CN113393053B - Equipment model selection optimization method of CCHP system based on prime motor - Google Patents

Equipment model selection optimization method of CCHP system based on prime motor Download PDF

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CN113393053B
CN113393053B CN202110733068.0A CN202110733068A CN113393053B CN 113393053 B CN113393053 B CN 113393053B CN 202110733068 A CN202110733068 A CN 202110733068A CN 113393053 B CN113393053 B CN 113393053B
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heat
user
prime mover
prime
boiler
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CN113393053A (en
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吕洪坤
韩高岩
国旭涛
蔡洁聪
孙聚伟
王均
马航
郑梦莲
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Zhejiang University ZJU
Electric Power Research Institute of State Grid Zhejiang Electric Power Co Ltd
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Zhejiang University ZJU
Electric Power Research Institute of State Grid Zhejiang Electric Power Co Ltd
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    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/12—Computing arrangements based on biological models using genetic models
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Abstract

The invention discloses an equipment model selection optimization method of a CCHP system based on prime movers, which is mainly characterized in that according to an energy supply model in a target operation mode, annual heat load demand data, annual electricity load demand data and annual cold load demand data are based, the minimized annual net cost C is taken as a target, performance curves of all prime movers in a target prime mover equipment library are fitted and then taken as prime mover characteristic performance curves, and the optimal capacity of the prime movers is obtained through a genetic algorithm; selecting a prime motor with the most similar optimal capacity as an optimal prime motor from a target prime motor equipment library; based on the actual capacity of the optimal prime mover and the performance characteristics in the target operation mode, the optimal capacity of the rest equipment in the CCHP system is obtained through a genetic algorithm, and the actual model selection of each equipment is determined according to the optimal capacity. Compared with a method for selecting the equipment combination with the minimized annual net cost by substituting the ergodic equipment library prime motor equipment into the optimization algorithm, the optimization time is greatly shortened.

Description

Equipment model selection optimization method of CCHP system based on prime motor
Technical Field
The invention belongs to the field of model selection optimization of CCHP systems, and particularly relates to a prime mover-based equipment model selection optimization method of a CCHP system.
Background
A Combined cooling and power (CCHP) system has the advantages of high primary energy utilization rate and less influence on environmental pollution, and is one of hot spots concerned by people in recent years. The CCHP system can simultaneously generate electric energy and heat energy, the energy utilization rate can reach 75% -80%, and the consumed energy is only 3/4 in the traditional thermoelectric power supply mode. Typical CCHP systems include (1) power generation units, such as gas turbines, internal combustion engines, fuel cells, and the like; (2) heating equipment such as waste heat boilers, gas boilers, and the like; (3) refrigeration equipment, such as lithium bromide absorption refrigerators, electric refrigerators, and the like.
The complexity requirements of a thermoelectric cooling system cause the environmental, economic and other performances of the system to be significantly influenced by the selection of prime movers, the capacity of other equipment in the system and the operation strategy of the system. When the model selection optimization is performed on the combined cooling heating and power system, a physical simulation model needs to be established for each device in the system so as to simulate the operation characteristics of each device under different operation conditions. The prime mover is used as the core equipment of the combined cooling heating and power system, and the accuracy of the performance curve of the prime mover has obvious influence on the simulation result and the model selection optimization result. Performance curves are generally adopted in related researches at home and abroad to describe the power generation efficiency of a prime motor under different load rates. When the capacity of equipment is optimized for the combined cooling heating and power system, the performance curves of certain prime motor units are usually adopted, and the representative performance curve of the prime motor is obtained after linear or nonlinear function fitting. The prime mover model obtained by adopting characteristic curve fitting does not represent the real model existing in the equipment library, and the characteristic performance curve is different from the actual performance curve of the prime mover. The accurate model selection result can be obtained by traversing the model of the prime mover in the equipment library, the method is time-consuming, and how to improve the prediction method of the performance curve of the prime mover on the premise of ensuring the model selection accuracy is a current concern because the optimization time is shortened.
Disclosure of Invention
The invention aims to overcome the defects in the prior art and provides a device type selection optimization method of a CCHP system based on a prime motor.
The invention adopts the following specific technical scheme:
the invention provides a device model selection optimization method of a CCHP system based on a prime motor, which comprises the following steps:
s1: respectively constructing an algorithm model of each device in the CCHP system according to the actual thermodynamic process; constructing an energy supply model in a target operation mode according to all algorithm models; the target operation mode comprises a heating operation mode and a heating operation mode;
the CCHP system comprises a prime motor, a waste heat boiler, an absorption refrigerator, a gas boiler and an electric refrigerator; the electric energy generated by the prime mover is transmitted to an external power grid through an electric wire for supplying power to a user; the heat energy generated by the prime motor is respectively transmitted to the waste heat boiler and the absorption refrigerator through a first pipeline; the heat generated by the waste heat boiler is transmitted to a heat supply pipeline for supplying heat to users; the cold energy generated by the absorption refrigerator is transmitted to a cold supply pipeline for supplying cold to users; part of the heat energy generated by the gas boiler is transmitted to the absorption refrigerator through a second pipeline, and part of the heat energy is directly transmitted to a heat supply pipeline; an electric refrigerator is connected to the power grid, and the cold energy generated by the electric refrigerator is transmitted to the cold supply pipeline through a third pipeline;
s2: acquiring annual heat load demand data, annual electricity load demand data and annual cold load demand data of a user according to actual energy consumption load data;
s3: according to an energy supply model in a target operation mode, based on the annual heat load demand data, annual electricity load demand data and annual cold load demand data, with the minimum annual net cost C as a target, fitting performance curves of all prime movers in a target prime mover equipment library to be used as prime mover characteristic performance curves, and obtaining the optimal capacity of the prime movers through a genetic algorithm; selecting a prime mover closest to the prime mover optimal capacity as an optimal prime mover in a target prime mover equipment library; based on the actual capacity of the optimal prime mover and the performance characteristics in the target operation mode, the optimal capacity of the rest equipment in the CCHP system is obtained through a genetic algorithm, and the actual model selection of each equipment is determined according to the optimal capacity;
the other devices in the CCHP system comprise a waste heat boiler, an absorption refrigerator, a gas boiler and an electric refrigerator.
Preferably, the prime mover is a gas turbine or an internal combustion engine.
Preferably, the heat energy generated by the prime mover comprises flue gas and jacket water, the flue gas is respectively conveyed to the waste heat boiler and the absorption refrigerator, and the jacket water is conveyed to the absorption refrigerator.
Preferably, the electric constant-heat operation mode is as follows:
s11: judging whether the total power supply capacity of a CHP system can meet the electric load requirement of a user, wherein the CHP system comprises a prime mover and a waste heat boiler; if the total power supply amount of the CHP system can meet the electrical load requirement of the user, the CHP system is used for supplying power to the user, and then the step S12 is carried out; if the total power supply amount of the CHP system can not meet the electrical load demand of the user, firstly enabling the CHP system to operate in the maximum power generation mode for supplying power, and simultaneously supplementing power to the user by the power grid, and then performing step S12;
s12: judging whether a CHP system can meet user heat requirements, wherein the user heat requirements comprise a cold load requirement and a heat load requirement of a user; if the total heat supply quantity of the CHP system can meet the heat demand of the user, the CHP system is used for supplying heat to the user; if the total heat supply of the CHP system can not meet the heat demand of the user, the CHP system is used for supplying heat to the user, and a gas boiler and/or an electric refrigerator are/is also used for supplying heat to the user.
Preferably, the operation mode with fixed temperature electricity is as follows:
s21: judging whether the total heat supply of a CHP system can meet the heat demand of a user, wherein the CHP system comprises a prime motor and a waste heat boiler, and the heat demand of the user comprises the cold load demand and the heat load demand of the user; if the total heat supply amount of the CHP system can meet the heat demand of the user, the CHP system is used for supplying heat to the user, and then the step S22 is carried out; if the total heat supply amount of the CHP system cannot meet the user heat demand, firstly, the CHP system is operated to supply heat in the maximum heat generation mode, and simultaneously, a gas boiler and/or an electric refrigerator is used to supply heat to the user, and then step S22 is performed;
s22: judging whether the total power supply capacity of the CHP system can meet the electrical load requirement of a user; if the total power supply capacity of the CHP system can meet the electric load requirement of a user, the CHP system is used for supplying power to the user; if the total power supply quantity of the CHP system cannot meet the electric load requirement of a user, the CHP system is firstly enabled to operate in the maximum power generation mode for supplying power, and meanwhile, the power grid supplies power for the user in a supplementing mode.
Preferably, the minimum annual net cost C is calculated by equations (1) to (4), and the equations (1) to (4) are specifically as follows:
C＝Cin+Cop-Igr (1)
Figure BDA0003140461850000031
Cop＝∑t＝1Fe(t)×Pe+Fgas(t)×Pgas (3)
Igr＝Egr(t)×Pe' (4)
wherein C is the annual cost, unit; cinThe investment cost is reduced for each device in the CCHP system, and the unit cost is obtained; copThe annual operating cost of the CCHP system is unit; i isgrThe unit is the income of the CCHP system after power is on line; q is the interest rate; n is the service life of the CCHP system in unit year; ciThe unit price of the equipment i is unit/kW, and the equipment i comprises a prime mover, a waste heat boiler, an absorption refrigerator, a gas boiler and an electric refrigerator; r isiThe rated power of the equipment i is kW; fe(t) the electricity purchased by the CCHP system at the moment t in kWh unit; fgas(t) time t is the purchase day of the CCHP systemNatural gas volume in kWh; p iseIs electricity price, unit cell/kWh; pgasNatural gas prices, unit cell/kWh; fgr(t) the remaining power grid-loading quantity of the CCHP system at the time t, and the unit kWh; pe‘For the price of electricity on the internet, unit cell/kWh.
Preferably, in step S3, the performance curves of all the prime movers are fitted to a group of curves in a clustering manner and used as the prime mover characteristic performance curves.
Further, the performance curve of the prime mover is an electric efficiency-load rate performance curve of the prime mover.
Furthermore, the clustering mode adopts a K-means clustering algorithm and is divided into two types with obvious characteristic difference.
Preferably, the performance curve of the prime mover is an electrical efficiency-load rate performance curve of the prime mover.
Compared with the prior art, the invention has the following beneficial effects:
the invention constructs an equipment model selection optimization method of a CCHP system based on a prime motor, a clustering fitting method is used for simulating a characteristic performance curve of the prime motor, the characteristic performance curve is substituted into a model for optimization solution, the actual model selection of the prime motor is carried out in an actual equipment library according to the predicted capacity of the prime motor obtained by optimization, and the actual prime motor capacity and performance characteristics are substituted into an optimization algorithm, so that the actual model selection of other equipment is obtained. Compared with the method for traversing the prime mover equipment library to compare the model selection in the prior art, the method disclosed by the invention more comprehensively solves the model selection problem in the complex CCHP system, can obtain the CCHP system equipment model with the best economic index in a shorter time, can accurately realize the equipment model selection, and greatly shortens the optimization time.
Drawings
FIG. 1 is a schematic diagram of the structure of a CCHP system;
FIG. 2 is a flow chart of operation of the CCHP system in a constant heat electric mode of operation (CCHP-FEL mode);
FIG. 3 is a flow chart of operation of the CCHP system in a hot fixed power mode of operation (CCHP-FHL mode);
fig. 4 is a graph of the results of the electrical efficiency-load factor performance curves of all the prime movers in the prime mover equipment library of examples 1 and 2 after being fitted in a clustering or non-clustering manner;
FIG. 5 is a partial flow diagram of a method for optimizing the type selection of equipment in accordance with the present invention;
fig. 6 is a flow chart of a prior art apparatus model selection optimization method (i.e., a comparison model selection method for traversing a prime mover apparatus library);
fig. 7 is a diagram (a) of optimized model selection results of a CCHP system in case a, a diagram (b) of optimized model selection results of a CCHP system in case b, and a diagram (c) of optimized model selection results of a CCHP system in case c, in the case c, under the method of using a cluster fitting performance curve and a non-cluster fitting performance curve of a prime mover and comparing and selecting models by traversing a prime mover equipment library in embodiment 1;
fig. 8 is a diagram (a) of the optimized model selection result of the CCHP system in case a, a diagram (b) of the optimized model selection result of the CCHP system in case b, and a diagram (c) of the optimized model selection result of the CCHP system in case c, in the embodiment 2, in the electric heating mode, by using the cluster-fitting performance curve and the non-cluster-fitting performance curve of the prime movers and the comparison model selection method of traversing the prime mover equipment library.
Detailed Description
The invention will be further elucidated and described with reference to the drawings and the detailed description. The technical features of the embodiments of the present invention can be combined correspondingly without mutual conflict.
As shown in fig. 1, the present invention provides a CCHP system based on a prime mover, which mainly includes the following devices: prime mover, exhaust-heat boiler, absorption refrigerator, gas boiler and electric refrigerator. The connection mode and structure of each device will be specifically described below.
The prime mover may employ a gas turbine or an Internal Combustion Engine (ICE), which generates heat or electricity by consuming natural gas. The electricity generated by the prime mover is transmitted through the electric wire to the external power grid for powering the user, providing the system with an electrical load. The system can also meet the electricity demand of the system by purchasing electricity from the power grid, and can simultaneously integrate the surplus electric energy into the power grid when the electricity production capacity of the system is surplus. The heat energy generated by the prime mover is respectively transmitted to the waste heat boiler and the absorption refrigerator through a first pipeline, taking the prime mover adopting an internal combustion engine as an example, the heat energy generated by the internal combustion engine comprises two parts of flue gas and jacket water; the heat energy of the flue gas is higher, so the flue gas is respectively conveyed to a waste heat boiler for heating and an absorption refrigerator for refrigerating; since the thermal energy of the jacket water is low, it is only sent to the absorption refrigerator for refrigeration.
The waste heat boiler generates heat by utilizing hot flue gas, provides heat load for the system, and transmits the generated heat to a heat supply pipeline for supplying heat to users. The absorption refrigerator generates cold energy by using heat energy such as hot flue gas or jacket water and the like to provide cold load, and the generated cold energy is conveyed to a cold supply pipeline for supplying cold to users. Therefore, in the CCHP mode of the present invention, "cold" also refers to "hot" in a broad sense, since "cold" is generated by driving an absorption refrigerator by providing heat energy through a prime mover, a gas boiler, or an electric refrigerator.
The gas boiler meets the heat requirement of the system by consuming natural gas and provides the heat energy required by the cooling load for the absorption refrigerator, namely, one part of the heat energy generated by the gas boiler is transmitted to the absorption refrigerator through the second pipeline, and the other part of the heat energy is directly transmitted to the heat supply pipeline. An electric refrigerator is connected to the power grid, and cold energy generated by the electric refrigerator is conveyed to a cold supply pipeline through a third pipeline to provide cold load for the system and meet partial heat requirement of the system.
In practical application, the system can be additionally provided with a solar power generation device and a wind power generation device which are connected with a power grid as required to provide electric load for the system and meet part of electric demands of the system, so that the electric quantity and the electric expense of the system from the power grid are reduced.
The present invention provides a type selection optimization method using the above CCHP system, which is not like the prior art shown in fig. 6, and obtains the device type selection under the minimum annual net cost by respectively substituting all the prime movers in the target device library into the optimization algorithm for optimization, but substitutes the optimization algorithm for the prime mover actual performance curve with the prime mover characteristic performance curve obtained by clustering or non-clustering fitting, and can obtain the device type selection of the more accurate optimal economic index in a shorter time, and the method specifically comprises the following steps:
s1: based on the CCHP system, algorithm models of all devices in the CCHP system are respectively constructed according to the actual thermodynamic process. That is, firstly, algorithm models of a prime mover, a waste heat boiler, an absorption chiller, a gas boiler and an electric chiller are constructed, and the algorithm models of the devices mainly comprise:
1. the motor is described by taking an internal combustion engine as an example, and the specific details are as follows:
the natural gas consumption of the internal combustion engine is expressed as:
Figure BDA0003140461850000061
wherein G is the amount of natural gas consumed by the internal combustion engine in m3(ii) a P is the power generation capacity of the internal combustion engine, and the unit kW is; etaeFor internal combustion engine electrical efficiency; CV is natural gas heat value, unit kWh/m3。
2. The waste heat boiler is used as main heat production equipment of a combined cooling heating and power system, and the heat production model is as follows:
Hout，boiler＝Hin，boiler×ηboiler (12)
in the formula, Hout，boilerThe unit is kW for the heat production of the waste heat boiler; hin，boilerThe unit kW is the heat entering the waste heat boiler; etaboilerThe heat efficiency of the waste heat boiler.
3. The absorption refrigerator is a main cold producing device of a triple co-generation system, high-temperature flue gas enters the refrigerator to perform double-effect refrigeration circulation, low-temperature cylinder liner water enters the refrigerator to perform single-effect refrigeration circulation, and a mathematical model of the refrigerator can be expressed as follows:
Cout，abc＝Qex×COPdouble+Qjw×COPsingle (13)
in the formula, Cout，abcThe unit kW is the refrigerating capacity of the refrigerator; qexTo enter refrigerationThe unit kW of the smoke heat of the machine; COPdoubleThe double-effect refrigeration efficiency of the refrigerator is achieved; qjwThe unit kW is the cylinder sleeve water heat entering the refrigerator; COPsingleThe single-effect refrigeration efficiency of the refrigerator.
4. The gas boiler is used as supplementary heating equipment of a triple-generation system, and is supplemented when the waste heat boiler generates insufficient heat and stores insufficient heat, and the model is as follows:
Hout，gas_boiler＝Hin，gas_boiler×ηgas_boiler (15)
in the formula, Hout，gas_boilerThe unit is kW for the heat production of a gas boiler; hin，gas-boilerThe unit kW is the heat entering the gas boiler; etagas_boilerThe thermal efficiency is the thermal efficiency of the gas boiler.
5. The electric refrigerator is used as a supplementary cooling device of the system, and supplementary cooling is performed when the refrigerator and cold storage are insufficient, and the model is as follows:
Chp＝Ein，hp×COPhp (16)
in the formula, ChpThe unit kW is the cooling capacity produced by the electric refrigerator; ein，hpThe unit kW is the electric quantity entering the electric refrigerator; COPhpThe refrigeration efficiency of the electric refrigerator is obtained.
And constructing an energy supply model in a target operation mode according to the algorithm models of all the devices, wherein the target operation mode comprises a power-on-heating operation mode (CCHP-FEL) and a power-on-heating operation mode (CCHP-FHL).
As shown in fig. 2, the constant heat operation mode (CCHP-FEL) refers to a mode in which the CCHP system is operated to satisfy the user's electrical load demand first and then satisfy the user's heat demand. The customer heat demand includes a customer's cooling load demand and heat load demand. The method comprises the following specific steps:
s11: judging whether the total power supply capacity of the CHP system can meet the electrical load demand of a user, wherein the CHP system comprises a prime mover and a waste heat boiler; if the total power supply amount of the CHP system can meet the electrical load requirement of the user, the CHP system is used for supplying power to the user, and then the step S12 is carried out; if the total power supply amount of the CHP system can not meet the electrical load demand of the user, firstly enabling the CHP system to operate in the maximum power generation mode for supplying power, and simultaneously supplementing power to the user by the power grid, and then performing step S12;
s12: judging whether the CHP system can meet the heat demand of a user, wherein the heat demand of the user comprises the cold load demand and the heat load demand of the user; if the total heat supply quantity of the CHP system can meet the heat demand of the user, the CHP system is used for supplying heat to the user; if the total heat supply of the CHP system can not meet the heat demand of the user, the CHP system is used for supplying heat to the user, and a gas boiler and/or an electric refrigerator are/is also used for supplying heat to the user.
As shown in FIG. 3, the on-demand hot mode (CCHP-FHL mode) is a mode in which the CCHP system operates to meet the user's thermal demand first and then the user's electrical load demand. The customer heat demand includes a customer's cooling load demand and heat load demand. The method comprises the following specific steps:
s21: judging whether the total heat supply of the CHP system can meet the heat demand of a user, wherein the CHP system comprises a prime motor and a waste heat boiler, and the heat demand of the user comprises the cold load demand and the heat load demand of the user; if the total heat supply amount of the CHP system can meet the heat demand of the user, the CHP system is used for supplying heat to the user, and then the step S22 is carried out; if the total heat supply of the CHP system can not meet the heat demand of the user, firstly, the CHP system is enabled to operate in the maximum heat production mode to supply heat, and meanwhile, a gas boiler and/or an electric refrigerator are/is used for supplying heat to the user, and then the step S22 is carried out;
s22: judging whether the total power supply capacity of the CHP system can meet the electrical load requirement of a user; if the total power supply capacity of the CHP system can meet the electrical load requirement of the user, the CHP system is used for supplying power to the user; if the total power supply quantity of the CHP system can not meet the electrical load requirement of a user, the CHP system is firstly enabled to operate in the maximum power generation mode for supplying power, and meanwhile, the power grid supplies power for the user in a supplementing mode.
S2: according to the actual energy consumption load data, acquiring annual heat load demand data, annual electricity load demand data and annual cold load demand data of a user.
S3: according to the energy supply model in the target operation mode, based on the annual heat load demand data, the annual electric load demand data and the annual cold load demand data obtained in step S2, the performance curves of all the prime movers in the target prime mover equipment library are fitted to be used as the prime mover characteristic performance curves, and the optimal capacity of the prime movers is obtained through a genetic algorithm, with the minimum annual net cost C as the target. And selecting the prime mover closest to the optimal capacity of the obtained prime mover as the optimal prime mover in the target prime mover equipment library. Based on the actual capacity of the optimal prime mover and the performance characteristics in the target operation mode, the optimal capacity of the rest equipment in the CCHP system is obtained through a genetic algorithm, and the actual model selection of each equipment is determined according to the optimal capacity. The other devices in the CCHP system comprise a waste heat boiler, an absorption refrigerator, a gas boiler and an electric refrigerator. The flow of this step is shown in detail in fig. 5.
Although the optimal capacity of the prime mover is obtained in the first genetic algorithm in step S3 and the optimal capacity of the remaining devices in the CCHP system is obtained in the second genetic algorithm, in the actual operation, the data obtained by each genetic algorithm includes the prime mover capacity, the waste heat boiler capacity, the absorption chiller capacity, the gas boiler capacity, and the electric chiller capacity. That is, the optimization factors of the genetic algorithm include prime mover capacity, waste heat boiler capacity, absorption chiller capacity, gas boiler capacity, and electric chiller capacity.
The following two specific methods can be adopted for the one-step operation of fitting the performance curves of all the prime movers in the target prime mover equipment library to be used as the prime mover characteristic performance curve: the first method is that firstly, the performance curves of all the prime movers are clustered and then fit into a group of curves, and the group of curves is used as the characteristic performance curve of the prime movers, and the method is called as a cluster fitting method; the second method is to fit the performance curves of all the prime movers directly into a set of curves, which is then used as the prime mover characteristic performance curve, and this method is called non-cluster fitting method. In the present embodiment, the performance curve of the prime mover is the electrical efficiency-load rate performance curve of the prime mover, as shown in fig. 4. The clustering mode adopts a K-means clustering algorithm and is divided into two types with obvious characteristic difference, and the result shows that the classification result obtained by adopting the clustering mode is matched with the capacity distribution results of all prime motors.
The minimum annual net cost C is calculated by formulas (1) to (4), and the formulas (1) to (4) are as follows:
C＝Cin+Cop-Igr (1)
Figure BDA0003140461850000091
Cop＝∑t＝1Fe(t)×Pe+Fgas(t)×Pgas (3)
Igr＝Egr(t)×Pe' (4)
wherein C is the annual cost, unit. CinThe cost is reduced and the cost is reduced for equipment in a CCHP system. CopIs the annual operating cost of the CCHP system, unit. I isgrThe unit is the income of the CCHP system after power is on line. q is the interest rate. And n is the service life of the CCHP system in unit of year. CiUnit cost, unit/kW for unit i. RiIs the rated power of the equipment i, in kW. FeAnd (t) the electricity purchasing quantity of the CCHP system at the time t is measured in kWh. FgasAnd (t) the amount of the natural gas purchased by the CCHP system at the time t in kWh. PeFor electricity prices, unit cell/kWh. PgasIs the natural gas value, unit cell/kWh. FgrAnd (t) is the remaining power grid-connected quantity of the CCHP system at the time t, and the unit kWh. Pe‘For the price of electricity on the internet, unit cell/kWh. Wherein, the equipment i refers to all equipment in the CCHP system, including a prime mover, a waste heat boiler, an absorption chiller, a gas boiler and an electric chiller.
If the system is operating in a heat-on-electricity mode (CCHP-FEL), the CHP system is first enabled to supply system electrical demand. If the electric demand to be met is less than the minimum output limit of the CHP system, the electric demand is supplied by the power grid; and if the electricity demand to be met is not less than the output limit, operating according to a normal flow. In cold seasons, the prime motor is operated to meet the electricity demand of the user, and if the maximum electricity production quantity of the prime motor is not enough to meet the electricity demand of the user, the electricity is supplemented by a power grid; if this is the caseThe refrigerating capacity of the refrigerator is insufficient and is supplemented by the electric refrigerator and the absorption refrigerator. In the hot season, the prime motor runs to meet the electric demand of the user, the power grid supplements the heat, and if the heat production quantity of the waste heat boiler is insufficient, the heat is supplemented by the gas boiler. The heat load of the system is met by the cooperation of a prime motor, a waste heat boiler, a gas boiler, an absorption refrigerator, an electric refrigerator and the like, the total natural gas consumption of the system is the natural gas consumption of the prime motor and the gas boiler, and the economic index C for triple generation of the heat and cold systems in the CCHP-FEL mode is obtainedCCHP-FEL。
If the system operates in the CCHP-FHL mode, in order to prevent the operation load rate from being too low, the system has the lowest output limit: if the cold and heat load demand is less than the CHP system minimum output limit, then the cold and heat load is powered by the prime mover, electric chiller or absorption chiller; and if the cold and hot load requirements are not less than the output limit, operating according to a normal flow. When the power is supplied in cold seasons, the absorption refrigerator supplies power, and if the power generation amount of the prime motor is not enough to meet the electricity demand of a user, electricity is purchased from the power grid for supplement. In the heating season, the waste heat boiler operates to meet the heat demand of a user, and if the maximum heat production quantity of the waste heat boiler is insufficient, the electric refrigerator and the gas boiler are used for supplementing the heat; and if the electricity generation amount of the prime motor is not enough to meet the electricity demand of the user, the electricity is purchased by the power grid for supplement. The electric load of the system is met by the cooperation of a prime motor, a power grid and the like, the total natural gas consumption of the system is the natural gas consumption of the gas turbine and the gas boiler, and the economic index C of the triple co-generation of the heat and cold electric system in the CCHP-FHL mode is obtainedCCHP-FHL。
Example 1
In order to verify the model selection optimization effect of the method, the CCHP system is utilized to optimize and select the equipment capacity of the CCHP system for user loads of different scales in an electric heating mode, so that the lowest annual cost of the system based on a prime motor and the corresponding optimization equipment model selection combination can be obtained in the CCHP-FEL mode, and the method comprises the following specific steps:
s1: based on a CCHP system, respectively constructing an algorithm model of each device in the CCHP system according to an actual thermodynamic process; and constructing an energy supply model in the electric heating operation mode according to all algorithm models.
S2: according to the actual energy consumption load data, acquiring annual heat load demand data, annual electricity load demand data and annual cold load demand data of a user.
In the embodiment, user models of three scale demand levels of case a (310 office buildings), case b (620 office buildings) and case c (930 office buildings) are simulated based on the demand of 31 office buildings in a certain area in the Shanghai. The user load comprises year-round demand dynamic data of the user electric load, the heat load and the cold load recorded by the intelligent electric meter.
S3: based on annual heat load demand data, annual electric load demand data and annual cold load demand data, the minimum annual net cost C is taken as a target, performance curves of all prime movers in a target prime mover equipment library are fitted to be used as prime mover characteristic performance curves, and the capacity of each equipment i of the CCHP system in different energy supply models is optimized through a genetic algorithm to obtain an optimal annual net cost value and the capacity of each equipment i of the CCHP system in the operation mode. And performing actual prime mover model selection in an actual equipment library according to the prime mover predicted capacity obtained through optimization, and substituting the actual prime mover capacity and the performance characteristics into an optimization algorithm to obtain the actual model selection of other equipment i'. In the step, the performance curves of the prime motors are predicted by respectively adopting a cluster fitting mode and a non-cluster fitting mode, so that the characteristic performance curves of the prime motors under two different fitting modes can be obtained, and two different equipment type selection optimization results are further obtained.
Wherein, each device i in the CCHP system comprises a prime motor, a waste heat boiler, an absorption refrigerator, a gas boiler and an electric refrigerator. The prime motor equipment library adopts equipment information in a relevant prime motor simulation software database to obtain an equipment library with 31 kinds of prime motors in total.
In addition, for user loads of different scales, all prime movers in the equipment library are selected and substituted into the optimization algorithm according to a traversing prime mover equipment library comparison model selection method in the prior art to obtain 31 system equipment model selection schemes and the corresponding minimum annual cost, and the system model selection combination corresponding to the minimum annual cost is selected, so that the optimal actual model selection under the existing equipment can be obtained.
As can be seen from fig. 7, at the scale requirement level of case a, the optimal equipment combination optimization model using the prime mover performance curve after the polymerization fitting method makes the system economic best is 2.0MW of internal combustion engine, 0.8MW of waste heat boiler, 1.8MW of absorption refrigerator, 3.9MW of gas boiler, and 9.6MW of electric refrigerator; the performance curve of the prime motor is obtained by adopting a non-polymerization fitting method, so that the optimal equipment combination optimization model of the system is 2.0MW for the internal combustion engine, 0.8MW for the waste heat boiler, 1.9MW for the absorption refrigerator, 3.8MW for the gas boiler and 9.5MW for the electric refrigerator; the optimal equipment optimization model selection of the system by adopting the traversing prime mover equipment library comparison model selection method is 2.0MW for an internal combustion engine, 0.7MW for a waste heat boiler, 1.8MW for an absorption refrigerator, 4.0MW for a gas boiler and 9.6MW for an electric refrigerator.
Under the scale requirement level of case b, the optimal equipment combination optimization model selection of the system with the best economic efficiency is 4.5MW for the internal combustion engine, 1.8MW for the waste heat boiler, 4.3MW for the absorption refrigerator, 7.2MW for the gas boiler and 18.6MW for the electric refrigerator by using the performance curve of the prime mover after the polymerization fitting method; the performance curve of the prime motor is obtained by adopting a non-polymerization fitting method, so that the optimal equipment combination optimization model of the system is selected to be 4.3MW of an internal combustion engine, 1.6MW of a waste heat boiler, 3.8MW of an absorption refrigerator, 7.6MW of a gas boiler and 19.0MW of an electric refrigerator; the optimal equipment optimization model selection of the system by traversing the comparison model selection method of the prime mover equipment base is 5.2MW of the internal combustion engine, 1.6MW of the waste heat boiler, 4.0MW of the absorption refrigerator, 7.4MW of the gas boiler and 18.8MW of the electric refrigerator.
Under the scale requirement level of case c, the optimal equipment combination optimization model selection of the system with the best economic efficiency is 5.2MW for the internal combustion engine, 2.4MW for the waste heat boiler, 6.0MW for the absorption refrigerator, 11.8MW for the gas boiler and 28.6MW for the electric refrigerator by using the performance curve of the prime mover after the polymerization fitting method; the performance curve of the prime motor is obtained by adopting a non-polymerization fitting method, so that the optimal equipment combination optimization model of the system is 5.2MW of an internal combustion engine, 2.4MW of a waste heat boiler, 5.7MW of an absorption refrigerator, 11.4MW of a gas boiler and 28.6MW of an electric refrigerator; the optimal equipment optimization model selection of the system by traversing the comparison model selection method of the prime mover equipment base is 5.2MW of the internal combustion engine, 1.7MW of the waste heat boiler, 4.0MW of the absorption refrigerator, 13.1MW of the gas boiler and 30.2MW of the electric refrigerator.
Example 2
In order to verify the model selection optimization effect of the method, the CCHP system is utilized to optimize and select the equipment capacity of the CCHP system for user loads of different scales in a power-on-demand mode, so that the lowest annual cost of the system based on a prime motor and the corresponding optimized equipment model selection combination can be obtained in the CCHP-FHL mode. The method adopted in the embodiment is the same as that in the embodiment, and only the operation mode is changed into the operation mode of using the heat and the power.
As can be seen from fig. 8, at the scale requirement level of case a, the optimal equipment combination optimization model using the prime mover performance curve after the polymerization fitting method makes the system economic best is 2.0MW of internal combustion engine, 0.7MW of waste heat boiler, 1.8MW of absorption refrigerator, 4.1MW of gas boiler, and 9.6MW of electric refrigerator; the performance curve of the prime motor is obtained by adopting a non-polymerization fitting method, so that the optimal equipment combination optimization model of the system is 2.0MW for the internal combustion engine, 0.9MW for the waste heat boiler, 2.1MW for the absorption refrigerator, 4.0MW for the gas boiler and 9.3MW for the electric refrigerator; the optimal equipment optimization model selection of the system by adopting the traversing prime mover equipment library comparison model selection method is 2.0MW for an internal combustion engine, 0.7MW for a waste heat boiler, 1.8MW for an absorption refrigerator, 4.3MW for a gas boiler and 9.6MW for an electric refrigerator.
Under the scale requirement level of case b, the optimal equipment combination optimization model selection of the system with the best economic efficiency is 4.5MW for the internal combustion engine, 1.6MW for the waste heat boiler, 4.3MW for the absorption refrigerator, 8.3MW for the gas boiler and 18.6MW for the electric refrigerator by using the performance curve of the prime mover after the polymerization fitting method; a prime motor performance curve is obtained by adopting a non-polymerization fitting method, so that the optimal equipment combination optimization model selection of the system economy is 4.5MW of an internal combustion engine, 1.8MW of a waste heat boiler, 4.5MW of an absorption refrigerator, 8.1MW of a gas boiler and 18.4MW of an electric refrigerator; the optimal equipment optimization model selection of the system by traversing the comparison model selection method of the prime mover equipment base is 5.2MW of the internal combustion engine, 1.6MW of the waste heat boiler, 3.8MW of the absorption refrigerator, 8.7MW of the gas boiler and 19.0MW of the electric refrigerator.
Under the scale requirement level of case c, the optimal equipment combination optimization model selection of the system with the best economy is realized by using a prime mover performance curve obtained by a polymerization fitting method, wherein the optimal equipment combination optimization model selection is 5.2MW for an internal combustion engine, 2.4MW for a waste heat boiler, 5.7MW for an absorption refrigerator, 12.4MW for a gas boiler and 28.6MW for an electric refrigerator; the performance curve of the prime motor is obtained by adopting a non-polymerization fitting method, so that the optimal equipment combination optimization model of the system is 7.8MW of an internal combustion engine, 2.7MW of a waste heat boiler, 6.4MW of an absorption refrigerator, 12.1MW of a gas boiler and 27.9MW of an electric refrigerator; the optimal equipment optimization model selection of the system by traversing the comparison model selection method of the prime mover equipment base is 5.2MW of the internal combustion engine, 1.7MW of the waste heat boiler, 4.0MW of the absorption refrigerator, 13.8MW of the gas boiler and 30.2MW of the electric refrigerator.
As can be seen from the embodiments 1 and 2, the CCHP system predicts the prime mover performance curve through a clustering or non-clustering fitting mode, can effectively replace an actual performance curve to optimize system equipment, and obtains an equipment model selection result which is similar to an optimal model selection result obtained in the prior art and has good accuracy. Therefore, the model selection optimization method effectively selects the operation mode of the CCHP system, and obtains a relatively accurate optimization model selection result in a relatively short algorithm optimization time.
The above-described embodiments are merely preferred embodiments of the present invention, which should not be construed as limiting the invention. Various changes and modifications may be made by one of ordinary skill in the pertinent art without departing from the spirit and scope of the present invention. Therefore, the technical scheme obtained by adopting the mode of equivalent replacement or equivalent transformation is within the protection scope of the invention.

Claims (9)

1. A device model selection optimization method of a CCHP system based on a prime motor is characterized by comprising the following steps:
s1: respectively constructing an algorithm model of each device in the CCHP system according to the actual thermodynamic process; constructing an energy supply model in a target operation mode according to all algorithm models; the target operation mode comprises a heating operation mode and a heating operation mode;
the CCHP system comprises a prime motor, a waste heat boiler, an absorption refrigerator, a gas boiler and an electric refrigerator; the electric energy generated by the prime mover is transmitted to an external power grid through an electric wire for supplying power to a user; the heat energy generated by the prime motor is respectively transmitted to the waste heat boiler and the absorption refrigerator through a first pipeline; the heat generated by the waste heat boiler is transmitted to a heat supply pipeline for supplying heat to users; the cold energy generated by the absorption refrigerator is transmitted to a cold supply pipeline for supplying cold to users; part of the heat energy generated by the gas-fired boiler is conveyed to the absorption refrigerator through a second pipeline, and part of the heat energy is directly conveyed to a heat supply pipeline; an electric refrigerator is connected to the power grid, and the cold energy generated by the electric refrigerator is transmitted to the cold supply pipeline through a third pipeline;
s2: acquiring annual heat load demand data, annual electricity load demand data and annual cold load demand data of a user according to actual energy consumption load data;
s3: according to an energy supply model in a target operation mode, based on the annual heat load demand data, annual electricity load demand data and annual cold load demand data, with the minimum annual net cost C as a target, fitting performance curves of all prime movers in a target prime mover equipment library to be used as prime mover characteristic performance curves, and obtaining the optimal capacity of the prime movers through a genetic algorithm; selecting a prime mover closest to the prime mover optimal capacity as an optimal prime mover in a target prime mover equipment library; based on the actual capacity of the optimal prime mover and the performance characteristics in the target operation mode, the optimal capacity of the rest equipment in the CCHP system is obtained through a genetic algorithm, and the actual model selection of each equipment is determined according to the optimal capacity;
the rest devices in the CCHP system comprise a waste heat boiler, an absorption refrigerator, a gas boiler and an electric refrigerator.
2. The plant-sizing optimization method according to claim 1, wherein the prime mover is a gas turbine or an internal combustion engine.
3. The plant model selection optimization method according to claim 1, wherein the heat energy generated by the prime mover comprises flue gas and jacket water, the flue gas is respectively conveyed to the waste heat boiler and the absorption chiller, and the jacket water is conveyed to the absorption chiller.
4. The plant model selection optimization method according to claim 1, characterized in that said electric thermo mode of operation is specifically as follows:
s11: judging whether the total power supply capacity of a CHP system can meet the electric load requirement of a user, wherein the CHP system comprises a prime mover and a waste heat boiler; if the total power supply amount of the CHP system can meet the electrical load demand of the user, the CHP system is used for supplying power to the user, and then the step S12 is carried out; if the total power supply amount of the CHP system can not meet the electrical load demand of the user, firstly enabling the CHP system to operate in the maximum power generation mode for supplying power, and simultaneously supplementing power to the user by the power grid, and then performing step S12;
s12: judging whether a CHP system can meet user heat requirements, wherein the user heat requirements comprise a cold load requirement and a heat load requirement of a user; if the total heat supply of the CHP system can meet the heat demand of the user, the CHP system is used for supplying heat to the user; if the total heat supply of the CHP system can not meet the heat demand of the user, the CHP system is used for supplying heat to the user, and a gas boiler and/or an electric refrigerator are/is also used for supplying heat to the user.
5. The equipment model selection optimization method according to claim 1, wherein the operation mode with fixed temperature power is as follows:
s21: judging whether the total heat supply of a CHP system can meet the heat demand of a user, wherein the CHP system comprises a prime motor and a waste heat boiler, and the heat demand of the user comprises the cold load demand and the heat load demand of the user; if the total heat supply amount of the CHP system can satisfy the user heat demand, the CHP system is used to supply heat to the user, and then step S22 is performed; if the total heat supply amount of the CHP system cannot meet the user heat demand, firstly, the CHP system is operated to supply heat in the maximum heat generation mode, and simultaneously, a gas boiler and/or an electric refrigerator is used to supply heat to the user, and then step S22 is performed;
s22: judging whether the total power supply capacity of the CHP system can meet the electrical load requirement of a user; if the total power supply capacity of the CHP system can meet the electrical load requirement of the user, the CHP system is used for supplying power to the user; if the total power supply quantity of the CHP system can not meet the electrical load requirement of a user, the CHP system is firstly enabled to operate in the maximum power generation mode for supplying power, and meanwhile, the power grid supplies power for the user in a supplementing mode.
6. The device model selection optimization method according to claim 1, wherein the minimum annual net cost C is calculated by equations (1) to (4), and the equations (1) to (4) are as follows:
C＝Cin+Cop-Igr (1)
Figure FDA0003566978840000021
Cop＝∑t＝1Fe(t)×Pe+Fgas(t)×Pgas (3)
Igr＝Fgr(t)×Pe' (4)
wherein C is the annual cost, unit; cinThe investment cost is reduced for each device in the CCHP system, and the unit cost is obtained; copThe annual operating cost of the CCHP system is unit; i isgrThe unit is the income of the CCHP system after power is on line; q is the interest rate; n is the service life of the CCHP system in unit year; ciThe unit price of the device i is unit/kW, and the device i comprises a prime motor, a waste heat boiler, an absorption refrigerator, a gas boiler and an electric refrigerator; r isiThe rated power of the equipment i is kW; fe(t) the CCHP system purchases electric quantity at t time, and the unit kWh; fgas(t) purchasing natural gas quantity in kWh by the CCHP system at the moment t; peIs electricity price, unit cell/kWh; pgasNatural gas prices, unit cell/kWh; fgr(t) the remaining power grid-loading quantity of the CCHP system at the time t, and the unit kWh; p ise‘For on-grid electricity prices, unit cell/kWh.
7. The apparatus model selection optimization method according to claim 1, wherein in step S3, the performance curves of all the prime movers are fitted to a set of curves in a clustering manner and used as the prime mover characteristic performance curves.
8. The apparatus model selection optimization method according to claim 1 or 7, characterized in that the performance curve of the prime mover is an electrical efficiency-load rate performance curve of the prime mover.
9. The device type selection optimization method according to claim 7, wherein the clustering mode adopts a K-means clustering algorithm and is divided into two classes with obvious characteristic difference.
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