CN112149980A - Energy efficiency analysis method and system for regional comprehensive energy system - Google Patents

Abstract

The invention discloses a method and a system for analyzing energy efficiency of a regional comprehensive energy system, wherein the method comprises the following steps: s1, calculating energy quality coefficients of different energy sources of the comprehensive energy system; s2, calculating an evaluation index of the comprehensive energy system energy efficiency evaluation index system; s3, calculating the weight and the combined weight of the evaluation index; s4, ranking the evaluation indexes. According to the method, the energy quality coefficient calculation, the evaluation index calculation and the index weight calculation are utilized, so that data are easy to obtain and are closer to the actual situation, and the practicability of the energy efficiency evaluation of the comprehensive energy system is enhanced; by utilizing the characteristics of different energy forms, the multi-energy advantage complementation and the cooperative optimization are realized, the comprehensive benefits of an energy system in the links of production, transmission and distribution, utilization, circulation and the like are improved, and the clean development of energy is effectively promoted, the efficient utilization of energy is supported, and the construction of energy conservation and emission reduction is realized.

Description

Energy efficiency analysis method and system for regional comprehensive energy system

Technical Field

The invention relates to a method and a system for analyzing energy efficiency of a regional comprehensive energy system, and belongs to the technical field of control of comprehensive energy systems.

Background

The energy is an important material basis for the development of national economy, and is in an extremely important strategic position in the national economy, and people can not leave the energy in production and life. The comprehensive energy system aims at high-efficiency clean utilization of energy, takes large-scale renewable energy consumption as background, and realizes cascade utilization of different grades of energy through scientific coordination and scheduling of different energy supply links such as electricity, heat, gas and cold; by means of multi-energy complementation, the large-scale access and efficient utilization of renewable energy sources are promoted, and the flexibility, safety and economy of an energy supply system are improved.

In the field of comprehensive energy, a comprehensive energy evaluation index is provided for a comprehensive energy system for promoting the utilization of renewable energy. However, currently, most of the energy efficiency evaluation methods are single energy efficiency evaluation methods, and a comprehensive energy evaluation system is not comprehensive enough. Therefore, to ensure efficient operation of the system, the system problems such as effective access of renewable energy and minimum operation energy loss need to be considered cooperatively, and the equipment problems such as the use efficiency characteristic of the energy conversion unit and pollutant emission of the terminal equipment need to be considered.

The energy efficiency analysis problem of the regional integrated energy system is a multi-attribute decision problem, but when the regional integrated energy system is in actual operation, the regional integrated energy system is influenced by internal and external operation boundaries (environment, climate, working conditions, user demand diversity and the like), is a high-dimensional, time-varying and nonlinear system, and inevitably has larger deviation from an actual operation state by taking a design value or a model calculation value as an evaluation reference, so that the regional integrated energy system is limited in engineering application.

Disclosure of Invention

In order to solve the problems, the invention provides an energy efficiency analysis method and system for an area-level comprehensive energy system, which can realize the complementation and collaborative optimization of multiple energy advantages, improve the comprehensive benefits of the energy system in the links of production, transmission and distribution, utilization, circulation and the like, and can effectively promote the clean development of energy, support the high-efficiency utilization of energy and save energy and reduce emission.

The technical scheme adopted for solving the technical problems is as follows:

in a first aspect, the energy efficiency analysis method for the regional-level integrated energy system provided in the embodiment of the present invention includes the following steps:

s1, calculating energy quality coefficients of different energy sources of the comprehensive energy system, wherein the energy quality coefficients are the ratio of the maximum work which can be done by the different energy sources to the total energy of the different energy sources;

s2, calculating an evaluation index of the comprehensive energy system energy efficiency evaluation index system based on the energy quality coefficient;

s3, calculating the weight and the combined weight of the evaluation index;

and S4, optimizing each index according to the weight and the combined weight to obtain the final evaluation index weight, and sequencing the evaluation indexes.

As a possible implementation manner of the embodiment, in step S1, the energy quality coefficients λ of the various energy sources are calculated as follows:

in the formula, Q is the total energy of various energy sources; w is total energyThe part of the quantity that can be converted into work, i.e. that possessed by this energy source

The number of the cells.

As a possible implementation manner of this embodiment, the calculating energy quality coefficients of different energy sources of the integrated energy system specifically includes:

energy mass coefficient lambda of fuel_{Burning device}Expressed as:

T_{burning device}Temperature of flue gas, T, produced for combustion of fuel₀Is the low temperature heat source temperature;

energy mass coefficient lambda of natural gas_gasExpressed as:

energy mass coefficient lambda of coal_coalExpressed as:

energy-mass coefficient lambda of municipal hot water_{Hot water}Expressed as:

the energy mass coefficient of municipal steam is expressed as:

in the formula, T_{Steam generator}Is the saturation temperature corresponding to the steam pressure;

from the supply temperature of the chilled water to the chilled waterIn the process of return water temperature, the energy-mass coefficient lambda of the chilled water_{Chilled water}Expressed as:

in the formula, T_gAnd T_hRespectively the supply and return water temperatures, T, of the chilled water₀Is the low temperature heat source temperature.

As a possible implementation manner of this embodiment, in step S2, the evaluation index of the energy efficiency evaluation index system of the integrated energy system includes a primary index and a secondary index, where the primary index includes an energy supply subsystem, an energy conversion subsystem, a medium-low voltage power grid, and economic and social benefits; the secondary indexes comprise power supply subsystem energy efficiency, cooling subsystem energy efficiency, heating subsystem energy efficiency, gas supply subsystem energy efficiency, power system energy efficiency, electricity-to-heat/cold energy conversion equipment energy efficiency, gas-to-electricity/heat energy conversion equipment energy efficiency, heat-to-cold energy conversion equipment energy efficiency, low-voltage load three-phase load unbalance qualification rate, low-voltage transformer area harmonic content qualification rate, low-voltage transformer area comprehensive line loss rate, low-voltage transformer area voltage qualification rate, low-voltage transformer area main line average section, low-voltage transformer area average power supply radius, power supply reliability, economy, unit energy supply cost, financial net present value, climate change and pollutant emission.

As a possible implementation manner of this embodiment, the calculating an evaluation index of the energy efficiency evaluation index system of the integrated energy system specifically includes:

the electric energy supply amount We in the power supply subsystem is as follows:

in the formula: eta_tRepresenting the transformer efficiency; eta_lineRepresenting the efficiency of the power line within the campus; gamma ray_e、γ_cA conversion coefficient representing electric and cold loads; we is the electric energy supply; e_chpRepresenting the electric energy generated by the triple co-generation; r_eIndicating a parkElectrical energy generated from internal renewable energy sources; p_eRepresenting externally input electrical energy; d_eAnd D_cRespectively representing the energy released by the electricity storage device and the cold storage device;

energy efficiency η of power supply subsystem_eComprises the following steps:

in the formula: eta_s,eAnd η_d,eThe storage and discharge efficiency of the power storage device is shown; s_eRepresenting the energy released by the electrical storage device;

heat and cold supply W of heat supply subsystem and cold supply subsystem_h、W_cRespectively as follows:

W_h＝[H_g-h+H_e-h+H_chp+R_h+(1-γ_h)D_h](1-0.01l_ha_h)

W_c＝[C_e-c+C_h-c+R_c+(1-γ_c)D_c](1-0.01l_ca_c)

in the formula: w_hIndicating the heat supply amount; w_cThe cooling capacity is represented; h_g-hAnd H_e-hRespectively representing the heat energy generated by natural gas and electric energy through an electric boiler and a gas boiler; h_chpRepresenting the heat energy generated by the triple co-generation; c_e-cAnd C_h-cRespectively representing cold energy converted from electric energy and heat energy through corresponding energy conversion equipment; r_h、R_cRespectively representing heat energy and cold energy generated by renewable energy sources; l_h、l_cRespectively representing the lengths of the hot and cold pipe networks; a is_h、a_cRespectively representing the dissipation rate of the hot pipe network and the cold pipe network per 100 meters; gamma ray_hA conversion coefficient representing the thermal load, calculated by 6.1; d_hRepresenting the energy released by the heat storage device;

energy system energy efficiency eta of heat supply subsystem and cold supply subsystem_h、η_cAre respectively as

In the formula: eta_s,h、η_d,hRespectively showing the heat storage efficiency and the heat release efficiency of the heat storage device; eta_s,c、η_d,cShowing the cold storage and release efficiency of the cold storage device; s_h、S_cRepresenting the energy released by the heat and cold storage devices;

the supply amount Wg of natural gas of the gas supply subsystem is as follows:

W_g＝P_g+G_e-g

in the formula: w_gRepresenting the natural gas supply; p_gRepresenting the amount of externally input natural gas; g_e-gRepresenting natural gas converted from electrical energy;

the lift Y of the water pump of the power system is as follows:

in the formula: y is₀Represents the theoretical lift, i.e. the lift at a flow rate of 0; f represents the friction coefficient; q_hpIndicating the flow rate of the pump; q_inAnd Q_outRespectively representing the flow of the inlet and the outlet of the pipeline when the pump is not added; the inlet and outlet head of the pump are thus respectively Y_inAnd Y_out：

Y_loss＝Y_in-Y_out

In the formula: y is_lossRepresenting lift loss; e_hpRepresents the electrical energy required by the pump to compensate for head losses; eta_hpRepresents the efficiency of the pump; w represents the weight of the liquid, i.e. the weight of one cubic meter of liquid;

power systemTransmission efficiency eta_mComprises the following steps:

in the formula: v_mRepresenting the amount of energy m transmitted through the pump; lambda [ alpha ]_mA conversion coefficient representing the energy m;

efficiency eta of electric conversion heat/cold energy conversion equipment_e-h、η_e-cComprises the following steps:

in the formula: c_OPe-hRepresents a heating coefficient of electric heating; c_OPe-cA refrigeration coefficient representing electrical refrigeration;

combined heat and power generation unit efficiency eta of gas-to-electricity/heat energy conversion equipment_chpComprises the following steps:

in the formula: e_CHP、H_chpRepresenting the electric energy and the heat energy generated by the cogeneration unit; lambda [ alpha ]_SteamRepresenting a conversion factor of the steam; g_chpNatural gas representing consumption by a cogeneration unit;

gas boiler equipment efficiency eta of gas-to-electricity/heat energy conversion equipment_g-hComprises the following steps:

in the formula: cop_g-hThe heat production coefficient of the natural gas is shown, namely the heat energy generated by the unit natural gas through the gas boiler;

heat to cold energyEfficiency η of the source conversion device_h-cComprises the following steps:

in the formula: cop_h-cRepresenting the refrigeration coefficient of the absorption refrigerator;

the calculation formula of the energy efficiency index of the medium and low voltage power grid is as follows:

the qualification rate of the low-voltage load three-phase load unbalance degree is that the number of the low-voltage three-phase load unbalance rate is less than 15 percent divided by the total number of the low-voltage transformer areas multiplied by 100 percent;

the qualification rate of the content of all waves in the low-voltage area is that the harmonic content meets the standard requirement, the number of the areas is divided by the total number of the low-voltage areas multiplied by 100 percent;

the comprehensive line loss rate of the low-voltage distribution area is equal to (total power supply quantity of the low-voltage distribution area-total power consumption of a household meter of the low-voltage distribution area) ÷ total power supply quantity of the low-voltage distribution area multiplied by 100%;

the low-voltage power supply voltage meeting rate is equal to the number of voltage monitoring points meeting the voltage qualification rate, divided by the total number of low-voltage E monitoring points multiplied by 100 percent;

the average section of the main line of the low-voltage transformer area is equal to the arithmetic average of the nominal sections of the main line of the low-voltage transformer area;

the average power supply radius of the low-voltage station area is equal to the arithmetic average value of the power supply radius of the low-voltage station area;

the power supply reliability is calculated by the following formula:

in the formula: lambda [ alpha ]_seRepresenting the theoretical failure rate of the power supply system; mu.s_seRepresenting the theoretical restoration rate of the power supply system; MTTR represents the theoretical average repair time of the power supply system; MTTF represents the average running time of the power supply system before theoretical failure; f represents the theoretical average failure frequency of the power supply system;

the economic benefit indexes are as follows:

in the formula: ECI represents an economic evaluation index of the comprehensive energy system; IC (integrated circuit)_i、MC_i、SC_iThe initial investment cost, the operation maintenance cost and the scrapping cost of the ith type energy unit in the comprehensive energy system are represented; IC (integrated circuit)_EAC,i、SC_EAC,iAn equal-year value representing the initial investment cost and the scrapping cost of the i-th type energy unit; IR represents the discount rate; l is_iRepresenting the lifecycle of the i-th class of energy units;_irepresenting the annual average load rate of the i-th type energy unit; w is a_iRepresents the annual energy production, kWh, of a class i energy unit; FC_i,jA type j fuel or electricity consumption representing a unit energy production of the type i energy unit; sigma_jRepresents the purchase cost of the j-th fuel; RC (resistor-capacitor) capacitor_iRepresenting the repair and maintenance cost of the i-th type energy unit;

the unit energy supply cost is calculated by the following formula:

in the formula: LCOE represents unit cost of energy supply; i is₀Representing an initial investment; v_RRepresenting a fixed asset residual; n represents the operating year of the project; a. the_nRepresents the operating cost of the nth year; d_nRepresents the depreciation of the nth year; p_nRepresents interest in year n; y is_nRepresents the energy supply of the nth year; i represents the discount rate;

the net present financial value is calculated using the formula:

in the formula: n represents a project calculation cycle; NC (numerical control)_tRepresenting the newly increased net cash flow in the t year in the calculation period; i.e. i_cRepresenting a benchmark rate of return;

the investment recovery period is calculated by the following formula:

the financial internal rate of return is calculated using the following formula:

in the formula: n represents a project calculation cycle; NC (numerical control)_tRepresenting the newly increased net cash flow in the t year in the calculation period;

the climate change index is as follows:

in the formula: ENIC represents the climate change index of the integrated energy system; CT represents a carbon trading price; w is a_iRepresenting the annual energy supply of the i-th type energy unit in the integrated energy system;_irepresenting the annual average load rate of the i-th type energy unit; CEC_iAn equivalent carbon dioxide emission representing a unit energy yield of a unit in a reference energy system corresponding to the i-th type energy unit; CE_iAn equivalent carbon dioxide emission amount representing a unit energy supply amount of the i-th type energy unit; GHE represents the i-th class energyThe amount of greenhouse gas j emitted per unit energy supply of the source unit;_CG,jan equivalence factor representing greenhouse gas j emissions converted to carbon dioxide emissions;

the pollutant emission indexes are as follows:

in the formula: ENIP represents a pollutant emission index of the comprehensive energy system; VP_jRepresenting the environmental value of the jth pollutant; w_iThe annual energy supply quantity, kW.h, of the i-th type energy unit in the comprehensive energy system is represented;_irepresenting the annual average load rate of the i-th type energy unit; PEC_i,jThe unit energy supply of the unit energy supply unit in the reference energy system corresponding to the ith type energy unit is expressed, and the jth pollutant is discharged; PE (polyethylene)_i,jAnd the j pollutant emission under the unit energy supply of the i type energy unit is shown.

As a possible implementation manner of this embodiment, in step S2, an evaluation index of the energy efficiency evaluation index system of the integrated energy system is normalized; the evaluation index

The indexes are divided into forward type, reverse type and intermediate type indexes;

the normalization process of the intermediate index is as follows:

wherein a and d are the lower and upper limits of the function, and b and c are the lower and upper limits of the intermediate interval [ b, c ];

the normalization process of the forward index is as follows:

wherein M is_j＝max{x_ij},m_j＝min_i{x_ij}，0≤a_ij≤1；

The normalization processing of the reverse index is as follows:

wherein M is_j＝max_i{x_ij},m_j＝min_i{x_ij}，0≤a_ij≤1。

As a possible implementation manner of this embodiment, in step S3, the process of calculating the weight of the evaluation index and the combination weight specifically includes:

obtaining subjective weight by using an analytic hierarchy process, obtaining objective weight by using an entropy weight method, and constructing a combined weighting method to calculate the weight of an evaluation index;

constructing a target function based on a moment estimation theory, and solving by adopting a nonlinear programming to obtain a combination weight of an evaluation index;

and optimizing each index by utilizing hierarchical clustering and expert intervention means to obtain the weight of the final evaluation index.

As one possible implementation manner of the present embodiment, in step S3,

the subjective weight calculation step is as follows:

selecting influence factors according to specific problems, and establishing a proper hierarchy; the hierarchy includes: a target layer, a criterion layer, a sub-criterion layer and a scheme layer;

② judging the relative importance of each factor in each level, wherein u_i,u_j(i, j ═ 1,2,3 … n) represents the factor u_ijRepresents u_iFor u is paired_jThe relative importance values of (a) refer to the numbers 1-9 and their inverse as a scale;

all relative importance values u to be obtained_ijForming a judgment matrix P:

thirdly, the maximum characteristic root of the judgment matrix needs to be solved firstλ_maxAnd the corresponding feature vector W, and then calculating the weight of the importance value:

P_W＝λ_maxw

in the formula, λ_maxIs the maximum characteristic root λ of the matrix_maxW is lambda_maxThe corresponding feature vector;

fourthly, calculating a consistency index CI:

wherein λ is_maxIn order to determine the maximum eigenvalue of the matrix,

calculating the consistency ratio

Wherein, RI is a random consistency index, RI ═ 000.520.891.121.261.361.411.461.491.521.541.561.581.59; the objective weight is calculated by the following steps:

firstly, constructing an index matrix

m is the number of evaluation samples, n is the number of evaluation indexes, v_ij(i 1,2, …, m; j 1,2, … n) is an index value;

normalizing the index matrix to obtain a normalized index matrix:

X＝(x_ij)_mn

in the formula, x_ijThe value of the j index of the ith sample in the matrix;

determining the index weight:

in the formula, h_ijThe probability of occurrence of each index; k is a radical of_iIs the information entropy of the system; s_jThe entropy weight expressed as the j index;

the index weight column vector is as follows:

S＝(s₁,s₂,…,s_n)^T

in the formula, s_nThe nth index weight;

weighted normalization matrices are as follows:

Y＝(y_ij)_mn＝(s_jx_ij)_mn

in the formula, y_ijA j index value of an i sample of the normalization matrix;

the calculation steps of the combination weight are as follows:

assuming that the relative importance of the subjective weight vector to the combination weight is α, the relative importance of the objective weight vector to the combination weight is β, and the deviation between the combination weight vector W and the subjective weight vector T is minimum, it is described by the following formula:

minH(w_j)＝α×(w_j-t_j)²+β×(w_j-s_j)²

∑w_j＝1,1≤j≤n

calculating the relative importance coefficient of the subjective and objective weight vector of the single index by using the subjective weight and the objective weight actual value of each index:

aiming at the evaluation indexes in the multi-decision matrix, calculating the relative importance coefficients of the overall subjective and objective weight vector:

for each index w_jWith H (w)_j) The minimum is excellent, and the following formula is converted:

converting the multi-objective optimization model into a single-objective optimization model for solving:

the step of optimizing each index by utilizing hierarchical clustering and expert intervention means is as follows:

firstly, each object is a cluster, the number of the objects contained in each cluster is 1, and the mutual distance between the clusters is calculated to obtain a distance matrix;

② two clusters (d) with the nearest distance_ij) The smallest two clusters) are merged into a new cluster;

recalculating the distance between the new cluster and the original cluster, and selecting the average distance between the new cluster and the original cluster as the distance between the two clusters;

fourthly, continuously repeating the third step and the fourth step until only one cluster is left or the end condition is reached: the number of clusters reaches a specified number or the inter-cluster distance reaches a threshold.

As a possible implementation manner of this embodiment, in step S4, the process of ranking the evaluation indexes is as follows:

(1) decision problem for setting multiple indexesThe scheme set is C ═ C (C)₁,C₂,…,C_m) The index set is M ═ M (M)₁,M₂,…,M_n) Scheme M_jFor index C_iAn evaluation value of r_ij(i 1,2, …, n; j 1,2, …, m), the multi-objective decision matrix R is obtained:

(2) by the matrix R ═ (R)_ij)_m×nSum weight vector W ═ W₁,w₂,…,w_m) Multiplying to form a weighted decision matrix Z ═ (Z)_ij)_m×n；

Calculating the positive ideal solution and the negative ideal solution of the index to obtain a positive ideal solution vector Z⁺And a negative ideal solution vector Z^-：

In the formula (I), the compound is shown in the specification,

(3) calculating the distance from each scheme to the ideal solution

Distance from the negative ideal solution

(4) Calculating the relative closeness of the comprehensive evaluation of each evaluation object:

(5) according to C_jAnd sorting the evaluation objects from big to small.

In a second aspect, an energy efficiency analysis system of a regional-level integrated energy system provided in an embodiment of the present invention includes:

the energy quality coefficient calculation module is used for calculating the energy quality coefficients of different energy sources of the comprehensive energy system;

the evaluation index calculation module is used for calculating the evaluation index of the comprehensive energy system energy efficiency evaluation index system;

the weight calculation module is used for calculating the weight and the combined weight of the evaluation indexes;

and the index sorting module is used for sorting the evaluation indexes.

The technical scheme of the embodiment of the invention has the following beneficial effects:

according to the technical scheme of the embodiment of the invention, energy quality coefficient calculation, evaluation index calculation and index weight calculation are utilized, so that data is easy to obtain and is closer to the actual situation, and the practicability of energy efficiency evaluation of the comprehensive energy system is enhanced; by utilizing the characteristics of different energy forms, the multi-energy advantage complementation and the cooperative optimization are realized, the comprehensive benefits of an energy system in the links of production, transmission and distribution, utilization, circulation and the like are improved, and the clean development of energy is effectively promoted, the efficient utilization of energy is supported, and the construction of energy conservation and emission reduction is realized.

Description of the drawings:

FIG. 1 is a flow diagram illustrating a method for energy efficiency analysis of a regional level integrated energy system in accordance with an exemplary embodiment;

FIG. 2 is a diagrammatical representation of an energization subsystem indicator in accordance with an exemplary embodiment;

fig. 3 is a block diagram illustrating a regional level integrated energy system energy efficiency analysis system according to an exemplary embodiment.

Detailed Description

The invention is further illustrated by the following examples in conjunction with the accompanying drawings:

in order to clearly explain the technical features of the present invention, the following detailed description of the present invention is provided with reference to the accompanying drawings. The following disclosure provides many different embodiments, or examples, for implementing different features of the invention. To simplify the disclosure of the present invention, the components and arrangements of specific examples are described below. Furthermore, the present invention may repeat reference numerals and/or letters in the various examples. This repetition is for the purpose of simplicity and clarity and does not in itself dictate a relationship between the various embodiments and/or configurations discussed. It should be noted that the components illustrated in the figures are not necessarily drawn to scale. Descriptions of well-known components and processing techniques and procedures are omitted so as to not unnecessarily limit the invention.

Fig. 1 is a flow chart illustrating a method for analyzing energy efficiency of a regional-level integrated energy system according to an exemplary embodiment. As shown in fig. 1, the energy efficiency analysis method for the regional-level integrated energy system according to the embodiment of the present invention includes the following steps:

s1, calculating energy quality coefficients of different energy sources of the comprehensive energy system;

s2, calculating an evaluation index of the comprehensive energy system energy efficiency evaluation index system;

s3, calculating the weight and the combined weight of the evaluation index;

s4, ranking the evaluation indexes.

In step S1, energy-quality coefficient calculation is performed on different energy sources by using an energy-quality coefficient calculation method, so as to obtain a unified energy source measurement using electricity as a core.

The method for calculating the energy quality coefficients of various energy sources comprises the following steps of defining the ratio of the maximum work which can be done by different energy sources to the external energy and the total energy of the energy sources as the energy quality coefficient of the energy source, and expressing the energy quality coefficient by lambda, wherein the calculation formula is as follows:

wherein Q is the total energy of the form of energy in kJ; w is the portion of total energy that can be converted into work, i.e. that possessed by this energy source

The amount of (C) is expressed in kJ.

(1) Energy quality coefficient of primary energy

The energy-quality coefficient of the fuel can be preliminarily expressed as:

according to the above formula and the application conditions of the related art, the energy-quality coefficients of various fuels can be obtained.

Energy and mass coefficient of natural gas

The energy coefficient of the natural gas is between 0.60 and 0.64 according to different environmental temperatures.

Energy quality coefficient of coal

The energy-mass coefficient of the coal is between 0.41 and 0.46 according to different environmental temperatures.

(2) Energy mass coefficient of secondary energy

Municipal hot water supply

At ambient temperature T₀As the low temperature heat source temperature, the supply water temperature and the return water temperature are respectively T_gAnd T_hAt a slave temperature T_gDown to temperature T_hIn the process, the energy-quality coefficient calculation formula of the municipal hot water is as follows:

② municipal steam

The energy mass coefficient of municipal steam is as follows:

in the formula, T vapor is the saturation temperature (in K) corresponding to the vapor pressure.

③ chilled water

At ambient temperature T₀As the low temperature heat source temperature, the supply water temperature and the return water temperature are respectively T_gAnd T_hFrom temperature T of the chilled water_gIs raised to a temperature T_hIn the process of (a), the part of energy which can be completely converted into work is:

therefore, the energy-mass coefficient of the chilled water is as follows, and the numerical value thereof is closely related to the temperature of the supply water and the return water.

In step S2, a comprehensive energy system multidimensional evaluation index system is constructed using energy efficiency, economic benefit, and social benefit, and a calculation method of each evaluation index is defined.

The multidimensional evaluation index system comprises a first-level index and a second-level index, and the first-level index comprises an energy supply subsystem, an energy conversion subsystem, a medium-low voltage power grid, economic benefits and social benefits as shown in table 1; the secondary indexes comprise power supply subsystem energy efficiency, cooling subsystem energy efficiency, heating subsystem energy efficiency, gas supply subsystem energy efficiency, power system energy efficiency, electricity-to-heat/cold energy conversion equipment energy efficiency, gas-to-electricity/heat energy conversion equipment energy efficiency, heat-to-cold energy conversion equipment energy efficiency, low-voltage load three-phase load unbalance qualification rate, low-voltage transformer area harmonic content qualification rate, low-voltage transformer area comprehensive line loss rate, low-voltage transformer area voltage qualification rate, low-voltage transformer area main line average section, low-voltage transformer area average power supply radius, power supply reliability, economy, unit energy supply cost, financial net present value, climate change and pollutant emission.

Table 1: comprehensive energy multi-dimensional energy efficiency assessment index system

(1) Energy efficiency index of energy supply subsystem and calculation method thereof

The energy supply subsystems are divided into air supply, power supply, heat supply and cold supply subsystems, and index descriptions of the energy supply subsystems are shown in figure 2.

Energy efficiency of power supply subsystem

The supply amount We of electric energy in the power supply subsystem is

In the formula: eta_tRepresenting the transformer efficiency; eta_lineRepresenting the efficiency of the power line within the campus; gamma ray_e、γ_cA conversion coefficient representing electric and cold loads; we is the electric energy supply (KW h); e_chpRepresents the electric energy (KW.h) generated by triple co-generation; r_eRepresents the electric energy (KW · h) generated by renewable energy sources in the park; p_eRepresents externally input electric energy (KW · h); d_e、D_cRepresents the energy (KW & h) released by the electricity and cold storage device.

Thus the energy efficiency η of the power supply subsystem_eIs composed of

In the formula: eta_s,e、η_d,eThe storage and discharge efficiency of the power storage device is represented and is determined by the type and model of the power storage device; s_eRepresents the energy (KW · h) released by the electric storage device.

Energy efficiency of cooling and heating subsystems

Heat and cold supply W of heat and cold supply subsystem_h、W_c. Respectively as follows:

W_h＝[H_g-h+H_e-h+H_chp+R_h+(1-γ_h)D_h](1-0.01l_ha_h)

W_c＝[C_e-c+C_h-c+R_c+(1-γ_c)D_c](1-0.01l_ca_c)

in the formula: w_hIndicating a heat supply amount (KW & h); w_cIndicating the cooling capacity (KW.h); h_g-hAnd H_e-hRespectively representing the heat energy (KW.h) generated by natural gas and electric energy through an electric boiler and a gas boiler; h_chpRepresents the heat energy (KW.h) generated by triple co-generation; c_e-cAnd C_h-cRespectively representing cold energy (KW.h) converted from electric energy and heat energy through corresponding energy conversion equipment; r_h、R_c. Respectively representing heat energy and cold energy (KW & h) generated by renewable energy; l_h、l_c. Respectively representing the lengths (m) of the hot and cold pipe networks; a is_h、a_cRespectively representing the dissipation rate of the hot pipe network and the cold pipe network per 100 meters; gamma ray_hA conversion coefficient representing the thermal load, calculated by 6.1; d_hIndicating the energy (KW · h) released by the heat storage device. Energy system energy efficiency eta of heating and cooling subsystem_h、η_cThe numerator denominator of (A) is similar to the power supply subsystem, respectively

In the formula: eta_s,h、η_d,hRespectively showing the heat storage efficiency and the heat release efficiency of the heat storage device; eta_s,c、η_d,cShowing the cold storage and release efficiency of the cold storage device; s_h、S_cIndicating the energy (KW · h) released by the heat and cold storage device.

Third, energy efficiency of air supply subsystem

The supply amount Wg of natural gas is shown in the following formula, and the energy efficiency of the energy system can be approximately regarded as 100%.

W_g＝P_g+G_e-g

In the formula: w_gIndicating the natural gas supply amount (KW · h); p_gRepresents the external input natural gas amount (KW h); g_e-gIndicating the conversion of electrical energy into natural gas (KW · h).

Energy efficiency of power system

The pump lift represents the pumping height of the pump, and is represented by Y, the common measurement unit is m, and the actual pump lift Y of the pump is:

in the formula: y is₀Represents the theoretical lift, i.e. the lift at a flow rate of 0; f represents the friction coefficient; q_hpIndicates the flow rate (m) of the pump³/h)；Q_inAnd Q_outRespectively representing the flow rates (m) at the inlet and outlet of the pipeline when no pump is added³H); the inlet and outlet head of the pump are thus respectively Y_inAnd Y_out。

Y_loss＝Y_in-Y_out

In the formula: y is_lossRepresenting lift loss; e_hpRepresents the electric energy (N/m) required by the pump to compensate the head loss³)；η_hpIndicating the efficiency of the pump, which varies according to the brand of the pump; w represents the weight of the liquid, i.e. the weight of one cubic meter of liquid (N/m)³) When the transmission medium is water, the water is,w is 9800N/m³The natural gas pressurizing and circulating pump and the water pump have similar electric energy consumption calculation methods, only the liquid weight difference is obtained, and the weight of the liquefied natural gas is only about 45% of the same volume of water.

On the basis, the transmission efficiency eta of the power system_mIs composed of

In the formula: v_mRepresenting the amount of energy m transmitted through the pump;

λ_mrepresenting the conversion factor of the energy m.

(2) Energy efficiency index of energy conversion system and calculation method thereof

Establishing an energy efficiency model of an energy conversion system, wherein the efficiency of energy conversion equipment represents the ratio of output energy after conversion to input energy before conversion, and the energy conversion equipment comprises the conversion processes of electricity/heat, gas/electricity, electricity/cold and heat/cold; and the comprehensive energy efficiency of the multi-energy system represents the ratio of the energy demand which can be met by the whole system to the input energy of the external system.

Energy efficiency of electric-to-heat/cold energy conversion equipment

Conversion of electrical to thermal/cold energy into a conversion process_e-h、η_e-cIs composed of

In the formula: c_OPe-hRepresents a heating coefficient of electric heating; c_OPe-cRepresenting the refrigeration coefficient of the electric refrigeration.

② energy efficiency of gas-to-electricity/heat energy conversion equipment

In the conversion process of gas-to-electricity/heat energy, the gas-to-electricity/heat energy is converted by a gas turbine and a waste heat recovery deviceThe cogeneration unit can realize the conversion of natural gas into electric energy and heat energy, and the efficiency eta of the equipment_chpComprises the following steps:

in the formula: e_CHP、H_chpRepresents electric energy and heat energy (KW & h) generated by the cogeneration unit; lambda [ alpha ]_SteamRepresenting a conversion factor of the steam; g_chpRepresenting the natural gas consumed by the cogeneration unit.

In the conversion facilities using natural gas as inlet energy, there is also a gas boiler facility which only realizes conversion of natural gas into heat energy, and the efficiency eta of the energy conversion process_g-hIs composed of

In the formula: cop_g-hWhich represents the heating coefficient of natural gas, i.e. the heat energy that can be generated by a gas boiler per unit of natural gas.

Energy efficiency of hot-to-cold energy conversion equipment

In the process of converting heat energy into cold energy, the inlet energy is heat energy, the outlet energy is cold energy, and the main conversion equipment is an absorption refrigerator. Efficiency eta of heat-to-cold energy conversion process_h-cIs composed of

In the formula: cop_h-cThe refrigeration coefficient of the absorption refrigerator is shown.

(3) Medium-low voltage power grid energy efficiency index and calculation method thereof

The qualification rate of the low-voltage load three-phase load unbalance degree is as follows: the qualification rate of the low-voltage load three-phase load unbalance degree is that the number of the low-voltage three-phase load unbalance rate is less than 15 percent divided by the total number of the low-voltage transformer areas multiplied by 100 percent;

the qualification rate of the harmonic content of the low-voltage transformer area is as follows: the qualification rate of the content of all waves in the low-voltage area is that the harmonic content meets the standard requirement, the number of the areas is divided by the total number of the low-voltage areas multiplied by 100 percent;

comprehensive line loss rate of the low-voltage transformer area: the comprehensive line loss rate of the low-voltage distribution area is equal to (total power supply quantity of the low-voltage distribution area-total power consumption of a household meter of the low-voltage distribution area) ÷ total power supply quantity of the low-voltage distribution area multiplied by 100%; (ii) a

Voltage qualification rate of the low-voltage transformer area: the low-voltage power supply voltage meeting rate is equal to the number of voltage monitoring points meeting the voltage qualification rate, divided by the total number of low-voltage E monitoring points multiplied by 100 percent

Average section of main line of low-voltage platform area: the average section of the main line of the low-voltage transformer area is equal to the arithmetic average of the nominal sections of the main line of the low-voltage transformer area;

average power supply radius of low-voltage transformer area: and the average power supply radius of the low-voltage station area is equal to the arithmetic average value of the power supply radius of the low-voltage station area.

The power supply reliability is the theoretical continuous power supply capacity of the power supply system to the user in the calculation period, and can be calculated by adopting the following formula:

in the formula: lambda [ alpha ]_seRepresenting the theoretical failure rate (failure times/year) of the power supply system; mu.s_seRepresenting the theoretical repair rate (repair times/year) of the power supply system; MTTR represents the theoretical average repair time (h) of the power supply system; MTTF represents the average running time (h) before theoretical failure of the power supply system; f represents the theoretical average failure frequency (failure times/year) of the power supply system.

(4) Economic benefit index and calculation method thereof

The economic evaluation index model can be represented by the following formula:

in the formula: ECI represents an economic evaluation index of the comprehensive energy system; IC (integrated circuit)_i、MC_i、SC_iThe initial investment cost, the operation maintenance cost and the scrapping cost of the ith type energy unit in the comprehensive energy system are represented; IC (integrated circuit)_EAC,i、SC_EAC,iAn equal-year value representing the initial investment cost and the scrapping cost of the i-th type energy unit; IR represents the discount rate; l is_iRepresenting the lifecycle of the i-th class of energy units;_irepresenting the annual average load rate of the i-th type energy unit; w is a_iRepresents the annual energy production, kWh, of a class i energy unit; FC_i,jA consumed fuel amount (or electricity consumption amount) representing a unit energy yield of the ith type energy unit; sigma_jRepresents the purchase cost of the j-th fuel; RC (resistor-capacitor) capacitor_iIndicating the repair and maintenance costs of the i-th energy unit.

The unit energy cost can be calculated using the following formula:

in the formula: LCOE represents unit cost of energy supply; i is₀Representing an initial investment; v_RRepresenting a fixed asset residual; n represents the operating year of the project; a. the_nRepresents the operating cost of the nth year; d_nRepresents the depreciation of the nth year; p_nRepresents interest in year n; y is_nRepresents the energy supply of the nth year; i represents the discount rate.

The net financial current value may be calculated using the following equation:

in the formula: n represents a project calculation cycle; NC (numerical control)_tRepresenting the newly increased net cash flow in the t year in the calculation period (the data are respectively according to the financial cash flow tables of all investments and capital funds); i.e. i_cIndicating the baseline rate of return.

The payback period can be calculated using the following formula:

the financial internal rate of return may be calculated using the following equation:

in the formula: n represents a project calculation cycle; NC (numerical control)_tRepresenting the new net cash flow in year t of the calculation cycle.

(5) Social benefit index and calculation method thereof

The climate change index model is as follows:

in the formula: ENIC represents the climate change index of the integrated energy system; CT represents a carbon trading price; w is a_iThe annual energy supply quantity, kW.h, of the i-th type energy unit in the comprehensive energy system is represented;_irepresenting the annual average load rate of the i-th type energy unit; CEC; CEC_iAn equivalent carbon dioxide emission, t/kW · h, representing the unit energy yield of the unit in the reference energy system corresponding to the i-th type energy unit; CE_iAn equivalent carbon dioxide emission t/kW · h representing the unit energy supply of the i-th type energy unit; GHE represents the emission amount of greenhouse gas j of the unit energy supply amount of the i-type energy unit, t/kW.h;_CG,jrepresenting the equivalence factor of greenhouse gas j emissions converted to carbon dioxide emissions.

In the pollutant emission index model, the more pollutant emission is reduced by the comprehensive energy system compared with a reference energy system, the higher equivalent economic value is brought, and the higher the system environment index is.

In the formula: ENIP represents a pollutant emission index of the comprehensive energy system; VP_jRepresenting the environmental value of the jth pollutant; w_iThe annual energy supply quantity, kW.h, of the i-th type energy unit in the comprehensive energy system is represented;_irepresenting the annual average load rate of the i-th type energy unit; PEC_i,jThe unit energy supply of the unit energy supply unit in the reference energy system corresponding to the ith type energy unit is expressed, and the jth pollutant is discharged; PE (polyethylene)_i,jAnd the j pollutant emission under the unit energy supply of the i type energy unit is shown.

(6) Index normalization method

Indexes are of different types and are divided into a forward type, a reverse type, an intermediate type and the like, and in order to unify the index types and evaluate a system more accurately, the indexes need to be normalized. The normalization method is as follows.

Intermediate index normalization processing method

And selecting a membership function method for processing aiming at the intermediate index.

Where a and d are the lower and upper limits of the function, and b and c are the lower and upper limits of the intermediate interval [ b, c ].

② forward type index

Processing for the forward indicator:

wherein M is_j＝max{x_ij},m_j＝min_i{x_ijThe value of the index is changed to be 0 to a by processing the index_ij≤1。

③ reverse type indicators

And (3) processing aiming at the reverse indexes:

wherein M is_j＝max_i{x_ij},m_j＝min_i{x_ijThe value of the index is changed to be 0 to a by processing the index_ijIn step S3, obtaining subjective weight by using an analytic hierarchy process, obtaining objective weight by using an entropy weight method, and constructing a combined weighting method to calculate the weight of an index system; constructing a target function based on a moment estimation theory, and solving by adopting nonlinear programming to obtain a combined weight; and optimizing each index by means of hierarchical clustering, expert intervention and the like to obtain the final index weight.

(1) Subjective weight calculation method

The subjective weight calculation adopts an analytic hierarchy process, and the specific analytic steps of the AHP analytic hierarchy process are as follows:

firstly, establishing a hierarchical model.

The influencing factors are selected according to specific problems, and an appropriate hierarchy is established. The hierarchy is divided according to circumstances, and generally includes: target layer, criteria layer, sub-criteria layer, scheme layer, etc.

② determining relative importance degree.

After the hierarchical model is built, the relative importance of each factor in each hierarchy needs to be judged, wherein u_i,u_j(i, j ═ 1,2,3 … n) represents the factor u_ijRepresents u_iFor u is paired_jThe numbers 1 to 9 and their inverses are cited as scales, and the specific relationship is shown in table 2.

Table 2: power supply level indicator detail

All relative importance values u to be obtained_ijAnd forming a judgment matrix P.

And thirdly, calculating importance sequencing.

Firstly, the maximum characteristic root lambda of the judgment matrix needs to be solved_maxAnd the corresponding feature vector w. The solving process is as follows:

P_W＝λ_maxw

after finding out the specific characteristic vector w, the result of w after normalization is the weight distribution of each factor.

And fourthly, checking the consistency.

After the weight distribution is obtained, whether the weight is reasonable or not needs to be judged through consistency check. First, a consistency index CI (consistency index) is calculated.

Wherein λ is_maxThe maximum eigenvalue of the decision matrix.

Calculating consistency ratio CR (consistency).

Wherein, RI is a random consistency index, and RI is [ 000.520.891.121.261.361.411.461.491.521.541.561.581.59 ].

To address the consistency problem, AHP provides a way to measure the consistency of comparisons made by decision makers. When CR <0.1, the judgment matrix is considered to have acceptable consistency, otherwise the judgment matrix is properly corrected.

(2) Objective weight calculation method

The entropy weight method is used as an objective weighting method, and the main idea is to determine the entropy value through the information entropy of each index, and then correct the weight through entropy weight calculation, so that the weight is more scientific, objective and feasible. The method comprises the following basic steps:

firstly, constructing an index matrix

The number of evaluation samples is m, the evaluation index is n, and each index value is v_ij(i 1,2, …, m; j 1,2, … n), the index matrix is as follows:

② normalizing index matrix

Normalizing the index matrix to obtain a normalized index matrix X ═ X_ij)_mnThe following are:

in the expression, x_ijThe value of the j index for the i sample in the matrix.

(iii) determining index weight by entropy weight method

In the formula, h_ijThe probability of occurrence of each index; k is a radical of_iIs the information entropy of the system; s_jExpressed as the entropy weight of the j-th index.

The index weight column vector is as follows:

S＝(s₁,s₂,…,s_n)^T

in the formula, s_nIs the nth index weight.

Weighted normalization

The weighted normalization matrix is as follows:

Y＝(y_ij)_mn＝(s_jx_ij)_mn

in the formula, y_ijThe ith index value of the ith sample of the normalization matrix.

(3) Combination weight calculation method

Let α be the relative importance of the subjective weight vector to the combining weight, β be the relative importance of the objective weight vector to the combining weight, and satisfy the minimum deviation between the combining weight vector W and the subjective weight vector T, which can be described by the following equation.

minH(w_j)＝α×(w_j-t_j)²+β×(w_j-s_j)²

∑w_j＝1,1≤j≤n。

According to the basic idea of the moment estimation theory, calculating the expected values of the subjective weight and the objective weight of each index, wherein the expected values of the subjective weight and the objective weight are the actual values of each index weight, namely t and s. By utilizing the subjective weight and the objective weight actual value of each index, the relative importance coefficient of the subjective and objective weight vector of a single index can be calculated as follows:

for the evaluation indexes in the multi-decision matrix, the relative importance coefficients of the overall subjective and objective weight vector can be calculated as follows:

for each index x_jWith H (w)_j) The minimum is excellent, and can be converted into the following formula:

the multi-objective optimization model can be converted into a single-objective optimization model for solving, and the following formula is adopted:

(4) index weight optimization decision based on hierarchical clustering and expert intervention

In the hierarchical clustering algorithm of the agglomeration, each element is initially taken as a cluster, two clusters with the minimum inter-cluster distance are continuously merged until only one cluster is left or an end condition is reached (the number of the clusters merged to be appointed or the inter-cluster distance reaches a threshold), an appointed object is clustered, the distance matrix size is N multiplied by N, and the basic process of the hierarchical clustering algorithm of the agglomeration based on the average distance is as follows:

1. each object is a cluster, the number of objects contained in each cluster is 1, and the distance matrix is obtained by calculating the mutual distance between the clusters

2. Two clusters closest in distance (d)_ij) The smallest two clusters) are merged into a new cluster;

3. recalculating the distance between the new cluster and the original cluster, and selecting the average distance between the new cluster and the original cluster as the distance between the two clusters;

4. the second and third steps are repeated until only one cluster remains or a finishing condition is reached (the number of clusters reaches a specified number or the inter-cluster distance reaches a threshold value).

After each combination of the hierarchical clustering algorithm, the distance between the new cluster and the original cluster needs to be recalculated, the distance matrix is updated for multiple times, two clusters with the minimum distance are continuously selected from the distance matrix, when the data objects are large, the calculation amount is huge, the time complexity of the algorithm is overlarge, and the application prospect of the hierarchical clustering algorithm is seriously influenced.

And then feeding the comprehensive opinions and the prediction problems back to the experts respectively, inquiring the opinions again, modifying the original opinions of the experts according to the comprehensive opinions, and then summarizing the opinions. Repeating the steps for many times, and gradually obtaining a more consistent prediction result.

In step S4, the evaluation index is evaluated by using a top order method (toposis method) that approximates to an ideal solution.

A TOPSIS evaluation model is applied to investment benefit evaluation, and the basic calculation process is as follows:

(1) multi-objective decision matrix construction

The scheme set of the multi-index decision problem is C ═ C₁,C₂,…,C_m) The index set is M ═ M (M)₁,M₂,…,M_n) Scheme M_jFor index C_iAn evaluation value of r_ij(i 1,2, …, n; j 1,2, …, m), the multi-objective decision matrix R is obtained as shown in the following equation.

(2) Calculation of positive and negative ideal solutions

By the matrix R ═ (R)_ij)_m×nSum weight vector W ═ W₁,w₂,…,w_m) Multiplying to form a weighted decision matrix Z ═ (Z)_ij)_m×n. Calculating the positive ideal solution and the negative ideal solution of the index to obtain a positive ideal solution vector Z + and a negative ideal solution vector Z-,

as shown in the following formula.

(3) Relative distance calculation

Calculating the distance from each scheme to the ideal solution

Distance from the negative ideal solution

The calculation method is shown in the following formula.

(4) Comprehensive evaluation value calculation

And calculating the relative closeness of the comprehensive evaluation of each evaluation object, wherein the relative closeness represents the closeness of each scheme and the optimal scheme, the greater the relative closeness, the more similar the scheme and the optimal scheme are, the higher the ranking is, and the calculation method is shown as the following formula.

(5) Ranking of evaluation results

The result is calculated by the above formula as C_jAnd sorting the evaluation objects from big to small.

Calculation example: multi-dimensional regional comprehensive energy efficiency assessment application

(1) Description of Integrated energy System

1. Boundary condition of system

A typical area consists of an industrial production area and a commercial area. Under the condition of considering the multi-energy complementary characteristic and the access of renewable energy sources, the electric load demand of the region is supplied by an external power grid and a CCHP unit, the heat load of the region is supplied by the CCHP unit and an electric boiler, and the cold load of the region is supplied by a conventional refrigerator, a ground source heat pump, a lithium bromide refrigerator and a cold storage water pool.

In consideration of the pollutant-free emission condition of renewable energy input in various energy technologies, the emission of all pollutants in the operation of the comprehensive energy system can be traced back to the production of electric energy. Pollutant emission intensity was used to measure pollutant emission per unit of power generation as shown in table 3.

Table 3: reference for intensity of pollutant discharge

2. Multi-dimensional energy efficiency assessment under different energy supply modes of multifunctional area

Selecting a typical scene of comprehensive energy at a certain area level to carry out multi-dimensional energy efficiency assessment, wherein the area comprises typical scenes of industrial production areas, commercial areas, administrative offices and the like, and different capacity allocation schemes are as follows:

(1) single target optimal energy supply mode

Under the environment benefit optimal mode, capacity allocation is carried out by taking carbon emission reduction and pollutant emission reduction as main targets, and the typical area allocation capacity condition is as follows: the system comprises a photovoltaic power generation system, a gas turbine 117630kW, an absorption refrigerator 70578kW, a waste heat boiler 56462kW, a gas boiler 54527kW, an electric refrigerator 6534.8kW and the rest of energy is provided by a power grid.

(2) Multi-target optimal energy supply mode

Under the optimal energy supply mode of multi-objective benefit, selecting appropriate distributed energy equipment under the typical regional resource condition, and carrying out capacity configuration by taking the lowest annual cost as a target, wherein the configured capacity condition is as follows: the system comprises a photovoltaic power generation system, a gas turbine 59627kW, an absorption refrigerator 35776kW, a waste heat boiler 28620kW, a gas boiler 76078kW, an electric refrigerator 30327kW and the rest of energy provided by a power grid.

The calculation of each index was performed according to the index calculation method, and the results are shown in table 4:

table 4: indexes and calculation results of different energy supply modes in typical area

Subjective weights of the first-level indexes and the second-level indexes are calculated by using an analytic hierarchy process, objective weights of the second-level indexes are calculated by using an entropy weight method, then an objective function of combined weights is constructed based on the thought of moment estimation, the optimal combined weights are obtained by using nonlinear programming solving calculation, and the results are shown in table 5:

table 5: index combination weight calculation result in multi-target benefit optimal energy supply mode

The TOPSIS evaluation method is used for evaluating the energy efficiency of two energy supply modes in each typical scene.

Through simulation, energy efficiency evaluation results of different energy supply modes of each typical region are shown in table 6.

Table 6: typical region energy efficiency evaluation calculation result

The energy efficiency of the multi-target benefit optimal energy supply mode is found to be superior to that of the environment single-target benefit optimal mode through evaluation.

Fig. 3 is a block diagram illustrating a regional level integrated energy system energy efficiency analysis system according to an exemplary embodiment. As shown in fig. 3, an energy efficiency analysis system of a regional-level integrated energy system according to an embodiment of the present invention includes:

the energy quality coefficient calculation module is used for calculating the energy quality coefficients of different energy sources of the comprehensive energy system;

the evaluation index calculation module is used for calculating the evaluation index of the comprehensive energy system energy efficiency evaluation index system;

the weight calculation module is used for calculating the weight and the combined weight of the evaluation indexes;

and the index sorting module is used for sorting the evaluation indexes.

The modules are used for implementing the steps of the regional comprehensive energy system energy efficiency analysis method.

According to the technical scheme of the embodiment of the invention, the energy efficiency of the comprehensive energy system can be evaluated. Because the data for establishing the quota mostly come from the energy consumption generated by the actual building, the data is easy to obtain, and the utilization rate of the renewable energy is calculated by utilizing the data such as the energy consumption quota and the like, the method is convenient and fast, and is closer to the reality.

As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, a division of modules is merely a division of logical functions, and an actual implementation may have another division, and for example, a plurality of modules or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of devices or modules through some communication interfaces, and may be in an electrical, mechanical or other form.

Modules described as separate parts may or may not be physically separate, and parts displayed as modules may or may not be physical modules, may be located in one place, or may be distributed on a plurality of network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment.

In addition, functional modules in the embodiments provided in the present application may be integrated into one processing module, or each module may exist alone physically, or two or more modules are integrated into one module.

The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

Finally, it should be noted that: the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting the same, and although the present invention is described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: modifications and equivalents may be made to the embodiments of the invention without departing from the spirit and scope of the invention, which is to be covered by the claims.

Claims (10)

1. A regional level comprehensive energy system energy efficiency analysis method is characterized by comprising the following steps:

s1, calculating energy quality coefficients of different energy sources of the comprehensive energy system, wherein the energy quality coefficients are the ratio of the maximum work which can be done by the different energy sources to the total energy of the different energy sources;

s2, calculating an evaluation index of the comprehensive energy system energy efficiency evaluation index system based on the energy quality coefficient;

s3, calculating the weight and the combined weight of the evaluation index;

and S4, optimizing each index according to the weight and the combined weight to obtain the final evaluation index weight, and sequencing the evaluation indexes.

2. The method for analyzing energy efficiency of regional-level integrated energy system according to claim 1, wherein in step S1, the energy-quality coefficients λ of different energy sources are calculated as follows:

in the formula, Q is the total energy of various energy sources; w is owned by energy

The number of the cells.

3. The method for analyzing the energy efficiency of the regional-level integrated energy system according to claim 2, wherein the calculating of the energy quality coefficients of the different energy sources of the integrated energy system specifically comprises:

energy mass coefficient lambda of fuel_{Burning device}Expressed as:

T_{burning device}Temperature of flue gas, T, produced for combustion of fuel₀Is the low temperature heat source temperature;

energy mass coefficient lambda of natural gas_gasExpressed as:

energy mass coefficient lambda of coal_coalExpressed as:

energy-mass coefficient lambda of municipal hot water_{Hot water}Expressed as:

the energy mass coefficient of municipal steam is expressed as:

in the formula, T_{Steam generator}Is saturation corresponding to steam pressure(ii) temperature;

in the process of increasing the water supply temperature of the chilled water to the water return temperature of the chilled water, the energy quality coefficient lambda of the chilled water_{Chilled water}Expressed as:

in the formula, T_gAnd T_hRespectively the supply and return water temperatures, T, of the chilled water₀Is the low temperature heat source temperature.

4. The method for analyzing the energy efficiency of the regional-level integrated energy system according to claim 1, wherein in step S2, the evaluation indexes of the energy efficiency evaluation index system of the integrated energy system include a primary index and a secondary index, and the primary index includes an energy supply subsystem, an energy conversion subsystem, a medium-low voltage power grid, economic benefits and social benefits; the secondary indexes comprise power supply subsystem energy efficiency, cooling subsystem energy efficiency, heating subsystem energy efficiency, gas supply subsystem energy efficiency, power system energy efficiency, electricity-to-heat/cold energy conversion equipment energy efficiency, gas-to-electricity/heat energy conversion equipment energy efficiency, heat-to-cold energy conversion equipment energy efficiency, low-voltage load three-phase load unbalance qualification rate, low-voltage transformer area harmonic content qualification rate, low-voltage transformer area comprehensive line loss rate, low-voltage transformer area voltage qualification rate, low-voltage transformer area main line average section, low-voltage transformer area average power supply radius, power supply reliability, economy, unit energy supply cost, financial net present value, climate change and pollutant emission.

5. The method for analyzing the energy efficiency of the regional-level integrated energy system according to claim 4, wherein the evaluation index of the energy efficiency evaluation index system of the comprehensive energy system is calculated by:

electric energy supply W in power supply subsystem_eComprises the following steps:

in the formula: eta_tRepresenting the transformer efficiency; eta_lineRepresenting the efficiency of the power line within the campus; gamma ray_e、γ_cA conversion coefficient representing electric and cold loads; we is the electric energy supply; e_chpRepresenting the electric energy generated by the triple co-generation; r_eRepresenting the electrical energy generated by renewable energy sources on the campus; p_eRepresenting externally input electrical energy; d_eAnd D_cRespectively representing the energy released by the electricity storage device and the cold storage device;

energy efficiency η of power supply subsystem_eComprises the following steps:

in the formula: eta_s,eAnd η_d,eThe storage and discharge efficiency of the power storage device is shown; s_eRepresenting the energy released by the electrical storage device;

heat and cold supply W of heat supply subsystem and cold supply subsystem_h、W_cRespectively as follows:

W_h＝[H_g-h+H_e-h+H_chp+R_h+(1-γ_h)D_h](1-0.01l_ha_h)

W_c＝[C_e-c+C_h-c+R_c+(1-γ_c)D_c](1-0.01l_ca_c)

in the formula: w_hIndicating the heat supply amount; w_cThe cooling capacity is represented; h_g-hAnd H_e-hRespectively representing the heat energy generated by natural gas and electric energy through an electric boiler and a gas boiler; h_chpRepresenting the heat energy generated by the triple co-generation; c_e-cAnd C_h-cRespectively representing cold energy converted from electric energy and heat energy through corresponding energy conversion equipment; r_h、R_cRespectively representing heat energy and cold energy generated by renewable energy sources; l_h、l_cRespectively representing the lengths of the hot and cold pipe networks; a is_h、a_cRespectively representing the dissipation rate of the hot pipe network and the cold pipe network per 100 meters; gamma ray_hIndicating thermal loadThe conversion coefficient is calculated by 6.1; d_hRepresenting the energy released by the heat storage device;

energy system energy efficiency eta of heat supply subsystem and cold supply subsystem_h、η_cAre respectively as

In the formula: eta_s,h、η_d,hRespectively showing the heat storage efficiency and the heat release efficiency of the heat storage device; eta_s,c、η_d,cShowing the cold storage and release efficiency of the cold storage device; s_h、S_cRepresenting the energy released by the heat and cold storage devices;

supply amount W of natural gas of gas supply subsystem_gComprises the following steps:

W_g＝P_g+G_e-g

in the formula: w_gRepresenting the natural gas supply; p_gRepresenting the amount of externally input natural gas; g_e-gRepresenting natural gas converted from electrical energy;

the lift Y of the water pump of the power system is as follows:

in the formula: y is₀Represents the theoretical lift, i.e. the lift at a flow rate of 0; f represents the friction coefficient; q_hpIndicating the flow rate of the pump;

the inlet and outlet lifts of the pump are Y_inAnd Y_out：

Y_loss＝Y_in-Y_out

In the formula: y is_lossRepresenting lift loss; e_hpRepresents the electrical energy required by the pump to compensate for head losses; eta_hpRepresents the efficiency of the pump; w represents the weight of the liquid;

power system transmission efficiency eta_mComprises the following steps:

in the formula: v_mRepresenting the amount of energy m transmitted through the pump; lambda [ alpha ]_mA conversion coefficient representing the energy m;

efficiency eta of electric conversion heat/cold energy conversion equipment_e-h、η_e-cComprises the following steps:

in the formula: c_OPe-hRepresents a heating coefficient of electric heating; c_OPe-cA refrigeration coefficient representing electrical refrigeration;

combined heat and power generation unit efficiency eta of gas-to-electricity/heat energy conversion equipment_chpComprises the following steps:

in the formula: e_CHP、H_chpRepresenting the electric energy and the heat energy generated by the cogeneration unit; lambda [ alpha ]_SteamRepresenting a conversion factor of the steam; g_chpNatural gas representing consumption by a cogeneration unit;

gas boiler equipment efficiency eta of gas-to-electricity/heat energy conversion equipment_g-hComprises the following steps:

in the formula: cop_g-hThe heat production coefficient of the natural gas is shown, namely the heat energy generated by the unit natural gas through the gas boiler;

efficiency eta of heat-to-cold energy conversion equipment_h-cComprises the following steps:

in the formula: cop_h-cRepresenting the refrigeration coefficient of the absorption refrigerator;

the calculation formula of the energy efficiency index of the medium and low voltage power grid is as follows:

the qualification rate of the low-voltage load three-phase load unbalance degree is that the number of the low-voltage three-phase load unbalance rate is less than 15 percent divided by the total number of the low-voltage transformer areas multiplied by 100 percent;

the qualification rate of the content of all waves in the low-voltage area is that the harmonic content meets the standard requirement, the number of the areas is divided by the total number of the low-voltage areas multiplied by 100 percent;

the comprehensive line loss rate of the low-voltage distribution area is equal to (total power supply quantity of the low-voltage distribution area-total power consumption of a household meter of the low-voltage distribution area) ÷ total power supply quantity of the low-voltage distribution area multiplied by 100%;

the low-voltage power supply voltage meeting rate is equal to the number of voltage monitoring points meeting the voltage qualification rate, divided by the total number of low-voltage E monitoring points multiplied by 100 percent;

the average section of the main line of the low-voltage transformer area is equal to the arithmetic average of the nominal sections of the main line of the low-voltage transformer area;

the average power supply radius of the low-voltage station area is equal to the arithmetic average value of the power supply radius of the low-voltage station area;

the power supply reliability is calculated by the following formula:

in the formula: lambda [ alpha ]_seRepresenting the theoretical failure rate of the power supply system; mu.s_seIndicating supply of powerThe theoretical repair rate of the system; MTTR represents the theoretical average repair time of the power supply system; MTTF represents the average running time of the power supply system before theoretical failure; f represents the theoretical average failure frequency of the power supply system;

the economic benefit indexes are as follows:

in the formula: ECI represents an economic evaluation index of the comprehensive energy system; IC (integrated circuit)_i、MC_i、SC_iThe initial investment cost, the operation maintenance cost and the scrapping cost of the ith type energy unit in the comprehensive energy system are represented; IC (integrated circuit)_EAC,i、SC_EAC,iAn equal-year value representing the initial investment cost and the scrapping cost of the i-th type energy unit; IR represents the discount rate; l is_iRepresenting the lifecycle of the i-th class of energy units;_irepresenting the annual average load rate of the i-th type energy unit; w is a_iRepresents the annual energy production, kWh, of a class i energy unit; FC_i,jA type j fuel or electricity consumption representing a unit energy production of the type i energy unit; sigma_jRepresents the purchase cost of the j-th fuel; RC (resistor-capacitor) capacitor_iRepresenting the repair and maintenance cost of the i-th type energy unit;

the unit energy supply cost is calculated by the following formula:

in the formula: LCOE represents unit cost of energy supply; i is₀Representing an initial investment; v_RRepresenting a fixed asset residual; n represents the operating year of the project; a. the_nRepresents the operating cost of the nth year; d_nRepresents the depreciation of the nth year; p_nRepresents interest in year n; y is_nRepresents the energy supply of the nth year; i represents the discount rate;

the net present financial value is calculated using the formula:

in the formula: n represents a project calculation cycle; NC (numerical control)_tRepresenting the newly increased net cash flow in the t year in the calculation period; i.e. i_cRepresenting a benchmark rate of return;

the investment recovery period is calculated by the following formula:

the financial internal rate of return is calculated using the following formula:

in the formula: n represents a project calculation cycle; NC (numerical control)_tRepresenting the newly increased net cash flow in the t year in the calculation period;

the climate change index is as follows:

in the formula: ENIC represents the climate change index of the integrated energy system; CT represents a carbon trading price; w is a_iRepresenting the annual energy supply of the i-th type energy unit in the integrated energy system;_irepresenting the annual average load rate of the i-th type energy unit; CEC_iAn equivalent carbon dioxide emission representing a unit energy yield of a unit in a reference energy system corresponding to the i-th type energy unit; CE_iAn equivalent carbon dioxide emission amount representing a unit energy supply amount of the i-th type energy unit; GHE represents the amount of greenhouse gas j emitted per unit energy supply of the i-th type energy unit;_CG,jan equivalence factor representing greenhouse gas j emissions converted to carbon dioxide emissions;

the pollutant emission indexes are as follows:

in the formula: ENIP represents a pollutant emission index of the comprehensive energy system; VP_jRepresenting the environmental value of the jth pollutant; w_iThe annual energy supply quantity, kW.h, of the i-th type energy unit in the comprehensive energy system is represented;_irepresenting the annual average load rate of the i-th type energy unit; PEC_i,jThe unit energy supply of the unit energy supply unit in the reference energy system corresponding to the ith type energy unit is expressed, and the jth pollutant is discharged; PE (polyethylene)_i,jAnd the j pollutant emission under the unit energy supply of the i type energy unit is shown.

6. The method for analyzing energy efficiency of regional-level integrated energy system according to claim 4, wherein in step S2, the evaluation index of the integrated energy system energy efficiency evaluation index system is normalized; the evaluation indexes are divided into forward type indexes, reverse type indexes and intermediate type indexes; the normalization process of the intermediate index is as follows:

wherein a and d are the lower and upper limits of the function, and b and c are the lower and upper limits of the intermediate interval [ b, c ];

the normalization process of the forward index is as follows:

wherein M is_j＝max{x_ij},m_j＝min_i{x_ij}，0≤a_ij≤1；

The normalization processing of the reverse index is as follows:

wherein M is_j＝max_i{x_ij},m_j＝min_i{x_ij}，0≤a_ij≤1。

7. The method for analyzing energy efficiency of an area-level renewable energy system according to claim 1, wherein in step S3, the process of calculating the weight of the evaluation index and the combination weight is specifically as follows:

obtaining subjective weight by using an analytic hierarchy process, obtaining objective weight by using an entropy weight method, and constructing a combined weighting method to calculate the weight of an evaluation index;

constructing a target function based on a moment estimation theory, and solving by adopting a nonlinear programming to obtain a combination weight of an evaluation index;

and optimizing each index by utilizing hierarchical clustering and expert intervention means to obtain the weight of the final evaluation index.

8. The area-level integrated energy system energy efficiency analysis method according to claim 7, wherein, in step S3,

firstly, selecting influence factors according to specific problems and establishing a hierarchy; the hierarchy includes: a target layer, a criterion layer, a sub-criterion layer and a scheme layer;

② judging the relative importance of each factor in each level, wherein u_i,u_jRepresenting factors, i ═ 1,2,3 … n, j ═ 1,2,3 … n, u_ijRepresents u_iFor u is paired_jThe relative importance values of (a) refer to the numbers 1-9 and their inverse as a scale;

all relative importance values u to be obtained_ijForming a judgment matrix P:

thirdly, the maximum characteristic root lambda of the judgment matrix needs to be solved_maxAnd the corresponding feature vector W, and then calculating the weight of the importance value:

P_W＝λ_maxw

in the formula, λ_maxIs the maximum characteristic root λ of the matrix_maxW is lambda_maxThe corresponding feature vector;

fourthly, calculating a consistency index CI:

wherein λ is_maxIn order to determine the maximum eigenvalue of the matrix,

calculating the consistency ratio

Wherein, RI is a random consistency index, RI ═ 000.520.891.121.261.361.411.461.491.521.541.561.581.59;

the objective weight is calculated by the following steps:

firstly, constructing an index matrix

m isNumber of evaluation samples, n is the number of evaluation indices, v_ij(i 1,2, …, m; j 1,2, … n) is an index value;

normalizing the index matrix to obtain a normalized index matrix:

X＝(x_ij)_mn

in the formula, x_ijThe value of the j index of the ith sample in the matrix;

determining the index weight:

in the formula, h_ijThe probability of occurrence of each index; k is a radical of_iIs the information entropy of the system; s_jThe entropy weight expressed as the j index;

the index weight column vector is as follows:

S＝(s₁,s₂,…,s_n)^T

in the formula, s_nThe nth index weight;

weighted normalization matrices are as follows:

Y＝(y_ij)_mn＝(s_jx_ij)_mn

in the formula, y_ijA j index value of an i sample of the normalization matrix;

the calculation steps of the combination weight are as follows:

assuming that the relative importance of the subjective weight vector to the combination weight is α, the relative importance of the objective weight vector to the combination weight is β, and the deviation between the combination weight vector W and the subjective weight vector T is minimum, it is described by the following formula:

minH(w_j)＝α×(w_j-t_j)²+β×(w_j-s_j)²

∑w_j＝1,1≤j≤n

calculating the relative importance coefficient of the subjective and objective weight vector of the single index by using the subjective weight and the objective weight actual value of each index:

aiming at the evaluation indexes in the multi-decision matrix, calculating the relative importance coefficients of the overall subjective and objective weight vector:

for each index w_jWith H (w)_i) The minimum is excellent, and the following formula is converted:

converting the multi-objective optimization model into a single-objective optimization model for solving:

the step of optimizing each index by utilizing hierarchical clustering and expert intervention means is as follows:

firstly, each object is a cluster, the number of the objects contained in each cluster is 1, and the mutual distance between the clusters is calculated to obtain a distance matrix;

two clusters closest to each other are combined into a new cluster;

recalculating the distance between the new cluster and the original cluster, and selecting the average distance between the new cluster and the original cluster as the distance between the two clusters;

fourthly, continuously repeating the third step and the fourth step until only one cluster is left or the end condition is reached: the number of clusters reaches a specified number or the inter-cluster distance reaches a threshold.

9. The method for analyzing energy efficiency of regional-level integrated energy system according to claim 1, wherein in step S4, the evaluation indexes are ranked as follows:

(1) the scheme set of the multi-index decision problem is C ═ C₁,C₂,…,C_m) The index set is M ═ M (M)₁,M₂,…,M_n) Scheme M_jFor index C_iAn evaluation value of r_ij(i 1,2, …, n; j 1,2, …, m), the multi-objective decision matrix R is obtained:

(2) by the matrix R ═ (R)_ij)_m×nSum weight vector W ═ W₁,w₂,…,w_m) Multiplying to form a weighted decision matrix Z ═ (Z)_ij)_m×n；

Calculating the positive ideal solution and the negative ideal solution of the index to obtain a positive ideal solution vector Z⁺And a negative ideal solution vector Z^-：

In the formula (I), the compound is shown in the specification,

(3) calculating the distance from each scheme to the ideal solution

Distance from the negative ideal solution

(4) Calculating the relative closeness of the comprehensive evaluation of each evaluation object:

(5) according to C_jAnd sorting the evaluation objects from big to small.

10. An area-level comprehensive energy system energy efficiency analysis system is characterized by comprising:

the energy quality coefficient calculation module is used for calculating the energy quality coefficients of different energy sources of the comprehensive energy system;

the evaluation index calculation module is used for calculating the evaluation index of the comprehensive energy system energy efficiency evaluation index system;

the weight calculation module is used for calculating the weight and the combined weight of the evaluation indexes;

and the index sorting module is used for sorting the evaluation indexes.

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