A method for co-optimizing energy and cost in highway route selection considering sunshine conditions along the route

Abstract

This invention relates to the field of highway route design technology, and specifically to a method for the coordinated optimization of energy and cost in highway route selection, taking into account the solar radiation conditions along the route. The method includes: forming a multi-attribute spatial node set; generating initial candidate paths step-by-step from the starting node using a random sampling strategy; obtaining the engineering cost and energy demand of the highway route selection based on a dual-objective optimization model of energy and cost; obtaining an initial set of feasible paths based on the constraints in the model; and employing a multi-objective optimization strategy to perform a global search and optimization of the paths to obtain the highway route scheme with optimal overall performance. This method comprehensively considers the solar radiation conditions under the influence of terrain shading and converts them into electrical energy usable by critical power facilities. It can effectively improve the solar energy utilization efficiency along the highway, reduce the external energy dependence of critical power facilities such as tunnel lighting, service areas, and toll stations, while also taking into account engineering costs, thus possessing significant theoretical and engineering application value.

Description

Technical Field

[0001] This invention relates to the field of highway route design technology, and in particular to a method for co-optimizing energy and cost in highway route selection that takes into account the sunshine conditions along the route. Background Technology

[0002] In the design phase of highway engineering, increasing attention is being paid to energy efficiency and environmental impact. As a crucial component of the transportation system, highways not only serve a transportation function, but their ancillary facilities (such as lighting systems) also generate continuous energy consumption during long-term operation. This consumption accounts for a high proportion of highway operating energy consumption and is characterized by its long-term, stable, and continuously increasing nature. During highway operation, energy consumption is mainly concentrated in key electrical facilities such as tunnel lighting, service areas, toll stations, and certain special road sections. Among these, tunnels, requiring 24 / 7 lighting, have the most significant energy consumption; while ancillary facilities such as service areas and toll stations also have continuous and stable electricity demands. With continuous technological advancements, solar energy is increasingly being efficiently converted into electricity for highway power supply, providing an effective path to reduce highway operating energy consumption. Route design, as the leading and overarching aspect of highway design, plays a decisive role in the construction and operation of highway projects. Therefore, in the highway design phase, if the ability to acquire solar energy resources along the route can be improved through reasonable route selection, and natural energy conditions can be taken into account and used uniformly for power supply of key facilities, it will be of great significance for reducing external energy dependence and electricity purchase demand and achieving green and low-carbon operation.

[0003] In actual highway route selection and design, due to the complex and varied terrain, routes often traverse mountainous, hilly, and valley areas. The terrain's shading conditions vary significantly at different locations, resulting in markedly uneven solar radiation acquisition along the route. For example, when a route passes through a valley or near a high terrain feature, solar radiation is easily blocked, reducing solar energy utilization efficiency and consequently affecting the stability and economics of the entire highway's power supply system and the subsequently developed highway energy storage system. Therefore, rationally avoiding areas with unfavorable sunlight and maximizing the potential for solar energy utilization along the route has become one of the key issues in green highway design.

[0004] However, current research on highway route optimization, both domestically and internationally, mainly focuses on traditional objectives such as engineering cost, route length, and operating cost. It typically constructs multi-objective optimization models and employs heuristic algorithms to solve these models, thereby obtaining optimal route solutions. Research on incorporating along-route solar radiation conditions into the route selection process and further transforming them into energy supply capacity remains relatively lacking, and a systematic modeling method and optimization framework have not yet been established. Furthermore, existing methods, when dealing with the impact of terrain shading on solar radiation, mostly remain at the macroscopic estimation level, making it difficult to perform fine-grained coupling analysis with specific route plans.

[0005] Furthermore, as a spatially continuous structure, highway routes exhibit complex interactions between their geometry and the surrounding terrain. Sunlight conditions are influenced not only by geographical location but also by route alignment, elevation changes, and surrounding topographical obstruction. This makes traditional optimization models based on route geometry or single environmental factors unsuitable for route selection problems that consider the coupling of energy and cost. Simultaneously, relying solely on manual experience for scheme comparison is not only labor-intensive and inefficient but also makes it difficult to comprehensively assess the differences in energy utilization among different route options, thus failing to guarantee the overall optimality of the chosen scheme.

[0006] Therefore, it is of great significance to provide a method for the coordinated optimization of energy and cost in highway route selection. Summary of the Invention

[0007] The main objective of this invention is to provide a method for co-optimizing energy and cost in highway route selection that considers sunlight conditions along the route. This method comprehensively considers sunlight conditions affected by terrain shading and converts this sunlight into electrical energy usable for critical power facilities such as tunnel lighting, service areas, and toll stations. While taking into account project costs, it achieves quantitative evaluation and global optimization of energy utilization efficiency. This aims to solve the problem that existing methods fail to consider sunlight conditions, thus failing to couple energy and cost considerations in route selection. The specific technical solution is as follows: This invention discloses a method for co-optimizing energy and cost in highway route selection considering sunshine conditions along the route, comprising the following steps: Step 1: Construct a computable spatial search model. Specifically, within the determined start and end points and the selected corridor, the study area is discretized according to the given spatial resolution, divided into regular grids, and a three-dimensional spatial search domain is constructed by combining topographic elevation information. At each grid node, topographic elevation, land cover type, geological conditions, and restricted area attributes are assigned to it, forming a multi-attribute spatial node set. Step 2: Based on the multi-attribute spatial node set from Step 1, starting from the starting node, generate initial candidate paths step by step according to the random sampling strategy; Step 3: For the highway route selection in the initial candidate paths obtained in Step 2, obtain the engineering cost and energy demand of each highway route based on the dual-objective optimization model of energy and cost for highway route selection; obtain the initial feasible path set based on the constraints in the dual-objective optimization model of energy and cost for highway route selection. Step 4: Based on the initial feasible path set obtained in Step 3, a multi-objective optimization strategy is used to perform a global search and optimization of the paths to obtain the highway route scheme with the best overall performance.

[0008] Preferably, the dual-objective optimization model for highway route selection, which considers both energy and cost, includes design variables, objective functions, and constraints. The coordinates of the intersection points of the highway lines and their corresponding radii, and the design elevations of the longitudinal slope change points and their corresponding mileages are used as design variables. Highway engineering cost External energy demand for critical power facilities Bi-objective function ; Constraints include geometric constraints as well as restricted areas and structural constraints.

[0009] Preferred highway engineering cost Calculate using the following formula: ; in: For road surface engineering costs; Costs for the structure; For earthwork and stonework costs, , For the first The earthwork volume of the section of the line; The number of segments into which the line is divided; Cost per unit of earthwork; External energy demand for critical power facilities Calculate using the following formula: ; in: The total energy demand for key power facilities along the highway; For solar energy supply.

[0010] Preferred total energy demand of key power facilities along the highway Calculate using the following formula: ; in: Number the type of electrical facility; Total number of facility types; For the first Unit power of such facilities; For the first The runtime of such facilities; For the first The number of such facilities; Key power facilities along the highway include lighting facilities in tunnels, service areas, toll stations, and interchanges.

[0011] Preferably, solar energy supply Calculate using the following formula: ; in: Photovoltaic conversion efficiency; For the first The solar radiation intensity of the section of the line; For the first The total area of ​​available photovoltaic panels for a given section of the line.

[0012] Preferred, the first Sunlight intensity of the section of the line The following steps are used to obtain: The following formula is used to calculate the first... Solar radiation intensity of the line segment : ; in: The solar radiation constant; For the first The angle of solar incidence on the section of the line; For the first Terrain obstruction coefficient of the section of the line; The following formula is used to calculate the first... Sunlight intensity of the section of the line : ; in: To calculate the time step, i.e., the length of the time interval; T is the number of time steps; Let be the solar radiation intensity of the i-th segment of the line during the j-th time period.

[0013] Preferred, the first Total area of ​​available photovoltaic panels for the line segment Calculate using the following formula: ; in: The area of ​​the fill slope along the route where photovoltaic panels can be installed; This refers to the area of ​​the excavated slope; The median strip area of ​​the highway to meet the layout requirements.

[0014] The preferred approach is to use the following formula to represent the dual-objective optimization model for highway route selection, which considers both energy and cost: ; ; in: Geometric constraints; Constraints for restricted areas and structures; These are constraints; The objective function is denoted as .

[0015] Preferably, the geometric constraints include planar geometric constraints and longitudinal section constraints. The planar geometric constraints include minimum radius constraints, straight line length constraints, minimum spiral length constraints connecting straight lines and circular curves, and linear continuity constraints. The longitudinal section geometric constraints include maximum longitudinal slope constraints, minimum and maximum slope length constraints, and vertical curve radius and vertical curve length constraints. Restricted areas and structural constraints include impassable ecological protection zones, areas with severe geological hazards, residential areas, and bodies of water, mountains, canyons, valleys, existing transportation routes, and obstacle areas that can be traversed by bridges or tunnels.

[0016] Preferably, a multi-objective optimization strategy is adopted to perform global search and optimization of the route. Specifically, the following steps are taken: a dual-objective optimization model for energy and cost of highway route selection is used to calculate the engineering cost and energy demand of the highway route selection for scheme evaluation; the NSGA-II algorithm is used for iterative search; a set of Pareto optimal solutions is obtained through non-dominated sorting; and the highway route scheme with the best comprehensive performance is selected based on the Pareto optimal solution set.

[0017] The effect of applying the technical solution of this invention is: (1) The energy and cost co-optimization method for highway route selection considering sunshine conditions along the route disclosed in this invention includes: Step 1: Constructing a computable spatial search model, specifically: within the determined start and end points and route selection corridor, the study area is discretized according to a given spatial resolution, divided into regular grids, and a three-dimensional spatial search domain is constructed in combination with terrain elevation information; on each grid node, terrain elevation, land cover type, geological conditions and restricted area attributes are assigned to form a multi-attribute spatial node set; Step 2: Based on the multi-attribute spatial node set in Step 1, starting from the starting node, an initial candidate path is generated step by step according to a random sampling strategy; Step 3: For the highway route selection in the initial candidate path obtained in Step 2, the engineering cost and energy demand of each highway route selection are obtained based on the dual-objective optimization model of energy and cost of highway route selection; the initial feasible path set is obtained based on the constraints in the dual-objective optimization model of energy and cost of highway route selection; Step 4: Based on the initial feasible path set obtained in Step 3, a multi-objective optimization strategy is used to perform global search and optimization of the path to obtain the highway route scheme with the best comprehensive performance. This invention establishes a dual-objective optimization model for highway route selection, considering topographic conditions, engineering constraints, and spatial continuity. Specifically, it establishes a model with the coordinates and radius of the highway's horizontal intersection points and the mileage and design elevation of the longitudinal slope change points as design variables, and the dual objective functions of highway construction cost and external energy demand of key power facilities as constraints, including geometric constraints, restricted areas, and structural constraints. Based on this model, a terrain-aware dual-objective guided search algorithm is proposed to achieve the optimal highway route. This method can effectively improve the solar energy utilization efficiency along the highway, reduce the external energy dependence of key power facilities such as tunnel lighting, service areas, and toll stations, while also considering project cost, thus possessing significant theoretical and engineering application value.

[0018] (2) This invention proposes a method for calculating solar radiation and converting energy along a highway. Specifically, by constructing a spatial relationship model between solar radiation and terrain shading, the solar energy acquisition capacity of each node along the highway is first calculated (the solar radiation intensity of the section of the highway is first calculated based on the solar radiation intensity of the route). Then, the solar energy resources along the route are uniformly converted and collected into a solar energy supply that can be used by key power facilities such as tunnels, service areas and toll stations. (i.e., using solar energy supply) (Obtained through calculation of expressions), realizing a quantitative mapping from "natural resources" to "engineered energy".

[0019] (3) In the route generation process of this invention, candidate routes are constructed in real time by dynamically changing design variables, and cost and energy index calculations (i.e., highway engineering cost) are completed simultaneously. External energy demand for critical power facilities This enables the coupled optimization of path generation and performance evaluation; and finds the optimal route scheme that balances engineering economy and energy supply capacity on a global scale.

[0020] (4) Compared with traditional methods that rely on human experience, this invention can significantly improve the efficiency of route selection and design, reduce the influence of human subjectivity, and effectively reduce engineering costs, external energy dependence and electricity purchase demand by making full use of the sunshine resources along the route. It has good engineering application prospects and promotion value. Attached Figure Description

[0021] 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 the structures shown in these drawings without creative effort.

[0022] Figure 1 This is a schematic diagram of a highway route selection energy and cost co-optimization method that considers the sunshine conditions along the route in an embodiment of the present invention; Figure 2 This is a schematic diagram illustrating the calculation principle of terrain occlusion factor in an embodiment of the present invention.

[0023] The objectives, features, and advantages of this invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0024] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. 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.

[0025] Example: This invention proposes a method for co-optimizing energy and cost in highway route selection, taking into account the solar radiation conditions along the route. See details below. Figure 1 Specifically, it includes the following steps: Step 1: Construct a computable spatial search model. Specifically, within the determined start and end points and the selected corridor, the study area is discretized according to the given spatial resolution, divided into regular grids, and a three-dimensional spatial search domain is constructed by combining topographic elevation information. At each grid node, topographic elevation, land cover type, geological conditions, and restricted area attributes are assigned to it, forming a multi-attribute spatial node set. Step 2: Based on the multi-attribute spatial node set from Step 1, starting from the starting node, generate initial candidate paths step by step according to the random sampling strategy; Step 3: For the highway route selection in the initial candidate paths obtained in Step 2, obtain the engineering cost and energy demand of each highway route based on the dual-objective optimization model of energy and cost for highway route selection; obtain the initial feasible path set based on the constraints in the dual-objective optimization model of energy and cost for highway route selection. Step 4: Based on the initial feasible path set obtained in Step 3, a multi-objective optimization strategy is used to perform a global search and optimization of the paths to obtain the highway route scheme with the best overall performance.

[0026] In this embodiment, the preferred dual-objective optimization model for highway route selection, which considers both energy and cost, includes design variables, objective functions, and constraints. The design variables are the coordinates of the horizontal intersection points and their corresponding radii, and the design elevations and corresponding mileages of the longitudinal profile slope change points. Specifically, the design variables for highway alignment are parametrically expressed through the spatial geometric information of the route, including horizontal and vertical profile information. The horizontal position information is represented by a sequence of horizontal intersection point coordinates, and the vertical profile information is represented by the design elevations and corresponding mileages of the longitudinal profile slope change points. Therefore, the design variables in the highway alignment optimization model can be represented by the following variables: ; in: and The coordinates of the intersection point of the highway lines; The radius of the curve corresponding to the intersection of the highway alignments. This refers to the design elevation of the slope change points in the longitudinal profile of the highway. This refers to the mileage corresponding to the slope change points in the longitudinal profile of the highway. This represents the number of intersections at the road level. The number of slope change points in the longitudinal profile of the highway; Highway routes are divided into Section, number of line segments The values ​​are 1, 2, 3, ... The unit length is determined by design experience.

[0027] Highway engineering cost External energy demand for critical power facilities Bi-objective function ; Constraints include geometric constraints as well as restricted areas and structural constraints.

[0028] In this embodiment, the project cost mainly includes earthwork costs, pavement costs, and structure costs (including bridges and tunnels). The highway project cost... Calculate using the following formula: ; in: For road surface engineering costs; Costs for the structure; For earthwork costs, the earthwork volume can be calculated using the cumulative summation of discrete elements of the line, specifically: , For the first The earthwork volume of the section of the line; The number of segments into which the line is divided; Cost per unit of earthwork.

[0029] In this embodiment, during the highway operation phase, key facilities such as tunnels, service areas, and toll stations are the main energy-consuming units. This embodiment, from the perspective of "energy supply-energy demand," takes the external energy dependence of key power-consuming facilities as one of the optimization objectives, specifically including: ① Based on the scale, operating time, and unit energy consumption parameters of various facilities, calculate their energy demand and summarize the total energy demand of key power-consuming facilities along the entire line, specifically: Total energy demand of key power facilities along the highway Calculate using the following formula: ; in: Number the type of electrical facility; Total number of facility types; For the first Unit power of such facilities; For the first The runtime of such facilities; For the first The number of such facilities; Key power facilities along the highway include lighting facilities in tunnels, service areas, toll stations, and interchanges.

[0030] ② Considering the supplementary effect of solar energy resources along the route on the power system, the solar energy supply is calculated as follows: Solar power supply Calculate using the following formula: ; in: Photovoltaic conversion efficiency; For the first The solar radiation intensity of the section of the line; For the first The total area of ​​available photovoltaic panels for a given section of the line.

[0031] ③ External energy demand of critical power facilities Calculate using the following formula: ; in: The total energy demand for key power facilities along the highway; For solar energy supply.

[0032] This indicator can effectively reflect the advantages and disadvantages of different route options in terms of energy self-sufficiency.

[0033] In this embodiment, a further preferred embodiment is that, due to the complex terrain along the highway, mountains and slopes can block solar radiation. Therefore, a solar radiation calculation model that considers the influence of terrain is needed. Solar radiation intensity and the angle of incidence satisfy a cosine relationship. The physical essence of this relationship is that the radiant energy received per unit area depends on the projected area of ​​that area perpendicular to the direction of sunlight. When sunlight is incident at an oblique angle, the same energy will be distributed over a larger actual surface area, resulting in a decrease in radiation intensity per unit area. Therefore, introducing a cosine term of the angle of incidence to correct for solar radiation can accurately reflect the differences in solar radiation under different slope aspects and route directions. The method for obtaining solar radiation intensity at any discrete point along the route is as follows: The following formula is used to calculate the first... Solar radiation intensity of the line segment : ; in: The solar radiation constant; For the first The angle of solar incidence on the section of the line; For the first Terrain obstruction coefficient of the section of the line.

[0034] To accurately characterize the shading effect of terrain on solar radiation, this invention establishes a shading discrimination method between sunlight and terrain based on spatial geometric relationships. For any discrete point on the route, a ray is constructed along the direction of solar incidence, and the terrain elevation information along the ray direction is obtained using a digital elevation model. By comparing the relationship between the solar radiation height and the terrain elevation, it is determined whether the point is in a shading state.

[0035] In the specific implementation, the maximum terrain shading angle of each terrain point relative to the current point along the sun direction is calculated and compared with the solar altitude angle: when the solar altitude angle is less than the terrain shading angle, the point is considered to be in a shading state. =0; otherwise, it is considered unobstructed. =1. Based on this discrimination result, a terrain shading coefficient is constructed to correct for solar radiation intensity, such as... Figure 2As shown. The cumulative solar radiation energy along the route is calculated. Solar radiation intensity exhibits significant temporal variation, therefore, it needs to be accumulated over time to obtain the total solar radiation energy per unit location. In the actual calculation process, time is discretized as follows: The following formula is used to calculate the first... Sunlight intensity of the section of the line : ; in: To calculate the time step, i.e., the length of the time interval; T is the number of time steps; Let be the solar radiation intensity of the i-th segment of the line during the j-th time period.

[0036] Solar energy supply Calculate using the following formula: ; in: Photovoltaic conversion efficiency; For the first The solar radiation intensity of the section of the line; For the first The total area of ​​available photovoltaic panels for a given section of the line.

[0037] In this embodiment, the first Total area of ​​photovoltaic panels available for this section of the line The area determined by the embankment slope area, the cut slope area, and the median strip area of ​​the highway where photovoltaic panels can be installed along the route, i.e., the... Total area of ​​photovoltaic panels available for this section of the line Calculate using the following formula: ; in: The area of ​​the fill slope along the route where photovoltaic panels can be installed; This refers to the area of ​​the excavated slope; The median strip area of ​​the highway to meet the layout requirements.

[0038] In this embodiment, to ensure that the highway alignment scheme meets the requirements of engineering feasibility and specifications, the present invention constructs two types of constraints, as follows: (1) Geometric constraints Geometric constraints are used to ensure that the highway alignment meets the design specifications. These include planar geometric constraints and longitudinal geometric constraints. Planar geometric constraints include minimum radius constraints, straight line length constraints, minimum spiral length constraints connecting straight lines and circular curves, and alignment continuity constraints. Longitudinal geometric constraints include maximum longitudinal slope constraints, minimum and maximum slope length constraints, and vertical curve radius and length constraints. The above geometric constraint requirements and values ​​are all derived from highway alignment design specifications and are denoted as follows: .

[0039] (2) Restricted areas and structural constraints Restricted areas and structural constraints are primarily used to prevent highway routes from traversing unsuitable construction areas, including impassable ecological reserves, areas with severe geological hazards, residential areas, and bodies of water, mountains, canyons, ravines, existing transportation routes, and obstacle areas that can be crossed by bridges or tunnels. These are denoted as […]. The obstacle area here refers to either naturally formed or artificially created obstacle areas.

[0040] Based on the above, the dual-objective optimization model for highway route selection, considering both energy and cost, is expressed by the following formula: ; ; in: Geometric constraints; Constraints for restricted areas and structures; These are constraints; The objective function is denoted as .

[0041] In this embodiment, the multi-objective optimization strategy is used to perform global search and optimization of the route. Specifically, the energy and cost dual-objective optimization model for highway route selection is used to calculate the engineering cost and energy demand of the highway route selection for scheme evaluation; the NSGA-II algorithm is used for iterative search; a set of Pareto optimal solutions is obtained through non-dominated sorting; and the highway route scheme with the best comprehensive performance is selected based on the Pareto optimal solution set.

[0042] The technical solution applied in this embodiment is as follows: The technical solution of this invention will be described using a complex mountainous highway section as an example. The aerial distance between the start and end points of this section is 50.2 km, the maximum elevation difference is about 1200 m, the terrain along the route is undulating, and there are complex landforms such as canyons and valleys. The local areas are significantly affected by the terrain, and the spatial differences in sunlight conditions are obvious.

[0043] First, the study area was spatially discretized into a regular grid of 100m × 100m, resulting in approximately 5050 grid nodes. Based on this, elevation, slope, and aspect information for each node was extracted from DEM data. In accordance with engineering standards, a maximum allowable longitudinal slope of 5% and a maximum alignment coefficient of 1.2 were set. Simultaneously, inaccessible areas such as residential areas, water bodies, and ecological protection zones were identified, representing approximately 12% of the study area. Based on this, spatial constraints for route selection were constructed.

[0044] In terms of cost modeling, unit cost parameters for different road sections are determined based on terrain conditions and project types. Combining information such as route alignment, longitudinal profile, and structures, the earthwork volume, bridge and tunnel volumes of candidate routes are calculated, thereby constructing an engineering cost evaluation model for the route scheme.

[0045] Regarding energy demand, based on highway grade and the layout of facilities along the route, key power-consuming facilities were identified, including tunnels, service areas, and toll stations. The energy consumption per unit length for typical tunnel lighting is approximately 2.5-3.5 kWh / (m·d), the comprehensive power load of service areas is approximately 800-1200 kWh / d, and the power load of toll stations is approximately 200-400 kWh / d. Combining the scale and operating conditions of various facilities, their energy demands were calculated, and the total energy demand of key power-consuming facilities along the entire route was then summarized. For the assessment of internal solar energy supply capacity, the typical solar altitude angle and azimuth angle throughout the year were calculated. By analyzing the spatial relationship between the solar incidence direction and the terrain slope and aspect, the terrain shading situation of each grid node at different times was determined, and the effective sunshine duration of each node was statistically analyzed. The calculation results show that the average effective sunshine duration in valley areas is approximately 4.5 h / d, while it can reach 7.5 h / d in ridges and open areas, corresponding to an annual average solar radiation of approximately 1300-1500 kWh / m². 2 Based on this, and taking into account the photovoltaic conversion efficiency (18%) and the available space along the route (the average deployable ratio is about 6%-10%), the solar energy that can be converted into electricity in each area along the route is estimated, and then accumulated along the route to obtain the total solar energy supply for different route schemes.

[0046] In terms of route generation and optimization, candidate routes are generated using a random sampling strategy with the starting point as the initial node, under the aforementioned constraints. Each route consists of a series of spatial nodes. During the generation process, infeasible routes that do not meet the longitudinal slope constraints, horizontal curve constraints, or cross restricted areas are eliminated, ultimately resulting in 57 feasible candidate routes with lengths ranging from approximately 56 to 62 km. Subsequently, engineering quantity calculations and cost assessments are performed on each candidate route. Considering the solar radiation conditions along the route, the solar energy supply capacity is mapped to the route, and the external energy demand of key power facilities is calculated. Based on this, the NSGA-II multi-objective optimization method is used to comprehensively evaluate the candidate routes, with engineering cost and external energy demand as optimization objectives. A Pareto optimal solution set (12 typical schemes) is obtained through non-dominated sorting, and the route scheme with the best overall performance is selected from these.

[0047] The results show that the optimized route prioritizes passing through ridge areas with better sunlight conditions and effectively avoids the shadowy areas of deep valleys. Compared with the traditional manual route selection scheme, this scheme reduces the project cost by about 1.5%, and significantly reduces external energy dependence while meeting the electricity needs of tunnels and roadside service facilities, with a decrease in electricity purchase demand of about 18%. This example verifies the effectiveness and engineering applicability of this method in achieving coordinated optimization of highway route selection and energy supply under complex mountainous conditions.

[0048] The above description is merely a preferred embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structural transformations made using the contents of the present invention's specification and drawings under the inventive concept of the present invention, or direct / indirect applications in other related technical fields, are included within the patent protection scope of the present invention.

Claims

1. A method for co-optimizing energy and cost in highway route selection considering sunshine conditions along the route, characterized in that, Includes the following steps: Step 1: Construct a computable spatial search model. Specifically, within the determined start and end points and the selected corridor, the study area is discretized according to the given spatial resolution, divided into regular grids, and a three-dimensional spatial search domain is constructed by combining terrain elevation information. Each grid node is assigned terrain elevation, land cover type, geological conditions, and restricted area attributes, forming a multi-attribute spatial node set; Step 2: Based on the multi-attribute spatial node set from Step 1, starting from the starting node, generate initial candidate paths step by step according to the random sampling strategy; Step 3: For the highway route selection in the initial candidate paths obtained in Step 2, obtain the engineering cost and energy demand of each highway route based on the dual-objective optimization model of energy and cost for highway route selection; obtain the initial feasible path set based on the constraints in the dual-objective optimization model of energy and cost for highway route selection. Step 4: Based on the initial feasible path set obtained in Step 3, a multi-objective optimization strategy is used to perform a global search and optimization of the paths to obtain the highway route scheme with the best overall performance. The dual-objective optimization model for highway route selection, which considers both energy and cost, includes design variables, objective functions, and constraints. The design variables are the coordinates of the horizontal intersection points of the highway and their corresponding radii, and the design elevations of the longitudinal slope change points and their corresponding mileages; the highway engineering cost is used as the design variable. External energy demand for critical power facilities Bi-objective function Constraints include geometric constraints as well as restricted areas and structural constraints. External energy demand for critical power facilities Calculate using the following formula: ； in: The total energy demand for key power facilities along the highway; For solar energy supply; Solar power supply Calculate using the following formula: ； in: Photovoltaic conversion efficiency; For the first The solar radiation intensity of the section of the line; For the first The total area of ​​available photovoltaic panels for the section of the line; No. Sunlight intensity of the section of the line The following steps are used to obtain: The following formula is used to calculate the first... Solar radiation intensity of the line segment : ； in: The solar radiation constant; For the first The angle of solar incidence on the section of the line; For the first The terrain shading coefficient of a route segment is specifically calculated by comparing the maximum terrain shading angle of each terrain point relative to the current point along the sun's direction with the solar altitude angle. When the solar altitude angle is less than the terrain shading angle, the point is considered to be in a shading state. =0; otherwise, it is considered unobstructed. =1; The following formula is used to calculate the first... Sunlight intensity of the section of the line : ； in: To calculate the time step, i.e., the length of the time interval; T is the number of time steps; Let be the solar radiation intensity of the i-th segment of the line during the j-th time period.

2. The method for co-optimizing energy and cost of highway route selection considering sunshine conditions along the route, as described in claim 1, is characterized in that... Highway engineering cost Calculate using the following formula: ； in: For road surface engineering costs; Costs for the structure; For earthwork and stonework costs, , For the first The earthwork volume of the section of the line; The number of segments into which the line is divided; Cost per unit of earthwork.

3. The method for co-optimizing energy and cost of highway route selection considering sunshine conditions along the route, as described in claim 1, is characterized in that... Total energy demand of key power facilities along the highway Calculate using the following formula: ； in: Number the type of electrical facility; Total number of facility types; For the first Unit power of such facilities; For the first The runtime of such facilities; For the first The number of such facilities; Key power facilities along the highway include lighting facilities in tunnels, service areas, toll stations, and interchanges.

4. The method for co-optimizing energy and cost of highway route selection considering sunshine conditions along the route, as described in claim 1, is characterized in that... No. Total area of ​​photovoltaic panels available for this section of the line Calculate using the following formula: ； in: This refers to the area of ​​the fill slope along the route where photovoltaic panels can be installed; This refers to the area of ​​the excavated slope; The median strip area of ​​the highway to meet the layout requirements.

5. The method for coordinated optimization of energy and cost in highway route selection considering sunshine conditions along the route, as described in any one of claims 1-3, is characterized in that... The dual-objective optimization model for highway route selection, considering both energy and cost, is expressed by the following formula: ； ； in: Geometric constraints; Constraints for restricted areas and structures; These are constraints; : is the objective function.

6. The method for co-optimizing energy and cost of highway route selection considering sunshine conditions along the route, as described in claim 5, is characterized in that... Geometric constraints include planar geometric constraints and longitudinal section constraints. Planar geometric constraints include minimum radius constraints, straight line length constraints, minimum spiral length constraints connecting straight lines and circular curves, and linear continuity constraints. Longitudinal section geometric constraints include maximum longitudinal slope constraints, minimum and maximum slope length constraints, and vertical curve radius and vertical curve length constraints. Restricted areas and structural constraints include impassable ecological protection zones, areas with severe geological hazards, residential areas, and bodies of water, mountains, canyons, valleys, existing transportation routes, and obstacle areas that can be traversed by bridges or tunnels.

7. The method for co-optimizing energy and cost of highway route selection considering sunshine conditions along the route, as described in claim 5, is characterized in that... The multi-objective optimization strategy is used to perform global search and optimization of the route. Specifically, a dual-objective optimization model for energy and cost of highway route selection is used to calculate the engineering cost and energy demand of the highway route selection and to evaluate the scheme. The NSGA-II algorithm is used for iterative search; a set of Pareto optimal solutions is obtained through non-dominated sorting; and the highway route scheme with the best overall performance is selected based on the Pareto optimal solution set.

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