CN113887006A - Steam power system optimization method and system based on pipe network constraint - Google Patents

Steam power system optimization method and system based on pipe network constraint Download PDF

Info

Publication number
CN113887006A
CN113887006A CN202111177893.3A CN202111177893A CN113887006A CN 113887006 A CN113887006 A CN 113887006A CN 202111177893 A CN202111177893 A CN 202111177893A CN 113887006 A CN113887006 A CN 113887006A
Authority
CN
China
Prior art keywords
steam
power system
pipe network
model
turbine
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.)
Pending
Application number
CN202111177893.3A
Other languages
Chinese (zh)
Inventor
王天宇
王炯
陆鹏飞
曹晓红
张鹏
孙楚桥
孔令建
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.)
CNOOC Huizhou Petrochemicals Co Ltd
Original Assignee
CNOOC Huizhou Petrochemicals Co Ltd
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 CNOOC Huizhou Petrochemicals Co Ltd filed Critical CNOOC Huizhou Petrochemicals Co Ltd
Priority to CN202111177893.3A priority Critical patent/CN113887006A/en
Publication of CN113887006A publication Critical patent/CN113887006A/en
Pending legal-status Critical Current

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/10—Geometric CAD
    • G06F30/18—Network design, e.g. design based on topological or interconnect aspects of utility systems, piping, heating ventilation air conditioning [HVAC] or cabling
    • 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
    • G06F30/28—Design optimisation, verification or simulation using fluid dynamics, e.g. using Navier-Stokes equations or computational fluid dynamics [CFD]
    • 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
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • 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—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
    • G06Q50/06—Electricity, gas or water supply
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2111/00—Details relating to CAD techniques
    • G06F2111/04—Constraint-based CAD
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2113/00—Details relating to the application field
    • G06F2113/08—Fluids
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2113/00—Details relating to the application field
    • G06F2113/14—Pipes
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
    • G06F2119/08—Thermal analysis or thermal optimisation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
    • G06F2119/14—Force analysis or force optimisation, e.g. static or dynamic forces

Abstract

The invention relates to a steam power system optimization method and system based on pipe network constraint, wherein the method comprises the following steps: obtaining a solving variable of a steam power system operation optimization model aiming at a pre-obtained demand variable; calculating by adopting a pipe network model based on the solving variables to obtain a calculation result; judging whether the calculation result meets the constraint condition of steam parameters required by the hot hydrazine, and repeating S1-S3 until the calculation result meets the constraint condition if the calculation result does not meet the constraint condition of adjusting the steam source steam generation parameters of the steam power system; if the new calculation result is met, the calculation result is used as a first calculation result, a first turbine model is adopted to obtain a new hot hydrazine steam demand according to the first calculation result, and the new hot hydrazine steam demand is used as a new demand variable and is input into a steam power system optimization model to obtain a new solution variable; and calculating by adopting a pipe network model according to the new solving variable to obtain a second calculation result, and adjusting the steam yield of the steam source according to the first calculation result and the second calculation result to enable the hot hydrazine parameter to be within a preset range.

Description

Steam power system optimization method and system based on pipe network constraint
Technical Field
The invention relates to the technical field of steam power systems, in particular to a steam power system optimization method and system based on pipe network constraint.
Background
At present, the dispatching and adjusting of steam power systems of most of domestic oil refining and chemical industry enterprises basically depends on experience, the load adjustment of equipment such as boilers, steam turbines, temperature and pressure reduction and the like excessively depends on manpower, the purposes of meeting the process steam demand and stably operating devices are basically only achieved, a large amount of energy is wasted, and the operating cost of the steam power systems is higher. The steam power system optimization modeling can be generally classified into a linear programming model and a nonlinear programming model.
If the steam parameters of each stage of steam pipe network are fixed, the model can be generally classified into linear programming, and then the distribution of each logistics flow and the constraint of each unit device of the system are optimized;
if the steam parameters are also used as optimization variables, the model can be generally classified as a complex nonlinear problem due to the complexity of the steam thermodynamic parameter calculation relation and the nonlinearity of the steam pipe network energy balance and the turbine work doing process, and then the design parameters and the operation parameters of the public engineering system with basically determined structure are optimized.
The linear programming model is simple and mature, but only approximates the nonlinear problem, and has a certain deviation from the actual situation, even a lot of differences sometimes, and the nonlinear programming model can better reflect the actual situation and can be used for design optimization of a new system and operation optimization of an existing system. The heat and power requirements of enterprises in different periods, the production load of the device, the composition of feeding materials, the specification of products and the change of external environment enable the chemical process generated in the device (unit) to be under the condition of changing the process, the actual situation is very complex, therefore, most of the existing steam power system optimization modeling simplifies the problem into a multi-cycle problem, each cycle has different running conditions, the possible schemes increase exponentially along with the increase of the number of the steam power system units and the cycles, the number of 0 and 1 variables in a mixed integer linear planning and mixed integer nonlinear planning model is increased rapidly, great difficulty is brought to model solution, and the traditional optimization solution algorithm is difficult to enable the problem to be converged to the optimal solution within reasonable time.
In addition, the main centralized consideration in the optimization modeling of the steam power system at present is the conversion link of the steam power system, namely the process requirements of each grade of steam are calculated according to the known fixed steam parameters, and the parameter change of the energy transmission link, namely the steam in the pipe network transmission process, is ignored. In practice, the transmission link has a great influence on the optimization of the conversion link of the steam power system. Therefore, the result obtained by the operation optimization of the conventional steam power system obviously deviates from the actual operation condition of an enterprise, and only can be an optimal solution under a simplified condition, so that the implementation in engineering is difficult to a certain extent.
Disclosure of Invention
Technical problem to be solved
In view of the above disadvantages and shortcomings of the prior art, the present invention provides a steam power system optimization method and system based on pipe network constraints, which solves the technical problems that the conversion link of the steam power system is mainly considered in the optimization modeling of the steam power system at present, that is, the process requirements of each grade of steam are calculated according to the known fixed steam parameters, and the energy transmission link, that is, the parameter change of the steam in the pipe network transmission process, is neglected.
(II) technical scheme
In order to achieve the purpose, the invention adopts the main technical scheme that:
in a first aspect, an embodiment of the present invention provides a steam power system optimization method based on pipe network constraints, where the method is applied to a steam power system of an oil refining chemical industry enterprise, and the method includes:
s1, aiming at the pre-acquired demand variable of the steam power system operation optimization model, acquiring the solving variable of the corresponding steam power system operation optimization model;
the steam power system operation optimization model consists of an equipment model and constraint conditions of the equipment model; the demand variables include: the steam demand and the total electric quantity demand of each pressure grade; the solution variables include: the steam yield of the boiler, the steam inlet quantity of the steam turbine, the steam extraction quantity and the steam exhaust quantity;
s2, calculating by adopting a pipe network model based on the solving variables to obtain a calculation result;
the pipe network model is a model of pressure drop and temperature drop of steam when the steam passes through a pipeline and flow of a pipe network node;
s3, judging whether the calculation result meets the preset constraint condition of the steam parameters required by the hot hydrazine, if not, adjusting the steam source steam generation parameters of the steam power system, and repeating S1-S3 until the steam source steam generation parameters meet the preset constraint condition;
s4, if yes, taking the calculation result as a first calculation result, adopting a first turbine model to obtain a new hot hydrazine steam demand according to the first calculation result, and inputting the new hot hydrazine steam demand as a new demand variable into the steam power system optimization model to obtain a new solution variable;
the first turbine model is a turbine model of inlet steam pressure drop and temperature drop;
and S5, calculating by adopting the pipe network model according to the new solving variable to obtain a second calculation result, and further adjusting the steam generation amount of the steam source according to the first calculation result and the second calculation result to enable the hot hydrazine parameter to be in a preset range.
Preferably, the adjusting the steam generation amount of the steam source according to the first calculation result and the second calculation result so that the hot hydrazine parameter is within a preset range specifically comprises:
and judging whether the absolute value of the difference between the first calculation result and the second calculation result is smaller than a preset range, if not, adjusting the steam generation amount of the steam source, and repeating the steps S1-S5 until the absolute value of the difference between the first calculation result and the second calculation result is in the preset range.
Preferably, the first and second liquid crystal materials are,
the equipment model includes: the boiler model, the second turbine model and the temperature and pressure reducer model;
the constraint conditions of the equipment model comprise the following preset conditions: an objective function, constraints on material balance, constraints on energy balance, constraints on plant capacity, and constraints on demand.
Preferably, the first and second liquid crystal materials are,
the second steam turbine model is one of a back pressure type steam turbine model, a condensing type steam turbine model, a steam extraction condensing type steam turbine model and a steam extraction back pressure type steam turbine model;
wherein the back pressure turbine model is:
D01＝－7.626+58.331W－30.817W2+6.558W3，(1MW≤W≤2MW)；
D02＝－74.011+96.9871W－25.190W2+2.418W3，(2MW＜W≤4.14MW)；
D03＝－152.313+95.093W－12.600W2+0.591W3，(4.14MW＜W≤6MW)；
w is the power generation capacity of the steam turbine;
D01the steam inlet quantity of the back pressure type steam turbine is the steam inlet quantity when the generated energy is more than or equal to 1MW and less than or equal to 2 MW;
D02the steam inlet quantity of the back pressure turbine is the steam inlet quantity when the generated energy is more than 2MW and less than or equal to 4.14 MW;
D03the steam inlet quantity of the back pressure turbine is the steam inlet quantity when the generated energy is more than 4.14MW and less than or equal to 6 MW;
the condensing steam turbine model is as follows:
D11＝2.562+3.915W，(1.1MW≤W≤8.3MW)；
D11the steam inlet quantity of the condensing steam turbine is the steam inlet quantity when the generated energy is more than or equal to 1.1MW and less than or equal to 8.3 MW;
D12＝－5.870+4.945W，(8.3MW＜W≤14MW)；
D12the steam inlet quantity of the condensing steam turbine is the steam inlet quantity when the generated energy is more than 8.3MW and less than or equal to 14 MW;
the steam extraction back pressure type steam turbine model is as follows:
D20＝4.245+0.797Dc+0.004W；
D20the steam inlet quantity of the steam extraction back pressure type steam turbine is obtained;
dc is the extraction steam volume of the extraction steam back pressure turbine.
Preferably, the first and second liquid crystal materials are,
the boiler model is as follows:
when the superheated steam pressure of the boiler is 3.82MPa and the temperature of the superheated steam is 450 ℃,
the fitting formula of the boiler efficiency when the rated gas production load is 75t/h is as follows:
η＝0.67+0.0038D－2.43×10—5D2；
the boiler efficiency fitting formula when the rated gas production load is 130 t/h:
η＝0.73+0.0011D－3.91×10—6D2；
eta is the boiler efficiency; d is the evaporation capacity of the boiler;
the temperature and pressure reduction device model is as follows:
Figure BDA0003296229810000051
D0the steam flow entering the temperature and pressure reducer;
Dkthe steam flow is the steam flow after being decompressed by the temperature and pressure reducer;
Figure BDA0003296229810000052
the proportion of the unevaporated water quantity to the total water spraying quantity;
hgsis the specific enthalpy of reduced water;
hstthe specific enthalpy of saturated water flowing out of the temperature and pressure reducing valve;
h0is the inlet steam specific enthalpy;
hkis the specific enthalpy of steam after pressure reduction.
Preferably, the first and second liquid crystal materials are,
the objective function is:
minc＝∑nYnZn+cfuelFfuel+csFs+cpowerP；
wherein, YnThe value of the state value of the equipment n in the steam power system is 0 or 1;
the device n in the steam power system is the nth device in all devices in the steam power system; the equipment is a boiler or a steam turbine;
Znthe depreciation cost of equipment n per hour;
cfuelthe price per ton of fuel;
Ffuelthe amount of fuel consumed per hour;
csthe price of purchased steam per ton;
Fsthe flow rate of outsourcing steam per hour;
cpowerthe price for buying electricity per degree;
p is purchased electricity;
c is the total cost per hour;
the constraint conditions of the material balance are as follows: the method is used for meeting the following requirements for equipment n in the steam power system:
∑inFn，in-∑outFn，out＝0；
wherein, Fn，inIs the flow rate of the stream flowing into the device n;
Fn，outis the flow rate of the material flow flowing out of the device n;
the constraint conditions of the energy balance are as follows: satisfies for the unit device n:
∑inFn，inHn，in-∑outFn，outHn，out-Wn-Qn＝0；
wherein Hn，inIs the specific enthalpy of the stream flowing into the plant n;
Hn，outis the specific enthalpy of the stream exiting the plant n;
Wnwork done to the outside for device n;
Qnheat released to the outside for the equipment n;
the constraints of the device capabilities include:
Fn,out,min≤Fn,out≤Fn,out,max；
Fn,out,minis the minimum stream flow out of the device n;
Fn,out,maxis the maximum stream flow out of the plant n;
Fn,in,min≤Fn,in≤Fn,in,max；
Fn,in,minis the minimum stream flow into the plant n;
Fn,in,maxis the maximum stream flow into the plant n;
Wn,min≤Wn≤Wn,max；
Wn,minis the minimum value of the work done by the device n to the outside;
Wn,maxthe maximum value of the work done by the device n to the outside world;
the constraint conditions of the requirements are as follows:
Figure BDA0003296229810000071
Figure BDA0003296229810000072
Pdemthe electric quantity required by the user;
Fn，s，kthe amount of kth stage steam to supply the user to the plant n;
Fs，kthe amount of purchased kth stage steam;
Fs，dem，kthe user is presented with a kth steam demand.
Preferably, the first and second liquid crystal materials are,
the pipe network model comprises:
the pressure drop of the steam through the pipeline satisfies the following conditions:
Figure BDA0003296229810000073
ΔPjtthe pressure drop of any pipeline j in a steam pipe network in the steam power system;
ρjt,averthe average density of steam of any pipeline j in a steam pipe network in a steam power system;
Figure BDA0003296229810000074
the steam flow of any pipeline j in a steam pipe network in a steam power system is squared;
Figure BDA0003296229810000075
the diameter of the pipe is 4 times of the diameter of any pipe j in a steam pipe network in a steam power system;
εjthe pipeline roughness of any pipeline j in a steam pipe network in a steam power system;
Ljfor any pipeline in steam pipe network in steam power systemj, the length of the pipe;
εjethe local friction coefficient of any pipeline j in a steam pipe network in a steam power system is obtained;
j is a pipeline set in a steam pipe network in the steam power system;
t is a period set;
e is a pipeline local resistance set;
the temperature drop of steam passing through any pipeline j in a steam pipe network in the steam power system meets the following requirements:
Figure BDA0003296229810000081
ΔTjtthe temperature of the steam of any pipeline j in a steam pipe network in a steam power system is reduced;
δ0jthe thickness of any pipeline j in a steam pipe network in a steam power system;
δjthe thickness of the heat insulation layer of any pipeline j in a steam pipe network in a steam power system;
Tjt,averthe average temperature of steam of any pipeline j in a steam pipe network in a steam power system;
Tathe temperature of the environment where a steam pipe network in the steam power system is located;
λjthe heat conductivity coefficient of any pipeline j in a steam pipe network in the steam power system;
Cp,jtthe average specific heat capacity of steam of any pipeline j in a steam pipe network in a steam power system;
αjtthe heat release coefficient of the outer surface of the heat insulation layer of any pipeline j in a steam pipe network in a steam power system to the surrounding environment is shown;
the node flow of a steam pipe network in the steam power system meets the following requirements:
Figure BDA0003296229810000082
mdjtthe steam flow through pipe j at node d.
Preferably, the first and second liquid crystal materials are,
the steam parameter constraint conditions required by the hot trap are as follows:
Figure BDA0003296229810000083
Figure BDA0003296229810000084
Figure BDA0003296229810000085
setting the lower limit of the steam pressure of the heat trap;
Pstcalculating the steam pressure of the hot trap;
Figure BDA0003296229810000091
setting the upper limit of the steam pressure of the hot trap;
Figure BDA0003296229810000092
setting the lower limit of the steam temperature of the hot trap;
Tstcalculating the temperature of the hot trap steam;
Figure BDA0003296229810000093
is the set upper limit of the steam temperature of the hot trap.
Preferably, the first and second liquid crystal materials are,
the first turbine model is:
Figure BDA0003296229810000094
a is a preset first coefficient;
b is a preset second coefficient;
mT,actis the actual steam demand of the turbine;
ΔP1to drive turbine inlet pressure variations;
Figure BDA0003296229810000095
the unit mass flow rate is low due to the reduction of the inlet pressure of the steam turbine;
ΔT1to drive turbine inlet temperature variation;
Figure BDA0003296229810000096
the unit mass flow rate is low in power generation amount due to the fact that the temperature of the inlet of the steam turbine is reduced;
the new heat trap steam demand is:
mst,act＝f(Pst,Tst,mst,dem)；
mst,actis the actual steam demand of the hot-trap;
mst,demsteam demand of the hot-trap;
f () is the preset and steam source demand parameter temperature T, pressure P, mst,demA function of interest;
Pstcalculating the pressure of the hot trap s;
Tstthe resulting hot-trap s temperature was calculated.
On the other hand, this embodiment still provides a steam power system optimization system based on pipe network constraint, the system includes:
at least one processor; and
at least one memory communicatively coupled to the processor, wherein the memory stores program instructions executable by the processor to invoke the program instructions to perform any of the above-described steam power system optimization methods based on grid constraints.
(III) advantageous effects
The invention has the beneficial effects that: according to the steam power system optimization method and system based on pipe network constraint, after the solving variables of the corresponding steam power system operation optimization model are obtained according to the pre-obtained demand variables of the steam power system operation optimization model, the pipe network model considering the pressure drop and the temperature drop of steam passing through a pipeline and the flow factors of pipe network nodes is adopted for calculation, and the steam source steam production parameters of the steam power system are adjusted through the calculation result.
Drawings
FIG. 1 is a flow chart of a steam power system optimization method based on pipe network constraints according to the present invention;
FIG. 2 is a schematic diagram of a steam power system optimization method based on pipe network constraints according to the present invention;
FIG. 3 is a diagram of operating conditions of a back pressure turbine in an embodiment of the present invention;
FIG. 4 is a diagram illustrating operating conditions of a condensing turbine according to an embodiment of the present invention;
FIG. 5 is a schematic view of a single extraction condensing turbine according to an embodiment of the present invention;
FIG. 6 is a graph showing a relationship between a flow rate, a power and a steam extraction amount when the back-extraction steam turbine is in a variable working condition according to an embodiment of the present invention;
FIG. 7 is a graph of the operating efficiency of a coal fired boiler in an embodiment of the present invention.
Detailed Description
For the purpose of better explaining the present invention and to facilitate understanding, the present invention will be described in detail by way of specific embodiments with reference to the accompanying drawings.
In order to better understand the above technical solutions, exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the invention are shown in the drawings, it should be understood that the invention can be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.
The steam power system is an important component of public engineering systems of large enterprises such as petrochemical industry, chemical industry and the like, converts primary energy (fuel and the like) into secondary energy (electricity, steam, hot water and the like), and provides process steam, heat energy and power required by process industry.
The steam power system generally produces steam from an industrial boiler, the steam is sent to equipment at each level through a steam pipe network with a plurality of pressure levels, such as high pressure, medium pressure, low pressure and the like, the pipe networks at each level are connected through a temperature reduction and pressure reduction device, the power or electric power required in the steam turbine production process can be purchased or output by a power grid due to the profit, the power provided by the steam power system accounts for the vast majority of the power consumption of the whole plant, and a part of heat energy of the produced steam is sourced from an energy recovery system which is complicated by petroleum and chemical production devices.
Therefore, the safe and stable operation of the steam power system is the basis of the safe, stable and long-period operation of an enterprise, and meanwhile, the steam power system is used as a large energy consumption user of the enterprise, the conversion efficiency of the steam power system directly influences the economy of the enterprise, and the steam power system is also a main source for generating pollutants.
Therefore, in order to improve the energy utilization level of the steam power system of the oil refining and chemical enterprises, the steam power system is very necessary to be reasonably and scientifically optimized.
Referring to fig. 1 and fig. 2, the present embodiment provides a steam power system optimization method based on pipe network constraints, where the method is applied to a steam power system of an oil refining chemical industry enterprise, and the method includes:
and S1, acquiring solving variables of the corresponding steam power system operation optimization model aiming at the pre-acquired demand variables of the steam power system operation optimization model.
The steam power system operation optimization model consists of an equipment model and constraint conditions of the equipment model; the demand variables include: the steam demand and the total electric quantity demand of each pressure grade; the solution variables include: the steam yield of the boiler, the steam inlet quantity of the steam turbine, the steam extraction quantity and the steam exhaust quantity.
The steam power system mainly completes the conversion process of fuel, steam and electric power and the adjustment among the steams with different pressure grades, and for the steam power system without a gas turbine, the conversion of each energy working medium is mainly realized through a boiler, a steam turbine and a desuperheater, so that the optimization of the steam power system needs to establish an equipment model for completing each conversion process, and establish constraint conditions and objective functions under the equipment model and the process requirement boundary determining conditions.
And S2, calculating by adopting a pipe network model based on the solving variables to obtain a calculation result.
The pipe network model is a model of pressure drop and temperature drop of steam passing through the pipeline and flow of pipe network nodes.
And S3, judging whether the calculation result meets the preset constraint condition of the steam parameters required by the hot hydrazine, if not, adjusting the steam source steam generation parameters of the steam power system, and repeating S1-S3 until the steam source steam generation parameters meet the preset constraint condition.
And S4, if the calculation result is met, taking the calculation result as a first calculation result, acquiring a new hot hydrazine steam demand by adopting a first turbine model according to the first calculation result, and inputting the new hot hydrazine steam demand as a new demand variable into the steam power system optimization model to acquire a new solution variable.
The first turbine model is a turbine model of inlet steam pressure drop and temperature drop.
And S5, calculating by adopting the pipe network model according to the new solving variable to obtain a second calculation result, and further adjusting the steam generation amount of the steam source according to the first calculation result and the second calculation result to enable the hot hydrazine parameter to be in a preset range.
The embodiment fully considers the demand change of the continuously changed processing amount, product scheme and other complex working conditions on steam and electric power under the market economic condition and the integration optimization of the steam power system and the pipe network conveying system.
In practical application of this embodiment, the adjusting the steam generation amount of the steam source according to the first calculation result and the second calculation result so that the hot hydrazine parameter is within a preset range specifically includes:
and judging whether the absolute value of the difference between the first calculation result and the second calculation result is smaller than a preset range, if not, adjusting the steam generation amount of the steam source, and repeating the steps S1-S5 until the absolute value of the difference between the first calculation result and the second calculation result is in the preset range.
In practical application of this embodiment, the device model includes: boiler model, second turbine model, temperature and pressure reducer model.
The constraint conditions of the equipment model comprise the following preset conditions: an objective function, constraints on material balance, constraints on energy balance, constraints on plant capacity, and constraints on demand.
In practical applications of this embodiment, the second steam turbine model is one of a back pressure steam turbine model, a condensing steam turbine model, a steam extraction condensing steam turbine model, and a steam extraction back pressure steam turbine model.
Wherein the back pressure turbine model is:
D01＝－7.626+58.331W－30.817W2+6.558W3，(1MW≤W≤2MW)。
D02＝－74.011+96.9871W－25.190W2+2.418W3，(2MW＜W≤4.14MW)。
D03＝－152.313+95.093W－12.600W2+0.591W3，(4.14MW＜W≤6MW)。
and W is the power generation capacity of the steam turbine.
D01The steam inlet quantity of the back pressure type steam turbine is the steam inlet quantity when the generated energy is more than or equal to 1MW and less than or equal to 2 MW.
D02The steam inlet quantity of the back pressure turbine is the steam inlet quantity when the generated energy is more than 2MW and less than or equal to 4.14 MW.
D03The steam inlet quantity of the back pressure turbine is the steam inlet quantity when the generated energy is more than 4.14MW and less than or equal to 6 MW.
The condensing steam turbine model is as follows:
D11＝2.562+3.915W，(1.1MW≤W≤8.3MW)。
D11the steam inlet quantity of the condensing steam turbine is the steam inlet quantity when the generated energy is more than or equal to 1.1MW and less than or equal to 8.3 MW.
D12＝－5.870+4.945W，(8.3MW＜W≤14MW)。
D12The steam inlet quantity of the condensing steam turbine is the steam inlet quantity when the generated energy is more than 8.3MW and less than or equal to 14 MW.
The steam extraction back pressure type steam turbine model is as follows:
D20＝4.245+0.797Dc+0.004W。
D20the steam inlet quantity of the steam extraction back pressure type steam turbine.
Dc is the extraction steam volume of the extraction steam back pressure turbine.
In specific applications, steam turbines in industry are mainly of back pressure type, condensing type, steam extraction condensing type and steam extraction back pressure type.
The main task of the back pressure turbine is to supply the amount of steam specified by the user under certain steam discharge parameters and to generate certain electric energy at the same time. Generally, the steam exhaust state and the heat supply amount of the back pressure turbine are determined according to the needs of users, namely, the electricity is determined by heat, so that the generating capacity of the unit is only determined by steam inlet parameters, and the heat and electricity loads can not be met at the same time. Therefore, although the back pressure turbine has the characteristics of power and heat cogeneration and good speed regulation, in an area without power grid supply, the back pressure turbine cannot operate alone but must operate in parallel with the condensing turbine, thereby limiting the application range of the back pressure turbine. The back pressure turbine is generally nozzle regulated, and the efficiency and flow curve shows obvious wave shape, so it is not suitable to treat the efficiency as constant. The curve of the work capacity and the steam consumption of the back pressure turbine can be generally processed by a piecewise function. By way of example, fig. 3 is a diagram of the operating conditions of a back pressure turbine with a nominal inlet pressure of 3.43MPa, a nominal inlet temperature of 435 ℃, a nominal exhaust pressure of 0.981MPa, a nominal operating exhaust temperature of 299.7 ℃ and a nominal inlet volume of 92.5 t/h.
The operating condition diagrams of the condensing steam turbine and the back pressure steam turbine with the same initial parameters of the condensing steam turbine are similar, only because the back pressure of the back pressure steam turbine is higher and the enthalpy drop for converting into mechanical work is smaller, the steam quantity required for generating the same power is larger, the corresponding no-load steam consumption is larger than that of the condensing steam turbine, the steam consumption line of the condensing steam turbine is below the back pressure steam turbine and the slope is smaller than that of the latter, for example, the operating condition diagram of the condensing steam turbine of a certain model is shown in fig. 4, the rated steam inlet pressure of the condensing steam turbine is 3.43MPa, the rated steam inlet temperature is 435 ℃, the rated steam outlet pressure is 0.0067MPa, and the rated steam inlet quantity is 68.6 t/h.
The extraction condensing steam turbine can meet the requirements of external electric energy and heat energy at the same time, and has higher regulation flexibility compared with a back pressure type turbine, so that the extraction condensing steam turbine is widely applied. For example, fig. 5 is a diagram illustrating the operation of a single extraction condensing steam turbine of a certain type. The rated steam inlet pressure of the steam turbine is 3.43MPa, the rated steam injection temperature is 435 ℃, the rated steam extraction pressure and the steam extraction temperature are 0.98lMPa and 305 ℃ respectively, the rated steam discharge pressure is 0.049MPa, and the rated steam inlet amount is 102 t/h. As can be seen from the figure, the relationship between the steam intake amount D0, the steam extraction amount Dc, and the power W can be directly expressed by a linear function.
The extraction back-pressure turbine can guarantee the thermal user demands of supplying two different steam pressures, can only reasonably work according to two thermal user thermal load curves, and has the defect that the electrical equipment of the device cannot be fully utilized during the period of reducing the thermal demands. Fig. 6 is a relation curve of flow rate, power and extraction steam quantity when the back extraction type steam turbine of a certain model is in variable working condition.
In practical application of this embodiment, the boiler model is:
when the superheated steam pressure of the boiler is 3.82MPa and the temperature of the superheated steam is 450 ℃,
the fitting formula of the boiler efficiency when the rated gas production load is 75t/h is as follows:
η＝0.67+0.0038D－2.43×10—5D2。
the boiler efficiency fitting formula when the rated gas production load is 130 t/h:
η＝0.73+0.0011D－3.91×10—6D2。
eta is the boiler efficiency; d is the evaporation capacity of the boiler.
In a steam power system, in order to meet the requirement of a technological process on steam, the load of a boiler is often changed within a certain range from the design working condition in actual operation, so that the variable working condition characteristic of the boiler, namely the relation between the efficiency of the boiler and the evaporation capacity when the load is changed, needs to be known. The efficiency of a design unit and a manufacturing plant only give the efficiency of rated evaporation capacity under a design working condition generally, the main reason is that the actual operation condition of a boiler is very complex, the actual efficiency of the same boiler often has a large difference with the design value, and the change of the actual operation state can greatly affect the efficiency of the boiler, so that the variable working condition characteristic of the relation between the boiler efficiency and the evaporation capacity needs to be obtained by experiments aiming at a specific furnace. For an oil-fired boiler, the fuel quantity is easy to measure, and the efficiency of the boiler can be measured and calculated by adopting a positive balance method generally to obtain a relation curve of the evaporation capacity and the efficiency of the boiler. For a coal-fired boiler, the coal consumption is difficult to accurately measure, the loss of the boiler can be measured, and the variable working condition characteristic of the boiler efficiency is calculated and obtained by an inverse equilibrium method. Practical calculation shows that when the load of the boiler is as low as 60%, the thermal efficiency of the boiler is 10% -20% lower than that of the rated load, and the thermal efficiency is the highest only when the load is 80% -100%, so that the boiler is in the optimal efficiency region for boiler operation. FIG. 7 is a graph showing the operating efficiency of a 130t/h coal-fired boiler commonly used in a certain enterprise.
The temperature and pressure reduction device model is as follows:
Figure BDA0003296229810000161
D0the steam flow entering the temperature and pressure reducer; dkThe steam flow is the steam flow after being decompressed by the temperature and pressure reducer;
Figure BDA0003296229810000162
the proportion of the unevaporated water quantity to the total water spraying quantity; h isgsIs the specific enthalpy of reduced water; h isstFor flow from a pressure-reducing or temperature-reducing valveSaturated water specific enthalpy; h is0Is the inlet steam specific enthalpy; h iskIs the specific enthalpy of steam after pressure reduction. Assuming that the enthalpy values in the above formula are not changed, the steam inlet amount and the steam outlet amount of the temperature and pressure reducing valve can be approximately expressed as a linear relation. The ratio of the two may be set to a constant in the optimization run calculation, depending on the actual operating conditions.
In the actual operation of the steam power system, when the heat load suddenly increases to exceed the design value, in order to ensure that the system still can work normally, some temperature and pressure reducing devices are often required to be arranged between the pressure steam pipelines. According to the thermodynamic principle, the presence of a pressure and temperature reducing valve reduces the work capacity of the steam, resulting in a loss of available energy, and therefore should in principle be kept as small or as small as possible.
In practical application of this embodiment, the objective function is:
minc＝∑nYnZn+cfuelFfuel+csFs+cpowerP；
wherein, YnThe value of the state value of the equipment n in the steam power system is 0 or 1; in this embodiment, a binary variable (value is 0 or 1) is used to represent whether the equipment is operated under a given working condition, when the value of the variable is 1, the equipment is operated, and 0 represents that the equipment is not used.
The device n in the steam power system is the nth device in all devices in the steam power system; the equipment is a boiler or a steam turbine.
ZnThe depreciation cost of equipment n per hour; c. CfuelThe price per ton of fuel; ffuelThe amount of fuel consumed per hour; c. CsThe price of purchased steam per ton; fsThe flow rate of outsourcing steam per hour; c. CpowerThe price for buying electricity per degree; p is purchased electricity; c is the total cost per hour;
the constraint conditions of the material balance are as follows: the method is used for meeting the following requirements for equipment n in the steam power system:
∑inFn，in-∑outFn，out＝0；
wherein，Fn，inIs the flow rate of the stream flowing into the device n; fn，outIs the flow rate of the stream flowing out of the device n.
The constraint conditions of the energy balance are as follows: satisfies for the unit device n:
∑inFn，inHn，in-∑outFn，outHn，out-Wn-Qn＝0；
wherein Hn，inIs the specific enthalpy of the stream flowing into the plant n; hn，outIs the specific enthalpy of the stream exiting the plant n; wnWork done to the outside for device n; qnThe heat given off by the device n to the outside.
The constraints of the device capabilities include:
Fn,out,min≤Fn,out≤Fn,out,max；
Fn,out,minis the minimum stream flow out of the plant n.
Fn,out,maxIs the maximum stream flow out of the plant n.
Fn,in,min≤Fn,in≤Fn,in,max；
Fn,in,minIs the minimum stream flow into the plant n.
Fn,in,maxIs the maximum stream flow into the plant n.
Wn,min≤Wn≤Wn,max；
Wn,minThe minimum value of the work done by the device n to the outside world.
Wn,maxThe maximum amount of work that the device n does to the outside world.
The constraint conditions of the requirements are as follows:
Figure BDA0003296229810000181
Figure BDA0003296229810000182
Pdemthe electric quantity required by the user; fn，s，kThe amount of kth stage steam to supply the user to the plant n; fs，kThe amount of purchased kth stage steam; fs，dem，kThe user is presented with a kth steam demand.
In practical application of this embodiment, the pipe network model includes:
the pressure drop of the steam through the pipeline satisfies the following conditions:
Figure BDA0003296229810000183
ΔPjtthe pressure drop of any pipeline j in a steam pipe network in the steam power system.
ρjt,averThe average density of steam in any pipeline j in a steam pipe network in the steam power system.
Figure BDA0003296229810000184
The steam flow of any pipeline j in a steam pipe network in the steam power system is squared.
Figure BDA0003296229810000185
The diameter of the pipe is 4 times of the diameter of any pipe j in a steam pipe network in a steam power system.
εjThe pipeline roughness of any pipeline j in a steam pipe network in a steam power system.
LjThe length of any pipeline j in a steam pipe network in the steam power system.
εjeThe local friction coefficient of any pipeline j in a steam pipe network in the steam power system.
J is the pipeline set in the steam pipe network in the steam power system.
T is a period set;
e is a pipeline local resistance set;
the temperature drop of steam passing through any pipeline j in a steam pipe network in the steam power system meets the following requirements:
Figure BDA0003296229810000191
ΔTjtthe temperature of the steam in any pipeline j in the steam pipe network in the steam power system is reduced.
δ0jThe thickness of any pipeline j in a steam pipe network in a steam power system.
δjThe thickness of the heat-insulating layer of any pipeline j in a steam pipe network in a steam power system.
Tjt,averThe average temperature of the steam of any pipeline j in the steam pipe network in the steam power system.
TaThe temperature of the environment where the steam pipe network in the steam power system is located.
λjThe heat conductivity coefficient of any pipeline j in a steam pipe network in the steam power system.
Cp,jtThe average specific heat capacity of the steam of any pipeline j in the steam pipe network in the steam power system.
αjtThe heat release coefficient of the outer surface of the heat insulation layer of any pipeline j in a steam power system to the surrounding environment.
The node flow of a steam pipe network in the steam power system meets the following requirements:
Figure BDA0003296229810000192
mdjtthe steam flow through pipe j at node d, that is, inflow + outflow-, and 0, are the material balance equations.
In practical application of this embodiment, the constraint conditions of the steam parameters required by the hot trap are as follows:
Figure BDA0003296229810000193
Figure BDA0003296229810000194
Figure BDA0003296229810000195
is the set lower limit of the vapor pressure of the hot trap.
PstTo calculate the hot trap vapor pressure in the results.
Figure BDA0003296229810000196
Is the set upper limit of the vapor pressure of the hot trap.
Figure BDA0003296229810000197
Is the set lower limit of the hot trap steam temperature.
TstThe resulting hot trap vapor temperature is calculated.
Figure BDA0003296229810000201
Is the set upper limit of the steam temperature of the hot trap.
In practical application of this embodiment, the first turbine model is:
Figure BDA0003296229810000202
a is a preset first coefficient.
b is a preset second coefficient.
mT,actIs the actual steam demand of the turbine.
ΔP1To drive the turbine inlet pressure delta.
Figure BDA0003296229810000203
The unit mass flow rate is low in power generation amount due to the fact that the pressure of the inlet of the steam turbine is reduced.
ΔT1For driving steamTurbine inlet temperature variation.
Figure BDA0003296229810000204
The unit mass flow rate is low in power generation amount due to the fact that the temperature of the inlet of the steam turbine is reduced.
The new heat trap steam demand is:
mst,act＝f(Pst,Tst,mst,dem)；
mst,actis the actual steam demand of the hot-trap.
mst,demSteam demand of the hot-trap.
f () is the preset and steam source demand parameter temperature T, pressure P, mst,demA function of interest; obtained by regression of a large amount of historical operating data.
PstThe resulting hot-trap s pressure is calculated.
TstThe resulting hot-trap s temperature was calculated.
In the embodiment of the invention, after the solving variables of the corresponding steam power system operation optimization model are obtained according to the demand variables of the pre-obtained steam power system operation optimization model, the pipe network model considering the pressure drop and the temperature drop of steam passing through the pipeline and the flow factors of the pipe network nodes is adopted for calculation, and the steam source steam production parameters of the steam power system are adjusted according to the calculation result.
Since the system described in the above embodiment of the present invention is a system used for implementing the method of the above embodiment of the present invention, a person skilled in the art can understand the specific structure and the modification of the system based on the method described in the above embodiment of the present invention, and thus the detailed description is omitted here. All systems adopted by the method of the above embodiments of the present invention are within the intended scope of the present invention.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions.
It should be noted that in the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The use of the terms first, second, third and the like are for convenience only and do not denote any order. These words are to be understood as part of the name of the component.
Furthermore, it should be noted that in the description of the present specification, the description of the term "one embodiment", "some embodiments", "examples", "specific examples" or "some examples", etc., means that a specific feature, structure, material or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, the claims should be construed to include preferred embodiments and all changes and modifications that fall within the scope of the invention.
It will be apparent to those skilled in the art that various modifications and variations can be made in the present invention without departing from the spirit or scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention should also include such modifications and variations.

Claims (10)

1. A steam power system optimization method based on pipe network constraint is applied to a steam power system of an oil refining chemical industry enterprise, and is characterized by comprising the following steps:
s1, aiming at the pre-acquired demand variable of the steam power system operation optimization model, acquiring the solving variable of the corresponding steam power system operation optimization model;
the steam power system operation optimization model consists of an equipment model and constraint conditions of the equipment model; the demand variables include: the steam demand and the total electric quantity demand of each pressure grade; the solution variables include: the steam yield of the boiler, the steam inlet quantity of the steam turbine, the steam extraction quantity and the steam exhaust quantity;
s2, calculating by adopting a pipe network model based on the solving variables to obtain a calculation result;
the pipe network model is a model of pressure drop and temperature drop of steam when the steam passes through a pipeline and flow of a pipe network node;
s3, judging whether the calculation result meets the preset constraint condition of the steam parameters required by the hot hydrazine, if not, adjusting the steam source steam generation parameters of the steam power system, and repeating S1-S3 until the steam source steam generation parameters meet the preset constraint condition;
s4, if yes, taking the calculation result as a first calculation result, adopting a first turbine model to obtain a new hot hydrazine steam demand according to the first calculation result, and inputting the new hot hydrazine steam demand as a new demand variable into the steam power system optimization model to obtain a new solution variable;
the first turbine model is a turbine model of inlet steam pressure drop and temperature drop;
and S5, calculating by adopting the pipe network model according to the new solving variable to obtain a second calculation result, and further adjusting the steam generation amount of the steam source according to the first calculation result and the second calculation result to enable the hot hydrazine parameter to be in a preset range.
2. The method according to claim 1, wherein the adjusting the steam generation amount of the steam source according to the first calculation result and the second calculation result to make the hot hydrazine parameter within a preset range specifically comprises:
and judging whether the absolute value of the difference between the first calculation result and the second calculation result is smaller than a preset range, if not, adjusting the steam generation amount of the steam source, and repeating the steps S1-S5 until the absolute value of the difference between the first calculation result and the second calculation result is in the preset range.
3. The method of claim 2,
the equipment model includes: the boiler model, the second turbine model and the temperature and pressure reducer model;
the constraint conditions of the equipment model comprise the following preset conditions: an objective function, constraints on material balance, constraints on energy balance, constraints on plant capacity, and constraints on demand.
4. The method of claim 3,
the second steam turbine model is one of a back pressure type steam turbine model, a condensing type steam turbine model, a steam extraction condensing type steam turbine model and a steam extraction back pressure type steam turbine model;
wherein the back pressure turbine model is:
D01＝－7.626+58.331W－30.817W2+6.558W3，(1MW≤W≤2MW)；
D02＝－74.011+96.9871W－25.190W2+2.418W3，(2MW＜W≤4.14MW)；
D03＝－152.313+95.093W－12.600W2+0.591W3，(4.14MW＜W≤6MW)；
w is the power generation capacity of the steam turbine;
D01the steam inlet quantity of the back pressure type steam turbine is the steam inlet quantity when the generated energy is more than or equal to 1MW and less than or equal to 2 MW;
D02the steam inlet quantity of the back pressure turbine is the steam inlet quantity when the generated energy is more than 2MW and less than or equal to 4.14 MW;
D03the steam inlet quantity of the back pressure turbine is the steam inlet quantity when the generated energy is more than 4.14MW and less than or equal to 6 MW;
the condensing steam turbine model is as follows:
D11＝2.562+3.915W，(1.1MW≤W≤8.3MW)；
D11the steam inlet quantity of the condensing steam turbine is the steam inlet quantity when the generated energy is more than or equal to 1.1MW and less than or equal to 8.3 MW;
D12＝－5.870+4.945W，(8.3MW＜W≤14MW)；
D12the steam inlet quantity of the condensing steam turbine is the steam inlet quantity when the generated energy is more than 8.3MW and less than or equal to 14 MW;
the steam extraction back pressure type steam turbine model is as follows:
D20＝4.245+0.797Dc+0.004W；
D20the steam inlet quantity of the steam extraction back pressure type steam turbine is obtained;
dc is the extraction steam volume of the extraction steam back pressure turbine.
5. The method of claim 4,
the boiler model is as follows:
when the superheated steam pressure of the boiler is 3.82MPa and the temperature of the superheated steam is 450 ℃,
the fitting formula of the boiler efficiency when the rated gas production load is 75t/h is as follows:
η＝0.67+0.0038D－2.43×10—5D2；
the boiler efficiency fitting formula when the rated gas production load is 130 t/h:
η＝0.73+0.0011D－3.91×10—6D2；
eta is the boiler efficiency; d is the evaporation capacity of the boiler;
the temperature and pressure reduction device model is as follows:
Figure FDA0003296229800000031
D0the steam flow entering the temperature and pressure reducer;
Dkthe steam flow is the steam flow after being decompressed by the temperature and pressure reducer;
Figure FDA0003296229800000032
the proportion of the unevaporated water quantity to the total water spraying quantity;
hgsis the specific enthalpy of reduced water;
hstthe specific enthalpy of saturated water flowing out of the temperature and pressure reducing valve;
h0is the inlet steam specific enthalpy;
hkis the specific enthalpy of steam after pressure reduction.
6. The method of claim 5,
the objective function is:
minc＝∑nYnZn+cfuelFfuel+csFs+cpowerP；
wherein, YnThe value of the state value of the equipment n in the steam power system is 0 or 1;
the device n in the steam power system is the nth device in all devices in the steam power system; the equipment is a boiler or a steam turbine;
Znthe depreciation cost of equipment n per hour;
cfuelthe price per ton of fuel;
Ffuelthe amount of fuel consumed per hour;
csthe price of purchased steam per ton;
Fsthe flow rate of outsourcing steam per hour;
cpowerthe price for buying electricity per degree;
p is purchased electricity;
c is the total cost per hour;
the constraint conditions of the material balance are as follows: the method is used for meeting the following requirements for equipment n in the steam power system:
∑inFn，in-∑outFn，out＝0；
wherein, Fn，inIs the flow rate of the stream flowing into the device n;
Fn，outis the flow rate of the material flow flowing out of the device n;
the constraint conditions of the energy balance are as follows: satisfies for the unit device n:
∑inFn，inHn，in-∑outFn，outHn，out-Wn-Qn＝0；
wherein Hn，inIs the specific enthalpy of the stream flowing into the plant n;
Hn，outis the specific enthalpy of the stream exiting the plant n;
Wnwork done to the outside for device n;
Qnheat released to the outside for the equipment n;
the constraints of the device capabilities include:
Fn,out,min≤Fn,out≤Fn,out,max；
Fn,out,minis the minimum stream flow out of the device n;
Fn,out,maxis the maximum stream flow out of the plant n;
Fn,in,min≤Fn,in≤Fn,in,max；
Fn,in,minis the minimum stream flow into the plant n;
Fn,in,maxis the maximum stream flow into the plant n;
Wn,min≤Wn≤Wn,max；
Wn,minis the minimum value of the work done by the device n to the outside;
Wn,maxthe maximum value of the work done by the device n to the outside world;
the constraint conditions of the requirements are as follows:
Figure FDA0003296229800000051
Figure FDA0003296229800000052
Pdemthe electric quantity required by the user;
Fn，s，kthe amount of kth stage steam to supply the user to the plant n;
Fs，kthe amount of purchased kth stage steam;
Fs，dem，kthe user is presented with a kth steam demand.
7. The method of claim 6,
the pipe network model comprises:
the pressure drop of the steam through the pipeline satisfies the following conditions:
Figure FDA0003296229800000053
ΔPjtthe pressure drop of any pipeline j in a steam pipe network in the steam power system;
ρjt,averthe average density of steam of any pipeline j in a steam pipe network in a steam power system;
Figure FDA0003296229800000061
the steam flow of any pipeline j in a steam pipe network in a steam power system is squared;
Figure FDA0003296229800000062
the diameter of the pipe is 4 times of the diameter of any pipe j in a steam pipe network in a steam power system;
εjthe pipeline roughness of any pipeline j in a steam pipe network in a steam power system;
Ljthe length of any pipeline j in a steam pipe network in a steam power system;
εjethe local friction coefficient of any pipeline j in a steam pipe network in a steam power system is obtained;
j is a pipeline set in a steam pipe network in the steam power system;
t is a period set;
e is a pipeline local resistance set;
the temperature drop of steam passing through any pipeline j in a steam pipe network in the steam power system meets the following requirements:
Figure FDA0003296229800000063
ΔTjtthe temperature of the steam of any pipeline j in a steam pipe network in a steam power system is reduced;
δ0jfor steam pipes in steam power systemsThe thickness of any pipe j in the mesh;
δjthe thickness of the heat insulation layer of any pipeline j in a steam pipe network in a steam power system;
Tjt,averthe average temperature of steam of any pipeline j in a steam pipe network in a steam power system;
Tathe temperature of the environment where a steam pipe network in the steam power system is located;
λjthe heat conductivity coefficient of any pipeline j in a steam pipe network in the steam power system;
Cp,jtthe average specific heat capacity of steam of any pipeline j in a steam pipe network in a steam power system;
αjtthe heat release coefficient of the outer surface of the heat insulation layer of any pipeline j in a steam pipe network in a steam power system to the surrounding environment is shown;
the node flow of a steam pipe network in the steam power system meets the following requirements:
Figure FDA0003296229800000071
mdjtthe steam flow through pipe j at node d.
8. The method of claim 7,
the steam parameter constraint conditions required by the hot trap are as follows:
Figure FDA0003296229800000072
Figure FDA0003296229800000073
Figure FDA0003296229800000074
setting the lower limit of the steam pressure of the heat trap;
Pstto countCalculating the steam pressure of the heat trap in the result;
Figure FDA0003296229800000075
setting the upper limit of the steam pressure of the hot trap;
Figure FDA0003296229800000076
setting the lower limit of the steam temperature of the hot trap;
Tstcalculating the temperature of the hot trap steam;
Figure FDA0003296229800000077
is the set upper limit of the steam temperature of the hot trap.
9. The method of claim 7,
the first turbine model is:
Figure FDA0003296229800000078
a is a preset first coefficient;
b is a preset second coefficient;
mT,actis the actual steam demand of the turbine;
ΔP1to drive turbine inlet pressure variations;
Figure FDA00032962298000000710
the unit mass flow rate is low due to the reduction of the inlet pressure of the steam turbine;
ΔT1to drive turbine inlet temperature variation;
Figure FDA0003296229800000079
the unit mass flow rate is low in power generation amount due to the fact that the temperature of the inlet of the steam turbine is reduced;
the new heat trap steam demand is:
mst,act＝f(Pst,Tst,mst,dem)；
mst,actis the actual steam demand of the hot-trap;
mst,demsteam demand of the hot-trap;
f () is the preset and steam source demand parameter temperature T, pressure P, mst,demA function of interest;
Pstcalculating the pressure of the hot trap s;
Tstthe resulting hot-trap s temperature was calculated.
10. A steam power system optimization system based on pipe network constraints, the system comprising:
at least one processor; and
at least one memory communicatively coupled to the processor, wherein the memory stores program instructions executable by the processor, and wherein the processor invokes the program instructions to perform the ductwork constraint-based steam power system optimization method of any of claims 1-9.
CN202111177893.3A 2021-10-09 2021-10-09 Steam power system optimization method and system based on pipe network constraint Pending CN113887006A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202111177893.3A CN113887006A (en) 2021-10-09 2021-10-09 Steam power system optimization method and system based on pipe network constraint

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202111177893.3A CN113887006A (en) 2021-10-09 2021-10-09 Steam power system optimization method and system based on pipe network constraint

Publications (1)

Publication Number Publication Date
CN113887006A true CN113887006A (en) 2022-01-04

Family

ID=79005774

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202111177893.3A Pending CN113887006A (en) 2021-10-09 2021-10-09 Steam power system optimization method and system based on pipe network constraint

Country Status (1)

Country Link
CN (1) CN113887006A (en)

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114896859A (en) * 2022-03-29 2022-08-12 湖北中创智优科技有限公司 Steam power and pipe network operation optimization method based on differential evolution
CN114896859B (en) * 2022-03-29 2024-05-03 湖北中创智优科技有限公司 Steam power and pipe network operation optimization method based on differential evolution

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114896859A (en) * 2022-03-29 2022-08-12 湖北中创智优科技有限公司 Steam power and pipe network operation optimization method based on differential evolution
CN114896859B (en) * 2022-03-29 2024-05-03 湖北中创智优科技有限公司 Steam power and pipe network operation optimization method based on differential evolution

Similar Documents

Publication Publication Date Title
CN106842909B (en) Power generation system for load control of power plant and control method thereof
CN104239981B (en) A kind of energy dynamic equilibrium and Optimization Scheduling based on multi-objective optimization algorithm
Chandan et al. Modeling and optimization of a combined cooling, heating and power plant system
JP6046890B2 (en) Steam turbine loading method and loading system
Ponce et al. Dynamic simulator and model predictive control of an integrated solar combined cycle plant
CN104268712B (en) Energy Sources Equilibrium and dispatching method based on improved mixing Populations evolution algorithm
Wang et al. Hydraulic resistance identification and optimal pressure control of district heating network
CN111815042A (en) Electric heating comprehensive energy system optimization scheduling method considering refinement heat supply network model
WO2013025962A1 (en) Thermo-economic modeling and optimization of a combined cooling, heating, and power plant
CN114266165A (en) Carbon emission-considered steam turbine layout optimization method in steam power system
Verda et al. Thermoeconomics as a tool for the design and analysis of energy savings initiatives in buildings connected to district heating networks
CN113887006A (en) Steam power system optimization method and system based on pipe network constraint
Genovski et al. Model research of the energy efficiency of a cogeneration backpressure steam turbine installation
Ma et al. Energy saving maximization on combined heat and power units in different scenarios
CN114936440A (en) Multi-energy coupling system simultaneous power flow simulation method and system under multi-time scale
CN110735682B (en) Distributed residual pressure power generation system based on multi-objective optimization algorithm and regulation and control method
Guo et al. Prediction of the heat load in central heating systems using GA-BP algorithm
CN112686447A (en) Multi-energy flow coupling load prediction method for offshore oil and gas field development
CN105512961A (en) Distributed energy supply method and supply system
Fadnes et al. Artificial neural network model for predicting CO2 heat pump behaviour in domestic hot water and space heating systems
Vittorio et al. Thermoeconomic approach for the analysis of low temperature district heating systems
Zeng et al. Model-based Electric Regulating Valve Design in Looped Steam Heating System User-side Temperature Control
Beiron Combined heat and power plant flexibility-Technical and economic potential and system interaction
Ebrahimi et al. Thermodynamic modeling and optimization of cogeneration heat and power system using evolutionary algorithm (genetic algorithm)
Khoshgoftar Manesh et al. Simulation and optimization of tehran oil refinery steam network in view of exergetic, exergoeconomic and environmental analysis

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