CN110991870A - Intensive characteristic comprehensive energy system data processing and calculating method - Google Patents
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Abstract
The invention discloses a comprehensive energy system data processing and calculating method with intensive characteristics, which comprises the following steps: acquiring data of the comprehensive energy system, and acquiring an integrated energy system evaluation index system with intensive characteristics; constructing a calculation formula of each index in an evaluation index system; determining the weight of each index in each index calculation formula; carrying out statistics on related parameters of intensive characteristic evaluation in the data of the comprehensive energy system; evaluating and counting according to intensive characteristics of the comprehensive energy system; the method and the device have the advantages that the determination of the integrated energy system intensive characteristic index system is focused, the index system is established aiming at the system planning scheme, the integrated energy system intensive characteristic is fully considered, the system energy planning process and result can be comprehensively planned, and the provided evaluation index system has universal adaptability.
Description
Technical Field
The invention relates to the technical field of data processing of an integrated energy system, in particular to a data processing and calculating method of the integrated energy system with intensive characteristics.
Background
The comprehensive energy system realizes mutual energy complementation, effectively improves the energy utilization rate, and provides a feasible way for solving the problem of new energy consumption, reducing environmental pollution and reducing fossil energy consumption; the establishment of a reasonable index system and the establishment of a perfect evaluation mechanism become important problems to be researched in the development process of the comprehensive energy system.
Most of the existing researches aim at a comprehensive energy system, an evaluation index system is constructed from different angles, and the aspects of operation, reliability, benefit and the like of the comprehensive energy system are evaluated. Some documents analyze the composition and the characteristics of the comprehensive energy system facing the park microgrid, consider 4 influence factors in the aspects of economy, reliability, energy consumption and environmental protection, establish an index evaluation model of the comprehensive energy system facing the park microgrid, determine the weight assignment of each index based on an Analytic Hierarchy Process (AHP) -improved entropy weight method, and establish a multi-criterion evaluation system; some documents establish different energy systems based on main equipment of a distributed energy system, solve to obtain optimal configuration, operation strategies and evaluation index values of the different systems according to cooling, heating and power load requirements, energy prices, equipment technical information and the like, establish an index evaluation matrix of the distributed energy system, solve weight distribution of different indexes by using an information entropy principle, and determine importance index weights by combining an expert evaluation method.
In summary, the existing evaluation index system of the comprehensive energy system mostly considers the synergistic effect of each energy in the system, and the multi-energy collaborative planning aims at realizing the intensive utilization of the construction planning of the energy system and various resources, the existing evaluation index system lacks the investigation on the fundamental target of the comprehensive energy system and lacks the integrity, the existing evaluation index system mostly sets the standard only aiming at the characteristics of a single stage for evaluation, and the index system lacks the universality.
In the planning stage of the comprehensive energy system, aiming at the characteristics of the energy system in different development stages, the concentration characteristic and the saving characteristic of the planning scheme of the comprehensive energy system are described through the intensive characteristic, the intensive degrees of different planning schemes are obtained through solving and are compared, the optimal planning scheme of the comprehensive energy system for the development and construction of the region, which gives consideration to the concentration characteristic and the saving characteristic, is obtained, and reference is provided for the construction and planning decision of the comprehensive energy system.
At present, research aiming at the evaluation of the comprehensive energy system is systematically developed, an evaluation index system considering economy, environment and efficiency is established, the development stage of the system is judged according to the coupling degree, the equipment utilization degree, the permeability of renewable energy sources, the energy conversion efficiency and the like of each stage of the comprehensive energy system, and a calculation model of main indexes is provided; in an evaluation index system of the comprehensive energy system, evaluation indexes and models of coupling equipment are lacked; the term "consolidation" includes concentration and conservation, and is used for measuring the relationship between the system income and the consumption, and it is scientific and reasonable to use the consolidation characteristic to express the quality of the comprehensive energy system planning.
Disclosure of Invention
This section is for the purpose of summarizing some aspects of embodiments of the invention and to briefly introduce some preferred embodiments. In this section, as well as in the abstract and the title of the invention of this application, simplifications or omissions may be made to avoid obscuring the purpose of the section, the abstract and the title, and such simplifications or omissions are not intended to limit the scope of the invention.
The invention is provided in view of the problem that the evaluation index under the intensive characteristic is not considered in the comprehensive energy system evaluation index system in the conventional comprehensive energy system evaluation and calculation method with the intensive characteristic.
Therefore, the invention aims to provide an integrated energy system data processing and calculating method with intensive characteristics.
In order to solve the technical problems, the invention provides the following technical scheme: a comprehensive energy system data processing and calculating method with intensive characteristics comprises the following steps: acquiring data of the comprehensive energy system, and acquiring an integrated energy system evaluation index system with intensive characteristics; constructing a calculation formula of each index in an evaluation index system; determining the weight of each index in each index calculation formula; carrying out statistics on related parameters of intensive characteristic evaluation in the data of the comprehensive energy system; and evaluating and counting according to the intensive characteristics of the comprehensive energy system.
As a preferable aspect of the intensive characteristic integrated energy system data processing and calculating method of the present invention, wherein: the comprehensive energy system planning evaluation index system considering the intensive characteristics comprises various correlation indexes of the carding comprehensive energy system.
As a preferable aspect of the intensive characteristic integrated energy system data processing and calculating method of the present invention, wherein: the indexes comprise economic benefit indexes, intensive benefit indexes, reliability indexes and environmental benefit indexes.
As a preferable aspect of the intensive characteristic integrated energy system data processing and calculating method of the present invention, wherein: the economic benefit index comprises initial input cost and net present value;
wherein the economic benefit index has an initial input cost CI,SThe calculation formula is as follows:
in the formula, n is the total number of equipment in the energy system; n is a radical ofNOMSimulating a total number of years for the energy system; ci,invAnnual initial investment cost is set for the ith equipment in the energy system; ci,insAnnual installation cost for the ith equipment in the energy system; ci,opcAnnual operation and maintenance cost of the ith equipment in the energy system; ci,chThe annual charge and discharge cost of the ith equipment in the energy system is saved; ci,eAnnual energy utilization cost of the ith equipment in the energy system;
wherein, the calculation formula of the net present value NPV of the economic benefit index is as follows:
in the formula, Ck,IThe k year fund inflow of the energy system; ck,OThe k year fund outflow amount of the energy system; r is the discount rate (reference profitability); k is the number of years of use.
As a preferable aspect of the intensive characteristic integrated energy system data processing and calculating method of the present invention, wherein: the intensive benefit indexes comprise coupling degree, coupling efficiency, energy utilization rate, equipment utilization rate and land utilization rate;
wherein the coupling degree η of the intensive benefit indexCThe calculation formula is as follows:
in the formula, EOI,GThe total amount of natural gas flowing into the coupling device in the energy system; eOI,PThe total amount of electricity flowing into the coupling device in the energy system; eI,GThe total natural gas input amount in the energy system; eI,PInputting total electric quantity into an energy system; lambda [ alpha ]GThe natural gas energy quality coefficient;
wherein the coupling efficiency η of the intensive benefit indexCEThe calculation formula is as follows:
in the formula, EOO,GOutputting the total natural gas quantity for the energy system coupling equipment; eOO,CThe total output cold quantity of the energy system coupling equipment is provided; eOO,HThe total output heat of the coupling equipment of the energy comprehensive system is provided; eOO,PThe total output electric quantity of the coupling equipment of the energy comprehensive system is provided; eO,GOutputting the total natural gas quantity for the energy system; eOI,PFor the total amount of electricity flowing into the coupling device in the energy system；λCEnergy quality coefficient of cold consumption; lambda [ alpha ]HEnergy-mass coefficient for heat consumption; lambda [ alpha ]GThe natural gas energy quality coefficient;
wherein the energy utilization rate η of the intensive benefit indexAUThe calculation formula is as follows:
in the formula, EO,GOutputting the total natural gas quantity for the energy system; eO,CThe total output cold quantity of the energy system is provided; eO,HThe total output heat of the energy system; eO,PThe total output electric quantity of the energy system is obtained; eI,PInputting total electric quantity into an energy system; lambda [ alpha ]CEnergy quality coefficient of cold consumption; lambda [ alpha ]HEnergy-mass coefficient for heat consumption; lambda [ alpha ]GThe natural gas energy quality coefficient;
wherein the equipment utilization η of the intensive benefit indexdeviceThe calculation formula is as follows:
in the formula, t0Planning the working time length for the equipment on average; t is tnThe actual working time of the nth equipment is taken as the actual working time of the nth equipment; n is the total number of equipment in the energy system;
wherein the land utilization η of the intensive benefit indexgroundThe calculation formula is as follows:
in the formula, SiThe occupied area of the ith equipment in the energy system is occupied; eI,PInputting total electric quantity into an energy system; n is the total number of equipment in the energy system; eI,GThe total natural gas input amount in the energy system; lambda [ alpha ]GIs the natural gas energy quality coefficient.
As a preferable aspect of the intensive characteristic integrated energy system data processing and calculating method of the present invention, wherein: the reliability indexes comprise failure frequency of the energy supply system, average failure duration of the energy supply system, expected shortage of energy of the energy supply system and average availability of energy supply;
wherein, the energy supply system fault frequency SAIFI calculation formula of the reliability index is as follows:
in the formula, CPThe times of insufficient power supply in the simulation process of the energy system are determined; cCThe times of insufficient cooling in the simulation process of the energy system are determined; cHThe times of insufficient heating system in the energy system simulation process are counted; cGThe times of insufficient air supply in the simulation process of the energy system are determined; lambda [ alpha ]CEnergy quality coefficient of cold consumption; lambda [ alpha ]HEnergy-mass coefficient for heat consumption; n is a radical ofNUMThe total number of users lack energy supply;
wherein, the calculation formula of the average fault duration SAIDI of the energy supply system of the reliability index is as follows:
in the formula, DPThe total duration of insufficient power supply in the energy system simulation process is provided; dCProviding the total duration of insufficient cooling in the energy system simulation process; dHThe insufficient heat supply duration time in the energy system simulation process is provided; dGThe total duration of insufficient gas supply in the energy system simulation process is set; lambda [ alpha ]CEnergy quality coefficient of cold consumption; lambda [ alpha ]HEnergy-mass coefficient for heat consumption; n is a radical ofNUMThe total number of users lack energy supply; lambda [ alpha ]GThe natural gas energy quality coefficient;
wherein, the expected energy supply lacking EENS calculation formula of the energy supply system of the reliability index is as follows:
in the formula, Nt is an energy systemTotal number of time periods in the simulation process; viSupplying energy for the lack of energy in the ith time period in the simulation process of the energy system;
wherein, the average energy supply availability ASAI calculation formula of the reliability index is as follows:
wherein 8760 is the total hours per year, and the simulation of the reliability operation condition is generally carried out by taking the year as a unit; dNUMThe duration of the energy supply shortage of the comprehensive energy system is prolonged; n is a radical ofNUMThe total number of users lack energy supply for the comprehensive energy system.
As a preferable aspect of the intensive characteristic integrated energy system data processing and calculating method of the present invention, wherein: the environmental benefit indicators include renewable energy permeability and pollutant emission level;
wherein the environmental benefit indicator has renewable energy permeability ηREThe calculation formula is as follows:
in the formula, EROThe total amount of energy generated for the energy system using renewable energy; eOThe total energy output in the energy system;
wherein the environmental benefit index pollutant emission level IEThe calculation formula is as follows:
in the formula, ve,iThe environmental value of the ith pollutant in the energy system; v isp,iA penalty factor for the ith pollutant in the energy system; v. ofk,iThe discharge coefficient of the ith pollutant; x represents the generation of x major pollutants in the energy system;
wherein, the i-th pollutants, i ═ 1,2 and 3 respectively represent pollutants CO2、SO2NOx, wherein:
ERO＝ERO,G·λG+ERO,C·λC+ERO,H·λH+ERO,P
EO＝EO,G·λG+EO,C·λC+EO,H·λH+EO,P
in the formula, ERO,GThe amount of gas generated for utilizing renewable resources in an energy system; eRO,CThe cold energy generated by renewable resources in the energy system is utilized; eRO,HHeat generated for utilization of renewable resources in an energy system; eRO,PElectricity generated by renewable resources in an energy system; eO,GOutputting the total natural gas quantity for the energy system; eO,CThe total output cold quantity of the energy system is provided; eO,HThe total output heat of the energy system; eO,PThe total output electric quantity of the energy system is obtained; lambda [ alpha ]CEnergy quality coefficient of cold consumption; lambda [ alpha ]HEnergy-mass coefficient for heat consumption; lambda [ alpha ]GIs the natural gas energy quality coefficient.
As a preferable aspect of the intensive characteristic integrated energy system data processing and calculating method of the present invention, wherein: the step of determining the weight of each index in each index calculation formula comprises the following steps:
carrying out normalization and standardization processing on each index;
calculating the entropy value of each index information in the evaluation system by adopting an entropy weight method;
determining each index weight.
As a preferable aspect of the intensive characteristic integrated energy system data processing and calculating method of the present invention, wherein: the step of counting the parameters related to intensive characteristic evaluation in the integrated energy system data comprises the following steps:
counting the planning evaluation related parameters of the comprehensive energy system considering the intensive characteristics;
collecting relevant data in a statistical manner;
the data comprises historical operation data and planning stage prediction data in an evaluation target time period.
As a preferable aspect of the intensive characteristic integrated energy system data processing and calculating method of the present invention, wherein: and calculating the comprehensive energy system planning evaluation score by taking a specific time interval as a unit according to the comprehensive energy system intensive characteristic evaluation statistics.
The invention has the beneficial effects that: the comprehensive energy system data processing algorithm fully considers the intensive characteristics, and the comprehensive energy system intensive characteristics are more pertinently considered to construct an energy system planning evaluation index system, so that reference is provided for selection of a comprehensive energy system planning scheme, the index system is established for the system planning scheme, the comprehensive energy system intensive characteristics are fully considered, the system energy planning process and result can be comprehensively planned, and the proposed evaluation index system has general adaptability.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise. Wherein:
fig. 1 is a schematic diagram of the overall structure of the integrated energy system data processing and calculating method of the intensive nature according to the present invention.
Fig. 2 is a flowchart of the steps of determining the weight of each index according to the integrated energy system data processing and calculating method of the intensive characteristics of the present invention.
Fig. 3 is a flowchart of the steps of weighting each index by using an entropy weight method according to the intensive comprehensive energy system data processing and calculating method of the present invention.
Fig. 4 is a flow chart of the steps of calculating the parameters related to the evaluation of the intensive characteristics of the integrated energy system planning according to the data processing and calculating method of the integrated energy system with intensive characteristics of the present invention.
Fig. 5 is a schematic structural diagram of an integrated energy system planning scheme of the integrated energy system data processing and computing method of the intensive nature according to the present invention.
FIG. 6 is a distribution diagram of the indexes of the integrated energy system data processing and calculating method according to the intensive feature of the present invention.
Fig. 7 is a structural diagram illustrating entropy values and weights of indexes of the integrated energy system data processing and calculating method with intensive characteristics.
Detailed Description
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in detail below.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, but the present invention may be practiced in other ways than those specifically described and will be readily apparent to those of ordinary skill in the art without departing from the spirit of the present invention, and therefore the present invention is not limited to the specific embodiments disclosed below.
Furthermore, reference herein to "one embodiment" or "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one implementation of the invention. The appearances of the phrase "in one embodiment" in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments.
Furthermore, the present invention is described in detail with reference to the drawings, and in the detailed description of the embodiments of the present invention, the cross-sectional view illustrating the structure of the device is not enlarged partially according to the general scale for convenience of illustration, and the drawings are only exemplary and should not be construed as limiting the scope of the present invention. In addition, the three-dimensional dimensions of length, width and depth should be included in the actual fabrication.
Example 1
Referring to fig. 1, there is provided an overall structural diagram of a method for processing and calculating integrated energy system data of intensive characteristics, as shown in fig. 1, the method for processing and calculating integrated energy system data of intensive characteristics includes the following steps:
s1: acquiring data of the comprehensive energy system, and acquiring an integrated energy system evaluation index system with intensive characteristics;
s2: constructing a calculation formula of each index in an evaluation index system;
s3: determining the weight of each index in each index calculation formula;
s4: carrying out statistics on related parameters of intensive characteristic evaluation in the data of the comprehensive energy system;
s5: and evaluating and counting according to the intensive characteristics of the comprehensive energy system.
Specifically, the main structure of the invention comprises the following steps:
s1: acquiring data of the comprehensive energy system, and acquiring an integrated energy system evaluation index system with intensive characteristics; the comprehensive energy system evaluation index system with the intensive characteristics is obtained according to the selection of comprehensive energy system planning equipment, a basic framework and the intensive characteristics, the equipment selection comprises CCHP, P2G, a gas turbine, a ground source heat pump and the like, the basic framework comprises basic frameworks such as electrical coupling, electric-thermal coupling, gas-thermal coupling and the like, and it needs to be noted that the comprehensive energy system planning evaluation index system with the intensive characteristics considered is obtained and also comprises various correlation indexes of the comprehensive energy system, and each index comprises an economic benefit index, an intensive benefit index, a reliability index and an environmental benefit index;
further, the comprehensive energy system planning evaluation index system with intensive characteristics comprises:
s2: constructing a calculation formula of each index in an evaluation index system; the method specifically plans and evaluates each index calculation formula in an index system, plans the purpose according to the operation characteristics of each energy device of the comprehensive energy system, and needs to be explained that the indexes are divided into a centralized characteristic index and a saving characteristic index, wherein each index comprises an economic benefit index, an intensive benefit index, a reliability index and an environmental benefit index, the operation characteristics of each energy device comprise a utilization rate, an operation efficiency, a pollutant emission level and the like, and the planning purpose is to realize the energy cascade utilization through the multi-energy coupled centralized planning, and finally achieve the purposes of economic saving, resource saving and environmental benefit improvement.
Further, the economic benefit index comprises initial investment cost and net present value; wherein the initial input cost C of economic benefit indexI,SThe calculation formula is as follows:
in the formula, n is the total number of equipment in the energy system; n is a radical ofNOMSimulating a total number of years for the energy system; ci,invAnnual initial investment cost is set for the ith equipment in the energy system; ci,insAnnual installation cost for the ith equipment in the energy system; ci,opcAnnual operation and maintenance cost of the ith equipment in the energy system; ci,chThe annual charge and discharge cost of the ith equipment in the energy system is saved; ci,eAnnual energy utilization cost of the ith equipment in the energy system;
the calculation formula of the net present value NPV of the economic benefit index is as follows:
in the formula, Ck,IThe k year fund inflow of the energy system; ck,OThe k year fund outflow amount of the energy system; r is the discount rate (reference profitability); k is the number of years of use.
Further, the intensive benefit indexes comprise coupling degree, coupling efficiency, energy utilization rate, equipment utilization rate and land utilization rate, wherein the coupling degree η of the intensive benefit indexesCThe calculation formula is as follows:
in the formula, EOI,GThe total amount of natural gas flowing into the coupling device in the energy system; eOI,PThe total amount of electricity flowing into the coupling device in the energy system; eI,GThe total natural gas input amount in the energy system; eI,PInputting total electric quantity into an energy system; lambda [ alpha ]GThe natural gas energy quality coefficient;
wherein the coupling efficiency η of the intensive benefit index is integratedCEThe calculation formula is as follows:
in the formula, EOO,GOutputting the total natural gas quantity for the energy system coupling equipment; eOO,CThe total output cold quantity of the energy system coupling equipment is provided; eOO,HThe total output heat of the coupling equipment of the energy comprehensive system is provided; eOO,PThe total output electric quantity of the coupling equipment of the energy comprehensive system is provided; eO,GOutputting the total natural gas quantity for the energy system; eOI,PThe total amount of electricity flowing into the coupling device in the energy system; lambda [ alpha ]CEnergy quality coefficient of cold consumption; lambda [ alpha ]HEnergy-mass coefficient for heat consumption; lambda [ alpha ]GThe natural gas energy quality coefficient;
wherein, the energy utilization rate η of the intensive benefit index is integratedAUThe calculation formula is as follows:
in the formula, EO,GOutputting the total natural gas quantity for the energy system; eO,CThe total output cold quantity of the energy system is provided; eO,HThe total output heat of the energy system; eO,PThe total output electric quantity of the energy system is obtained; eI,PInputting total electric quantity into an energy system; lambda [ alpha ]CEnergy quality coefficient of cold consumption; lambda [ alpha ]HEnergy-mass coefficient for heat consumption; lambda [ alpha ]GThe natural gas energy quality coefficient;
wherein the equipment utilization rate η of the intensive benefit index is integrateddeviceThe calculation formula is as follows:
in the formula, t0Planning the working time length for the equipment on average; t is tnThe actual working time of the nth equipment is taken as the actual working time of the nth equipment; n is the total number of equipment in the energy system;
wherein the content of the first and second substances,land utilization η of intensive benefit indexgroundThe calculation formula is as follows:
in the formula, SiThe occupied area of the ith equipment in the energy system is occupied; eI,PInputting total electric quantity into an energy system; n is the total number of equipment in the energy system; eI,GThe total natural gas input amount in the energy system; lambda [ alpha ]GIs the natural gas energy quality coefficient.
Further, the reliability indexes comprise failure frequency of the energy supply system, average failure duration of the energy supply system, expected shortage of energy of the energy supply system and average availability of the energy supply; wherein, the energy supply system fault frequency SAIFI computational formula of reliability index is:
in the formula, CPThe times of insufficient power supply in the simulation process of the energy system are determined; cCThe times of insufficient cooling in the simulation process of the energy system are determined; cHThe times of insufficient heating system in the energy system simulation process are counted; cGThe times of insufficient air supply in the simulation process of the energy system are determined; lambda [ alpha ]CEnergy quality coefficient of cold consumption; lambda [ alpha ]HEnergy-mass coefficient for heat consumption; n is a radical ofNUMThe total number of users lack energy supply for the comprehensive energy system;
the SAIDI calculation formula of the mean fault duration time of the energy supply system of the reliability index is as follows:
in the formula, DPThe total duration of insufficient power supply in the energy system simulation process is provided; dCProviding the total duration of insufficient cooling in the energy system simulation process; dHThe insufficient heat supply duration time in the energy system simulation process is provided; dGFor use in the simulation of energy systemsInsufficient gas supply for a total duration; lambda [ alpha ]CEnergy quality coefficient of cold consumption; lambda [ alpha ]HEnergy-mass coefficient for heat consumption; n is a radical ofNUMThe total number of users lack energy supply for the comprehensive energy system; lambda [ alpha ]GThe natural gas energy quality coefficient;
the expected energy supply lacking EENS calculation formula of the energy supply system of the reliability index is as follows:
in the formula, Nt is the total number of time periods in the simulation process of the energy system; viSupplying energy for the lack of energy in the ith time period in the simulation process of the energy system; vP,iThe power shortage in the ith time period in the simulation process of the comprehensive energy system is realized; vC,iThe lack of the supplied cold energy in the ith time period in the simulation process of the comprehensive energy system; vH,iThe heat supply shortage in the ith time period in the simulation process of the comprehensive energy system is realized; vG,iThe gas shortage in the ith time period in the simulation process of the comprehensive energy system is realized; lambda [ alpha ]GThe natural gas energy quality coefficient;
wherein, the average energy supply availability ASAI calculation formula of the reliability index is as follows:
wherein 8760 is the total hours per year, and the simulation of the reliability operation condition is generally carried out by taking the year as a unit; dNUMThe duration of the energy supply shortage of the comprehensive energy system is prolonged; n is a radical ofNUMThe total number of users lack energy supply for the comprehensive energy system.
Further, the environmental benefit index comprises the renewable energy permeability and the pollutant emission level, wherein the renewable energy permeability η of the environmental benefit indexREThe calculation formula is as follows:
in the formula, EROFor the benefit of energy systemTotal amount of energy generated with renewable energy; eOThe total energy output in the energy system;
wherein the environmental benefit index pollutant emission level IEThe calculation formula is as follows:
in the formula, ve,iThe environmental value of the ith pollutant in the energy system; v isp,iA penalty factor for the ith pollutant in the energy system; v. ofk,iThe discharge coefficient of the ith pollutant; x represents the generation of x major pollutants in the energy system;
wherein, the i-th pollutant, i ═ 1,2 and 3 respectively represent pollutant CO2、SO2NOx, wherein:
ERO＝ERO,G·λG+ERO,C·λC+ERO,H·λH+ERO,P
EO＝EO,G·λG+EO,C·λC+EO,H·λH+EO,P
in the formula, ERO,GThe amount of gas generated for utilizing renewable resources in an energy system; eRO,CThe cold energy generated by renewable resources in the energy system is utilized; eRO,HHeat generated for utilization of renewable resources in an energy system; eRO,PElectricity generated by renewable resources in an energy system; eO,GOutputting the total natural gas quantity for the energy system; eO,CThe total output cold quantity of the energy system is provided; eO,HThe total output heat of the energy system; eO,PThe total output electric quantity of the energy system is obtained; lambda [ alpha ]CEnergy quality coefficient of cold consumption; lambda [ alpha ]HEnergy-mass coefficient for heat consumption; lambda [ alpha ]GIs the natural gas energy quality coefficient.
It should be noted that the energy-quality coefficients are all calculated according to the second law of thermodynamics to obtain the energy-quality coefficient lambda based on the electric energy, so as to solve the problem that the energy dimensions in the energy system are not uniform, visually express the grades of different energies,wherein, the energy quality coefficient includes: natural gas energy quality coefficient lambdagasEnergy-quality coefficient lambda of municipal hot waterhotwEnergy-mass coefficient lambda of municipal steamsteamEnergy mass coefficient lambda of chilled watercoldwEnergy quality coefficient lambda of cold consumptionCAnd the energy-mass coefficient lambda of the heat consumptionHNatural gas energy quality coefficient lambdagasEnergy-quality coefficient lambda of municipal hot waterhotwEnergy-mass coefficient lambda of municipal steamsteamEnergy mass coefficient lambda of chilled watercoldwEnergy quality coefficient lambda of cold consumptionCAnd the energy-mass coefficient lambda of the heat consumptionHThe calculation formula of (a) is as follows:
in the formula, TgasThe temperature (K) at which the natural gas is completely combusted; t is0For reference temperature, K, η is averaged to obtain an average conversion efficiency of 0.8, TgAnd ThSupply water temperature and return water temperature K of municipal hot water respectively; t issteamSaturation temperature (K) corresponding to steam pressure; t is the dew point temperature.
S3: determining the weight of each index in each index calculation formula; wherein, the step of determining each index weight comprises:
s31: carrying out normalization and standardization processing on each index;
s32: calculating information entropy values of all indexes in an evaluation system by adopting an entropy weight method, wherein the information entropy values of all indexes can be obtained according to the difference degree of the index values of different planning schemes, and each index has an information entropy value;
s33: determining each index weight.
Further, the specific step of solving the weight of each index by using the entropy weight method comprises the following steps:
s321: evaluation schemes for n comparative analyses are designated Y ═ Y1,y2,…,yn](ii) a The index system has m evaluation indexes, and is marked as X ═ X1,x2,…,xm](ii) a Scheme yiThe next jth index value is denoted as aijWhere i is 1,2, …, n, j is 1,2, …, m.
S322: for the index that needs to be maximized, normalization is performed using the following formula to obtain the yiNormalized value b of the next j indexij：
For the index to be minimized, normalization is performed using the following formula to obtain the yiNormalized value b of the next j indexij：
S323: normalizing the normalized index value to calculate the y-th index value by the following formulaiNormalized value P of the next j indexij：
S324: calculating the size of information entropy of each index, and solving the weight of the jth index by combining the information entropy, wherein the important index values comprise: the information entropy ej of the jth index, the weight ω j of the jth index,
wherein k is 1/lnn
S4: carrying out statistics on related parameters of intensive characteristic evaluation in the data of the comprehensive energy system; the method comprises the following steps of calculating relevant parameters of the planning intensive characteristic evaluation of the comprehensive energy system:
s41: counting the planning evaluation related parameters of the comprehensive energy system considering the intensive characteristics;
s42: collecting relevant data in a statistical manner;
the data comprises historical operating data and planning stage prediction data in an evaluation target time period, and according to a comprehensive energy system planning evaluation index system considering intensive characteristics, the data required to be collected comprises the following steps: the method comprises the following steps of measuring the environmental temperature of an area to be evaluated, the energy price of the area to be evaluated, the output curve of each energy supply unit, the load curve of each typical day, the installation cost of each unit, the operation and maintenance cost, the energy consumption cost, the pollutant discharge condition, each load prediction curve and each energy prediction price.
S5: and (4) evaluating and counting according to the intensive characteristics of the comprehensive energy system, wherein reasonable time intervals are selected according to the formula of S2 and the weight determined by the formula of S3 by adopting the data acquired by S4, and time-interval-by-time calculation is carried out to form a planning evaluation score of the comprehensive energy system taking a specific time interval as a unit.
Example 2
As shown in fig. 5, the integrated energy system mainly comprises the following three parts: an IEEE14 node power distribution system, an 11 node natural gas distribution system and a 15 node thermodynamic system are arranged, and an IEEE14 node power node 6 is connected with a node 1 in a natural gas network through a gas turbine; the power nodes 4 and 9 are respectively connected with a wind power generator set, in order to absorb wind power to the maximum extent and avoid the blockage of a natural gas network line, the input end of electricity-to-gas conversion is connected with the node 9 of a power network, the output end of electricity-to-gas conversion is connected with the node 7 of the natural gas network, meanwhile, the nodes 4 and 9 of the power network are respectively connected with an electric energy storage device, and a thermal power generator set on the power node 2 is changed into a CCHP connected with a thermal power node 8 and simultaneously connected with the node 1 of the natural gas network.
Assuming that three planning schemes are applied to the system, the planning targets are respectively the best economic benefit, the best environmental benefit and the maximum coupling degree, the specific planning scheme is shown in table 1, and the economic parameters and the reliability parameters of each energy device are shown in table 2.
Table 1 comprehensive energy system planning scheme table
TABLE 2 economic and reliability parameter table for energy supply equipment
And calculating a method based on each index according to the existing planning data and each parameter of the energy equipment.
Wherein, when carrying out reliability analysis, the trouble component and the equipment of considering include: a distribution line, a hot water pipeline, a gas turbine, a gas boiler, an electric boiler and an electric refrigerator; in making the environmental benefit calculations, the air pollutants considered include: CO2, SO2 and NOx, in combination with the pollutant emission situation of each energy device, are used to calculate each index value for each integrated energy system planning scheme simulation, as shown in table 3, the following conditions are provided:
in the first scheme, because the initial input cost of the coupling equipment and the distributed power supply is high, the second scheme which is planned by taking the highest economic benefit as a target has less coupling equipment and lower coupling degree;
the scheme II is that more traditional energy supply devices are still planned and installed in the planning scheme due to low coupling degree, and the traditional energy supply devices have high energy utilization cost, so that the net present value on the time section of the decade is low while the renewable energy consumption rate improving capacity of the system is poor;
according to the third scheme, the coupling degree is taken as a planning target, the installation capacity of the coupling equipment is large, but the initial investment cost is high, the utilization rate of the equipment is reduced, and meanwhile, the energy conversion efficiency, the net present value and the environment sustainable capability are improved along with the improvement of the permeability and the consumption rate of renewable energy;
compared with an independent planning system, the renewable energy permeability of all planning schemes is improved, so that the energy utilization rate of each scheme exceeds 1.
TABLE 3 evaluation index calculation results
TABLE 4 evaluation index calculation results at B stage
Based on the integrated energy system intensive characteristic index system, various indexes of various planning evaluation schemes are standardized and normalized, the distribution condition of various index values is calculated and obtained as shown in fig. 6, and then the entropy value and the weight of each index are calculated and obtained according to an entropy weight method as shown in fig. 7.
The result shows that the difference degree of the indexes 4 and 9 is maximum, the difference between the energy utilization rate and the environment sustainable improvement capacity is maximum, the corresponding information entropy is minimum, the weight occupied by the index is maximum in the final evaluation calculation, the purpose of comprehensively examining the centralized characteristics and the saving characteristics of the comprehensive energy system in intensive evaluation can be achieved, and the weight design is consistent with the design purpose of an evaluation system.
According to the calculated information entropy and the calculated index weight, the evaluation value of each planning scheme can be calculated by combining calculated values of each index of the system, as shown in table 5, in the evaluation value of each planning scheme calculated according to the size of the objective evaluation index, the evaluation of the scheme two is higher, and compared with the scheme one, the evaluation method has the advantages of lower operation and maintenance cost, lower environmental management cost, better renewable energy consumption rate improving capability and environmental sustainability improving capability; in the third scheme, the capacity of centralized supply of each energy source in the system is improved, so that the initial input cost is too high, the overall cost of the system is higher, and the improvement space is provided compared with the second scheme.
TABLE 5 evaluation results of intensive characteristics of integrated energy systems
| Planning scheme | Scheme one | Scheme two | Scheme three |
| Evaluation value of A stage | 0.406 | 0.367 | 0.258 |
| Evaluation value of B stage | 0.297 | 0.408 | 0.377 |
It is important to note that the construction and arrangement of the present application as shown in the various exemplary embodiments is illustrative only. Although only a few embodiments have been described in detail in this disclosure, those skilled in the art who review this disclosure will readily appreciate that many modifications are possible (e.g., variations in sizes, dimensions, structures, shapes and proportions of the various elements, values of parameters (e.g., temperatures, pressures, etc.), mounting arrangements, use of materials, colors, orientations, etc.) without materially departing from the novel teachings and advantages of the subject matter recited in this application. For example, elements shown as integrally formed may be constructed of multiple parts or elements, the position of elements may be reversed or otherwise varied, and the nature or number of discrete elements or positions may be altered or varied. Accordingly, all such modifications are intended to be included within the scope of this invention. The order or sequence of any process or method steps may be varied or re-sequenced according to alternative embodiments. In the claims, any means-plus-function clause is intended to cover the structures described herein as performing the recited function and not only structural equivalents but also equivalent structures. Other substitutions, modifications, changes and omissions may be made in the design, operating conditions and arrangement of the exemplary embodiments without departing from the scope of the present inventions. Therefore, the present invention is not limited to a particular embodiment, but extends to various modifications that nevertheless fall within the scope of the appended claims.
Moreover, in an effort to provide a concise description of the exemplary embodiments, all features of an actual implementation may not be described (i.e., those unrelated to the presently contemplated best mode of carrying out the invention, or those unrelated to enabling the invention).
It should be appreciated that in the development of any such actual implementation, as in any engineering or design project, numerous implementation-specific decisions may be made. Such a development effort might be complex and time consuming, but would nevertheless be a routine undertaking of design, fabrication, and manufacture for those of ordinary skill having the benefit of this disclosure, without undue experimentation.
It should be noted that the above-mentioned embodiments are only for illustrating the technical solutions of the present invention and not for limiting, and although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions may be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, which should be covered by the claims of the present invention.
Claims (10)
1. A comprehensive energy system data processing and calculating method with intensive characteristics is characterized by comprising the following steps: the method comprises the following steps:
acquiring data of the comprehensive energy system, and acquiring an integrated energy system evaluation index system with intensive characteristics;
constructing a calculation formula of each index in an evaluation index system;
determining the weight of each index in each index calculation formula;
carrying out statistics on related parameters of intensive characteristic evaluation in the data of the comprehensive energy system;
and evaluating and counting according to the intensive characteristics of the comprehensive energy system.
2. The intensive property integrated energy system data processing computing method of claim 1, wherein: the comprehensive energy system planning evaluation index system considering the intensive characteristics comprises various correlation indexes of the carding comprehensive energy system.
3. The intensive property integrated energy system data processing calculation method according to claim 1 or 2, wherein: the indexes comprise economic benefit indexes, intensive benefit indexes, reliability indexes and environmental benefit indexes.
4. The intensive property integrated energy system data processing computing method of claim 3, wherein: the economic benefit index comprises initial input cost and net present value;
wherein the economic benefit index has an initial input cost CI,SThe calculation formula is as follows:
in the formula, n is the total number of equipment in the energy system; n is a radical ofNOMSimulating a total number of years for the energy system; ci,invAnnual initial investment cost for ith equipment in energy system；Ci,insAnnual installation cost for the ith equipment in the energy system; ci,opcAnnual operation and maintenance cost of the ith equipment in the energy system; ci,chThe annual charge and discharge cost of the ith equipment in the energy system is saved; ci,eAnnual energy utilization cost of the ith equipment in the energy system;
wherein, the calculation formula of the net present value NPV of the economic benefit index is as follows:
in the formula, Ck,IThe k year fund inflow of the energy system; ck,OThe k year fund outflow amount of the energy system; r is the discount rate (reference profitability); k is the number of years of use.
5. The intensive property integrated energy system data processing computing method of claim 4, wherein: the intensive benefit indexes comprise coupling degree, coupling efficiency, energy utilization rate, equipment utilization rate and land utilization rate;
wherein the coupling degree η of the intensive benefit indexCThe calculation formula is as follows:
in the formula, EOI,GThe total amount of natural gas flowing into the coupling device in the energy system; eOI,PThe total amount of electricity flowing into the coupling device in the energy system; eI,GThe total natural gas input amount in the energy system; eI,PInputting total electric quantity into an energy system; lambda [ alpha ]GThe natural gas energy quality coefficient;
wherein the coupling efficiency η of the intensive benefit indexCEThe calculation formula is as follows:
in the formula, EOO,GOutputting the total natural gas quantity for the energy system coupling equipment; eOO,CThe total output cold quantity of the energy system coupling equipment is provided; eOO,HThe total output heat of the coupling equipment of the energy comprehensive system is provided; eOO,PThe total output electric quantity of the coupling equipment of the energy comprehensive system is provided; eO,GOutputting the total natural gas quantity for the energy system; eOI,PThe total amount of electricity flowing into the coupling device in the energy system; lambda [ alpha ]CEnergy quality coefficient of cold consumption; lambda [ alpha ]HEnergy-mass coefficient for heat consumption; lambda [ alpha ]GThe natural gas energy quality coefficient;
wherein the energy utilization rate η of the intensive benefit indexAUThe calculation formula is as follows:
in the formula, EO,GOutputting the total natural gas quantity for the energy system; eO,CThe total output cold quantity of the energy system is provided; eO,HThe total output heat of the energy system; eO,PThe total output electric quantity of the energy system is obtained; eI,PInputting total electric quantity into an energy system; lambda [ alpha ]CEnergy quality coefficient of cold consumption; lambda [ alpha ]HEnergy-mass coefficient for heat consumption; lambda [ alpha ]GThe natural gas energy quality coefficient;
wherein the equipment utilization η of the intensive benefit indexdeviceThe calculation formula is as follows:
in the formula, t0Planning the working time length for the equipment on average; t is tnThe actual working time of the nth equipment is taken as the actual working time of the nth equipment; n is the total number of equipment in the energy system;
wherein the land utilization η of the intensive benefit indexgroundThe calculation formula is as follows:
in the formula, SiThe occupied area of the ith equipment in the energy system is occupied; eI,PInputting total electric quantity into an energy system; n is the total number of equipment in the energy system; eI,GThe total natural gas input amount in the energy system; lambda [ alpha ]GIs the natural gas energy quality coefficient.
6. The intensive property integrated energy system data processing calculation method according to claim 4 or 5, wherein: the reliability indexes comprise failure frequency of the energy supply system, average failure duration of the energy supply system, expected shortage of energy of the energy supply system and average availability of energy supply;
wherein, the energy supply system fault frequency SAIFI calculation formula of the reliability index is as follows:
in the formula, CPThe times of insufficient power supply in the simulation process of the energy system are determined; cCThe times of insufficient cooling in the simulation process of the energy system are determined; cHThe times of insufficient heating system in the energy system simulation process are counted; cGThe times of insufficient air supply in the simulation process of the energy system are determined; lambda [ alpha ]CEnergy quality coefficient of cold consumption; lambda [ alpha ]HEnergy-mass coefficient for heat consumption; n is a radical ofNUMThe total number of users lack energy supply;
wherein, the calculation formula of the average fault duration SAIDI of the energy supply system of the reliability index is as follows:
in the formula, DPThe total duration of insufficient power supply in the energy system simulation process is provided; dCProviding the total duration of insufficient cooling in the energy system simulation process; dHThe insufficient heat supply duration time in the energy system simulation process is provided; dGThe total duration of insufficient gas supply in the energy system simulation process is set; lambda [ alpha ]CEnergy quality coefficient of cold consumption; lambda [ alpha ]HTo dissipate heat energyA prime coefficient; n is a radical ofNUMThe total number of users lack energy supply; lambda [ alpha ]GThe natural gas energy quality coefficient;
wherein, the expected energy supply lacking EENS calculation formula of the energy supply system of the reliability index is as follows:
in the formula, Nt is the total number of time periods in the simulation process of the energy system; viSupplying energy for the lack of energy in the ith time period in the simulation process of the energy system;
wherein, the average energy supply availability ASAI calculation formula of the reliability index is as follows:
wherein 8760 is the total hours per year, and the simulation of the reliability operation condition is generally carried out by taking the year as a unit; dNUMThe duration of the energy supply shortage of the comprehensive energy system is prolonged; n is a radical ofNUMThe total number of users lack energy supply for the comprehensive energy system.
7. The intensive property integrated energy system data processing computational method of claim 6, wherein: the environmental benefit indicators include renewable energy permeability and pollutant emission level;
wherein the environmental benefit indicator has renewable energy permeability ηREThe calculation formula is as follows:
in the formula, EROThe total amount of energy generated for the energy system using renewable energy; eOThe total energy output in the energy system;
wherein the environmental benefit index pollutant emission level IEThe calculation formula is as follows:
in the formula, ve,iThe environmental value of the ith pollutant in the energy system; v isp,iA penalty factor for the ith pollutant in the energy system; v. ofk,iThe discharge coefficient of the ith pollutant; x represents the generation of x major pollutants in the energy system;
wherein, the i-th pollutants, i ═ 1,2 and 3 respectively represent pollutants CO2、SO2NOx, wherein:
ERO＝ERO,G·λG+ERO,C·λC+ERO,H·λH+ERO,P
EO＝EO,G·λG+EO,C·λC+EO,H·λH+EO,P
in the formula, ERO,GThe amount of gas generated for utilizing renewable resources in an energy system; eRO,CThe cold energy generated by renewable resources in the energy system is utilized; eRO,HHeat generated for utilization of renewable resources in an energy system; eRO,PElectricity generated by renewable resources in an energy system; eO,GOutputting the total natural gas quantity for the energy system; eO,CThe total output cold quantity of the energy system is provided; eO,HThe total output heat of the energy system; eO,PThe total output electric quantity of the energy system is obtained; lambda [ alpha ]CEnergy quality coefficient of cold consumption; lambda [ alpha ]HEnergy-mass coefficient for heat consumption; lambda [ alpha ]GIs the natural gas energy quality coefficient.
8. The intensive property integrated energy system data processing computing method of claim 7, wherein: the step of determining the weight of each index in each index calculation formula comprises the following steps:
carrying out normalization and standardization processing on each index;
calculating the entropy value of each index information in the evaluation system by adopting an entropy weight method;
determining each index weight.
9. The intensive property integrated energy system data processing computing method of claim 8, wherein: the step of counting the parameters related to intensive characteristic evaluation in the integrated energy system data comprises the following steps:
counting the planning evaluation related parameters of the comprehensive energy system considering the intensive characteristics;
collecting relevant data in a statistical manner;
the data comprises historical operation data and planning stage prediction data in an evaluation target time period.
10. The intensive property integrated energy system data processing computing method of claim 9, wherein: and calculating the comprehensive energy system planning evaluation score by taking a specific time interval as a unit according to the comprehensive energy system intensive characteristic evaluation statistics.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111553608A (en) * | 2020-05-06 | 2020-08-18 | 国网河北省电力有限公司沧州供电分公司 | Benefit evaluation method for urban distribution network comprehensive energy system |
| CN112465214B (en) * | 2020-11-24 | 2023-12-01 | 浙江大学 | Coupling degree calculation method for comprehensive energy system full life cycle |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102096769A (en) * | 2011-01-24 | 2011-06-15 | 浙江工业大学 | Weighting-based method for measuring comprehensive performance of distributed CCHP (Combined Cooling, Heating and Power) system |
| CN105183991A (en) * | 2015-09-07 | 2015-12-23 | 国网天津市电力公司 | Planning and design method of regional integrated energy system |
| CN106600104A (en) * | 2016-11-07 | 2017-04-26 | 国网江苏省电力公司 | Evaluation method for evaluating energy efficiency of integrated energy system |
| CN108647888A (en) * | 2018-05-11 | 2018-10-12 | 国网电力科学研究院(武汉)能效测评有限公司 | A kind of overall efficiency evaluation method of cool and thermal power multiple-energy-source energy supplying system |
| CN108932562A (en) * | 2018-06-27 | 2018-12-04 | 国网山东省电力公司经济技术研究院 | Integrated energy system comprehensive benefit assessment model method for building up |
| CN109800996A (en) * | 2019-01-30 | 2019-05-24 | 南方电网科学研究院有限责任公司 | Energy efficiency evaluation method and device for comprehensive energy system |
| CN110147568A (en) * | 2019-04-04 | 2019-08-20 | 清华大学 | Integrated energy system energy efficiency evaluating method and device |
| CN110458449A (en) * | 2019-08-08 | 2019-11-15 | 国网能源研究院有限公司 | Regional complex energy supply system cooperative development evaluation method |
-
2019
- 2019-11-29 CN CN201911204694.XA patent/CN110991870B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102096769A (en) * | 2011-01-24 | 2011-06-15 | 浙江工业大学 | Weighting-based method for measuring comprehensive performance of distributed CCHP (Combined Cooling, Heating and Power) system |
| CN105183991A (en) * | 2015-09-07 | 2015-12-23 | 国网天津市电力公司 | Planning and design method of regional integrated energy system |
| CN106600104A (en) * | 2016-11-07 | 2017-04-26 | 国网江苏省电力公司 | Evaluation method for evaluating energy efficiency of integrated energy system |
| CN108647888A (en) * | 2018-05-11 | 2018-10-12 | 国网电力科学研究院(武汉)能效测评有限公司 | A kind of overall efficiency evaluation method of cool and thermal power multiple-energy-source energy supplying system |
| CN108932562A (en) * | 2018-06-27 | 2018-12-04 | 国网山东省电力公司经济技术研究院 | Integrated energy system comprehensive benefit assessment model method for building up |
| CN109800996A (en) * | 2019-01-30 | 2019-05-24 | 南方电网科学研究院有限责任公司 | Energy efficiency evaluation method and device for comprehensive energy system |
| CN110147568A (en) * | 2019-04-04 | 2019-08-20 | 清华大学 | Integrated energy system energy efficiency evaluating method and device |
| CN110458449A (en) * | 2019-08-08 | 2019-11-15 | 国网能源研究院有限公司 | Regional complex energy supply system cooperative development evaluation method |
Non-Patent Citations (1)
| Title |
|---|
| 张立地 等: "综合能源背景下的配电网规划研究" * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111553608A (en) * | 2020-05-06 | 2020-08-18 | 国网河北省电力有限公司沧州供电分公司 | Benefit evaluation method for urban distribution network comprehensive energy system |
| CN112465214B (en) * | 2020-11-24 | 2023-12-01 | 浙江大学 | Coupling degree calculation method for comprehensive energy system full life cycle |
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|---|---|
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