CN114708118B - Distributed gas energy state monitoring method and system based on neural network - Google Patents
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Abstract
The invention discloses a method and a system for monitoring the state of distributed gas energy based on a neural network, which can ensure the real-time performance and the effectiveness of monitoring data by acquiring the gas consumption of each distributed gas energy user side in each operation time period in a community energy management platform and analyzing the comprehensive energy utilization efficiency index of each distributed gas energy user side according to the electricity, the heat energy and the cold energy generated by each distributed gas energy user side in each operation time period, thereby meeting the requirements of the accuracy and the reliability of the energy utilization efficiency analysis result of the user side, and simultaneously evaluating the comprehensive waste gas emission influence index of each distributed gas energy user side according to the waste gas emission concentration of each distributed gas energy user side in each operation time period, thereby realizing the real-time monitoring and the feedback control of the waste gas emitted by the user side, and further maintaining the green energy image of the community energy management platform.
Description
Technical Field
The invention relates to the field of gas energy state monitoring, in particular to a distributed gas energy state monitoring method and system based on a neural network.
Background
Distributed gas energy systems are an emerging energy industry with government focus support. Governments in various places provide various policy support and economic subsidy measures for distributed gas energy projects, and the policies and subsidies are directly linked with the running state, the actual energy utilization efficiency and the like of a distributed gas energy system. Therefore, a mature, stable and reliable distributed gas energy state monitoring system is urgently needed in actual work.
At present, the existing distributed gas energy state monitoring technology can only monitor and analyze the utilization efficiency of distributed gas energy comprehensively, namely, managers analyze the energy utilization efficiency of distributed gas energy user sides according to the comprehensive operation data of the distributed gas energy user sides in each month, but the problems of poor automation and intelligence degree exist, so that the real-time performance and effectiveness of monitoring data are influenced, and the accuracy and reliability of the energy utilization efficiency analysis result of the user sides are further difficult to meet the requirements.
The existing distributed gas energy state monitoring technology lacks real-time monitoring and feedback control on the exhaust gas discharged by a distributed gas energy user side, and the situation that the exhaust gas discharge concentration of the user side exceeds the standard and is not processed in time exists, so that the situation that the user side corresponds to the family home environment is polluted, and further the life safety of the user side corresponding to family members is seriously threatened, further the energy-saving benefit, the environmental protection benefit and the economic and social benefit of a distributed gas energy system can not be realized, and the negative influence is caused on the green energy image of a community energy management platform.
Disclosure of Invention
Aiming at the problems, the invention provides a distributed gas energy state monitoring method and system based on a neural network, and the method and system can realize the function of monitoring and analyzing the state of the distributed gas energy.
The technical scheme adopted by the invention for solving the technical problems is as follows:
in a first aspect, the invention provides a distributed gas energy state monitoring method based on a neural network, comprising the following steps:
s1, numbering of distributed gas energy user sides: acquiring each distributed gas energy user side in the community energy management platform, and numbering each distributed gas energy user side in the community energy management platform;
s2, acquiring the gas consumption of the user side: acquiring the gas consumption of each distributed gas energy user side in the community energy management platform in each operation time period, and analyzing the heat energy conversion amount of each distributed gas energy user side in each operation time period;
s3, analyzing the power generation heat energy consumption of the user side: acquiring the electric quantity generated by each distributed gas energy user side in each operation time period, and analyzing the generated heat energy consumption of each distributed gas energy user side in each operation time period;
s4, evaluating the power utilization efficiency of the user side: evaluating the average electric energy utilization efficiency proportionality coefficient of each distributed gas energy user side according to the generated heat energy consumption of each distributed gas energy user side in each operation time period;
s5, obtaining the heat energy and cold energy usage of the user side: acquiring the heat energy usage amount and the cold energy usage amount of each distributed gas energy user side in each operation time period to obtain the average residual heat energy utilization efficiency proportionality coefficient of each distributed gas energy user side;
s6, analyzing the comprehensive energy utilization efficiency index: analyzing the comprehensive energy utilization efficiency index of each distributed gas energy user side, and screening and counting corresponding numbers of each distributed gas energy user side with unqualified energy utilization efficiency;
s7, estimating the influence index of the exhaust emission of the user side: detecting the exhaust emission concentration of each distributed gas energy user side in each operation time period, and evaluating the comprehensive exhaust emission influence index of each distributed gas energy user side;
s8, analyzing and processing the community energy management platform: and comparing the comprehensive exhaust emission influence index of each distributed gas energy user side with a preset safe exhaust emission influence index threshold, processing according to a comparison result, and displaying the corresponding number of each distributed gas energy user side with unqualified energy utilization efficiency.
On the basis of the foregoing embodiment, the analyzing, in step S2, the heat energy conversion amount of each distributed gas energy user side in each operation time period specifically includes:
recording the real-time running time of each distributed gas energy user side in the community energy management platform, and dividing the real-time running time of each distributed gas energy user side in the community energy management platform into running time periods according to preset time intervals;
acquiring the gas consumption of each distributed gas energy user side in each operation time period in the community energy management platform, andextracting standard heat energy conversion rate corresponding to each distributed gas energy user side stored in a gas energy management database, and analyzing heat energy conversion quantity Q of each distributed gas energy user side in each operation time period i t j Where i is 1, 2.. and n, i is the number of the ith distributed gas energy user terminal, and j is 1, 2.. and m, j is the jth operation time period.
On the basis of the above embodiment, the analyzing, in step S3, the generated heat energy consumption of each distributed gas energy user side in each operation time period includes:
acquiring the electric quantity generated by each distributed gas energy user side in each operation time period, and marking the electric quantity generated by each distributed gas energy user side in each operation time period as w i t j ；
Extracting standard heat energy consumption corresponding to unit electric quantity generated by each distributed gas energy user side stored in a gas energy management database, and marking the standard heat energy consumption corresponding to the unit electric quantity generated by each distributed gas energy user side as q i ；
Analyzing power generation heat energy consumption Q 'of each distributed gas energy user side in each operation time period' i t′ j ＝w i t j *q i (1+ μ), where μ is represented as a preset power generation heat consumption amount correction weight factor.
On the basis of the foregoing embodiment, in the step S4, the average power utilization ratio coefficient of each distributed gas energy user side is evaluated, and the specific evaluation manner is as follows:
converting heat energy Q of each distributed gas energy user side in each operation time period i t j And generating heat energy consumption Q 'of each distributed gas energy user side in each operation time period' i t′ j Substituting into an analysis formula of the proportional coefficient of the electric energy utilization efficiency
Obtaining the average electric energy utilization efficiency proportionality coefficient xi of each distributed gas energy user side i Wherein m is represented as a partitionThe number of operation time periods, alpha, is expressed as a preset electric energy utilization efficiency corresponding influence factor, theta i And the rated electric energy utilization efficiency of the ith distributed gas energy user side is expressed as preset rated electric energy utilization efficiency.
On the basis of the foregoing embodiment, the obtaining of the heat energy usage amount and the cold energy usage amount of each distributed gas energy user side in each operation time period in step S5 specifically includes:
the method comprises the steps of obtaining heat energy usage of each distributed gas energy user side in each operation time period, analyzing and obtaining heat energy usage utilization efficiency of each distributed gas energy user side in each operation time period according to the heat energy usage of each distributed gas energy user side in each operation time period, and marking the heat energy usage utilization efficiency of each distributed gas energy user side in each operation time period as x i t j ；
The method comprises the steps of obtaining the cold energy usage amount of each distributed gas energy user side in each operation time period, analyzing and obtaining the cold energy usage amount utilization efficiency of each distributed gas energy user side in each operation time period according to the cold energy usage amount of each distributed gas energy user side in each operation time period, and marking the cold energy usage amount utilization efficiency of each distributed gas energy user side in each operation time period as y i t j 。
On the basis of the foregoing embodiment, the average remaining heat energy utilization efficiency proportional coefficient of each distributed gas energy user side is obtained in step S5, and the specific obtaining manner is as follows:
utilizing efficiency x of heat energy usage of each distributed gas energy user side in each operation time period i t j And cold energy use efficiency y i t j Substituting into the analysis formula of the heat energy utilization efficiency proportionality coefficient
Obtaining the average residual heat energy utilization efficiency proportional coefficient psi of each distributed gas energy user side i Where m is expressed as the number of divided operating periods, β 1 And beta 2 Respectively expressed as preset heat energy utilization efficiency corresponding influenceThe factor and the preset cold energy utilization efficiency correspond to an influence factor, and beta 1 +β 2 ＝1，X′ i And Y' i Respectively representing the rated heat energy utilization efficiency and the rated cold energy utilization efficiency of the preset ith distributed gas energy user side.
On the basis of the foregoing embodiment, the specific detailed process in step S6 includes:
the average electric energy utilization efficiency proportionality coefficient xi of each distributed gas energy user side i And average residual heat energy utilization efficiency proportional coefficient psi i Substitution into the formula phi i ＝λ 1 *ξ i +λ 2 *ψ i Obtaining the comprehensive energy utilization efficiency index phi of each distributed gas energy user side i Wherein λ is 1 And λ 2 Respectively expressed as a preset electric energy utilization efficiency influence weight factor and a preset residual heat energy utilization efficiency influence weight factor;
and comparing the comprehensive energy utilization efficiency index of each distributed gas energy user side with a preset standard energy utilization efficiency index threshold, if the comprehensive energy utilization efficiency index of a certain distributed gas energy user side is smaller than the preset standard energy utilization efficiency index threshold, indicating that the energy utilization efficiency of the distributed gas energy user side is unqualified, and counting the corresponding number of each distributed gas energy user side with unqualified energy utilization efficiency.
On the basis of the above embodiment, in the step S7, the comprehensive exhaust emission influence index of each distributed gas energy user side is evaluated in a specific evaluation manner:
detecting the exhaust emission concentration of corresponding user sides in each operation time period through exhaust gas detection equipment arranged in exhaust emission ports in each distributed gas energy user side, wherein the exhaust comprises carbon monoxide, carbon dioxide, nitric oxide and methane, substituting the exhaust emission concentration of each distributed gas energy user side in each operation time period into an exhaust emission influence index evaluation formula, and obtaining the comprehensive exhaust emission influence index of each distributed gas energy user side
On the basis of the above embodiment, the step S8 of comparing the comprehensive exhaust emission influence index of each distributed gas energy user side with the preset safe exhaust emission influence index threshold, and processing according to the comparison result includes:
the comprehensive exhaust emission influence index of each distributed gas energy user side is compared with a preset safe exhaust emission influence index threshold, if the comprehensive exhaust emission influence index of a certain distributed gas energy user side is smaller than or equal to the preset safe exhaust emission influence index threshold, it is indicated that the exhaust emission of the distributed gas energy user side meets the standard, and if the comprehensive exhaust emission influence index of a certain distributed gas energy user side is larger than the preset safe exhaust emission influence index threshold, it is indicated that the exhaust emission of the distributed gas energy user side does not meet the standard, voice early warning reminding is performed.
In a second aspect, the present invention further provides a distributed gas energy state monitoring system based on a neural network, including:
distributed gas energy user side numbering module: the system comprises a community energy management platform, a management center and a management center, wherein the community energy management platform is used for acquiring distributed gas energy user sides in the community energy management platform and numbering the distributed gas energy user sides in the community energy management platform;
the user side gas consumption obtaining module: the system comprises a community energy management platform, a heat energy management system and a heat energy management system, wherein the community energy management platform is used for acquiring the gas consumption of each distributed gas energy user side in each operation time period and analyzing the heat energy conversion amount of each distributed gas energy user side in each operation time period;
the user side power generation heat energy consumption analysis module: the system comprises a power generation system, a power generation system and a power generation system, wherein the power generation system is used for acquiring electric quantity generated by each distributed gas energy user side in each operation time period and analyzing the power generation heat energy consumption of each distributed gas energy user side in each operation time period;
the user side electric energy utilization efficiency evaluation module: the system comprises a power generation system, a distributed gas energy source client, a power generation system and a power generation system, wherein the power generation system is used for generating power for each distributed gas energy source client;
the user side heat energy and cold energy usage acquisition module: the system is used for acquiring the heat energy usage amount and the cold energy usage amount of each distributed gas energy user side in each operation time period to obtain the average residual heat energy utilization efficiency proportionality coefficient of each distributed gas energy user side;
comprehensive energy utilization efficiency index analysis module: the comprehensive energy utilization efficiency index analysis system is used for analyzing the comprehensive energy utilization efficiency index of each distributed gas energy user side and screening and counting corresponding numbers of each distributed gas energy user side with unqualified energy utilization efficiency;
the user side exhaust emission influence index evaluation module: the system is used for detecting the exhaust emission concentration of each distributed gas energy user side in each operation time period and evaluating the comprehensive exhaust emission influence index of each distributed gas energy user side;
the community energy management platform analysis processing module: the system comprises a data processing system, a data processing system and a data processing system, wherein the data processing system is used for comparing the comprehensive exhaust emission influence index of each distributed gas energy user side with a preset safe exhaust emission influence index threshold, processing according to the comparison result, and displaying the corresponding number of each distributed gas energy user side with unqualified energy utilization efficiency;
a gas energy management database: the system is used for storing the standard heat energy conversion rate corresponding to each distributed gas energy user side and the standard heat energy consumption corresponding to the unit electric quantity generated by each distributed gas energy user side.
Compared with the prior art, the distributed gas energy state monitoring method and system based on the neural network have the following beneficial effects:
according to the distributed gas energy state monitoring method and system based on the neural network, the gas consumption of each distributed gas energy user side in each operation time period in the community energy management platform is obtained, the heat energy conversion amount of each distributed gas energy user side in each operation time period is obtained, and the comprehensive energy utilization efficiency index of each distributed gas energy user side is analyzed according to the generated electric quantity, the heat energy utilization amount and the cold energy utilization amount of each distributed gas energy user side in each operation time period, so that the automation degree and the intelligence degree of the distributed gas energy state monitoring technology are effectively improved, the real-time performance and the effectiveness of the distributed gas energy state monitoring data are ensured, and the accuracy and the reliability requirements of the energy utilization efficiency analysis result of the user side are further met.
The distributed gas energy state monitoring method and the system based on the neural network analyze the comprehensive exhaust emission influence index of each distributed gas energy user side by detecting the exhaust emission concentration of each distributed gas energy user side in each operation time period, simultaneously, the safety waste gas emission influence index is respectively compared with a preset safety waste gas emission influence index threshold value and processed according to the comparison result, thereby realizing real-time monitoring and feedback control of the exhaust gas discharged by the distributed gas energy user side, can effectively avoid the situation that the exhaust emission concentration of the user side exceeds the standard and the user side is not processed in time, further ensure the life safety of the user side corresponding to the family home environment and family members, the energy-saving benefit, the environmental protection benefit and the economic and social benefit of the distributed gas energy system are realized to a great extent, and the green energy image of the community energy management platform is further maintained.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the description below are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic flow diagram of the process of the present invention;
fig. 2 is a system module connection diagram of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, a first aspect of the present invention provides a method for monitoring the state of a distributed gas energy based on a neural network, including the following steps:
s1, numbering of distributed gas energy user sides: and acquiring each distributed gas energy user side in the community energy management platform, and numbering each distributed gas energy user side in the community energy management platform.
S2, acquiring the gas consumption of the user side: the method comprises the steps of obtaining the gas consumption of each distributed gas energy user side in each operation time period in a community energy management platform, and analyzing the heat energy conversion amount of each distributed gas energy user side in each operation time period.
As a preferable scheme, the analyzing the heat energy conversion amount of each distributed gas energy user side in each operation time period in step S2 specifically includes:
recording the real-time running time of each distributed gas energy user side in the community energy management platform, and dividing the real-time running time of each distributed gas energy user side in the community energy management platform into running time periods according to preset time intervals;
acquiring the gas consumption of each distributed gas energy user side in the community energy management platform in each operation time period, extracting the standard heat energy conversion rate corresponding to each distributed gas energy user side stored in the gas energy management database, and analyzing the heat energy conversion quantity Q of each distributed gas energy user side in each operation time period i t j Where i is 1, 2.. and n, i is the number of the ith distributed gas energy user terminal, and j is 1, 2.. and m, j is the jth operation time period.
As an embodiment of the present invention, the analysis formula of the heat energy conversion amount of each distributed gas energy user end in each operation time period is Q i t j ＝p i t j *k i Wherein Q is i t j Expressed as the ith distributionThe heat energy conversion amount p of the formula gas energy user end in the jth operation time section i t j Expressed as the gas consumption, k, of the ith distributed gas energy user side in the jth operation time period i And the standard heat energy conversion rate is expressed as the standard heat energy conversion rate corresponding to the ith distributed gas energy user side.
S3, analyzing the power generation heat energy consumption of the user side: the method comprises the steps of obtaining electric quantity generated by each distributed gas energy user side in each operation time period, and analyzing the generated heat energy consumption of each distributed gas energy user side in each operation time period.
As a preferable scheme, the analyzing of the generated heat consumption of each distributed gas energy user side in each operation time period in step S3 includes:
acquiring the electric quantity generated by each distributed gas energy user side in each operation time period, and marking the electric quantity generated by each distributed gas energy user side in each operation time period as w i t j ；
Extracting standard heat energy consumption corresponding to unit electric quantity generated by each distributed gas energy user side stored in a gas energy management database, and marking the standard heat energy consumption corresponding to the unit electric quantity generated by each distributed gas energy user side as q i ；
Analyzing power generation heat energy consumption Q 'of each distributed gas energy user side in each operation time period' i t′ j ＝w i t j *q i (1+ μ), where μ is represented as a preset power generation heat consumption amount correction weight factor.
S4, evaluating the power utilization efficiency of the user side: and evaluating the average electric energy utilization efficiency proportionality coefficient of each distributed gas energy user side according to the generated heat energy consumption of each distributed gas energy user side in each operation time period.
As a preferable scheme, in the step S4, the average power utilization ratio coefficient of each distributed gas energy user side is evaluated, and the specific evaluation manner is as follows:
converting heat energy Q of each distributed gas energy user side in each operation time period i t j And generating heat energy consumption Q 'of each distributed gas energy user side in each operation time period' i t′ j Substituting into the analysis formula of the proportional coefficient of the electric energy utilization efficiency
Obtaining the average electric energy utilization efficiency proportionality coefficient xi of each distributed gas energy user side i Where m is the number of divided operation periods, α is a preset influence factor corresponding to the electric energy utilization efficiency, and θ i And the rated electric energy utilization efficiency of the ith distributed gas energy user side is expressed.
S5, obtaining the heat energy and cold energy consumption of the user side: and acquiring the heat energy usage amount and the cold energy usage amount of each distributed gas energy user side in each operation time period to obtain the average residual heat energy utilization efficiency proportionality coefficient of each distributed gas energy user side.
As a preferable scheme, the acquiring of the heat energy usage amount and the cold energy usage amount of each distributed gas energy user side in each operation time period in step S5 specifically includes:
the method comprises the steps of obtaining heat energy usage of each distributed gas energy user side in each operation time period, analyzing and obtaining heat energy usage utilization efficiency of each distributed gas energy user side in each operation time period according to the heat energy usage of each distributed gas energy user side in each operation time period, and marking the heat energy usage utilization efficiency of each distributed gas energy user side in each operation time period as x i t j ；
The method comprises the steps of obtaining the cold energy usage amount of each distributed gas energy user side in each operation time period, analyzing and obtaining the cold energy usage amount utilization efficiency of each distributed gas energy user side in each operation time period according to the cold energy usage amount of each distributed gas energy user side in each operation time period, and marking the cold energy usage amount utilization efficiency of each distributed gas energy user side in each operation time period as y i t j 。
As a specific embodiment of the present invention, the analyzing and obtaining the utilization efficiency of the heat energy usage of each distributed gas energy user side in each operation time period includes:
substituting heat energy conversion amount, power generation heat energy consumption amount and heat energy usage amount of each distributed gas energy user side in each operation time period into a heat energy usage amount utilization efficiency analysis formula
Obtaining the utilization efficiency x of the heat energy consumption of each distributed gas energy user side in each operation time period i t j Wherein r is i t j The heat energy usage amount of the ith distributed gas energy user side in the jth operation time period is shown.
As a specific embodiment of the present invention, the analyzing and obtaining the utilization efficiency of the cold energy usage amount of each distributed gas energy user side in each operation time period includes:
substituting the heat energy conversion amount, the power generation heat energy consumption amount and the cold energy consumption amount of each distributed gas energy user end in each operation time period into a cold energy utilization efficiency analysis formula
Obtaining the utilization efficiency y of the cold energy consumption of each distributed gas energy user side in each operation time period i t j Wherein r' i t j The amount of cold energy used by the ith distributed gas energy user side in the jth operation time period is represented, and delta is a standard conversion rate corresponding to preset heat energy conversion cold energy.
As a preferable scheme, the step S5 obtains an average remaining heat energy utilization efficiency proportional coefficient of each distributed gas energy user side, and the specific obtaining method is as follows:
the utilization efficiency x of the heat energy consumption of each distributed gas energy user side in each operation time period i t j And cold energy use efficiency y i t j Substituting into the analysis formula of the heat energy utilization efficiency proportionality coefficient
To obtainAverage residual heat energy utilization efficiency proportionality coefficient psi of each distributed gas energy user side i Where m is expressed as the number of divided operating periods, β 1 And beta 2 Expressed as a preset influence factor corresponding to the heat energy utilization efficiency and a preset influence factor corresponding to the cold energy utilization efficiency, respectively, and beta 1 +β 2 ＝1，X′ i And Y' i Respectively representing the rated heat energy utilization efficiency and the rated cold energy utilization efficiency of the preset ith distributed gas energy user side.
S6, analyzing the comprehensive energy utilization efficiency index: and analyzing the comprehensive energy utilization efficiency index of each distributed gas energy user side, and screening and counting the corresponding number of each distributed gas energy user side with unqualified energy utilization efficiency.
As a preferable scheme, the specific detailed process in step S6 includes:
the average electric energy utilization efficiency proportionality coefficient xi of each distributed gas energy user side i And the average residual heat energy utilization efficiency proportionality coefficient psi i Substitution into the formula phi i ＝λ 1 *ξ i +λ 2 *ψ i Obtaining the comprehensive energy utilization efficiency index phi of each distributed gas energy user side i Wherein λ is 1 And λ 2 Respectively expressed as a preset electric energy utilization efficiency influence weight factor and a preset residual heat energy utilization efficiency influence weight factor;
and comparing the comprehensive energy utilization efficiency index of each distributed gas energy user side with a preset standard energy utilization efficiency index threshold, if the comprehensive energy utilization efficiency index of a certain distributed gas energy user side is smaller than the preset standard energy utilization efficiency index threshold, indicating that the energy utilization efficiency of the distributed gas energy user side is unqualified, and counting the corresponding number of each distributed gas energy user side with unqualified energy utilization efficiency.
In this embodiment, the heat energy conversion amount of each distributed gas energy user side in each operation time period is obtained by obtaining the gas consumption amount of each distributed gas energy user side in each operation time period in the community energy management platform, and the comprehensive energy utilization efficiency index of each distributed gas energy user side is analyzed according to the electricity, heat energy and cold energy generated by each distributed gas energy user side in each operation time period, so that the automation degree and the intelligence degree of the distributed gas energy state monitoring technology are effectively improved, the real-time performance and the effectiveness of the distributed gas energy state monitoring data are ensured, and the accuracy and the reliability requirements of the energy utilization efficiency analysis result of the user side are further met.
S7, estimating the influence index of the exhaust emission of the user side: and detecting the exhaust emission concentration of each distributed gas energy user side in each operation time period, and evaluating the comprehensive exhaust emission influence index of each distributed gas energy user side.
As a preferable scheme, in the step S7, the comprehensive exhaust emission influence index of each distributed gas energy user side is evaluated, and the specific evaluation manner is as follows:
detecting the exhaust emission concentration of corresponding user sides in each operation time period through exhaust gas detection equipment arranged in exhaust emission ports in each distributed gas energy user side, wherein the exhaust comprises carbon monoxide, carbon dioxide, nitric oxide and methane, substituting the exhaust emission concentration of each distributed gas energy user side in each operation time period into an exhaust emission influence index evaluation formula, and obtaining the comprehensive exhaust emission influence index of each distributed gas energy user side
As a specific embodiment of the present invention, the exhaust gas detection apparatus includes a carbon monoxide sensor, a carbon dioxide sensor, a nitrogen oxide sensor, and a methane concentration detector, the carbon monoxide sensor is configured to detect a carbon monoxide concentration of each distributed gas energy user in each operation period, the carbon dioxide sensor is configured to detect a carbon dioxide concentration of each distributed gas energy user in each operation period, the nitrogen oxide sensor is configured to detect a nitrogen oxide concentration of each distributed gas energy user in each operation period, and the methane concentration detector is configured to detect a methane concentration of each distributed gas energy user in each operation period.
Further, the above-mentioned middle exhaust emission influence index evaluation formula is
Wherein
Expressed as the integrated exhaust emission impact index, gamma, at the ith distributed gas energy user side 1 、γ 2 、γ 3 、γ 4 Respectively expressed as preset emission influence proportional coefficients of carbon monoxide, carbon dioxide, nitrogen oxide and methane, f 1 a ij 、f 2 a ij 、f 3 a ij 、f 4 a ij Respectively expressed as carbon monoxide emission concentration, carbon dioxide emission concentration, nitrogen oxide emission concentration and methane emission concentration in the ith operation time period at the ith distributed gas energy user side 1 a An 、f 2 a An 、f 3 a An 、f 4 a An Respectively expressed as the corresponding safe carbon monoxide emission concentration, the safe carbon dioxide emission concentration, the safe nitrogen oxide emission concentration and the safe methane emission concentration, delta f, of the preset standard distributed gas energy user side in the operation process 4 Expressed as a preset safe methane emission concentration allowable error value.
S8, analyzing and processing the community energy management platform: the comprehensive exhaust emission influence index of each distributed gas energy user side is compared with a preset safe exhaust emission influence index threshold, the comprehensive exhaust emission influence index is processed according to a comparison result, the corresponding serial numbers of each distributed gas energy user side with unqualified energy utilization efficiency are displayed simultaneously, and corresponding door-to-door processing is carried out according to the displayed serial numbers through community energy management platform management personnel.
As a preferable scheme, the step S8 of comparing the comprehensive exhaust emission influence index of each distributed gas energy user side with a preset safe exhaust emission influence index threshold, and processing according to the comparison result includes:
the comprehensive exhaust emission influence index of each distributed gas energy user side is compared with a preset safe exhaust emission influence index threshold, if the comprehensive exhaust emission influence index of a certain distributed gas energy user side is smaller than or equal to the preset safe exhaust emission influence index threshold, it is indicated that the exhaust emission of the distributed gas energy user side meets the standard, and if the comprehensive exhaust emission influence index of a certain distributed gas energy user side is larger than the preset safe exhaust emission influence index threshold, it is indicated that the exhaust emission of the distributed gas energy user side does not meet the standard, voice early warning reminding is performed.
In this embodiment, the comprehensive exhaust emission influence index of each distributed gas energy user side is analyzed by detecting the exhaust emission concentration of each distributed gas energy user side in each operation time period, and is simultaneously compared with the preset safe exhaust emission influence index threshold value and processed according to the comparison result, so that the exhaust emission of each distributed gas energy user side is monitored and feedback-controlled in real time, the situation that the exhaust emission concentration of the user side exceeds the standard and is not processed in time can be effectively avoided, the life safety of the user side corresponding to the family home environment and family members is further ensured, the energy-saving benefit, the environmental protection benefit and the economic and social benefit of the distributed gas energy system are realized to a great extent, and the green energy image of the community energy management platform is further maintained.
In a second aspect, the invention further provides a distributed gas energy state monitoring system based on a neural network, which includes a distributed gas energy user side numbering module, a user side gas consumption obtaining module, a user side power generation heat energy consumption analyzing module, a user side electric energy utilization efficiency evaluating module, a user side heat energy and cold energy usage obtaining module, a comprehensive energy utilization efficiency index analyzing module, a user side exhaust emission influence index evaluating module, a community energy management platform analyzing and processing module and a gas energy management database.
The distributed gas energy user end numbering module is respectively connected with a user end gas consumption acquisition module and a user end heat energy and cold energy consumption acquisition module, the user end gas consumption acquisition module is respectively connected with a user end power generation heat energy consumption analysis module, the system comprises a user side electric energy utilization efficiency evaluation module, a gas energy management database, a user side power generation heat energy consumption analysis module, a user side electric energy utilization efficiency evaluation module and a gas energy management database, wherein the user side power generation heat energy consumption analysis module is respectively connected with the user side electric energy utilization efficiency evaluation module and the gas energy management database, a comprehensive energy utilization efficiency index analysis module is respectively connected with the user side electric energy utilization efficiency evaluation module and a user side heat energy and cold energy consumption acquisition module, the user side waste gas emission influence index evaluation module is connected with a distributed gas energy user side numbering module, and a community energy management platform analysis processing module is respectively connected with the comprehensive energy utilization efficiency index analysis module and the user side waste gas emission influence index evaluation module.
The distributed gas energy user side numbering module is used for acquiring each distributed gas energy user side in the community energy management platform and numbering each distributed gas energy user side in the community energy management platform;
the user side gas consumption acquisition module is used for acquiring the gas consumption of each distributed gas energy user side in the community energy management platform in each operation time period and analyzing the heat energy conversion amount of each distributed gas energy user side in each operation time period;
the user side power generation heat energy consumption analysis module is used for acquiring electric quantity generated by each distributed gas energy user side in each operation time period and analyzing power generation heat energy consumption of each distributed gas energy user side in each operation time period;
the user side electric energy utilization efficiency evaluation module is used for evaluating the average electric energy utilization efficiency proportionality coefficient of each distributed gas energy user side according to the power generation heat energy consumption of each distributed gas energy user side in each operation time period;
the user side heat energy and cold energy usage acquisition module is used for acquiring heat energy usage and cold energy usage of each distributed gas energy user side in each operation time period to obtain an average residual heat energy utilization efficiency proportional coefficient of each distributed gas energy user side;
the comprehensive energy utilization efficiency index analysis module is used for analyzing the comprehensive energy utilization efficiency index of each distributed gas energy user side and screening and counting corresponding numbers of each distributed gas energy user side with unqualified energy utilization efficiency;
the user side waste gas emission influence index evaluation module is used for detecting the waste gas emission concentration of each distributed gas energy user side in each operation time period and evaluating the comprehensive waste gas emission influence index of each distributed gas energy user side;
the community energy management platform analysis processing module is used for comparing the comprehensive exhaust emission influence index of each distributed gas energy user side with a preset safe exhaust emission influence index threshold, processing according to the comparison result, and displaying the corresponding number of each distributed gas energy user side with unqualified energy utilization efficiency;
the gas energy management database is used for storing the standard heat energy conversion rate corresponding to each distributed gas energy user side and the standard heat energy consumption amount corresponding to the unit electric quantity generated by each distributed gas energy user side.
The foregoing is merely exemplary and illustrative of the principles of the present invention and various modifications, additions and substitutions of the specific embodiments described herein may be made by those skilled in the art without departing from the principles of the present invention or exceeding the scope of the claims set forth herein.
Claims (10)
1. The distributed gas energy state monitoring method based on the neural network is characterized by comprising the following steps of:
s1, numbering distributed gas energy user sides: acquiring each distributed gas energy user side in the community energy management platform, and numbering each distributed gas energy user side in the community energy management platform;
s2, acquiring the gas consumption of the user side: acquiring the gas consumption of each distributed gas energy user side in the community energy management platform in each operation time period, and analyzing the heat energy conversion amount of each distributed gas energy user side in each operation time period;
s3, analyzing the power generation heat energy consumption of the user side: acquiring the electric quantity generated by each distributed gas energy user side in each operation time period, and analyzing the generated heat energy consumption of each distributed gas energy user side in each operation time period;
s4, evaluating the power utilization efficiency of the user side: according to the power generation heat energy consumption of each distributed gas energy user side in each operation time period, evaluating the average electric energy utilization efficiency proportionality coefficient of each distributed gas energy user side;
s5, obtaining the heat energy and cold energy usage of the user side: acquiring the heat energy usage amount and the cold energy usage amount of each distributed gas energy user side in each operation time period to obtain the average residual heat energy utilization efficiency proportionality coefficient of each distributed gas energy user side;
s6, analyzing the comprehensive energy utilization efficiency index: analyzing the comprehensive energy utilization efficiency index of each distributed gas energy user side, and screening and counting corresponding numbers of each distributed gas energy user side with unqualified energy utilization efficiency;
s7, evaluating the influence index of the exhaust emission of the user side: detecting the exhaust emission concentration of each distributed gas energy user side in each operation time period, and evaluating the comprehensive exhaust emission influence index of each distributed gas energy user side;
s8, analyzing and processing the community energy management platform: and comparing the comprehensive exhaust emission influence index of each distributed gas energy user side with a preset safe exhaust emission influence index threshold, processing according to a comparison result, and displaying the corresponding number of each distributed gas energy user side with unqualified energy utilization efficiency.
2. The neural network-based distributed gas energy state monitoring method according to claim 1, wherein: in the step S2, analyzing the heat energy conversion amount of each distributed gas energy user side in each operation time period includes:
recording the real-time running time of each distributed gas energy user side in the community energy management platform, and dividing the real-time running time of each distributed gas energy user side in the community energy management platform into running time periods according to preset time intervals;
acquiring the gas consumption of each distributed gas energy user side in the community energy management platform in each operation time period, extracting the standard heat energy conversion rate corresponding to each distributed gas energy user side stored in the gas energy management database, and analyzing the heat energy conversion rate Q of each distributed gas energy user side in each operation time period i t j The i is the number of the ith distributed gas energy user end, and the j is the number of the jth operation time period, wherein the i is 1, 2.
3. The neural network-based distributed gas energy state monitoring method according to claim 1, wherein: in the step S3, analyzing the power generation heat consumption of each distributed gas energy user side in each operation time period includes:
acquiring the electric quantity generated by each distributed gas energy user side in each operation time period, and marking the electric quantity generated by each distributed gas energy user side in each operation time period as w i t j ；
Extracting standard heat energy consumption corresponding to unit electric quantity generated by each distributed gas energy user side stored in a gas energy management database, and marking the standard heat energy consumption corresponding to the unit electric quantity generated by each distributed gas energy user side as q i ；
Analyzing power generation heat energy consumption Q 'of each distributed gas energy user side in each operation time period' i t′ j ＝w i t j *q i (1+ μ), where μ is represented as a preset power generation heat consumption amount correction weight factor.
4. The neural network-based distributed gas energy state monitoring method according to claim 1, wherein: in the step S4, the average power utilization ratio coefficient of each distributed gas energy user side is evaluated, and the specific evaluation method is as follows:
converting heat energy Q of each distributed gas energy user side in each operation time period i t j And generating heat energy consumption Q 'of each distributed gas energy user side in each operation time period' i t′ j Substituting into an analysis formula of the proportional coefficient of the electric energy utilization efficiency
Obtaining the average electric energy utilization efficiency proportional coefficient xi of each distributed gas energy user side i Where m is the number of divided operation periods, α is a preset influence factor corresponding to the electric energy utilization efficiency, and θ i And the rated electric energy utilization efficiency of the ith distributed gas energy user side is expressed.
5. The neural network-based distributed gas energy state monitoring method according to claim 1, wherein: in step S5, obtaining the heat energy usage amount and the cold energy usage amount of each distributed gas energy user side in each operation time period specifically includes:
the method comprises the steps of obtaining heat energy usage of each distributed gas energy user side in each operation time period, analyzing and obtaining heat energy usage utilization efficiency of each distributed gas energy user side in each operation time period according to the heat energy usage of each distributed gas energy user side in each operation time period, and marking the heat energy usage utilization efficiency of each distributed gas energy user side in each operation time period as x i t j ；
The method comprises the steps of obtaining the cold energy usage amount of each distributed gas energy user side in each operation time period, analyzing and obtaining the cold energy usage amount utilization efficiency of each distributed gas energy user side in each operation time period according to the cold energy usage amount of each distributed gas energy user side in each operation time period, and marking the cold energy usage amount utilization efficiency of each distributed gas energy user side in each operation time period as y i t j 。
6. The neural network-based distributed gas energy state monitoring method according to claim 1, wherein: in the step S5, an average remaining heat energy utilization ratio coefficient of each distributed gas energy user side is obtained, and the specific obtaining method is as follows:
utilizing efficiency x of heat energy usage of each distributed gas energy user side in each operation time period i t j And cold energy use efficiency y i t j Substituting into the analysis formula of the heat energy utilization efficiency proportionality coefficient
Obtaining the average residual heat energy utilization efficiency proportional coefficient psi of each distributed gas energy user side i Where m is expressed as the number of divided operating periods, β 1 And beta 2 Expressed as a preset influence factor corresponding to the heat energy utilization efficiency and a preset influence factor corresponding to the cold energy utilization efficiency, respectively, and beta 1 +β 2 ＝1，X′ i And Y i ' is respectively expressed as the rated heat energy utilization efficiency and the rated cold energy utilization efficiency of the preset ith distributed gas energy user side.
7. The neural network-based distributed gas energy state monitoring method according to claim 1, characterized in that: the specific detailed process in step S6 includes:
the average electric energy utilization efficiency proportional coefficient xi of each distributed gas energy user side i And average residual heat energy utilization efficiency proportional coefficient psi i Substituting into formula phi i ＝λ 1 *ξ i +λ 2 *ψ i Obtaining the comprehensive energy utilization efficiency index phi of each distributed gas energy user side i Wherein λ is 1 And λ 2 Respectively expressed as a preset electric energy utilization efficiency influence weight factor and a preset residual heat energy utilization efficiency influence weight factor;
and comparing the comprehensive energy utilization efficiency index of each distributed gas energy user side with a preset standard energy utilization efficiency index threshold, if the comprehensive energy utilization efficiency index of a certain distributed gas energy user side is smaller than the preset standard energy utilization efficiency index threshold, indicating that the energy utilization efficiency of the distributed gas energy user side is unqualified, and counting the corresponding number of each distributed gas energy user side with unqualified energy utilization efficiency.
8. The neural network-based distributed gas energy state monitoring method according to claim 1, wherein: in the step S7, the comprehensive exhaust emission influence index of each distributed gas energy user side is evaluated, and the specific evaluation mode is as follows:
detecting the exhaust emission concentration of corresponding user sides in each operation time period through exhaust gas detection equipment arranged in exhaust emission ports in each distributed gas energy user side, wherein the exhaust comprises carbon monoxide, carbon dioxide, nitrogen oxide and methane, substituting the exhaust emission concentration of each distributed gas energy user side in each operation time period into an exhaust emission influence index evaluation formula, and obtaining the comprehensive exhaust emission influence index of each distributed gas energy user side
9. The neural network-based distributed gas energy state monitoring method according to claim 1, wherein: in step S8, the comprehensive exhaust emission influence index of each distributed gas energy user side is compared with a preset safe exhaust emission influence index threshold, and the processing is performed according to the comparison result, including:
the comprehensive exhaust emission influence index of each distributed gas energy user side is compared with a preset safe exhaust emission influence index threshold, if the comprehensive exhaust emission influence index of a certain distributed gas energy user side is smaller than or equal to the preset safe exhaust emission influence index threshold, it is indicated that the exhaust emission of the distributed gas energy user side meets the standard, and if the comprehensive exhaust emission influence index of a certain distributed gas energy user side is larger than the preset safe exhaust emission influence index threshold, it is indicated that the exhaust emission of the distributed gas energy user side does not meet the standard, voice early warning reminding is performed.
10. Distributed gas energy state monitoring system based on neural network, its characterized in that includes:
distributed gas energy user side numbering module: the system comprises a community energy management platform, a management center and a management center, wherein the community energy management platform is used for acquiring distributed gas energy user sides in the community energy management platform and numbering the distributed gas energy user sides in the community energy management platform;
the user side gas consumption obtaining module: the system is used for acquiring the gas consumption of each distributed gas energy user side in each operation time period in the community energy management platform and analyzing the heat energy conversion amount of each distributed gas energy user side in each operation time period;
the user side power generation heat energy consumption analysis module: the system comprises a power generation system, a power generation system and a power generation system, wherein the power generation system is used for acquiring electric quantity generated by each distributed gas energy user side in each operation time period and analyzing the power generation heat energy consumption of each distributed gas energy user side in each operation time period;
the user side electric energy utilization efficiency evaluation module: the system comprises a power generation system, a distributed gas energy source client, a power generation system and a power generation system, wherein the power generation system is used for generating power for each distributed gas energy source client;
the user side heat energy and cold energy usage acquisition module: the system is used for acquiring the heat energy usage amount and the cold energy usage amount of each distributed gas energy user side in each operation time period to obtain the average residual heat energy utilization efficiency proportionality coefficient of each distributed gas energy user side;
the comprehensive energy utilization efficiency index analysis module is used for: the comprehensive energy utilization efficiency index analysis system is used for analyzing the comprehensive energy utilization efficiency index of each distributed gas energy user side and screening and counting corresponding numbers of each distributed gas energy user side with unqualified energy utilization efficiency;
the user side exhaust emission influence index evaluation module: the system is used for detecting the exhaust emission concentration of each distributed gas energy user side in each operation time period and evaluating the comprehensive exhaust emission influence index of each distributed gas energy user side;
the community energy management platform analysis processing module: the system is used for comparing the comprehensive exhaust emission influence index of each distributed gas energy user side with a preset safe exhaust emission influence index threshold, processing according to the comparison result, and displaying the corresponding number of each distributed gas energy user side with unqualified energy utilization efficiency;
a gas energy management database: the system is used for storing the standard heat energy conversion rate corresponding to each distributed gas energy user side and the standard heat energy consumption corresponding to the unit electric quantity generated by each distributed gas energy user side.
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