CN114648173A - Planning method of building comprehensive energy system based on multi-target ant lion algorithm - Google Patents
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Abstract
The invention discloses a planning method of a building comprehensive energy system based on a multi-target ant lion algorithm, which is applied to the field of energy planning. Establishing a mathematical model of each energy device with complementary coupling characteristics in a building comprehensive energy system of a planning scene, and simultaneously establishing power curve parameters of cooling, heating and power loads and photovoltaic and wind power generation; determining and establishing an objective function taking economic planning indexes of a planning scene as targets; constructing feasible domains for solving the objective function under the inequality constraint conditions of a cold-heat-electricity energy storage device, controllable unit power, electricity purchasing power and electricity selling power, and the equality constraint conditions which simultaneously meet the cold-heat-electricity power balance; and in the feasible domain for solving the objective function, solving the objective function by applying a multi-objective ant lion algorithm to obtain the configuration of each energy device in the building comprehensive energy system of the planning scene. The economic operation cost of the system is effectively reduced, the carbon emission is reduced, and the problem of environmental pollution to a certain degree is effectively solved.
Description
Technical Field
The invention relates to the field of energy planning, in particular to a planning method of a building comprehensive energy system based on a multi-target ant lion algorithm.
Background
In recent years, the economic development of China is rapid, and the energy demand is increasing day by day. The traditional fossil energy not only causes serious damage to the natural environment, but also cannot meet the increasing energy demand in China. Under the new trend that the energy pressure and the environmental pressure are increased continuously, a novel multi-energy complementary power system is constructed, and low-carbon power development is imperative. A Building Integrated Energy System (BIES) constructed by various energy sources such as electricity, heat, gas and the like can promote the consumption of renewable energy sources such as wind power, photoelectricity and the like, realize the interconversion of various energy sources, improve the utilization efficiency of the energy sources and have important significance for realizing carbon peak reaching and carbon neutralization.
The building comprehensive energy system is a multi-energy combined operation system, the coupling relation among different energy networks is strong, and the comprehensive energy utilization efficiency of the system can be greatly improved through complementary substitution among different energy forms. In the comprehensive energy scene planning, the capacity configuration and the power characteristic among various energy devices are planned in a lump according to the complementary coupling characteristic among different energy sources instead of the simple superposition of multiple energy sources, so that the multi-energy complementary effect is realized. Furthermore, the supporting capacity of low-grade energy on high-grade electric energy is fully developed, the interconversion of various types of energy and electric energy is promoted, the bottleneck problem that a comprehensive energy system is difficult to balance on site is solved, the construction of an energy internet in a service area is realized, and the change scientific development of an energy system in the area is promoted.
The building comprehensive energy system multi-energy planning can meet the requirements of realizing the most reasonable configuration and the maximum consumption of distributed green energy such as photovoltaic and the like under the planning target, solving the reasonable configuration capacity of storage equipment in various energy forms, effectively utilizing the peak clipping and valley filling of the multi-energy storage equipment, reducing the impact on the load peak period and improving the reliability and the safety of power supply/cold/heat supply. On one hand, the renewable energy can be effectively promoted to be developed and applied, on the other hand, the shortage of fossil energy is relieved, and the environmental pollution is reduced.
Therefore, how to provide a planning method of a comprehensive energy system of a building based on a multi-objective ant lion algorithm, which can carry out the most reasonable configuration on multi-energy resources, realize the maximum consumption of the multi-energy resources, carry out the most reasonable configuration on capacity of a multi-energy storage device and realize the peak clipping and valley filling of the multi-energy storage device, is an urgent problem to be solved by technical personnel in the field.
Disclosure of Invention
In view of the above, the invention provides a method for planning a building comprehensive energy system based on a multi-target ant lion algorithm. By adding a wind power generation system, a photoelectric renewable energy power generation system, a ground source heat pump system and an energy storage system on the basis of a traditional combined cooling heating and power system, a building comprehensive energy system which has stronger coupling relation and stronger complementary substitution among multiple energy sources and can carry out peak clipping and valley filling by using the multi-energy storage system is constructed; then, expressing each energy device in the building integrated energy system by using a mathematical model, and introducing cold and heat load prediction data and photovoltaic and wind power generation data of a typical day of a planning scene every month to construct a cold and heat load power parameter curve of the planning scene based on the mathematical model of each energy device; determining an economic planning index which takes the minimum economic and environmental maintenance cost as an economic planning index, and constructing an objective function which takes the economic planning index as a target according to each economic and environmental maintenance cost and each energy equipment mathematical model; the method comprises the steps of constructing an equality constraint condition of the power balance of cooling, heating and power according to mathematical models of energy equipment in a building integrated energy system, cooling, heating and power loads and power curve parameters of photovoltaic and wind power generation, constructing an inequality constraint condition of a cooling, heating and power energy storage device, controllable power of each unit, electricity purchasing and electricity selling power according to the mathematical models of the energy equipment in the building integrated energy system and complementary coupling characteristics among the mathematical models of the energy equipment, and constructing an equality constraint condition which simultaneously meets the power balance of the cooling, heating and power and a feasible region of solving an objective function under the inequality constraint condition of the cooling, heating and power energy storage device, the controllable power of each unit, the electricity purchasing and the electricity selling power; and in the feasible domain for solving the objective function, solving the objective function by applying a multi-objective ant lion algorithm to obtain the configuration of each energy device in the building comprehensive energy system of the planning scene. The invention not only adds a wind power generation system, a photoelectric renewable energy power generation system, a ground source heat pump system and an energy storage system on the basis of the traditional combined cooling heating and power system to construct a comprehensive energy system for construction with stronger coupling relation and stronger complementary substitution among multiple energy sources, and can utilize the multi-energy storage system to carry out peak clipping and valley filling, but also fully introduces the complementary coupling characteristic among the multiple energy source devices in a feasible domain for constructing an equation constraint condition which simultaneously meets the power balance of the cooling, heating and power and solving an objective function under the inequality constraint condition of the cooling, heating and power energy storage devices and controllable power of each unit, electricity purchasing and electricity selling power, and realizes the most reasonable configuration and maximum absorption of the multiple energy sources. Finally, practical simulation verification is carried out on buildings in certain northeast regions, and results show that the planning method of the comprehensive energy system of the buildings based on the multi-target ant lion algorithm can promote the consumption of renewable energy sources such as wind power and photoelectric energy, realize peak clipping and valley filling of power loads, effectively reduce the economic operation cost of the system, reduce carbon emission and effectively solve the problem of environmental pollution to a certain extent.
In order to achieve the purpose, the invention adopts the following technical scheme:
a planning method of a building comprehensive energy system based on a multi-target ant lion algorithm comprises the following steps:
step (1): the method comprises the steps of constructing mathematical models of energy equipment in a building comprehensive energy system of a planning scene, wherein the mathematical models of the energy equipment have complementary coupling characteristics, and simultaneously establishing cold, heat and power loads and power curve parameters of photovoltaic and wind power generation;
step (2): determining an economic planning index of a planning scene, and establishing an objective function taking the economic planning index as a target;
and (3): the method comprises the steps that an equality constraint condition of the cold-heat-electricity power balance is constructed according to mathematical models of energy equipment in a building comprehensive energy system, cold-heat-electricity loads and power curve parameters of photovoltaic power generation and wind power generation; constructing inequality constraint conditions of a cold-hot electricity energy storage device, a controllable unit power, a purchased electricity and a sold electricity power according to the mathematical models of the energy devices in the building integrated energy system and the complementary coupling characteristics among the mathematical models of the energy devices; constructing feasible domains for solving the objective function under the inequality constraint conditions of a cold-heat-electricity energy storage device, controllable unit power, electricity purchasing power and electricity selling power, and the equality constraint conditions which simultaneously meet the cold-heat-electricity power balance;
and (4): and in the feasible domain for solving the objective function, solving the objective function by applying a multi-objective ant lion algorithm to obtain the configuration of each energy device in the building comprehensive energy system of the planning scene.
Optionally, in step (1), each energy device in the building integrated energy system includes: the system comprises a gas turbine, a waste heat boiler, an absorption refrigerator, an electric boiler, a storage battery for storing energy, a cold storage tank for storing energy, a heat storage tank for storing energy, photovoltaic power generation, wind power generation, a ground source heat pump and a central air conditioner.
Optionally, in the step (1), a specific method for constructing a mathematical model of each energy device in the building integrated energy system is as follows:
the gas turbine obtains electric energy and heat energy by burning gas, and the mathematical model is as follows:
wherein, PMT(t) represents gas turbine electrical power output; hMT(t) represents gas turbine thermal power output; η MT represents the conversion efficiency of the gas turbine; kh0Represents a heating coefficient;
representing the waste heat recovery ratio; t is1、T2Represents an ambient temperature coefficient; t is0Representing an actual temperature value; qMT(t) represents the gas input power of the gas turbine; h represents the natural gas combustion condensation coefficient;
the exhaust-heat boiler obtains heat energy by absorbing the flue gas waste heat generated by the gas turbine and converting the flue gas waste heat into high-temperature steam, and the mathematical model is as follows:
PWHB(t)＝QWHB(t)ηWHBCOPWHB
wherein, PWHB(t) represents heat output power; COPWHBRepresents a heating coefficient; qWHB(t) represents the waste heat input power of the waste heat boiler; etaWHBRepresenting the conversion efficiency of the waste heat boiler;
the absorption refrigerator obtains cold energy by absorbing the steam waste heat generated by the conversion of the waste heat boiler, and the mathematical model is as follows:
PAR(t)＝QAR(t)ηARCOPAR
wherein, PAR(t) represents cold output power; qAR(t) represents the residual heat input power of the absorption refrigerator; etaARExpressing the conversion efficiency of the absorption refrigerator; COPARRepresents the refrigeration coefficient;
the electric boiler obtains heat energy by consuming electric energy, and a mathematical model is as follows:
PEB(t)＝ηEBQEB(t)
wherein, PEB(t) represents the output power of the gas boiler; etaEBRepresents the thermal efficiency of the gas boiler; qEB(t) represents gas boiler electrical input power;
the storage battery stores energy, stores electric energy when the price of electricity is low, releases electric energy when the price of electricity is high, and the mathematical model is as follows:
wherein S isES(t) represents a battery capacity; pES(t)、
Respectively representing the charging power and the charging efficiency of the storage battery; qES(t)、
Respectively representing the discharge power and the discharge efficiency of the storage battery; sigmaESExpressing the loss coefficient of the storage battery;
cold storage tank energy storage stores cold energy when the electrovalence is low, releases cold energy when the electrovalence is high, and mathematical model is as follows:
wherein M isIS(t) represents a cold storage tank capacity; pIS(t)、
Respectively representing the refrigeration power and the refrigeration efficiency of the cold accumulation tank; qIS(t)、
Respectively representing the cold discharge power and the cold discharge efficiency of the cold storage tank; sigmaISExpressing the loss coefficient of the cold accumulation tank;
the heat accumulation jar energy storage stores heat energy when the electrovalence is low, releases heat energy when the electrovalence is high, and mathematical model is as follows:
wherein HHS(t) represents the capacity of the heat storage tank; pHS(t)、
Respectively representing the heat storage power and the heat storage efficiency of the heat storage tank; qHS(t)、
Respectively representing the heat release power and the heat release efficiency of the heat storage tank; sigmaHSRepresenting the loss coefficient of the heat storage tank;
photovoltaic power generation, through photovoltaic effect with solar energy conversion electric energy, the mathematical model is as follows:
wherein, PPV(t) represents output power; pSTCRepresents the output power under standard test; gSTCRepresenting standard illumination intensity, and having a value of 1000W/m3；GPV(t)Representing the actual received illumination intensity; k represents a power temperature coefficient, and the value is-0.0047/DEG C; t isrRepresenting a reference temperature, with a value of 25 ℃; t ise(t) represents a battery temperature; t isamdRepresents the ambient temperature;
wind power generation, which converts wind energy into electric energy, and the mathematical model is as follows:
wherein, PWT(t) represents the fan output power; prRepresenting the rated power of the fan; v. ofrRepresenting the rated wind speed of the fan; v. ofciIndicating the starting working wind speed of the fan; v. ofcoIndicating the working wind speed of the fan;
the ground source heat pump converts low-grade energy in soil into high-grade heat energy or cold energy through a small amount of high-grade electric energy, and a mathematical model is as follows:
CHP(t)＝PHP(t)*copc*ZHP
QHP(t)＝PHP(t)*coph*(1-ZHP)
wherein, Php(t) represents input electric power; chp(t) represents output cold power; qhp(t) represents the output thermal power; copc represents the refrigeration coefficient; coph represents a heating coefficient; zhpThe selection of a refrigeration and heating mode is shown, when the numerical value is 0, heating is shown, and when the numerical value is 1, refrigeration is shown;
the central air conditioner obtains heat energy or cold energy by consuming electric energy, and the mathematical model is as follows:
QAC(t)＝PAC(t)ηAC
wherein Q isAC(t) represents cooling or heating power of the central air conditioner; pAC(t) a rated power consumption of the central air conditioner; etaACShowing the cooling and heating efficiency of the central air conditioner.
Optionally, in the step (2), the economic planning index is: the operation and maintenance cost and the environmental cost of the building comprehensive energy system are minimum; the operation and maintenance cost comprises the following steps: electricity purchasing and selling cost, gas purchasing cost and equipment maintenance cost; environmental costs include carbon emissions costs, nitrogen emissions costs, sulfur emissions costs.
Optionally, in the step (2), an objective function is established according to the operation and maintenance cost, the environmental cost, and a mathematical model of each energy device in the building integrated energy system, specifically:
minF＝ftoc，flcoc
wherein f istocRepresenting the cost of operation and maintenance, flcocRepresents an environmental cost;
fGAS(t)＝fGASMTPMT(t)
fPSE(t)＝fPE(t)PPE(t)-fSE(t)PSE(t)
fMU(t)＝fMTPMT(t)+fARPAR(t)+fEBPEB(t)+fWHBPWHB(t)+fPVPPV(t)+fWTPWT(t)+fHPPHP(t)+fIS(PIS(t)-QIS(t))+fHs(PHS(t)-QHS(t))+fES(PES(t)-QES(t))+fACPAC(t)
wherein T represents the total number of planning time periods; f. ofGAS(t) represents natural gas purchase cost; f. ofPSE(t) represents the cost of purchasing and selling electricity to a municipal power grid; f. ofMU(t) represents the maintenance cost of each unit of the system; f. ofGASMTRepresents the cost of natural gas consumption by the gas turbine; f. ofPE(t) represents a purchase electricity cost; f. ofSE(t) represents a cost of electricity sales; pPE(t) represents the power purchased; pSE(t) represents selling electric power; f. ofMT、fAR、fWHB、fEB、fPV、fWT、fHP、fIS、fHS、fES、fACRespectively representing the maintenance costs of a gas turbine, an absorption refrigerator, a waste heat boiler, an electric boiler, photovoltaic power generation, wind power generation, a ground source heat pump, ice storage, a heat storage tank, a storage battery and a central air conditioner;
respectively representing the environmental emission cost of CO2, NOx and SO 2;
respectively representing the environmental coefficients of electric energy emission pollution;
respectively representing the environmental coefficients of the gas emission pollution.
Optionally, in the step (3),
the equality constraint condition of the cold-heat-electricity power balance is as follows:
cold power balance:
QAC(t)+PAR(t)+CHP(t)+QIS(t)＝QCL(t)+PIS(t)
and (3) heat power balance:
PWHB(t)+PEB(t)+Qh p(t)+QAC(t)+Qh s(t)＝QHL(t)+PHS(t)
electric power balance:
PMT(t)+PPE(t)+PPV(t)+PWT(t)+QES(t)
＝PEL(t)+PSE(t)+PAC(t)+PHP(t)+PEB(t)+PES(t)
wherein QCL(t) represents a user cooling load; qHL(t) represents user thermal load; pEL(t) represents a consumer electrical load;
the inequality constraint conditions of the cold, heat and electricity energy storage device are as follows:
and (3) battery restraint:
and (3) cold storage tank restraint:
and (3) restraint of the heat storage tank:
wherein,
respectively representing the lower limit and the upper limit of the capacity of the storage battery;
respectively representing the lower limit and the upper limit of the charging power;
respectively representing the lower limit and the upper limit of the discharge power;
respectively representing the lower limit and the upper limit of the capacity of the cold accumulation tank;
respectively representing the lower limit and the upper limit of the ice making power;
respectively representing the lower limit and the upper limit of the ice melting power;
respectively representing the lower limit and the upper limit of the capacity of the heat storage tank;
respectively representing the lower limit and the upper limit of the heat storage power of the heat storage tank;
respectively representing the lower limit and the upper limit of the heat release power of the heat storage tank;
the inequality constraint conditions for controlling the power of each unit are as follows:
each controllable unit includes: the system comprises a gas turbine, a waste heat boiler, an absorption refrigerator, an electric boiler, photovoltaic power generation, wind power generation, a ground source heat pump and a central air conditioner;
wherein,
representing the lower limit of the controllable unit power;
representing the upper limit of the controllable unit; pi(t) representing the actual power of each unit;
the inequality constraint conditions of electricity purchasing and electricity selling power are as follows:
wherein,
respectively representing the lower limit and the upper limit of the power purchasing power;
respectively representing the lower limit and the upper limit of the power selling.
Optionally, in the step (4), the configuration of each energy device in the building integrated energy system for planning the scene includes: whether each energy device is configured, the configured capacity and the operating power curve of each configured energy device.
According to the technical scheme, compared with the prior art, the building comprehensive energy system planning method based on the multi-target ant lion algorithm is disclosed by the invention. According to the method, a wind power and photoelectric renewable energy power generation system, a ground source heat pump system and an energy storage system are added on the basis of a traditional combined cooling heating and power system, so that a building comprehensive energy system which is stronger in coupling relation and stronger in complementary substitution among multiple energy sources and can perform peak clipping and valley filling by using the multiple energy source energy storage system is constructed; then, expressing each energy device in the building integrated energy system by using a mathematical model, and introducing cold and heat load prediction data and photovoltaic and wind power generation data of a typical day of a planning scene every month to construct a cold and heat load power parameter curve of the planning scene based on the mathematical model of each energy device; determining an economic planning index which takes the minimum economic and environmental maintenance cost as an economic planning index, and constructing an objective function which takes the economic planning index as a target according to each economic and environmental maintenance cost and each energy equipment mathematical model; the method comprises the steps of constructing an equality constraint condition of cold-heat-electricity power balance according to mathematical models and cold-heat-electricity loads of energy equipment in a building integrated energy system and power curve parameters of photovoltaic power generation and wind power generation, constructing an inequality constraint condition of a cold-heat-electricity energy storage device, power of each controllable unit, power purchase and power sale according to complementary coupling characteristics among the mathematical models and the mathematical models of the energy equipment in the building integrated energy system, and constructing an equality constraint condition which simultaneously meets the cold-heat-electricity power balance and a feasible region of a solution objective function under the inequality constraint condition of the cold-heat-electricity energy storage device, the power of each controllable unit, the power of each purchasing and power sale; and in the feasible domain for solving the objective function, solving the objective function by applying a multi-objective ant lion algorithm to obtain the configuration of each energy device in the building comprehensive energy system of the planning scene. The invention not only adds a wind power generation system, a photoelectric renewable energy power generation system, a ground source heat pump system and an energy storage system on the basis of the traditional combined cooling heating and power system to construct a comprehensive energy system for construction with stronger coupling relation and stronger complementary substitution among multiple energy sources, and can utilize the multi-energy storage system to carry out peak clipping and valley filling, but also fully introduces the complementary coupling characteristic among the multiple energy source devices in a feasible domain for constructing an equation constraint condition which simultaneously meets the power balance of the cooling, heating and power and solving an objective function under the inequality constraint condition of the cooling, heating and power energy storage devices and controllable power of each unit, electricity purchasing and electricity selling power, and realizes the most reasonable configuration and maximum absorption of the multiple energy sources. Finally, practical simulation verification is carried out on buildings in certain northeast regions, and results show that the planning method of the comprehensive energy system of the buildings based on the multi-target ant lion algorithm can promote the consumption of renewable energy sources such as wind power and photoelectricity, realize peak clipping and valley filling of power loads, effectively reduce the economic operation cost of the system, reduce carbon emission and effectively solve the problem of environmental pollution to a certain extent.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the embodiments or the prior art descriptions will be briefly described below, it is obvious that the drawings in the following description are only embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
Fig. 1 is a schematic diagram of each energy device in the building integrated energy system of the invention.
Fig. 2 is a schematic diagram of power curve parameters of the cooling, heating and power load, photovoltaic power generation and wind power generation in embodiment 2 of the present invention.
Fig. 3 is a schematic diagram of pareto optimal front edge targeting environmental cost and operation and maintenance cost in embodiment 2 of the present invention.
Fig. 4 is a schematic diagram of electrical load balancing in embodiment 2 of the present invention.
Fig. 5 is a schematic diagram of the cooling load balancing in embodiment 2 of the present invention.
FIG. 6 is a schematic view of heat load balancing in example 2 of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example 1:
the embodiment 1 of the invention discloses a planning method of a building comprehensive energy system based on a multi-target ant lion algorithm, which comprises the following steps:
step (1): the method comprises the following steps of constructing mathematical models of all energy devices in a building comprehensive energy system of a planning scene, wherein the mathematical models of all the energy devices have complementary coupling characteristics, and the mathematical models are as follows:
as shown in fig. 1, each energy device in the building integrated energy system includes: the system comprises a gas turbine, a waste heat boiler, an absorption refrigerator, an electric boiler, a storage battery for storing energy, a cold storage tank for storing energy, a heat storage tank for storing energy, photovoltaic power generation, wind power generation, a ground source heat pump and a central air conditioner.
The gas turbine is the core of the CCHP system and is one of important energy supply devices of the whole comprehensive system energy system. The combustion gas obtains electric energy and heat energy by burning the combustion gas, and has higher combustion efficiency compared with other internal combustion engines, so the combustion gas is widely used in a comprehensive energy system, and a mathematical model is as follows:
wherein, PMT(t) represents gas turbine electrical power output; hMT(t) represents gas turbine thermal power output; etaMTRepresenting the conversion efficiency of the gas turbine; kh0Represents a heating coefficient;
representing the waste heat recovery ratio; t is1、T2Represents an ambient temperature coefficient; t is0Representing an actual temperature value; qMT(t) represents the gas input power of the gas turbine; h represents the condensation coefficient of natural gas combustion.
The exhaust-heat boiler is the important component part of CCHP system, provides heat energy for the system through the flue gas waste heat that absorbs gas turbine production and turn into high-temperature steam, great improvement the utilization efficiency of the energy, mathematical model as follows:
PWHB(t)＝QWHB(t)ηWHBCOPWHB
wherein, PWHB(t) represents heat output power; COPWHBRepresents a heating coefficient; qWHB(t) represents the waste heat input power of the waste heat boiler; etaWHBIndicating the conversion efficiency of the waste heat boiler.
The required cold energy of comprehensive energy system is prepared through the steam waste heat that absorption waste heat boiler conversion produced to the absorption refrigerator, has promoted entire system's energy utilization ratio, and the mathematical model is as follows:
PAR(t)＝QAR(t)ηARCOPAR
wherein, PAR(t) represents cold output power; qAR(t) represents the residual heat input power of the absorption refrigerator; etaARExpressing the conversion efficiency of the absorption refrigerator; COPARIndicating the refrigeration coefficient.
Electric boiler obtains heat energy through consuming electric energy, also can satisfy the user to the demand of hot water, because it need not to bind the operation with other equipment, has promoted the flexibility of system greatly, and mathematical model is as follows:
PEB(t)＝ηEBQEB(t)
wherein, PEB(t) represents the output power of the gas boiler; etaEBRepresents the thermal efficiency of the gas boiler; qEB(t) represents the gas boiler electrical input power.
The battery can be when the electrovalence is low deposit the electric energy so that the electrovalence releases the electric energy when high for the system energy supply, has improved the flexibility ratio of system, is favorable to the load of system's peak clipping to fill in the valley and the new forms of energy consumption, and mathematical model is as follows:
wherein，SES(t) represents a battery capacity; pES(t)、
Respectively representing the charging power and the charging efficiency of the storage battery; qES(t)、
Respectively representing the discharge power and the discharge efficiency of the storage battery; sigmaESThe battery loss factor is expressed.
The cold-storage tank device is the same as the storage battery, can store cold volume when the electrovalence is low so that the electrovalence releases when high for the system energy supply, and mathematical model is as follows:
wherein M isIS(t) represents a cold storage tank capacity; pIS(t)、
Respectively representing the refrigeration power and the refrigeration efficiency of the cold accumulation tank; qIS(t)、
Respectively representing the cold discharge power and the cold discharge efficiency of the cold storage tank; sigmaISThe loss coefficient of the cold storage tank is shown.
The heat storage tank has similar functions to the two devices, and the mathematical model is as follows:
wherein HHS(t) represents the capacity of the heat storage tank; pHS(t)、
Respectively representing the heat storage power and the heat storage efficiency of the heat storage tank; qHS(t)、
Respectively representing the heat release power and the heat release efficiency of the heat storage tank; sigmaHSRepresenting the loss factor of the heat storage tank.
Photovoltaic power generation converts solar energy into electric energy by utilizing a photovoltaic effect, and a mathematical model is as follows:
wherein, PPV(t) represents output power; pSTCRepresents the output power under standard test; gSTCRepresenting standard illumination intensity, and having a value of 1000W/m3；GPV(t)Representing the actual received illumination intensity; k represents a power temperature coefficient, and the value is-0.0047/DEG C; t isrRepresenting a reference temperature, with a value of 25 ℃; t ise(t) represents a battery temperature; t isamdRepresenting the ambient temperature.
Wind power generation, because wind energy has the characteristics of randomness and volatility, a fan can be influenced by factors such as wind speed and wind direction, a linear function model is adopted for simplifying analysis, and a mathematical model is as follows:
wherein, PWT(t) represents the fan output power; p isrRepresenting the rated power of the fan; v. ofrRepresenting the rated wind speed of the fan; v. ofciIndicating the starting working wind speed of the fan; v. ofcoIndicating the wind speed at which the fan stops operating.
The ground source heat pump can convert low-grade energy in the soil into high-grade heat energy or cold energy by using a small amount of high-grade electric energy for users to use. The ground source heat pump is energy-saving, efficient, green and environment-friendly, the energy efficiency ratio of the energy supply is generally close to 4.0, the conversion efficiency is very high, the emission pollution is reduced by about 70% compared with the traditional equipment such as a gas boiler, and the mathematical model is as follows:
CHP(t)＝PHP(t)*copc*ZHP
QHP(t)＝PHP(t)*coph*(1-ZHP)
wherein, Php(t) represents input electric power; chp(t) represents output cold power; qhp(t) represents the output thermal power; copc represents the refrigeration coefficient; coph represents a heating coefficient; z is a linear or branched memberhpThe selection of the cooling and heating mode is shown, the heating is shown when the numerical value is 0, and the cooling is shown when the numerical value is 1.
The central air conditioner is an indispensable device in a building, has high flexibility and good user experience, and adopts the following mathematical models:
QAC(t)＝PAC(t)ηAC
wherein Q isAC(t) represents cooling or heating power of the central air conditioner; pAC(t) represents rated power consumption of the central air conditioner; etaACShowing the cooling and heating efficiency of the central air conditioner.
And meanwhile, the cold, heat and power loads and power curve parameters of photovoltaic and wind power generation are established.
Step (2): determining an economic planning index of a planning scene, and establishing an objective function taking the economic planning index as a target, wherein the economic planning index is as follows:
the energy planning of the building integrated energy system is a multi-objective planning problem, when the operation cost of the system is considered, not only the economy but also the low-carbon and environment-friendly environmental problem need to be considered, and the objective function also needs to comprehensively consider two aspects of the economy and the environment. The minimum operation and maintenance cost and the minimum environmental cost of the building comprehensive energy system are taken as objective functions, the operation and maintenance cost comprises electricity purchasing and selling cost, gas purchasing cost and equipment maintenance cost, and the environmental cost comprises carbon emission cost, nitrogen emission cost and sulfur emission cost.
Establishing an objective function according to the operation and maintenance cost, the environment cost and a mathematical model of each energy device in the building comprehensive energy system, which specifically comprises the following steps:
minF＝ftoc，flcoc
wherein f istocRepresenting the cost of operation and maintenance, flcocRepresenting the cost of the environment.
fGAS(t)＝fGASMTPMT(t)
fPSE(t)＝fPE(t)PPE(t)-fSE(t)PSE(t)
fMU(t)＝fMTPMT(t)+fARPAR(t)+fEBPEB(t)+fWHBPWHB(t)+fPVPPV(t)+fWTPWT(t)+fHPPHP(t)+fIS(PIS(t)-QIS(t))+fHS(PHS(t)-QHS(t))+fES(PES(t)-QES(t))+fACPAC(t)
Wherein T represents the total number of planning time periods; f. ofGAS(t) represents natural gas purchase cost; f. ofPSE(t) represents the cost of purchasing and selling electricity to a municipal power grid; f. ofMU(t) represents the maintenance cost of each unit of the system; f. ofGASMTRepresents the cost of natural gas consumption by the gas turbine; f. ofPE(t) represents a purchase cost of electricity; f. ofSE(t) represents a cost of electricity sales; p isPE(t) represents the power purchased; pSE(t) represents selling electric power; f. ofMT、fAR、fWHB、fEB、fPV、fWT、fHP、fIS、fHS、fES、fACRespectively representing a gas turbine, an absorption refrigerator, a waste heat boiler, an electric boiler, photovoltaic power generation, wind power generation, a ground source heat pump, an ice storage and a heat storage tankMaintenance costs of the storage battery and the central air conditioner;
respectively representing the environmental emission cost of CO2, NOx and SO 2;
respectively representing the environmental coefficients of electric energy emission pollution;
respectively representing the environmental coefficients of the gas emission pollution.
And (3): the method comprises the steps that an equality constraint condition of the cold-heat-electricity power balance is constructed according to mathematical models of energy equipment in a building comprehensive energy system, cold-heat-electricity loads and power curve parameters of photovoltaic power generation and wind power generation; constructing inequality constraint conditions of a cold-hot electricity energy storage device, a controllable unit power, a purchased electricity and a sold electricity power according to the mathematical models of the energy devices in the building integrated energy system and the complementary coupling characteristics among the mathematical models of the energy devices; the feasible domain for solving the objective function under the inequality constraint conditions of the cold, heat and electricity energy storage device, the controllable power of each unit, the electricity purchasing power and the electricity selling power and simultaneously meeting the equality constraint conditions of the cold, heat and electricity power balance is constructed as follows:
the equality constraint condition of the cold-heat-electricity power balance is as follows:
cold power balance:
QAC(t)+PAR(t)+CHP(t)+QIS(t)＝QCL(t)+PIS(t)
and (3) heat power balance:
PWHB(t)+PEB(t)+Qh p(t)+QAC(t)+Qh s(t)＝QHL(t)+PHS(t)
electric power balance:
PMT(t)+PPE(t)+PPV(t)+PWT(t)+QES(t)
＝PEL(t)+PSE(t)+PAC(t)+PHP(t)+PEB(t)+PES(t)
wherein Q isCL(t) represents a user cooling load; qHL(t) represents user thermal load; p isEL(t) represents the consumer electrical load.
The inequality constraint conditions of the cold, heat and electricity energy storage device are as follows:
and (3) battery restraint:
and (3) cold storage tank restraint:
and (3) restraint of the heat storage tank:
wherein,
respectively representing the lower limit and the upper limit of the capacity of the storage battery;
respectively representing the lower limit and the upper limit of the charging power;
respectively representing the lower limit and the upper limit of the discharge power;
respectively representing the lower limit and the upper limit of the capacity of the cold accumulation tank;
respectively representing the lower limit and the upper limit of the ice making power;
respectively representing the lower limit and the upper limit of the ice melting power;
respectively representing the lower limit and the upper limit of the capacity of the heat storage tank;
respectively representing the lower limit and the upper limit of the heat storage power of the heat storage tank;
respectively representing the lower limit and the upper limit of the heat release power of the heat storage tank.
The inequality constraint conditions for controlling the power of each unit are as follows:
each controllable unit includes: the system comprises a gas turbine, a waste heat boiler, an absorption refrigerator, an electric boiler, photovoltaic power generation, wind power generation, a ground source heat pump and a central air conditioner.
Wherein,
representing the lower limit of the controllable unit power;
representing the upper limit of the controllable unit; pi (t) represents the actual power of each unit.
The inequality constraint conditions of electricity purchasing and electricity selling power are as follows:
wherein,
respectively representing the lower limit and the upper limit of the power purchasing power;
respectively representing the lower limit and the upper limit of the power selling.
And (4): in the feasible domain of solving the objective function, the objective function is solved by applying a multi-objective ant lion algorithm to obtain the configuration of each energy device in the building comprehensive energy system of the planning scene, and the method comprises the following steps: whether each energy device is configured, the configured capacity and the operating power curve of each configured energy device.
The invention discloses a planning method of a building comprehensive energy system based on a multi-target ant lion algorithm. According to the method, a wind power and photoelectric renewable energy power generation system, a ground source heat pump system and an energy storage system are added on the basis of a traditional combined cooling heating and power system, so that a building comprehensive energy system which is stronger in coupling relation among multiple energy sources and stronger in complementary substitution and can perform peak clipping and valley filling by using the multi-energy storage system is constructed; then, expressing each energy device in the building integrated energy system by using a mathematical model, and introducing cold and heat load prediction data and photovoltaic and wind power generation data of a typical day of a planning scene every month to construct a cold and heat load power parameter curve of the planning scene based on the mathematical model of each energy device; determining an economic planning index which takes the minimum economic and environmental maintenance cost as an economic planning index, and constructing an objective function which takes the economic planning index as a target according to each economic and environmental maintenance cost and each energy equipment mathematical model; the method comprises the steps of constructing an equality constraint condition of the power balance of cooling, heating and power according to mathematical models of energy equipment in a building integrated energy system, cooling, heating and power loads and power curve parameters of photovoltaic and wind power generation, constructing an inequality constraint condition of a cooling, heating and power energy storage device, controllable power of each unit, electricity purchasing and electricity selling power according to the mathematical models of the energy equipment in the building integrated energy system and complementary coupling characteristics among the mathematical models of the energy equipment, and constructing an equality constraint condition which simultaneously meets the power balance of the cooling, heating and power and a feasible region of solving an objective function under the inequality constraint condition of the cooling, heating and power energy storage device, the controllable power of each unit, the electricity purchasing and the electricity selling power; and in the feasible region for solving the objective function, solving the objective function by applying a multi-objective ant lion algorithm to obtain the configuration of each energy device in the building comprehensive energy system of the planning scene. The invention not only adds a wind power generation system, a photoelectric renewable energy power generation system, a ground source heat pump system and an energy storage system on the basis of the traditional combined cooling heating and power system to construct a comprehensive energy system for construction with stronger coupling relation and stronger complementary substitution among multiple energy sources, and can utilize the multi-energy storage system to carry out peak clipping and valley filling, but also fully introduces the complementary coupling characteristic among the multiple energy source devices in a feasible domain for constructing an equation constraint condition which simultaneously meets the power balance of the cooling, heating and power and solving an objective function under the inequality constraint condition of the cooling, heating and power energy storage devices and controllable power of each unit, electricity purchasing and electricity selling power, and realizes the most reasonable configuration and maximum absorption of the multiple energy sources.
Example 2:
in embodiment 2 of the present invention, actual simulation verification is performed on buildings in a northeast area, and on the basis of the mathematical model of each energy device with complementary coupling characteristics in the building integrated energy system of the planning scene constructed in step (1), the cold and thermal load prediction data and the photovoltaic and wind power generation data of the northeast area on a typical day per month are substituted to obtain the cold and thermal load and the photovoltaic and wind power generation power curve parameters of the northeast area, as shown in fig. 2.
Establishing a digital model of an objective function according to the operation and maintenance cost, the environmental cost and the mathematical model of each energy device in the building integrated energy system in the step (2), and establishing an equality constraint condition of the cold-heat-electricity power balance according to the mathematical model of each energy device in the building integrated energy system, the cold-heat-electricity load and the power curve parameters of photovoltaic power generation and wind power generation in the step (3); constructing inequality constraint conditions of a cold, heat and electricity energy storage device, controllable power of each unit, electricity purchasing power and electricity selling power according to mathematical models of each energy device in the building comprehensive energy system and complementary coupling characteristics among the mathematical models of each energy device; and on the basis of constructing a feasible domain digital model for solving an objective function under the inequality constraint conditions of a cold, heat and power energy storage device, controllable unit power, electricity purchasing and electricity selling power and simultaneously meeting the equality constraint conditions of cold, heat and power balance, substituting the feasible domain digital model into the northeast region and the corresponding parameter values in the digital model.
In the feasible domain of solving the objective function in the northeast region, the objective function is solved by applying a multi-objective ant lion algorithm to obtain A, B, C three configuration modes. And performing optimization planning according to the new energy power, the parameters of each device of the system, the electric energy price, the environmental penalty and other data, wherein the pareto optimal front edge with the environmental cost and the operation and maintenance cost as targets is shown in fig. 3. It can be seen that the higher the operation and maintenance cost is, the lower the environmental cost is, and the power configuration scheme of the system device cannot simultaneously minimize the two costs, which indicates that the environmental cost and the operation and maintenance cost are contradictory. Considering the situations of lowest and highest environmental cost and operation and maintenance cost, the whole solution set is divided into three typical modes, namely an A mode with the highest environmental cost, a C mode with the highest operation and maintenance cost and a B mode with the intermediate environmental cost and operation and maintenance cost. The analysis was performed for three typical cost patterns, and table 1 is a comparative analysis of the cost of the three typical patterns. The method comprises the following steps of firstly analyzing the type A, wherein the type A has the highest environmental cost and the lowest running cost among the three types, and in the mode, the CCHP unit has less power, more energy is purchased from a power grid, and less consumed new energy is used for generating electricity; the C type has the lowest environmental cost and the highest operation cost among the three types, and under the mode, the system has less energy purchase from a power grid, and the CCHP unit has more power and consumes more new energy to generate electricity; the B type is between the A type and the C type, and the environmental cost and the operation cost are lower than those of the other two types, wherein the environmental cost is reduced by 52.8 percent compared with the A type, the operation cost is reduced by 7.6 percent compared with the C type, the total cost is reduced by 8.2 percent compared with the C type, and the total cost is reduced by 3.9 percent compared with the A type. And combining the environmental and economic comprehensive consideration, wherein the type B is the optimal solution.
Table 1: A. b, C model cost comparison
The type B planning results are analyzed in combination with the above analysis, and the electrical load balance diagram, the cold load balance diagram, and the heat load balance diagram are shown in fig. 4, 5, and 6.
In fig. 4, due to the high electric energy quality and stable energy supply effect of the municipal power grid, most of the power supply of the building is supplied by the municipal power grid, and the micro gas turbine and the renewable energy source are responsible for supplying the rest of the power supply. The micro gas turbine has relatively low maintenance cost, can operate all the time and has stable power, the storage battery stores electric quantity under the condition of low electricity price or surplus power supply so as to be called when the power supply price is high, the wind power and the photoelectric consumption conditions are good, the power of the photoelectric generator is most obvious when the photoelectric generator is 11 hours to 14 hours, the consumption condition is the best, and the wind power consumption effect is relatively stable all day long.
In fig. 5 it can be seen that the heat load is mainly provided by the waste heat boiler, and a small part by the electric boiler, and that the power of the waste heat boiler is determined by the micro gas turbine, which is more power evident at 0-8 and 20-24 hours, so that the waste heat boiler bears most of the heat load at 0-8 and 20-24 hours.
In fig. 6, it can be seen that the cooling of the system is supplied mainly by the ground source heat pump, absorption refrigerator and cold storage tank at 0-8, and the central air conditioner supplies most of the cooling energy at 10-14 and 17-20, because the cooling load is peaked throughout the day and a stable and efficient supply is required. The power of the absorption refrigerator is also determined by the micro gas turbine, so the energy supply effect is stable. The ground source heat pump has stable cold supply effect, can consume the electric power generated by the renewable energy source and convert the electric power into cold energy, and promotes the consumption of the renewable energy source. The cold accumulation tank can store cold when the system supplies cold enough for later planning.
The configuration of each energy device in the building integrated energy system finally obtaining the planning scene, as shown in fig. 4, 5, and 6, includes: whether each energy device is configured, the configured capacity and the operating power curve of each configured energy device.
The multi-energy planning actual simulation verification result of buildings in certain northeast China shows that: the planning method of the comprehensive energy system for the building based on the multi-target ant lion algorithm can promote the consumption of renewable energy sources such as wind power, photoelectricity and the like, realize peak clipping and valley filling of power load, effectively reduce the economic operation cost of the system, reduce carbon emission and effectively solve the problem of environmental pollution to a certain extent.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. The device disclosed by the embodiment corresponds to the method disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the method part for description.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (7)
1. A planning method of a building comprehensive energy system based on a multi-target ant lion algorithm is characterized by comprising the following steps:
step (1): the method comprises the steps of constructing mathematical models of energy equipment in a building comprehensive energy system of a planning scene, wherein the mathematical models of the energy equipment have complementary coupling characteristics, and simultaneously establishing cold, heat and power loads and power curve parameters of photovoltaic and wind power generation;
step (2): determining an economic planning index of the planning scene, and establishing an objective function taking the economic planning index as a target;
and (3): constructing an equality constraint condition of the power balance of the cooling, heating and power according to mathematical models of energy equipment in the building comprehensive energy system, the cooling, heating and power loads and power curve parameters of the photovoltaic power generation and the wind power generation; constructing inequality constraint conditions of a cold-hot electricity energy storage device, a controllable unit power, a purchased electricity and a sold electricity power according to the mathematical models of the energy devices in the building integrated energy system and the complementary coupling characteristics among the mathematical models of the energy devices; constructing feasible domains for solving the objective function under the equality constraint condition which simultaneously meets the power balance of the cold, heat and electricity and the inequality constraint condition of the cold, heat and electricity energy storage device, the power of each controllable unit, the electricity purchasing power and the electricity selling power;
and (4): and in the feasible domain for solving the objective function, solving the objective function by applying a multi-objective ant lion algorithm to obtain the configuration of each energy device in the building comprehensive energy system of the planning scene.
2. The method for planning the integrated energy system for buildings based on the multi-objective ant lion algorithm according to claim 1, wherein in the step (1), each energy device in the integrated energy system for buildings comprises: the system comprises a gas turbine, a waste heat boiler, an absorption refrigerator, an electric boiler, a storage battery for storing energy, a cold storage tank for storing energy, a heat storage tank for storing energy, photovoltaic power generation, wind power generation, a ground source heat pump and a central air conditioner.
3. The method for planning the comprehensive energy system for the building based on the multi-target ant lion algorithm according to the claim 2, wherein in the step (1), the specific method for constructing the mathematical model of each energy device in the comprehensive energy system for the building is as follows:
the gas turbine obtains electric energy and heat energy by burning gas, and the mathematical model is as follows:
wherein, PMT(t) represents gas turbine electrical power output; hMT(t) represents gas turbine thermal power output; etaMTRepresents the conversion efficiency of the gas turbine; kh0Represents a heating coefficient;
representing the waste heat recovery ratio; t is1、T2Represents an ambient temperature coefficient; t is0Representing an actual temperature value; qMT(t) represents the gas input power of the gas turbine; h represents the natural gas combustion condensation coefficient;
the exhaust-heat boiler obtains heat energy by absorbing the flue gas waste heat generated by the gas turbine and converting the flue gas waste heat into high-temperature steam, and the mathematical model is as follows:
PWHB(t)＝QWHB(t)ηWHBCOPWHB
wherein, PWHB(t) represents heat output power; COPWHBRepresents a heating coefficient; qWHB(t) represents the input power of the waste heat boiler; etaWHBRepresenting the conversion efficiency of the waste heat boiler;
the absorption refrigerator obtains cold energy by absorbing the steam waste heat generated by the conversion of the waste heat boiler, and the mathematical model is as follows:
PAR(t)＝QAR(t)ηARCOPAR
wherein, PAR(t) represents cold output power; qAR(t) represents the residual heat input power of the absorption refrigerator; etaARExpressing the conversion efficiency of the absorption refrigerator; COPARRepresents the refrigeration coefficient;
the electric boiler obtains heat energy by consuming electric energy, and a mathematical model is as follows:
PEB(t)＝ηEBQEB(t)
wherein, PEB(t) represents the output power of the gas boiler; etaEBRepresents the thermal efficiency of the gas boiler; qEB(t) represents gas boiler electrical input power;
the storage battery stores energy, stores electric energy when the price of electricity is low, releases electric energy when the price of electricity is high, and the mathematical model is as follows:
wherein S isES(t) represents a battery capacity; pES(t)、
Respectively representing the charging power and the charging efficiency of the storage battery; qES(t)、
Respectively representing the discharge power and the discharge efficiency of the storage battery; sigmaESRepresenting the loss coefficient of the storage battery;
cold storage tank energy storage stores cold energy when the electrovalence is low, releases cold energy when the electrovalence is high, and mathematical model is as follows:
wherein M isIS(t) represents a cold storage tank capacity; pIS(t)、
Respectively showing the refrigeration power and the refrigeration efficiency of the cold accumulation tank; qIS(t)、
Respectively representing the cold discharge power and the cold discharge efficiency of the cold storage tank; sigmaISExpressing the loss coefficient of the cold accumulation tank;
the heat accumulation jar energy storage stores heat energy when the electrovalence is low, releases heat energy when the electrovalence is high, and mathematical model is as follows:
wherein HHS(t) represents the capacity of the heat storage tank; pHS(t)、
Respectively representing the heat storage power and the heat storage efficiency of the heat storage tank; qHS(t)、
Respectively representing the heat release power and the heat release efficiency of the heat storage tank; sigmaHSRepresenting the loss coefficient of the heat storage tank;
photovoltaic power generation, through photovoltaic effect with solar energy conversion electric energy, the mathematical model is as follows:
wherein, PPV(t) represents output power; pSTCRepresents the output power under standard test; gSTCRepresenting standard illumination intensity, and having a value of 1000W/m3；GPV(t) represents the actual received illumination intensity; k represents a power temperature coefficient, and the value is-0.0047/DEG C; t isrRepresenting a reference temperature, with a value of 25 ℃; t ise(t) represents a battery temperature; t isamdRepresents the ambient temperature;
wind power generation, which converts wind energy into electric energy, and the mathematical model is as follows:
wherein, PWT(t) represents the fan output power; prRepresenting the rated power of the fan; v isrRepresenting the rated wind speed of the fan; v. ofciIndicating the starting working wind speed of the fan; v iscoIndicating the working wind speed of the fan;
the ground source heat pump converts low-grade energy in soil into high-grade heat energy or cold energy through a small amount of high-grade electric energy, and a mathematical model is as follows:
CHP(t)＝PHP(t)*copc*ZHP
QHP(t)＝PHP(t)*coph*(1-ZHP)
wherein, Php(t) represents input electric power; chp(t) represents output cold power; qhp(t) represents the output thermal power; copc represents the refrigeration coefficient; coph represents a heating coefficient; z is a linear or branched memberhpThe selection of a refrigeration and heating mode is shown, when the numerical value is 0, heating is shown, and when the numerical value is 1, refrigeration is shown;
the central air conditioner obtains heat energy or cold energy by consuming electric energy, and the mathematical model is as follows:
QAC(t)＝PAC(t)ηAC
wherein Q isAC(t) represents cooling or heating power of the central air conditioner; pAC(t) represents rated power consumption of the central air conditioner; etaACShowing the cooling and heating efficiency of the central air conditioner.
4. The method for planning the comprehensive energy system for the building based on the multi-objective ant lion algorithm as claimed in claim 3, wherein in the step (2), the economic planning indexes are as follows: the operation and maintenance cost and the environmental cost of the building comprehensive energy system are minimum; the operational maintenance costs include: electricity purchasing and selling cost, gas purchasing cost and equipment maintenance cost; the environmental costs include carbon emission costs, nitrogen emission costs, sulfur emission costs.
5. The method for planning the comprehensive energy system for the building based on the multi-objective ant lion algorithm as claimed in claim 4, wherein in the step (2), the objective function is established according to the operation and maintenance cost, the environmental cost and a mathematical model of each energy device in the comprehensive energy system for the building, specifically:
minF＝ftoc，flcoc
wherein f istocRepresenting the cost of operation and maintenance, flcocRepresents an environmental cost;
fGAS(t)＝fGASMTPMT(t)
fPSE(t)＝fPE(t)PPE(t)-fSE(t)PSE(t)
fMU(t)＝fMTPMT(t)+fARPAR(t)+fEBPEB(t)+fWHBPWHB(t)+fPVPPV(t)+fWTPWT(t)+fHPPHP(t)+fIS(PIS(t)-QIS(t))+fHS(PHS(t)-QHS(t))+fES(PES(t)-QES(t))+fACPAC(t)
wherein T represents the total number of planning time periods; f. ofGAS(t) represents natural gas purchase cost; f. ofPSE(t) represents the cost of purchasing and selling electricity to a municipal power grid; f. ofMU(t) represents the maintenance cost of each unit of the system; f. ofGASMTRepresents the cost of natural gas consumption by the gas turbine; f. ofPE(t) represents a purchase cost of electricity; f. ofSE(t) represents a cost of electricity sales; pPE(t) represents the power purchased; p isSE(t) represents selling electric power; f. ofMT、fAR、fWHB、fEB、fPV、fWT、fHP、fIS、fHS、fES、fACRespectively representing the maintenance costs of a gas turbine, an absorption refrigerator, a waste heat boiler, an electric boiler, photovoltaic power generation, wind power generation, a ground source heat pump, ice storage, a heat storage tank, a storage battery and a central air conditioner;
respectively representing the environmental emission cost of CO2, NOx and SO 2;
respectively representing the environmental coefficients of electric energy emission pollution;
respectively representing the environmental coefficients of the gas emission pollution.
6. The method for planning the comprehensive energy system for buildings based on the multi-objective ant lion algorithm as claimed in claim 5, wherein in the step (3),
the equality constraint condition of the cold, heat and electricity power balance is as follows:
cold power balance:
QAC(t)+PAR(t)+CHP(t)+QIS(t)＝QCL(t)+PIS(t)
and (3) heat power balance:
PWHB(t)+PEB(t)+Qhp(t)+QAC(t)+Qhs(t)＝QHL(t)+PHS(t)
electric power balance:
PMT(t)+PPE(t)+PPV(t)+PWT(t)+QES(t)
＝PEL(t)+PSE(t)+PAC(t)+PHP(t)+PEB(t)+PES(t)
wherein Q isCL(t) represents a user cooling load; qHL(t) represents user thermal load; pEL(t) represents a consumer electrical load;
the inequality constraint conditions of the cold, heat and electricity energy storage device are as follows:
and (3) battery restraint:
and (3) cold storage tank restraint:
and (3) restraint of the heat storage tank:
wherein,
respectively representing the lower limit and the upper limit of the capacity of the storage battery;
respectively representing the lower limit and the upper limit of the charging power;
respectively representing the lower limit and the upper limit of the discharge power;
respectively representing the lower limit and the upper limit of the capacity of the cold accumulation tank;
respectively representing the lower limit and the upper limit of the ice making power;
respectively representing the lower limit and the upper limit of the ice melting power;
respectively representing the lower limit and the upper limit of the capacity of the heat storage tank;
respectively representing the lower limit and the upper limit of the heat storage power of the heat storage tank;
respectively representing the lower limit and the upper limit of the heat release power of the heat storage tank;
the inequality constraint conditions of the controllable power of each unit are as follows:
each controllable unit includes: the system comprises a gas turbine, a waste heat boiler, an absorption refrigerator, an electric boiler, photovoltaic power generation, wind power generation, a ground source heat pump and a central air conditioner;
wherein,
representing the lower limit of the controllable unit power;
representing the upper limit of the controllable unit; pi(t) representing the actual power of each unit;
the inequality constraint conditions of the electricity purchasing power and the electricity selling power are as follows:
wherein,
respectively representing the lower limit and the upper limit of the purchased power;
respectively representing the lower limit and the upper limit of the power selling.
7. The method for planning the comprehensive energy system for the building based on the multi-objective ant lion algorithm according to claim 1, wherein in the step (4), the configuration of each energy device in the comprehensive energy system for the building of the planning scenario includes: whether each energy device is configured, the configured capacity and the operating power curve of each configured energy device.
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