CN105095539A - Steam straight pipe comprising steam power system optimization method and system - Google Patents

Abstract

The invention discloses a operation optimization method and system for a steam power system integrating a steam straight pipe, a power station, and apparatus produced and used steam. The method comprises: determining performance indicators of all devices comprised by the steam power system, a pipe parameter of the steam straight pipe, and a process parameter of the steam power system; establishing a nonlinear mathematical model of the steam power system; performing simulation solution on the established nonlinear mathematical model of the steam power system; setting a value range for a variable considered in an optimization calculation; setting an objective function for the optimization calculation; performing optimization solution on the nonlinear mathematical model of the initial steam power system, which means looking for optimal operation and running values of a flow direction, a flow rate, a pressure, and a temperature variable of the steam system, so as to provide the whole system with the highest energy efficiency; and determining whether an optimization result satisfies a steam power system optimization objective; and if the optimization result satisfies the steam power system optimization objective, completing the optimization calculation.

Description

Include steam power system optimization method and the system of steam straight tube

Technical field

The present invention relates to steam power field, in particular to the operation optimization method and system of the steam power system of a kind of integrated steam straight tube, power station and device product vapour.

Background technology

Steam power system is the important component part in large-size chemical or petrochemical complex device, its task provides the required public work such as power, electric power, heat energy to procedures system, and design level, the operation and control performance of steam power system have material impact to the energy utilization efficiency of process industrial and economic performance.

The systematic parameter optimization that steam power system flowage structure is fixing, to the design parameter of a certain organization plan and the optimization of operating conditions when mainly comprising the optimization of existing system operating conditions and new system or the old system reform.At present, for this kind of steam power system operation parameter optimization, it is simplify steam pipe system model that the method setting up Related Mathematical Models mainly contains two kinds: one, the on-stream pressure of fixed steam pipe network and operating temperature are definite value, do not consider the pressure drop that exists in steam pipe system and heat waste, and the variable in the model of emphasis optimizing power station.Obviously, this does not meet reality, because steam flows in steam pipe system certainly exist heat radiation and crushing, can cause the reduction of vapor (steam) temperature and pressure, thus the vapor (steam) temperature of each point in pipe network and pressure are changed.In process industry, the distance of vapor transmission is usually comparatively far away, and the temperature drop of steam and pressure drop are all relatively more remarkable, if do not consider this change in mathematical model, will produce comparatively big error with actual operating data.Two is simplify power station model, only power station model is pressed the model treatment of steam generating equipment, do not consider its regulating and controlling effect to steam power system, and each node flow, temperature and pressure in emphasis simulation steam pipe system, calculate pressure drop and the heat waste of each steam pipeline section.Equally, so also can have comparatively big error with actual, because the flow of steam, temperature and pressure are all the variablees that can regulate and control in power station, this traffic load that must affect each node in steam pipe system is distributed and temperature and pressure.These two kinds of methods above, all there is no the mathematical model of integrated power station, steam pipe system system and process unit steam inside system, although simplify calculating to a certain extent, but there is relatively large deviation in simulation and optimum results and real data, the directive significance reduction that steam power system is optimized.

How to realize the integrated optimization of steam pipe system model and the power station such as boiler, turbodynamo device model and process unit steam inside system, thus solve the associated bottleneck of steam power system operation parameter optimization, proposing the optimization method of more realistic performance constraint, is the research direction place of those skilled in the art.

Summary of the invention

The invention provides the operation optimization method and system of the steam power system of a kind of integrated steam straight tube, power station and device product vapour, in order to overcome at least one problem existed in prior art.

For achieving the above object, the invention provides the operation optimization method of the steam power system of a kind of integrated steam straight tube, power station and device product vapour, comprising the following steps:

S1, determines the technological parameter of the performance characteristic parameter of each equipment needed for steam power system, the pipe parameter of steam straight tube and described steam power system;

S2, according to the energy conservation equation of described steam power system, the mass-conservation equation of described steam power system, vapor flow equation in described steam straight tube, the energy conservation equation of described each equipment, the mass-conservation equation of described each equipment, two mass rate constrain equations flowed in described steam straight tube, two heat waste equations flowed to and two pressure drop equations flowed in described steam straight tube, and the performance characteristic parameter of described each equipment and the technological parameter of described steam power system set up the nonlinear mathematical model of steam power system, wherein said nonlinear mathematical model comprise double fluid to steam straight tube mathematical model and power station and device produce steam-using system model,

S3, carries out analog approach to described nonlinear mathematical model, obtains simulation trial result, and wherein, this simulation trial result comprises the performance characteristic parameter of all devices in described steam power system;

S4, set the span of optimized variable in described nonlinear mathematical model, and set the optimization object function of described nonlinear mathematical model, the steam load flowing stock and equipment key node in wherein said nonlinear mathematical model distributes, pressure and temperature value is variable, changes in the numerical range of specifying;

S5, optimizes the initial feasible solution of computing as described nonlinear mathematical model using described simulation trial result, the decreasing gradient that calculation optimization calculates in the span of described optimized variable;

S6, is optimized computing according to described decreasing gradient, obtains the new feasible solution of described nonlinear mathematical model and new decreasing gradient value;

S7, judges whether described new decreasing gradient value is less than setting threshold value, if be less than described setting threshold value, performs step S8; Otherwise return step S6, and utilize described new feasible solution and new decreasing gradient value to proceed to optimize computing;

S8, judge whether the feasible solution being less than the decreasing gradient value of described setting threshold value corresponding makes the value of described optimization object function in the span of described optimized variable, reach minimum, if so, then using the operational factor of the feasible solution of correspondence as described steam power system.

Optionally, said method is further comprising the steps of:

If the judged result in step S8 is to make the value of described optimization object function reach minimum in the span of described optimized variable, then returns the span that step S4 adjusts described optimized variable, re-start optimization computing.

Optionally, the described pressure drop equation flowed to for each straight length two is:

$\mathrm{\ΔP}1=\mathrm{\λ}\·\frac{l+l_e}{d}\·{\mathrm{\ρ}}_m\·\frac{\left|u1\right|\·u1}{2},\mathrm{\ΔP}2=\mathrm{\λ}\·\frac{l+l_e}{d}\·{\mathrm{\ρ}}_m\·\frac{\left|u2\right|\·u2}{2}$

Wherein, Δ P1, Δ P2 be in pipeline section steam flow left and to the right flow two kinds of pipeline pressures that may flow to fall; λ is coefficient of pipe friction; D is internal diameter of the pipeline; L is length of straight pipe; l _efor equivalent length; ρ _mfor the average density of steam in pipeline; U1, u2 are that in pipeline section, steam flows left and flows two kinds of steam flow rates that may flow to the right.

Optionally, the described heat waste equation flowed to for each straight length two is:

$\mathrm{\ΔH}1=\frac{k\·\mathrm{\π}\·D_2\·(T-T_0)\·L}{F1},\mathrm{\ΔH}2=\frac{k\·\mathrm{\π}\·D_2\·(T-T_0)\·L}{F2}$

Wherein, Δ H1, Δ H2 are that in pipeline section, steam flows left and flows two kinds of heat waste amounts that may flow to the right, D ₁for internal diameter of the pipeline, D ₂for heat-insulation layer external diameter, L is length of pipe section, and T is tank wall temperature, i.e. vapor (steam) temperature, T ₀for pipeline air themperature, α _sfor the overall heat transfer coefficient between insulation layer surface to surrounding air, λ is insulation material thermal conductivity, F1, F2 be in pipeline section steam flow left and flow to the right two kinds may flow to for steam mass flow.

Optionally, the mass rate constrain equation that described each straight length two flows to is:

F1·F2＝0

Wherein, F1, F2 are that in pipeline section, steam flows left and flows two kinds of steam mass flows that may flow to the right.

Optionally, described optimization object function is:

TOC=TPC+TFC+TSC, and make objective function reach minimum in the span of optimized variable, wherein, TOC is year operation cost, and TPC is year electricity cost, and TFC is year fuel cost, and TSC is year steam buying expenses;

Or be:

TC=TCC+TPC+TFC+TSC, wherein, TC is annual total cost, and TCC is year investment cost, and TPC is year electricity cost, and TFC is year fuel cost, and TSC is year steam buying expenses.

For achieving the above object, the invention provides the operation optimization system of the steam power system of a kind of integrated steam straight tube, power station and device product vapour, comprising:

Performance parameter module, for determining the technological parameter of the performance characteristic parameter of each equipment needed for steam power system, the pipe parameter of steam straight tube and described steam power system;

MBM, for the energy conservation equation according to described steam power system, the mass-conservation equation of described steam power system, vapor flow equation in described steam straight tube, the energy conservation equation of described each equipment, the mass-conservation equation of described each equipment, two mass rate constrain equations flowed in described steam straight tube, two heat waste equations flowed to and two pressure drop equations flowed in described steam straight tube, and the performance characteristic parameter of described each equipment and the technological parameter of described steam power system set up the nonlinear mathematical model of steam power system, wherein said nonlinear mathematical model comprise double fluid to steam straight tube mathematical model and power station and device produce steam-using system model,

Analog approach module, for carrying out analog approach to described nonlinear mathematical model, obtains simulation trial result, and wherein, this simulation trial result comprises the performance characteristic parameter of all devices in described steam power system;

Optimal Setting module, for setting the span of optimized variable in described nonlinear mathematical model, and set the optimization object function of described nonlinear mathematical model, the steam load flowing stock and equipment key node in wherein said nonlinear mathematical model distributes, pressure and temperature value is variable, changes in the numerical range of specifying;

Optimization Solution module, for described simulation trial result to be optimized the initial feasible solution of computing as described nonlinear mathematical model, the decreasing gradient that calculation optimization calculates in the span of described optimized variable, and be optimized computing according to described decreasing gradient, obtain the new feasible solution of described nonlinear mathematical model and new decreasing gradient value;

Grads threshold judge module, for judging whether described new decreasing gradient value is less than setting threshold value, if be less than described setting threshold value, judges that execution module performs; Otherwise utilize described new feasible solution and new decreasing gradient value to proceed to optimize computing by described Optimization Solution module;

Judge execution module, whether make the value of described optimization object function in the span of described optimized variable, reach minimum for the feasible solution that the decreasing gradient value judging to be less than described setting threshold value is corresponding, if so, then using the operational factor of the feasible solution of correspondence as described steam power system.

Optionally, described judgement execution module is also for being when the value of described optimization object function can not be made to reach minimum in the span of described optimized variable when judged result, then adjusted the span of described optimized variable by described Optimal Setting module, re-start optimization computing.

Optionally, the described pressure drop equation flowed to for each straight length two is:

$\mathrm{\ΔP}1=\mathrm{\λ}\·\frac{l+l_e}{d}\·{\mathrm{\ρ}}_m\·\frac{\left|u1\right|\·u1}{2},\mathrm{\ΔP}2=\mathrm{\λ}\·\frac{l+l_e}{d}\·{\mathrm{\ρ}}_m\·\frac{\left|u2\right|\·u2}{2}$

Wherein, Δ P1, Δ P2 be in pipeline section steam flow left and to the right flow two kinds of pipeline pressures that may flow to fall; λ is coefficient of pipe friction; D is internal diameter of the pipeline; L is length of straight pipe; l _efor equivalent length; ρ _mfor the average density of steam in pipeline; U1, u2 are that in pipeline section, steam flows left and flows two kinds of steam flow rates that may flow to the right.

Optionally, the described heat waste equation flowed to for each straight length two is:

$\mathrm{\ΔH}1=\frac{k\·\mathrm{\π}\·D_2\·(T-T_0)\·L}{F1},\mathrm{\ΔH}2=\frac{k\·\mathrm{\π}\·D_2\·(T-T_0)\·L}{F2}$

Wherein, Δ H1, Δ H2 are that in pipeline section, steam flows left and flows two kinds of heat waste amounts that may flow to the right, D ₁for internal diameter of the pipeline, D ₂for heat-insulation layer external diameter, L is length of pipe section, and T is tank wall temperature, i.e. vapor (steam) temperature, T ₀for pipeline air themperature, α _sfor the overall heat transfer coefficient between insulation layer surface to surrounding air, λ is insulation material thermal conductivity, and F1, F2 are that in pipeline section, steam flows left and flows two kinds of steam mass flows that may flow to the right.

Optionally, the mass rate constrain equation that described each straight length two flows to is:

F1·F2＝0

Wherein, F1, F2 are that in pipeline section, steam flows left and flows two kinds of steam mass flows that may flow to the right.

Optionally, described optimization object function is:

TOC=TPC+TFC+TSC, and make objective function reach minimum in the span of optimized variable, wherein, TOC is year operation cost, and TPC is year electricity cost, and TFC is year fuel cost, and TSC is year steam buying expenses;

Or be:

TC=TCC+TPC+TFC+TSC, wherein, TC is annual total cost, and TCC is year investment cost, and TPC is year electricity cost, and TFC is year fuel cost, and TSC is year steam buying expenses.

The operation optimization that present invention achieves the steam power system of integrated steam straight tube, power station and device product vapour calculates, and carries out operation parameter optimization, reduce power consumption and the running cost of system under the prerequisite not changing system architecture flow process to system.In addition, one group of feasible solution is provided, as optimizing the initial solution of computing, and according to the decreasing gradient of described initial solution calculation optimization computing by the simulation trial of model, make optimization computing search the optimum solution of model along gradient direction, improve the reliability and counting yield of optimizing computing.

Compared with prior art, method of the present invention can realize integrated simulation and optimization to steam straight tube with power station and device vapour system, considers the directivity of vapor flow, describes the product vaporous state of pipe network diverse location in actual production process more accurately.This optimization method also combines the description accuracy of non-linear modeling method to complex network problem, and have employed rational optimized algorithm, can set up steam power system mathematical model quickly and accurately and Optimization Solution.

Accompanying drawing explanation

In order to be illustrated more clearly in the embodiment of the present invention or technical scheme of the prior art, be briefly described to the accompanying drawing used required in embodiment or description of the prior art below, apparently, accompanying drawing in the following describes is only some embodiments of the present invention, for those of ordinary skill in the art, under the prerequisite not paying creative work, other accompanying drawing can also be obtained according to these accompanying drawings.

Fig. 1 is the operation optimization method flow diagram of the steam power system of the integrated steam straight tube of one embodiment of the invention, power station and device product vapour;

Fig. 2 is the steam power system schematic diagram of one embodiment of the invention.

Embodiment

Below in conjunction with the accompanying drawing in the embodiment of the present invention, be clearly and completely described the technical scheme in the embodiment of the present invention, obviously, described embodiment is only the present invention's part embodiment, instead of whole embodiments.Based on the embodiment in the present invention, those of ordinary skill in the art, not paying the every other embodiment obtained under creative work prerequisite, belong to the scope of protection of the invention.

Fig. 1 is the operation optimization method flow diagram of the steam power system of the integrated steam straight tube of one embodiment of the invention, power station and device product vapour; As shown in the figure, this operation optimization method comprises the following steps:

S1, determines the technological parameter of the performance characteristic parameter of each equipment needed for steam power system, the pipe parameter of steam straight tube and described steam power system;

Wherein equipment performance characteristic parameter comprises the operating parameter of the operating load of equipment, the operational efficiency of equipment and equipment.Steam power system technological parameter comprises a year running time, systematic electricity demand, fuel data, working condition and system exhaust emissions.

S2, according to the energy conservation equation of described steam power system, vapor flow equation in described steam straight tube, the mass-conservation equation of described steam power system, the band energy conservation equation of described each equipment, the mass-conservation equation of described each equipment, two mass rate constrain equations flowed in described steam straight tube, the heat waste equation that described steam straight tube two flows to and two pressure drop equations flowed to, and the performance characteristic parameter of described each equipment and the technological parameter of described steam power system set up the nonlinear mathematical model of steam power system, wherein said nonlinear mathematical model comprise double fluid to steam straight tube mathematical model and power station and device produce steam-using system model,

The substance of the nonlinear mathematical model of steam power system comprises: the material balance of each unit and energy equilibrium in steam power system, the mobility status of steam in steam straight tube, entire system mass balance and energy equilibrium, the physical condition of system or design code constraint, steam heat mechanical characteristic, and the constraint condition etc. representing all kinds of parameter value scope.

The modeling method wherein related to, it is the nonlinear mathematical model setting up primary steam power system, mainly comprise material balance and the energy equilibrium of each unit in steam power system, entire system mass balance and energy equilibrium, the physical condition of system or design code constraint, steam heat mechanical characteristic, and represent all kinds of parameter value scope.Wherein, for steam straight tube model, with the independent pipeline section of each on straight tube for unit sets up above-mentioned equation.In setting straight tube, the flow direction of each pipeline section, flow, pressure, temperature are variable, the modeling of Large steam straight tube can be processed, utilize these parameters of length of pipe section, pipe thickness and insulation material, set up the temperature drop equation in steam straight tube and pressure drop equation, temperature drop when calculation of steam flows in each pipeline section and pressure drop, judge the flow direction of steam in pipeline section simultaneously.Wherein, temperature drop equation is associated with heat transfer coefficient, heat transfer temperature difference, pipe thickness and steam flow, and pressure drop equation is also associated with steam flow rate, length of pipe section, pipeline section diameter and vapour density.

Simultaneously, include steam delivery system in steam power system optimization, the detailed model of exploitation steam straight tube, the calculation of steam straight tube pressure loss everywhere and thermal loss, consider the structure of steam straight tube under actual condition, the relative position of each process units and everywhere operational factor on the impact of whole steam power system, and judge the directivity of each pipeline section vapor flow in steam straight tube, the actual operating state of reflection steam straight tube.Simultaneously, the steam load distribution, the pressure and temperature that flow stock and equipment (comprising steam straight tube) key node are all carried out modeling process as variable, makes steam power system model can embody temperature in actual industrial system, pressure changing condition.Due to temperature, pressure as variable process, then the thermodynamic behaviour of steam must be included in model, and therefore whole model has very strong nonlinear characteristic.

Merit attention and be, in this method, in pipeline, steam flow defines two flow directions in left and right, and the span in each direction be [0, FMax], FMax be this pipeline section interior by maximum flow.Arranging two having stayed of flowing in model equation finally must have one to be 0, is calculated by optimization, and about result, two flow directions can only retain in a flow direction flow, so just makes the method include flow direction in steam straight tube pipeline section in optimization category.

Set up the method for the nonlinear mathematical model of steam power system, mainly comprise material balance (i.e. the mass conservation) and energy equilibrium (i.e. energy conservation) constraint of each unit, the property relationship of system and design code constraint, steam heat force parameter compute associations equation, and represent the bound constrained of all kinds of parameter value scope.

The pressure drop equation that described each straight length two flows to is:

$\mathrm{\ΔP}1=\mathrm{\λ}\·\frac{l+l_e}{d}\·{\mathrm{\ρ}}_m\·\frac{\left|u1\right|\·u1}{2},\mathrm{\ΔP}2=\mathrm{\λ}\·\frac{l+l_e}{d}\·{\mathrm{\ρ}}_m\·\frac{\left|u2\right|\·u2}{2}$

Wherein, Δ P1, Δ P2 be in pipeline section steam flow left and to the right flow two kinds of pipeline pressures that may flow to fall; λ is coefficient of pipe friction; D is internal diameter of the pipeline; L is length of straight pipe; l _efor equivalent length; ρ _mfor the average density of steam in pipeline; U1, u2 are that in pipeline section, steam flows left and flows two kinds of steam flow rates that may flow to the right.

The heat waste equation that described each straight length two flows to is:

$\mathrm{\ΔH}1=\frac{k\·\mathrm{\π}\·D_2\·(T-T_0)\·L}{F1},\mathrm{\ΔH}2=\frac{k\·\mathrm{\π}\·D_2\·(T-T_0)\·L}{F2}$

Wherein, Δ H1, Δ H2 are that in pipeline section, steam flows left and flows two kinds of heat waste amounts that may flow to the right, D ₁for internal diameter of the pipeline, D ₂for heat-insulation layer external diameter, L is length of pipe section, and T is tank wall temperature, i.e. vapor (steam) temperature, T ₀for pipeline air themperature, α _sfor the overall heat transfer coefficient between insulation layer surface to surrounding air, λ is insulation material thermal conductivity, and F1, F2 are that in pipeline section, steam flows left and flows two kinds of steam mass flows that may flow to the right.

The mass rate constrain equation that described each straight length two flows to is:

F1·F2＝0

Wherein, F1, F2 are that in pipeline section, steam flows left and flows two kinds of steam mass flows that may flow to the right.

S3, carries out analog approach to described nonlinear mathematical model, obtains simulation trial result, and wherein, this simulation trial result comprises the performance characteristic parameter of all devices in described steam power system;

S4, set the span of optimized variable in described nonlinear mathematical model, and set the optimization object function of described nonlinear mathematical model, the steam load flowing stock and equipment key node in wherein said nonlinear mathematical model distributes, pressure and temperature value is variable, changes in the numerical range of specifying.Be different from general operation optimization method, in this method, in pipeline, steam flow defines two flow directions in left and right, and the span in each direction be [0, FMax], FMax be this pipeline section interior by maximum flow.Arranging two having stayed of flowing in model equation finally must have one to be 0, is calculated by optimization, and about result, two flow directions can only retain in a flow direction flow, so just makes the method include flow direction in steam straight tube pipeline section in optimization category;

Described optimization object function is:

TOC=TPC+TFC+TSC, and make objective function reach minimum in the span of optimized variable, wherein, TOC is year operation cost, and TPC is year electricity cost, and TFC is year fuel cost, and TSC is year steam buying expenses;

Or be:

TC=TCC+TPC+TFC+TSC, wherein, TC is annual total cost, and TCC is year investment cost, and TPC is year electricity cost, and TFC is year fuel cost, and TSC is year steam buying expenses.

S5, optimizes the initial feasible solution of computing as described nonlinear mathematical model using described simulation trial result, the decreasing gradient that calculation optimization calculates in the span of described optimized variable;

S6, is optimized computing according to described decreasing gradient, obtains the new feasible solution of described nonlinear mathematical model and new decreasing gradient value;

S7, judges whether described new decreasing gradient value is less than setting threshold value, if be less than described setting threshold value, performs step S8; Otherwise return step S6, and utilize described new feasible solution and new decreasing gradient value to proceed to optimize computing;

S8, judge whether the feasible solution being less than the decreasing gradient value of described setting threshold value corresponding makes the value of described optimization object function in the span of described optimized variable, reach minimum, if so, then using the operational factor of the feasible solution of correspondence as described steam power system; If judged result is to make the value of described optimization object function reach minimum in the span of described optimized variable, then returns the span that step S4 adjusts described optimized variable, re-start optimization computing.

The operation optimization above embodiments enabling the steam power system of integrated steam straight tube, power station and device product vapour calculates, and carries out operation parameter optimization, reduce power consumption and the running cost of system under the prerequisite not changing system architecture flow process to system.In addition, one group of feasible solution is provided, as optimizing the initial solution of computing, and according to the decreasing gradient of described initial solution calculation optimization computing by the simulation trial of model, make optimization computing search the optimum solution of model along gradient direction, improve the reliability and counting yield of optimizing computing.

Compared with prior art, method of the present invention can realize integrated simulation and optimization to steam straight tube with power station and device vapour system, considers the directivity of vapor flow, describes the product vaporous state of pipe network diverse location in actual production process more accurately.This optimization method also combines the description accuracy of non-linear modeling method to complex network problem, and have employed rational optimized algorithm, can set up steam power system mathematical model quickly and accurately and Optimization Solution.

In addition, applicant has developed corresponding Optimization Software i-Steam, incorporates above model buildings method and optimization method, makes the operation optimization calculation automation of steam power system, and ensure that the accurate and quick of calculating, the experience reducing technician relies on.

Be described below in conjunction with the operation optimization method of a real case to steam power system of the present invention.

Case background:

With the power station of little refinery plant, be made up of, be responsible for the task of providing 35bar steam to downstream unit two boilers, downstream steam plant comprises a steam turbine and two steam heaters.The energy requirement of plant area is in table 1:

Table 1

Turbine work requirement	[kW]	5000
			1# steam heater load	[kW]	30000
2# steam heater load	[kW]	60000

The environmental baseline of plant area is in table 2:

Table 2

Atmospheric pressure

[bar]

1

Atmospheric temperature	[C]	20
			Running time in year	[hours]	8000
Boiler feed water temperature	[C]	150
			Demineralized water price	[$/t]	5
Input electricity price lattice	[$/(kWh)]	1
			Fuel	[-]	Mark coal
Plant area's electricity needs	[kW]	10000

The implementation procedure of background case in i-Steam is as follows:

1, set up and solve primary steam power system nonlinear model

2, create an operation interface, build steam power system nonlinear model according to basic flowsheet of coal preparation and primary design data, input analog parameter, is shown in Fig. 2.

In Fig. 2, the point of admission of steam straight tube and go out vapour point and have 5.1# and 2# boiler is respectively to carrying 35bar steam in pipe network, its point of admission is node 2 on this steam pipe system and node 4 respectively, and 1# well heater, pressure and temperature reducing, steam turbine and 2# well heater is node 1 on this steam pipe system with vapour point respectively, node 2, node 3 and node 5.Be corresponding pipeline section between every two nodes, according to clooating sequence from left to right, being pipeline section 1 between node 1 and node 2, is pipeline section 2 between node 2 and node 3, the like, also comprise pipeline section 3 and pipeline section 4.

The efficiency of 1# boiler is the efficiency of 95%, 2# boiler is 90%, is coal-burning boiler.

The workload demand of 1# steam heater is the workload demand of 30MW, 2# steam heater is 60MW, and the power demand of steam turbine is 5MW.

Utilize i-Steam software to carry out nonlinear model analog computation, and guarantee to simulate successfully.Main analog the results are shown in Table 3, and other associated analog results also can be checked in destination file.

Table 3

3, the span of optimized variable, to optimizing in calculating the optimized variable setting span needing to consider.In table 4:

Table 4

4, objective function is determined

According to optimizing the optimization aim calculated, determine objective function.In present case, how main consideration boiler, under the prerequisite meeting steam supply demand, reduces the operation cost of this system.Therefore, to be chosen to be the year operation cost of this system minimum for objective function.

5, design optimization calculates

After the above step is finished, the nonlinear model analog result obtained in 4.2.1 can be integrated the optimized variable span of setting by iSteam software automatically, with most off year operation cost for objective function, utilize GRG algorithm Automatic Optimal to solve this model, solving result is the optimal operational parameters met under power demands condition.

6, analog result and optimum results contrast

The optimum results of Fig. 2 steam power system model and original analog result are contrasted, compares and optimize the change of forward/backward operation condition and the change of economic benefit, in table 5.

Table 5

Contrast about the optimum results of steam pipe system and original analog result, comparing result is in table 6:

Table 6

Contrast finds, in optimum results, boiler duty and the pressure that steams, the intake pressure of steam turbine and flow all there occurs change, and operation cost, fuel cost all have decline with demineralized water expense compared with analog result simultaneously, and energy-saving benefit is obvious.

Be below the operation optimization system of the steam power system of the integrated steam straight tube corresponding with said method embodiment, power station and device product vapour, comprise:

Performance parameter module, for determining the technological parameter of the performance characteristic parameter of each equipment needed for steam power system, the pipe parameter of steam straight tube and described steam power system;

MBM, for the energy conservation equation according to described steam power system band direction vector, the mass-conservation equation of described steam power system, vapor flow equation in described steam straight tube, the energy conservation equation of described each equipment, the mass-conservation equation of described each equipment, the pressure drop equation of the heat waste equation in steam straight tube and band direction vector, and the performance characteristic parameter of described each equipment and the technological parameter of described steam power system set up the nonlinear mathematical model of steam power system, wherein said nonlinear mathematical model comprises the steam straight tube mathematical model and power station and device product steam-using system model of being with direction vector,

Analog approach module, for carrying out analog approach to described nonlinear mathematical model, obtains simulation trial result, and wherein, this simulation trial result comprises the performance characteristic parameter of all devices in described steam power system;

Optimal Setting module, for setting the span of optimized variable in described nonlinear mathematical model, and set the optimization object function of described nonlinear mathematical model, the steam load flowing stock and equipment key node in wherein said nonlinear mathematical model distributes, pressure and temperature value is variable, changes in the numerical range of specifying;

Optimization Solution module, for described simulation trial result to be optimized the initial feasible solution of computing as described nonlinear mathematical model, the decreasing gradient that calculation optimization calculates in the span of described optimized variable, and be optimized computing according to described decreasing gradient, obtain the new feasible solution of described nonlinear mathematical model and new decreasing gradient value;

Grads threshold judge module, for judging whether described new decreasing gradient value is less than setting threshold value, if be less than described setting threshold value, judges that execution module performs; Otherwise utilize described new feasible solution and new decreasing gradient value to proceed to optimize computing by described Optimization Solution module;

Judge execution module, whether make the value of described optimization object function in the span of described optimized variable, reach minimum for the feasible solution that the decreasing gradient value judging to be less than described setting threshold value is corresponding, if so, then using the operational factor of the feasible solution of correspondence as described steam power system.

Optionally, described judgement execution module is also for being when the value of described optimization object function can not be made to reach minimum in the span of described optimized variable when judged result, then adjusted the span of described optimized variable by described Optimal Setting module, re-start optimization computing.

Optionally, the pressure drop equation that described each pipeline section two flows to is:

$\mathrm{\ΔP}1=\mathrm{\λ}\·\frac{l+l_e}{d}\·{\mathrm{\ρ}}_m\·\frac{\left|u1\right|\·u1}{2},\mathrm{\ΔP}2=\mathrm{\λ}\·\frac{l+l_e}{d}\·{\mathrm{\ρ}}_m\·\frac{\left|u2\right|\·u2}{2}$

Wherein, Δ P1, Δ P2 be in pipeline section steam flow left and to the right flow two kinds of pipeline pressures that may flow to fall; λ is coefficient of pipe friction; D is internal diameter of the pipeline; L is length of straight pipe; l _efor equivalent length; ρ _mfor the average density of steam in pipeline; U1, u2 are that in pipeline section, steam flows left and flows two kinds of steam flow rates that may flow to the right.

Optionally, the heat waste equation that described each pipeline section two flows to is:

$\mathrm{\ΔH}1=\frac{k\·\mathrm{\π}\·D_2\·(T-T_0)\·L}{F1},\mathrm{\ΔH}2=\frac{k\·\mathrm{\π}\·D_2\·(T-T_0)\·L}{F2}$

Wherein, Δ H1, Δ H2 are that in pipeline section, steam flows left and flows two kinds of heat waste amounts that may flow to the right, D ₁for internal diameter of the pipeline, D ₂for heat-insulation layer external diameter, L is length of pipe section, and T is tank wall temperature, i.e. vapor (steam) temperature, T ₀for pipeline air themperature, α _sfor the overall heat transfer coefficient between insulation layer surface to surrounding air, λ is insulation material thermal conductivity, and F1, F2 are that in pipeline section, steam flows left and flows two kinds of steam mass flows that may flow to the right.

Optionally, described optimization object function is:

TOC=TPC+TFC+TSC, and make objective function reach minimum in the span of optimized variable, wherein, TOC is year operation cost, and TPC is year electricity cost, and TFC is year fuel cost, and TSC is year steam buying expenses;

Or be:

TC=TCC+TPC+TFC+TSC, wherein, TC is annual total cost, and TCC is year investment cost, and TPC is year electricity cost, and TFC is year fuel cost, and TSC is year steam buying expenses.

The operation optimization above embodiments enabling the steam power system of integrated steam straight tube, power station and device product vapour calculates, and carries out operation parameter optimization, reduce power consumption and the running cost of system under the prerequisite not changing system architecture flow process to system.In addition, one group of feasible solution is provided, as optimizing the initial solution of computing, and according to the decreasing gradient of described initial solution calculation optimization computing by the simulation trial of model, make optimization computing search the optimum solution of model along gradient direction, improve the reliability and counting yield of optimizing computing.

Compared with prior art, method of the present invention can realize integrated simulation and optimization to steam straight tube with power station and device vapour system, considers the directivity of vapor flow, describes the product vaporous state of pipe network diverse location in actual production process more accurately.This optimization method also combines the description accuracy of non-linear modeling method to complex network problem, and have employed rational optimized algorithm, can set up steam power system mathematical model quickly and accurately and Optimization Solution.

One of ordinary skill in the art will appreciate that: accompanying drawing is the schematic diagram of an embodiment, the module in accompanying drawing or flow process might not be that enforcement the present invention is necessary.

One of ordinary skill in the art will appreciate that: the module in the device in embodiment can describe according to embodiment and be distributed in the device of embodiment, also can carry out respective change and be arranged in the one or more devices being different from the present embodiment.The module of above-described embodiment can merge into a module, also can split into multiple submodule further.

Last it is noted that above embodiment is only in order to illustrate technical scheme of the present invention, be not intended to limit; Although with reference to previous embodiment to invention has been detailed description, those of ordinary skill in the art is to be understood that: it still can be modified to the technical scheme described in previous embodiment, or carries out equivalent replacement to wherein portion of techniques feature; And these amendments or replacement, do not make the essence of appropriate technical solution depart from the spirit and scope of embodiment of the present invention technical scheme.

Claims (10)

1. an operation optimization method for the steam power system of integrated steam straight tube, power station and device product vapour, is characterized in that, comprise the following steps:

S1, determines the technological parameter of the performance characteristic parameter of each equipment needed for steam power system, the pipe parameter of steam straight tube and described steam power system;

S2, according to the energy conservation equation of described steam power system, the mass-conservation equation of described steam power system, vapor flow equation in described steam straight tube, the energy conservation equation of described each equipment, the mass-conservation equation of described each equipment, two mass rate constrain equations flowed in described steam straight tube, two heat waste equations flowed to and two pressure drop equations flowed in described steam straight tube, and the performance characteristic parameter of described each equipment and the technological parameter of described steam power system set up the nonlinear mathematical model of steam power system, wherein said nonlinear mathematical model comprise double fluid to steam straight tube mathematical model and power station and device produce steam-using system model,

S3, carries out analog approach to described nonlinear mathematical model, obtains simulation trial result, and wherein, this simulation trial result comprises the performance characteristic parameter of all devices in described steam power system;

S4, set the span of optimized variable in described nonlinear mathematical model, and set the optimization object function of described nonlinear mathematical model, flow the steam flow of stock and equipment key node in wherein said nonlinear mathematical model, load distribution, pressure and temperature value be variable, change in the numerical range of specifying;

S5, optimizes the initial feasible solution of computing as described nonlinear mathematical model using described simulation trial result, the decreasing gradient that calculation optimization calculates in the span of described optimized variable;

S6, is optimized computing according to described decreasing gradient, obtains the new feasible solution of described nonlinear mathematical model and new decreasing gradient value;

S7, judges whether described new decreasing gradient value is less than setting threshold value, if be less than described setting threshold value, performs step S8; Otherwise return step S6, and utilize described new feasible solution and new decreasing gradient value to proceed to optimize computing;

S8, judge whether the feasible solution being less than the decreasing gradient value of described setting threshold value corresponding makes the value of described optimization object function in the span of described optimized variable, reach minimum, if so, then using the operational factor of the feasible solution of correspondence as described steam power system.

2. method according to claim 1, is characterized in that, further comprising the steps of:

If the judged result in step S8 is to make the value of described optimization object function reach minimum in the span of described optimized variable, then returns the span that step S4 adjusts described optimized variable, re-start optimization computing.

3. method according to claim 1, is characterized in that, for each straight length, described two pressure drop equations flowed to are:

$\mathrm{\ΔP}1=\mathrm{\λ}\·\frac{l+l_e}{d}\·{\mathrm{\ρ}}_m\·\frac{\left|u1\right|\·u1}{2},\mathrm{\ΔP}2=\mathrm{\λ}\·\frac{l+l_e}{d}\·{\mathrm{\ρ}}_m\·\frac{\left|u2\right|\·u2}{2}$

Wherein, Δ P1, Δ P2 are that in pipeline section, steam flows left and flows two kinds of Pressure Drops that may flow to the right; λ is coefficient of pipe friction; D is internal diameter of the pipeline; L is length of straight pipe; l _efor equivalent length; ρ _mfor the average density of steam in pipeline; U1, u2 are that in pipeline section, steam flows left and flows two kinds of steam flow rates that may flow to the right.

4. method according to claim 1, is characterized in that, for each straight length, described two heat waste equations flowed to are:

$\mathrm{\ΔH}1=\frac{k\·\mathrm{\π}\·D_2\·(T-T_0)\·L}{F1},\mathrm{\ΔH}2=\frac{k\·\mathrm{\π}\·D_2\·(T-T_0)\·L}{F2}$

Wherein, Δ H1, Δ H2 are that in pipeline section, steam flows left and flows two kinds of heat waste amounts that may flow to the right, D ₁for internal diameter of the pipeline, D ₂for heat-insulation layer external diameter, L is length of pipe section, and T is tank wall temperature, i.e. vapor (steam) temperature, T ₀for pipeline air themperature, α _sfor the overall heat transfer coefficient between insulation layer surface to surrounding air, λ is insulation material thermal conductivity, and F1, F2 are that in pipeline section, steam flows left and flows two kinds of steam mass flows that may flow to the right.

5. method according to claim 1, is characterized in that, for each straight length, described two mass rate constrain equations flowed to are:

F1·F2＝0

Wherein, F1, F2 are that in pipeline section, steam flows left and flows two kinds of steam mass flows that may flow to the right.

6. method according to claim 1, is characterized in that, described optimization object function is:

TOC=TPC+TFC+TSC, and make objective function reach minimum in the span of optimized variable, wherein, TOC is year operation cost, and TPC is year electricity cost, and TFC is year fuel cost, and TSC is year steam buying expenses;

Or be:

TC=TCC+TPC+TFC+TSC, wherein, TC is annual total cost, and TCC is year investment cost, and TPC is year electricity cost, and TFC is year fuel cost, and TSC is year steam buying expenses.

7. an operation optimization system for the steam power system of integrated steam straight tube, power station and device product vapour, is characterized in that, comprising:

Performance parameter module, for determining the technological parameter of the performance characteristic parameter of each equipment needed for steam power system, the pipe parameter of steam straight tube and described steam power system;

MBM, for the energy conservation equation according to described steam power system, the mass-conservation equation of described steam power system, vapor flow equation in described steam straight tube, the energy conservation equation of described each equipment, the mass-conservation equation of described each equipment, two mass rate constrain equations flowed in described steam straight tube, two heat waste equations flowed to and two pressure drop equations flowed in described steam straight tube, and the performance characteristic parameter of described each equipment and the technological parameter of described steam power system set up the nonlinear mathematical model of steam power system, wherein said nonlinear mathematical model comprise double fluid to steam straight tube mathematical model and power station and device produce steam-using system model,

Analog approach module, for carrying out analog approach to described nonlinear mathematical model, obtains simulation trial result, and wherein, this simulation trial result comprises the performance characteristic parameter of all devices in described steam power system;

Optimal Setting module, for setting the span of optimized variable in described nonlinear mathematical model, and set the optimization object function of described nonlinear mathematical model, the steam load flowing stock and equipment key node in wherein said nonlinear mathematical model distributes, pressure and temperature value is variable, changes in the numerical range of specifying;

Optimization Solution module, for described simulation trial result to be optimized the initial feasible solution of computing as described nonlinear mathematical model, the decreasing gradient that calculation optimization calculates in the span of described optimized variable, and be optimized computing according to described decreasing gradient, obtain the new feasible solution of described nonlinear mathematical model and new decreasing gradient value;

Grads threshold judge module, for judging whether described new decreasing gradient value is less than setting threshold value, if be less than described setting threshold value, judges that execution module performs; Otherwise utilize described new feasible solution and new decreasing gradient value to proceed to optimize computing by described Optimization Solution module;

Judge execution module, whether make the value of described optimization object function in the span of described optimized variable, reach minimum for the feasible solution that the decreasing gradient value judging to be less than described setting threshold value is corresponding, if so, then using the operational factor of the feasible solution of correspondence as described steam power system.

8. system according to claim 7, it is characterized in that, described judgement execution module is also for being when the value of described optimization object function can not be made to reach minimum in the span of described optimized variable when judged result, then adjusted the span of described optimized variable by described Optimal Setting module, re-start optimization computing.

9. system according to claim 7, is characterized in that, for each straight length, described two pressure drop equations flowed to are:

$\mathrm{\ΔP}1=\mathrm{\λ}\·\frac{l+l_e}{d}\·{\mathrm{\ρ}}_m\·\frac{\left|u1\right|\·u1}{2},\mathrm{\ΔP}2=\mathrm{\λ}\·\frac{l+l_e}{d}\·{\mathrm{\ρ}}_m\·\frac{\left|u2\right|\·u2}{2}$

Wherein, Δ P1, Δ P2 are that in pipeline section, steam flows left and flows two kinds of Pressure Drops that may flow to the right; λ is coefficient of pipe friction; D is internal diameter of the pipeline; L is length of straight pipe; l _efor equivalent length; ρ _mfor the average density of steam in pipeline; U1, u2 are that in pipeline section, steam flows left and flows two kinds of steam flow rates that may flow to the right.

10. system according to claim 7, is characterized in that, for each straight length, described two heat waste equations flowed to are:

$\mathrm{\ΔH}1=\frac{k\·\mathrm{\π}\·D_2\·(T-T_0)\·L}{F1},\mathrm{\ΔH}2=\frac{k\·\mathrm{\π}\·D_2\·(T-T_0)\·L}{F2}$

Wherein, Δ H1, Δ H2 are that in pipeline section, steam flows left and flows two kinds of heat waste amounts that may flow to the right, D ₁for internal diameter of the pipeline, D ₂for heat-insulation layer external diameter, L is length of pipe section, and T is tank wall temperature, i.e. vapor (steam) temperature, T ₀for pipeline air themperature, α _sfor the overall heat transfer coefficient between insulation layer surface to surrounding air, λ is insulation material thermal conductivity, F1, F2 be in pipeline section steam flow left and flow to the right two kinds may flow to for steam mass flow.