CN110991719B - Method for optimizing layout pipe diameters in layering mode for regional heat supply pipe network of intelligent comprehensive energy system - Google Patents
Method for optimizing layout pipe diameters in layering mode for regional heat supply pipe network of intelligent comprehensive energy system Download PDFInfo
- Publication number
- CN110991719B CN110991719B CN201911166478.0A CN201911166478A CN110991719B CN 110991719 B CN110991719 B CN 110991719B CN 201911166478 A CN201911166478 A CN 201911166478A CN 110991719 B CN110991719 B CN 110991719B
- Authority
- CN
- China
- Prior art keywords
- pipe
- network
- section
- heat supply
- pipe diameter
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 36
- 238000005457 optimization Methods 0.000 claims abstract description 33
- 230000002068 genetic effect Effects 0.000 claims abstract description 18
- 238000006243 chemical reaction Methods 0.000 claims abstract description 12
- 238000011234 economic evaluation Methods 0.000 claims abstract description 12
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 94
- 238000004364 calculation method Methods 0.000 claims description 35
- 238000010438 heat treatment Methods 0.000 claims description 34
- 239000002689 soil Substances 0.000 claims description 16
- 230000001419 dependent effect Effects 0.000 claims description 15
- 238000010276 construction Methods 0.000 claims description 14
- 230000003044 adaptive effect Effects 0.000 claims description 7
- 238000009933 burial Methods 0.000 claims description 7
- 238000009413 insulation Methods 0.000 claims description 6
- 230000005611 electricity Effects 0.000 claims description 5
- 238000004891 communication Methods 0.000 claims description 4
- 230000000694 effects Effects 0.000 claims description 4
- 238000012423 maintenance Methods 0.000 claims description 4
- 238000007667 floating Methods 0.000 claims description 3
- 239000012774 insulation material Substances 0.000 claims description 3
- 238000004519 manufacturing process Methods 0.000 claims description 3
- 230000035772 mutation Effects 0.000 claims description 3
- 238000012546 transfer Methods 0.000 claims description 3
- 238000011156 evaluation Methods 0.000 abstract 1
- 238000013461 design Methods 0.000 description 15
- 238000010586 diagram Methods 0.000 description 11
- 238000012795 verification Methods 0.000 description 3
- 241000525154 Micrathena beta Species 0.000 description 2
- 230000008901 benefit Effects 0.000 description 2
- 238000005265 energy consumption Methods 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000015572 biosynthetic process Effects 0.000 description 1
- 230000002860 competitive effect Effects 0.000 description 1
- 238000001816 cooling Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000009826 distribution Methods 0.000 description 1
- 238000009434 installation Methods 0.000 description 1
- 230000010354 integration Effects 0.000 description 1
- 238000012417 linear regression Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000009428 plumbing Methods 0.000 description 1
- 229920002635 polyurethane Polymers 0.000 description 1
- 239000004814 polyurethane Substances 0.000 description 1
- 238000004321 preservation Methods 0.000 description 1
- 238000011084 recovery Methods 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
- 238000003786 synthesis reaction Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0201—Market modelling; Market analysis; Collecting market data
- G06Q30/0206—Price or cost determination based on market factors
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/06—Energy or water supply
Landscapes
- Business, Economics & Management (AREA)
- Engineering & Computer Science (AREA)
- Strategic Management (AREA)
- Economics (AREA)
- Development Economics (AREA)
- Physics & Mathematics (AREA)
- Accounting & Taxation (AREA)
- Entrepreneurship & Innovation (AREA)
- Marketing (AREA)
- Finance (AREA)
- Human Resources & Organizations (AREA)
- General Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Tourism & Hospitality (AREA)
- Game Theory and Decision Science (AREA)
- Health & Medical Sciences (AREA)
- Quality & Reliability (AREA)
- Water Supply & Treatment (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Public Health (AREA)
- Data Mining & Analysis (AREA)
- Operations Research (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses a hierarchical optimization method for pipe diameters of a regional heat supply pipe network layout of an intelligent comprehensive energy system, which comprises the following steps of S1, primarily optimizing the pipe diameters; step S2, optimizing the layout of the heat supply pipe network; calculating the lowest pipe network cost by adopting a minimum tree generation method and a preliminarily optimized pipe diameter; thereby determining the optimal heat supply network trend scheme; step S3, finely optimizing the pipe diameter again, including establishing a pipe network economic evaluation objective function; establishing a pipe network economic evaluation objective function related to pipe diameter; and adopting an integer self-adaptive genetic algorithm to carry out minimum value solution on the evaluation target function to obtain the optimal pipe diameter. The invention uses the preliminarily optimized pipe diameter to optimize the layout of the heat supply pipe network. And then, the optimal heat supply network trend scheme which reaches the optimal layout is subjected to fine optimization of the pipe diameter again by adopting an integer genetic algorithm, so that the optimal pipe diameter combination and the minimum annual conversion cost under the optimal heat supply network trend scheme can be obtained, and the sum of the investment and the operation cost of a pipe network is minimized.
Description
Technical Field
The invention relates to a regional heat supply network system, in particular to a method for optimizing the layout and pipe diameter of a regional heat supply pipe network of an intelligent comprehensive energy system in a layered mode.
Background
The problem of optimizing the layout of the regional heat supply network means that after the positions of an energy center station and a heat station are determined, the connection of pipelines between the energy center station and the heat station has multiple schemes, and an optimal pipe network layout scheme is found from multiple pipe network connection layout schemes, so that the optimized pipe network has the optimal performance on one or more performance indexes such as economy, energy consumption or energy supply stability.
The layout optimization of the regional cooling and heating pipe network is used as the basis of the pipe network pipe diameter optimization design and is also the basis of the pipe network operation optimization design. Only on the premise of a reasonable and optimal pipe network layout, the result of pipe network pipe diameter optimization design can ensure that the whole pipe network system is globally optimal, so that the pipe network layout optimization is particularly important in the optimization design of the whole pipe network system.
The regional heat supply network layout principle is determined by technical and economic analysis according to various factors such as heat load distribution, heat source positions, relationships with various aboveground and underground pipelines and structures, hydrological conditions, geological conditions and the like under the guidance of urban construction planning.
The determination of the layout of the lines of the district heating network should obey the following basic principles:
1. is economically reasonable: the trunk lines are required to be short and straight, and the trunk lines are arranged in a heat load concentration area as far as possible. It is to be noted that the valves, compensators and certain plumbing fixtures (e.g., air release, water release, drain, etc.) in the lines are properly positioned, as this will involve the location and number of examination rooms or operating platforms, which should be minimized as much as possible.
2. Technically reliable: the pipeline should avoid the unfavorable areas of soft soil, earthquake fracture zone, landslide danger zone, high underground water level and the like as much as possible. The pipeline should pass through less main traffic lines. Generally parallel to the center line of the roadway and should be laid as far as possible outside the roadway. Typically the pipeline should run along only one side of the street. The pipeline laid on the ground does not influence the beautiful city environment and does not hinder traffic. The heat supply pipeline, various pipelines and buildings are arranged in a coordinated way, and the distance between the heat supply pipeline and the pipelines and the buildings can ensure the safe operation and the convenient construction and maintenance.
The problem of optimizing the pipe diameter of the pipe network of the regional heat supply network system is that after the pipe network layout of the regional heat supply network system is determined, the pipe diameters of all the pipe sections have schemes with various pipe diameter specifications, and an optimal pipe diameter combination scheme is searched in the schemes with various pipe diameter specifications, so that the optimized pipe network has optimal performance on one or more performance indexes such as economy, energy consumption or energy supply stability.
The optimization of pipe diameter is the core in the optimization design of a pipe network system. The economic evaluation of the pipe network mainly comprises the integration of two aspects of investment cost and operation cost, and the investment cost and the operation cost for the construction of the pipe network are two mutually restricted indexes. The smaller the pipe diameter of the pipe network is, the smaller the construction investment cost is, but the larger the pipe network conveying resistance is, the larger the electric power operation cost consumed by the circulating water pump is; on the contrary, the larger the pipe diameter is, the more the investment is, and the less the electric power operation cost is. Therefore, the pipe network pipe diameter optimization design should comprehensively consider the influence of two aspects of investment and operation cost, and select a group of pipe diameters to comprehensively minimize the construction investment cost and the operation cost of the pipe network, so that the pipe network has the best economy. Therefore, under the condition of a certain layout of the pipe network, the optimal pipe diameter of each section, namely the optimal economic pipe diameter, is designed, so that the sum of the investment and the operating cost of the pipe network is minimized.
Disclosure of Invention
The technical problem to be solved by the invention is to provide a method for optimizing the layout pipe diameter of the regional heat supply pipe network of the intelligent integrated energy system in a layering manner aiming at the defects of the prior art. Then, an integer genetic algorithm is adopted, the annual reduced cost of the pipe network is used as a pipe diameter optimization objective function, pipe diameter optimization is carried out on the optimal layout obtained by optimizing the pipe network layout, and the optimal pipe diameter combination and the minimum annual reduced cost under the layout are obtained.
In order to solve the technical problems, the invention adopts the technical scheme that:
a layout and pipe diameter layered optimization method for a regional heat supply pipe network of an intelligent comprehensive energy system comprises the following steps.
Step S1, the pipe diameter is optimized initially: performing initial optimization calculation on the inner diameter of each section of pipe section in the heat supply pipe network according to the following formula:
in the formula (d)jThe inner diameter of the j section of the pipe section in a certain heat supply network trend scheme is in the unit of m.
Δ1The absolute roughness of the inner wall of the pipe section is constant. C is the specific heat of water.
ρ1As water density, is a function of the temperature t of the water, in a hot water network,
R1for designed hot water network specific friction resistance, unit is pa/m。QjThe heat load of the j-th section is in MW.
tngThe temperature of water supplied to the designed hot water network is measured in degrees centigrade. t is tnhThe return water temperature of the designed hot water network is measured in degrees centigrade.
Step S2, the heat supply pipe network optimizing layout includes the following steps:
step S21, laying nodes: the method comprises the following steps of distributing g nodes in a heat supply pipe network, wherein the nodes comprise heating power stations and heat users, and each section area is provided with at least one heat user node.
Step S22, collecting the heat supply network trend scheme: and (3) taking the current position of the heat station as an initial node and taking the full coverage of each block as a principle, and finding out all possible d heat network trend schemes, wherein d is more than 5.
Step S23, the number of pipe sections is distributed: assume that the total number of nodes included in each heat network trend scenario in step S22 is m, where m is ≦ g. The number of the pipe sections required to be laid in each heat supply network trend scheme is n, and n is m-1.
Step S24, calculating the inner diameter of the pipe section: for each pipe section laid in each heat network routing scheme in the step S23, calculating the inner diameter of the pipe section according to the step S1:
step S25, calculating the lowest pipe network cost minS, wherein the calculation method comprises the following steps:
f(dj)＝a+b·dj
in the formula, S is the total cost of the pipe network of a certain heat supply network trend scheme, and the unit is ten thousand yuan. ljThe length of the j section of the heat supply network trend scheme is measured in meters. f (d)j) The unit length of the jth pipe section is the cost, and the unit is ten thousand yuan/meter. Wherein a and b are regression coefficients.
Minimum pipe network costDuring solution, a connected graph is constructed for each heat supply network trend scheme, wherein m nodes serve as m connected components, and f (d) is usedj) And ljThe product of the two is used as the weight edge to be selected in the connected graph. And obtaining the edge with the minimum weight matched with the connected component by adopting a minimum tree generation method until the selection of the m-1 edges with the minimum weight is completed.
Step S26, the preferred heat net trend scenario determination: and for the d types of heat supply network trend schemes collected in the step S22, calculating the lowest pipe network cost of each type of heat supply network trend scheme according to the step S25, and selecting the first five types of heat supply network trend schemes with the lowest total price from the calculated d types of lowest pipe network costs as the optimal heat supply network trend scheme.
Step S27, determining the optimal heat supply network trend scheme: and (3) replacing the positions of the heat station once or twice, repeating the steps from S22 to S26 to obtain 10 or 15 kinds of optimized heat supply network trend schemes, and selecting one heat supply network trend scheme from the 10 or 15 kinds of optimized heat supply network trend schemes as the optimal heat supply network trend scheme from the aspects of total manufacturing cost and difficulty and easiness in pipe network layout.
Step S3, the pipe diameter is refined again, and the method specifically comprises the following steps:
step S31, establishing a pipe network economic evaluation objective function: aiming at the optimal heat supply network trend scheme determined in the step S27, a method with minimum annual conversion cost of the pipe network is adopted to evaluate the economical efficiency of the pipe network, and an objective function shown as follows is established:
Mincost＝XtCtz+Cr+C△Q+Cα
wherein, Cα＝αCtz
Then: cost ═ Xt+α)Ctz+Cr+C△Q
In the formula: mincost-the annual conversion minimum cost function of the pipe network. cost-annual conversion of the pipe network into total cost. Xt-standard investment effect factor. CtzThe total investment and construction cost of the pipe network system. CrThe annual power cost of the pipe network system, namely the annual running electricity cost of the circulating water pump. CΔQ-annual heat loss cost of pipe network system. CαThe annual depreciation and annual maintenance cost of the pipe network system, and alpha is the depreciation rate.
Step S32, total investment and construction cost C of pipe network systemtzAnd calculating according to the following formula:
in the formula: f (d)i) The same as f (d) in step S25j) Only the interchange of i and j needs to be done.
Step S33, annual running electric charge C of water pumprAnd calculating according to the following formula:
in the formula:
Rithe specific friction resistance of the ith section of pipe section is equal to the pipe diameter d of the ith section of pipe sectioniAs a function of the inverse ratio. li-length of section i, m. ldli-local resistance equivalent length of section i. Eta-efficiency of circulating water pump.
Hgt-number of heating hours throughout the year. Pd-industrial electricity prices.
Step S34, annual heat loss cost C of pipe network system△QThe calculation formula is as follows:
ΔQi＝ΔQig+ΔQih
in the formula: c△Q-heat loss conversion cost of water pipelineTen thousand yuan per year. COP is the energy efficiency ratio of the cold and heat source unit in the energy station during heating. Delta Qig、ΔQihAnd heat loss of a water supply pipeline and a water return pipeline in the ith section of the pipe section is W. t is tg、thThe temperature of the heating medium of the water supply pipeline and the water return pipeline is lower than the temperature of the heating medium of the water supply pipeline and the water return pipeline. t is tdb-temperature of soil at pipeline centerline position, deg.C. li-the length of the section i is m. Beta is an accessory heat loss additional coefficient, and the underground laying is 0.15-0.2. Ribg、RibhThermal insulation layer thermal resistance (m DEG C)/W of water supply pipeline and water return pipeline in the ith section of pipe is related to pipe diameter d of the ith section of pipeiAs a function of (c). RitThe thermal resistance of the soil in the ith section of pipe (m DEG C)/W is related to the pipe diameter d of the ith section of pipeiAs a function of (c). RcThe additional thermal resistance (m DEG C)/W caused by mutual heat transfer influence during the direct burying of the double pipes.
Step S35, establishing a pipe network economic evaluation objective function Y (d) related to pipe diameteri): c in step S32tzCr in step S33, and C in step S34△QSubstituting the obtained value into the annual reduced lowest cost function Y of the pipe network established in the step S31 to obtain Y and the pipe diameter diThe functional correspondence of (a) is obtained, i.e. Y (d) is obtainedi)。
Step S36, optimizing the pipe diameter DsSolving: evaluating the objective function Y (d) of step S35 by using an integer adaptive genetic algorithmi) Carrying out minimum value solving, when the corresponding Y value is minimum, the corresponding group of pipe diameter values containing n sections of pipe network pipe sections is the solved optimal pipe diameter Ds。
In step S36, an integer self-adaptive genetic algorithm is adopted to solve the optimal pipe diameter DsThe method comprises the following steps:
step S361, determining a pipe diameter decision dependent variable d: evaluating an objective function Y (d) of the pipe network economy of the pipe diameter established in the step S35i) Has a pipe diameter decision variable D, and D ═ D1，d2，...，di，...，dn). Thus the pipe diameter decision variable D has n pipe diameter decision dependent variables D, each D having a value of 13 specification models, fromThe small to large orders are DN200, DN300, DN350, DN400, DN450, DN500, DN600, DN700, DN800, DN900, DN1000 and DN1200 in sequence.
Step S362, rounding the pipe diameter decision dependent variable d: DN200, DN300, DN350, DN400, DN450, DN500, DN600, DN700, DN800, DN900, DN1000, DN1200 are replaced with integer codes 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, respectively. Therefore, the value range of each pipe diameter decision dependent variable d is [1, 13 ].
Step S363, determining the initial population, including the following step S3:
step S363a) integer code assignment: and (5) carrying out integer coding assignment according to the step S362 on the inner diameter values of the n sections of pipe sections in the optimal layout obtained by optimizing the pipe network layout.
Step S363b) setting the pipe diameter up-down adjustment range: giving a pipe diameter up-and-down adjustment range, so that each pipe diameter decision dependent variable d subjected to integer coding assignment in the step S363a) can float up and down in the pipe diameter up-and-down adjustment range.
Step S363c) forming an initial population: substituting the integer code assigned in the step S363a) and the integer code floating up and down in the step S363b) into the pipe network economic evaluation target function Y (d) related to the pipe diameter established in the step S35i) In (3), an initial population is formed.
Step S364, optimizing the pipe diameter DsSolving: performing integer heredity, crossing, variation and selection or combination operation on the initial population in the step S363 by adopting an integer self-adaptive genetic algorithm, and when the corresponding Y value is minimum, the pipe diameter value of a group of corresponding pipe network pipe sections containing n sections is the solved optimal pipe diameter Ds。
In step S364, when the integer adaptive genetic algorithm is adopted for solving, the crossing rate pcAnd the rate of variation pmThe self-adaptive adjustment is carried out according to the following formula:
in the formula: f. ofmax-the maximum fitness value in the population.
-mean fitness value for each generation population.
f*The greater fitness value in the two individuals that crossed.
f-fitness value of the individual undergoing the mutation. k is a radical of1，k2，k3，k4-each taking the undetermined value of the interval (0, 1).
In step S364, when the integer adaptive genetic algorithm is used for solving, it is ensured that the good individuals of each generation are not destroyed by using the elite selection policy, so that they are directly copied to the next generation, and thus the crossover rate p is obtainedcAnd the rate of variation pmThe following formula is used for calculation:
wherein, take pc1＝0.9、pm1＝0.1。
In step S34, heat insulation layer thermal resistance R of water supply pipeline and water return pipelineibg、RibhThe following formula is adopted for calculation:
wherein d isiw＝di+2dim
diz＝di+2dim+2dis
In the formula: lambda is the thermal conductivity of the thermal insulation material, (m DEG C)/W. dizThe diameter of the outer surface of the heat-insulating layer of the i-th section of pipe section, m。
diw-the diameter of the outer surface of the i-th section of pipe, m. dim-wall thickness, m, of the ith tube section.
dis-the thickness of the insulating layer of the section i, m.
In step S34, soil thermal resistance RitThe calculation formula of (a) is as follows:
in the formula: lambda [ alpha ]tThe soil thermal conductivity coefficient (m DEG C)/W is 1.2-2.5. H is the reduced burial depth of the pipeline, m.
In step S34, the calculation formula of the reduced burial depth H of the pipeline is as follows:
in the formula: h-the buried depth from the ground surface to the center of the pipeline, m. Alpha is alphakThe surface heat release coefficient of the earth surface soil, (m DEG C)/W.
In step S34, add thermal resistance RcThe calculation formula of (a) is as follows:
in the formula: b-the distance between the central lines of the two pipes when the double pipes are directly buried, m.
In step S33, the specific friction resistance R of the ith segmentiThe calculation formula of (a) is as follows:
in the formula:
Gi-water flow in section i.
KiAbsolute roughness of the inner wall of the i-th section of pipe.
ρ -density of water.
di-pipe diameter of section i, m.
The invention has the following beneficial effects:
1. and (4) carrying out optimized layout of the heat supply pipe network by using the preliminarily optimized pipe diameter.
2. When the heat supply pipe network is optimally distributed, according to a mathematical programming theory, the optimal configuration of the regional heat supply system pipe network (the optimal configuration of the pipe network and the stations which are coordinated with the overall park planning) which is coordinated with the overall park planning is researched by taking the optimal economic benefit as a target, so that the purposes of saving investment and operating cost are achieved.
3. And adopting an integer genetic algorithm to perform the fine optimization of the pipe diameter again on the optimal heat supply network trend scheme which reaches the optimal layout, thereby obtaining the optimal pipe diameter combination and the minimum annual conversion cost under the optimal heat supply network trend scheme, namely minimizing the sum of the investment and the operating cost of a pipe network.
4. The economic performance of the district heating system is improved, and a theoretical basis is provided for accelerating the application and development of the district heating system.
Drawings
FIG. 1 shows a schematic view of a heat source point placed in the middle of an exemplary zone.
FIG. 2 shows a schematic diagram of possible connections of heating pipelines with heat source points arranged in the north of an exemplary area.
Fig. 3 shows a schematic diagram of a first preferred heat grid orientation when the heat source points are located north of the exemplary zone.
Fig. 4 shows a schematic diagram of a second preferred heat grid orientation when the heat source points are located north of the exemplary zone.
Fig. 5 shows a schematic diagram of a third preferred heat network orientation when the heat source points are located north of the exemplary zone.
Fig. 6 shows a schematic diagram of a fourth preferred heat network orientation when the heat source points are located north of the exemplary zone.
Fig. 7 shows a schematic diagram of a fifth preferred heat grid orientation when the heat source points are located north of the exemplary zone.
Figure 8 shows a schematic view of possible connections of the heating pipeline when the heat source point is arranged in the middle of the demonstration area.
Figure 9 shows a schematic view of a first preferred heat grid orientation when the heat source points are placed in the middle of an exemplary zone.
Figure 10 shows a schematic diagram of a second preferred heat grid orientation scheme with heat source points placed in the middle of the exemplary zones.
Fig. 11 shows a schematic view of a third preferred heat network orientation when the heat source points are placed in the middle of the exemplary zones.
Fig. 12 shows a schematic representation of a fourth preferred heat network orientation when the heat source points are placed in the middle of the exemplary zones.
Figure 13 shows a schematic diagram of a fifth preferred heat grid orientation with heat source points placed in the middle of the exemplary zones.
FIG. 14 is a graph showing the cost of the piping in the example.
FIG. 15 is a schematic view showing the optimal tube diameter when the heat source points are arranged in the north of the demonstration area.
FIG. 16 shows a table of annual converted cost data when heat source points are located north of an exemplary area.
FIG. 17 shows a schematic view of the optimal tube diameter when the heat source point is placed in the middle of the demonstration zone.
Fig. 18 shows a table of annual converted charge data when heat source points are arranged in the middle of the demonstration area.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and specific preferred embodiments.
In the description of the present invention, it is to be understood that the terms "left side", "right side", "upper part", "lower part", etc., indicate orientations or positional relationships based on those shown in the drawings, and are only for convenience of describing the present invention and simplifying the description, but do not indicate or imply that the referred device or element must have a specific orientation, be constructed in a specific orientation, and be operated, and that "first", "second", etc., do not represent an important degree of the component parts, and thus are not to be construed as limiting the present invention. The specific dimensions used in the present example are only for illustrating the technical solution and do not limit the scope of protection of the present invention.
A layout and pipe diameter layered optimization method for a regional heat supply pipe network of an intelligent comprehensive energy system comprises the following steps.
Step S1, the pipe diameter is optimized initially: performing initial optimization calculation on the inner diameter of each section of pipe section in the heat supply pipe network according to the following formula:
in the formula (d)jThe inner diameter of the j section of a certain heat supply network trend scheme is in unit of m; greater than DN50 and less than DN1400 are required. Delta1Is the absolute roughness of the inner wall of the pipe section, and is constant, preferably delta1＝5×10-4。ρ1As water density, is a function of the temperature t of the water, in a hot water network,
R1for designed hot water network specific friction resistance, unit is pa/m；R1Requires less than 120pa/m。 QjThe heat load of the j-th section is in MW. C is the specific heat of water. t is tngThe temperature of water supplied to the designed hot water network is measured in degrees centigrade. t is tnhThe return water temperature of the designed hot water network is measured in degrees centigrade.
Heat load Q of j-th pipe sectionjThe calculation method comprises the following steps:
step S11, calculating the designed water flow, wherein the calculation formula is as follows:
Q1j＝C·Gj·(tng-tnh)·10-6
in the formula, Q1jThe design heat load for the j-th section is in MW. GjAnd designing water flow for the j section. GjDuring design, it is ensured that the maximum flow velocity in the pipe section does not exceed 3.5 m/s.
Step S12, design water flow verification: the design water flow for all sections in a certain heat network run is calculated according to step 41. And substituting the calculated design water flow of all the pipe sections into the node flowIn the equation of quantity balance, verification is performed. When the verification is qualified, the heat load Q of the j section of the pipe section isjEqual to the design heat load Q of the j-th section of pipe1j. Otherwise, the water flow of each pipe section needs to be adjusted according to the node flow balance equation so as to meet the node flow balance equation. At this time, the j-th section of the pipe section is subjected to a heat load QjAnd calculating according to the adjusted water flow of the j section of pipe.
Step S2, the heat supply pipe network optimizing layout includes the following steps:
and step S21, laying nodes.
The hot water pipe network comprises c sections, g nodes are distributed in the hot water pipe network, one node represents a heating power station, and the position can be adjusted. g-1 nodes represent hot users and are positioned in c areas, c is less than or equal to g-1, and each area is provided with at least one hot user node. In the embodiment, a primary section is set according to the division of the exemplary function section, a secondary section is set in the primary section according to the section area, and 1-2 nodes are respectively set in each secondary section according to the garden planning.
In this embodiment, the primary zone includes an a zone (industrial zone 1), a B zone (commercial zone), a C zone (residential zone), a D zone (industrial zone 2), and an E zone (industrial zone 3), that is, C is 5.
1 node is respectively arranged in the A area, the B area and the C area, 2 secondary areas D1-1, D1-2, E1-1 and E1-2 are respectively arranged in the D area and the E area, 1 node is respectively arranged in each secondary area, and 9 hot users are in total.
Building areas of D1-1 and D1-2 are 43000 square meters, heat supply areas are 38700 square meters, and the heat supply areas are 1800 square meters for office work, 36000 square meters for factory buildings and 900 square meters for machine rooms respectively; the building areas of E1-1 and E1-2 are 73000 square meters and 63000 square meters respectively, the heating areas are 65700 square meters and 56700 respectively, and the heating areas are 1800 square meters for office work, 63000 square meters for plant, 900 square meters for machine room and 1800 square meters for office work, 54000 square meters for plant and 900 square meters for machine room respectively. The total load of each secondary area 1-24 can be calculated through load calculation.
The maximum load per hour of each district is taken as the design load of the optimization design of the pipe network, as shown in table 1.
TABLE 1 design loads of nodes
The heating power station, also called heat source point, can be adjusted in position. In this embodiment, the heat source points have two layout schemes. The first scheme arranges the heat source points north of the demonstration area; the second solution places the heat source point in the middle of the demonstration zone. Step S22, collecting the heat supply network trend scheme: and (3) taking the current position of the heating power station as an initial node, and finding out all possible d types of heat supply network trend schemes with d being more than 5 on the principle of fully covering the c sections.
First, the heat source is in the north
The heat supply pipe network is primarily connected with the graph, and the total number of the nodes is 10, namely g is 10. Wherein, the node 1 is a heat source point, and the nodes 2 to 10 are heat users. In 10 nodes, there are 17 possible pipe segment connections, and the information of pipe lengths of 1-17 pipe segments is shown in table 2.
TABLE 2 preliminary connection and pipe length information for heat source points in the north pipe section
| Serial number | Pipe segment numbering | Pipe section initial joint | Pipe section end node | Pipe length (m) |
| 1 | 1 | 1 | 2 | 585 |
| 2 | 2 | 2 | 5 | 1274 |
| 3 | 3 | 1 | 3 | 793 |
| 4 | 4 | 1 | 4 | 1118 |
| 5 | 5 | 1 | 5 | 1495 |
| 6 | 6 | 3 | 4 | 572 |
| 7 | 6 | 4 | 3 | 572 |
| 8 | 7 | 4 | 5 | 1547 |
| 9 | 8 | 5 | 6 | 871 |
| 10 | 8 | 6 | 5 | 871 |
| 11 | 9 | 2 | 4 | 845 |
| 12 | 9 | 4 | 2 | 845 |
| 13 | 10 | 2 | 6 | 2106 |
| 14 | 11 | 5 | 7 | 286 |
| 15 | 12 | 5 | 8 | 299 |
| 16 | 13 | 7 | 8 | 325 |
| 17 | 13 | 8 | 7 | 325 |
| 18 | 14 | 8 | 9 | 403 |
| 19 | 14 | 9 | 8 | 403 |
| 20 | 15 | 6 | 9 | 364 |
| 21 | 16 | 6 | 10 | 405 |
| 22 | 17 | 9 | 10 | 390 |
| 23 | 17 | 10 | 9 | 390 |
In the 17 possible pipe section connections, not less than 10 heat supply network trend schemes are formed, namely d is more than or equal to 10, and each heat supply network trend scheme takes the current position of a heat source point (node 1) as a starting node and takes the principle of fully covering five primary slice areas as a principle.
Second, the heat source point is in the middle
The preliminary connection diagram of the heating network is shown in fig. 8, namely g ═ 10. Wherein, the node 1 is a heat source point, and the nodes 2 to 10 are heat users. In 10 nodes, there are 16 possible pipe segment connections, and the information of pipe lengths of 1-16 pipe segments is shown in table 3.
In 16 possible pipe section connections, not less than 10 heat supply network trend schemes are formed, namely d is more than or equal to 10, each heat supply network trend scheme takes the current position of a heat source point (node 1) as a starting node, and the principle of fully covering five primary slice areas is taken.
TABLE 3 connection of heat source points at intermediate pipe sections and pipe lengths
| Serial number | Pipe segment numbering | Pipe section initial joint | Pipe section end node | Pipe length (m) |
| 1 | 1 | 1 | 2 | 1430 |
| 2 | 2 | 2 | 4 | 845 |
| 3 | 2 | 4 | 2 | 845 |
| 4 | 3 | 2 | 3 | 1079 |
| 5 | 3 | 3 | 2 | 1079 |
| 6 | 4 | 1 | 4 | 793 |
| 7 | 5 | 1 | 5 | 676 |
| 8 | 6 | 2 | 5 | 1274 |
| 9 | 6 | 5 | 2 | 1274 |
| 10 | 7 | 3 | 4 | 572 |
| 11 | 7 | 4 | 3 | 572 |
| 12 | 8 | 5 | 6 | 871 |
| 13 | 9 | 5 | 7 | 286 |
| 14 | 10 | 5 | 8 | 299 |
| 15 | 11 | 7 | 8 | 325 |
| 16 | 11 | 8 | 7 | 325 |
| 17 | 12 | 8 | 9 | 403 |
| 18 | 12 | 9 | 8 | 403 |
| 19 | 13 | 6 | 9 | 364 |
| 20 | 14 | 6 | 10 | 405 |
| 21 | 15 | 9 | 10 | 390 |
| 22 | 15 | 10 | 9 | 390 |
| 23 | 16 | 1 | 7 | 468 |
And step S23, laying out the number of pipe sections.
Assume that the total number of nodes included in each heat network trend scenario in step S22 is m, where m is ≦ g. The number of the pipe sections required to be laid in each heat supply network trend scheme is n, and n is m-1.
And step S24, calculating the inner diameter of the pipe section. And calculating the inner diameter of each pipe section laid in each heat network trend scheme in the step S23 according to the formula in the step S1.
Step S25, calculating the lowest pipe network cost minS, wherein the calculation method comprises the following steps:
f(dj)＝a+b·dj
in the formula, S is the total cost of the pipe network of a certain heat supply network trend scheme, and the unit is ten thousand yuan. ljThe length of the j section of the heat supply network trend scheme is measured in meters. f (d)j) The unit length of the jth pipe section is the cost, and the unit is ten thousand yuan/meter. Wherein a and b are regression coefficients. The concrete solving method of the regression coefficients a and b is as follows.
The investment of the pipe network can be written into a function of the pipe diameter of each pipe section, all investments of the pipe network construction are included, such as the cost of pipes, pipeline accessories, the thickness of a heat preservation layer and construction, and the form of the investment can adopt corresponding regression model fitting according to the comprehensive cost of the pipe network.
The investment of the pipe network can be calculated according to the municipal engineering investment estimation index, and the comprehensive cost of the thermal pipelines with different pipe diameters and different laying modes in unit length is calculated. The directly-buried thermal pipeline is widely applied in recent years due to the advantages of low cost, short construction period, small occupied area and the like. The cost per unit length of the direct-buried installation, the polyurethane insulation, the bellows compensator, and the hot water pipe having a nominal diameter from DN50 to DN1000, which are obtained from the estimation index, are shown in table 4.
TABLE 4 cost per unit length of directly buried pipeline
| Nominal pipe diameter (mm) | Cost (Yuan/m) | Nominal pipe diameter (mm) | Cost (Yuan/m) |
| 50 | 325.09 | 350 | 1710.00 |
| 65 | 392.84 | 400 | 1954.04 |
| 80 | 450.61 | 450 | 2125.09 |
| 100 | 545.61 | 500 | 2412.15 |
| 125 | 651.63 | 600 | 2900.26 |
| 150 | 748.17 | 700 | 3363.02 |
| 200 | 1002.98 | 800 | 3838.97 |
| 250 | 1262.01 | 900 | 4330.89 |
| 300 | 1480.97 | 1000 | 5369.61 |
The results of table 4 are plotted as a pipeline cost curve as shown in fig. 14, and it can be seen from fig. 14 that the investment of the pipeline and the pipe diameter are approximately in a linear relationship, and the regression can be performed according to a linear regression model-least square method, and the regression formula is:
f(dj)＝a+b·dj
wherein:
fitting the data in table 4 yields the following regression equation:
f(dj)＝9.4868+4.942·dj
the concrete solving method of the lowest pipe network cost is as follows:
when solving the lowest pipe network cost, firstly constructing a communication graph for each heat supply network trend scheme, wherein m nodes are used as m communication components, and f (d) is usedj) And ljThe product of the two is used as the weight edge to be selected in the connected graph. And obtaining the edge with the minimum weight matched with the connected component by adopting a minimum tree generation method until the selection of the m-1 edges with the minimum weight is completed.
At step S26, a preferred heat net walk scenario determination is made.
And for the d types of heat supply network trend schemes collected in the step S22, calculating the lowest pipe network cost of each type of heat supply network trend scheme according to the step S25, and selecting the first five types of heat supply network trend schemes with the lowest total price from the calculated d types of lowest pipe network costs as the optimal heat supply network trend scheme.
First, the heat source is in the north
After the layout optimization calculation according to step S25, the first 5 preferred heat network trend schemes with the lowest total cost of the pipeline (the lowest total cost is the best) are listed, as shown in table 5, the network connection diagrams of each layout scheme are respectively shown in fig. 3 to fig. 7.
TABLE 5 comparison of the first 5 placement schemes for heat source points in the North
Second, the heat source point is in the middle
After the layout optimization calculation according to step S25, the first 5 preferred heat network trend schemes with the lowest total cost of the pipeline (the lowest total cost is the best) are listed, as shown in table 6, the network connection diagrams of each layout scheme are respectively shown in fig. 9 to fig. 13.
TABLE 6 comparison of the top 5 placement schemes with heat source points in the middle
Step S27, optimal heat supply network trend scheme determination
And (4) once or twice replacing the heat station positions, and repeating the steps from S22 to S26 to obtain 10 or 15 preferred heat network trend schemes. In this embodiment, the heat station (heat source point) is initially located north of the demonstration area, and then replaced in the middle of the demonstration area, or located elsewhere, specifically according to the geographical environment and the need.
From the view points of total manufacturing cost and difficulty and easiness in arrangement of pipe networks, one heat supply network trend scheme is selected from 10 or 15 optimal heat supply network trend schemes to serve as an optimal heat supply network trend scheme.
In this embodiment, the heat source points are arranged in the north of the demonstration area and in the middle of the demonstration area, the geographic environment is not affected, and all the 10 optimal heat supply network trend schemes calculated by the minimum tree method are feasible. Therefore, the total cost is considered to be the lowest, and in the 10 preferred heat supply network trend schemes, the first scheme with the heat source point in the middle has the lowest total cost, so that the scheme is selected as the optimal heat supply network trend scheme. If the heat source point is limited by geographical factors, the first scheme with the heat source point in the north is selected as the optimal heat supply network trend scheme.
And step S3, finely optimizing the pipe diameter again, and specifically comprising the following steps.
Step S31, establishing a pipe network economic evaluation objective function: aiming at the optimal heat supply network trend scheme determined in the step S27, a method with minimum annual conversion cost of the pipe network is adopted to evaluate the economical efficiency of the pipe network, and an objective function shown as follows is established:
Mincost＝XtCtz+Cr+C△Q+Cα
wherein, Cα＝αCtz
Then: cost ═ Xt+α)Ctz+Cr+C△Q
In the formula: mincost-the annual conversion minimum cost function of the pipe network. cost-annual conversion of the pipe network into total cost. Xt-standard investment effect factor. CtzThe total investment and construction cost of the pipe network system. CrThe annual power cost of the pipe network system, namely the annual running electricity cost of the circulating water pump. CΔQ-annual heat loss cost of pipe network system. CαThe annual depreciation and annual maintenance cost of the pipe network system, and alpha is the depreciation rate.
The above-mentioned standard investment effect coefficient XtIt is preferable to have the following two algorithms.
The first algorithm is as follows: the calculation is carried out by a static method, and the calculation formula is preferably as follows:
in the formula: t-investment recovery period.
And (3) algorithm II: the calculation is carried out by adopting a dynamic method, and the calculation formula is preferably as follows:
in the formula: i represents interest rate and m represents the number of calculated interest in the fund occupation period.
Step S32, total investment and construction cost C of pipe network systemtzAnd calculating according to the following formula:
f(di)＝a+b·di
in the formula, f (d)i) The same as f (d) in step S25j) Only i and j need to be performedAnd (4) exchanging.
Step S33, annual running electric charge C of water pumprAnd calculating according to the following formula:
in the formula: riThe specific friction resistance of the ith section of pipe section is equal to the pipe diameter d of the ith section of pipe sectioniAs a function of the inverse ratio. li-length of section i, m. ldli-the local resistance equivalent length of the section i is a known value. Eta-efficiency of circulating water pump. Hgt-number of heating hours throughout the year. Pd-industrial electricity prices. t is tngThe temperature of water supplied to the designed hot water network is measured in degrees centigrade. t is tnhThe return water temperature of the designed hot water network is measured in degrees centigrade.
Specific friction resistance R of the ith section of pipeiThe calculation formula of (c) is preferably as follows:
in the formula: gi-water flow of the ith segment of pipe is calculated in the same manner as G in step S11j。KiAbsolute roughness of the inner wall of the i-th section of pipe. ρ -density of water. di-pipe diameter of section i, m.
Step S34, annual heat loss cost C of pipe network system△QThe calculation formula is as follows:
ΔQi＝ΔQig+ΔQih
in the formula: c△QThe heat loss of the water conveying pipeline is converted into cost which is ten thousand yuan per year. COP is the energy efficiency ratio of the cold and heat source unit in the energy station during heating. Delta Qig、ΔQihAnd heat loss of a water supply pipeline and a water return pipeline in the ith section of the pipe section is W.
tg、thThe temperature of the heating medium of the water supply pipeline and the water return pipeline is lower than the temperature of the heating medium of the water supply pipeline and the water return pipeline. t is tdb-temperature of soil at pipeline centerline position, deg.C.
li-the length of the section i is m. Beta is an accessory heat loss additional coefficient, and the underground laying is 0.15-0.2.
Ribg、RibhThermal insulation layer thermal resistance (m DEG C)/W of water supply pipeline and water return pipeline in the ith section of pipe is related to pipe diameter d of the ith section of pipeiAs a function of (c). RitThe thermal resistance of the soil in the ith section of pipe (m DEG C)/W is related to the pipe diameter d of the ith section of pipeiAs a function of (c).
RcThe additional thermal resistance (m DEG C)/W caused by mutual heat transfer influence during the direct burying of the double pipes.
Thermal resistance R of heat-insulating layers of the water supply pipeline and the water return pipelineibg、RibhAre preferably calculated using the following formula:
wherein d isiw＝di+2dim
diz＝di+2dim+2dis
In the formula: lambda is the thermal conductivity of the thermal insulation material, (m DEG C)/W. dizThe diameter m of the outer surface of the insulating layer of the ith section of pipe section. diw-the diameter of the outer surface of the i-th section of pipe, m. dim-wall thickness, m, of the ith tube section.
dis-the thickness of the insulating layer of the section i, m.
When calculating the thermal resistances of the heat-insulating layers of the water supply pipeline and the water return pipeline, only the thickness of the heat-insulating layer in the corresponding pipeline is needed, if the thicknesses of the two heat-insulating layers are the same, the thermal resistances of the heat-insulating layers of the water supply pipeline and the water return pipeline are the same, otherwise, the thermal resistances are different.
The soil thermal resistance RitThe calculation formula of (c) is preferably as follows:
in the formula: lambda [ alpha ]tThe soil thermal conductivity coefficient (m DEG C)/W is 1.2-2.5.
H-the reduced burial depth of the pipeline, m; the remaining parameters are expressed above the same.
The above calculation formula of the reduced burial depth H of the pipeline is preferably as follows:
in the formula: h-the buried depth from the ground surface to the center of the pipeline, m.
αkThe surface heat release coefficient of the earth surface soil, (m DEG C)/W, is 12-15.
The above additional thermal resistance RcThe calculation formula of (a) is as follows:
in the formula: b-the distance between the central lines of the two pipes when the two pipes are directly buried, m; the remaining parameters are expressed above the same.
Step S35, establishing a pipe network economic evaluation objective function Y (d) related to pipe diameteri)。
C in step S32tzCr in step S33, and C in step S34△QSubstituting the obtained value into the annual reduced lowest cost function Y of the pipe network established in the step S31 to obtain Y and the pipe diameter diThe functional correspondence of (a) is obtained, i.e. Y (d) is obtainedi)。
Step S36, optimizing the pipe diameter DsSolving, including the following steps S3:
and step S361, determining a pipe diameter decision dependent variable d.
Evaluating an objective function Y (d) of the pipe network economy of the pipe diameter established in the step S35i) Has a pipe diameter decision variable D, and D ═ D1，d2，...，di...，dn). Therefore, the pipe diameter decision variable D has n pipe diameter decision dependent variables D, each D has values of 13 specification models, and the values are sequentially DN200, DN300, DN350, DN400, DN450, DN500, DN600, DN700, DN800, DN900, DN1000 and DN1200 from small to large.
Step S362, rounding the pipe diameter decision dependent variable d.
DN200, DN300, DN350, DN400, DN450, DN500, DN600, DN700, DN800, DN900, DN1000, DN1200 are replaced with integer codes 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, respectively. Therefore, the value range of each pipe diameter decision dependent variable d is [1, 13 ].
In step S363, the initial population is determined, which includes the following step S3.
Step S363a) integer code assignment: and (5) carrying out integer coding assignment according to the step S362 on the inner diameter values of the n sections of pipe sections in the optimal layout obtained by optimizing the pipe network layout.
Step S363b) setting the pipe diameter up-down adjustment range: giving a pipe diameter up-and-down adjustment range, so that each pipe diameter decision dependent variable d subjected to integer coding assignment in the step S363a) can float up and down in the pipe diameter up-and-down adjustment range.
The given pipe diameter up-down adjustment range is preferably [ -3, 3], and when the integer code is assigned to be 5, the integer code in [2, 8] can be adopted.
Step S363c) forming an initial population: substituting the integer code assigned in the step S363a) and the integer code floating up and down in the step S363b) into the pipe network economic evaluation target function Y (d) related to the pipe diameter established in the step S35i) In (3), an initial population is formed.
Step S364, optimizing the pipe diameter DsSolving: performing integer heredity, crossing, variation and selection or synthesis on the initial population of the step S363 by adopting an integer self-adaptive genetic algorithmAnd operating, when the corresponding Y value is minimum, the corresponding group of pipe diameter values containing n sections of pipe network pipe sections is the solved optimal pipe diameter Ds. Operators are preferably selected by the competitive bidding method, and the genetic algebra is preferably 100.
When the integer self-adaptive genetic algorithm is adopted for solving, the cross rate p iscAnd the rate of variation pmThe adaptive adjustment is preferably performed according to the following formula:
in the formula: f. ofmax-the maximum fitness value in the population.
-mean fitness value for each generation population.
f*The greater fitness value in the two individuals that crossed. f-fitness value of the individual undergoing the mutation.
k1，k2，k3，k4-taking the pending value of the (0, 1) interval.
When the integer self-adaptive genetic algorithm is adopted for solving, the elite selection strategy is adopted to ensure that the excellent individuals of each generation are not damaged and are directly copied into the next generation, so that the crossing rate pcAnd the rate of variation pmThe following formula is used for calculation:
wherein, take pc1＝0.9、pm10.1 is an empirical value.
In this embodiment, the pipe diameter is optimized by using 5 optimal heat network trend schemes with the heat source point in the north and the heat source point in the middle.
1. The heat source point is in the north: the pipe diameter optimization results are shown in fig. 15 and 16.
2. The heat source point is in the middle: the pipe diameter optimization results are shown in fig. 17 and 18.
As can be seen from fig. 16 and 18, the heat source point is in the middle, the total investment in the pipeline is 1253.2 ten thousand yuan and the total annual cost is 221.69 ten thousand yuan, compared with the heat source point in the north, the total investment in the pipeline is 1531.12 ten thousand yuan and the total annual cost is 271.71 ten thousand yuan, the total investment is 277.92 ten thousand yuan, and the annual cost is saved by 50.02 ten thousand yuan.
Although the preferred embodiments of the present invention have been described in detail, the present invention is not limited to the details of the embodiments, and various equivalent modifications can be made within the technical spirit of the present invention, and the scope of the present invention is also within the scope of the present invention.
Claims (9)
1. A layout pipe diameter layered optimization method for a regional heat supply pipe network of an intelligent comprehensive energy system is characterized by comprising the following steps: the method comprises the following steps: step S1, the pipe diameter is optimized initially: performing initial optimization calculation on the inner diameter of each section of pipe section in the heat supply pipe network according to the following formula:
in the formula (d)jThe inner diameter of the j section of a certain heat supply network trend scheme is in unit of m;
Δ1the absolute roughness of the inner wall of the pipe section is constant; c is the specific heat of water;
ρ1as water density, is a function of the temperature t of the water, in a hot water network,
R1for designed hot water network specific friction resistance, unit is pa/m；QjThe heat load of the j section is the unit MW;
tngthe water supply temperature for the designed hot water network is measured in units of; t is tnhThe return water temperature of the designed hot water network is measured in units of;
step S2, the heat supply pipe network optimizing layout includes the following steps:
step S21, laying nodes: g nodes are distributed in a heat supply pipe network, the nodes comprise heat stations and heat users, and each section area is provided with at least one heat user node;
step S22, collecting the heat supply network trend scheme: taking the current position of the heating station as an initial node and taking the full coverage of each block as a principle, finding out all possible d types of heat supply network trend schemes, wherein d is more than 5;
step S23, the number of pipe sections is distributed: assuming that the total number of nodes included in each heat supply network trend scheme in the step S22 is m, wherein m is less than or equal to g; the number of the pipe sections required to be laid in each heat supply network trend scheme is n, and n is m-1;
step S24, calculating the inner diameter of the pipe section: calculating the inner diameter of each pipe section laid in each heat supply network trend scheme in the step S23 according to the step S1;
step S25, calculating the lowest pipe network cost minS, wherein the calculation method comprises the following steps:
f(dj)＝a+b·dj
in the formula, S is the total cost of a pipe network of a certain heat supply network trend scheme, and the unit is ten thousand yuan; ljThe length of the j section of a certain heat supply network trend scheme is in meters; f (d)j) The unit length of the jth pipe section is the cost, and the unit is ten thousand yuan/meter; wherein a and b are regression coefficients;
when solving the lowest pipe network cost, firstly constructing a communication graph for each heat supply network trend scheme, wherein m nodes are used as m communication components, and f (d) is usedj) And ljThe product of the two is used as a weight side to be selected in the connected graph; by using the mostThe treelet generation method obtains the edge with the minimum weight matched with the connected component until the selection of the m-1 edges with the minimum weight is completed;
step S26, the preferred heat net trend scenario determination: for the d types of heat supply network trend schemes collected in the step S22, calculating the lowest pipe network cost of each type of heat supply network trend scheme according to the step S25, and selecting the first five types of heat supply network trend schemes with the lowest total price from the calculated d types of lowest pipe network costs as the optimal heat supply network trend scheme;
step S27, determining the optimal heat supply network trend scheme: changing the positions of the heat station once or twice, repeating the steps from S22 to S26 to obtain 10 or 15 optimal heat supply network trend schemes, and selecting one heat supply network trend scheme from the 10 or 15 optimal heat supply network trend schemes as the optimal heat supply network trend scheme from the viewpoints of total manufacturing cost and difficulty and easiness in pipe network arrangement;
step S3, the pipe diameter is refined again, and the method specifically comprises the following steps:
step S31, establishing a pipe network economic evaluation objective function: aiming at the optimal heat supply network trend scheme determined in the step S27, a method with minimum annual conversion cost of the pipe network is adopted to evaluate the economical efficiency of the pipe network, and an objective function shown as follows is established:
Mincost＝XtCtz+Cr+CΔQ+Cα
wherein, Cα＝αCtz
Then: cost ═ Xt+α)Ctz+Cr+CΔQ
In the formula: mincost-the annual conversion minimum cost function of the pipe network; cost-annual conversion of the total cost of the pipe network; xt-standard investment effect factor; ctz-total investment and construction costs of the pipe network system; crThe annual power cost of the pipe network system; cΔQ-annual heat loss cost of the pipe network system; cαThe annual depreciation and annual maintenance cost of the pipe network system, alpha is the depreciation rate;
step S32, total investment and construction cost C of pipe network systemtzAnd calculating according to the following formula:
in the formula: f (d)i) The same as f (d) in step S25j) Only i and j need to be interchanged;
step S33, annual running electric charge C of water pumprAnd calculating according to the following formula:
in the formula:
Rithe specific friction resistance of the ith section of pipe section is equal to the pipe diameter d of the ith section of pipe sectioniA function that is inversely proportional; li-segment i length, m; ldli-local resistance equivalent length of section i; eta-circulating water pump efficiency;
Hgt-number of heating hours throughout the year; pd-industrial electricity prices;
step S34, annual heat loss cost C of pipe network systemΔQThe calculation formula is as follows:
ΔQi＝ΔQig+ΔQih
in the formula: cΔQThe heat loss of the water conveying pipeline is converted into cost which is ten thousand yuan per year; COP is the energy efficiency ratio of the cold and heat source units in the energy station during heating; delta Qig、ΔQihHeat loss of a water supply pipeline and a water return pipeline in the ith section of the pipe section is W; t is tg、th-a water supply pipe,The temperature of the heating medium of the water return pipeline is lower than the temperature of the heating medium of the water return pipeline; t is tdb-the soil temperature at the pipeline centerline position, deg.c; li-the length of the section i is in m; beta is an accessory heat loss additional coefficient, and the underground laying is 0.15-0.2; ribg、RibhThermal insulation layer thermal resistance (m DEG C)/W of water supply pipeline and water return pipeline in the ith section of pipe is related to pipe diameter d of the ith section of pipeiA function of (a);
Ritthe thermal resistance of the soil in the ith section of pipe (m DEG C)/W is related to the pipe diameter d of the ith section of pipeiA function of (a); rcThe additional thermal resistance (m DEG C)/W caused by mutual heat transfer influence during the double-pipe direct burial laying;
step S35, establishing a pipe network economic evaluation objective function Y (d) related to pipe diameteri): c in step S32tzCr in step S33, and C in step S34ΔQSubstituting the obtained value into the annual reduced lowest cost function Y of the pipe network established in the step S31 to obtain Y and the pipe diameter diThe functional correspondence of (a) is obtained, i.e. Y (d) is obtainedi)；
Step S36, optimizing the pipe diameter DsSolving: evaluating the objective function Y (d) of step S35 by using an integer adaptive genetic algorithmi) Carrying out minimum value solving, when the corresponding Y value is minimum, the corresponding group of pipe diameter values containing n sections of pipe network pipe sections is the solved optimal pipe diameter Ds。
2. The intelligent integrated energy system district heating network layout pipe diameter hierarchical optimization method according to claim 1, characterized in that: in step S36, an integer self-adaptive genetic algorithm is adopted to solve the optimal pipe diameter DsThe method comprises the following steps:
step S361, determining a pipe diameter decision dependent variable d: evaluating an objective function Y (d) of the pipe network economy of the pipe diameter established in the step S35i) Has a pipe diameter decision variable D, and D ═ D1，d2，...，di...，dn) (ii) a Therefore, the pipe diameter decision variable D has n pipe diameter decision dependent variables D, each D has values of 13 specification models, and the values are DN200 and DN300 in sequence from small to big、DN350、DN400、DN450、DN500、DN600、DN700、DN800、DN900、DN1000、DN1200；
Step S362, rounding the pipe diameter decision dependent variable d: substituting DN200, DN300, DN350, DN400, DN450, DN500, DN600, DN700, DN800, DN900, DN1000, DN1200 with integer codes 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13; therefore, the value range of each pipe diameter decision dependent variable d is [1, 13 ];
step S363, determining the initial population, including the following step S3:
step S363a) integer code assignment: referring to the inner diameter values of the n sections of pipe sections in the optimal layout obtained by optimizing the layout of the pipe network
Step S362, integer coding assignment is carried out;
step S363b) setting the pipe diameter up-down adjustment range: giving a pipe diameter up-and-down adjustment range, so that each pipe diameter decision dependent variable d subjected to integer coding assignment in the step S363a) can float up and down in the pipe diameter up-and-down adjustment range;
step S363c) forming an initial population: substituting the integer code assigned in the step S363a) and the integer code floating up and down in the step S363b) into the pipe network economic evaluation target function Y (d) related to the pipe diameter established in the step S35i) Forming an initial population;
step S364, optimizing the pipe diameter DsSolving: performing integer heredity, crossing, variation and selection or combination operation on the initial population in the step S363 by adopting an integer self-adaptive genetic algorithm, and when the corresponding Y value is minimum, the pipe diameter value of a group of corresponding pipe network pipe sections containing n sections is the solved optimal pipe diameter Ds。
3. The intelligent integrated energy system district heating network layout pipe diameter hierarchical optimization method according to claim 2, characterized in that: in step S364, when the integer adaptive genetic algorithm is adopted for solving, the crossing rate pcAnd the rate of variation PmThe self-adaptive adjustment is carried out according to the following formula:
in the formula: f. ofmax-a maximum fitness value in the population;
-mean fitness value for each generation population;
f*-the greater fitness value in the two individuals undergoing intersection;
f-fitness value of the individual undergoing mutation; k is a radical of1、k2、k3、k4-each taking the undetermined value of the interval (0, 1).
4. The intelligent integrated energy system district heating network layout pipe diameter hierarchical optimization method according to claim 3, characterized in that: in step S364, when the integer adaptive genetic algorithm is used for solving, it is ensured that the good individuals of each generation are not destroyed by using the elite selection policy, so that they are directly copied to the next generation, and thus the crossover rate p is obtainedcAnd the rate of variation PmThe following formula is used for calculation:
wherein, take pc1＝0.9、Pm1＝0.1。
5. The intelligent integrated energy system district heating network layout pipe diameter hierarchical optimization method according to claim 1, characterized in that: in step S34, heat insulation layer thermal resistance R of water supply pipeline and water return pipelineibg、RibhThe following formula is adopted for calculation:
wherein d isiw＝di+2dim
diz＝di+2dim+2dis
In the formula: lambda is the thermal conductivity of the thermal insulation material, (m DEG C)/W; dizThe diameter m of the outer surface of the insulating layer of the ith section of the pipe section;
diw-the diameter of the outer surface of the i section of pipe, m; dim-the wall thickness of the section i, m;
dis-the thickness of the insulating layer of the section i, m.
6. The intelligent integrated energy system district heating network layout pipe diameter hierarchical optimization method according to claim 5, characterized in that: in step S34, soil thermal resistance RitThe calculation formula of (a) is as follows:
in the formula: lambda [ alpha ]tThe soil heat conductivity coefficient (m ·) is/W, and 1.2-2.5 is taken; h is the reduced burial depth of the pipeline, m.
7. The intelligent integrated energy system district heating network layout pipe diameter hierarchical optimization method according to claim 6, characterized in that: in step S34, the calculation formula of the reduced burial depth H of the pipeline is as follows:
in the formula: h is the buried depth from the ground surface to the center of the pipeline, m; alpha is alphakThe surface heat release coefficient of the earth surface soil, (m DEG C)/W.
8. The intelligent integrated energy system district heating network layout pipe diameter hierarchical optimization method according to claim 7, characterized in that: in step S34, add thermal resistance RcThe calculation formula of (a) is as follows:
in the formula: b-the distance between the central lines of the two pipes when the double pipes are directly buried, m.
9. The intelligent integrated energy system district heating network layout pipe diameter hierarchical optimization method according to claim 1, characterized in that: in step S33, the specific friction resistance R of the ith segmentiThe calculation formula of (a) is as follows:
in the formula:
Gi-water flow in section i;
Ki-absolute roughness of the inner wall of the i-th section of pipe;
ρ -density of water;
di-pipe diameter of section i, m.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911166478.0A CN110991719B (en) | 2019-11-25 | 2019-11-25 | Method for optimizing layout pipe diameters in layering mode for regional heat supply pipe network of intelligent comprehensive energy system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911166478.0A CN110991719B (en) | 2019-11-25 | 2019-11-25 | Method for optimizing layout pipe diameters in layering mode for regional heat supply pipe network of intelligent comprehensive energy system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110991719A CN110991719A (en) | 2020-04-10 |
| CN110991719B true CN110991719B (en) | 2020-10-27 |
Family
ID=70086621
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201911166478.0A Active CN110991719B (en) | 2019-11-25 | 2019-11-25 | Method for optimizing layout pipe diameters in layering mode for regional heat supply pipe network of intelligent comprehensive energy system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110991719B (en) |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111415272B (en) * | 2020-04-24 | 2020-12-08 | 中国水利水电科学研究院 | Dynamic optimization method for preventive replacement time of water supply pipe network |
| CN112464309B (en) * | 2020-11-24 | 2024-04-30 | 中天众达智慧城市科技有限公司 | Equipment arrangement method for smart city data center |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103761385A (en) * | 2014-01-17 | 2014-04-30 | 河南理工大学 | Optimized design method for mult-heat-source annular pipe network |
| CN103939968A (en) * | 2014-04-15 | 2014-07-23 | 河南理工大学 | Method for arranging circulating water pumps of multi-heat-source looped network heating supply system and adjusting pipe network parameters |
| CN109140234A (en) * | 2018-08-31 | 2019-01-04 | 江汉大学 | A kind of optimization method and device of heating steam pipe network |
| CN110334877A (en) * | 2019-07-10 | 2019-10-15 | 北京石油化工学院 | A method of optimization central heating heat distribution pipeline specific frictional resistance |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106998079B (en) * | 2017-04-28 | 2020-05-05 | 东南大学 | Modeling method of combined heat and power optimization scheduling model |
| CN110110913B (en) * | 2019-04-26 | 2022-06-07 | 国网福建省电力有限公司 | Optimal configuration method for energy station of large-scale park comprehensive energy system |
-
2019
- 2019-11-25 CN CN201911166478.0A patent/CN110991719B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103761385A (en) * | 2014-01-17 | 2014-04-30 | 河南理工大学 | Optimized design method for mult-heat-source annular pipe network |
| CN103939968A (en) * | 2014-04-15 | 2014-07-23 | 河南理工大学 | Method for arranging circulating water pumps of multi-heat-source looped network heating supply system and adjusting pipe network parameters |
| CN109140234A (en) * | 2018-08-31 | 2019-01-04 | 江汉大学 | A kind of optimization method and device of heating steam pipe network |
| CN110334877A (en) * | 2019-07-10 | 2019-10-15 | 北京石油化工学院 | A method of optimization central heating heat distribution pipeline specific frictional resistance |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110991719A (en) | 2020-04-10 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110717226B (en) | Regional comprehensive energy system layout planning method considering topological characteristics of energy network | |
| Chow et al. | Applying district-cooling technology in Hong Kong | |
| CN110991719B (en) | Method for optimizing layout pipe diameters in layering mode for regional heat supply pipe network of intelligent comprehensive energy system | |
| CN114529123A (en) | Urban intelligent energy network hierarchical planning method | |
| CN111046513B (en) | Intelligent comprehensive energy system heating pipe network layout optimization design method | |
| Ding et al. | A graph-theory-based dynamic programming planning method for distributed energy system planning: Campus area as a case study | |
| Xue et al. | Quantitative study on adjacent room heat transfer: Heating load and influencing factors | |
| WO2019059877A1 (en) | Method for comprehensive thermal renovation of buildings or structures | |
| Yassine et al. | Effectiveness of the earth tube heat exchanger system coupled to a space model in achieving thermal comfort in rural areas | |
| Kokogiannakis et al. | Support for the integration of green roof constructions within Chinese building energy performance policies | |
| Chen et al. | Assessments of multiple operation strategies in a passive office Building in Cold Region of China | |
| Battaglia et al. | Dynamic modelling of geothermal heat pump system coupled with positive-energy building | |
| El Kadiri et al. | Thermal performance of a residential building in Ben Guerir city: A comparative evaluation for an optimized thermal load needs | |
| Harter et al. | Life cycle assessment of technical building services of large residential building stocks using semantic 3D city models | |
| CN115234973B (en) | Method for determining dynamic heat supply strategy of heat supply network | |
| CN110968948A (en) | Heat supply pipe network pipe diameter optimization design method in intelligent comprehensive energy system | |
| Huang et al. | Building energy and thermo-hydraulic simulation (BETHS) for district heat system in residential communities: A case of Shenyang, China | |
| CN112561201B (en) | Method for planning and selecting site of district heating station | |
| Feng et al. | Optimal design of pipe network of district cooling system based on genetic algorithm | |
| Şendil | Operation of water distribution networks | |
| Vasilev et al. | Approach development to the pipeline networks design an integrated heat and cold supply system on the example of Yakutsk city | |
| Ruan et al. | Collaborative optimization design for district distributed energy system based on energy station and pipeline network interactions | |
| CN107299783A (en) | Boat changes type distributed busbar protection compartment system | |
| Syranov et al. | Modeling, research and optimization of heat losses during transport in energy systems | |
| Melekhin | Modeling of engineering systems of buildings and structures using BIM technologies |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |