mileage and incurring additional environmental pressures and economic costs. The vast amount of unused rooftop space in cities can serve as a direct vehicle for urban agriculture and clean energy production. Therefore, designers must conduct a thorough assessment and planning of the physical and energy production of target blocks during the design phase to achieve a scientific and efficient, productive transformation design.

[0003] Currently, there are few design methods for increasing productivity in urban renewal, and most focus on assessing and planning a single resource type. In agriculture, total yield is generally estimated based on empirical data and available planting area. In energy, renewable energy production software is used to simulate current design solutions to obtain a simulated overall system output. Adjustments are then made based on the results compared to pre-determined design targets. This approach relies too heavily on empirical data, ignoring the impact of complex urban morphology on environmental factors that influence resource production, such as solar radiation, sunshine duration, and temperature. Consequently, it fails to accurately assess resource production potential. Furthermore, the lack of a coordinated approach to planning and design for multiple resources can easily lead to overproduction of certain resources and underproduction of others. This not only wastes resources and production space, but also defeats the purpose of localized resource production. In summary, conventional design methods, limited by designers' experience, conventional process mindsets, and technical tools, suffer from low accuracy in assessing production potential, limited solution optimization, and a significant workload. Traditional design methods not only require designers to have prior experience in urban agriculture and renewable energy design, but also consume significant time and effort in repeated comparisons and revisions, making them unsuitable for the work needs of grassroots planning and architectural professionals. With the advancement of the "urban dual renovation" concept in urban renewal in my country, local design professionals are urgently seeking simple and rapid configuration methods and practical tools for productive renovation of urban rooftops. Summary of the Invention

[0004] The purpose of the present invention is to address the technical defects existing in the prior art and provide a method for generating and optimizing a rooftop productive transformation layout plan, so as to carry out urban agriculture and photovoltaic power generation transformation on the roofs of specific areas, thereby solving the technical problems of inaccurate potential assessment, discontinuous environmental simulation and potential calculation, insufficient space utilization caused by the inability to coordinate multiple resources, and inefficient result comparison and modification.

[0005] The technical solution adopted to achieve the purpose of the present invention is:

[0006] A method for generating and optimizing a layout plan for a productive rooftop renovation comprises the following steps:

[0007] Step 1: Create a 3D model of the urban block that needs to undergo rooftop productive transformation in the simulation module;

[0008] Step 2, picking up the block geometry model and the selected remodeled roof in the block 3D model obtained in step 1;

[0009] Step 3: Extract the regional environmental data throughout the year. Enter information such as the sun's trajectory, radiation intensity, and hourly sunshine duration into the environmental simulation calculator. Perform a physical environmental simulation on the selected roofs from Step 2, and select roofs that meet the physical environmental conditions as suitable roofs.

[0010] Step 4: Establish agricultural potential calculation models and photovoltaic potential calculation models to calculate the average annual yield per unit area of ​​each suitable roof when applying different production strategies, including open-air cultivation, rooftop photovoltaics, rooftop greenhouses, and photovoltaic greenhouses;

[0011] When the production strategy is open-air planting or rooftop greenhouse, the annual average yield is the annual average agricultural yield; when the production strategy is rooftop photovoltaic, the annual average yield is the annual average photovoltaic yield; when the production strategy is photovoltaic greenhouse, the annual average yield includes the annual average agricultural yield and the annual average photovoltaic yield. The agricultural potential calculation model is used to calculate the annual average agricultural yield per unit area, and the photovoltaic potential calculation model is used to calculate the annual average photovoltaic yield per unit area;

[0012] Step 5: Based on the average annual output and renovation cost obtained in step 4, run an iterative calculation to obtain the cost-benefit coefficient of each roof under different strategies. k , used to indicate the degree to which a roof is more suitable for a certain strategy, and is used as a screening criterion in the optimization operator;

[0013] Step 6: The cost-benefit coefficients of open-air planting, rooftop photovoltaic, rooftop greenhouse and photovoltaic greenhouse rooftop transformation obtained in step 5 are calculated as follows: kInput the "cost-benefit coefficient of system one", "cost-benefit coefficient of system two" and "cost-benefit coefficient of system three" in the multi-objective optimization module in the order of selection. The remaining transformation strategies are automatically input into the multi-objective optimization module as "cost-benefit coefficient of system four". Input the suitable roofs obtained in step 3 into the multi-objective optimization module. The constraint condition is that the total number of roofs to be transformed must not exceed the total number of roofs in the block, but roofs that have not been updated are allowed. Then, the proportion of each production strategy is obtained through the genetic algorithm to obtain the optimal configuration scheme of the roof transformation strategy. In the optimal configuration scheme, the total agricultural output is maximized Fmax, the total photovoltaic output is maximized Emax, and the total transformation cost is minimized Costmi n ;

[0014] Step 7: In the multidimensional evaluation module, a multidimensional evaluation calculation model for roof renovation plans is established based on the economic benefits and environmental impacts of various roof renovation strategies. Based on the optimized configuration plan obtained in step 6, the multidimensional evaluation calculation model generates resource indicators, economic indicators, and environmental indicators for each configuration plan as decision support for the optimized configuration plan.

[0015] In the above technical solution, in step 1, the basic geometric shape is created in Rhino software and then imported into the Grasshopper platform to create a 3D model of the block.

[0016] In the above technical solution, in step 3, operational meteorological data in EPW format is imported into the simulation module to extract the sun's trajectory path, radiation intensity information and temperature information in the area.

[0017] In the above technical solution, in step 3, a parametric model is established on the Grasshopper platform, an environmental simulation calculation kernel is formed through the Ladybug program in the platform, and suitable roofs are screened based on plant growth conditions and photovoltaic potential thresholds.

[0018] In the above technical solution, in step 4, the average annual agricultural yield per unit area is calculated using an agricultural potential calculation model, which is:

[0019] Y pt =1.522×10 -5 ×(1-α)(1-β)(1-γ)×q×f t ;

[0020] f t =4.301×10 -2 t-5.771×10- 4 t 2 ;

[0021] Y ptis the agricultural output per square meter per year, f t is the temperature correction function, α is the reflectivity, α=0.83L i / L0, L0 is the maximum leaf area index; L i is the leaf area index in a certain period of time; β is the leakage rate; γ is the light saturation limit, that is, the proportion of light exceeding the light saturation point; q is the total solar radiation projected per unit area per unit time, and t is the annual average temperature.

[0022] In the above technical solution, in step 4, the average annual photovoltaic output per unit area is calculated using a photovoltaic output calculation model, which is:

[0023] E e =I G ×PV×K×(1-R d ) N-1

[0024] Among them E e is the photovoltaic output per square meter per year, I G is the annual accumulated solar radiation on the roof surface, obtained from the physical environment simulation in step 3. PV is the photoelectric conversion efficiency of the photovoltaic module, and K is the energy efficiency ratio.

[0025] In the above technical solution, in step 5, the cost-benefit coefficient Self k The calculation method is:

[0026]

[0027] Yield k The annual output per unit area using k types of production strategies for each roof; Population is the total population of the block; Per k is the per capita resource demand; Cost k is the transformation cost per unit area of ​​type k production strategy; x k The roof area that is transformed to implement type k production strategy, where k is open-air cultivation, rooftop photovoltaics, rooftop greenhouse or photovoltaic greenhouse.

[0028] In the above technical solution, in step 6, the calculation formula for total agricultural output is:

[0029]

[0030] F is the total agricultural output; n is the number of types of rooftop agricultural production transformation strategies; a j is the agricultural output per unit area of ​​the j-type production strategy in rooftop agricultural production; x j It is the area that can be used for production of type j agricultural production.

[0031] The total photovoltaic output is calculated as:

[0032]

[0033] E is the total photovoltaic output; m is the number of rooftop power production transformation strategies; b i is the photovoltaic output per unit area of ​​type i production strategy in rooftop electricity production; y i It is the area where Class I electricity production can be used for production.

[0034] The total cost of the renovation is calculated using the total renovation cost calculation model, which is:

[0035]

[0036] Cost is the total cost of transformation; n is the number of types of rooftop agricultural production transformation strategies; Cost j is the unit cost of production strategy type j in rooftop agriculture production; x j is the area that can be used for production under the j-type agricultural production situation; m is the number of types of rooftop power production transformation strategies; y i is the area where Class I electricity production can be used for production; Cost i is the unit cost of type i production strategy in rooftop photovoltaic production.

[0037] In the above technical solution, in step 7, the production potential calculation core in the multidimensional evaluation model calculates resource indicators, and the resource indicators include agricultural self-sufficiency rate and energy self-sufficiency rate; the economic indicator calculation core in the multidimensional evaluation model calculates economic indicators, and the economic indicators include return on investment and investment payback period; the environmental impact calculation core in the multidimensional evaluation model calculates environmental indicators, and the environmental indicators include global warming potential, water consumption, electricity consumption, agricultural mileage carbon reduction potential, and renewable energy carbon reduction potential.

[0038] In the above technical solution, the calculation formula for agricultural self-sufficiency rate is:

[0039]

[0040] Vegetable self is the agricultural self-sufficiency rate; k is the average annual output per unit of type k production strategy; x k The roof area that is transformed for type k production strategy; Population is the total population of the block; Per k is the per capita resource demand;

[0041] The formula for calculating energy self-sufficiency rate is:

[0042]

[0043] Among them, Electric self is the energy self-sufficiency rate; a l is the average annual output per unit of type l production strategy; x l The roof area that is modified for type l production strategy; Population is the total population of the block; Per l l is the per capita resource demand;

[0044] The formula for calculating return on investment is:

[0045]

[0046] ROI is the return on investment; t Cost is the annual income; t is the total annual expenditure; Investment is the initial cost;

[0047]

[0048] Investment is the initial cost; n is the number of rooftop agricultural production transformation strategies; Cost j is the unit cost of production strategy type j in rooftop agriculture production; x j is the area that can be used for production under the j-type agricultural production situation; m is the number of types of rooftop power production transformation strategies; b i is the average annual output per unit of production strategy type i in rooftop agricultural production; y i is the area where Class I electricity production can be used for production; Cost i is the unit cost of type i production strategy in rooftop photovoltaic production.

[0049] The specific calculation method of the investment return period is as follows:

[0050]

[0051] Paybacktime is the investment return period; Revenue t Cost is the annual income; t is the total annual expenditure; Investment is the initial cost.

[0052] The calculation method for the carbon reduction potential of agricultural mileage is:

[0053] F c =P veg ×J×L

[0054] Among them F c Reduce carbon emissions from agricultural mileage;veg represents the total agricultural transport volume; J represents the average carbon dioxide emissions per ton of agricultural transport per kilometer; L represents the agricultural transport mileage.

[0055] The calculation method for the carbon reduction potential of renewable energy is:

[0056] E c =P ele ×J

[0057] Among them F c Reduce carbon emissions from agricultural mileage; veg represents the total agricultural transport volume; J represents the average carbon dioxide emissions per ton of agricultural transport per kilometer; L represents the agricultural transport mileage.

[0058] Compared with the prior art, the present invention has the following beneficial effects:

[0059] 1. The present invention establishes a method for generating and optimizing layout plans for productive roof renovations, which can quickly generate a relatively optimal set of plans under multiple conflicting objectives, providing comprehensive, fast and accurate decision-making support for productive roof renovation plans. This eliminates the need for designers to manually calculate, compare and modify plans, thereby improving design efficiency.

[0060] 2. The present invention utilizes a precise environmental simulation operator and a resource yield calculation formula based on the physical environment. Only basic environmental information needs to be input to accurately calculate the agricultural and photovoltaic production potential in a complex urban environment, making it convenient for designers who lack knowledge of urban agriculture and photovoltaics to use.

[0061] 3. The operation method of the present invention is simple and fast. It relies on the visualization of the spatial effects of the scheme using Rhinoceros and Grasshopper platforms, which are commonly used in the architectural planning industry. The results are more intuitive and can be directly deepened based on the optimization results. It has strong practicality and scalability and can adapt to the practical application in the design stage of rooftop productive transformation schemes in different regions. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1 Shown is a principle flow chart of a method for generating and optimizing a layout plan for productive rooftop renovation.

[0063] Figure 2 It is the Pareto optimal solution set for the productive transformation of the roofs of the building in the case block obtained based on the multi-objective optimization algorithm in step 6.

[0064] Figure 3 This is a schematic diagram of the rooftop productive transformation configuration plan obtained in step 6. Roofs of different colors represent different transformation plans. DETAILED DESCRIPTION

[0065] The present invention will be further described in detail below with reference to specific embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0066] Example 1

[0067] A method for generating and optimizing a layout plan for a productive rooftop renovation comprises the following steps:

[0068] Step 1: Select the urban block that needs to undergo rooftop productive transformation and create a 3D model of the block:

[0069] Rhino software was used as a program visualization and 3D modeling tool to draw the geometric model of the target block.

[0070] Step 2, picking up the block geometry model and the selected remodeled roof in the block 3D model obtained in step 1;

[0071] Using Grasshopper as the parametric programming platform, pick up the geometric model drawn in Rhino software in step 1 and the selected renovated roof respectively.

[0072] Step 3: Extract the regional environmental data throughout the year. Enter information such as the sun's trajectory, radiation intensity, and hourly sunshine duration into the environmental simulation calculator. Then, select the selected roofs for renovation obtained in Step 2, perform a physical environmental simulation on them, and select roofs that meet the physical environmental conditions as suitable roofs.

[0073] Step 4: Build agricultural potential calculation models and photovoltaic potential calculation models in Grasshopper to calculate the average annual yield per unit area for each suitable roof when applying different production strategies, including open-air cultivation, rooftop photovoltaics, rooftop greenhouses, and / or photovoltaic greenhouses.

[0074] When the production strategy is open-air planting or rooftop greenhouse, the average annual yield per unit area is k is the annual agricultural output. When the production strategy is rooftop photovoltaics, the average annual yield per unit area is Yield k is the annual output of photovoltaics. When the production strategy is photovoltaic greenhouse, the annual average output per unit area is Yield k Including annual agricultural output and annual photovoltaic output;

[0075] The average annual agricultural output per unit area is calculated using the agricultural potential calculation model, which is:

[0076] Y pt =1.522×10 -5 ×(1-α)(1-β)(1-γ)×q×f t

[0077] f t =4.301×10 -2 t-5.771×10 -4 t 2

[0078] Among them, Y pt is the agricultural output per square meter per year, f t is the temperature correction function. α is the reflectivity, which can be written as a linear function with the growth of leaf area during the entire crop growth period: α=0.83L i / L0, where L0 is the maximum leaf area index; L i is the leaf area index for a certain period of time; β is the light leakage rate, and the amount of light leaking onto the soil surface varies with different crop groups and different growth stages; γ is the light saturation limit, that is, the proportion of light exceeding the light saturation point; q is the total solar radiation projected per unit area per unit time (wh / m 2 ). t is the annual average temperature, in degrees Celsius (℃).

[0079] The average annual photovoltaic output per unit area is calculated using the photovoltaic output calculation model, which is:

[0080] E e =I G ×η PV ×K×(1-R d ) N-1

[0081] Among them E e is the photovoltaic output per square meter per year. G is the annual accumulated solar radiation on the roof surface, obtained from the physical environment simulation in step 3. PV = is the photovoltaic module's photoelectric conversion efficiency, which is determined by the module type. K is the overall efficiency coefficient, also known as the energy efficiency ratio, which represents the conversion efficiency of the entire system from input to output. It reflects the efficiency of the entire photovoltaic system after energy losses due to a series of factors such as the inverter, temperature, shading, dust, and circuit losses.

[0082] Step 5: Based on the average annual output and transformation cost obtained in step 4, iteratively calculate the cost-benefit coefficient of each roof when applying different production strategies (open-air planting, rooftop photovoltaic, rooftop greenhouse, photovoltaic greenhouse) k , the formula is as follows:

[0083]

[0084] Among them, Self k The cost-benefit coefficient for self-sufficiency of each roof; Yield kThe annual output per unit area of ​​each roof using the k-type production strategy; Population is the total population of the block, the data comes from the seventh census of China; Per k is the per capita resource demand; Cost k is the transformation cost per unit area of ​​type k production strategy, obtained through market data; x k Rooftop area converted for type k production strategy, where k is open-air cultivation, rooftop photovoltaics, rooftop greenhouses, or photovoltaic greenhouses. Data from the 2023 Tianjin Statistical Yearbook.

[0085] Step 6. Input the "cost-benefit coefficient of system 1", "cost-benefit coefficient of system 2", and "cost-benefit coefficient of system 3" of each strategy obtained in step 4 into the input end of the multi-objective optimization module as the basis for determining the use of the roof. The input order represents the priority of the roof renovation type selected by the user. After entering the first three cost-benefit coefficients, the system defaults to the "cost-benefit coefficient of system 4" for the strategy not entered. The suitable roof obtained in step 3 is input into the multi-objective optimization module.

[0086] Connect the "cost-benefit coefficient of system 1", "cost-benefit coefficient of system 2", "cost-benefit coefficient of system 3", and "cost-benefit coefficient of system 4" to the variable end of Octopus in the Grasshopper platform, and connect the "total agricultural output", "total photovoltaic output", and "total transformation cost" at the output end of the "multi-objective optimization module" to the target end of Octopus.

[0087] The constraint is that the total number of roofs to be renovated must not exceed the total number of roofs in the block, but some roofs that have not been renovated are allowed. The specific expression is as follows: Among them, NumberRoof is the total number of roofs in the target block, s is the s-type production strategy, Roof s is the number of rooftops occupied by the s-type strategy.

[0088] The formula for calculating total agricultural output is:

[0089]

[0090] F is the total agricultural output, in kg; n is the number of types of rooftop agricultural production transformation strategies; a j is the agricultural output per unit area of ​​production strategy j in rooftop agricultural production, in kg / m 2 ;x j is the area available for production in agricultural production type j, in m 2 .

[0091] The total photovoltaic output is calculated as:

[0092]

[0093] E is the total photovoltaic output, in kWh; m is the number of rooftop power production transformation strategies; b is the total photovoltaic output, in kWh; i is the photovoltaic output per unit area of ​​type i production strategy in rooftop electricity production, in kWh / m 2 ;y i is the area where type i electricity production can be used for production, in m 2 .

[0094] The total cost of the renovation is calculated using the total renovation cost calculation model, which is:

[0095]

[0096] Cost is the total cost of transformation, in RMB; n is the number of types of rooftop agricultural production transformation strategies; Cost j is the unit cost of production strategy type j in rooftop agricultural production, in yuan / m 2 ;x j is the area that can be used for production under the j-type agricultural production situation, in m 2 ;m the number of rooftop power production transformation strategies;b i is the average annual output per unit of production strategy type i in rooftop agricultural production, in kWh / m 2 ;y i is the area where type i electricity production can be used for production, in m 2 Cost i is the unit cost of type i production strategy in rooftop photovoltaic production, in yuan / Kw / h.

[0097] The mathematical expression of Octopus multi-objective optimization is: max 、E max Cost min , which respectively represent the maximization of total agricultural output, the maximization of total photovoltaic output, and the minimization of total transformation cost.

[0098] The Pareto optimal solution set for the productive transformation of the rooftops of the case block buildings obtained based on the multi-objective optimization algorithm in step 6 is as follows: Figure 2 As shown in the figure, the schematic diagram of the rooftop productive transformation configuration scheme is as follows Figure 3 shown.

[0099] Step 7: In the multidimensional evaluation module, a multidimensional evaluation calculation model for roof renovation plans is established based on the economic benefits and environmental impacts of various roof renovation strategies. Based on the optimized configuration plan obtained in step 6, the multidimensional evaluation calculation model generates resource indicators, economic indicators, and environmental indicators for each configuration plan as decision support for the optimized configuration plan.

[0100] The production potential calculation core in the multidimensional evaluation model calculates resource indicators, and the resource indicators include agricultural self-sufficiency rate and energy self-sufficiency rate; the economic indicator calculation core in the multidimensional evaluation model calculates economic indicators, and the economic indicators include return on investment and investment payback period; the environmental impact calculation core in the multidimensional evaluation model calculates environmental indicators, and the environmental indicators include global warming potential, water consumption, electricity consumption, agricultural mileage carbon reduction potential, and renewable energy carbon reduction potential.

[0101] The formula for calculating agricultural self-sufficiency rate is:

[0102]

[0103] Vegetable self is the agricultural self-sufficiency rate, a k is the average annual output per unit of type k production strategy; x k The roof area that is transformed for the k-type production strategy; Population is the total population of the block, the data comes from the seventh census of China; Per k is the per capita resource demand, and the data comes from the "2023 Tianjin Statistical Yearbook".

[0104] The specific method for energy self-sufficiency rate is as follows:

[0105]

[0106] Among them, Electric self is the energy self-sufficiency rate; a l is the average annual output per unit of type l production strategy; x l The roof area that has been transformed for type l production strategy; Population is the total population of the block, the data comes from the seventh census of China; Per l l is the per capita resource demand, and the data comes from the "2021 Tianjin Statistical Yearbook".

[0107] The specific method of initial cost is as follows:

[0108]

[0109] Investment is the initial cost, in yuan; n is the number of types of rooftop agricultural production transformation strategies; Costj is the unit cost of production strategy type j in rooftop agricultural production, in yuan / m 2 ;x j is the area that can be used for production under the j-type agricultural production situation, in m 2 ;m the number of rooftop power production transformation strategies;b i is the average annual output per unit of production strategy type i in rooftop agricultural production, in kWh / m 2 ;y i is the area where type i electricity production can be used for production, in m 2 Cost i is the unit cost of type i production strategy in rooftop photovoltaic production, in yuan / Kw / h.

[0110] The specific calculation method for return on investment (ROI) is as follows:

[0111]

[0112] ROI is the return on investment; t Cost is the annual income; t is the total annual expenditure; Investment is the initial cost.

[0113] The specific calculation method of investment return period is as follows:

[0114]

[0115] Paybacktime is the investment return period; Revenue t Cost is the annual income; t is the total annual expenditure;

[0116] Investment is the initial cost.

[0117] The calculation method for the carbon reduction potential of agricultural mileage is:

[0118] F c =P veg ×J×L

[0119] Among them F c is the carbon reduction of agricultural mileage, in units of P veg represents the total amount of agricultural transportation, in tons (t), which is equivalent to agricultural production in this study; J represents the average carbon dioxide emissions per ton of agricultural transportation per kilometer, in L represents agricultural transport mileage, in kilometers (km).

[0120] The carbon reduction potential of renewable energy is calculated using the following formula:

[0121] E c =P ele ×J

[0122] Among them E c is the carbon reduction of photovoltaic power generation, in units of P ele represents the total photovoltaic power generation, in kilowatt-hours; J represents the amount of carbon dioxide emissions reduced per kilowatt-hour of average photovoltaic power generation.

[0123] In addition to the environmental benefits, the environmental sustainability index also considers the environmental costs of a productive roof renewal strategy throughout its lifecycle, comprehensively assessing the negative environmental impacts of the roof system's construction, operation, production, and product distribution. Due to the varying units of various materials, this paper uses a unified global warming potential (GWP) to convert each component's expenditures. Specific data is calculated based on relevant Chinese national standards and previous literature, tailored to the specific roofing strategy.

[0124] The rooftop system's construction includes (i) structural installation; (ii) system maintenance, including the repair and replacement of equipment within the system; and (iii) component end-of-life disposal. The operational aspects of the system consider environmental impacts such as (i) water; (ii) energy; and (iii) fertilizers, pesticides, and seeds.

[0125] Table 1 Economic and environmental parameters of roof systems

[0126]

[0127] Example 2

[0128] This example uses the rooftop productive renovation design project in Xuefu Street, Nankai District, Tianjin, as the specific analysis context. Known conditions were identified during the planning phase: the street includes nine residential communities and two high-rise office buildings. According to survey data, the street has a permanent population of 32,706 people. The building types include low-rise, multi-story, mid-rise, and high-rise buildings. The building density is high, and the urban form is complex. Based on preliminary surveys, CAD drawings and a 3D point cloud model of the area have been obtained.

[0129] By using Rhino software, Grasshopper platform, TT Toolbox program, Octopus program and the roof productive renovation layout plan generation and optimization method of the present invention, a variety of roof productive renewal design plans and calculation evaluation indicators are quickly generated in the selected block.

[0130] In this embodiment, the deterministic parameters include the square plane and number of roofs to be renovated, the type of photovoltaic modules, the efficiency of photovoltaic modules, the total population of the block, the per capita vegetable consumption, the per capita electricity consumption, and the EPW format climate data file for the Tianjin area. Using the renovation configuration method of the present invention, a set of productive roof renovation design plans that meet multiple predetermined goals and their resource, economic, and environmental evaluations can be obtained, such as Figure 2 Finally, 57 Pareto optimal solutions were obtained, as shown in Table 2.

[0131] Table 2 Optimization results list

[0132]

[0133]

[0134]

[0135] The process method of the present invention can solve the lack of design methods for productive transformation of rooftop space in urban blocks and the technical difficulties of cumbersome processes and repetitive work in existing design processes; it can save a lot of time and cost and improve calculation accuracy, and simulate the physical environment of urban blocks based on meteorological data, and use multi-objective optimization methods to achieve the established design goals; the use of this tool does not require designers to have knowledge of urban agriculture and photovoltaic power generation, only the basic information of the site and the design goals need to be input to obtain multiple sets of optimal solutions, and the economic and environmental indicators of each plan can be automatically calculated to support the decision-making of the design plan; the final result is presented to the user in a visual form, the user and the tool are highly interactive, and the practicability and promotion are strong.

[0136] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for generating and optimizing a rooftop production transformation layout plan, characterized in that: The following steps are involved: Step 1: Create a 3D model of the urban block that needs to undergo rooftop productive transformation in the simulation module; Step 2, picking up the block geometry model and the selected remodeled roof in the block 3D model obtained in step 1; Step 3: Extract the regional environmental data throughout the year. Enter information such as the sun's trajectory, radiation intensity, and hourly sunshine duration into the environmental simulation calculator. Perform a physical environmental simulation on the selected roofs from Step 2, and select roofs that meet the physical environmental conditions as suitable roofs. Step 4: Establish agricultural potential calculation models and photovoltaic potential calculation models to calculate the average annual yield per unit area of ​​each suitable roof when applying different production strategies, including open-air cultivation, rooftop photovoltaics, rooftop greenhouses, and photovoltaic greenhouses; When the production strategy is open-air planting or rooftop greenhouse, the annual average yield is the annual average agricultural yield; when the production strategy is rooftop photovoltaic, the annual average yield is the annual average photovoltaic yield; when the production strategy is photovoltaic greenhouse, the annual average yield includes the annual average agricultural yield and the annual average photovoltaic yield. The agricultural potential calculation model is used to calculate the annual average agricultural yield per unit area, and the photovoltaic potential calculation model is used to calculate the annual average photovoltaic yield per unit area; Step 5: Based on the average annual output and renovation cost obtained in step 4, run an iterative calculation to obtain the cost-benefit coefficient of each roof under different strategies. k , used to indicate the degree to which a roof is more suitable for a certain strategy, and is used as a screening criterion in the optimization operator; Step 6: The cost-benefit coefficients of open-air planting, rooftop photovoltaic, rooftop greenhouse and photovoltaic greenhouse rooftop transformation obtained in step 5 are calculated as follows: k Input the "cost-benefit coefficient of system 1", "cost-benefit coefficient of system 2", and "cost-benefit coefficient of system 3" into the multi-objective optimization module in the order of selection. The remaining transformation strategies are automatically input into the multi-objective optimization module as "cost-benefit coefficient of system 4". The suitable roofs obtained in step 3 are input into the multi-objective optimization module. The constraint is that the total number of roofs to be transformed must not exceed the total number of roofs in the block, but some roofs that have not been updated are allowed. Then, the proportion of each production strategy is obtained through the genetic algorithm, thereby obtaining the optimal configuration scheme of the roof transformation strategy. In the optimal configuration scheme, the total agricultural output is maximized F. max , maximizing the total photovoltaic output E max , minimize the total cost of transformation min ; Step 7: In the multidimensional evaluation module, a multidimensional evaluation calculation model for roof renovation plans is established based on the economic benefits and environmental impacts of various roof renovation strategies. Based on the optimized configuration plan obtained in step 6, the multidimensional evaluation calculation model generates resource indicators, economic indicators, and environmental indicators for each configuration plan as decision support for the optimized configuration plan.

2. The method for generating and optimizing a rooftop productive transformation layout plan according to claim 1, wherein: In step 1, the basic geometric shape is created in Rhino software and then imported into the Grasshopper platform to create a 3D model of the block.

3. The method for generating and optimizing a rooftop productive transformation layout plan according to claim 1, wherein: In step 3, operational meteorological data in EPW format is imported into the simulation module to extract the sun's trajectory path, radiation intensity information, and temperature information within the region.

4. The method for generating and optimizing a rooftop productive transformation layout plan according to claim 1, wherein: In step 3, a parameterized model is established on the Grasshopper platform, an environmental simulation calculation kernel is formed through the Ladybug program in the platform, and suitable roofs are screened based on plant growth conditions and photovoltaic potential thresholds.

5. The method for generating and optimizing a rooftop productive transformation layout plan according to claim 1, wherein: In step 4, the average annual agricultural yield per unit area is calculated using an agricultural potential calculation model, which is: Y pt =1.522×10 -5 ×(1-a)(1-b)(1-c)×q×f t ; f t =4.301×10 -2 t-5.771×10 -4 t 2 ; Y pt is the agricultural output per square meter per year, f t is the temperature correction function, α is the reflectivity, α=0.83L i / L0, L0 is the maximum leaf area index; L i is the leaf area index in a certain period of time; β is the leakage rate; γ is the light saturation limit, that is, the proportion of light exceeding the light saturation point; q is the total solar radiation projected per unit area per unit time, and t is the annual average temperature.

6. The method for generating and optimizing a rooftop productive transformation layout plan according to claim 1, wherein: In step 4, the average annual photovoltaic output per unit area is calculated using a photovoltaic output calculation model, which is: E e =I G × PV ×K×(1-R d ) N-1 Among them E e is the photovoltaic output per square meter per year, I G is the annual accumulated solar radiation on the roof surface, obtained from the physical environment simulation in step 3; PV is the photoelectric conversion efficiency of the photovoltaic module, and K is the energy efficiency ratio.

7. The method for generating and optimizing a rooftop productive transformation layout plan according to claim 1, wherein: In step 5, the cost-benefit coefficient Self k The calculation method is: Yield k The annual output per unit area using k types of production strategies for each roof; Population is the total population of the block; Per k is the per capita resource demand; Cost k is the transformation cost per unit area of ​​type k production strategy; x k The roof area that is transformed to implement type k production strategy, where k is open-air cultivation, rooftop photovoltaics, rooftop greenhouse or photovoltaic greenhouse.

8. The method for generating and optimizing a rooftop productive transformation layout plan according to claim 1, wherein: In step 6, the calculation formula for total agricultural output is: F is the total agricultural output; n is the number of types of rooftop agricultural production transformation strategies; a j is the agricultural output per unit area of ​​the j-type production strategy in rooftop agricultural production; x j is the area that can be used for production by type j of agricultural production; The total photovoltaic output is calculated as: E is the total photovoltaic output; m is the number of rooftop power production transformation strategies; b i is the photovoltaic output per unit area of ​​type i production strategy in rooftop electricity production; y i is the area where type i electricity production can be productively utilized; The total cost of the renovation is calculated using the total renovation cost calculation model, which is: Cost is the total cost of transformation; n is the number of types of rooftop agricultural production transformation strategies; Cost j is the unit cost of production strategy type j in rooftop agriculture production; x j is the area that can be used for production under the j-type agricultural production situation; m is the number of types of rooftop power production transformation strategies; y i is the area where Class I electricity production can be used for production; Cost i is the unit cost of type i production strategy in rooftop photovoltaic production.

9. The method for generating and optimizing a rooftop productive transformation layout plan according to claim 1, wherein: In step 7, the production potential calculation core in the multidimensional evaluation model calculates resource indicators, and the resource indicators include agricultural self-sufficiency rate and energy self-sufficiency rate; the economic indicator calculation core in the multidimensional evaluation model calculates economic indicators, and the economic indicators include return on investment and investment payback period; the environmental impact calculation core in the multidimensional evaluation model calculates environmental indicators, and the environmental indicators include global warming potential, water consumption, electricity consumption, agricultural mileage carbon reduction potential, and renewable energy carbon reduction potential.

10. The method for generating and optimizing a rooftop productive transformation layout plan according to claim 9, wherein: The formula for calculating agricultural self-sufficiency rate is: Vegetable self is the agricultural self-sufficiency rate; k is the average annual output per unit of type k production strategy; x k The roof area that is transformed for type k production strategy; Population is the total population of the block; Per k is the per capita resource demand; The formula for calculating energy self-sufficiency rate is: Among them, Electric self is the energy self-sufficiency rate; a l is the average annual output per unit of type l production strategy; x l The roof area that is modified for type l production strategy; Population is the total population of the block; Per l l is the per capita resource demand; The formula for calculating return on investment is: ROI is the return on investment; t Cost is the annual income; t is the total annual expenditure; Investment is the initial cost; Investment is the initial cost; n is the number of rooftop agricultural production transformation strategies; Cost j is the unit cost of production strategy type j in rooftop agriculture production; x j is the area that can be used for production under the j-type agricultural production situation; m is the number of types of rooftop power production transformation strategies; b i is the average annual output per unit of production strategy type i in rooftop agricultural production; y i is the area where Class I electricity production can be used for production; Cost i is the unit cost of type i production strategy in rooftop photovoltaic production; The specific calculation method of investment return period is as follows: Paybacktime is the investment return period; Revenue t Cost is the annual income; t is the total annual expenditure; Investment is the initial cost; The calculation method for the carbon reduction potential of agricultural mileage is: F c =P veg ×J×L Among them F c Reduce carbon emissions from agricultural mileage; veg represents the total amount of agricultural transportation; J represents the average carbon dioxide emissions per ton of agricultural transportation per kilometer; L represents the agricultural transportation mileage; The calculation method for the carbon reduction potential of renewable energy is: AND c =P ele ×J Among them F c Reduce carbon emissions from agricultural mileage; veg represents the total agricultural transport volume; J represents the average carbon dioxide emissions per ton of agricultural transport per kilometer; L represents the agricultural transport mileage.

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