CN108805360B - Method for determining transportation cost of transporting urban biomass carrier to biomass power plant - Google Patents
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Abstract
The invention provides a method for determining the transportation cost of transporting an urban biomass carrier to a biomass power plant, belonging to the technical field of urban planning. On the premise of constructing a biomass power plant in a suburb, the method of the invention finally obtains the optimal transportation cost scheme by evaluating the stock of the urban biomass carriers, measuring and calculating the biomass potential energy supply range, determining the position of the biomass power plant, determining the transportation mode influence parameters and analyzing and calculating the transportation cost according to the road network. The method can determine the stock and the potential of the urban greening biomass carrier, and has a detailed quantitative analysis basis for developing, utilizing and constructing the biomass energy in the urban area.
Description
Technical Field
The invention relates to a method for determining the transportation cost of transporting an urban biomass carrier to a biomass power plant, belonging to the technical field of urban planning.
Background
In the current urban development of China, the quantity of biomass carriers such as residual branches and fallen leaves is very large, but the biomass carriers are mostly discarded as green energy sources, so that a great deal of resources are wasted. At the present stage, biomass carriers such as residual branches, fallen leaves and the like generated by urban greening in China are not reasonably utilized, and the whole biomass carriers are in a state of lacking a unified planning and operation scheme.
Disclosure of Invention
The invention aims at the situation that biomass carriers such as residual branches, fallen leaves and the like generated in urban greening in China are not reasonably utilized and a unified planning and operation scheme is lacked, and establishes a new biomass utilization mode, in particular to a biomass power plant which collects urban biomass carriers in a centralized manner and transports the urban biomass carriers to suburbs. Meanwhile, in the face of the problem that the treatment and transportation of the urban biomass carriers are inconsistent, a transportation cost calculation method for transporting the urban biomass carriers to the biomass power plant is established. On the premise of constructing a biomass power plant in a suburb, the method of the invention finally obtains the optimal transportation cost scheme by evaluating the stock of the urban biomass carriers, measuring and calculating the biomass potential energy supply range, determining the position of the biomass power plant, determining the transportation mode influence parameters and analyzing and calculating the transportation cost according to the road network. The technical scheme is as follows:
a transportation cost determination method of transporting an urban biomass carrier to a biomass power plant, the method comprising:
the first step is as follows: determining the plant type and weight of biomass carriers generated in urban areas according to the distribution data of parks, green belts and street trees in the urban areas, measuring the heat value by adopting a heat value detector, and then acquiring the potential energy storage of all the biomass carriers according to the heat value;
the second step is that: determining the heat energy demand level in the urban area according to the population distribution density and the geographic distribution state of the suburban area, and simultaneously acquiring the appropriate supply range corresponding to the urban biomass carrier according to the energy stock in the first step by combining the annual, month and daytime electricity utilization fluctuation coefficients;
the third step: measuring and calculating a load center according to the suitable supply range in the second step, and determining the optimal site of the power plant by depending on the network form of the existing urban road;
the fourth step: determining the relation between the speed and the oil consumption according to the model of the specific transport vehicle; performing annual data analysis on the road network in the suitable supply range in the second step to determine a congestion coefficient; acquiring possible trends of a transportation route by relying on a GPS map navigation system;
the fifth step: and establishing an optimal transportation cost scheme according to the comprehensive measurement and calculation model of the transportation cost by utilizing the oil consumption relation, the congestion coefficient and the path length in the fourth step.
Further, the specific process of the potential energy stock of all the biomass carriers in the first step comprises the following steps:
the method comprises the following steps: determining the range, position and type of urban greening by utilizing a mapping vector map, a far infrared remote sensing drawing and an unmanned aerial vehicle aerial photograph of an urban planning department; determining a greening part needing to be trimmed in all greening types in the city, wherein the greening part needing to be trimmed is a source area of the biomass carrier; is also the target of analysis required in the subsequent steps;
step two: acquiring the weight of the biomass carriers generated every year by all greening types in the city according to a biomass carrier weight calculation model, wherein the biomass carrier weight calculation model comprises the following steps:
wherein B is the total weight of various biomass carriers, and the unit is kg; i is the greening number, n is the total number of greening, AiIs the area of the green area, and the unit is m2；DiThe planting density of the greening area is shown in the unit of plants/m2；WiThe unit of the biomass carrier weight is kg/plant, wherein the biomass carrier weight is generated by once pruning one plant in a green area; t isiPruning times required for one year of a green area;
step three: the method comprises the following steps of performing heat value detection on biomass carriers generated by all greening types in a city by using a heat value detector to generate an integral biomass potential value model, wherein the biomass potential value model comprises the following steps:
wherein E isbThe unit of the total potential of the biomass carrier is kJ, and the total potential of the biomass carrier is the potential energy stock of all the biomass carriers; i is the greening number, n is the total number of greening, AiIs the area of the green area, and the unit is m2；DiThe planting density of the greening area is shown in the unit of plants/m2；WiThe unit of the biomass carrier weight is kg/plant, wherein the biomass carrier weight is generated by once pruning one plant in a green area; t isiPruning times required for one year of a green area; hiIs the calorific value corresponding to the type of the biomass carrier and has the unit of kJ/kg.
Further, the second step of obtaining the suitable supply range includes:
step 1: acquiring the power energy development trend of the urban area according to the power consumption level in the urban historical statistics yearbook, wherein the model of the power energy demand development trend is as follows:
in the above formula, the first and second carbon atoms are,
the unit of the electric energy demand of the urban area after x years is kW; j is the number of the residential area, m is the total number of the residential areas in the urban area, RjIs the area of residential areas in urban areas in hm2；RjThe unit of the electricity density of residential areas in urban areas is kWh/hm2(ii) a Alpha is the electroelasticity coefficient;
step 2: according to the heat consumption level in the annual book of the city calendar year statistics, a model for obtaining the heat development trend of the city area is as follows:
wherein,the unit is kJ for the heat energy requirement of the urban area after x years; k is the number of the residential area, q is the total number of the residential area, RkThe heat density of the residential area of the urban area is kJ/hm2；GkThe heat density of the residential area of the urban area is kJ/hm2(ii) a Beta is a thermal elastic coefficient;
and step 3: combining the heat energy demand of the urban area after x years in the future obtained in the step1 and the heat energy demand of the urban area after x years in the future obtained in the step2, obtaining the energy demand of the urban area after x years in the future, wherein the energy demand model is as follows:
wherein E isxThe energy demand of the urban area after x years in the future is expressed in kWh; a is the power utilization fluctuation coefficient; b is the heat utilization accident loss coefficient;
and 4, step 4: and determining the size and the boundary of the supply range of the biomass power plant to be constructed according to the energy demand of the urban area after x years in the future and by combining the indexes of the urban area such as energy demand level, resident density and area.
Further, the third step of the concrete process of the optimal site selection of the power plant site comprises the following steps:
step 1: inputting the determined population space distribution data in the supply range into Arcgis software, and defining density grades by taking population density as a standard to form person/km2Determining the area of the load center through network analysis by using 0-10, 10-20 and 20-30 … hierarchical layers which are taken as units;
step 2: dividing urban roads in a supply range into four levels of an express way, a main road, a secondary road and a branch, determining respective passing speeds according to road widths, tracking congestion coefficients of each road by means of a GPS technology, and further obtaining the congestion coefficients of each road;
and 3, step 3: by means of Arcgis software, four principles of setting the region where the load center is located, along the edge of a secondary urban trunk road, downwind of a main urban wind and approaching the suburban area as much as possible are screened, and finally, a site selection position suitable for building a biomass power plant is determined; the site selection positions suitable for constructing the biomass power plant are single or multiple.
Further, the fourth step of acquiring the possible trend of the transportation route comprises:
step a: actually measuring the relation between the running speed and the oil consumption of a specific transport vehicle according to the specific model of the specific transport vehicle, and drawing a relation graph of the average running speed and the oil consumption of the transport vehicle;
step b: dividing urban roads in a supply range into four levels of an express way, a main road, a secondary road and a branch, determining respective passing speeds according to road widths, tracking congestion coefficients of each road by means of a GPS technology, and further obtaining the congestion coefficients of each road;
step c: and c, according to the grade of the urban road, the passing speed and the congestion coefficient obtained in the step b, determining corresponding running speed and oil consumption data in the relation graph of the average running speed and the oil consumption of the transport vehicle in the step a, and further obtaining the possible trend of the transport route.
Further, the fifth step of establishing an optimal transportation cost plan according to the comprehensive measurement and calculation model of the transportation cost by using the fuel consumption relationship, the congestion coefficient and the path length in the fourth step includes:
step 1: the method comprises the steps that a vector map acquired by a planning department is used as measurement and calculation original data, GPS navigation route data are combined, and oil consumption indexes of outgoing transport vehicles at each site on each road are acquired aiming at multiple site selection positions suitable for building a biomass power plant in a comprehensive measurement and calculation model of transport cost, so that the cost generated by transport is calculated according to oil price; the comprehensive measurement model of the transportation cost comprises the following steps:
wherein D is the transportation cost, J is the fuel price, w is the number of sections of the lorry passing through the expressway in the area, and QaFor the volume of oil consumption per hundred kilometers of a truck running on a highway, YaFor highway congestion coefficient, AwThe distance of a truck passing through a section of express way, x is the number of sections of truck passing through a main road in the area, and QbFor the volume of oil consumption per hundred kilometers of a truck running on a main road, YbIs the congestion coefficient of the main road, y is the number of sections of the truck passing the secondary main road in the area, QcFor the volume of oil consumption of one hundred kilometers when the truck is running on the secondary trunk road, YcIs the congestion coefficient of the secondary trunk road, z is the number of sections of the passing branch road of the truck in the area, QdFor the volume of oil consumption per hundred kilometers of a truck running on a branch road, YdThe branch congestion coefficient is obtained;
step 2: and establishing an optimal transportation cost scheme according to the transportation cost of each site selection position suitable for constructing the biomass power plant obtained in Step 1.
The invention has the beneficial effects that:
the invention provides a method for calculating the transportation cost of transporting urban biomass carriers to a biomass power plant aiming at the construction strategy, wherein the method can be mainly summarized into the following beneficial effects.
(1) The method comprises the steps of performing system evaluation on residual biomass carriers generated by urban greening, determining detailed vegetation types and species types, and accurately measuring the heat value by adopting a detection instrument, so that the stock and the potential of the urban greening biomass carriers can be determined, and the development and utilization construction behaviors of biomass energy sources in an urban range have a detailed quantitative analysis basis.
(2) The logic formula of multiple influence factors is set, the supply range can be calculated according to regional population space distribution data and road network real-time monitoring data, the data source is easy to obtain and reliable, and a calculation result with higher precision can be obtained in a lower-cost mode.
(3) Compared with the traditional transportation cost calculation, indexes such as oil consumption of specific vehicles, road congestion coefficients and the like are added, so that the whole transportation cost calculation process is closer to the actual situation, and a planning suggestion of economic cost estimation can be provided for a biomass power plant to be built more accurately.
Drawings
Fig. 1 is a mode of an operating principle of a transportation cost calculation method for transporting an urban biomass carrier to a biomass power plant.
Detailed Description
The present invention will be further described with reference to the following specific examples, but the present invention is not limited to these examples.
Example 1:
a transportation cost determination method of transporting an urban biomass carrier to a biomass power plant, the method comprising:
the first step is as follows: determining the plant type and weight of biomass carriers generated in urban areas according to the distribution data of parks, green belts and street trees in the urban areas, measuring the heat value by adopting a heat value detector, and then acquiring the potential energy storage of all the biomass carriers according to the heat value;
the second step is that: determining the heat energy demand level in the urban area according to the population distribution density and the geographic distribution state of the suburban area, and simultaneously acquiring the appropriate supply range corresponding to the urban biomass carrier according to the energy stock in the first step by combining the annual, month and daytime electricity utilization fluctuation coefficients;
the third step: measuring and calculating a load center according to the suitable supply range in the second step, and determining the optimal site of the power plant by depending on the network form of the existing urban road;
the fourth step: determining the relation between the speed and the oil consumption according to the model of the specific transport vehicle; performing annual data analysis on the road network in the suitable supply range in the second step to determine a congestion coefficient; acquiring possible trends of a transportation route by relying on a GPS map navigation system;
the fifth step: and establishing an optimal transportation cost scheme according to the comprehensive measurement and calculation model of the transportation cost by utilizing the oil consumption relation, the congestion coefficient and the path length in the fourth step.
Wherein, the specific process of the potential energy stock of all the biomass carriers in the first step comprises the following steps:
the method comprises the following steps: determining the range, position and type of urban greening by utilizing a mapping vector map, a far infrared remote sensing drawing and an unmanned aerial vehicle aerial photograph of an urban planning department; determining a greening part needing to be trimmed in all greening types in the city, wherein the greening part needing to be trimmed is a source area of the biomass carrier; is also the target of analysis required in the subsequent steps;
step two: acquiring the weight of the biomass carriers generated every year by all greening types in the city according to a biomass carrier weight calculation model, wherein the biomass carrier weight calculation model comprises the following steps:
wherein B is the total weight of various biomass carriers, and the unit is kg; i is the greening number, n is the total number of greening, AiIs the area of the green area, and the unit is m2；DiFor planting density in green areaUnit is one/m2；WiThe unit of the biomass carrier weight is kg/plant, wherein the biomass carrier weight is generated by once pruning one plant in a green area; t isiPruning times required for one year of a green area;
step three: the method comprises the following steps of performing heat value detection on biomass carriers generated by all greening types in a city by using a heat value detector to generate an integral biomass potential value model, wherein the biomass potential value model comprises the following steps:
wherein E isbThe unit of the total potential of the biomass carrier is kJ, and the total potential of the biomass carrier is the potential energy stock of all the biomass carriers; i is the greening number, n is the total number of greening, AiIs the area of the green area, and the unit is m2；DiThe planting density of the greening area is shown in the unit of plants/m2；WiThe unit of the biomass carrier weight is kg/plant, wherein the biomass carrier weight is generated by once pruning one plant in a green area; t isiPruning times required for one year of a green area; hiIs the calorific value corresponding to the type of the biomass carrier and has the unit of kJ/kg.
Based on the investigation and calculation of the three steps, the potential energy of the biomass carrier in the whole urban area can be obtained, the unit of the potential energy is kJ, the calculation of the heat energy is facilitated, and the potential energy can be converted into a kWh power unit when the power supply demand is estimated.
The second step of obtaining the suitable supply range comprises the following steps:
step 1: acquiring the power energy development trend of the urban area according to the power consumption level in the urban historical statistics yearbook, wherein the model of the power energy demand development trend is as follows:
in the above formula, the first and second carbon atoms are,
the unit of the electric energy demand of the urban area after x years is kW; j is the number of the residential area, m is the total number of the residential areas in the urban area, RjIs the area of residential areas in urban areas in hm2；RjThe unit of the electricity density of residential areas in urban areas is kWh/hm2(ii) a Alpha is the electroelasticity coefficient;
because the biomass power plant service object to be constructed is a common resident with stable demand development, in order to predict the future more reasonably, the electric power energy demand development trend model integrates the influence factors of the load density method and the elastic coefficient method, and can calculate the energy demand development trend more accurately.
Step 2: according to the heat consumption level in the annual book of the city calendar year statistics, a model for obtaining the heat development trend of the city area is as follows:
wherein,the unit is kJ for the heat energy requirement of the urban area after x years; k is the number of the residential area, q is the total number of the residential area, RkThe heat density of the residential area of the urban area is kJ/hm2；GkThe heat density of the residential area of the urban area is kJ/hm2(ii) a Beta is a thermal elastic coefficient;
because the biomass power plant service object to be constructed is a common resident with stable demand development, in order to predict the future more reasonably, the thermal development trend model of the urban area integrates the influence factors of the load density method and the elastic coefficient method, and the energy demand development trend can be calculated more accurately.
And step 3: combining the heat energy demand of the urban area after x years in the future obtained in the step1 and the heat energy demand of the urban area after x years in the future obtained in the step2, obtaining the energy demand of the urban area after x years in the future, wherein the energy demand model is as follows:
wherein E isxThe energy demand of the urban area after x years in the future is expressed in kWh; a is the power utilization fluctuation coefficient; b is the heat utilization accident loss coefficient (for convenience and unified calculation of the power utilization level, the conversion unit is kWh);
since step1 and step2 only determine the basic requirements of heat energy and electric energy, the problem of fluctuation peaks has not been considered. Therefore, historical year statistical data are further retrieved, power consumption peak data of the year, month and day are obtained, and a power consumption fluctuation coefficient a is determined. In contrast, the heat energy consumption is relatively stable (heating in winter), but the pipe network is also damaged accidentally, so the present embodiment sets a heat utilization accidental loss coefficient b.
And 4, step 4: and determining the size and the boundary of the supply range of the biomass power plant to be constructed according to the energy demand of the urban area after x years in the future and by combining the indexes of the urban area such as energy demand level, resident density and area.
The third step is that the concrete process of the optimal site selection of the power plant site comprises the following steps:
step 1: inputting the determined population space distribution data in the supply range into Arcgis software, and defining density grades by taking population density as a standard to form person/km2Determining the area of the load center through network analysis by using 0-10, 10-20 and 20-30 … hierarchical layers which are taken as units;
step 2: dividing urban roads in a supply range into four levels of an express way, a main road, a secondary road and a branch, determining respective passing speeds according to road widths, tracking congestion coefficients of each road by means of a GPS technology, and further obtaining the congestion coefficients of each road;
and 3, step 3: by means of Arcgis software, four principles of setting the region where the load center is located, along the edge of a secondary urban trunk road, downwind of a main urban wind and approaching the suburban area as much as possible are screened, and finally, a site selection position suitable for building a biomass power plant is determined; the site selection positions suitable for constructing the biomass power plant are single or multiple.
Fourthly, the process of acquiring the possible trend of the transportation route comprises the following steps:
step a: actually measuring the relation between the running speed and the oil consumption of a specific transport vehicle according to the specific model of the specific transport vehicle, and drawing a relation graph of the average running speed and the oil consumption of the transport vehicle;
step b: dividing urban roads in a supply range into four levels of an express way, a main road, a secondary road and a branch, determining respective passing speeds according to road widths, tracking congestion coefficients of each road by means of a GPS technology, and further obtaining the congestion coefficients of each road;
step c: and c, according to the grade of the urban road, the passing speed and the congestion coefficient obtained in the step b, determining corresponding running speed and oil consumption data in the relation graph of the average running speed and the oil consumption of the transport vehicle in the step a, and further obtaining the possible trend of the transport route.
And fifthly, the concrete process of establishing the optimal transportation cost scheme according to the comprehensive measurement and calculation model of the transportation cost by using the oil consumption relation, the congestion coefficient and the path length in the fourth step comprises the following steps:
step 1: the method comprises the steps that a vector map acquired by a planning department is used as measurement and calculation original data, GPS navigation route data are combined, and oil consumption indexes of outgoing transport vehicles at each site on each road are acquired aiming at multiple site selection positions suitable for building a biomass power plant in a comprehensive measurement and calculation model of transport cost, so that the cost generated by transport is calculated according to oil price; the comprehensive measurement model of the transportation cost comprises the following steps:
wherein D is the transportation cost, J is the fuel price, w is the number of sections of the lorry passing through the expressway in the area, and QaFor the volume of oil consumption per hundred kilometers of a truck running on a highway, YaFor highway congestion coefficient, AwThe distance of a truck passing through a section of express way, x is the number of sections of truck passing through a main road in the area, and QbFor the volume of oil consumption per hundred kilometers of a truck running on a main road, YbIs the congestion coefficient of the main road, y is the number of sections of the truck passing the secondary main road in the area, QcFor the volume of oil consumption of one hundred kilometers when the truck is running on the secondary trunk road, YcIs the congestion coefficient of the secondary trunk road, z is the number of sections of the passing branch road of the truck in the area, QdFor the volume of oil consumption per hundred kilometers of a truck running on a branch road, YdThe branch congestion coefficient is obtained;
step 2: and establishing an optimal transportation cost scheme according to the transportation cost of each site selection position suitable for constructing the biomass power plant obtained in Step 1.
The transportation cost determination method for transporting the urban biomass carrier to the biomass power plant has the following beneficial effects:
(1) the method comprises the steps of performing system evaluation on residual biomass carriers generated by urban greening, determining detailed vegetation types and species types, and accurately measuring the heat value by adopting a detection instrument, so that the stock and the potential of the urban greening biomass carriers can be determined, and the development and utilization construction behaviors of biomass energy sources in an urban range have a detailed quantitative analysis basis.
(2) The logic formula of multiple influence factors is set, the supply range can be calculated according to regional population space distribution data and road network real-time monitoring data, the data source is easy to obtain and reliable, and a calculation result with higher precision can be obtained in a lower-cost mode.
(3) Compared with the traditional transportation cost calculation, indexes such as oil consumption of specific vehicles, road congestion coefficients and the like are added, so that the whole transportation cost calculation process is closer to the actual situation, and a planning suggestion of economic cost estimation can be provided for a biomass power plant to be built more accurately.
Although the present invention has been described with reference to the preferred embodiments, it should be understood that various changes and modifications can be made therein by those skilled in the art without departing from the spirit and scope of the invention as defined in the appended claims.
Claims (2)
1. A method of determining transportation costs for transporting an urban biomass carrier to a biomass power plant, the method comprising:
the first step is as follows: determining the plant type and weight of biomass carriers generated in urban areas according to the distribution data of parks, green belts and street trees in the urban areas, measuring the heat value by adopting a heat value detector, and then acquiring the potential energy storage of all the biomass carriers according to the heat value;
the second step is that: determining the heat energy demand level in the urban area according to the population distribution density and the geographic distribution state of the suburban area, and simultaneously acquiring the appropriate supply range corresponding to the urban biomass carrier according to the energy stock in the first step by combining the annual, month and daytime electricity utilization fluctuation coefficients;
the third step: measuring and calculating a load center according to the suitable supply range in the second step, and determining the optimal site of the power plant by depending on the network form of the existing urban road;
the fourth step: determining the relation between the speed and the oil consumption according to the model of the specific transport vehicle; performing annual data analysis on the road network in the suitable supply range in the second step to determine a congestion coefficient and a path length; acquiring the trend of a transportation route by relying on a GPS map navigation system;
the fifth step: establishing an optimal transportation cost scheme according to a comprehensive measurement and calculation model of the transportation cost by utilizing the relation between the speed and the oil consumption, the congestion coefficient and the path length in the fourth step;
wherein, the specific process of the potential energy stock of all the biomass carriers in the first step comprises the following steps:
the method comprises the following steps: determining the range, position and type of urban greening by utilizing a mapping vector map, a far infrared remote sensing drawing and an unmanned aerial vehicle aerial photograph of an urban planning department; determining a greening part needing to be trimmed in all greening types in the urban area, wherein the greening part needing to be trimmed is a source area of the biomass carrier; is also the target of analysis required in the subsequent steps;
step two: acquiring the weight of the biomass carriers generated each year by all greening types in the urban area according to a biomass carrier weight calculation model, wherein the biomass carrier weight calculation model comprises the following steps:
wherein B is the total weight of various biomass carriers, and the unit is kg; i is the greening number, n is the total number of greening, AiIs the area of the green area, and the unit is m2；DiThe planting density of the greening area is shown in the unit of plants/m2；WiThe unit of the biomass carrier weight is kg/plant, wherein the biomass carrier weight is generated by once pruning one plant in a green area; t isiPruning times required for one year of a green area;
step three: the method comprises the following steps of performing heat value detection on biomass carriers generated by all greening types in a city by using a heat value detector to generate an integral biomass potential value model, wherein the biomass potential value model comprises the following steps:
wherein E isbThe unit of the total potential of the biomass carrier is kJ, and the total potential of the biomass carrier is the potential energy stock of all the biomass carriers; i is the greening number, n is the total number of greening, AiIs the area of the green area, and the unit is m2；DiThe planting density of the greening area is shown in the unit of plants/m2；WiThe unit of the biomass carrier weight is kg/plant, wherein the biomass carrier weight is generated by once pruning one plant in a green area; t isiPruning times required for one year of a green area; hiThe calorific value corresponding to the type of the biomass carrier is kJ/kg;
the second step of obtaining the suitable supply range comprises the following steps:
step 1: acquiring the power energy development trend of the urban area according to the power consumption level in the urban historical statistics yearbook, wherein the model of the power energy demand development trend is as follows:
in the above formula, the first and second carbon atoms are,the unit of the electric energy demand of the urban area after x years is kW; j is the number of the residential area, m is the total number of the residential areas in the urban area, RjIs the area of residential areas in urban areas in hm2；PjThe unit of the electricity density of residential areas in urban areas is kWh/hm2(ii) a Alpha is the electroelasticity coefficient;
step 2: according to the heat consumption level in the annual book of the city calendar year statistics, a model for obtaining the heat development trend of the city area is as follows:
wherein,
the unit is kJ for the heat energy requirement of the urban area after x years; k is the number of the residential area, q is the total number of the residential area, RkIs the heat utilization area of the residential area of the urban area, and the unit is hm2；GkThe heat density of the residential area of the urban area is kJ/hm2(ii) a Beta is a thermal elastic coefficient;
and step 3: combining the electric energy demand of the urban area after x years in the future obtained in the step1 and the heat energy demand of the urban area after x years in the future obtained in the step2, obtaining the energy demand of the urban area after x years in the future, wherein the energy demand model is as follows:
wherein E isxThe energy demand of the urban area after x years in the future is expressed in kWh; a is the power utilization fluctuation coefficient; b is the heat utilization accident loss coefficient;
and 4, step 4: determining the size and the boundary of a supply range of a biomass power plant to be constructed according to the energy demand of the urban area after x years in the future and by combining the energy demand level, the resident density and the area index of the urban area;
and fifthly, the concrete process of establishing the optimal transportation cost scheme according to the comprehensive measurement and calculation model of the transportation cost by utilizing the relation between the speed and the oil consumption, the congestion coefficient and the path length in the fourth step comprises the following steps:
step 1: the method comprises the steps that a vector map acquired by a planning department is used as measurement and calculation original data, GPS navigation route data are combined, and oil consumption indexes of outgoing transport vehicles at each site on each road are acquired aiming at multiple site selection positions suitable for building a biomass power plant in a comprehensive measurement and calculation model of transport cost, so that the cost generated by transport is calculated according to oil price; the comprehensive measurement model of the transportation cost comprises the following steps:
wherein D is the transportation cost, J is the fuel price, w is the number of sections of the lorry passing through the expressway in the area, and QawThe oil consumption volume of a truck running on an express way is one hundred kilometers when the truck passes through a certain section of express way in an area, and Y isaFor highway congestion coefficient, AwThe distance of a truck passing through a section of express way, x is the number of sections of truck passing through a main road in the area, and QbxThe oil consumption volume of one hundred kilometers when the truck runs on a trunk road when the truck approaches a section of the trunk road in an area, YbIs the congestion coefficient of the main road, y is the number of sections of the truck passing the secondary main road in the area, QcyThe oil consumption volume of one hundred kilometers when a truck runs on a secondary main road when the truck passes through a certain section of the secondary main road in an area, YcIs the congestion coefficient of the secondary trunk road, and z is the passing branch of the truck in the areaNumber of stages of road, QdzThe oil consumption volume of hundred kilometers when the truck passes through a certain section of branch road in the area and the truck runs on the branch road, YdThe branch congestion coefficient is obtained;
step 2: according to the transportation cost of each site selection position suitable for building the biomass power plant obtained at Step1, establishing an optimal transportation cost scheme;
the third step is that the concrete process of the optimal site selection of the power plant site comprises the following steps:
step 1: inputting the determined population space distribution data in the supply range into Arcgis software, and defining density grades by taking population density as a standard to form person/km2Determining the area of the load center through network analysis by using 0-10, 10-20 and 20-30 hierarchical layers which are taken as units;
step 2: dividing urban roads in a supply range into four levels of an express way, a main road, a secondary road and a branch, determining respective passing speeds according to road widths, tracking congestion coefficients of each road by means of a GPS technology, and further obtaining the congestion coefficients of each road;
and 3, step 3: by means of Arcgis software, the method is set in an area where a load center is located, four principles of being along the edge of a secondary urban trunk road, downwind from a main urban wind direction and being close to a suburban area are screened, and finally, a site selection position suitable for building a biomass power plant is determined;
the site selection positions suitable for constructing the biomass power plant are single or multiple.
2. The transportation cost determination method according to claim 1, wherein the fourth step of obtaining the transportation route trend comprises:
step a: actually measuring the relation between the running speed and the oil consumption of a specific transport vehicle according to the specific model of the specific transport vehicle, and drawing a relation graph of the average running speed and the oil consumption of the transport vehicle;
step b: dividing urban roads in a supply range into four levels of an express way, a main road, a secondary road and a branch, determining respective passing speeds according to road widths, tracking congestion coefficients of each road by means of a GPS technology, and further obtaining the congestion coefficients of each road;
step c: and c, according to the grade of the urban road, the passing speed and the congestion coefficient obtained in the step b, determining corresponding running speed and oil consumption data in the relation graph of the average running speed and the oil consumption of the transport vehicle in the step a, and further obtaining the trend of the transport route.
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