CN112182887A - Comprehensive energy system planning optimization simulation method - Google Patents

Comprehensive energy system planning optimization simulation method Download PDF

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CN112182887A
CN112182887A CN202011055709.3A CN202011055709A CN112182887A CN 112182887 A CN112182887 A CN 112182887A CN 202011055709 A CN202011055709 A CN 202011055709A CN 112182887 A CN112182887 A CN 112182887A
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王若愚
邵志奇
蔡京陶
叶键民
毛森茂
王卿玮
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Abstract

本发明涉及一种综合能源系统规划优化仿真方法，包括：步骤S1，根据能源特性，建立基于EQC的

Figure DDA0002710814300000011
效率分析模型；步骤S2，根据综合能源系统多能耦合分析，建立四层能量中心模型；步骤S3，根据综合能源系统中的非凸因素，建立改进的凸规划模型；步骤S4，根据经济性和
Figure DDA0002710814300000012
效率建立综合能源系统规划优化模型。本发明以经济性和
Figure DDA0002710814300000013
效率为目标的多目标规划优化，在能源综合利用过程中实现了质的匹配，在各方面都达到了性能的综合平衡。

Figure 202011055709

The invention relates to a comprehensive energy system planning optimization simulation method, comprising: step S1, establishing an EQC-based system according to energy characteristics

Figure DDA0002710814300000011
Efficiency analysis model; step S2, establishing a four-layer energy center model according to the multi-energy coupling analysis of the integrated energy system; step S3, establishing an improved convex programming model according to the non-convex factors in the integrated energy system; step S4, according to the economic and
Figure DDA0002710814300000012
Efficiency Establish a comprehensive energy system planning optimization model. The present invention is economical and
Figure DDA0002710814300000013
The multi-objective planning optimization with efficiency as the goal achieves qualitative matching in the process of comprehensive energy utilization, and achieves a comprehensive balance of performance in all aspects.

Figure 202011055709

Description

Comprehensive energy system planning optimization simulation method
Technical Field
The invention relates to the technical field of energy, in particular to a comprehensive energy system planning optimization simulation method.
Background
Today, with increasingly severe global energy situation, it is an urgent need to realize economic, efficient, safe and clean utilization of energy resources. Therefore, Integrated Energy Systems (IES) are introduced as a potential solution to future energy problems. The IES can coordinate operation and management of various new energy sources in a unified manner, the effect of complementation and mutual assistance of various energy sources is achieved, and complementary advantages of various energy source forms, such as electric power, natural gas, heating and cooling, are reflected. Energy conservation, emission reduction and maximized renewable energy utilization are requirements for establishing a comprehensive energy system, and the economic efficiency of the whole planning result must be considered when the comprehensive energy system is reasonably planned and designed. Meanwhile, improving the comprehensive utilization level of energy is always the core goal of the optimization design of the comprehensive energy system, which requires accurate evaluation of energy efficiency.
Scholars at home and abroad have partial research on energy efficiency, Huangzi Shuo et al propose a dimension-expression for calculating the comprehensive energy efficiency of the system, and determine that the technical level of energy conversion, the structure of cold, heat and electricity requirements and the like are key factors influencing the comprehensive energy efficiency of the system; the steam shunt et al considers the multi-energy flow characteristics of the system and the intervention influence of renewable energy sources and provides a comprehensive energy utilization rate index suitable for the energy efficiency evaluation of the multi-energy collaborative park; guo Yanfei et al have established different types of comprehensive energy system energy analysis and
Figure BDA0002710814280000011
analyzing the mathematical model to obtain the result by experiment
Figure BDA0002710814280000012
The analytical method is the most effective method for evaluating the thermal efficiency of the system. At present, the research on the overall energy efficiency of the multi-energy complementary distributed energy system is still less discussed at home and abroad.
Currently, on the one hand, the conventional energy efficiency method widely applied to the power system ignores the difference in quality of the multiple energy forms due to the lack of a proper standard for measuring the comprehensive energy utilization level of the industrial enterprise, and thus the conventional energy efficiency method is not suitable for the multi-energy coupling field. On the other hand, the planning and research of the comprehensive energy system lacks the joint planning of an energy generator and an energy storage device and an efficient solution thereof. In the past, the mutual coupling relation of multiple energy sources in the system is neglected for focusing on the action performance of single energy source, and if the global optimality of the result cannot be guaranteed by continuously adopting the past system planning, the traditional method needs to be optimized, and a simulation model suitable for the future comprehensive energy source system is provided.
Disclosure of Invention
The technical problem to be solved by the invention is to provide a multi-objective optimization comprehensive energy system planning optimization simulation method aiming at economic optimization and highest energy utilization efficiency on the basis of meeting the load requirements of users.
In order to solve the technical problem, the invention provides an optimization simulation method for a comprehensive energy system planning, which comprises the following steps:
step S1, establishing EQC-based according to energy characteristics
Figure BDA0002710814280000021
An efficiency analysis model;
step S2, establishing a four-layer energy center model according to the multi-energy coupling analysis of the comprehensive energy system;
step S3, establishing an improved convex planning model according to non-convex factors in the comprehensive energy system;
step S4, based onEconomic efficiency and
Figure BDA0002710814280000022
and (4) establishing a comprehensive energy system planning optimization model.
Further, the step S1 specifically includes:
step S11, establishing
Figure BDA0002710814280000023
An efficiency analysis model;
step S12, respectively calculating the total input of the comprehensive energy system
Figure BDA0002710814280000024
And sum of outputs
Figure BDA0002710814280000025
Further, established
Figure BDA0002710814280000026
The calculation formula of the efficiency analysis model is as follows:
F2＝Nx0/Nxi＝(Nx0 E+Nx0 T+Nx0 C)/(Nxi EPet+Nxi Gas+Nxi solar)
wherein: nx0For the total output of the integrated energy system
Figure BDA0002710814280000027
The units are MJ, NxiFor the total input of the integrated energy system
Figure BDA0002710814280000028
The unit is MJ; general of integrated energy system input
Figure BDA0002710814280000029
The method comprises the following steps: corresponding to purchased electric quantity
Figure BDA00027108142800000210
Value Nxi EPetCorresponding to the natural gas consumed
Figure BDA00027108142800000211
Value Nxi GasCorresponding to photovoltaic power generation
Figure BDA00027108142800000212
Value Nxi solarCorresponding to fan generation
Figure BDA00027108142800000213
Value Nxi Pw(ii) a Total output of comprehensive energy system
Figure BDA00027108142800000214
The method comprises the following steps: output corresponding to cold load
Figure BDA00027108142800000215
Nx0 cOutput corresponding to thermal load
Figure BDA00027108142800000216
Nx0 tOutputs corresponding to the electric loads respectively
Figure BDA00027108142800000217
Nx0 E。
Further, the total input of the integrated energy system
Figure BDA00027108142800000218
And sum of outputs
Figure BDA00027108142800000219
The calculation formula of (2) is as follows:
Nxi EPet＝3600×QEPet
Nxi Gas＝QGasTA
Nxi solar＝Σ[QSolarS(1-TE/TSolar)Δt/106]
Nx0 E＝QE
Nx0 T＝QT(1-TS-ref/TT)
Nx0 C＝QC(TS-ref/TC-1)
wherein: qEPetThe unit is MWh for the purchased electric quantity outside the system; qGasThe amount of natural gas consumed by the system is given in m3；TAIs the average low-level heating value of natural gas and has the unit of MJ/m3；QSolarIs solar irradiance with the unit of W/m2(ii) a S is the irradiation area in m2；TEIs ambient temperature in K; t isSolarThe value is 5777K for the solar temperature; t isTAnd TCThe temperature of hot and cold working media is expressed in unit; qEThe unit of the output electric quantity of the comprehensive energy system is MJ; qTOutputting heat for the comprehensive energy system, wherein the unit is MJ; qCThe unit of the output cold quantity of the comprehensive energy system is MJ.
Further, the step S2 specifically includes:
step S21, dividing the energy conversion process of the comprehensive energy system into four layers, namely a distribution layer, a conversion layer, an integration layer and a storage layer, and obtaining a four-layer energy center model structure;
and step S22, drawing the model according to the four-layer energy center model structure.
Further, the step S3 specifically includes:
step S31, establishing an original non-convex planning model according to non-convex factors in the comprehensive energy system;
in step S32, an improved convex programming model is established based on the convex relaxation strategy.
Further, the step S4 specifically includes:
step S41, constructing an objective function of the annual total cost of the comprehensive energy system;
step S42, establishing constraint of multi-objective collaborative optimization, including: the method comprises the following steps of investment capacity constraint, building area constraint, power supply constraint of a power grid, energy supply equipment operation constraint, natural gas network capacity constraint, reliability constraint, demand response constraint, wind turbine generator constraint and external network energy purchasing constraint.
Further, the objective function of the annual total cost of the integrated energy system constructed in the step S41 is as follows:
Figure BDA0002710814280000031
wherein, Cin、fin(x) Is the initial investment cost of the comprehensive energy system, X is the decision variable for planning construction, Cop、fip(p) annual operating cost of the integrated energy system over lifetime, Cmc、fmc(p) annual maintenance cost of the integrated energy system, Cmc、fce(p) annual carbon emission cost of the integrated energy system, Cbt、fbtAnd (p) is subsidy income of government to the power generation of the comprehensive energy system, and p is a decision variable of the operation of the comprehensive energy system.
Further, the initial investment cost of the integrated energy system investment comprises the purchase cost, the installation cost, the land cost and other expenses of the equipment, and the calculation formula is as follows:
Figure BDA0002710814280000032
wherein y is the design life of the comprehensive energy system, and r is the discount rate; c. CiPurchasing cost for each equipment in the comprehensive energy system; x is the number ofiPlanning the optimal number of the devices; j is a function ofiThe use cost of land occupied by each device of the comprehensive energy system; t is tiThe installation cost of each device; el is the remaining cost spent in the construction phase;
the annual operation cost of the comprehensive energy system in the life cycle comprises annual fuel consumption cost and annual electric energy purchase cost in the whole life cycle, and the calculation formula is as follows:
Figure BDA0002710814280000041
wherein, PiThe operating output condition of the ith device is obtained; etaiThe power consumption proportionality coefficient of the ith equipment is obtained; giFor the output of the i-th plant consuming natural gas, kappaiThe proportional coefficient of the consumed fuel gas of the ith equipment;
the calculation formula of the annual maintenance cost of the integrated energy system is as follows:
Figure BDA0002710814280000042
wherein, wiMaintenance cost for a single device;
the calculation formula of the annual carbon emission cost of the integrated energy system is as follows:
Figure BDA0002710814280000043
wherein N isiIs the carbon emission of the i equipment in a unit period, and beta is the unit carbon emission cost.
Further, the formula for the investment capacity constraint is as follows:
Tmax≥fin(x)
wherein, TmaxThe maximum investment capacity is built for the comprehensive energy system;
the formula for the constraint of building area is as follows:
Figure BDA0002710814280000044
wherein m isiLand area occupied for installation of i-th equipment, AZmaxUsable land area for building comprehensive energy systems;
the formula of the power supply constraint of the power grid is as follows:
Figure BDA0002710814280000045
Figure BDA0002710814280000046
wherein D ismaxFor maximum power supply capacity of the grid, Pmax iFor the power consumption of the ith equipment, Umax iIs the generated power of the ith plant, Lq maxThe method comprises the following steps of designing an electric load for the interior of a comprehensive energy system, wherein S is a safe electric utilization coefficient;
the formula of the energy supply equipment operation constraint is as follows:
Figure BDA0002710814280000051
wherein Q isi minAnd Qmax iRespectively the minimum power and the maximum power of the cooling/heating of the ith equipment; delta Qi downAnd Δ Qup iThe climbing rates of the output reduction and the output increase of the ith equipment are respectively set;
the natural gas network capacity constraint calculation formula is as follows:
Figure BDA0002710814280000052
wherein PQmin,J，PQmax,lRespectively representing the upper and lower limits of the flow of the natural gas pipeline l, cll.yFor safe fluctuation coefficient of pipe transmission flow, Vmin,sAnd Vmax,sUpper and lower limits respectively representing the amount of supplied air given by the weather supplier s;
the reliability constraint needs to satisfy the following relation:
ΔLb s≤ΔLmax
wherein, Δ LmaxThe upper limit of insufficient electric energy;
the formula for the demand response constraint is as follows:
Pt min≤Pt≤Pt max
wherein, PtFor the load of the integrated energy system at time t, Pt min，Pt maxRespectively representing the upper limit and the lower limit of the demand response load of the comprehensive energy system at the moment t;
the formula of the wind turbine generator constraint is as follows:
0≤Wt≤Wt pre
wherein, Wt prePredicting wind power;
the formula of the external network purchase energy constraint is as follows:
0≤Enet,t≤Enet,max
0≤Gnet,t≤Gnet,max
wherein E isnet,maxAnd Gnet,maxRespectively the upper limit of buying electric energy and natural gas for the external network.
The embodiment of the invention has the beneficial effects that: in an economical manner
Figure BDA0002710814280000053
Efficiency is targeted multi-objective planning optimization, quality matching is achieved in the process of comprehensive utilization of energy, and comprehensive balance of performance is achieved in all aspects.
Drawings
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 description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic flow chart of a comprehensive energy system planning optimization simulation method according to an embodiment of the present invention.
Fig. 2 is a schematic specific flow chart of a comprehensive energy system planning optimization simulation method according to an embodiment of the present invention.
Figure 3 is a graph of typical daily load of a campus according to an embodiment of the present invention.
FIG. 4 is a view showing an embodiment according to the present invention
Figure BDA0002710814280000061
Obtaining the efficiency of each apparatus by calculation model
Figure BDA0002710814280000062
Efficiency rate is shown schematically.
Detailed Description
The following description of the embodiments refers to the accompanying drawings, which are included to illustrate specific embodiments in which the invention may be practiced.
Referring to fig. 1, an embodiment of the invention provides an integrated energy system planning optimization simulation method, including:
step S1, establishing EQC-based according to energy characteristics
Figure BDA0002710814280000063
An efficiency analysis model;
step S2, establishing a four-layer energy center model according to the multi-energy coupling analysis of the comprehensive energy system;
step S3, establishing an improved convex planning model according to non-convex factors in the comprehensive energy system;
step S4, according to economic factors
Figure BDA0002710814280000064
And (4) establishing a comprehensive energy system planning optimization model.
Specifically, in this embodiment, the physical model is: the energy acquisition types in the park comprise wind energy, solar energy and natural gas, the energy supply types comprise cold, heat, electricity and gas, and the distributed energy sources are provided with a fan, a photovoltaic device, a gas turbine, a gas boiler, a lithium bromide water chiller, an electric refrigerator, a storage battery, a heat storage tank and the like. The integrated energy system load analysis based on Energy Quality Coefficient (EQC) includes electrical/mechanical power, hot water, steam, space heating of buildings, space cooling of buildings, fossil fuels.
Referring to fig. 2, in step S1 of the present embodiment, the EQC is established based on the energy characteristics
Figure BDA0002710814280000065
And (4) an efficiency analysis model.
Figure BDA0002710814280000066
The efficiency reflects the comprehensive energy system pair
Figure BDA0002710814280000067
The utilization degree of the thermodynamic system can be used as an important index for evaluating the perfection degree of the thermodynamic system.
Figure BDA0002710814280000068
Efficiency the system is evaluated on the basis of an analysis of the quality of the system energy. In an integrated energy system is defined as the total output of the whole system
Figure BDA0002710814280000069
(avails)
Figure BDA00027108142800000610
) Sum of system inputs
Figure BDA0002710814280000071
(cost up)
Figure BDA0002710814280000072
) The ratio of the amount of the water to the amount of the water,
Figure BDA0002710814280000073
efficiency reflects the perfection of energy conversion in the integrated energy system. Thus, step S1 specifically includes:
step S11, establishing
Figure BDA0002710814280000074
An efficiency analysis model; the calculation formula is as follows:
F2＝Nx0/Nxi＝(Nx0 E+Nx0 T+Nx0 C)/(Nxi EPet+Nxi Gas+Nxi solar)
wherein: nx0For the total output of the integrated energy system
Figure BDA00027108142800000718
The units are MJ, NxiFor the total input of the integrated energy system
Figure BDA00027108142800000719
The unit is MJ; general of integrated energy system input
Figure BDA0002710814280000077
The method comprises the following steps: corresponding to purchased electric quantity
Figure BDA0002710814280000078
Value Nxi EPetCorresponding to the natural gas consumed
Figure BDA0002710814280000079
Value Nxi GasCorresponding to photovoltaic power generation
Figure BDA00027108142800000710
Value Nxi solarCorresponding to fan generation
Figure BDA00027108142800000711
Value Nxi Pw(ii) a Total output of comprehensive energy system
Figure BDA00027108142800000712
The method comprises the following steps: output corresponding to cold load
Figure BDA00027108142800000713
Nx0 cOutput corresponding to thermal load
Figure BDA00027108142800000714
Nx0 tOutputs corresponding to the electric loads respectively
Figure BDA00027108142800000715
Nx0 E。
Step S12, respectively calculating the total input of the comprehensive energy system
Figure BDA00027108142800000716
And sum of outputs
Figure BDA00027108142800000720
The calculation formula is as follows:
Nxi EPet＝3600×QEPet
Nxi Gas＝QGasTA
Nxi solar＝Σ[QSolarS(1-TE/TSolar)Δt/106]
Nx0 E＝QE
Nx0 T＝QT(1-TS-ref/TT)
Nx0 C＝QC(S-ref/TC-1)
wherein: qEPetThe unit is MWh for the purchased electric quantity outside the system; qGasThe amount of natural gas consumed by the system is given in m3；TAIs the average low-level heating value of natural gas and has the unit of MJ/m3；QSolarIs solar irradiance with the unit of W/m2(ii) a S is the irradiation area in m2；TEIs ambient temperature in K; t isSolarThe value is 5777K for the solar temperature; t isTAnd TCThe temperature of hot and cold working media is expressed in unit; qEThe unit of the output electric quantity of the comprehensive energy system is MJ; qTOutputting heat for the comprehensive energy system, wherein the unit is MJ; qCThe unit of the output cold quantity of the comprehensive energy system is MJ.
In step S2 of this embodiment, based on the multi-energy coupling principle, the energy conversion process of the integrated energy system is divided into four layers, i.e., a distribution layer, a conversion layer, an integration layer, and a storage layer, so that an optimization space is provided for the complementation of multiple energy sources on the premise of ensuring the balance of energy supply and demand; the model is then rendered according to the structural framework.
Thus, step S2 specifically includes:
step S21, dividing the energy conversion process of the comprehensive energy system into four layers, namely a distribution layer, a conversion layer, an integration layer and a storage layer, and obtaining a four-layer energy center model structure;
and step S22, drawing the model according to the four-layer energy center model structure.
Further, step S3 specifically includes:
step S31, establishing an original non-convex planning model according to non-convex factors in the comprehensive energy system;
in step S32, an improved convex programming model is established based on the convex relaxation strategy.
Further, step S4 specifically includes:
step S41, constructing an objective function of the annual total cost of the comprehensive energy system;
step S42, establishing constraint of multi-objective collaborative optimization, including: the method comprises the following steps of investment capacity constraint, building area constraint, power supply constraint of a power grid, energy supply equipment operation constraint, natural gas network capacity constraint, reliability constraint, demand response constraint, wind turbine generator constraint and external network energy purchasing constraint.
The annual total cost mainly comprises the annual value of initial investment cost of the initial stage of the comprehensive energy system, the annual operation cost (including energy consumption and labor cost input) of the comprehensive energy system, the annual maintenance cost inside the comprehensive system, the annual carbon emission cost of the comprehensive energy system and the like. Meanwhile, subsidy benefits of governments on power generation of the comprehensive energy system are considered. The objective function is:
Figure BDA0002710814280000081
wherein, Cin、fin(x) Is a comprehensive energy systemInitial investment cost of total investment, X is decision variable for planning construction, Cop、fop(p) annual operating cost of the integrated energy system over lifetime, Cmc、fmc(p) annual maintenance cost of the integrated energy system, Cce、fce(p) annual carbon emission cost of the integrated energy system, Cbt、fbtAnd (p) is subsidy income of government to the power generation of the comprehensive energy system, and p is a decision variable of the operation of the comprehensive energy system.
Further, the initial investment cost of the integrated energy system investment comprises the purchase cost, the installation cost, the land cost and other expenses of the equipment, and the calculation formula is as follows:
Figure BDA0002710814280000082
wherein y is the design life of the comprehensive energy system, and r is the discount rate; c. CiPurchasing cost for each equipment in the comprehensive energy system; x is the number ofiPlanning the optimal number of the devices; j is a function ofiThe use cost of land occupied by each device of the comprehensive energy system; t is tiThe installation cost of each device; el is the remaining cost spent in the construction phase;
the annual operation cost of the comprehensive energy system in the life cycle comprises annual fuel consumption cost and annual electric energy purchase cost in the whole life cycle, and the calculation formula is as follows:
Figure BDA0002710814280000091
wherein, PiThe operating output condition of the ith device is obtained; etaiThe power consumption proportionality coefficient of the ith equipment is obtained; giFor the output of the i-th plant consuming natural gas, kappaiThe proportional coefficient of the consumed fuel gas of the ith equipment;
the calculation formula of the annual maintenance cost of the integrated energy system is as follows:
Figure BDA0002710814280000092
wherein, wiMaintenance cost for a single device;
the calculation formula of the annual carbon emission cost of the integrated energy system is as follows:
Figure BDA0002710814280000093
wherein N isiIs the carbon emission of the i equipment in a unit period, and beta is the unit carbon emission cost.
Further, the formula for the investment capacity constraint is as follows:
Tmax≥fin(x)
wherein, TmaxThe maximum investment capacity is built for the comprehensive energy system;
the formula for the constraint of building area is as follows:
Figure BDA0002710814280000094
wherein m isiLand area occupied for installation of i-th equipment, AZmaxUsable land area for building comprehensive energy systems;
the formula of the power supply constraint of the power grid is as follows:
Figure BDA0002710814280000095
Figure BDA0002710814280000096
wherein D ismaxFor maximum power supply capacity of the grid, Pmax iFor the power consumption of the ith equipment, Umax iIs the generated power of the ith plant, Lq maxElectricity utilization negative electrode designed for internal of comprehensive energy systemThe charge and S are safe electricity utilization coefficients;
the formula of the energy supply equipment operation constraint is as follows:
Figure BDA0002710814280000101
wherein Q isi minAnd Qmax iRespectively the minimum power and the maximum power of the cooling/heating of the ith equipment; delta Qi downAnd Δ Qup iThe climbing rates of the output reduction and the output increase of the ith equipment are respectively set;
the natural gas network capacity constraint calculation formula is as follows:
Figure BDA0002710814280000102
wherein PQmin,J，PQmax,lRespectively representing the upper and lower limits of the flow of the natural gas pipeline l, cll.yFor safe fluctuation coefficient of pipe transmission flow, Vmin,sAnd Vmax,sUpper and lower limits respectively representing the amount of supplied air given by the weather supplier s;
the reliability constraint needs to satisfy the following relation:
ΔLb s≤ΔLmax
wherein, Δ LmaxThe upper limit of insufficient electric energy;
the formula for the demand response constraint is as follows:
Pt min≤Pt≤Pt max
wherein, PtFor the load of the integrated energy system at time t, Pt min，Pt maxRespectively representing the upper limit and the lower limit of the demand response load of the comprehensive energy system at the moment t;
the formula of the wind turbine generator constraint is as follows:
0≤Wt≤Wt pre
wherein, Wt prePredicting wind power;
the formula of the external network purchase energy constraint is as follows:
0≤Enet,t≤Enet,max
0≤Gnet,t≤Gnet,max
wherein E isnet,maxAnd Gnet,maxRespectively the upper limit of buying electric energy and natural gas for the external network.
The invention is further illustrated by means of a specific application example.
(one) application instance analysis
Application example data are as follows:
the park establishes an IES with three load requirements of cold, heat and electricity, wherein refrigeration refers to space refrigeration in a building, and heating refers to industrial hot water with the supply temperature of 170 ℃ and the return temperature of 40 ℃. The life cycle N is set to 20 years and the discount rate R is set to a constant of 0.07. The time-of-use electricity price of the electric power is 0.90 yuan/kW.h at peak time (8:00-11:00, 16:00-22:00), 0.40 yuan/kW.h at valley time (23:00-7:00), and 0.65 yuan/kW.h at ordinary time (12:00-15: 00). While the price of natural gas, neglecting its seasonal variation, is set to a constant of 2.45 yuan/m 3. The carbon tax rating is 0.15 yuan/kg.C, and the carbon emission coefficients of electricity, fuel and renewable energy are 220, 180 and 0 kg.C/MWh, respectively. Typical daily load requirements for a campus obtained by cluster analysis are shown in figure 3.
Candidate energy generators include transformers (T), photovoltaic Panels (PV), Cogeneration (CHP), Gas Boilers (GB), electric boilers (ELB), solar collectors (STC), Absorption Chillers (AC), and Electric Heat Pumps (EHP). Candidate energy storage devices include Batteries (BAT), thermal storage tanks (HST), and ice storage tanks (CWS). And the candidate networks include a power supply network (EL), a heating pipe network (HP) and a cooling pipe network (CP). The site selection problem of the equipment and the division of the energy supply area are not deeply discussed, and the configuration nodes of the centralized equipment and the energy supply area thereof are directly given according to experience. Specific parameters of each apparatus are shown in table 1:
TABLE 1 Equipment parameters
Figure BDA0002710814280000111
(II) result display
To verify the validity of the model constructed by the invention, the planning optimization is carried out by taking the annual total cost as a single target (scheme 1) so as to
Figure BDA0002710814280000112
Efficiency planning optimization for Single goal (case 2) and Total cost in years
Figure BDA0002710814280000113
The efficiency is compared with the efficiency in the planning optimization (scheme 3).
According to table 1, the total annual cost of each equipment investment under different scenarios is known: from the point of view of the investment costs of the equipment, photovoltaic Panels (PV) and solar collectors (STC) are not good choices because of their high cost of deployment. Cogeneration (CHP) should not be chosen because there are more economical options in both power generation and heat supply, namely transformer (T) and Gas Boiler (GB). The equipment configuration cost of the absorption refrigerator (AC) and the Electric Heat Pump (EHP) is similar, but considering that the absorption refrigerator (AC) needs an additional regional cooling network for centralized cooling, the investment cost of the absorption refrigerator (AC) is reasonable to be higher than that of the Electric Heat Pump (EHP).
According to the invention
Figure BDA0002710814280000123
Obtaining the efficiency of each apparatus by calculation model
Figure BDA0002710814280000124
Efficiency rate, as shown in figure 4.
From
Figure BDA0002710814280000125
From an efficiency point of view, electric boilers (ELB) (21.53%) and Electric Heat Pumps (EHP) (33.67%) perform poorly because they consume high quality electrical energy and only produce poor heating or cooling. In contrast, consuming renewable energy sources: (PV and STC) of the installation
Figure BDA0002710814280000126
The efficiency is set at 100% because of the renewable energy they consume. The three kinds of heat generators
Figure BDA0002710814280000127
Efficiency ranked from high to low, Combined Heat and Power (CHP) (75.22%), Gas Boiler (GB) (31.17%) and electric boiler (ELB) (21.53%). As refrigerating apparatus, absorption refrigerators (AC) (74.59%)
Figure BDA0002710814280000128
The efficiency is much better than that of an Electric Heat Pump (EHP) (33.67%), although its COP value (90%) is much lower than that of the latter (380%), indicating that Absorption Chillers (AC) should be preferred. In addition, if the heat consumed by the alternating current comes from industrial waste heat, it
Figure BDA0002710814280000129
The efficiency will be further improved.
Figure BDA0002710814280000121
Figure BDA0002710814280000122
Wherein M is1-M4Respectively representing the distribution layers (M) in the four-layer energy center model established according to the multi-energy coupling analysis of the comprehensive energy system1) Conversion layer (M)2) An integration layer (M)3) Storage layer (M)4)；M1The parameters in (3) are distribution coefficients of different types of equipment in the distribution layer, and are used as decision variables to provide alternative energy paths for optimization.
Depending on the specific energy form, the energy output units can be divided into three categories, i.e. generating units (including T, PV, CHP), heating units (including CHP, GB, ELB) and cooling units (including AC, EHP). Schemes 1-3 Containment of the respective devicesThe volume planning results are shown in Table 2, the economy is
Figure BDA0002710814280000133
The results of the efficiency analysis planning are shown in table 3.
TABLE 2 Capacity planning results for each scenario of equipment
Figure BDA0002710814280000131
TABLE 3 economics of each protocol
Figure BDA0002710814280000134
Results of the efficiency planning
Figure BDA0002710814280000132
From the above results, it was found that, first, the heat generation temperature due to STC: (<100 ℃ C. does not meet the industrial heat requirement (170 ℃ C.), so STC is not chosen in any of the schemes. In contrast, photovoltaic power generation has been recognized in all schemes, reaching the upper bound of installed capacity, which indicates that photovoltaic power generation is a clean form of power generation without consuming fossil fuels, in terms of economy, conventional energy efficiency and
Figure BDA0002710814280000135
the efficiency aspect is advocated. In scheme 1 and scheme 2, cogeneration is considered the first choice in power and heating subsystems, indicating that cogeneration is an economic and concentrated heat source
Figure BDA0002710814280000136
Is superior to GB and ELB in efficiency. Natural gas is preferred as a dispersed heat source, being superior to electrical energy. Scheme 1 considers EHP to have better performance and AC should be eliminated. Therefore, in an integrated energy system without a regional cooling network, a decentralized mode should be employed. Only scheme 2 considers AC to have better performance than EHP, and the centralized mode and the decentralized mode should be jointly appliedFor use in IES. Therefore, a centralized cooling area cooling network is built in part of the industrial park to fully utilize the waste heat.
The main difference between scheme 1 and scheme 2 is whether alternating current and concentrated cooling are used. From the data in fig. 4 (air conditioner (AC) 74.59%, EHP 33.67%) it was found that air conditioning is beneficial for energy cascade utilization in industrial parks and other situations where excess heat is present. It should be appreciated that solution 2 neglects economics and may result in blindly large scale construction. The main energy forms of the scheme 3 are natural gas, renewable energy and low-quality heat supply, the high-quality power consumption is relatively low, and the quality matching is realized in the comprehensive utilization process of the energy, so the invention has the advantages of economy and low cost
Figure BDA0002710814280000141
Efficiency is targeted multi-objective planning optimization, and comprehensive balance of performance is achieved in all aspects.
As can be seen from the above description, the embodiments of the present invention have the following beneficial effects: in an economical manner
Figure BDA0002710814280000142
Efficiency is targeted multi-objective planning optimization, quality matching is achieved in the process of comprehensive utilization of energy, and comprehensive balance of performance is achieved in all aspects.
The above disclosure is only for the purpose of illustrating the preferred embodiments of the present invention, and it is therefore to be understood that the invention is not limited by the scope of the appended claims.

Claims (10)

1. A comprehensive energy system planning optimization simulation method is characterized by comprising the following steps:
step S1, establishing EQC-based according to energy characteristics
Figure FDA0002710814270000011
An efficiency analysis model;
step S2, establishing a four-layer energy center model according to the multi-energy coupling analysis of the comprehensive energy system;
step S3, establishing an improved convex planning model according to non-convex factors in the comprehensive energy system;
step S4, according to economic factors
Figure FDA0002710814270000012
And (4) establishing a comprehensive energy system planning optimization model.
2. The integrated energy system planning optimization simulation method according to claim 1, wherein the step S1 specifically includes:
step S11, establishing
Figure FDA0002710814270000013
An efficiency analysis model;
step S12, respectively calculating the total input of the comprehensive energy system
Figure FDA0002710814270000014
And sum of outputs
Figure FDA0002710814270000015
。
3. The integrated energy system planning optimization simulation method of claim 2, wherein the established integrated energy system planning optimization simulation method is
Figure FDA0002710814270000016
The calculation formula of the efficiency analysis model is as follows:
F2＝Nx0/Nxi＝(Nx0 E+Nx0 T+Nx0 C)/(Nxi EPet+Nxi Gas+Nxi solar)
wherein: nx0For the total output of the integrated energy system
Figure FDA00027108142700000120
The units are MJ, NxiFor the total input of the integrated energy system
Figure FDA00027108142700000121
The unit is MJ; general of integrated energy system input
Figure FDA0002710814270000019
The method comprises the following steps: corresponding to purchased electric quantity
Figure FDA00027108142700000110
Value Nxi EPetCorresponding to the natural gas consumed
Figure FDA00027108142700000111
Value Nxi GasCorresponding to photovoltaic power generation
Figure FDA00027108142700000112
Value Nxi solarCorresponding to fan generation
Figure FDA00027108142700000113
Value Nxi Pw(ii) a Total output of comprehensive energy system
Figure FDA00027108142700000114
The method comprises the following steps: output corresponding to cold load
Figure FDA00027108142700000115
Nx0 cOutput corresponding to thermal load
Figure FDA00027108142700000116
Nx0 tOutputs corresponding to the electric loads respectively
Figure FDA00027108142700000117
Nx0 E。
4. The integrated energy system planning optimization simulation method of claim 3, wherein the total of integrated energy system inputs
Figure FDA00027108142700000118
And sum of outputs
Figure FDA00027108142700000119
The calculation formula of (2) is as follows:
Nxi EPet＝3600×QEPet
Nxi Gas＝QGasTA
Nxi solar＝∑[QSolarS(1-TE/TSolar)Δt/106]
Nx0 E＝QE
Nx0 T＝QT(1-TS-ref/TT)
Nx0 C＝QC(TS-ref/TC-1)
wherein: qEPetThe unit is MWh for the purchased electric quantity outside the system; qGasThe amount of natural gas consumed by the system is given in m3；TAIs the average low-level heating value of natural gas and has the unit of MJ/m3；QSolarIs solar irradiance with the unit of W/m2(ii) a S is the irradiation area in m2；TEIs ambient temperature in K; t isSolarThe value is 5777K for the solar temperature; t isTAnd TCThe temperature of hot and cold working media is expressed in unit; qEThe unit of the output electric quantity of the comprehensive energy system is MJ; qTOutputting heat for the comprehensive energy system, wherein the unit is MJ; qCThe unit of the output cold quantity of the comprehensive energy system is MJ.
5. The integrated energy system planning optimization simulation method according to claim 1, wherein the step S2 specifically includes:
step S21, dividing the energy conversion process of the comprehensive energy system into four layers, namely a distribution layer, a conversion layer, an integration layer and a storage layer, and obtaining a four-layer energy center model structure;
and step S22, drawing the model according to the four-layer energy center model structure.
6. The integrated energy system planning optimization simulation method according to claim 1, wherein the step S3 specifically includes:
step S31, establishing an original non-convex planning model according to non-convex factors in the comprehensive energy system;
in step S32, an improved convex programming model is established based on the convex relaxation strategy.
7. The integrated energy system planning optimization simulation method according to claim 1, wherein the step S4 specifically includes:
step S41, constructing an objective function of the annual total cost of the comprehensive energy system;
step S42, establishing constraint of multi-objective collaborative optimization, including: the method comprises the following steps of investment capacity constraint, building area constraint, power supply constraint of a power grid, energy supply equipment operation constraint, natural gas network capacity constraint, reliability constraint, demand response constraint, wind turbine generator constraint and external network energy purchasing constraint.
8. The method for optimizing simulation of an integrated energy system planning according to claim 7, wherein the objective function of the annual total cost of the integrated energy system constructed in the step S41 is:
Figure FDA0002710814270000021
wherein C isin、fin(x) Is the initial investment cost of the comprehensive energy system, X is the decision variable for planning construction, Cop、fop(p) annual operating cost of the integrated energy system over lifetime, Cmc、fmc(p) annual maintenance cost of the integrated energy system, Cce、fce(p) annual carbon emission cost of the integrated energy system, Cbt、fbtAnd (p) is subsidy income of government to the power generation of the comprehensive energy system, and p is a decision variable of the operation of the comprehensive energy system.
9. The method according to claim 8, wherein the initial investment cost of the integrated energy system comprises the purchase cost, installation cost, land cost and other expenses of the equipment, and the calculation formula is as follows:
Figure FDA0002710814270000031
wherein y is the design life of the comprehensive energy system, and r is the discount rate; c. CiPurchasing cost for each equipment in the comprehensive energy system; x is the number ofiPlanning the optimal number of the devices; j is a function ofiThe use cost of land occupied by each device of the comprehensive energy system; t is tiThe installation cost of each device; el is the remaining cost spent in the construction phase;
the annual operation cost of the comprehensive energy system in the life cycle comprises annual fuel consumption cost and annual electric energy purchase cost in the whole life cycle, and the calculation formula is as follows:
Figure FDA0002710814270000032
wherein, PiThe operating output condition of the ith device is obtained; etaiThe power consumption proportionality coefficient of the ith equipment is obtained; giFor the output of the i-th plant consuming natural gas, kappaiThe proportional coefficient of the consumed fuel gas of the ith equipment;
the calculation formula of the annual maintenance cost of the integrated energy system is as follows:
Figure FDA0002710814270000033
wherein, wiMaintenance cost for a single device;
the calculation formula of the annual carbon emission cost of the integrated energy system is as follows:
Figure FDA0002710814270000034
wherein N isiIs the carbon emission of the i equipment in a unit period, and beta is the unit carbon emission cost.
10. The integrated energy system planning optimization simulation method of claim 7, wherein the formula of the investment capacity constraint is as follows:
Tmax≥fin(x)
wherein, TmaxThe maximum investment capacity is built for the comprehensive energy system;
the formula for the constraint of building area is as follows:
Figure FDA0002710814270000035
wherein m isiLand area occupied for installation of i-th equipment, AZmaxUsable land area for building comprehensive energy systems;
the formula of the power supply constraint of the power grid is as follows:
Figure FDA0002710814270000041
Figure FDA0002710814270000042
wherein D ismaxFor maximum power supply capacity of the grid, Pmax iFor the power consumption of the ith equipment, Umax iIs the generated power of the ith plant, Lq maxThe method comprises the following steps of designing an electric load for the interior of a comprehensive energy system, wherein S is a safe electric utilization coefficient;
the formula of the energy supply equipment operation constraint is as follows:
Figure FDA0002710814270000043
wherein Q isi minAnd Qmax iRespectively the minimum power and the maximum power of the cooling/heating of the ith equipment; delta Qi downAnd Δ Qup iThe climbing rates of the output reduction and the output increase of the ith equipment are respectively set;
the natural gas network capacity constraint calculation formula is as follows:
Figure FDA0002710814270000044
wherein PQmin,J，PQmax,lRespectively representing the upper and lower limits of the flow of the natural gas pipeline l, cll.yFor safe fluctuation coefficient of pipe transmission flow, Vmin,sAnd Vmax,sUpper and lower limits respectively representing the amount of supplied air given by the weather supplier s;
the reliability constraint needs to satisfy the following relation:
ΔLb s≤ΔLmax
wherein, Δ LmaxThe upper limit of insufficient electric energy;
the formula for the demand response constraint is as follows:
Pt min≤Pt≤Pt max
wherein, PtFor the load of the integrated energy system at time t, Pt min，Pt maxRespectively representing the upper limit and the lower limit of the demand response load of the comprehensive energy system at the moment t;
the formula of the wind turbine generator constraint is as follows:
0≤Wt≤Wt pre
wherein, Wt prePredicting wind power;
the formula of the external network purchase energy constraint is as follows:
0≤Enet,t≤Enet,max
0≤Gnet,t≤Gnet,max
wherein E isnet,maxAnd Gnet,maxRespectively the upper limit of buying electric energy and natural gas for the external network.
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