CN115293928A - Microgrid operation optimization and energy efficiency management system - Google Patents
Microgrid operation optimization and energy efficiency management system Download PDFInfo
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- CN115293928A CN115293928A CN202210995094.5A CN202210995094A CN115293928A CN 115293928 A CN115293928 A CN 115293928A CN 202210995094 A CN202210995094 A CN 202210995094A CN 115293928 A CN115293928 A CN 115293928A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/06—Electricity, gas or water supply
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/10—Power transmission or distribution systems management focussing at grid-level, e.g. load flow analysis, node profile computation, meshed network optimisation, active network management or spinning reserve management
Abstract
The invention provides a microgrid operation optimization and energy efficiency management system, which comprises a data acquisition unit, a data storage unit, an electricity utilization matching unit and an electricity utilization adjusting unit, wherein the data acquisition unit is used for acquiring data; the data acquisition unit inputs the acquired electricity consumption into the data storage unit for storage, the electricity matching unit matches the electricity consumption in advance, and the electricity adjusting unit makes optimization adjustment according to the acquired electricity consumption and the electricity consumption in advance; the data acquisition unit comprises an industrial power acquisition module and a household power acquisition module. In the invention, when B0n is less than B1n, the electricity utilization regulating unit marks the house user as an output type house, when B0n = B1n, the electricity utilization regulating unit marks the factory as a balanced type house, and the redundant electricity consumption of the output type house is transmitted to the input type house through the electricity utilization regulating unit to meet the electricity consumption of the output type house, so that the electricity utilization of a microgrid is optimized and managed according to actual conditions to improve the power supply efficiency.
Description
Technical Field
The invention relates to the technical field of power grid management systems, in particular to a micro-grid operation optimization and energy efficiency management system.
Background
With the development of power grid technology and information technology, smart power grid technology becomes an important technology for promoting power grid development and improving user experience. The smart grid is a novel grid formed by highly integrating modern advanced sensing measurement technology, network technology, communication technology, computing technology, automation, intelligent control technology and the like with a physical grid on the basis of the physical grid comprising various power generation equipment, power transmission and distribution networks, electric equipment and energy storage equipment.
Chinese patent application No. 201720411593.X discloses a power grid power supply management system, including master controller, electric energy conversion device and a plurality of voltage sensor, a plurality of voltage sensor with the master controller electricity is connected, voltage sensor can the perception voltage in the electric wire netting to convert electrical signal transmission to the master controller, the master controller judges whether current moment is in power consumption peak period, if be in the power consumption low peak period, then controller control hydrogen and oxygen storage are made through water electrolysis hydrogen manufacturing module to unnecessary electric energy in the electric wire netting to the electric energy conversion device, judge current moment and be in the power consumption peak period when the master controller, and the power supply is not enough in the electric wire netting, the master controller control hydrogen oxygen discharging module reaction among the electric energy conversion device discharges to convey the electric energy to the electric wire netting in, through the master controller is right electric energy conversion device's real time control, reasonable energy storage has improved electric energy utilization.
However, the following problems exist in the technical scheme: the existing power supply can be divided into industrial power consumption and residential power consumption according to categories, and the management system cannot perform intelligent optimized management on the industrial power consumption and the residential power consumption.
Disclosure of Invention
To remedy the deficiencies of the prior art, at least one of the technical problems set forth in the background is addressed.
The technical scheme adopted by the invention for solving the technical problems is as follows: according to the microgrid operation optimization and energy efficiency management system, redundant power consumption of an output type house is transmitted to an input type house through the power consumption adjusting unit so as to meet the power consumption of the input type house, and then power consumption of a microgrid is optimized and managed according to actual conditions, balanced use of electric power is achieved, and power supply efficiency is improved.
In order to achieve the purpose, the invention provides the following technical scheme:
a microgrid operation optimization and energy efficiency management system comprises a data acquisition unit, a data storage unit, an electricity utilization matching unit and an electricity utilization adjusting unit;
the data acquisition unit inputs the acquired electricity consumption into the data storage unit for storage, the electricity matching unit matches the electricity consumption in advance, and the electricity adjusting unit makes optimal adjustment according to the acquired electricity consumption and the electricity consumption in advance;
the data acquisition unit comprises an industrial electricity acquisition module and a household electricity acquisition module, wherein the industrial electricity acquisition module is connected with an electricity meter of each factory and is used for acquiring electricity consumption of each factory; the household electricity consumption acquisition module is connected with an electricity meter of each residential user and used for acquiring the electricity consumption of each residential user.
The industrial electricity collection module is used for marking each factory, electricity consumption of each factory is collected in sequence and marked as A01, A02, A03,. A0n, and total electricity consumption is A0, wherein A0= A01+ A02+ A03. + A0n;
the power utilization matching unit marks each factory, matches the preset power consumption for each factory in sequence and marks the preset power consumption as A11, A12 and A13.. A1n, and the total preset power consumption is A1, wherein A1= A11+ A12+ A13. + A1n;
when A0n < A1n, the electricity utilization regulating unit marks the factory as an output type factory, when A0n > A1n, the electricity utilization regulating unit marks the factory as an input type factory, and when A0n = A1n, the electricity utilization regulating unit marks the factory as a balanced type factory; and the power utilization regulating unit is used for transmitting the redundant power utilization amount of the output type factory to the input type factory for use.
The household electricity collection module marks each residential user, collects electricity consumption of the residential users in sequence and marks the electricity consumption as B01, B02, B03,. B0n, and total electricity consumption is B0, wherein B0= B01+ B02+ B03. + B0n;
the electricity utilization matching unit marks each residential user, matches the electricity utilization quantity for each residential user in sequence and marks the electricity utilization quantity as B11, B12 and B13.. B1n, wherein the total electricity utilization quantity is B1, and B1= B11+ B12+ B13. + B1n;
when B0n < B1n, the electricity usage adjustment unit marks the residential user as an export-type residence, when B0n > B1n, the electricity usage adjustment unit marks the residential user as an import-type residence, when B0n = B1n, the electricity usage adjustment unit marks the residential user as a balance-type residence;
and the electricity utilization adjusting unit transmits the redundant electricity consumption of the output type house to the input type house to meet the electricity consumption of the input type house.
The industrial power utilization acquisition module is used for acquiring power utilization quantity of each factory in time when the industrial power utilization acquisition module fails, so that data are lost; and the data simulation unit calls the data recorded in the data storage unit, and the simulation data corresponding to the missing data is obtained by combining K neighbor algorithm with K electricity consumption data near the recorded data.
The data simulation unit selects N pieces of mark data closest to the missing data, records data from near to far by taking the mark data as a starting point to form a resume, records a minimum value m1 and an average value m2 in the resume data each time, uses a K nearest neighbor algorithm for each missing data for 2 times, and judges whether to carry out an estimation process according to a calculation result, wherein the K takes m1 and m2 respectively.
After the data simulation unit uses the K nearest neighbor algorithm for 2 times on the missing data, the obtained data are the same, and the data are the replacement data, otherwise, the estimation process is carried out;
the data simulation unit carries out an estimation process and comprises the following steps:
carrying out assignment operation on the average value m2 through m2= m2-x, then respectively taking m1 and m2 for K and using a K nearest neighbor algorithm for 2 times, and if the obtained data are consistent, taking the data as replacement data;
if the obtained results are inconsistent, carrying out assignment operation on the minimum value m1 through m1= m1+ y, then respectively taking m1 and m2 for K and using a K nearest neighbor algorithm for 2 times, and if the obtained data are consistent, taking the data as replacement data;
if the obtained data are still inconsistent, repeating the process until the same result is obtained;
wherein x = (m 2-m 1)/N, y = x-1, and x, y are both integers not less than 0.
The data simulation unit adopts a spark R parallelization k-means algorithm, realizes the classification of the power grid data according to the type marks, and matches the corresponding data transmission channel for the power grid data based on the classification result.
The data model building unit averagely divides the historical data stored and recorded in the data storage unit into a plurality of time period data and carries out normalization processing;
the data model building unit calculates a characteristic value distribution function of the historical data, obtains an upper distribution limit function and a lower distribution limit function of the characteristic value distribution function, and builds a limit distribution map about the characteristic value of the historical data.
The data model building unit calculates a characteristic value distribution function of the real-time data collected by the data collecting unit and builds a data distribution map about the characteristic value of the real-time data;
and merging the images of the limit distribution map and the data distribution map according to a unified standard, wherein if the data distribution map is positioned in the limit distribution map, the operation state of the power grid is stable, otherwise, the operation state of the power grid is abnormal.
Still include emergent deposit unit, when A0 is less than A1, the power consumption regulating unit with input type factory unnecessary power consumption carry to store in the emergent deposit unit, when A0 is greater than A1, emergent deposit unit is the power supply of input type factory.
The invention has the following beneficial effects:
1. according to the invention, when B0n is less than B1n, the electricity utilization regulating unit marks the residential user as an output type residential building, when B0n is greater than B1n, the electricity utilization regulating unit marks the residential user as an input type residential building, when B0n = B1n, the electricity utilization regulating unit marks the factory as a balance type residential building, redundant electricity consumption of the output type residential building is transmitted to the input type residential building through the electricity utilization regulating unit to meet the electricity consumption, further, the electricity utilization of a micro-grid is optimally managed according to actual conditions, the balanced use of the electricity is realized, and the power supply efficiency is improved.
2. In the invention, a characteristic value distribution function of real-time data acquired by a data acquisition unit is calculated by a data model construction unit, and a data distribution map about the characteristic value of the real-time data is established; and merging the images of the limit distribution map and the data distribution map according to a unified standard, wherein if the data distribution map is positioned in the limit distribution map, the running state of the power grid is stable, otherwise, the running state of the power grid is abnormal, and further the running state of the power grid can be monitored.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without inventive exercise.
The invention will be further explained with reference to the drawings.
FIG. 1 is a block diagram of a management system according to the present invention;
FIG. 2 is a block diagram of a data acquisition unit according to the present invention.
Detailed Description
In order to make the technical means, the creation characteristics, the achievement purposes and the effects of the invention easy to understand, the invention is further described with the specific embodiments. It is to be understood that the described embodiments are merely exemplary of the invention, and not restrictive of the full scope of the invention. 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.
The first embodiment is as follows:
as shown in fig. 1 and fig. 2, the present embodiment provides a microgrid operation optimization and energy efficiency management system, which includes a data acquisition unit, a data storage unit, an electricity utilization matching unit, and an electricity utilization adjusting unit; the data acquisition unit inputs the acquired electricity consumption into the data storage unit for storage, the electricity matching unit matches the pre-used electricity consumption, and the electricity adjusting unit makes optimization adjustment according to the acquired electricity consumption and the pre-used electricity consumption; the data acquisition unit comprises an industrial electricity acquisition module and a household electricity acquisition module, wherein the industrial electricity acquisition module is connected with an electricity meter of each factory and is used for acquiring the electricity consumption of each factory; the household electricity consumption acquisition module is connected with an electricity meter of each residential user and used for acquiring the electricity consumption of each residential user.
In this embodiment, the industrial electricity collection module marks each factory, sequentially collects electricity consumption of each factory and marks the electricity consumption as a01, a02, a03,. A0n, and the total electricity consumption is A0, where A0= a01+ a02+ a03. + A0n;
marking each factory by using an electricity matching unit, matching the electricity consumption in turn and marking the electricity consumption as A11, A12, A13,. A1n, wherein the total electricity consumption is A1, and A1= A11+ A12+ A13. + A1n;
when A0n < A1n, the electricity utilization regulating unit marks the factory as an output type factory, when A0n > A1n, the electricity utilization regulating unit marks the factory as an input type factory, and when A0n = A1n, the electricity utilization regulating unit marks the factory as a balanced type factory; and the electricity utilization regulating unit is used for transmitting the redundant electricity consumption of the output type factory to the input type factory for use.
The household electricity consumption acquisition module marks each residential user, acquires electricity consumption of the residential users in sequence and marks the electricity consumption as B01, B02, B03.. B0n, and the total electricity consumption is B0, wherein B0= B01+ B02+ B03. + B0n;
marking each residential user by an electricity matching unit, matching the electricity consumption of each residential user in sequence and marking the residential user as B11, B12 and B13,. B1n, wherein the total electricity consumption is B1, and B1= B11+ B12+ B13.. + B1n;
when B0n < B1n, the electricity consumption adjusting unit marks the residential user as an output type residential building, when B0n > B1n, the electricity consumption adjusting unit marks the residential user as an input type residential building, and when B0n = B1n, the electricity consumption adjusting unit marks the factory as a balance type residential building;
the electricity utilization regulating unit transmits the redundant electricity consumption of the output type house to the input type house to meet the electricity consumption of the input type house.
Example two:
as shown in fig. 1, in which the same or corresponding components as in the first embodiment are denoted by the same reference numerals as in the first embodiment, only the points of difference from the first embodiment will be described below for the sake of convenience. The second embodiment is different from the first embodiment in that:
the embodiment also comprises a data simulation unit, wherein when the industrial power acquisition module fails to acquire the power consumption of each factory in time, the data is lost; and the data simulation unit calls out the data recorded in the data storage unit, and the simulation data corresponding to the missing data is obtained by combining K electricity consumption data near the recorded data through a K neighbor algorithm.
The data simulation unit selects N pieces of mark data closest to the missing data, records data from near to far by taking the mark data as a starting point to form a resume, records a minimum value m1 and an average value m2 in the resume data each time, uses a K nearest neighbor algorithm for each missing data for 2 times, and judges whether to carry out an estimation process according to a calculation result, wherein the K takes m1 and m2 respectively.
After the data simulation unit uses the K nearest neighbor algorithm for 2 times on the missing data, the obtained data are the same, and the data are the replacement data, otherwise, the estimation process is carried out;
the data simulation unit carries out an estimation process and comprises the following steps:
carrying out assignment operation on the average value m2 through m2= m2-x, then respectively taking m1 and m2 for K and using a K nearest neighbor algorithm for 2 times, and if the obtained data are consistent, taking the data as replacement data;
if the obtained results are inconsistent, carrying out assignment operation on the minimum value m1 through m1= m1+ y, then respectively taking m1 and m2 for K and using a K nearest neighbor algorithm for 2 times, and if the obtained data are consistent, taking the data as replacement data;
if the obtained data are still inconsistent, repeating the process until the same result is obtained;
wherein x = (m 2-m 1)/N, y = x-1, and x and y are integers not less than 0.
The data simulation unit adopts a spark R parallelization k-means algorithm, realizes the classification of the power grid data according to the type marks, and matches the corresponding data transmission channel for the power grid data based on the classification result.
The data model building unit averagely divides historical data recorded in the data storage unit into a plurality of time period data and carries out normalization processing;
the data model building unit calculates a characteristic value distribution function of the historical data, obtains an upper distribution limit function and a lower distribution limit function of the characteristic value distribution function, and builds a limit distribution diagram related to the characteristic value of the historical data.
The data model building unit calculates a characteristic value distribution function of the real-time data collected by the data collecting unit and builds a data distribution map about the characteristic value of the real-time data;
and merging the images of the limit distribution map and the data distribution map according to a unified standard, wherein if the data distribution map is positioned in the limit distribution map, the operation state of the power grid is stable, otherwise, the operation state of the power grid is abnormal.
The embodiment further comprises an emergency storage unit, when A0 is smaller than A1, the power utilization adjusting unit transmits the redundant power consumption of the input type factory to the emergency storage unit for storage, and when A0 is larger than A1, the emergency storage unit supplies power to the input type factory.
The foregoing illustrates and describes the principles, general features, and advantages of the present invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are given by way of illustration of the principles of the present invention, and that various changes and modifications may be made without departing from the spirit and scope of the invention as defined by the appended claims. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (10)
1. A microgrid operation optimization and energy efficiency management system is characterized by comprising a data acquisition unit, a data storage unit, an electricity utilization matching unit and an electricity utilization adjusting unit;
the data acquisition unit inputs the acquired electricity consumption into the data storage unit for storage, the electricity matching unit matches the electricity consumption in advance, and the electricity adjusting unit makes optimization adjustment according to the acquired electricity consumption and the electricity consumption in advance;
the data acquisition unit comprises an industrial electricity acquisition module and a household electricity acquisition module, wherein the industrial electricity acquisition module is connected with an electricity meter of each factory and is used for acquiring electricity consumption of each factory; the household electricity collection module is connected with an electricity meter of each residential user and used for collecting electricity consumption of each residential user.
2. The microgrid operation optimization and energy efficiency management system of claim 1, characterized in that the industrial electricity collection module marks each factory and collects electricity consumption thereof in sequence and marks the electricity consumption as a01, a02, a03.. A0n, and the total electricity consumption is A0, wherein A0= a01+ a02+ a03. + A0n;
the power utilization matching unit marks each factory, matches the preset power consumption for each factory in sequence and marks the preset power consumption as A11, A12 and A13.. A1n, and the total preset power consumption is A1, wherein A1= A11+ A12+ A13. + A1n;
when A0n < A1n, the electricity utilization regulating unit marks the factory as an output type factory, when A0n > A1n, the electricity utilization regulating unit marks the factory as an input type factory, and when A0n = A1n, the electricity utilization regulating unit marks the factory as a balanced type factory; and the electricity utilization regulating unit is used for transmitting the redundant electricity consumption of the output type factory to the input type factory for use.
3. The microgrid operation optimization and energy efficiency management system according to claim 2, characterized in that the household electricity collection module marks each residential user, collects electricity consumption thereof in sequence and marks the electricity consumption as B01, B02, B03.. B0n, and if the total electricity consumption is B0, then B0= B01+ B02+ B03.. B.0 n;
the electricity utilization matching unit marks each residential user, matches the electricity utilization quantity for each residential user in sequence and marks the electricity utilization quantity as B11, B12 and B13,. B1n, and if the total electricity utilization quantity is B1, B1= B11+ B12+ B13.. + B1n;
when B0n < B1n, the electricity usage adjustment unit marks the residential user as an export-type residence, when B0n > B1n, the electricity usage adjustment unit marks the residential user as an import-type residence, when B0n = B1n, the electricity usage adjustment unit marks the residential user as a balance-type residence;
and the electricity utilization adjusting unit transmits the redundant electricity consumption of the output type house to the input type house to meet the electricity consumption of the input type house.
4. The microgrid operation optimization and energy efficiency management system of claim 3, characterized by further comprising a data simulation unit, when the industrial power utilization acquisition module fails to timely acquire the power utilization of each factory, resulting in data loss; and the data simulation unit calls the data recorded in the data storage unit, and the simulation data corresponding to the missing data is obtained by combining K neighbor algorithm with K electricity consumption data near the recorded data.
5. The microgrid operation optimization and energy efficiency management system according to claim 4, characterized in that the data simulation unit selects N pieces of mark data closest to missing data, records data from near to far with the mark data as a starting point to form a resume, records a minimum value m1 and an average value m2 in each resume data, uses a K nearest neighbor algorithm for each missing data for 2 times, and K respectively takes m1 and m2 and judges whether to perform an estimation process according to a calculation result.
6. The microgrid operation optimization and energy efficiency management system according to claim 5, characterized in that after the data simulation unit uses the K nearest neighbor algorithm for 2 times on missing data, the obtained data are the same, and if not, the data are replaced, and if not, an estimation process is performed;
the data simulation unit carries out the estimation process as follows:
carrying out assignment operation on the average value m2 through m2= m2-x, then respectively taking m1 and m2 for K, and using a 2-time K neighbor algorithm, wherein if the obtained data are consistent, the data are replacement data;
if the obtained results are inconsistent, carrying out assignment operation on the minimum value m1 through m1= m1+ y, then respectively taking m1 and m2 for K and using a K nearest neighbor algorithm for 2 times, and if the obtained data are consistent, taking the data as replacement data;
if the obtained data are still inconsistent, repeating the process until the same result is obtained; wherein x = (m 2-m 1)/N, y = x-1, and x, y are both integers not less than 0.
7. The microgrid operation optimization and energy efficiency management system according to claim 6, characterized in that the data simulation unit adopts a parallelization k-means algorithm of SparkR, realizes classification of grid data according to type labels, and matches the corresponding data transmission channels for the grid data based on the classification result.
8. The microgrid operation optimization and energy efficiency management system of claim 7, characterized by further comprising a data model construction unit, wherein the data model construction unit averagely divides historical data stored and recorded in the data storage unit into a plurality of time period data and performs normalization processing;
the data model building unit calculates a characteristic value distribution function of the historical data, obtains an upper distribution limit function and a lower distribution limit function of the characteristic value distribution function, and builds a limit distribution map about the characteristic value of the historical data.
9. The microgrid operation optimization and energy efficiency management system of claim 8, wherein the data model building unit calculates a characteristic value distribution function of the real-time data collected by the data collection unit and builds a data distribution map about the characteristic values of the real-time data;
and image merging is carried out on the limit distribution map and the data distribution map according to a unified standard, if the data distribution map is positioned in the limit distribution map, the running state of the power grid is stable, otherwise, the running state of the power grid is abnormal.
10. The microgrid operation optimization and energy efficiency management system of claim 9, further comprising an emergency reserve unit, wherein when A0 is smaller than A1, the power utilization regulating unit transmits excess power utilization of the input type factory to the emergency reserve unit for storage, and when A0 is larger than A1, the emergency reserve unit supplies power to the input type factory.
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