CN110118380B - Equivalent design capacity calculation method for solar heating system - Google Patents

Equivalent design capacity calculation method for solar heating system Download PDF

Info

Publication number
CN110118380B
CN110118380B CN201910302951.7A CN201910302951A CN110118380B CN 110118380 B CN110118380 B CN 110118380B CN 201910302951 A CN201910302951 A CN 201910302951A CN 110118380 B CN110118380 B CN 110118380B
Authority
CN
China
Prior art keywords
capacity
solar
heating
heat source
auxiliary heat
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
Application number
CN201910302951.7A
Other languages
Chinese (zh)
Other versions
CN110118380A (en
Inventor
田喆
兰博
牛纪德
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Tianjin University
Original Assignee
Tianjin University
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Tianjin University filed Critical Tianjin University
Priority to CN201910302951.7A priority Critical patent/CN110118380B/en
Publication of CN110118380A publication Critical patent/CN110118380A/en
Application granted granted Critical
Publication of CN110118380B publication Critical patent/CN110118380B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24—HEATING; RANGES; VENTILATING
    • F24D—DOMESTIC- OR SPACE-HEATING SYSTEMS, e.g. CENTRAL HEATING SYSTEMS; DOMESTIC HOT-WATER SUPPLY SYSTEMS; ELEMENTS OR COMPONENTS THEREFOR
    • F24D15/00—Other domestic- or space-heating systems
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24—HEATING; RANGES; VENTILATING
    • F24D—DOMESTIC- OR SPACE-HEATING SYSTEMS, e.g. CENTRAL HEATING SYSTEMS; DOMESTIC HOT-WATER SUPPLY SYSTEMS; ELEMENTS OR COMPONENTS THEREFOR
    • F24D19/00—Details
    • F24D19/10—Arrangement or mounting of control or safety devices
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/10—Geometric CAD
    • G06F30/13—Architectural design, e.g. computer-aided architectural design [CAAD] related to design of buildings, bridges, landscapes, production plants or roads
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/20—Design optimisation, verification or simulation
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
    • Y02B10/00—Integration of renewable energy sources in buildings
    • Y02B10/20—Solar thermal
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
    • Y02B10/00—Integration of renewable energy sources in buildings
    • Y02B10/70—Hybrid systems, e.g. uninterruptible or back-up power supplies integrating renewable energies

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Geometry (AREA)
  • General Engineering & Computer Science (AREA)
  • Computer Hardware Design (AREA)
  • General Physics & Mathematics (AREA)
  • Mechanical Engineering (AREA)
  • Evolutionary Computation (AREA)
  • Combustion & Propulsion (AREA)
  • Chemical & Material Sciences (AREA)
  • Thermal Sciences (AREA)
  • Structural Engineering (AREA)
  • Civil Engineering (AREA)
  • Architecture (AREA)
  • Computational Mathematics (AREA)
  • Mathematical Analysis (AREA)
  • Mathematical Optimization (AREA)
  • Pure & Applied Mathematics (AREA)
  • Supply And Distribution Of Alternating Current (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

The invention discloses a method for calculating equivalent design capacity of a solar heating system, which comprises the following steps: step 1: inputting historical measured meteorological data and thermal parameters of a building, and performing computer simulation by using EnergyPlus software to obtain a building heating load; step 2: calculating to obtain the area of the solar heat collector and the capacity of the auxiliary heat source; and step 3: adjusting the capacity of an auxiliary heat source in the heating system by adopting a bisection method; and 4, step 4: evaluating equivalent design capacity of a solar heating system; and 5: and calculating convergence judgment to obtain the final equivalent design capacity of the solar heating system. The method can calculate the equivalent design capacity actually provided by the solar heating system under the condition of considering weather uncertainty, reduce the auxiliary heat source capacity according to the calculated equivalent design capacity on the premise of ensuring the user energy demand, and improve the economic benefit of the system.

Description

Equivalent design capacity calculation method for solar heating system
Technical Field
The invention relates to the field of solar simulation analysis, in particular to a method for calculating equivalent design capacity of a solar heating system.
Background
As the demand for renewable energy increases year by year, its consumption is projected to increase from 7.1% in 2015 to 13% in 2040, which accounts for the percentage of total energy worldwide. Renewable energy makes it possible to replace traditional energy, however due to uncertainties caused by variations in real-time production, the planning of the production capacity of some renewable energy sources is challenging. Therefore, accurate resource capacity value assessment is critical to long-term planning of the system.
In the capacity planning and designing process of the solar heating system, an engineering design manual is generally adopted for calculation, for example, in GB50495-2009 technical Specification for solar heating engineering, the average solar radiation amount on the lighting surface of a local heat collector is adopted to be combined with the solar guarantee rate and the heat consumption of a building to calculate the total area of the solar heat collector of the system. In the method, the mean value is adopted to replace the change value, and the uncertain change of weather is not considered, so that the solar heat collector is generally considered to have only energy value but no capacity value, and an auxiliary heat source is often added into the system to carry out combined energy supply. In addition, for a solar heating system, the building heating load and the solar heat collector heating load are obviously influenced by time-by-time weather factors, the reliability of the system is greatly reduced due to the mismatching of the energy in time, and the basic requirement of the time-by-time matching of the heat supply and the load requirement is neglected even if the time sequence characteristic is neglected.
Although the design method adopting the national standard can ensure the reliable operation of the whole system, the method ignores that the reliable system capacity can be provided to a certain extent during the solar heat supply in the actual operation, thereby having a certain capacity value. If the system capacity after solar energy is added is not reasonably evaluated, the capacity provided by the solar energy is neglected, so that the problems of overlarge initial design and increased initial investment of an actual energy supply system are caused.
Disclosure of Invention
The invention aims to overcome the defects in the prior art and provide a method for calculating the equivalent design capacity of a solar heating system, which can obtain the equivalent design capacity of a solar heat collector meeting the actual engineering requirements by taking the system reliability as a constraint index and provides a reference for designers.
The purpose of the invention is realized by the following technical scheme:
a method for calculating equivalent design capacity of a solar heating system comprises the following steps:
step 1: historical measured meteorological data and thermal parameters of the building are input, and computer simulation is carried out by adopting EnergyPlus software to obtain the heating load of the building.
Step 2: and calculating to obtain the area of the solar heat collector and the capacity of the auxiliary heat source. The area of the initial solar heat collector and the capacity of the auxiliary heat source are calculated by a method in GB50495-2009 technical Specification for solar heating engineering.
Figure BDA0002028851870000021
In the formula: a. theCThe total area of the solar heat collector of the direct system; qHConsuming heat for the building; j. the design is a squareTAverage daily solar radiation on the lighting surface of the local solar collector; f is the solar energy guarantee rate; etacdThe average heat collection efficiency of the solar heat collector is obtained; etaLThe heat loss rate of the pipeline and the heat storage device.
In the above formula, the heat consumption of the building is the heating load of the building, and the initial capacity C of the auxiliary heat source is QHAnd the rest of the parameters are obtained by consulting the attached table in the specification.
And step 3: and adjusting the capacity of an auxiliary heat source in the heating system by adopting a bisection method. Let Cmax＝C，CminWhen the value is 0, the auxiliary heat source initial change capacity is calculated by the equation (2). The capacity of the new auxiliary heat source is shown as the formula (3).
CΔa＝(Cmax+Cmin) (2)
C'＝C-CΔa (3)
In the formula: cΔaInitial capacity change for auxiliary heat source; and C' is the capacity of the new auxiliary heat source.
And 4, step 4: and evaluating the equivalent design capacity of the solar heating system. And (3) judging whether the system is reliable or not according to the hourly space-time heating load of the building obtained by simulating in the step 1 and the hourly space-time capacity of the new auxiliary heat source obtained in the step 3 and the hourly space-time size relationship between the energy supply of the new auxiliary heat source and the heating load obtained by TRNSYS simulation calculation. v (t) is a reliability calculation index in the t hour, and if the energy supply amount is larger than the required amount, the system is reliable in the t hour (v (t) ═ 1), whereas unreliable (v (t) ═ 0), as shown in equation (4).
The probability of insufficient heating is lambda1The ratio of the unreliable hours to the total simulation hours (m) is expressed by equation (5). Accumulating the heating load in all unreliable hours to obtain the heating insufficient load lambda2The heating reliability (β) is defined as shown in formula (7) by formula (6).
Figure BDA0002028851870000022
In the formula: delta Qhl(t) the heating shortage load in the t hour, Qhl(t) heating capacity at time t, Qst(t) the amount of stored heat at time t, QaAnd (t) is the auxiliary boiler heat supply amount at the time t.
Figure BDA0002028851870000023
Figure BDA0002028851870000024
Figure BDA0002028851870000025
And 5: and calculating convergence judgment to obtain the final equivalent design capacity of the solar heating system.
The reliability of a boiler heating system and the like is selected as a constraint condition, and a solar heat collector can replace the capacity of an auxiliary boiler to be used as the equivalent design capacity in the solar heating system, as shown in a formula (8):
f(C,QH)＝f(C+Asc-CΔa,QH) (8)
wherein f (-) is a reliability calculation function, C is an auxiliary heat source capacity, AscIs the area of the solar heat collector.
As can be seen from equation (8), the capacity of the auxiliary heat source can be reduced by increasing the area of the solar collector, and the reduced capacity of the auxiliary heat source is the equivalent design capacity (C) of the solar collectore) As shown in formula (9).
Ce＝CΔa (9)
The heating supply shortage probability calculated by the indexes in the step 3 and the step 4 is lambda1' and underheating load amount lambda2' and the set probability of insufficient heating is lambda1And insufficient heating load lambda2The comparison is carried out, and the comparison is carried out,the comparison method adopts convergence index judgment, wherein the convergence index comprises the relative error of the number of hours of insufficient heating load (1') relative error with respect to the amount of under-heating load ((C)2') and threshold values are set to10.5% and2the calculation is shown in formulas (10) and (11), respectively, at 5%.
Figure BDA0002028851870000031
Figure BDA0002028851870000032
If it is1'<1And is2'<2Then calculate convergence to obtain CΔaI.e. the equivalent design capacity Ce(ii) a Otherwise, determining lambda1'>λ1And lambda2'>λ2If yes, let Cmax＝CΔaIf not, let Cmin＝CΔaAnd returning to the step 3 to the step 5 for calculation again until the calculation is converged.
Compared with the prior art, the technical scheme of the invention has the following beneficial effects:
1. the method for calculating the equivalent design capacity of the solar heating system solves the problem that the solar energy supply is not counted at present due to the fact that in the energy planning stage, the solar heating system is influenced by weather factors and has the characteristics of variability and uncertainty. And theoretical calculation basis is provided for quantification of actual solar energy supply.
2. Compared with the traditional engineering specification design method, the method provided by the invention can solve the problem that the capacity of the auxiliary heat source is increased due to neglecting the effective capacity which can be provided by the solar heat collector. After the equivalent design capacity is calculated, the capacity of the auxiliary heat source can be reduced, and the economical efficiency of the system can be improved.
3. According to the invention, through EnergyPlus and TRNSYS simulation software, the actual solar heat supply amount and the building heating load are simulated, the time-by-time operation conditions of the building and the heating equipment under the actual condition are considered in combination with reliability analysis, and compared with the traditional planning method, the hourly system reliability is considered and is closer to the actual condition.
Drawings
Fig. 1 is a flow chart of a method for calculating equivalent design capacity of a solar heating system provided by the invention.
Fig. 2 is a schematic diagram of a solar heating system in an embodiment of the invention.
Fig. 3 is a graph of the 20-year hourly load simulation results in the embodiment of the present invention.
FIG. 4 is a time-wise load probability distribution statistical chart in an embodiment of the present invention.
Fig. 5 is a graph of a simulation result of 20-year hourly heating load in the embodiment of the present invention.
Detailed Description
The invention is described in further detail below with reference to the figures and specific examples. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
As shown in fig. 1, a method for calculating an equivalent design capacity of a solar heating system includes the following steps:
step 1: historical measured meteorological data and thermal parameters of the building are input, and computer simulation is carried out by adopting EnergyPlus software to obtain the heating load of the building.
Step 2: and calculating to obtain the area of the solar heat collector and the capacity of the auxiliary heat source. The area of the initial solar heat collector and the capacity of the auxiliary heat source are calculated by adopting a method in GB50495 plus 2009 technical Specification for solar heating engineering.
Figure BDA0002028851870000041
In the formula: a. theCThe total area of the solar heat collector of the direct system; qHConsuming heat for the building; j. the design is a squareTAverage daily solar radiation on the lighting surface of the local solar collector; f is the solar energy guarantee rate; etacdFor solar heat collectorsAverage heat collection efficiency; etaLThe heat loss rate of the pipeline and the heat storage device.
In the above formula, the heat consumption of the building is the heating load of the building, and the initial capacity C of the auxiliary heat source is QHAnd the rest of the parameters are obtained by consulting the attached table in the specification.
And step 3: and adjusting the capacity of an auxiliary heat source in the heating system by adopting a bisection method. Let Cmax＝C，CminWhen the value is 0, the auxiliary heat source initial change capacity is calculated by the equation (2). The capacity of the new auxiliary heat source is shown as the formula (3).
CΔa＝(Cmax+Cmin) (2)
C'＝C-CΔa (3)
In the formula: cΔaInitial capacity change for auxiliary heat source; and C' is the capacity of the new auxiliary heat source.
And 4, step 4: and evaluating the equivalent design capacity of the solar heating system. And (3) judging whether the system is reliable or not according to the hourly space-time heating load of the building obtained by simulating in the step 1 and the hourly space-time capacity of the new auxiliary heat source obtained in the step 3 and the hourly space-time size relationship between the energy supply of the new auxiliary heat source and the heating load obtained by TRNSYS simulation calculation. v (t) is a reliability calculation index in the t hour, and if the energy supply amount is larger than the required amount, the system is reliable in the t hour (v (t) ═ 1), whereas unreliable (v (t) ═ 0), as shown in equation (4).
The probability of insufficient heating is lambda1The ratio of the unreliable hours to the total simulation hours (m) is expressed by equation (5). Accumulating the heating load in all unreliable hours to obtain the heating insufficient load lambda2The heating reliability (β) is defined as shown in formula (7) by formula (6).
Figure BDA0002028851870000051
In the formula: delta Qhl(t) the heating shortage load in the t hour, Qhl(t) heating capacity at time t, Qst(t) the amount of stored heat at time t, QaAnd (t) is the auxiliary boiler heat supply amount at the time t.
Figure BDA0002028851870000052
Figure BDA0002028851870000053
Figure BDA0002028851870000054
And 5: and calculating convergence judgment to obtain the final equivalent design capacity of the solar heating system.
The reliability of a boiler heating system and the like is selected as a constraint condition, and a solar heat collector can replace the capacity of an auxiliary boiler to be used as the equivalent design capacity in the solar heating system, as shown in a formula (8):
f(C,QH)＝f(C+Asc-CΔa,QH) (8)
wherein f (-) is a reliability calculation function, C is an auxiliary heat source capacity, AscIs the area of the solar heat collector.
As can be seen from equation (8), the capacity of the auxiliary heat source can be reduced by increasing the area of the solar collector, and the reduced capacity of the auxiliary heat source is the equivalent design capacity (C) of the solar collectore) As shown in formula (9).
Ce＝CΔa (9)
The heating supply shortage probability calculated by the indexes in the step 3 and the step 4 is lambda1' and underheating load amount lambda2' and the set probability of insufficient heating is lambda1And insufficient heating load lambda2Comparing, and judging by adopting a convergence index by the comparison method, wherein the convergence index comprises the relative error of the number of hours of insufficient heating load (1') relative error with respect to the amount of under-heating load ((C)2') and threshold values are set to10.5% and2the calculation is shown in formulas (10) and (11), respectively, at 5%.
Figure BDA0002028851870000055
Figure BDA0002028851870000056
If it is1'<1And is2'<2Then calculate convergence to obtain CΔaI.e. the equivalent design capacity Ce(ii) a Otherwise, determining lambda1'>λ1And lambda2'>λ2If yes, let Cmax＝CΔaIf not, let Cmin＝CΔaAnd (5) returning to the steps (3) - (5) to calculate until the calculation is converged.
Example (b):
the invention adopts 20-year actual weather data in area A as a basis, and designs the following buildings as simulation examples to verify the applicability of the method.
1) And (3) simulation data statement:
the building is oriented to southeast, has 3 layers in total, and has a heating area 1440m2. The indoor design temperature of the winter heating is 22 ℃, and the specific design parameters are shown in table 1. The heating time is 11 months and 15 days to 3 months and 15 days every year, and the total time is 121 days. The daily heating time is 9: 00-17: 00, the total annual heating hours of the solar heating system is (H1089H). In order to find out the uncertainty change of meteorological elements along with time, the invention adopts time-by-time actual meteorological data from 1991 to 2010 to simulate, and embodies the uncertainty of heating load and equipment performance every year.
The heat supply equipment selects a solar flat plate collector and an auxiliary boiler. The simulation adopts EnergyPlus software to calculate the building heating load, and generates the dynamic building heating load per hour in the heating season by inputting detailed information such as the geographical position, the orientation, the parameters of the enclosure structure, the internal disturbance of personnel, local meteorological data and the like of the building. The TRNSYS software is adopted to simulate the energy supply condition of equipment, the simulation schematic diagram of the heating system is shown in figure 2, and the specific simulation setting parameters are shown in table 1.
TABLE 1 simulation concrete setup parameters
Figure BDA0002028851870000061
Figure BDA0002028851870000071
2) Calculating to obtain the area of the solar heat collector and the capacity of the auxiliary heat source:
FIG. 3 is a time chart of the heating load of the building, and the area of the solar heat collector is 100m by calculation according to the building load carry-in formula (1) in FIG. 32The capacity of the auxiliary heat source is 84.8 kW. The probability statistics of the heating load time by time of 20 years is carried out, and the obtained result is shown in fig. 4, wherein the maximum heating load can be seen to be 113kW, the load exceeding 100kW is very little, and most of the load is concentrated in the interval of 0-80 kW.
3) After the dichotomy adjustment, a solar heat supply simulation result is as follows:
the effective solar energy gain is calculated according to the formula (1):
Qsc＝FRAc[It(τα)e-UL(Ti-Ta)] (1)
in the formula, QscThe solar heat collector is heated; fRA solar thermal collector thermal migration factor; i istIs the amount of solar radiation on the inclined surface; (tau. alpha.)eThe product of the transmittance of the glass cover plate and the absorption ratio of the heat absorption plate; u shapeLThe total heat loss coefficient of the solar heat collector; t isiIs the solar collector inlet temperature; t isaIs the ambient air temperature. Wherein, FR、(τα)e、UL、TiThe parameters of the solar heat collector are obtained by referring to the table 1. The other meteorological parameters are obtained according to 20-year hourly meteorological data.
Irradiation amount (I) on inclined plane of solar flat plate collectort) As shown in formula (2):
Figure BDA0002028851870000072
in the formula ItThe irradiation amount on the inclined plane; i isbThe irradiation amount is directly irradiated on the horizontal plane; i isdThe irradiation amount is scattered on the horizontal plane; beta is the inclination angle of the solar flat plate collector; rho is the surface reflectivity; rbIs a correction factor for direct radiation on an inclined plane. Wherein, beta, rho and RbThe intrinsic parameters were obtained by referring to table 1, and the remaining solar radiation parameters were obtained from 20 year chronological meteorological data.
The heat supply of the solar heat collector with a unit area in the solar heating system obtained by the above simulation is shown in fig. 5. The solar heat collector can continuously provide heat as a heat source, and can provide heat with an auxiliary heat source at the same time, and can provide 600W/m even in the later part of hours of heating every year2The above heat, this part of energy cannot be ignored. The solar heat supply system has certain capacity value in the actual operation process, and the design planning capacity of the auxiliary heat source can be effectively reduced.
Fig. 5 also shows that in the heating period of 1089h every year, the solar heat utilization system is obviously affected by the uncertainty of weather due to different meteorological parameters at the same time in different years, and the uncertainty of heat supply exists. In addition, as the building type is an office building and intermittent heating is adopted, the heat obtained by the solar heat collector has periodicity in days. And by combining the load uncertainty obtained by the analysis, the load and the heat obtained by the solar heat collector are simultaneously influenced by solar radiation and show periodic changes, and a time correlation exists. Therefore, the invention adopts a reliability concept, analyzes the time-by-time energy matching condition as the evaluation index of the reliability by a simulation mode, and calculates the equivalent design capacity of the solar heating system considering uncertainty under the design reliability.
4) Equivalent design capacity under design reliability:
according to ASHRAE design manual, when calculating heating design load, 99.6% or 99% of the accumulated outdoor dry bulb temperature is selected as the outdoor dry bulb temperatureThe design temperature is 99.6 percent as a selection basis, and the heating shortage probability of the office building is calculated to be lambda10.4%, insufficient heating load lambda2Is 331 kW.
Under the condition of selecting the same 99.6% reliability, the invention adopts the same area of the solar heat collector to calculate, and obtains the planning design result considering the equivalent design capacity by calculation. The actual solar collector can provide an equivalent design capacity of 12.9kW, so the actual boiler design capacity is 72.1kW, a 15.2% reduction in design capacity. Therefore, under the condition of ensuring that the system has the same reliability, the equivalent design capacity of the solar heating system is considered, the design capacity of the auxiliary heat source can be effectively reduced, and the economic benefit of the system is improved.
TABLE 2 equivalent Capacity calculation results under design reliability
Figure BDA0002028851870000081
The present invention is not limited to the above-described embodiments. The foregoing description of the specific embodiments is intended to describe and illustrate the technical solutions of the present invention, and the above specific embodiments are merely illustrative and not restrictive. Those skilled in the art can make many changes and modifications to the invention without departing from the spirit and scope of the invention as defined in the appended claims.

Claims (1)

1. A method for calculating equivalent design capacity of a solar heating system is characterized by comprising the following steps:
step 1: inputting historical measured meteorological data and thermal parameters of a building, and performing computer simulation by using EnergyPlus software to obtain a building heating load;
step 2: calculating to obtain the area of the solar heat collector and the capacity of the auxiliary heat source; calculating by using a method in GB50495-2009 technical Specification for solar heating and heating projects to obtain the area of an initial solar heat collector and the capacity of an auxiliary heat source;
Figure FDA0002028851860000011
in the formula: a. theCThe total area of the solar heat collector of the direct system; qHConsuming heat for the building; j. the design is a squareTAverage daily solar radiation on the lighting surface of the local solar collector; f is the solar energy guarantee rate; etacdThe average heat collection efficiency of the solar heat collector is obtained; etaLThe heat loss rate of the pipeline and the heat storage device;
heat consumption Q of building in the above formulaHI.e. the building heating load, the initial capacity C of the auxiliary heat source is QHThe other parameters are obtained by looking up an attached table in the specification;
and step 3: adjusting the capacity of an auxiliary heat source in the heating system by adopting a bisection method; let Cmax＝C，CminCalculating to obtain the initial change capacity of the auxiliary heat source according to the formula (2) when the initial change capacity of the auxiliary heat source is 0; the capacity of the new auxiliary heat source is shown as the formula (3):
CΔa＝(Cmax+Cmin) (2)
C'＝C-CΔa (3)
in the formula: cΔaInitial capacity change for auxiliary heat source; c' is the new auxiliary heat source capacity;
and 4, step 4: evaluating equivalent design capacity of a solar heating system; judging whether the system is reliable or not according to the hourly space-time heating load of the building obtained by simulating in the step 1 and the hourly space-time capacity of the new auxiliary heat source obtained in the step 3 and the hourly space-time size relationship between the energy supply of the new auxiliary heat source and the heating load obtained by TRNSYS simulation calculation; v (t) is a reliability calculation index in the t hour, and if the energy supply amount is larger than the demand amount, the system is reliable in the t hour (v (t) ═ 1), otherwise, the system is unreliable (v (t) ═ 0), as shown in formula (4);
the probability of insufficient heating is lambda1The ratio of unreliable hours to total simulation hours (m) is expressed by formula (5); accumulating the heating load in all unreliable hours to obtain the insufficient heating loadλ2The heating reliability (β) is defined as represented by formula (7) represented by formula (6);
Figure FDA0002028851860000012
in the formula: delta Qhl(t) the heating shortage load in the t hour, Qhl(t) heating capacity at time t, Qst(t) the amount of stored heat at time t, Qa(t) auxiliary boiler heat supply at time t;
Figure FDA0002028851860000013
Figure FDA0002028851860000014
Figure FDA0002028851860000021
and 5: calculating convergence judgment to obtain the final equivalent design capacity of the solar heating system;
the reliability of a boiler heating system and the like is selected as a constraint condition, and a solar heat collector can replace the capacity of an auxiliary boiler to be used as the equivalent design capacity in the solar heating system, as shown in a formula (8):
f(C,QH)＝f(C+Asc-CΔa,QH) (8)
wherein f (-) is a reliability calculation function, C is an auxiliary heat source capacity, AscThe area of the solar heat collector;
from the equation (8), the capacity of the auxiliary heat source is reduced by increasing the area of the solar collector, and the reduced capacity of the auxiliary heat source is the equivalent design capacity (C) of the solar collectore) As shown in formula (9);
Ce＝CΔa (9)
the heating supply shortage probability calculated by the indexes in the step 3 and the step 4 is lambda1' and underheating load amount lambda2' and the set probability of insufficient heating is lambda1And insufficient heating load lambda2Comparing, and judging by adopting a convergence index by the comparison method, wherein the convergence index comprises the relative error of the number of hours of insufficient heating load (1') relative error with respect to the amount of under-heating load ((C)2') and threshold values are set to10.5% and25%, respectively calculating as shown in formulas (10) and (11);
Figure FDA0002028851860000022
Figure FDA0002028851860000023
if it is1'<1And is2'<2Then calculate convergence to obtain CΔaI.e. the equivalent design capacity Ce(ii) a Otherwise, determining lambda1'>λ1And lambda2'>λ2If yes, let Cmax＝CΔaIf not, let Cmin＝CΔaAnd returning to the step 3 to the step 5 for calculation again until the calculation is converged.
CN201910302951.7A 2019-04-16 2019-04-16 Equivalent design capacity calculation method for solar heating system Active CN110118380B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201910302951.7A CN110118380B (en) 2019-04-16 2019-04-16 Equivalent design capacity calculation method for solar heating system

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201910302951.7A CN110118380B (en) 2019-04-16 2019-04-16 Equivalent design capacity calculation method for solar heating system

Publications (2)

Publication Number Publication Date
CN110118380A CN110118380A (en) 2019-08-13
CN110118380B true CN110118380B (en) 2020-12-29

Family

ID=67520996

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201910302951.7A Active CN110118380B (en) 2019-04-16 2019-04-16 Equivalent design capacity calculation method for solar heating system

Country Status (1)

Country Link
CN (1) CN110118380B (en)

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110795683A (en) * 2019-10-22 2020-02-14 北京中环合创环保能源科技有限公司 Solar heat collector area calculation method and device
TWI825717B (en) * 2022-05-11 2023-12-11 廣騰再生能源股份有限公司 Value evaluation apparatus for solar power station

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103438611A (en) * 2013-07-26 2013-12-11 西安交通大学 Optimized design method of solar ground source heat pump system
CN105066481A (en) * 2015-07-29 2015-11-18 上海交通大学 Large solar heating system model based on transient system (TRNSYS) and modeling method
CN105240916A (en) * 2015-11-05 2016-01-13 中国建筑西南设计研究院有限公司 Active solar system optimization method suitable for building in cold plateau area
CN107477553A (en) * 2017-07-31 2017-12-15 国网天津节能服务有限公司 A kind of energy control strategy based on solar energy, electric boiler complementation heat storage boiler
CN109325273A (en) * 2018-09-06 2019-02-12 天津大学 Solar thermal collector power output modelling method of probabilistic based on nonparametric probability

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103438611A (en) * 2013-07-26 2013-12-11 西安交通大学 Optimized design method of solar ground source heat pump system
CN105066481A (en) * 2015-07-29 2015-11-18 上海交通大学 Large solar heating system model based on transient system (TRNSYS) and modeling method
CN105240916A (en) * 2015-11-05 2016-01-13 中国建筑西南设计研究院有限公司 Active solar system optimization method suitable for building in cold plateau area
CN107477553A (en) * 2017-07-31 2017-12-15 国网天津节能服务有限公司 A kind of energy control strategy based on solar energy, electric boiler complementation heat storage boiler
CN109325273A (en) * 2018-09-06 2019-02-12 天津大学 Solar thermal collector power output modelling method of probabilistic based on nonparametric probability

Also Published As

Publication number Publication date
CN110118380A (en) 2019-08-13

Similar Documents

Publication Publication Date Title
Taveres-Cachat et al. A methodology to improve the performance of PV integrated shading devices using multi-objective optimization
Skandalos et al. An optimization approach to photovoltaic building integration towards low energy buildings in different climate zones
Dávi et al. Energy performance evaluation of a net plus-energy residential building with grid-connected photovoltaic system in Brazil
Zhao et al. Optimal PV panel tilt angle based on solar radiation prediction
CN110118380B (en) Equivalent design capacity calculation method for solar heating system
CN112036026A (en) Building thermal load prediction method based on heat storage system
Carpino et al. Improve decision-making process and reduce risks in the energy retrofit of existing buildings through uncertainty and sensitivity analysis
CN104794545B (en) A kind of Method for optimized planning of the grid-connected scheme of power distribution network
Kong et al. Long term forecast of local electrical demand and evaluation of future impacts on the electricity distribution network
Lan et al. Improving the design method of a solar heating system considering weather uncertainty and system reliability
Kharait et al. Energy yield and clipping loss corrections for hourly inputs in climates with solar variability
Oh et al. An integrated model for estimating the techno-economic performance of the distributed solar generation system on building façades: Focused on energy demand and supply
Carrera et al. Energy efficiency analysis of east-west oriented photovoltaic systems for buildings: a technical-economic-environmental approach
CN110751402B (en) Green building energy consumption quota determining method based on control strategy
Hong et al. Estimating the loss ratio of solar photovoltaic electricity generation through stochastic analysis
Vecchi et al. Self-Sufficiency Building Energy Modelling from Urban to Block-Scale with PV Technology.
Putri et al. Building integrated photovoltaic for rooftop and facade application in Indonesia
Lorenzati et al. Social housing in Italy: Energy audit and dynamic simulation towards a nZEB policy
Barzegar et al. Evaluation of the effect of building orientation on achieved solar radiation-a NE-SW orientated case of urban residence in sem-iarid climate
Li et al. Effect of obstruction on thermal performance of solar water heaters
Opare et al. The Impact of Roof Coating and Solar PV System in the Tropical Region of Ghana
Fan et al. An optimization model for building envelope retrofit considering energy performance certificate
Karaguzel Simulation-based parametric analysis of building systems integrative solar photovoltaics
Qiao et al. Multi-objective optimization of building integrated photovoltaic windows in office building
Hassan Optimizing the integration of renewable energy systems in buildings

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
CP02 Change in the address of a patent holder

Address after: 300452 Binhai Industrial Research Institute Campus of Tianjin University, No. 48 Jialingjiang Road, Binhai New Area, Tianjin

Patentee after: Tianjin University

Address before: 300072 Tianjin City, Nankai District Wei Jin Road No. 92

Patentee before: Tianjin University

CP02 Change in the address of a patent holder