CN116823008A

CN116823008A - Park energy utilization efficiency evaluation method, system, equipment and storage medium

Info

Publication number: CN116823008A
Application number: CN202310078376.3A
Authority: CN
Inventors: 刘一江; 郑燕; 王硕; 霍慧娟; 徐丹; 辛诚; 李薇薇; 荀超; 叶颖津
Original assignee: State Grid Economic And Technological Research Institute Co LtdB412 State Grid Office; Economic and Technological Research Institute of State Grid Fujian Electric Power Co Ltd
Current assignee: State Grid Economic And Technological Research Institute Co LtdB412 State Grid Office; Economic and Technological Research Institute of State Grid Fujian Electric Power Co Ltd
Priority date: 2023-01-17
Filing date: 2023-01-17
Publication date: 2023-09-29

Abstract

The invention relates to a park energy utilization efficiency evaluation method, a system, equipment and a storage medium, which comprise the following steps: based on a predetermined index selection thought and basis, constructing a layering evaluation index system for evaluating the energy utilization efficiency of the park comprehensive energy system; based on the established hierarchical evaluation index system, an energy efficiency evaluation model is established by utilizing a fuzzy comprehensive evaluation method of an AHP-entropy weight method, and the energy utilization efficiency of the park comprehensive energy system item is evaluated, so that an evaluation result is obtained. The invention can accurately reflect key influence factors of the energy efficiency level of the comprehensive energy system by deep excavation, provides a calculation method of the energy efficiency index of the comprehensive energy system, establishes the energy efficiency evaluation index system of the comprehensive energy system, can provide reference for the operation evaluation of the subsequent comprehensive energy system, and can be widely applied to the technical field of comprehensive energy system evaluation.

Description

Park energy utilization efficiency evaluation method, system, equipment and storage medium

Technical Field

The invention relates to a park energy utilization efficiency evaluation method, a system, equipment and a storage medium, and belongs to the technical field of comprehensive energy system evaluation.

Background

The comprehensive energy system taking the new energy as a main body is constructed in the area, so that the peak regulation and frequency modulation requirements caused by the uncertainty and the fluctuation of the renewable energy power generation and the threats caused by the safe operation and grid connection management of the power grid can be effectively solved. At present, how to construct a comprehensive energy system in a park has become a research hotspot in recent years, and a plurality of research results exist in the aspects of modeling, planning, operation optimization and the like.

However, in general, there is a gap in the aspects of energy efficiency improvement and project comprehensive evaluation of the comprehensive energy system, and in order to effectively play the role of the comprehensive energy system in the energy green low-carbon transformation process in China, research on the comprehensive energy system evaluation technology aiming at energy efficiency improvement is needed to be carried out.

Disclosure of Invention

Aiming at the problems, the invention aims to provide a park energy utilization efficiency evaluation method, a system, equipment and a storage medium, which are used for comprehensively evaluating the energy efficiency of a comprehensive energy system by establishing the comprehensive energy system energy efficiency evaluation index system and combining a fuzzy comprehensive evaluation technology.

In order to achieve the above purpose, the present invention adopts the following technical scheme:

in a first aspect, the present invention provides a method for evaluating energy efficiency of a campus, comprising the steps of:

Based on a predetermined index selection thought and basis, constructing a layering evaluation index system for evaluating the energy utilization efficiency of the park comprehensive energy system;

based on the established hierarchical evaluation index system, an energy efficiency evaluation model is established by utilizing a fuzzy comprehensive evaluation method of an AHP-entropy weight method, and the energy utilization efficiency of the park comprehensive energy system item is evaluated, so that an evaluation result is obtained.

Further, the step of constructing a hierarchical evaluation index system for evaluating the energy utilization efficiency of the park comprehensive energy system based on the predetermined index selection thought and basis includes:

determining an index selection thought and an index selection basis;

selecting the energy utilization efficiency evaluation index of the park comprehensive energy system according to the determined index selection thought and basis;

systematic sum-up is carried out on the energy utilization efficiency evaluation indexes of the selected park comprehensive energy system, and a hierarchical evaluation index system is formed based on the related quantitative relation of each evaluation index.

Further, the hierarchical assessment index system includes at least one of: economic efficiency, green efficiency, physical efficiency, safety efficiency, reliable efficiency and intelligent efficiency evaluation indexes;

The economic efficiency evaluation index includes at least one of: unit load investment, unit load cost, revenue cost ratio, internal rate of return, investment recovery period;

the green efficiency evaluation index includes at least one of: unit energy consumption emission, pollutant emission reduction rate, carbon emission reduction index, carbon emission balance index and renewable energy permeability;

the physical efficiency evaluation index includes at least one of the following: the power grid line loss rate, the pipe network heat/cold loss rate, the equipment average utilization rate and the energy comprehensive utilization efficiency;

the safety efficiency evaluation index includes at least one of the following: energy supply shortage rate, unplanned system outage coefficient, peak average load rate and valley average load rate;

the reliability efficiency assessment indicator comprises at least one of: energy self-supply rate, comprehensive voltage qualification rate, power supply reliability, cooling/heating reliability and stability;

the intelligent efficiency assessment indicator includes at least one of: intelligent prediction accuracy, intelligent diagnosis accuracy and system fault self-healing capacity.

Further, the establishing hierarchical evaluation index system is based on an energy efficiency evaluation model established by using a fuzzy comprehensive evaluation method of an AHP-entropy weight method, and the energy utilization efficiency of the park comprehensive energy system item is evaluated to obtain an evaluation result, which comprises the following steps:

Analyzing the index weight based on an analytic hierarchy process to obtain a first index weight vector of each evaluation index;

analyzing the index weight based on an entropy method to obtain a second index weight vector of each evaluation index;

and based on the first index weight vector and the second index weight vector, evaluating the energy utilization efficiency of the park comprehensive energy system by adopting a fuzzy comprehensive evaluation method to obtain the energy efficiency utilization grade of the comprehensive energy system.

Further, the analyzing the index weight based on the analytic hierarchy process to obtain a first index weight vector of each evaluation index includes:

establishing a hierarchical structure model based on membership among all evaluation indexes;

based on a hierarchical structure model, comparing importance of every two elements in each hierarchy relative to the elements of the upper layer, and constructing a judgment matrix based on the obtained importance values;

and calculating the characteristic vector and the maximum characteristic value based on the judgment matrix, and taking the characteristic vector corresponding to the maximum characteristic value meeting the consistency test as a first index weight vector.

Further, the analysis of the index weight based on the entropy method to obtain a second index weight vector of each evaluation index includes:

Carrying out standardization processing on each evaluation index data;

calculating information entropy of each evaluation index based on the standardized evaluation index value;

based on the information entropy of each evaluation index, calculating to obtain the entropy weight of each evaluation index;

and obtaining a second index weight vector based on the entropy weight method based on the entropy weight of each evaluation index.

Further, the estimating the energy utilization efficiency of the park comprehensive energy system by using a fuzzy comprehensive estimating method based on the first index weight vector and the second index weight vector to obtain the energy efficiency utilization grade of the comprehensive energy system comprises the following steps:

determining a mathematical model of fuzzy comprehensive evaluation, wherein in the model, the energy efficiency utilization level of a comprehensive energy system is taken as an evaluation object set, each evaluation index in a layering evaluation index system is taken as a characteristic factor set, and an evaluation statement set is established according to the evaluation object set and the characteristic factor set; the first index weight vector and the second index weight vector are subjected to weighted combination to obtain a fuzzy weight vector used for representing the importance degree of each characteristic factor in the characteristic factor set;

carrying out single factor evaluation on each factor in the characteristic factor set based on the evaluation statement set, and normalizing to obtain a comprehensive evaluation matrix aiming at the evaluation object set;

And obtaining the energy efficiency utilization level of the comprehensive energy system based on the fuzzy weight vector and the comprehensive evaluation matrix.

In a second aspect, the present invention provides a system for estimating energy efficiency of a campus, comprising:

the basic data acquisition unit is used for importing basic data and preprocessing the basic data;

the index system construction unit is used for constructing a layering evaluation index system for evaluating the energy utilization efficiency of the park comprehensive energy system based on a predetermined index selection thought and basis;

the energy efficiency utilization rate evaluation unit is used for constructing an energy efficiency evaluation model by utilizing a fuzzy comprehensive evaluation method of an AHP-entropy weight method based on the established hierarchical evaluation index system, and evaluating the energy utilization rate of the park comprehensive energy system item to obtain an evaluation result.

In a third aspect, the present invention provides a processing apparatus comprising at least a processor and a memory, the memory having stored thereon a computer program which when executed by the processor performs the steps of the method for assessing energy efficiency of a campus.

In a fourth aspect, the invention provides a computer storage medium having stored thereon computer readable instructions executable by a processor to perform the steps of the campus energy utilization efficiency assessment method.

Due to the adoption of the technical scheme, the invention has the following advantages:

1. the invention can accurately reflect key influence factors of the energy efficiency level of the energy system by deep excavation, provides a calculation method of the energy efficiency index of the comprehensive energy system, establishes an energy efficiency evaluation index system of the comprehensive energy system, and can provide reference for the operation assessment of the subsequent comprehensive energy system;

2. at present, the energy efficiency level of the comprehensive energy system lacks overall cognition, and the energy efficiency classification of the system is not clear, so that the overall operation efficiency is calculated based on the actual operation condition of the comprehensive energy system, a reference can be provided for the energy efficiency standard determination of the comprehensive energy system, and the planning and operation of the comprehensive energy system can be guided;

3. the invention comprehensively considers energy efficiency factors, economic factors, environmental factors, safety factors, reliability factors and intelligent factors, covers distributed energy, medium-low voltage distribution networks, natural gas networks, heating systems, cooling systems, energy storage and other systems, and can comprehensively and truly reflect the internal structure, external state, the relationship among subsystems in the system and the realization degree of energy conservation and emission reduction targets of the regional comprehensive energy system.

Therefore, the invention can be widely applied to the technical field of comprehensive energy system evaluation.

Drawings

Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Like parts are designated with like reference numerals throughout the drawings. In the drawings:

FIG. 1 is a diagram of a selection idea of a park energy utilization rate evaluation index provided by an embodiment of the invention;

FIG. 2 is a flow chart of a system construction for evaluating energy efficiency of a park comprehensive energy system according to an embodiment of the invention;

FIG. 3 is a fuzzy comprehensive evaluation flow chart based on an AHP-entropy weight method provided by the embodiment of the invention;

FIG. 4 is a block diagram of a system for evaluating energy utilization efficiency of a campus provided by an embodiment of the present invention;

fig. 5 is a schematic diagram of a fuzzy converter according to an embodiment of the present invention.

Detailed Description

In order to make the objects, technical solutions and advantages of the embodiments of the present invention more clear, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. It will be apparent that the described embodiments are some, but not all, embodiments of the invention. All other embodiments, which are obtained by a person skilled in the art based on the described embodiments of the invention, fall within the scope of protection of the invention.

It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the present application. As used herein, the singular is also intended to include the plural unless the context clearly indicates otherwise, and furthermore, it is to be understood that the terms "comprises" and/or "comprising" when used in this specification are taken to specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof.

In some embodiments of the application, a method for evaluating energy utilization efficiency of a park is provided, and a hierarchical evaluation index system of the energy utilization efficiency of the park comprehensive energy system is established for the problem that the energy efficiency level of the comprehensive energy system lacks overall cognition and the energy efficiency classification of the system is not clear; meanwhile, an energy efficiency evaluation model is built by using a fuzzy comprehensive evaluation method of the AHP-entropy weight method, and the energy utilization efficiency of the park comprehensive energy system item is evaluated. The application can accurately reflect key influence factors of the energy efficiency level of the comprehensive energy system by deep excavation, provides a calculation method of the energy efficiency index of the comprehensive energy system, establishes the energy efficiency evaluation index system of the comprehensive energy system, can provide reference for the operation evaluation of the subsequent comprehensive energy system, and can be widely applied to the technical field of comprehensive energy system evaluation.

In accordance therewith, in other embodiments of the present invention, a system, apparatus and storage medium for campus energy efficiency assessment are provided.

Example 1

As shown in fig. 1, the method for evaluating energy utilization efficiency of a campus provided in this embodiment includes the following steps:

1) Based on a predetermined index selection thought and basis, a layering evaluation index system for evaluating the energy utilization efficiency of the park comprehensive energy system is constructed.

Specifically, the above step 1) may be achieved by:

1.1 Determining an index selection concept

The energy utilization efficiency evaluation index system of the park comprehensive energy system is an organic series consisting of a plurality of mutually connected, mutually complementary and hierarchical and structural indexes, and has three conditions: the method can describe and characterize the current situation of each aspect of the development of things at a certain moment; secondly, various aspects of change trend of the object development at a certain moment can be described and represented; thirdly, the coordination degree of various aspects of the development of things can be described and represented.

Specifically, the energy utilization efficiency evaluation index system of the park comprehensive energy system established by the invention has the following functions:

(1) The functions are described. The basic conditions of energy resource utilization, energy resource saving, environmental pollution and the like in the current park can be comprehensively reflected and systematically expressed through an index system.

(2) The function is explained. The logic clues of the internal operation rules and the causal relationship of the park comprehensive energy system can be analyzed and found out through the index system.

(3) And (5) evaluating the function. Namely, according to an index system, the actual condition of the energy utilization efficiency can be objectively evaluated.

(4) Monitoring function. The method can effectively and scientifically measure the problems and the severity of the problems in the implementation process of the comprehensive energy system through an index system, and provides data for solving the problems.

(5) And a prediction function. Namely, the basic trend of energy utilization efficiency development can be predicted scientifically through an index system.

As shown in fig. 1, in this embodiment, the energy efficiency evaluation index system of the integrated energy system of the campus is constructed to follow the "objective-work object-connotation-influence factor-evaluation method" mode. The index selection thinking is as follows: purpose, object, connotation, influencing factors and methods.

As shown in fig. 2, the comprehensive energy system project has the professional, emerging and special properties, and whether the indexes are reasonable or not can be judged only by widely collecting and analyzing massive related research documents and performing field investigation, so that the primary indexes and the secondary indexes of the comprehensive energy system energy utilization efficiency evaluation index system are determined by adopting a theoretical analysis method, a frequency statistics method and an expert investigation method.

1.2 Determining index selection basis

Under the energy internet background, the energy utilization efficiency evaluation index system of the park comprehensive energy system is obviously different from the traditional power grid project and mainly comprises the following three aspects:

economic benefit and green benefit of comprehensive energy projects need to be quantitatively embodied. The floor implementation of the comprehensive energy project can not only bring the explicit energy-saving economic efficiency for reducing the energy consumption cost to project investors, but also bring the implicit environmental protection benefits for reducing carbon dioxide emission, pollutant emission and the like to the project investors, and the floor implementation is also the development of the comprehensive energy project. The energy-saving economic efficiency can be calculated by energy cost analysis, but the green benefit is difficult to be quantitatively embodied, and is rarely considered in the benefit measuring and calculating method of the traditional power grid project. Therefore, when the benefit measurement and calculation of the comprehensive energy project is carried out, the environmental protection benefit of the project needs to be quantified, and the carbon emission reduction benefit after project transformation and the emission reduction benefit of sulfur dioxide and nitrogen oxides in the atmospheric pollutants are considered, so that a more scientific and comprehensive benefit measurement and calculation result is provided.

The utilization efficiency of energy and the reliability and the safety of project operation have great influence on project benefits. For a plurality of systems with highly coupled energy input, conversion, consumption and storage, considering that the energy utilization efficiency of a certain technology or a certain link is not enough to reflect the efficiency level of the whole system alone, the whole system needs to be taken into consideration as a whole to examine the energy utilization level. Meanwhile, the energy is efficient, reliable and safe to run, is regarded as the main trend of intensive research and development in the comprehensive energy field, and is a foundation for guaranteeing the stability of regional energy.

The comprehensive energy projects have diversified characteristics, and the intelligent degree of the system is required to be embodied. Under the comprehensive energization of the energy Internet, the content and the form of comprehensive energy projects are more diversified, the projects relate to a wide field and a plurality of technical types, and various technical characteristics, operation modes and the like are different, and if intelligent evaluation standards are not available, the operation efficiency and the development level of the system are greatly reduced. Therefore, the benefit measurement of the comprehensive energy project is developed, and an index with the intelligence degree of the evaluation system is required to be selected, so that the working efficiency of the comprehensive energy project is improved.

Therefore, based on the analysis, the method comprehensively considers the energy efficiency factors, economic factors, environmental factors, safety factors, reliability factors and intelligent factors of the comprehensive energy project, covers the systems such as distributed energy, a power distribution network, a heating system, a cooling system and energy storage, and establishes a park comprehensive energy system energy utilization efficiency evaluation model. Wherein, the interaction of the energy system, the economic system and the environmental system is related to each other, the safety and the reliability are the basic stones of the energy system, and the intelligent degree is the footbed stones of the energy system.

1.3 According to the determined index selection thought and basis, selecting the energy utilization efficiency evaluation index of the park comprehensive energy system.

With the development of integrated energy systems and the advancement of construction processes, the evaluation of the integrated energy efficiency of integrated energy projects has become a necessary task. The energy utilization efficiency evaluation index system of the park comprehensive energy system is established, so that an evaluation reference can be provided for evaluating the construction level of the comprehensive energy projects in China, and guidance information and related suggestions can be provided for planning and developing the comprehensive energy projects. Therefore, according to the principle and thought, through an index screening model, the method disclosed by the invention cuts in from six aspects of economic efficiency, green efficiency, physical efficiency, safety efficiency, reliable efficiency and intelligent efficiency of the comprehensive energy system, builds the energy utilization efficiency evaluation of the comprehensive energy system of the park, and comprehensively reflects the energy efficiency condition of the comprehensive energy project.

Specifically, each evaluation index is described as follows:

1.3.1 Economic efficiency evaluation index

The economic efficiency evaluation index covers three aspects of cost, income and development, and specifically comprises indexes such as unit load investment, unit load cost, income cost ratio, internal income rate, investment recovery period and the like.

(1) Investment in unit load

The unit load investment refers to the investment cost generated by the integrated energy system to meet the unit load.

C _t,d ＝C _t,C /∑(L _e +L _h +L _c ) (1)

Wherein C is _t,d Investment in unit load is calculated; c (C) _t,C Investment for total load, element; l (L) _e ，L _h ，L _c Respectively electric heatingCold load, kWh.

(2) Cost per unit load

The unit load cost refers to the energy cost generated by the integrated energy system to meet the unit load, including all costs generated in the investment stage and the operation stage.

C _c,d ＝C _ax /∑(L _e +L _h +L _c ) (2)

Wherein C is _c,d The unit load cost is the element; c (C) _ax For annual cost, the element.

(3) Cost of income ratio

The revenue cost ratio refers to the ratio between the revenue generated by the operation of the integrated energy system over a period of time and the costs of the operation of the integrated energy system.

P＝B _r /C _p (3)

Wherein P is the income cost ratio,%; b (B) _r Is the total income, ten thousand yuan; c (C) _p The total cost is now ten thousand yuan.

(4) Internal yield

The internal rate of return refers to the rate of return when the total amount of funds inflow and the total amount of funds outflow are equal and the net present value is equal to zero during the operation of the integrated energy system.

Wherein B is _p Is the total income, ten thousand yuan; IRR is the internal yield,%.

(5) Investment recovery period

The term "investment recovery period" is also called "investment recovery period", and refers to the time (period) required for the total amount of returns obtained after investment project investment to reach the total amount of investment invested in the investment project.

Wherein T is the system investment recovery period and the year; c is the systemThe price of unit energy in the product is C _e Yuan/kWh, unit heat value is C _h Yuan/kWh, unit cold price is C _c meta/kWh; q is generated energy in the system and is Q _E kWh, heat supply amount Q _H kWh, refrigerating capacity of Q _C ，kWh，A _r Is a conversion value of initial investment year, and is ten thousand yuan.

Calculation value A of initial investment year _r The calculation formula of (2) is as follows:

wherein i is the discount rate,%; n is the operational life of the project and the year.

1.3.2 Green efficiency evaluation index)

After the park establishes the comprehensive energy system, the renewable energy utilization rate is improved, the pollution is reduced, the emission is reduced, and the energy structure is optimized. The environmental efficiency of the product can be evaluated from the aspects of synergy and emission reduction and clean production. The green efficiency evaluation index in the embodiment specifically includes 5 indexes of unit energy consumption emission, pollutant emission reduction rate, carbon emission reduction index, carbon emission balance index and renewable energy permeability.

(1) Unit energy consumption and discharge amount

The unit energy consumption emission amount refers to the ratio of a certain pollutant emission amount to the system energy consumption amount in a certain period.

Wherein C is unit energy consumption and emission; b is the number of pollution equivalent produced by unit energy consumption, kg/d; e is the energy consumption of the system and kg of standard coal.

(2) Pollutant emission reduction rate

Pollutant emission reduction rate refers to how much the pollutant emission reduction rate is reduced by a percentage compared with the current year and the last year.

Wherein delta is pollutant emission reduction rate;the emissions of nitrogen, carbon and sulfide in the last year are kg respectively;the emissions of nitrogen, carbon and sulfide of the system are kg in the present year.

(3) Carbon emission reduction index

The carbon emission reduction index refers to the percentage of carbon dioxide emission reduction in the year compared to the last year.

Wherein delta _c Is carbon emission reduction index;for the carbon emission of the last year system kg->Is the carbon emission of the system in the present year, kg.

(4) Carbon emission balance index

The carbon emission balance index refers to the percentage of the sum of the actual carbon emission of enterprises lower than the national approval emission index in the total emission of the system operation.

Wherein S is _c Is a carbon emission balance index; r is R _c The discharge index is approved by the carbon discharge country, kg, m _c Kg is the actual total carbon emissions of the system.

(5) Permeability of renewable energy source

The renewable energy permeability is the proportion of renewable energy generating capacity to total generating capacity, is a measure of the permeability of renewable energy in an energy system, can represent the environmental protection performance of the system, is closely related to the economical efficiency of the system, and is an important parameter for evaluating the contribution of renewable energy.

Wherein D is ₁ Is the permeability of renewable energy sources; q (Q) _renew Annual energy production of renewable energy in a park comprehensive energy system, kWh; q (Q) _elc kWh is the total electrical load on the campus.

1.3.3 Physical efficiency evaluation index

Based on analysis of multidimensional influence factors of the comprehensive energy system, the embodiment selects an evaluation index from the energy-saving high-efficiency perspective. The physical efficiency evaluation index aims to reflect that after the comprehensive energy system is established, the energy utilization efficiency can be improved, the energy is saved, and the primary energy consumption is reduced. The method mainly establishes evaluation indexes from three angles of energy transmission, energy conversion and energy utilization, and specifically comprises the following steps: the power grid line loss rate, the pipe network heat/cold loss rate, the equipment average utilization rate and the energy comprehensive utilization efficiency are 4 indexes.

(1) Line loss rate of power grid

Grid line loss refers to the percentage of electrical energy lost in the power network (line loss load) that is supplied to the power network (supply load) to assess the economics of the power system operation. The index of reducing the line loss rate of the power grid refers to the difference value of the line loss rate before and after multi-energy coordination.

Wherein lambda is ₁ The power grid line loss rate,%; e is the total transmission amount of electric energy, kWh; e (E) _lost kWh is the lost electrical energy.

(2) Pipe network heat/cold loss rate

The pipe network cold/heat loss rate refers to the proportion of lost energy accounting for the total energy consumption, and the smaller the value is, the better the energy utilization is.

Wherein lambda is _H/C Heat/cold loss rate of pipe network,%; H/C is the total heat/cold energy transmission amount of a pipe network and kg of standard coal; h _lost /C _lost For lost heat/cold energy, kg of standard coal.

(3) Average utilization of equipment

The average utilization rate of the equipment is a technical and economic index reflecting the working state and the production efficiency of the terminal equipment, and refers to the percentage of the actual use average time of the equipment per year to the planned use time. Whether the energy terminal equipment can fully utilize directly influences the high-efficiency utilization of energy.

Wherein eta _e Average utilization rate of equipment; t (T) ₀ The unit plan working time length, h, is calculated by optimization; t (T) _n H is the actual working time length of the nth equipment in unit time; n (N) _e The energy system is a table for integrating the number of energy link devices in the energy system.

(4) Comprehensive utilization efficiency of energy

The comprehensive utilization efficiency of energy refers to the ratio of the effective energy generated by an energy system to the effective energy input, and is a comprehensive index reflecting the energy consumption level and the utilization effect, i.e. the effective utilization degree of energy.

Wherein C is ₈ The comprehensive utilization efficiency of energy is realized; u (U) _E The energy system is effective energy generated by the energy system, and the standard coal is kilogram; s is S _E The energy system is used for inputting effective energy into the energy system, and the standard coal is kg.

1.3.4 Safety efficiency evaluation index

Based on the analysis of the multidimensional influencing factors of the comprehensive energy system, the section selects the evaluation index from the safety angle. The safety and reliability assessment index aims at reacting, namely the capacity of all cold and hot electric equipment to operate within the safety limit allowed by the cold and hot electric equipment; secondly, when being interfered by accidents, the cold, hot and electric networks keep the stable operation capability. The section mainly establishes evaluation indexes from the angles of energy supply guarantee, energy supply safety and power grid guarantee, and specifically comprises the following steps: the energy supply shortage rate, the unplanned system outage coefficient, the peak average load rate and the valley average load rate are 4 indexes.

(1) Rate of insufficient energy supply

The energy supply shortage rate refers to the sum of cold, heat and electric energy which cannot be emitted, and comprises energy which cannot be utilized or completely utilized by the user load due to the failure of a new energy source, the lack of energy for overhauling and the failure of equipment elements of the power distribution network, and the total supply requirement proportion is occupied.

Wherein P is _loss The energy supply shortage rate is given; w (W) _E 、W _C 、W _H The electric, cold and heat load demands are respectively, kWh; ΔW (delta W) _E 、ΔW _C 、ΔW _H The supply shortage of electric energy, cold energy and heat energy is respectively known as kWh.

(2) Non-planned system outage coefficient

The unplanned system outage coefficient refers to the percentage of the garden zone system energy interruption during the evaluation time.

Wherein UOF is an unplanned system outage coefficient; u (U) _OH The system is not planned to be shut down for hours, h, PH is the number of hours during statistics, and h.

(3) Peak average load factor

The peak average load rate is the average value of the peak values of each period of the comprehensive energy system, is one of important standards for measuring the stability of the system, and is more beneficial to the safe operation of the system as the peak average load rate is lower.

Wherein, the liquid crystal display device comprises a liquid crystal display device,peak average load rate; p (P) _max kWh, which is the maximum load; />Load average, kWh.

(4) Valley average load factor

The average load rate of the valley is the average value of the valley in each period of the comprehensive energy system, is one of important standards for measuring the stability of the system, and is more beneficial to the safe operation of the system as the average load rate of the valley is higher.

Wherein, beta is the average load factor of the valley value; p (P) _min As a load minimum, kWh;load average, kWh.

1.3.5 Reliable efficiency evaluation index

The stable operation is an important guarantee for sustainable development of the comprehensive energy system, and the section selects an evaluation index from a reliable angle. The section mainly establishes evaluation indexes from two angles of functional margin and energy supply stability, and specifically comprises the following steps: the energy self-supply rate, the comprehensive voltage qualification rate, the power supply reliability, the cooling/heating reliability and the stability are 4 indexes.

(1) Self-supply rate of energy

Along with the rapid growth of economy, the energy supply is sufficient, stable and safe, and has important significance for maintaining smooth operation of economy and society and guaranteeing economic development. The energy self-sufficient rate of a park refers to the specific gravity of the total amount of energy required by the park, which is occupied by the energy provided by the park. The higher the index, the safer and more reliable the energy supply for the campus.

Wherein B is ₃ Is the self-supply rate of energy; e (E) _S The total energy provided for the comprehensive energy system is kg of standard coal; e (E) _Q The total amount of energy supply in the system is kg of standard coal.

(2) Comprehensive voltage qualification rate

The integrated voltage yield refers to the percentage of the actual operating voltage over the allowable voltage deviation range that is the cumulative operating time (minutes) versus the corresponding total operating statistical time (minutes).

Wherein, H is the qualification rate of the comprehensive voltage of the customer,%; h is a _s Representing the qualification time of single customer voltage, h; h is a _a Representing a single customer voltage monitoring time, h.

(3) Reliability of power supply

The power supply reliability refers to the ratio of the shortage of electric power supplied to the user during the evaluation time.

Wherein W is _LE To park electric load demand, kWh, E _res 、E _MT 、E _out The output of the new energy, the generated energy of the gas turbine and the discharged energy of the storage battery are respectively shown as kWh.

(4) Cooling/heating reliability and stability

Cooling/heating reliability and stability refer to the characteristic of the system that continuously meets user demand as load changes. The evaluation of the two can be embodied by the sum of the times of the faults of the cold/heat source supply system and the times of the temperature of the heating room in winter exceeding the recommended section of the regional standard, or the sum of the times of the temperature of the cooling room in summer exceeding the recommended section of the regional standard.

Wherein, N is the reliability and stability of cooling/heating; lambda (lambda) ₁ To provide cooling/heating system failure times, mu ₁ The number of times that the temperature of the heating room in winter exceeds the recommended section of the regional standard or the number of times that the temperature of the cooling room in summer exceeds the recommended section of the regional standard is counted.

1.3.6 Intelligent efficiency assessment index)

The intelligent efficiency index mainly refers to intelligent operation scheduling, and specifically comprises 3 indexes of intelligent prediction accuracy, intelligent diagnosis accuracy and system fault self-healing capacity.

(1) Intelligent prediction accuracy

The intelligent prediction accuracy is an important function of the system, and the index measures the accuracy degree of the regional system for power generation output prediction such as wind power generation, solar power generation and the like, power demand prediction and the like.

Wherein eta _f The intelligent prediction accuracy is%; n is the total number of load prediction points; As a load predictive value, kW;is the actual value of the load, kW.

(2) Intelligent diagnosis accuracy

The intelligent diagnosis accuracy is an important characteristic of an intelligent system, is a basis for realizing normal operation of the system, and is the accuracy of the intelligent equipment for diagnosing the system faults according to measured data and comparing the system faults with actual faults.

Wherein eta _ID For intelligent diagnosis accuracy,%; DIA (digital information A) _r The correct times and times of faults are intelligently diagnosed; DIA (digital information A) ₀ The total times and times of faults are intelligently diagnosed.

(3) Self-healing capability of system fault

The system fault self-healing capability refers to the capability of an intelligent regulation system to isolate a problem element from the system or to recover from a fault state to a normal operating state. The interaction capability between the power grid self equipment can be measured through the index.

Wherein H is _SHRR The self-healing capacity of system faults is achieved; p (P) _Ⅰ,t 、P _II,t 、P _II,t The actual recovery power of the load of the I level, the II level and the III level is kW; omega ₁ 、ω ₂ 、ω ₃ The load class weight coefficients correspond to the I-class, II-class and III-class loads respectively;the original power requirements of the loads of all levels at the moment t are kW respectively; t (T) _c H is the duration of the fault; Δt is the time interval, h.

1.4 Systematic sum of the energy utilization efficiency evaluation indexes of the selected park comprehensive energy system is carried out, and a hierarchical evaluation index system is formed based on the related quantitative relation of each evaluation index.

Systematic summarizing the selected evaluation indexes: the existing resources of the park are utilized as much as possible in the aspect of economic efficiency, so that higher economic input and output and return on investment are realized; the emission of greenhouse gases is mainly reduced in terms of environmental efficiency, the emission of three wastes is less, and the energy supply ratio of clean energy sources is improved; the energy utilization efficiency of the comprehensive energy system and the utilization efficiency of equipment in the comprehensive energy system are mainly considered in the aspect of physical efficiency; in the aspect of safety efficiency, the safety of energy supply is mainly considered, the risk of insufficient energy supply is reduced, and the failure rate of equipment is reduced. A hierarchical evaluation index system is formed based on the relevant quantization relations of the respective indexes as shown in table 1 below.

Table 1 comprehensive energy System energy efficiency assessment index System

2) Based on the established hierarchical evaluation index system, an energy efficiency evaluation model is established by utilizing a fuzzy comprehensive evaluation method of an AHP-entropy weight method, and the energy utilization efficiency of the park comprehensive energy system item is evaluated, so that an evaluation result is obtained.

The evaluation of the energy utilization efficiency of the park comprehensive energy system energy relates to a plurality of aspects, and has multi-level and ambiguity. Thus, the present invention evaluates it using a fuzzy synthesis method. Aiming at the defects existing in the traditional evaluation process, the invention establishes a fuzzy comprehensive evaluation model based on an AHP-entropy weight method, and performs comprehensive analysis from various layers and multiple aspects.

Specifically, the above step 2) may be achieved by:

2.1 Based on the analytic hierarchy process, analyzing the index weight to obtain a first index weight vector of each evaluation index.

The steps of Analytical Hierarchy Process (AHP) modeling include: establishing a hierarchical structure model; constructing a judgment matrix; ordering the hierarchical list and checking consistency; the total ordering and consistency test of the layers are realized as follows:

2.1.1 Based on the membership between the evaluation indexes, building a hierarchical structural model.

When the AHP analysis is applied to evaluate the problem, the problem is systemized, the factors are layered, and a factor hierarchical structure model is constructed. Under this model, complex problems are decomposed into components that form several levels of elements by attribute and relationship. The elements of the previous level are dominant as criteria to the elements of the next level, which is a refinement of the elements of the previous level. These levels generally fall into the following three categories: (1) target layer: there is one element in the layer and is mainly used for analyzing and evaluating the preset target of the problem, namely the first-level index shown in table 1; (2) criterion layer: the layer contains intermediate links involved in achieving the aim, and the intermediate links can consist of a plurality of layers, including criteria and sub-criteria to be considered, namely, secondary indexes shown in table 1; (3) scheme layer: this hierarchy should belong to the lowest hierarchy in the hierarchical model, and includes various measures, decision schemes, etc. that are selectable to reach the target hierarchy element, i.e., three-level indexes shown in table 1.

2.1.2 Based on the structure model of the hierarchical level, comparing the importance of every two elements in each level relative to the upper element, and constructing a judgment matrix based on the obtained importance value.

On the basis of establishing a hierarchical structure model and defining membership relations among hierarchical elements, the construction of the pairwise judgment matrixes can be started. The judgment matrix is an information base for performing an analytic hierarchy process and is also a key for obtaining a weight coefficient. In order to enable the judgment to be quantified, a proper scale is generally introduced when comparing the factors in pairs, so that the judgment results are represented in the form of numerical values, and finally a judgment matrix A is formed. At present, most scholars are used for constructing a 1-9-level scale method proposed by Saath for the scale of a judgment matrix, and the assignment rule of the judgment result is shown in the following table:

table 2 judges the scale and meaning of the matrix

According to the assignment rules indicated in table 2, importance values of the elements after pairwise comparison can be obtained, and these values form a final n-order judgment matrix:

in matrix A, a _ij Is the result of the importance comparison of element i and element j relative to the upper layer element, and has a _ij >0，a _ii ＝1，a _ji ＝1/a _ij ，i,j＝1,2,3...n。

2.1.3 Based on the judgment matrix, calculating the characteristic vector and the maximum characteristic value, and taking the characteristic vector corresponding to the maximum characteristic value meeting the consistency test as a first index weight vector.

The single-level ranking refers to the importance ranking of the same-level factors to the index factors of the previous level in the analytic hierarchy process, and is generally implemented by calculating a judgment matrix A= (a) _ij ) _n×n Corresponding to the maximum eigenvalue lambda _max Is determined by the feature vector w of (a).

(1) The judgment matrix a= (a _ij ) _n×n Normalizing according to the columns to obtain a normalized matrix

The calculation formula of each element in the normalized matrix is as follows:

wherein a is _ij Comparing and judging the relative importance degree of the factor i and the factor j;the values are normalized for the decision matrix.

(2) For normalized matrixThe average value of the element sums of each row is calculated to obtain a feature vector w= [ w ] ₁ ,w ₂ ,…,w _n ] ^T 。

Wherein the matrix is normalizedThe calculation formula of the average value of the element sums of each row is as follows:

(3) based on the eigenvector, calculating to obtain the maximum eigenvalue lambda of the judgment matrix _max 。

(4) And carrying out consistency test based on the maximum eigenvalue of the judgment matrix, and taking the eigenvector meeting the consistency test as a first index weight vector.

In order to ensure the rationality of weight distribution obtained by applying the analytic hierarchy process, the coordination among the importance levels of the elements needs to be checked, namely, consistency check is carried out, so that the situation of contradiction among the relative importance levels of the factors is avoided. Firstly, the consistency index CI of the judgment matrix A is calculated, namely

The larger the value of CI indicates the worse the consistency of the decision matrix, the random consistency ratio is defined as C _R I.e.

Wherein, RI is an average random consistency index of the judgment matrix a, and the value of RI is only related to the order of the matrix, which can be obtained by looking up a table, and the specific values are shown in the following table 3.

TABLE 3 random uniformity index RI values

n	1	2	3	4	5	6	7	8	9	10	11
												RI	0	0	0.58	0.90	1.12	1.24	1.32	1.41	1.45	1.49	1.51

In general, C _R The smaller the rule, the better the consistency of the judgment matrix. C (C) _R <0.1, then it is stated that the decision matrix has acceptable satisfactory consistency, otherwise it should be adjusted and corrected.

2.2 The index weight is analyzed based on the entropy method, and a second index weight vector of each evaluation index is obtained.

The entropy method is to calculate the information entropy of the index and measure the information quantity of the data, namely to determine the weight of the index according to the influence of the relative change degree of the index on the whole, and is an objective weighting method. Entropy is a measure of uncertainty. When the difference provided by the index is large, the uncertainty is smaller, which means that the useful information quantity is larger, the entropy value is smaller, and the entropy weight is larger; otherwise the opposite is true.

In the comprehensive evaluation process, the contribution and the effect of each factor are different, different weight distribution is given according to the effect of each factor, so that the data of each factor can fully play a role, and the evaluation result is more objective and reliable. The entropy weight method is used as an important component of the objective weighting method, the basic idea is to determine objective weights according to the size of index variability, the larger the information entropy is, the higher the variation degree is, the larger the information content is, and the correspondingly higher the weights are, and vice versa. The method has the advantages of simple calculation and strong objectivity, overcomes the defects of a subjective weighting method, and has wide application range. The entropy weight method comprises the following specific calculation steps:

2.2.1 Standardized processing is performed on each evaluation index data.

Let an evaluation matrix composed of n evaluation indexes and m evaluation objects be y= (Y) _ij ) _n×m I=1, 2, n; j=1, 2, m; the calculation formula for performing standardized processing on the index data is as follows:

wherein E is _ij Normalized contribution of the jth index of the ith grid optimization project to be implemented, y _ij And optimizing the contribution degree of the jth index of the project for the ith grid to be implemented.

2.2.2 Calculating the information entropy of each evaluation index.

According to the information entropy definition, the entropy value of the ith index is as follows:

wherein, when E _ij When=0, let E _ij lnE _ij ＝0。

2.2.3 Based on the information entropy of each evaluation index, calculating to obtain the entropy weight of each evaluation index.

Wherein, the entropy weight of the ith evaluation index can be expressed as:

2.2.4 Based on the entropy weight of each evaluation index, a second index weight vector W' based on the entropy weight method is obtained:

W'＝(w ₁ ',w ₂ ',...,w _n ') (35)

2.3 The first index weight vector and the second index weight vector calculated based on the AHP method and the analytic hierarchy process are weighted and combined to obtain combined weights, and the energy utilization efficiency of the park comprehensive energy system is evaluated by adopting a fuzzy comprehensive evaluation method to obtain the energy efficiency utilization grade of the comprehensive energy system.

The fuzzy comprehensive evaluation is a method of considering various influences when evaluating an evaluation object. Different from the traditional comprehensive evaluation method, the method is based on the fuzzy mathematical theory, and qualitative factors can be conveniently and efficiently analyzed and processed, and are difficult to process when the traditional comprehensive evaluation method is used, so that the method compensates for the improvement of the traditional comprehensive evaluation method, and the traditional evaluation method is widely applied.

The mathematical model of fuzzy comprehensive evaluation generally comprises three basic elements:

(1) set of characteristic factors: u= { U ₁ ,u ₂ ,...,u _m }；

(2) Collection of evaluation sentences: v= { V ₁ ,v ₂ ,...,v _n }；

(3) Single factor evaluation function f: U-F%V)，

After the three basic elements are determined, the fuzzy relation R can be calculated _f E F (U X V), there are: r is R _f (u _i ,v _j )＝f(u _i )(v _j )＝r _ij . By R _f A fuzzy transformation matrix from U to V may be constructed:

as shown in FIG. 4, to have a clearer understanding of the fuzzy comprehensive evaluation model (U, V, R), it is approximately regarded as a converter, firstly, A epsilon F (U) is input, then R and the corresponding fuzzy operation rule are passedAnd finally, obtaining an output comprehensive evaluation result B epsilon F (V).

Specifically, the flow of the fuzzy synthesis method comprises the following steps:

2.3.1 A set of evaluation objects, a set of feature factors, and a set of evaluation sentences are determined.

Constructing an evaluation object set o= { O ₁ ,o ₂ ,...,o _n The O may include only one element, and in this embodiment, the energy efficiency utilization level of the campus integrated energy system may be an evaluation target. Next, the evaluation object is analyzed to determine u= { U ₁ ,u ₂ ,...,u _m Characteristics of the object to be evaluated are described, and in this embodiment, each evaluation index is used as a characteristic. Further, according to the object to be evaluated and the characteristic factors thereof, an appropriate evaluation statement set V= { V is established ₁ ,v ₂ ,...,v _n I.e. the evaluation result, in general v= { very feasible, general, infeasible }.

2.3.2 A fuzzy weight vector a is determined.

A represents the importance degree of each element in the characteristic factor set relative to the final evaluation purpose, and the characteristic factor set is obtained by calculating by an entropy weight method and a mean square error method.

2.3.3 A fuzzy transformation matrix R is calculated.

Firstly, evaluating a single factor aiming at each element, and recording the j-th comment V in V _j For the ith element U in U _i The evaluation degree of (2) is r _ij And is normalized to meetIn turn determining the requirement of a fuzzy mapping R from U to V _f ＝(r _i1 ,r _i2 ,...,r _in ) Finally, a comprehensive evaluation matrix for the evaluated object is jointly constructed:

2.3.4 And (3) obtaining an evaluation result by utilizing fuzzy complex operation.

After the definition of a and R, the above-described complex operator is further used to calculate the result, and the obtained result is a fuzzy comprehensive evaluation result of each evaluation object. In the invention, a weighted average operator is selected, namely:

B＝AR＝(b ₁ ,b ₂ ,...,b _n ) (38)

wherein, the liquid crystal display device comprises a liquid crystal display device,

2.3.5 And (3) fuzzy comprehensive evaluation result analysis.

The quantization processing is to further quantize the existing evaluation results to obtain the comprehensive score, so that on one hand, people can know the evaluation objects more precisely and specifically, and on the other hand, the transverse evaluation of the evaluation objects is realized. In the process of quantifying the evaluation object, the corresponding score is firstly assigned to each evaluation statement on V, and is combined with the calculated result B, and the final comprehensive score is obtained by adopting a corresponding operator for operation. The weighted average operator is commonly used, and the calculation method is as follows:

wherein c _j Is the score assigned to the j-th evaluation statement on V.

And similarly, the fuzzy comprehensive evaluation results of the indexes of each level can be obtained, and targeted transformation and investment are carried out aiming at weak layers.

In conclusion, the hierarchical evaluation index system of the park comprehensive energy system constructed by the invention is rich, and index data are sufficient. By constructing an energy efficiency evaluation model by using a fuzzy comprehensive evaluation method of an AHP-entropy weight method, the energy efficiency of a comprehensive energy project is evaluated, and expert experience and objective data information are comprehensively considered, so that the evaluation result is more scientific, objective and credible.

Example 2

In contrast to the above embodiment 1, which provides a method for evaluating energy efficiency of a campus, this embodiment provides a system for evaluating energy efficiency of a campus. The system provided in this embodiment may implement the method for evaluating energy utilization efficiency of a campus of embodiment 1, where the system may be implemented by software, hardware, or a combination of software and hardware. For example, the system may include integrated or separate functional modules or functional units to perform the corresponding steps in the methods of embodiment 1. Since the system of this embodiment is substantially similar to the method embodiment, the description of this embodiment is relatively simple, and the relevant points may be found in part in the description of embodiment 1, which is provided by way of illustration only.

As shown in fig. 5, the system for evaluating energy utilization efficiency of a campus provided in this embodiment includes:

the index value calculation unit is used for constructing a layering evaluation index system for evaluating the energy utilization efficiency of the park comprehensive energy system based on a predetermined index selection thought and basis, and calculating an evaluation index value;

Preferably, the basic data acquisition unit comprises an import basic data module and a data preprocessing module. The data input basic data module is used for inputting basic data, operating according to project requirements, clicking a basic data input button, popping up a dialog box, selecting the position of the data, and directly inputting the data, wherein the part of data serves for calculation and analysis of other modules; the data preprocessing module is used for preprocessing the imported basic data.

Preferably, the index value calculation unit includes: the system comprises an economic efficiency evaluation index calculation module, a green efficiency evaluation index calculation module, a physical efficiency evaluation index calculation module, a safety efficiency evaluation index calculation module, a reliable efficiency evaluation index calculation module and an intelligent efficiency evaluation index calculation module. Wherein, the functions of each module are respectively:

the economic efficiency evaluation index calculation module reflects the ratio of the current value of the cost in the life cycle to the current value of the generated energy in the life cycle by calculating and displaying cost indexes (unit load investment and unit load cost); reflecting the relation between the campus operation cost and the profit brought by the campus operation by displaying the revenue class index (revenue cost ratio); the development effect such as feasibility of the park project, development expectation degree and the like is reflected by displaying development type indexes (internal yield and investment recovery period).

The green efficiency evaluation index calculation module is used for showing the effects of carbon dioxide emission reduction and energy efficiency improvement after construction of a reaction park by virtue of synergistic emission reduction indexes (unit energy consumption emission, pollutant emission reduction rate, carbon emission reduction index and carbon emission balance index); the level of clean energy consumption by the campus is reflected by the demonstration of clean production class indicators (renewable energy permeability).

The physical efficiency evaluation index calculation module reflects the efficiency degree of energy transmission of a park by displaying energy transmission efficiency indexes (power grid line loss rate and pipe network heat/cold loss rate), so that constraint consideration is facilitated during operation; the energy conversion efficiency of energy-storage equipment and the energy consumption degree of the energy-storage equipment are reflected by displaying an energy conversion efficiency index (average utilization rate of equipment); the comprehensive energy efficiency degree of the park is reflected through the energy utilization efficiency index (comprehensive energy utilization efficiency).

The safety efficiency evaluation index calculation module is used for measuring the reliability of energy supply of a park by displaying power supply guarantee indexes (energy supply shortage rate and unplanned system outage coefficient); the adjustability of the operation of the power grid in the park is reflected by displaying the power grid guarantee class indexes (peak average load rate and valley average load rate).

The reliable efficiency evaluation index calculation module reflects the energy abundance level of the system by displaying energy supply margin indexes (energy self-supply rate); the qualification rate and the reliability of the energy supply of the system are reflected by showing the energy supply stability indexes (the comprehensive voltage qualification rate, the power supply reliability, the heat supply/cold supply reliability and the stability of the customer); the intelligent information level of the system is reflected by displaying intelligent information level class indexes (intelligent prediction accuracy, intelligent diagnosis accuracy and system fault self-healing capacity).

Preferably, the energy efficiency utilization rate evaluation unit includes: the system comprises a weight setting module, a comprehensive evaluation module and a result deriving module. The weight setting module is used for analyzing the index weight based on an analytic hierarchy process to obtain an index weight vector of each evaluation index; the evaluation standard setting module is used for setting a comment set of the index to obtain a comment grade corresponding to the index; the comprehensive evaluation module is used for evaluating the energy utilization efficiency of the park comprehensive energy system by adopting a fuzzy comprehensive evaluation method to obtain the energy utilization level of the comprehensive energy system; the result export module is used for exporting the final comprehensive evaluation result in the transverse and longitudinal directions in the form of an Excel table.

Specifically, in the weight setting module, as the Analytic Hierarchy Process (AHP) is selected as a method for determining the weight, the analytic hierarchy process replaces the assumption caused by subjective judgment factors of people by a quantitative form expression and processing method through qualitative evaluation. Therefore, in the weight setting module, the invention uses AHP calculation to obtain the weight of each index of the bottommost layer relative to the highest layer. The module is used for displaying the weight of each index value of the first part relative to the highest layer, firstly, three-level indexes under one index are compared two by two, the relative importance of N indexes in the same layer is scored by an expert, the score is input into a dialog box, the interface displays the weight corresponding to each index, and a weight result meeting scientific requirements and being objective is obtained.

And in the evaluation standard setting module, after the index is quantized, a comment set is determined according to the index attribute. In general, comment sets tend to have very feasible, general, infeasible, etc. categories. And dividing the index into equal parts according to the numerical range corresponding to the index, thereby forming an evaluation standard.

The module is used for displaying the comprehensive evaluation of the system and the grade corresponding to the comprehensive evaluation, wherein the comprehensive evaluation is a method for evaluating a plurality of indexes for a plurality of units of evaluation, and the units of evaluation can be evaluated more reasonably and accurately. The module of the project is to comprehensively evaluate a plurality of indexes of the first part, firstly, the indexes are classified into grades, each grade corresponds to a certain numerical range, and the grade of each index is judged by calculating the numerical value of each index in the index values through the identification module. And carrying out evaluation analysis on each index through the corresponding grade of the index. And secondly, classifying the indexes, determining the weights of the indexes, and finally, adopting a longitudinal evaluation method of an AHP fuzzy comprehensive evaluation method to obtain a final comprehensive evaluation result and evaluating the comprehensive energy efficiency of the park. The interface displays the final evaluation result, and then in order to better display the comparison result of various items, the scores of comprehensive evaluation of the items such as good, medium, bad and the like are displayed in a table form, so that the comparison analysis of users is facilitated.

Through the operation and the display of the module, the evaluation unit can be evaluated more scientifically, more reasonably and more accurately.

Example 3

The present embodiment provides a processing device corresponding to the method for evaluating energy utilization efficiency of a campus provided in the present embodiment 1, where the processing device may be a processing device for a client, for example, a mobile phone, a notebook computer, a tablet computer, a desktop computer, or the like, to execute the method of embodiment 1.

The processing device comprises a processor, a memory, a communication interface and a bus, wherein the processor, the memory and the communication interface are connected through the bus so as to complete communication among each other. The memory stores a computer program executable on the processor, and the processor executes the method for evaluating energy utilization efficiency of a campus provided in embodiment 1 when the processor executes the computer program.

In some embodiments, the memory may be a high-speed random access memory (RAM: random Access Memory), and may also include non-volatile memory (non-volatile memory), such as at least one disk memory.

In other embodiments, the processor may be a Central Processing Unit (CPU), a Digital Signal Processor (DSP), or other general purpose processor, which is not limited herein.

Example 4

The method for evaluating the efficiency of energy utilization of a campus of this embodiment 1 may be embodied as a computer program product, which may include a computer readable storage medium having computer readable program instructions for executing the method for evaluating the efficiency of energy utilization of a campus of this embodiment 1.

The computer readable storage medium may be a tangible device that retains and stores instructions for use by an instruction execution device. The computer readable storage medium may be, for example, but not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any combination of the preceding.

Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. The method for evaluating the energy utilization efficiency of the park is characterized by comprising the following steps of:

2. The method for evaluating energy utilization efficiency of a campus as claimed in claim 1, wherein the step of constructing a hierarchical evaluation index system for evaluating energy utilization efficiency of a comprehensive energy system of the campus based on a predetermined index selection idea and basis comprises:

determining an index selection thought and an index selection basis;

3. The method of energy efficiency assessment for a campus of claim 2, wherein the hierarchical assessment index system comprises at least one of: economic efficiency, green efficiency, physical efficiency, safety efficiency, reliable efficiency and intelligent efficiency evaluation indexes;

4. The method for evaluating energy utilization efficiency of a campus as claimed in claim 1, wherein the establishing a hierarchical evaluation index system based on the fuzzy comprehensive evaluation method of AHP-entropy weight method is used to establish an energy efficiency evaluation model, and the evaluating the energy utilization efficiency of the campus comprehensive energy system item to obtain an evaluation result comprises:

5. The method for evaluating energy utilization efficiency of a campus of claim 4, wherein the analyzing the index weights based on the hierarchical analysis method to obtain a first index weight vector of each evaluation index comprises:

6. The method for evaluating energy utilization efficiency of a campus of claim 4, wherein the analyzing the index weights based on the entropy method to obtain the second index weight vector of each evaluation index comprises:

carrying out standardization processing on each evaluation index data;

7. The method for evaluating energy utilization efficiency of a campus as claimed in claim 4, wherein the evaluating the energy utilization efficiency of the comprehensive energy system of the campus by using the fuzzy comprehensive evaluation method based on the first index weight vector and the second index weight vector to obtain the energy utilization level of the comprehensive energy system comprises:

8. A system for evaluating energy efficiency of a campus, comprising:

9. A processing apparatus comprising at least a processor and a memory, the memory having stored thereon a computer program, characterized in that the processor executes to implement the steps of the campus energy utilization efficiency assessment method of any one of claims 1 to 7 when the computer program is run by the processor.

10. A computer storage medium having stored thereon computer readable instructions executable by a processor to perform the steps of the method of campus energy utilization efficiency assessment according to any one of claims 1 to 7.