CN114492997B - Multi-station fusion comprehensive energy station carbon flow state potential sensing and low-carbon operation method - Google Patents
Multi-station fusion comprehensive energy station carbon flow state potential sensing and low-carbon operation method Download PDFInfo
- Publication number
- CN114492997B CN114492997B CN202210093595.4A CN202210093595A CN114492997B CN 114492997 B CN114492997 B CN 114492997B CN 202210093595 A CN202210093595 A CN 202210093595A CN 114492997 B CN114492997 B CN 114492997B
- Authority
- CN
- China
- Prior art keywords
- station
- carbon
- energy
- comprehensive energy
- flow
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 229910052799 carbon Inorganic materials 0.000 title claims abstract description 115
- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 title claims abstract description 80
- 238000000034 method Methods 0.000 title claims abstract description 18
- 230000004927 fusion Effects 0.000 title claims abstract description 17
- 238000010248 power generation Methods 0.000 claims abstract description 14
- 238000010276 construction Methods 0.000 claims abstract description 9
- 238000004146 energy storage Methods 0.000 claims description 32
- 238000010586 diagram Methods 0.000 claims description 9
- 238000005457 optimization Methods 0.000 claims description 9
- 238000005265 energy consumption Methods 0.000 claims description 7
- 238000013461 design Methods 0.000 claims description 5
- 238000007599 discharging Methods 0.000 claims description 5
- 238000004364 calculation method Methods 0.000 claims description 4
- 238000007689 inspection Methods 0.000 claims description 3
- 238000010521 absorption reaction Methods 0.000 claims description 2
- 238000004378 air conditioning Methods 0.000 claims description 2
- 238000010438 heat treatment Methods 0.000 claims description 2
- 238000009423 ventilation Methods 0.000 claims description 2
- GELKBWJHTRAYNV-UHFFFAOYSA-K lithium iron phosphate Chemical compound [Li+].[Fe+2].[O-]P([O-])([O-])=O GELKBWJHTRAYNV-UHFFFAOYSA-K 0.000 claims 1
- 238000013439 planning Methods 0.000 abstract description 4
- 230000009467 reduction Effects 0.000 description 7
- 238000011161 development Methods 0.000 description 5
- 238000004891 communication Methods 0.000 description 4
- 238000009826 distribution Methods 0.000 description 4
- 230000008569 process Effects 0.000 description 4
- 238000011160 research Methods 0.000 description 4
- 238000004458 analytical method Methods 0.000 description 3
- 238000004134 energy conservation Methods 0.000 description 3
- 238000012423 maintenance Methods 0.000 description 3
- 230000008901 benefit Effects 0.000 description 2
- 239000003990 capacitor Substances 0.000 description 2
- 239000003086 colorant Substances 0.000 description 2
- 238000007405 data analysis Methods 0.000 description 2
- 238000013480 data collection Methods 0.000 description 2
- 230000005611 electricity Effects 0.000 description 2
- 230000006870 function Effects 0.000 description 2
- 238000005286 illumination Methods 0.000 description 2
- 229910001386 lithium phosphate Inorganic materials 0.000 description 2
- 230000001105 regulatory effect Effects 0.000 description 2
- TWQULNDIKKJZPH-UHFFFAOYSA-K trilithium;phosphate Chemical compound [Li+].[Li+].[Li+].[O-]P([O-])([O-])=O TWQULNDIKKJZPH-UHFFFAOYSA-K 0.000 description 2
- 238000011144 upstream manufacturing Methods 0.000 description 2
- 238000013084 building-integrated photovoltaic technology Methods 0.000 description 1
- 239000003245 coal Substances 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000005243 fluidization Methods 0.000 description 1
- 239000005431 greenhouse gas Substances 0.000 description 1
- 229910052751 metal Inorganic materials 0.000 description 1
- 239000002184 metal Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 229910021421 monocrystalline silicon Inorganic materials 0.000 description 1
- 238000006386 neutralization reaction Methods 0.000 description 1
- 230000008447 perception Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
Classifications
-
- 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
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
-
- 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
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06312—Adjustment or analysis of established resource schedule, e.g. resource or task levelling, or dynamic rescheduling
-
- 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
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06313—Resource planning in a project environment
-
- 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—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/06—Energy or water supply
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2111/00—Details relating to CAD techniques
- G06F2111/04—Constraint-based CAD
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2113/00—Details relating to the application field
- G06F2113/04—Power grid distribution networks
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E40/00—Technologies for an efficient electrical power generation, transmission or distribution
- Y02E40/70—Smart grids as climate change mitigation technology in the energy generation sector
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
Landscapes
- Business, Economics & Management (AREA)
- Engineering & Computer Science (AREA)
- Human Resources & Organizations (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Entrepreneurship & Innovation (AREA)
- General Business, Economics & Management (AREA)
- Tourism & Hospitality (AREA)
- Marketing (AREA)
- Development Economics (AREA)
- Quality & Reliability (AREA)
- Game Theory and Decision Science (AREA)
- Operations Research (AREA)
- Educational Administration (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Charge And Discharge Circuits For Batteries Or The Like (AREA)
- Public Health (AREA)
- Computer Hardware Design (AREA)
- Evolutionary Computation (AREA)
- Geometry (AREA)
- General Engineering & Computer Science (AREA)
- Primary Health Care (AREA)
- Biodiversity & Conservation Biology (AREA)
- Water Supply & Treatment (AREA)
Abstract
The invention discloses a multi-station fusion comprehensive energy station carbon flow state potential sensing and low-carbon operation method, and belongs to the technical field of electric power energy. Firstly, determining a main body structure, capacity configuration, arrangement form and wiring mode of a comprehensive energy station based on the principles of maximum utilization and most efficient construction and function positioning; then drawing an energy flow-carbon flow graph, and tracking a carbon source and perceiving a carbon flow situation; and analyzing energy flow and carbon flow information aiming at the load capacity and photovoltaic power generation characteristics of various facilities of the comprehensive energy station to obtain main factors influencing carbon emission, and constructing a low-carbon optimized operation model. The invention realizes the real-time sensing and low-carbon operation of the carbon flow state potential of the comprehensive energy station, intuitively displays the energy structure, the energy flow direction and the carbon flow information of the comprehensive energy station, and provides an energy-saving and emission-reducing strategy for the operation of the existing comprehensive energy station and the planning of the comprehensive energy station to be built.
Description
Technical Field
The invention provides a multi-station fusion comprehensive energy station carbon flow state potential sensing and low-carbon operation method, and belongs to the technical field of electric power energy.
Background
In the process of achieving the peak of carbon and the aim of carbon neutralization, the energy industry plays an important role and plays a role in national energy supply and low-carbon transformation. Development of low-carbon power is a necessary way to achieve the goal of reducing carbon in the power industry. The comprehensive energy station is taken as a national strategic emerging industry, is an important development direction of comprehensive energy service, is also an active attempt for the electric power industry to seek to achieve a double-carbon target, and the national energy bureau in 2020 brings the comprehensive energy service into national energy planning to encourage active exploration of multi-station fusion and multi-station integrated comprehensive integral station construction. The analysis of the total energy consumption and the greenhouse gas emission in the operation process of the comprehensive energy station can provide support for analyzing key factors affecting the energy efficiency and emission reduction of the comprehensive energy station.
At present, most of carbon fluidization potential sensing researches are on macroscopic level such as countries, cities and industrial parks, primary energy sources of a microscopic multi-station integrated comprehensive energy station, energy flows of transformers and various terminal equipment and carbon emission flow monitoring researches are lacked, and therefore energy efficiency of the comprehensive energy station cannot be effectively analyzed, and key factors for emission reduction are extracted.
Disclosure of Invention
The invention provides a multi-station fusion comprehensive energy station carbon flow state potential sensing and low-carbon operation method, which can effectively solve the key problems in the background technology.
In order to achieve the above purpose, the present invention adopts the following technical scheme:
a multi-station fusion comprehensive energy station carbon flow state potential sensing and low-carbon operation method comprises the following steps:
Step one: determining a main body structure, capacity configuration, arrangement form and wiring mode of each main body based on the principle of 'maximum utilization and most efficient construction' and the functional positioning of the comprehensive energy station;
Step two: collecting actual operation data and carbon emission intensity factor statistics of the comprehensive energy station, calculating to obtain energy types, tide directions and carbon emission directions in each period, and drawing an energy flow-carbon flow diagram so as to sense carbon flow situations in the comprehensive energy station in real time;
Step three: aiming at the load capacity and photovoltaic power generation characteristics of various facilities of the comprehensive energy station, a daily scheduling operation optimization model of the comprehensive energy station is constructed, and the charge and discharge time of the energy storage module is adjusted according to photovoltaic output prediction and in-station load power prediction so as to ensure the maximum absorption of the output of the photovoltaic module in the station and realize low-carbon operation of the comprehensive energy station.
As a further preferred scheme, in the first step, the multi-station fusion comprehensive energy station may include a photovoltaic module, a charging module, an energy storage module, a data center module, a 5G module, a super capacitor module, and the like, according to the functional positioning of the comprehensive energy station. The photovoltaic module mainly adopts roof photovoltaic; if a metal roof is adopted, BIPV integrated components are adopted for the new station, and the new station is built in the same period as the engineering of the transformer substation body; when the old station is transformed/the building under other conditions is a concrete roof, the traditional monocrystalline silicon photovoltaic panel can be adopted, and the maintenance operation and maintenance requirements are fully considered. If the illumination conditions around the site are extremely poor, the photovoltaic module can be canceled after illumination analysis thematic demonstration is carried out. The charging module mainly adopts an integrated charging pile for charging and using the operation, maintenance and overhaul vehicles in the system. The super capacitor and the energy storage module are combined with power grid planning and data center configuration condition selection, the construction scale is definitely established, and the access system is designed according to actual conditions. The 5G communication tower and the data center take the service provider requirement as main design input. The comprehensive energy stations with different function types are adjusted, spliced and freely combined according to the modules, all matched comprehensive energy facilities adopt a modularized arrangement form, the arrangement form and the body structure of the transformer substation are not required to be changed, and the comprehensive energy stations can be freely matched according to requirements.
The main body structure of the typical comprehensive energy station comprises a 110kV transformer substation body module, a photovoltaic module, a charging module, a configuration energy storage module, a data center module and a 5G base station module.
As a further preferable scheme, in the first step, the capacity configuration, arrangement form and wiring mode of each main body of the comprehensive energy station are as follows: based on a 110kV intelligent substation modularized construction general design 110-A2-6 scheme, a substation module comprises a 110kV/10-35kV main transformer and a box-type transformer, and a 380V indoor power station transformer; the photovoltaic module adopts a roof photovoltaic array arranged on the roof of the main building and the charging parking space; the load in the station comprises lighting, heating ventilation, air conditioning load and the like; the charging module adopts integrated direct current quick charging and is mainly used for vehicle inspection operation in the comprehensive energy station; the energy storage module adopts a prefabricated box type lithium phosphate battery, and can provide power reserve for a data center and a 5G base station; the 5G module selects a 45m pole tower which is arranged on one side close to the wall; the data center module integrates an IT equipment warehouse and an air conditioner outdoor machine room in the container and is arranged on one side of the enclosing wall.
As a further preferred scheme, in the second step, the carbon flow density is defined as the unit of active power flow P and the unit of kgCO 2/kWh of carbon emission; the carbon flow of the comprehensive energy station at a certain moment can be characterized by the density of the carbon flow, and the calculation formula is as follows:
Where F is the carbon emission for a given time from 0 to T for a device or branch and ρ is the carbon flow density.
Drawing a real-time energy flow-carbon flow diagram of a multi-station fusion comprehensive energy station based on carbon flow density, wherein the method comprises the following steps of:
1) Collecting data; the actual operation data of the comprehensive energy station comprises load data in the station, downstream load data, solar irradiance, ambient temperature, electric vehicle charging power data, energy storage module charging and discharging power data and the like; clean energy power generation duty ratio of the comprehensive energy station; a carbon emission intensity factor;
2) Analyzing data; carrying out statistical calculation on the corresponding data to obtain the energy type, the tide direction, the carbon emission flow direction and the total daily carbon emission amount of the comprehensive energy station in each period;
3) Drawing a graph; considering the source and destination of the energy type, energy source or carbon stream, including primary energy, secondary energy, direct use primary energy and various energy consuming terminals; representing the flow direction and the size of the energy flow or carbon flow data by connecting lines between each object; according to energy consumption of terminals power or carbon emissions ratio of quantities to plot the width of the connecting line.
In the third step, aiming at the load capacity and photovoltaic power generation characteristics of various facilities of the comprehensive energy station, a daily scheduling optimization operation model of the comprehensive energy station is constructed, and the charge and discharge time of the energy storage module is adjusted according to photovoltaic output prediction and in-station load power prediction so as to ensure the maximum consumption of the output of the photovoltaic module in the station, and low-carbon operation of the comprehensive energy station is realized. The constructed optimized operation model is as follows:
objective function:
Constraint conditions:
Wherein t is the time period considered by day-ahead optimization operation, A PV is the area of a photovoltaic panel, eta PV is the photovoltaic power generation efficiency, I (t) is the predicted solar irradiation intensity, A PVηPV I (t) is the upper limit of the exportable electric power of the photovoltaic power station, E PV (t) is the electric power actually output by the photovoltaic power station, P eload (t) is the electric power predicted value of load consumption in the station, E batc (t) is the electric power charged into a battery at the moment t, E batd (t) is the electric power released by the battery at the moment t, E bat (t) is the residual capacity of the battery at the moment t, E bat (t-1) is the residual capacity of the battery at the moment t-1, eta batc is the charging efficiency of the battery, and eta batd is the release efficiency of the battery.
The built model aims at absorbing the photovoltaic output of the comprehensive energy station, and when the photovoltaic output is larger than the load in the station such as 5G, a data center and the like, the energy storage module starts to charge; otherwise, the energy storage module stops charging. And (3) optimizing an operation plan in the future, and adjusting the charge and discharge time of the energy storage module according to the photovoltaic output prediction and the in-station load power prediction under the condition of meeting the constraints of the energy storage module and the photovoltaic module, so as to realize the low-carbon operation of the comprehensive energy station.
Advantageous effects
The comprehensive energy station is used as a national strategic emerging industry category, belongs to an application scene of the comprehensive energy service, and is also an important development direction of the comprehensive energy service. The development of comprehensive energy station carbon flow state potential sensing and carpet operation research has important guiding significance for low-carbon development of propulsion energy and clean energy consumption and exploration of reasonable emission reduction ways. The invention provides a carbon flow state potential sensing and low-carbon operation method for a multi-station integrated comprehensive energy station, which effectively improves the energy flow and carbon emission flow state potential sensing capability of primary energy, transformers and various terminal devices of the multi-station integrated comprehensive energy station and provides support for effectively analyzing the energy efficiency of the comprehensive energy station and extracting and reducing emission key factors. The application of the invention can greatly improve the scale and the operation efficiency of the comprehensive energy station and obviously reduce the related carbon emission. The invention can bring remarkable economic and social benefit benefits for comprehensive energy service enterprises, power grid operation enterprises and power grid operation scientific research institutions.
Drawings
In order that the invention may be more readily understood, a more particular description of the invention will be rendered by reference to specific embodiments that are illustrated in the appended drawings, in which:
FIG. 1 is a diagram of a multi-station fusion comprehensive energy station structure layout and energy relation;
FIG. 2 multiple station fusion comprehensive energy station energy flow-carbon flow sensing analysis and graph drawing;
FIG. 3 is a multi-station fusion comprehensive energy real-time energy flow state potential diagram;
FIG. 4 is a graph of the real-time carbon flow pattern potential of a multi-station fusion comprehensive energy station;
fig. 5 is an all-day carbon emission map (with and without photovoltaic modules) for an optimized energy storage mode of operation.
Detailed Description
The invention is further described below with reference to the accompanying drawings. The following examples are only for more clearly illustrating the technical aspects of the present invention, and are not intended to limit the scope of the present invention.
Step 1: the main structure of the typical comprehensive energy station is determined by adopting the principle of 'maximum utilization and most efficient construction' and the functional positioning of the comprehensive energy station, and the main structure consists of an existing 110kV transformer substation module, a photovoltaic module, a charging module, an energy storage module, a data center module and a 5G communication tower module.
The main transformer of the comprehensive energy station continuously supplies power to the downstream 10-35kV power distribution network user load. Losses occur when the main transformer supplies power. In addition to the load in the integrated energy station, the station transformer also needs to supply power to the integrated direct current charger of the charging module. Under normal conditions, the charging module charges the electric automobile at night, and the rest of the charging module does not work. The photovoltaic module provides active power when sunlight is sufficient and preferentially provides active power for 5G and data centers. When there is a surplus, the energy storage module is charged from the photovoltaic module. If there are surplus, the photovoltaic module will supply power to the downstream loads of the integrated energy station. The energy storage module provides peak-to-valley shifting service for the charging station, the 5G module and the data center by using peak-to-valley electricity price, and peak regulation is considered to be required to be carried out in the early morning with lower load of the power distribution network or in the noon with stronger photovoltaic power, and discharging is carried out in the late peak electricity utilization. Since the energy storage module is used for 5G and backup of the data center module, the charge and discharge capacity is 50% of the rated capacity. The 5G module and the data center module are in a working state all the day, and uninterrupted power supply is required all the day.
The substation module generally comprises a 110kV/10-35kV main transformer and a box-type transformer, and a 380V indoor power station transformer. The photovoltaic module adopts a roof photovoltaic array arranged on the roof of the main building and the charging parking space. The charging module adopts an integrated direct current charger and is mainly used for comprehensive energy station operation vehicle inspection. The energy storage module adopts a prefabricated box type lithium phosphate battery, and can provide power reserve for a data center and a 5G base station. The 5G module selects a 45m pole tower which is arranged on one side close to the wall. The data center module integrates an IT equipment warehouse and an air conditioner outdoor machine room in the container and is arranged on one side of the enclosing wall. An overall frame diagram of the integrated energy station is shown in fig. 1.
Considering the roof area of a traditional 110kV transformer substation, the capacity of the photovoltaic module is set to 120kW. The integrated direct-current charger of the charging module is 60kW, and 35% -100% of the charging module is charged each time. The standard capacity of the energy storage module is 1000kWh, with 500kWh being the backup capacity of the 5G and data center. Due to the battery self-discharge phenomenon, the battery self-discharge loss is completely determined by the upstream grid, the supplementary energy storage module is discharged from the charging during the standby period when the supplementary energy storage module is still fully charged, and the discharging waiting charging is completed during the standby period when 50% of rated capacity is maintained. The average power of the data center was maintained at 100kW, while the average power of the 5G communication tower was 3kW.
Step 2: and (3) collecting and arranging typical comprehensive energy station data based on the layout structure and capacity configuration obtained in the step (1), and drawing an energy flow-carbon flow diagram.
The carbon emission intensity of the electric energy transmitted from the upstream to the downstream power distribution network through the comprehensive energy station is estimated from the proportion of the renewable energy power generation amount in Jiangsu province from 1 in 2021 to 9 in 2021. The carbon emission intensity of renewable energy power generation is 0. Except for renewable energy power generation, all resources are assumed to be coal power generation, and the carbon emission intensity is 0.85kgCO 2/kWh.
Selecting a certain moment of a certain operation day, establishing an energy flow-carbon flow model of the comprehensive energy station, calculating the carbon emission of each device, and drawing an energy flow-carbon flow diagram of the comprehensive energy station, wherein the specific steps are as follows:
1) And (5) data collection. Collecting actual operation data, power consumption data of various energy consumption terminals and the proportional relation between different types of energy and carbon emission, wherein the data comprise actual load data in a station and distribution network load for calculating the load loss of a transformer; solar irradiance and ambient temperature, which are used for active power output calculation of the photovoltaic module; charging power data of the electric automobile, charging and discharging power data of the energy storage module, coal-electricity carbon emission intensity and the like.
2) And (5) data analysis. The collected data is classified, counted and analyzed. According to the application purpose of the energy flow-carbon flow graph, three aspects of primary energy, secondary energy or directly utilized primary energy, transformers and various terminal consumption are reasonably classified, corresponding data are calculated in a statistics mode, and finally estimated values of the energy types, the power flow directions, the carbon emission flow directions of all time sections and the total carbon emission amount of the all-day comprehensive energy station are obtained, so that data support is provided for drawing the energy flow graph and the carbon flow graph.
3) And (5) drawing a graph. And drawing an energy flow chart and a carbon flow chart of the comprehensive energy station according to the data obtained in the two links, as shown in fig. 3 and 4. Only considering the source and the destination of energy types, energy flows or carbon flows in the drawing process, wherein the drawing process comprises three level objects of primary energy, secondary energy, directly utilized primary energy and various energy consumption terminals, the connecting lines among the objects represent the flow direction and the size of energy flow or carbon flow data, the width of the connecting lines is drawn according to the ratio of the power or carbon emission of the energy consumption terminal pointed by each connecting line to the total power or the total carbon emission of the time interval, and the data size is represented by the different widths of the connecting lines, so that the energy flows and the carbon flows are all from left to right. Different sources of energy are represented in different colors in the energy flow graph, and different directions of the carbon flow are represented in different colors in the carbon flow graph.
Step 3: aiming at the load capacity and photovoltaic power generation characteristics of various facilities of the comprehensive energy station, a daily scheduling optimization operation model of the comprehensive energy station is constructed so as to ensure the maximum consumption of the photovoltaic module output in the station and realize the low-carbon operation of the comprehensive energy station. The built model aims at absorbing the photovoltaic output of the comprehensive energy station, and when the photovoltaic output is larger than the load in the station such as 5G, a data center and the like, the energy storage module starts to charge; otherwise, the energy storage module stops charging. In the day-ahead optimization operation plan, the charge and discharge time of the energy storage module is regulated according to the photovoltaic output prediction and the in-station load power prediction under the condition that the constraints of the energy storage module and the photovoltaic module are met, so that the low-carbon operation of the comprehensive energy station is realized.
Examples:
The 2021 year 2 month 11 days with stronger solar irradiance are selected. Photovoltaic output forecast and load forecast data were collected at 00:00am-23:55pm every 15 minutes. At 11 am, the photovoltaic output meets the load in the station, and the 5G communication station and the data center module run at full load. At this time, the photovoltaic output remains and the energy storage module enters a charging mode. And according to the photovoltaic output and all the in-station load predictions, the charge and discharge time of the energy storage module is regulated, the operation mode of the energy storage module is optimized, and the total daily carbon emission of the comprehensive energy station is 2915.67kg. In contrast, the carbon emissions were reduced by 23.13% when the photovoltaic was not operating. The carbon emission profile versus graph is shown in fig. 5.
The invention realizes the perception of the carbon flow state potential of the comprehensive energy station by data collection, data analysis and graph drawing aiming at the energy source, the energy type, the energy direction, the carbon emission flow and the carbon emission amount of the comprehensive energy station based on the energy flow-carbon flow theory; aiming at the requirements of energy conservation and emission reduction under the double-carbon target, the low-carbon operation of the comprehensive energy station is realized. Obviously, the invention can provide basic design scheme and operation guidance of the 110kV comprehensive energy station, analyze the total carbon emission of the comprehensive energy station aiming at the comprehensive energy station emission reduction target, provide strategies for energy conservation and emission reduction of the existing comprehensive energy station, and provide suggestions for energy conservation and emission reduction of future comprehensive energy station planning, design, construction and operation.
The foregoing is only a preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art, who is within the scope of the present invention, should make equivalent substitutions or modifications according to the technical scheme of the present invention and the inventive concept thereof, and should be covered by the scope of the present invention.
Claims (3)
1. A multi-station fusion comprehensive energy station carbon flow state potential sensing and low-carbon operation method is characterized in that: comprising the following steps:
Step one: determining a main body structure, capacity configuration, arrangement form and wiring mode of each main body based on the principle of 'maximum utilization and most efficient construction' and the functional positioning of the comprehensive energy station;
Step two: collecting actual operation data and carbon emission intensity factor statistics of the comprehensive energy station, calculating to obtain energy types, tide directions and carbon emission directions in each period, and drawing an energy flow-carbon flow diagram so as to sense carbon flow situations in the comprehensive energy station in real time;
In the second step, defining the carbon flow density as the unit active power flow P and the carbon emission of unit kgCO 2/kWh; the carbon flow of the comprehensive energy station at a certain moment is characterized by the density of the carbon flow; drawing a real-time energy flow-carbon flow diagram of a multi-station fusion comprehensive energy station based on carbon flow density, wherein the method comprises the following steps of:
1) Collecting data; the actual operation data of the comprehensive energy station is collected and comprises load data in the station, downstream load data, solar irradiance, ambient temperature, electric vehicle charging power data, energy storage module charging and discharging power data, clean energy power generation occupation ratio of the comprehensive energy station and carbon emission intensity factors;
2) Analyzing data; carrying out statistical calculation on the corresponding data to obtain the energy type, the tide direction, the carbon emission flow direction and the total daily carbon emission amount of the comprehensive energy station in each period;
3) Drawing a graph; considering the source and destination of the energy type, energy source or carbon stream, including primary energy, secondary energy, direct use primary energy and various energy consuming terminals; representing the flow direction and the size of the energy flow or carbon flow data by connecting lines between each object; drawing the width of the connecting line according to the ratio of the power or carbon emission of the energy consumption terminal;
step three: aiming at the load capacity and photovoltaic power generation characteristics of various facilities of the comprehensive energy station, a daily scheduling optimization operation model of the comprehensive energy station is constructed, and the charge and discharge time of the energy storage module is adjusted according to photovoltaic output prediction and in-station load power prediction so as to ensure the maximum absorption of the output of the photovoltaic module in the station and realize low-carbon operation of the comprehensive energy station;
In the third step, aiming at the load capacity and photovoltaic power generation characteristics of various facilities of the comprehensive energy station, a daily scheduling operation optimization model of the comprehensive energy station is constructed, wherein the optimization operation model is as follows:
objective function:
Constraint conditions:
Wherein t is the time period considered by day-ahead optimization operation, A PV is the area of a photovoltaic panel, eta PV is the photovoltaic power generation efficiency, I (t) is the predicted solar irradiation intensity, A PVηPV I (t) is the upper limit of the exportable electric power of the photovoltaic power station, E PV (t) is the electric power actually output by the photovoltaic power station, P eload (t) is the electric power predicted value of load consumption in the station, E batc (t) is the electric power charged into a battery at the moment t, E batd (t) is the electric power released by the battery at the moment t, E bat (t) is the residual capacity of the battery at the moment t, E bat (t-1) is the residual capacity of the battery at the moment t-1, eta batc is the charging efficiency of the battery, and eta batd is the release efficiency of the battery.
2. The multi-station fusion comprehensive energy station carbon flow state potential sensing and low-carbon operation method according to claim 1, wherein the method comprises the following steps of: in the first step, the main structure of the typical comprehensive energy station comprises a 110kV transformer substation body module, a photovoltaic module, a charging module, a configuration energy storage module, a data center module and a 5G base station module.
3. The multi-station fusion comprehensive energy station carbon flow state potential sensing and low-carbon operation method according to claim 1, wherein the method comprises the following steps of: in the first step, the capacity configuration, arrangement form and wiring mode of each main body of the comprehensive energy station are as follows: based on a 110kV intelligent substation modularized construction general design 110-A2-6 scheme, a substation module comprises a 110kV/10-35kV main transformer and a box-type transformer, and a 380V indoor power station transformer; the photovoltaic module adopts a roof photovoltaic array arranged on the roof of the main building and the charging parking space; the load in the station comprises lighting, heating ventilation and air conditioning loads; the charging module adopts integrated direct current quick charging and is used for comprehensive vehicle inspection operation in the energy station; the energy storage module adopts a prefabricated box type lithium iron phosphate battery to provide power reserve for a data center and a 5G base station; the 5G module selects a 45m pole tower which is arranged on one side close to the wall; the data center module integrates an IT equipment warehouse and an air conditioner outdoor machine room in the container and is arranged on one side of the enclosing wall.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210093595.4A CN114492997B (en) | 2022-01-26 | 2022-01-26 | Multi-station fusion comprehensive energy station carbon flow state potential sensing and low-carbon operation method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210093595.4A CN114492997B (en) | 2022-01-26 | 2022-01-26 | Multi-station fusion comprehensive energy station carbon flow state potential sensing and low-carbon operation method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN114492997A CN114492997A (en) | 2022-05-13 |
| CN114492997B true CN114492997B (en) | 2024-08-02 |
Family
ID=81475255
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210093595.4A Active CN114492997B (en) | 2022-01-26 | 2022-01-26 | Multi-station fusion comprehensive energy station carbon flow state potential sensing and low-carbon operation method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114492997B (en) |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114707776B (en) * | 2022-06-08 | 2022-09-02 | 山东暖谷新能源环保科技有限公司 | Carbon emission double control-based low-carbon energy consumption optimization system and method |
| CN117710153B (en) * | 2024-02-06 | 2024-05-10 | 深圳市先行电气技术有限公司 | Energy utilization auxiliary decision-making method and system based on multi-terminal equipment |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108876000A (en) * | 2018-04-28 | 2018-11-23 | 国网江苏电力设计咨询有限公司 | A kind of photovoltaic charge station light, storage, transformer capacity coordinate and optimize configuration method |
| CN110611336A (en) * | 2019-10-10 | 2019-12-24 | 国网(苏州)城市能源研究院有限责任公司 | Optimized operation method of park comprehensive energy system with double-stage demand side response |
Family Cites Families (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111200293B (en) * | 2018-11-16 | 2022-03-01 | 国网能源研究院有限公司 | Battery loss and distributed power grid battery energy storage day-ahead random scheduling method |
| CN111064181A (en) * | 2019-11-20 | 2020-04-24 | 国网浙江省电力有限公司杭州供电公司 | Power supply and charging station configuration method based on charging load space schedulable characteristic |
| CN111277006B (en) * | 2020-02-28 | 2022-05-27 | 东北电力大学 | Low-carbon control method for power system containing gas-coal-wind turbine generator |
| CN111339689B (en) * | 2020-03-30 | 2023-02-07 | 广东工业大学 | Building comprehensive energy scheduling method, system, storage medium and computer equipment |
| CN111641207B (en) * | 2020-06-03 | 2023-06-09 | 国网上海市电力公司 | Regional energy complex virtual aggregation system and method |
| CN111697604B (en) * | 2020-06-19 | 2021-12-28 | 中国电力科学研究院有限公司 | Configuration method, system and equipment for integrating multiple stations |
| CN112464477A (en) * | 2020-11-27 | 2021-03-09 | 国网山东省电力公司青岛供电公司 | Multi-energy coupling comprehensive energy operation simulation method considering demand response |
| CN113326467B (en) * | 2021-04-27 | 2023-10-31 | 国网上海市电力公司 | Multi-target optimization method, storage medium and optimization system for multi-station fusion comprehensive energy system based on multiple uncertainties |
| CN113315165B (en) * | 2021-05-17 | 2022-11-29 | 国网上海市电力公司 | Four-station integrated comprehensive energy system coordination control method and system |
| CN113868588A (en) * | 2021-09-29 | 2021-12-31 | 江苏智臻能源科技有限公司 | Method for constructing energy flow carbon flow map of cell |
| CN113642936B (en) * | 2021-10-13 | 2022-09-09 | 中国电力科学研究院有限公司 | Method, terminal and system for analyzing edge of demand side carbon flow |
| CN113746144B (en) * | 2021-11-08 | 2022-03-22 | 南京东博智慧能源研究院有限公司 | Source-grid-load real-time interaction electric carbon control method and intelligent management system thereof |
-
2022
- 2022-01-26 CN CN202210093595.4A patent/CN114492997B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108876000A (en) * | 2018-04-28 | 2018-11-23 | 国网江苏电力设计咨询有限公司 | A kind of photovoltaic charge station light, storage, transformer capacity coordinate and optimize configuration method |
| CN110611336A (en) * | 2019-10-10 | 2019-12-24 | 国网(苏州)城市能源研究院有限责任公司 | Optimized operation method of park comprehensive energy system with double-stage demand side response |
Also Published As
| Publication number | Publication date |
|---|---|
| CN114492997A (en) | 2022-05-13 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN103236718B (en) | Source-network-load automatic control system and method for intelligent microgrid | |
| Guo et al. | Co-optimization method research and comprehensive benefits analysis of regional integrated energy system | |
| Guo et al. | Multi-objective optimization design and multi-attribute decision-making method of a distributed energy system based on nearly zero-energy community load forecasting | |
| CN106849109B (en) | A kind of urban distribution network load control method for the access of scale charging pile | |
| Zhu et al. | Optimization scheduling of a wind–photovoltaic–gas–electric vehicles Community-Integrated Energy System considering uncertainty and carbon emissions reduction | |
| CN114492997B (en) | Multi-station fusion comprehensive energy station carbon flow state potential sensing and low-carbon operation method | |
| CN111641213B (en) | Construction method and application method of safe and economic operation boundary of flexible transformer area | |
| CN114336745A (en) | Multi-energy complementary intelligent energy system based on source network charge storage and control method | |
| CN112152200B (en) | Multi-station fusion integration method and system based on intelligent micro-grid | |
| Prasad et al. | A Comprehensive Review on Photovoltaic Charging Station for Electric Vehicles | |
| CN114580746A (en) | Comprehensive energy station composite energy storage configuration optimization method based on low-carbon economic benefit quantification | |
| CN110728393A (en) | Comprehensive energy management oriented system and intelligent user terminal | |
| Wang et al. | Optimal sizing of photovoltaic and battery energy storage of electric vehicle charging station based on two-part electricity pricing | |
| CN114784789B (en) | Iron tower basic station new forms of energy storage teletransmission electrical power generating system | |
| Vigneshkumar et al. | Optimal sizing and operation of solar PV powered EV battery swapping station for Indian petroleum retail outlet | |
| Shi et al. | Economic operation of industrial microgrids with multiple kinds of flexible loads | |
| CN114006390A (en) | Electric vehicle charging load participation power grid interaction simulation method and system | |
| Ren et al. | Research on energy conversion module configuration method of multi-energy transformation integrated equipment adapted to highway traffic scenes | |
| CN110929908B (en) | Collaborative optimization method and system for capacity allocation and economic scheduling of multi-microgrid system | |
| Li et al. | Energy Flow and Carbon Emission Flow Analysis for the Integrated Energy Station | |
| Cheng et al. | Research on the mode of energy distribution network for smart low-carbon city | |
| Cao et al. | Optimal capacity configuration of battery storage system for zero energy office building on campus | |
| Jiarui et al. | Research on Demand Response Strategy of Electricity Market Based on Intelligent Power Consumption | |
| Hui et al. | Research on charge and discharge control strategy of electric vehicles in building micro-grid based on V2G mode | |
| Ye et al. | Current Status and Prospects of Research on New Urban User-Side Energy Interconnection System Planning |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| TA01 | Transfer of patent application right | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20220808 Address after: 210008 No. 251, Gulou District, Jiangsu, Zhongshan Road, Nanjing Applicant after: STATE GRID JIANGSU ECONOMIC Research Institute Address before: 210008 No. 251, Gulou District, Jiangsu, Zhongshan Road, Nanjing Applicant before: STATE GRID JIANGSU ECONOMIC Research Institute Applicant before: HOHAI University |
|
| GR01 | Patent grant | ||
| GR01 | Patent grant |