CN113642788A - Diversified heat source optimization planning method suitable for large-scale medium-deep geothermal region - Google Patents
Diversified heat source optimization planning method suitable for large-scale medium-deep geothermal region Download PDFInfo
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Abstract
The invention belongs to the technical field of heat source optimization planning, and discloses a diversified heat source optimization planning method suitable for a large-scale medium-deep geothermal area, which comprises the following steps: analyzing the characteristics of various heat source forms in a large-scale medium-deep geothermal region, and carrying out technical evaluation on the heat source forms, media, parameters, technical paths and energy consumption aspects; comparing initial investment, running cost and annual cost of various heat sources in a large-scale medium-deep geothermal region to obtain a quantitative index; the configuration design of the heating plant is reasonably optimized through various energy-saving control technologies; and analyzing an optimization design scheme by combining typical engineering in the area, compiling and optimizing a system energy supply curve, and finally realizing comprehensive optimization of heat source planning design of the large-scale medium-deep geothermal area. The invention optimizes the heat source planning design of a large area through the technical path of analysis, evaluation and utilization, and optimizes and designs diversified heat source heating schemes through calculating annual dynamic load.
Description
Technical Field
The invention belongs to the technical field of heat source optimization planning, and particularly relates to a diversified heat source optimization planning method suitable for large-scale medium-deep geothermal areas.
Background
At present, with the development of intelligent power distribution and energy internet technologies, multi-party interaction involving the complementary characteristics of multiple energy demands has become an effective way to solve the problems of low efficiency and power shortage of energy systems. The regional integrated energy system (rees) is a new energy supply mode, and it uses advanced energy conversion and transmission technology to convert the resources of solar energy, wind energy, geothermal energy, Natural Gas (NG), biomass, etc. into the energy sources of cold, heat, electricity, etc. required by consumers, thus improving the comprehensive utilization rate of energy sources and the flexibility, safety, economy and self-healing ability of the energy supply system. The planning design is one of core technology systems of the comprehensive energy system, and is directly related to the economy, the environmental protection and the reliability of the system. In the planning and designing process, intermittent, flexible and changeable combination schemes of the renewable energy system and different system operation control strategies need to be considered, and the traditional deterministic optimization method is no longer suitable for capacity planning of the system. Therefore, the reasonable RIES capacity planning can delay the construction of the traditional energy supply system, improve the reliability of the energy supply of the system and meet the requirements of users on the energy quality and the requirements of governments on environmental protection. However, the existing heat source optimization planning method mainly aims at the lowest economic cost of planning a micro-grid and a distributed power supply capacity, lacks effective verification on the planning rationality, and cannot ensure the reliability of a planning result. Therefore, a new heat source optimization planning method suitable for large-scale medium-deep geothermal areas is needed to overcome the problems and disadvantages of the prior art.
Through the above analysis, the problems and defects of the prior art are as follows: the existing heat source optimization planning method mainly aims at the lowest economic cost of planning a micro-grid and a distributed power supply capacity, lacks effective verification on the planning rationality, and cannot ensure the reliability of a planning result.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a diversified heat source optimization planning method suitable for large-scale medium-deep geothermal regions.
The invention is realized in such a way that a diversified heat source optimization planning method suitable for large-scale medium-depth geothermal areas comprises the following steps:
analyzing the characteristics of various heat source forms in a large-scale medium-deep geothermal region, and carrying out technical evaluation on the heat source forms, media, parameters, technical paths and energy consumption aspects;
comparing initial investment, running cost and annual cost of various heat sources in the large-scale medium-deep geothermal region through a dynamic calculation method to obtain a quantitative index;
thirdly, processing the quantized indexes, and reasonably optimizing the configuration design of the heating plant according to the processing result of the quantized indexes by various energy-saving control technologies;
and step four, analyzing and optimizing a design scheme by combining typical engineering in the area, compiling and optimizing a system energy supply curve, and finally realizing comprehensive optimization of the heat source planning design of the large-scale medium-deep geothermal area.
Further, in the first step, the analyzing characteristics of various heat source forms in the large-scale medium-deep geothermal region and performing technical evaluation on the heat source forms, mediums, parameters, technical paths and energy consumption aspects includes:
(1) establishing a heat source technology evaluation model based on a Modelica language;
(2) setting a heat source minimum delay objective function, establishing large-scale middle-deep geothermal area source-load space distribution constraint, and solving the objective function by adopting a particle swarm optimization algorithm;
(3) and establishing data communication between the model building based on the Modelica language and the heat supply network topology planning based on the particle swarm optimization algorithm, and calling model calculation data in the optimization process.
Further, in the step (1), the heat source technology evaluation model comprises a partial differential equation of a mass continuous equation, an energy balance equation, a pipeline friction resistance equation and a momentum conservation equation.
Further, the expression of the mass continuity equation is:
wherein x is the distance of the large-scale medium-deep geothermal region, and along the coordinate x, the unit m; t is time; ρ is ρ (x, t) represents the heat source vapor density in kg/m3(ii) a v is v (x, t) represents the heat source steam flow rate in m/s; A. a (x) is the heat source steam flow area in m2；
The expression of the energy balance equation is:
wherein T is T (x, T) which represents the temperature of heat source steam and has a unit of K; u is u (x, t) represents the specific internal energy, unit J; z is z (x) represents the height of the heat source from the ground in m; g is gravity in m/s2；
The expression of the momentum conservation equation is as follows:
wherein, FFIs resistance, in units of N;
the expression of the pipeline frictional resistance equation is as follows:
wherein f is the coefficient of friction; s is the perimeter, in m;
the heat exchange equation between the node and the external environment is as follows:
q＝α(Ts-Ta)；
wherein q represents the heat exchange amount in W/m2；TsIs the heat source steam temperature, unit K; t isaIs the heat source steam temperature, unit K; alpha is heat transfer coefficient and unit W/m2·K。
Further, in step three, the processing the quantization index includes:
(1) determining index data of at least one quantitative index based on the volume price data in the first large-scale medium-depth geothermal region return measurement interval;
(2) determining a multi-space indication parameter of the at least one quantitative indicator at each specified time within the first large middle-deep geothermal region survey area based on the indicator data;
(3) determining a prior decision value in the first test interval based on weight values respectively corresponding to an ascending stage and a descending stage of the price in the first large-scale medium-deep geothermal region return interval;
(4) and determining the processed quantitative index data based on the prior decision value and the multi-space indication parameter at each appointed moment.
Further, the multi-null indication parameter is a parameter for indicating a multi-head signal and a null-head signal.
Further, in the third step, the energy-saving control technology comprises a time-sharing and zoning energy supply scheme, a climate compensation technology, a heat supply station centralized control technology and a heat source energy-saving control technology.
Further, in step four, the analyzing and optimizing the design scheme includes:
(1) establishing a heat source side load constraint, a heat supply network transmission and distribution capacity constraint and a heat supply network splitting model;
(2) determining the feasible load distribution domain or the combination relation range among the multiple heat sources according to the model;
(3) and analyzing the optimization design scheme according to the load distribution feasible domain or the combination relation range.
Another object of the present invention is to provide a diversified heat source optimized planning system for a large-scale middle-depth geothermal region, which applies the diversified heat source optimized planning method for a large-scale middle-depth geothermal region, the diversified heat source optimized planning system for a large-scale middle-depth geothermal region including:
the heat source technology evaluation module is used for analyzing the characteristics of various heat source forms in the large-scale medium-deep geothermal region and carrying out technology evaluation on the aspects of the heat source forms, media, parameters, technical paths and energy consumption;
the quantitative index determining module is used for comparing initial investment, running cost and annual cost of various heat sources in the large-scale medium-deep geothermal area through a dynamic calculation method to obtain quantitative indexes;
the heat supply station configuration optimization module is used for processing the quantitative indexes and reasonably optimizing the configuration design of the heat supply station through various energy-saving control technologies;
and the heat source planning design optimization module is used for analyzing and optimizing a design scheme by combining typical projects in the area, compiling and optimizing a system energy supply curve, and finally realizing comprehensive optimization of heat source planning design of the large-scale medium-deep geothermal area.
It is another object of the present invention to provide a computer program product stored on a computer readable medium, comprising a computer readable program for providing a user input interface to implement the diversified heat source optimization planning method for large and medium-deep geothermal areas when executed on an electronic device.
Another object of the present invention is to provide a computer-readable storage medium storing instructions which, when executed on a computer, cause the computer to execute the diversified heat source optimization planning method suitable for large-scale medium-depth geothermal regions.
Another object of the present invention is to provide an information data processing terminal for implementing the diversified heat source optimization planning system suitable for large-scale medium-depth geothermal regions.
By combining all the technical schemes, the invention has the advantages and positive effects that: the diversified heat source optimization planning method suitable for the large-scale medium-depth geothermal area is optimized aiming at the heat source planning design of the large-scale area through the technical path of analysis, evaluation and utilization, the annual dynamic load of each subarea is calculated through simulation according to the function division of different buildings in the area and different area types, the highest value is calculated through superposition by combining the simultaneous use coefficients, the load characteristics are analyzed, and then the diversified heat source heating scheme is optimized and designed.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments of the present invention will be briefly described below, and it is obvious that the drawings described below are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a flowchart of a diversified heat source optimization planning method suitable for a large-scale medium-depth geothermal region according to an embodiment of the present invention.
Fig. 2 is a flowchart of a method for analyzing characteristics of various heat source types in a large-scale medium-deep geothermal region and performing technical evaluation on the heat source types, media, parameters, technical paths and energy consumption aspects according to an embodiment of the present invention.
Fig. 3 is a flowchart of a method for processing quantization index according to an embodiment of the present invention.
FIG. 4 is a flowchart of a method for analyzing an optimal design solution according to an embodiment of the present invention.
FIG. 5 is a block diagram of a diversified heat source optimization planning system suitable for large-scale medium-depth geothermal regions according to an embodiment of the present invention;
in the figure: 1. a heat source technology evaluation module; 2. a quantization index determination module; 3. a heating plant configuration optimizing module; 4. and a heat source planning design optimization module.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail with reference to the following embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Aiming at the problems in the prior art, the invention provides a diversified heat source optimization planning method suitable for large-scale medium-deep geothermal regions, and the invention is described in detail below with reference to the accompanying drawings.
As shown in fig. 1, the diversified heat source optimization planning method suitable for large-scale medium-deep geothermal regions provided by the embodiment of the invention includes the following steps:
s101, analyzing the characteristics of various heat source forms in a large-scale medium-deep geothermal region, and carrying out technical evaluation on the heat source forms, media, parameters, technical paths and energy consumption aspects;
s102, comparing initial investment, running cost and annual cost of various heat sources in a large-scale medium-deep geothermal region through a dynamic calculation method to obtain a quantitative index;
s103, processing the quantitative indexes, and reasonably optimizing the configuration design of the heating plant according to the processing result of the quantitative indexes by various energy-saving control technologies;
and S104, analyzing an optimization design scheme by combining typical projects in the area, compiling and optimizing a system energy supply curve, and finally realizing comprehensive optimization of heat source planning design of the large-scale medium-deep geothermal area.
In the embodiment of the invention, cold water is used as the medium, and the cold water is heated to become hot water.
As shown in fig. 2, in step S101, the analyzing characteristics of various heat source types in a large-scale medium-deep geothermal region and performing technical evaluation on the heat source types, mediums, parameters, technical paths, and energy consumption includes:
s201, establishing a heat source technology evaluation model based on a Modelica language;
s202, setting a heat source minimum delay objective function, establishing large-scale medium-deep geothermal area source-load space distribution constraint, and solving the objective function by adopting a particle swarm optimization algorithm;
s203, establishing data communication between the model building based on the Modelica language and the heat supply network topology planning based on the particle swarm optimization algorithm, and calling model calculation data in the optimization process.
In step S201 provided in the embodiment of the present invention, the heat source technology evaluation model includes a partial differential equation of a mass continuity equation, an energy balance equation, a pipeline frictional resistance equation, and a momentum conservation equation.
The expression of the mass continuity equation provided by the embodiment of the invention is as follows:
wherein x is the distance of the large-scale medium-deep geothermal region, and along the coordinate x, the unit m; t is time; ρ is ρ (x, t) represents the heat source vapor density in kg/m3(ii) a v is v (x, t) represents the heat source steam flow rate in m/s; A. a (x) is the heat source steam flow area in m2。
The expression of the energy balance equation provided by the embodiment of the invention is as follows:
wherein T is T (x, T) which represents the temperature of heat source steam and has a unit of K; u is u (x, t) represents the specific internal energy, unit J; z is z (x) represents the height of the heat source from the ground in m; g is gravity in m/s2。
The expression of the momentum conservation equation provided by the embodiment of the invention is as follows:
wherein, FFIs resistance, in units of N.
The embodiment of the invention provides an expression of a pipeline frictional resistance equation, which is as follows:
wherein f is the coefficient of friction; s is the circumference, in m.
The heat exchange equation between the node and the external environment provided by the embodiment of the invention is as follows:
q＝α(Ts-Ta)；
wherein q represents the heat exchange amount in W/m2；TsIs the heat source steam temperature, unit K; t isaIs the heat source steam temperature, unit K; alpha is heat transfer coefficient and unit W/m2·K。
As shown in fig. 3, in step S103, the processing of the quantization index according to the embodiment of the present invention includes:
s301, determining index data of at least one quantitative index based on the volume price data in the first large middle-deep geothermal region return measurement interval;
s302, determining a multi-space indication parameter of the at least one quantitative index at each designated moment in the first large middle-deep geothermal region survey area based on the index data;
s303, determining a prior decision value in the first detection interval based on weight values respectively corresponding to an ascending stage and a descending stage of the price in the first large-scale medium-deep geothermal region detection interval;
s304, determining the processed quantitative index data based on the prior decision value and the multi-empty indication parameter at each appointed moment.
The multi-null indication parameter provided by the embodiment of the invention is a parameter for indicating a multi-head signal and a null-head signal.
In step S103 provided in the embodiment of the present invention, the energy saving control technology includes a time-sharing and partitioned energy supply scheme, a climate compensation technology, a heating station centralized control technology, and a heat source energy saving control technology.
As shown in fig. 4, in step S104 provided in the embodiment of the present invention, the analyzing and optimizing the design scheme includes:
s401, establishing a heat source side load constraint, a heat supply network transmission and distribution capacity constraint and a heat supply network splitting model;
s402, determining a feasible load distribution domain or a combination relation range among multiple heat sources according to the model;
and S403, analyzing the optimization design scheme according to the load distribution feasible domain or the combination relation range.
As shown in fig. 5, the diversified heat source optimization planning system suitable for large-scale medium-deep geothermal region provided by the embodiment of the invention includes:
the heat source technology evaluation module 1 is used for analyzing the characteristics of various heat source forms in a large-scale medium-deep geothermal area and carrying out technology evaluation on the aspects of heat source forms, media, parameters, technical paths and energy consumption;
the quantitative index determining module 2 is used for comparing initial investment, running cost and annual cost of various heat sources in the large-scale medium-deep geothermal area through a dynamic calculation method to obtain quantitative indexes;
the heat supply station configuration optimization module 3 is used for processing the quantitative indexes and reasonably optimizing the configuration design of the heat supply station through various energy-saving control technologies;
and the heat source planning design optimization module 4 is used for analyzing and optimizing a design scheme by combining typical projects in the area, compiling and optimizing a system energy supply curve, and finally realizing comprehensive optimization of heat source planning design of the large-scale medium-deep geothermal area.
The invention is further described with reference to specific examples.
The method mainly comprises the steps of analyzing, evaluating and utilizing, optimizing the heat source planning design of a large area, dividing functions of different buildings in the area according to different area types, calculating annual dynamic loads of all subareas through simulation, combining simultaneous use coefficients, calculating the highest value in a superposition mode, analyzing the load characteristics, and further optimizing and designing diversified heat source heat supply schemes.
Firstly, analyzing the characteristics of various heat source forms in an area, and carrying out technical evaluation on the aspects of the heat source forms, media, parameters, technical paths, energy consumption and the like; comparing initial investment, running cost and annual cost of various heat sources by a dynamic calculation method to obtain a quantitative index, and providing a basis for heat source type selection of a large area;
secondly, through various energy-saving control technologies: the method comprises a time-sharing and zoning energy supply scheme, a climate compensation technology, a heat supply station centralized control technology and energy-saving control of a heat source, and the configuration design of the heat supply station is reasonably optimized;
and thirdly, analyzing an optimization design scheme by combining typical engineering in the area, compiling and optimizing a system energy supply curve, and finally achieving comprehensive optimization of large-area heat source planning design.
In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When used in whole or in part, can be implemented in a computer program product that includes one or more computer instructions. When loaded or executed on a computer, cause the flow or functions according to embodiments of the invention to occur, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, the computer instructions may be transmitted from one website site, computer, server, or data center to another website site, computer, server, or data center via wire (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL), or wireless (e.g., infrared, wireless, microwave, etc.)). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device, such as a server, a data center, etc., that includes one or more of the available media. The usable medium may be a magnetic medium (e.g., floppy Disk, hard Disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., Solid State Disk (SSD)), among others.
The above description is only for the purpose of illustrating the present invention and the appended claims are not to be construed as limiting the scope of the invention, which is intended to cover all modifications, equivalents and improvements that are within the spirit and scope of the invention as defined by the appended claims.
Claims (10)
1. A diversified heat source optimization planning method suitable for a large-scale middle-depth geothermal area is characterized by comprising the following steps of:
analyzing the characteristics of various heat source forms in a large-scale medium-deep geothermal region, and carrying out technical evaluation on the heat source forms, media, parameters, technical paths and energy consumption aspects;
comparing initial investment, running cost and annual cost of various heat sources in the large-scale medium-deep geothermal region through a dynamic calculation method to obtain a quantitative index;
thirdly, processing the quantized indexes, and reasonably optimizing the configuration design of the heating plant according to the processing result of the quantized indexes by various energy-saving control technologies;
and step four, analyzing and optimizing a design scheme by combining typical engineering in the area, compiling and optimizing a system energy supply curve, and finally realizing comprehensive optimization of the heat source planning design of the large-scale medium-deep geothermal area.
2. A diversified heat source optimization planning method suitable for large and medium-sized geothermal areas according to claim 1, wherein in the first step, the analyzing characteristics of various heat source types in the large and medium-sized geothermal area and performing technical evaluation on the heat source types, mediums, parameters, technical paths and energy consumption comprises:
(1) establishing a heat source technology evaluation model based on a Modelica language;
(2) setting a heat source minimum delay objective function, establishing large-scale middle-deep geothermal area source-load space distribution constraint, and solving the objective function by adopting a particle swarm optimization algorithm;
(3) and establishing data communication between the model building based on the Modelica language and the heat supply network topology planning based on the particle swarm optimization algorithm, and calling model calculation data in the optimization process.
3. A diversified heat source optimization planning method suitable for large-scale medium-deep geothermal areas according to claim 2, wherein in the step (1), the heat source technology evaluation model comprises partial differential equations of a mass continuity equation, an energy balance equation, a pipeline frictional resistance equation and a momentum conservation equation.
4. A diversified heat source optimization planning method suitable for large-scale medium-deep geothermal areas according to claim 3, wherein the expression of the mass continuity equation is as follows:
wherein x is the distance of the large-scale medium-deep geothermal region, and along the coordinate x, the unit m; t is time; ρ is ρ (x, t) represents the heat source vapor density in kg/m3(ii) a v is v (x, t) represents the heat source steam flow rate in m/s; A. a (x) is the heat source steam flow area in m2；
The expression of the energy balance equation is:
wherein T is T (x, T) which represents the temperature of heat source steam and has a unit of K; u is u (x, t) represents the specific internal energy, unit J; z is z (x) represents the height of the heat source from the ground in m; g is gravity in m/s2；
The expression of the momentum conservation equation is as follows:
wherein, FFIs resistance, in units of N;
the expression of the pipeline frictional resistance equation is as follows:
wherein f is the coefficient of friction; s is the perimeter, in m;
the heat exchange equation between the node and the external environment is as follows:
q＝α(Ts-Ta)；
wherein q represents the heat exchange amount in W/m2；TsIs the heat source steam temperature, unit K; t isaIs the heat source steam temperature, unit K; alpha is heat transfer coefficient and unit W/m2·K。
5. A diversified heat source optimization planning method suitable for large-scale medium-deep geothermal areas according to claim 1, wherein in step three, the processing of the quantitative index comprises:
(1) determining index data of at least one quantitative index based on the volume price data in the first large-scale medium-depth geothermal region return measurement interval;
(2) determining a multi-space indication parameter of the at least one quantitative indicator at each specified time within the first large middle-deep geothermal region survey area based on the indicator data;
(3) determining a prior decision value in the first test interval based on weight values respectively corresponding to an ascending stage and a descending stage of the price in the first large-scale medium-deep geothermal region return interval;
(4) and determining the processed quantitative index data based on the prior decision value and the multi-space indication parameter at each appointed moment.
6. A diversified heat source optimization planning method suitable for a large-scale medium-deep geothermal area according to claim 5, wherein the multi-empty indication parameter is a parameter for indicating a multi-empty signal and an empty signal.
7. The diversified heat source optimization planning method suitable for the large-scale medium-deep geothermal area according to claim 1, wherein in the third step, the energy-saving control technology comprises a time-sharing and regional energy supply scheme, a climate compensation technology, a heat supply station centralized control technology and a heat source energy-saving control technology.
8. A diversified heat source optimization planning method suitable for large-scale medium-deep geothermal areas according to claim 1, wherein in step four, the analyzing and optimizing design scheme comprises:
(1) establishing a heat source side load constraint, a heat supply network transmission and distribution capacity constraint and a heat supply network splitting model;
(2) determining the feasible load distribution domain or the combination relation range among the multiple heat sources according to the model;
(3) and analyzing the optimization design scheme according to the load distribution feasible domain or the combination relation range.
9. A diversified heat source optimization planning system for large-scale medium-depth geothermal areas applying the diversified heat source optimization planning method for large-scale medium-depth geothermal areas according to any one of claims 1 to 8, the diversified heat source optimization planning system for large-scale medium-depth geothermal areas comprising:
the heat source technology evaluation module is used for analyzing the characteristics of various heat source forms in the large-scale medium-deep geothermal region and carrying out technology evaluation on the aspects of the heat source forms, media, parameters, technical paths and energy consumption;
the quantitative index determining module is used for comparing initial investment, running cost and annual cost of various heat sources in the large-scale medium-deep geothermal area through a dynamic calculation method to obtain quantitative indexes;
the heat supply station configuration optimization module is used for processing the quantitative indexes and reasonably optimizing the configuration design of the heat supply station through various energy-saving control technologies;
and the heat source planning design optimization module is used for analyzing and optimizing a design scheme by combining typical projects in the area, compiling and optimizing a system energy supply curve, and finally realizing comprehensive optimization of heat source planning design of the large-scale medium-deep geothermal area.
10. A computer program product stored on a computer readable medium, comprising a computer readable program for providing a user input interface for implementing a method for optimized planning of heat sources for large, medium-depth geothermal areas as diversified according to any one of claims 1-8 when executed on an electronic device.
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