Power grid optimization method, device, equipment, storage medium and program product
By constructing a power carbon intensity diagram model and incorporating simulated generating units to calculate power carbon intensity, the problem of inaccurate power grid optimization schemes in existing technologies has been solved. This has enabled more accurate power grid optimization and simulation of new energy generating units, thereby improving the environmental friendliness of the power grid.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- ENVISION DIGITAL INT PTE LTD
- Filing Date
- 2022-09-21
- Publication Date
- 2026-04-14
AI Technical Summary
In existing technologies, power grid optimization schemes that only aim to reduce total carbon emissions cannot accurately represent the quality of the power grid, resulting in inaccurate optimization schemes.
By constructing a power carbon intensity diagram model and adding simulated generating units to calculate power carbon intensity, the generator unit structure of the target power grid is optimized, and a more accurate optimization scheme is determined with the goal of optimizing carbon intensity.
It has enabled more accurate power grid optimization schemes, improved the environmental friendliness of the power grid and the sustainability of the power generation process, especially the simulation of the impact of the access of new energy generator units on the overall carbon intensity of the power grid.
Smart Images
Figure CN115577505B_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of power technology, and in particular to a method, apparatus, equipment, storage medium, and program product for optimizing a power grid. Background Technology
[0002] In the field of power technology, the information contained in a power generation grid can be represented in the form of a topology diagram.
[0003] In related technologies, power grids are optimized with the goal of reducing the total carbon emissions of the power grid. However, when the power generation capacity is low, a low total carbon emission does not necessarily mean that the current power grid is better. In other words, the total carbon emission is sometimes not a very accurate representation of the quality of the current power grid, which leads to the inaccuracy of the optimization scheme of the power grid based on the total carbon emission. Summary of the Invention
[0004] This application provides a method, apparatus, device, storage medium, and program product for optimizing a power grid, which can improve the accuracy of power grid optimization schemes. The technical solution is as follows:
[0005] According to one aspect of the embodiments of this application, a method for optimizing a power grid is provided, the method comprising:
[0006] Obtain a first power carbon intensity map model, which includes power carbon intensity information of the target power grid;
[0007] Add m simulated generator units to the first power carbon intensity map model to construct the second power carbon intensity map model, where m is a positive integer;
[0008] By adjusting the output power of the simulation unit, the power carbon intensity of the second power carbon intensity diagram model is calculated, and the power carbon intensity calculation result of the second power carbon intensity diagram model is obtained.
[0009] Based on the calculation results of the power carbon intensity of the second power carbon intensity map model, the second power carbon intensity map model is analyzed to determine the optimization scheme of the target power grid. The calculation results of the power carbon intensity of the optimization scheme of the target power grid are better than the calculation results of the power carbon intensity corresponding to the first power carbon intensity map model.
[0010] According to one aspect of the embodiments of this application, a power grid optimization apparatus is provided, the apparatus comprising:
[0011] The model acquisition module is used to acquire a first power carbon intensity map model, which includes power carbon intensity information of the target power grid.
[0012] The model building module is used to add m simulated units to the first power carbon intensity map model and build the second power carbon intensity map model, where m is a positive integer;
[0013] The carbon intensity calculation module is used to calculate the carbon intensity of the second power carbon intensity diagram model by adjusting the output power of the simulation unit, and obtain the carbon intensity calculation result of the second power carbon intensity diagram model.
[0014] The scheme determination module is used to analyze the second power carbon intensity map model based on the power carbon intensity calculation results of the second power carbon intensity map model, and determine the optimization scheme of the target power grid. The power carbon intensity calculation results of the optimization scheme of the target power grid are better than the power carbon intensity calculation results corresponding to the first power carbon intensity map model.
[0015] According to one aspect of the embodiments of this application, a computer device is provided, the computer device including a processor and a memory, the memory storing a computer program, the computer program being loaded and executed by the processor to implement the above-described power grid optimization method.
[0016] According to one aspect of the present application, a computer-readable storage medium is provided, wherein a computer program is stored in the computer-readable storage medium, the computer program being loaded and executed by a processor to implement the above-described power grid optimization method.
[0017] According to one aspect of the embodiments of this application, a computer program product is provided, which is loaded and executed by a processor to implement the above-described power grid optimization method.
[0018] The technical solutions provided in this application embodiment may have the following beneficial effects:
[0019] By connecting simulated generator units to the graph model corresponding to the target power grid, the calculation results of the power carbon intensity of the power carbon intensity graph model (i.e., the second power carbon intensity graph model) corresponding to the target power grid are simulated and analyzed after the generator units simulated by the simulated generator units are connected to the target power grid. Based on the calculation results of power carbon intensity, the optimization scheme of the target power grid is determined. Compared with the optimization scheme that only aims to reduce total carbon emissions, the embodiment of this application mainly aims to optimize carbon intensity, and the obtained optimization scheme is more accurate.
[0020] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description
[0021] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0022] Figure 1 This is a flowchart of a power grid optimization method provided in one embodiment of this application;
[0023] Figure 2 This is a schematic diagram of a graphical model provided in one embodiment of this application;
[0024] Figure 3 This is a schematic diagram of a graphical model provided in another embodiment of this application;
[0025] Figure 4 This is a flowchart of a compensation method for a power grid simulation unit provided in one embodiment of this application;
[0026] Figure 5 This is a flowchart of a power grid optimization method provided in another embodiment of this application;
[0027] Figure 6 This is a schematic diagram of a graphical model provided in another embodiment of this application;
[0028] Figure 7 This is a block diagram of a power grid optimization device provided in one embodiment of this application;
[0029] Figure 8 This is a block diagram of a computer device provided in one embodiment of this application. Detailed Implementation
[0030] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of methods consistent with some aspects of this application as detailed in the appended claims.
[0031] The method provided in this application can be executed by a computer device, which refers to an electronic device with data computing, processing, and storage capabilities. This computer device can be a terminal such as a PC (Personal Computer), tablet computer, smartphone, wearable device, or intelligent robot; or it can be a server. The server can be an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services.
[0032] The technical solution of this application will be described and illustrated below through several embodiments.
[0033] Please refer to Figure 1 This document illustrates a flowchart of a power grid optimization method according to an embodiment of this application. In this embodiment, the method is primarily illustrated by its application to the computer device described above. The method may include the following steps (110-140):
[0034] Step 110: Obtain the first power carbon intensity map model, which includes the power carbon intensity information of the target power grid.
[0035] In some embodiments, the target power grid refers to a power generation grid within a specified area, such as the power generation grid of a country, a city, or a province. The first power carbon intensity graph model is a graph model of the topology constructed based on power grid information and carbon flow information within the target power grid. The first power carbon intensity graph model stores the power carbon intensity information of the target power grid in the form of a graph database.
[0036] In some embodiments, step 110 further includes the following steps:
[0037] 1. Obtain the grid information of the target power grid. The grid information is used to indicate the equipment information of the target power grid and the connection information between the equipment.
[0038] In some embodiments, the grid information of the target power grid includes the equipment and feeders contained in the target power grid, the connection information between the equipment and feeders, and the attribute data of the aforementioned equipment and feeders. The attribute data of the equipment may include attribute data such as the model, rated voltage, rated current, and rated power of the equipment / feeder. Optionally, the equipment includes power generation equipment (such as generators, generator sets, power plants, etc.) and power transformation equipment (such as substations), etc., which are not specifically limited in this embodiment. Feeders can be connected to equipment or to other feeders.
[0039] 2. Construct a power grid diagram model based on power grid information.
[0040] In some embodiments, based on power grid information, a topology network (i.e., a topology graph) is constructed with devices as nodes and feeders as edges, and the attribute data of the devices and feeders are added to the topology network to obtain a power grid graph model of the target power grid. The power grid graph model is also a graph database.
[0041] 3. Obtain the carbon intensity information of the target power grid. Construct a first carbon intensity graph model based on the power grid graph model and the carbon intensity information of the target power grid. The carbon intensity information of the target power grid includes the current information and carbon flow information in the target power grid.
[0042] In some embodiments, the current in the power grid can also be referred to as power flow, that is, current information can also be called power flow information. Carbon emissions also occur during power generation, consumption, and transmission. Therefore, the carbon emissions caused by the current in the power grid are called carbon flow, and the direction of carbon flow is the same as the direction of the current.
[0043] The carbon emissions of each node and feeder in the power grid diagram model are obtained, that is, the carbon emissions of power generation equipment during power generation and current transmission. By dividing the carbon emissions in the same time period by the corresponding output / consumption of electricity, the electrical carbon intensity of each node and feeder in that time period can be calculated. The calculated electrical carbon intensity values are stored in the power grid diagram model to obtain the first electrical carbon intensity diagram model.
[0044] Step 120: Add m simulated units to the first power carbon intensity map model to construct the second power carbon intensity map model, where m is a positive integer.
[0045] In some embodiments, one or more simulated generator sets are added to a first power carbon intensity map model. Each simulated generator set can be used to simulate a generator set, such as simulating the power generation and / or power output of each power generation device in the generator set at different time periods. In some embodiments, the target power grid may include a transmission network and a distribution network; the simulated generator set may be a generator set in the distribution network or a generator set in the transmission network.
[0046] In some embodiments, the simulation unit can be a simulation of a new energy generator set. The new energy generator set can include hydropower, wind power, and photovoltaic power.
[0047] In some embodiments, the first power carbon intensity map model includes n power generation nodes, where n is a positive integer, and step 120 includes at least one of the following two cases:
[0048] Case 1: While maintaining the n power generation nodes in the first power carbon intensity graph model, add at least one simulation unit for simulating generator sets, and associate the first simulation unit with the associated nodes in the first power carbon intensity graph to construct the second power carbon intensity graph model.
[0049] In some embodiments, the power grid diagram model and the first power carbon intensity diagram model include n power generation nodes, each power generation node representing a generator, a generator set, or a power plant. While keeping the number of n power generation nodes and their positions in the first power carbon intensity diagram model unchanged, at least one additional simulated generator set is added to the first power carbon intensity diagram model to obtain a second power carbon intensity diagram model.
[0050] Case 2: Replace at least one of the n power generation nodes with a simulated unit to construct a second power carbon intensity map model.
[0051] In some embodiments, for at least one of the n power generation nodes, each power generation node is replaced with a simulated unit to obtain a second power carbon intensity map model.
[0052] In some embodiments, such as Figure 2 As shown, for the power generation node 11 in the first or second power carbon intensity map model, when the power generation node 11 is used to represent the generator set of the transmission network, the power generation node 11 is associated with other equipment nodes 12, and the other equipment nodes 12 are used to represent other generator sets, switches and buses.
[0053] In some embodiments, such as Figure 3 As shown, for the generator node 13 in the first or second power carbon intensity map model, when the generator node 13 is used to simulate the generator set of the distribution network, the generator node 13 is associated with the feeder node 14 and is associated with the substation node 15 through the feeder node 14.
[0054] In some embodiments, such as Figure 2 or Figure 3 As shown, the calculation node 16 in the first or second power carbon intensity map model is used to store the calculation parameters and results related to the generator set (i.e., the generating node), and the calculation node 16 is associated with the corresponding substation or feeder for convenient statistical analysis.
[0055] In some embodiments, a simulation system is obtained by adding simulated generating units, which are distributed renewable energy generating units added to the distribution network. For simplicity, the topology of the simulated generating units added to this simulation system is similar to the topology of most feeder equivalent loads in the transmission network model. In some embodiments, to simulate distributed renewable energy generating units in the distribution network, the simulated generating units are only added to substations with 10kV buses and connected to the 10kV buses in the substation via switches. Considering that distributed renewable energy generating units in the distribution network are generally connected to the transmission network via feeders, the simulated generating units can only be added to substations with loads. To simulate the self-consumption of renewable energy generating units in the distribution network and for the purpose of simplifying calculations, the capacity of newly added simulated generating units needs to be limited: for example, the capacity of the simulated generating units is not greater than the total load within the substation.
[0056] Step 130: By adjusting the output power of the simulation unit, the power carbon intensity of the second power carbon intensity diagram model is calculated to obtain the power carbon intensity calculation result of the second power carbon intensity diagram model.
[0057] In some embodiments, based on the second power carbon intensity map model, power carbon intensity calculations (also referred to as carbon intensity calculations) are performed on each power generation node, feeder node, substation node, and other equipment node in the second power carbon intensity map model to obtain the power carbon intensity calculation results of the second power carbon intensity map model. The power carbon intensity calculation results obtained by performing carbon intensity calculations on the nodes can be referred to as node carbon intensity. In some embodiments, the output power (i.e., power generation power, also called output) of the simulated unit can be varied. Each time the output power of the simulated unit changes, the power carbon intensity calculation is re-performed on the second power carbon intensity map model to obtain the power carbon intensity calculation results of the second power carbon intensity map model.
[0058] In some embodiments, the target power grid includes multiple regions. The calculation results of the power carbon intensity of the power carbon intensity map model also include the carbon intensity corresponding to each region in the target power grid, which can also be referred to as the regional carbon intensity. The regional carbon intensity can be calculated based on the calculation results obtained by calculating the power carbon intensity of each generation node, feeder node, substation node, and other equipment node; the regional carbon intensity can also be obtained by dividing the total carbon emissions of the corresponding region in the same time period by the final output electricity.
[0059] In some embodiments, the output power of a simulator can be adjusted by increasing or decreasing the number of simulators, or by directly modifying the output power parameters of one or more simulators.
[0060] Step 140: Based on the calculation results of the power carbon intensity of the second power carbon intensity map model, analyze the second power carbon intensity map model to determine the optimization scheme of the target power grid.
[0061] Among them, the calculated carbon intensity of the target power grid's optimized scheme is better than the calculated carbon intensity of the first carbon intensity diagram model.
[0062] In some embodiments, the calculation results of the power carbon intensity of the second power carbon intensity graphical model are compared and analyzed under different output power of the simulated units. The graphical model of the simulated unit corresponding to the optimal calculation result in the power carbon intensity calculation results is determined as the graphical model corresponding to the optimization scheme of the target power grid. That is, according to the number of simulated units corresponding to the optimal calculation result and the parameters of each simulated unit (such as the output power of each simulated unit, the position of each simulated unit in the target power grid, etc.), generator units are added to the target power grid (such as replacing the original generator units and / or adding new generator units) to obtain a new power grid structure for the target power grid, that is, a new power carbon intensity graphical model corresponding to the target power grid.
[0063] In some implementations, the carbon intensity of the first power grid is calculated using the first power carbon intensity map model, yielding the calculated carbon intensity result corresponding to the first power carbon intensity map model. Clearly, the calculated carbon intensity result of the optimized scheme for the target power grid should be superior to the calculated carbon intensity result corresponding to the first power carbon intensity map model in one or more aspects. For example, the nodal carbon intensity corresponding to the optimized scheme for the target power grid may be lower than the nodal carbon intensity corresponding to the first power carbon intensity map model; or, for another example, the regional carbon intensity corresponding to the optimized scheme for the target power grid may be lower than the regional carbon intensity corresponding to the first power carbon intensity map model.
[0064] In some embodiments, the calculation results of the power carbon intensity of a first power carbon intensity map model are obtained; if the calculation results of the power carbon intensity of a second power carbon intensity map model are better than those of the first power carbon intensity map model, the target power grid is optimized based on the second power carbon intensity map model. In this case, the number of simulated generators and their positions in the target power grid are fixed. If the calculation results of the power carbon intensity corresponding to the output power of the simulated generators within a certain range are better than those of the first power carbon intensity map model, after replacing the simulated generators with real generators, the generators in the target power grid are controlled to generate electricity according to the range of their output power.
[0065] In summary, the technical solution provided in this application involves connecting a simulated generator unit to the graph model corresponding to the target power grid. After connecting the generator unit simulated by the simulated generator unit to the target power grid, the calculation results of the power carbon intensity of the power carbon intensity graph model (i.e., the second power carbon intensity graph model) corresponding to the target power grid are simulated and analyzed. Based on the calculation results of the power carbon intensity, an optimization scheme for the target power grid is determined. Compared with an optimization scheme that only aims to reduce total carbon emissions, this application embodiment mainly aims to optimize carbon intensity, resulting in a more accurate optimization scheme.
[0066] In addition, in this embodiment of the application, by using a simulation unit to simulate the new energy generator set, the impact of the new energy generator set on the carbon intensity of other generator sets and the target power grid as a whole can be simulated and analyzed. This helps to formulate or optimize the scheme of adding new energy generator sets to the target power grid, making the power generation process of the target power grid more environmentally friendly.
[0067] In some implementations, the target power grid is divided into multiple regions; the method also includes:
[0068] 1. Determine the compensation area corresponding to the simulation unit;
[0069] 2. If there are thermal power units within the compensation area, and the power generation capacity of the thermal power units is greater than that of the simulated units, then the thermal power units shall be used to compensate for the simulated units.
[0070] 3. If there are no thermal power units within the compensation area, update the area of the compensation area until there are thermal power units within the compensation area and the power generation capacity of the thermal power units is greater than that of the simulated units; use thermal power units to compensate for the simulated units.
[0071] In some embodiments, updating the area of the compensation region means determining other regions as the updated compensation region. For example, the region closest to the area where the simulator is located is preferentially selected as the compensation region.
[0072] like Figure 4 As shown, the method includes the following steps (41-46):
[0073] Step 41: Determine the plant to which the simulation unit belongs;
[0074] Step 42: Determine the area where the plant to which the simulation unit belongs is located as the compensation area;
[0075] Step 43: Determine whether there are thermal power units within the compensation area. If yes, proceed to step 45; otherwise, proceed to step 44.
[0076] Step 44: Update the area range of the compensation region, and start executing from step 43;
[0077] Step 45: Determine whether the power generation capacity of the thermal power unit in the compensation area is greater than that of the simulated unit. If yes, proceed to step 46; otherwise, proceed to step 44.
[0078] Step 46: Use the thermal power units in the compensation zone to compensate the simulated unit.
[0079] In the above implementation, to simulate the substitution of thermal power generation by new energy power generation, simulated units are used to replace thermal power units while ensuring the power balance of the entire system. While correcting the output of the calculated bus corresponding to the simulated units, compensatory adjustments need to be made to the output of some thermal power units. For example... Figure 4 As shown, in order to simulate the impact of new energy generator units on the carbon emission intensity of electricity in the region, the thermal power units that are adjusted for compensation will be selected from the thermal power units in the same region first. If the output value of the thermal power units in this region is insufficient to compensate for the output of the simulated units, the thermal power units in the nearest adjacent region will be found for compensation based on the telemetry data of the transmission network.
[0080] Calculation of carbon emission intensity of electricity:
[0081] The fundamental way to achieve carbon neutrality is to reduce carbon emissions, that is, to provide corresponding solutions for carbon emission reduction. The statistical accounting of carbon emissions is an important basis. This is directly related to whether the carbon emission reduction plan is reasonable, whether the corresponding management and operation mechanism is effective, and ultimately determines whether the carbon peak and carbon neutrality goals can be truly achieved. The carbon intensity of electricity can be defined as: the ratio of the carbon emissions generated by power generation (or consumption) in a given area within a given time to the carbon emissions from the input (or output) of electricity, to the sum of the power generation (or consumption) and the input (or output) of electricity, which is the carbon dioxide content corresponding to a unit of electricity (such as one kilowatt-hour) in a given area within a given time. The above-mentioned areas can be divided according to administrative divisions, or they can be divided into different levels of companies and different voltage levels of power plants according to the power grid operation and management units. For a certain area, the regional power grid power balance equation is formula (1):
[0082]
[0083] In the formula, I n，a，t For the amount of electricity input from neighboring region n to region a during time period t, N a L is the set of regions where the input electricity is in region a. a It is the set of loads in region a, D l，t NL is the electricity consumption of load 1 during time period t. a，t M is the network loss of region a during time period t. a O is the set of regions that output electrical energy from region a. x，m，tThis refers to the electrical energy output from region a to region m during time period t. Due to the coupling relationship between carbon flow and current, the multi-input-output balance equation for regional carbon emissions can be defined as (2):
[0084]
[0085] Among them, CIEC n，t Let n be the electrical carbon intensity of region n during time period t, CIEC a，t Let e be the electrical carbon intensity of region a during time period t. k Let k be the carbon emission factor of generator k. Since the input data only includes information about regional power generation and electrical energy input from other regions, the method for calculating the carbon emission intensity of this region is called the upstream method.
[0086] Furthermore, for a specific power grid region, its electricity carbon intensity is divided into power generation carbon intensity, grid-side carbon intensity, and electricity consumption carbon intensity. Assuming region a, its power generation carbon intensity can be defined as (3):
[0087]
[0088] In the formula, CIEG a，t G represents the carbon emission intensity of electricity generated in region a during time period t. a G is the set of all generators in the region. k，t Let e be the amount of electricity generated by generator k during time period t. k Let be the carbon emission factor of generator k. The regional power generation carbon intensity is related to its fuel type and power generation efficiency, with coal-fired power units having the highest intensity, followed by natural gas units. Renewable energy generation from wind, solar, and hydropower is relatively low, generally taken as 0. For ease of calculation and verification, this paper sets the carbon emission factor of new energy units to 1. It is evident that the regional power generation carbon intensity depends only on the amount of electricity generated within the region and the resulting carbon emissions. Within the region, the higher the proportion of renewable energy and low-carbon power generation, the lower the regional power generation carbon intensity.
[0089] Based on the multi-input-output balance equation of regional carbon emissions, the power carbon intensity on the grid side of region a is defined as (4):
[0090]
[0091] In the formula, I n，a，t Let Na be the amount of electricity input from neighboring region n to region a during time period t, where Na is the set of regions into which region a receives electrical energy. (CIEC) n，tLet be the grid-side carbon intensity of a neighboring region n. For regions that are pure electricity exporters, their electricity generation carbon intensity is the same as their grid-side carbon intensity. For regions that are electricity importers, their grid-side carbon intensity needs to consider the electricity imported from neighboring grids, i.e., electricity transactions with neighboring regional grids, and the resulting carbon emissions. Therefore, the grid-side carbon intensity of neighboring grids will affect the region's grid-side carbon intensity.
[0092] From the perspective of user electricity load in the region, based on the electricity carbon intensity on the grid side in the region, the electricity carbon intensity in the region is defined as (5):
[0093]
[0094] In the formula, CIEL a，t Let Load be the carbon emission intensity of electricity consumption in region a during time period t. a P is the set of all loads within the region. l，t For the power consumption of load 1 in time period t, CIEC a，t The target area represents the carbon emission intensity on the grid side. Therefore, the carbon emissions from the loads within this area are...
[0095] Consider the calculation of the electrical carbon intensity of the simulated unit:
[0096] For a certain region, considering the access of distributed new energy simulation units in the region from the power generation side, the total power generation of non-green electricity (i.e., electricity generated by new energy generator units) in the region decreases, and the total carbon emissions from power generation in the region decrease, which is (6):
[0097]
[0098] In the formula, CESG a，t For region a, considering the carbon emissions of the generated electricity from the simulated generator units during time period t, G s，a G is the set of all simulation units used to simulate new energy generator sets within the region. s，t e represents the power generation of the simulated unit s during time period t. s Let be the carbon emission factor of generator s. Since all the simulated generators are new energy generators, their power generation carbon emission factor is 1. Considering the power generation carbon intensity CISG of region a in time period t, the carbon emission factor for the simulated generators is... a，t It can be defined as (7):
[0099]
[0100] According to formula (4), considering the power carbon intensity (CISC) of the simulated unit in region a during time period t on the grid side. a，t It can be defined as (8):
[0101]
[0102] Considering the presupposition that there is no green electricity trading between neighboring areas and that electricity is generated and consumed within the region, the carbon emissions generated by electricity consumption within the region are... Therefore, considering the carbon intensity CISL of the electricity consumption side of the simulated unit in region a during time period t. a，t It can be defined as (9):
[0103]
[0104] In some embodiments, such as Figure 5 As shown, the method may include the following steps (51-58):
[0105] Step 51: Obtain the power carbon intensity map model corresponding to the target power grid.
[0106] Step 52: Determine whether a simulated generator unit needs to be added to the power carbon intensity diagram model. If yes, proceed to step 53; otherwise, proceed to step 54.
[0107] Step 53: Add the simulated unit to the power carbon intensity diagram model.
[0108] Step 54: Perform topology analysis and state estimation on the power carbon intensity map model.
[0109] In some embodiments, after adding a simulation unit, in the graph-based topology analysis stage, the simulation unit will participate in the topology analysis calculation like other devices, generating corresponding computational bus nodes.
[0110] In some embodiments, the state estimation of the power carbon intensity graph model is a graph-based state estimation, which can achieve millisecond-level calculation speed. This millisecond-level state estimation based on graph computation uses only existing real-time measurement data (such as real-time power transmission or output, real-time power consumption or power consumption, etc.). For the calculation bus corresponding to the simulated unit, active and reactive power outputs are set to 0 for state estimation calculation, without affecting the state estimation results of the calculation buses corresponding to other equipment.
[0111] The power carbon intensity graph model in step 54 can refer to either the first power carbon intensity graph model or the second power carbon intensity graph model mentioned above.
[0112] Step 55: Based on the power flow of the target power grid, calculate the power carbon intensity of the target power grid to obtain the power carbon intensity calculation results of the power carbon intensity diagram model.
[0113] In some embodiments, during power flow calculation, the active and reactive power outputs of the calculation bus corresponding to the simulated unit are adjusted. The active power output of the calculation bus corresponding to the simulated unit is adjusted to the simulated active power of the simulated unit, and the reactive power output is adjusted to 40% or other percentage of the active power value. This application embodiment does not specifically limit this.
[0114] Step 56: Determine whether the power carbon intensity map model contains simulated units. If yes, proceed to step 57; otherwise, proceed to step 58.
[0115] Step 57: Output the original calculation results of the target power grid's carbon intensity.
[0116] Step 58: Output the calculated results of the power carbon intensity of the target power grid after the addition of the simulated generating units.
[0117] Based on the regional carbon intensity calculation results of the above simulation system, a region with thermal power units as the main power generation structure is selected as a case study for simulated unit connection analysis. For example... Figure 6 As shown, the example system displays the target area and its adjacent areas according to a scale map based on the actual geographical area. The carbon intensity of area 17 is greater than that of area 18, which is greater than that of area 19, which is greater than that of area 20, which is greater than that of area 21, which is greater than that of area 22, which is greater than that of area 23. Plant 24 within area 17 is selected as the simulated generator unit connected to the plant. The effects of adjusting the power output of different simulated generator units on the carbon intensity of the plant nodes and the overall regional carbon intensity are observed. The current regional carbon intensity of area 17 is 864.56, and the current total load is 553.52, while the current load measurement of plant 18 is 110.8128, and the carbon intensity is 874.52.
[0118] Simulated generating units were added to power plant 24, and power flow and carbon intensity calculations were performed. The results are shown in Table 1. As the output of the simulated generating units increases, the power generation within the power plant increases, the input power decreases, and the output power increases. Since the simulated generating units are distributed renewable energy units, the proportion of green electricity consumption in the power plant and the region increases with the increase of the simulated generating unit output. For the power plant, the output of the simulated generating units has a significant impact on the total power generation within the plant. Therefore, the node carbon intensity of power plant 24 decreases significantly. When the power generation output of the simulated generating units is close to the total load within the plant, the power plant can reach a near-zero carbon state (carbon intensity of 23.65). Region 17 includes a total of 46 power plants. The impact of the reduction in carbon intensity of a single power plant node on the regional carbon intensity will be reflected according to the proportion of that power plant in the total power generation and total load within the region. Since the selected power plant has a high proportion of power generation and load in Region 17, the regional carbon intensity also decreases significantly.
[0119] Table 1
[0120]
[0121]
[0122] The following are embodiments of the apparatus described in this application, which can be used to execute the embodiments of the method described in this application. For details not disclosed in the apparatus embodiments of this application, please refer to the embodiments of the method described in this application.
[0123] Please refer to Figure 7 This diagram illustrates a block diagram of a power grid optimization device according to an embodiment of this application. The device has the functionality to implement the aforementioned power grid optimization method example; this functionality can be implemented in hardware or by hardware executing corresponding software. The device can be the computer device described above, or it can be mounted on a computer device. The device 700 may include: a model acquisition module 710, a model construction module 720, a carbon intensity calculation module 730, and a scheme determination module 740.
[0124] The model acquisition module 710 is used to acquire a first power carbon intensity map model, which includes power carbon intensity information of the target power grid.
[0125] The model building module 720 is used to add m simulated units to the first power carbon intensity map model and build a second power carbon intensity map model, where m is a positive integer.
[0126] The carbon intensity calculation module 730 is used to calculate the carbon intensity of the second power carbon intensity diagram model by adjusting the output power of the simulation unit, and obtain the carbon intensity calculation result of the second power carbon intensity diagram model.
[0127] The scheme determination module 740 is used to analyze the second power carbon intensity map model based on the power carbon intensity calculation results of the second power carbon intensity map model, and determine the optimization scheme of the target power grid. The power carbon intensity calculation results of the optimization scheme of the target power grid are better than the power carbon intensity calculation results corresponding to the first power carbon intensity map model.
[0128] In some embodiments, the model acquisition module 710 is configured to:
[0129] Obtain the grid information of the target power grid, wherein the grid information is used to indicate the equipment information and connection information between the equipment in the target power grid;
[0130] Based on the power grid information, a power grid diagram model is constructed;
[0131] Obtain the carbon intensity information of the target power grid, and construct the first carbon intensity graph model based on the power grid graph model and the carbon intensity information of the target power grid. The carbon intensity information of the target power grid includes current information and carbon flow information in the target power grid.
[0132] In some embodiments, the first power carbon intensity map model includes n power generation nodes, where n is a positive integer;
[0133] In some embodiments, the model building module 720 is configured to perform at least one of the following:
[0134] Based on maintaining the n power generation nodes in the first power carbon intensity map model, at least one simulation unit for simulating generator sets is added, and the first simulation unit is associated with the associated nodes in the first power carbon intensity map to construct the second power carbon intensity map model.
[0135] Replace at least one of the n power generation nodes with the simulated unit to construct the second power carbon intensity map model.
[0136] In some embodiments, for the power generation nodes in the first or second power carbon intensity map model:
[0137] In the case where the power generation node is used to represent a generator set of the transmission network, the power generation node is associated with other equipment nodes, which are used to represent other generator sets, switches, and buses;
[0138] In the case where the generator node is used to simulate a generator set in a distribution network, the generator node is associated with a feeder node and, through the feeder node, with a substation node.
[0139] In some embodiments, the target power grid is divided into multiple regions, and the device 700 further includes:
[0140] The region determination module is used to determine the compensation region corresponding to the simulation unit.
[0141] The compensation module is used to compensate the simulated unit using the thermal power unit when there is a thermal power unit in the compensation area and the power generation of the thermal power unit is greater than the power generation of the simulated unit.
[0142] The compensation module is further configured to update the area range of the compensation region when there is no thermal power unit in the compensation region, until there is a thermal power unit in the compensation region and the power generation of the thermal power unit is greater than the power generation of the simulated unit; and use the thermal power unit to compensate the simulated unit.
[0143] In some embodiments, the scheme determination module 740 is configured to:
[0144] Obtain the calculation results of the electric carbon intensity of the first electric carbon intensity map model;
[0145] If the calculation result of the power carbon intensity of the second power carbon intensity map model is better than the calculation result of the power carbon intensity of the first power carbon intensity map model, the target power grid is optimized based on the second power carbon intensity map model.
[0146] In summary, the technical solution provided in this application involves connecting a simulated generator unit to the graph model corresponding to the target power grid. After connecting the generator unit simulated by the simulated generator unit to the target power grid, the calculation results of the power carbon intensity of the power carbon intensity graph model (i.e., the second power carbon intensity graph model) corresponding to the target power grid are simulated and analyzed. Based on the calculation results of the power carbon intensity, an optimization scheme for the target power grid is determined. Compared with an optimization scheme that only aims to reduce total carbon emissions, this application embodiment mainly aims to optimize carbon intensity, resulting in a more accurate optimization scheme.
[0147] It should be noted that the apparatus provided in the above embodiments is only illustrated by the division of the above functional modules when implementing its functions. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the apparatus and method embodiments provided in the above embodiments belong to the same concept, and the specific implementation process can be found in the method embodiments, which will not be repeated here.
[0148] Please refer to Figure 8 This diagram illustrates a structural block diagram of a computer device according to an embodiment of this application. The computer device is used to implement the power grid optimization method provided in the above embodiments. Specifically:
[0149] The computer device 800 includes a CPU (Central Processing Unit) 801, a system memory 804 including RAM (Random Access Memory) 802 and ROM (Read-Only Memory) 803, and a system bus 805 connecting the system memory 804 and the central processing unit 801. The computer device 800 also includes a basic I / O (Input / Output) system 806 that facilitates information transfer between various components within the computer, and a mass storage device 807 for storing the operating system 813, application programs 814, and other program modules 815.
[0150] The basic input / output system 806 includes a display 808 for displaying information and an input device 809 for user input, such as a mouse or keyboard. Both the display 808 and the input device 809 are connected to the central processing unit 801 via an input / output controller 810 connected to the system bus 805. The basic input / output system 806 may also include the input / output controller 810 for receiving and processing input from multiple other devices such as a keyboard, mouse, or electronic stylus. Similarly, the input / output controller 810 also provides output to a display screen, printer, or other types of output devices.
[0151] The mass storage device 807 is connected to the central processing unit 801 via a mass storage controller (not shown) connected to the system bus 805. The mass storage device 807 and its associated computer-readable media provide non-volatile storage for the computer device 800. That is, the mass storage device 807 may include computer-readable media (not shown) such as a hard disk or a CD-ROM (Compact Disc Read-Only Memory) drive.
[0152] Without loss of generality, the computer-readable medium may include computer storage media and communication media. Computer storage media include volatile and non-volatile, removable and non-removable media implemented using any method or technology for storing information such as computer-readable instructions, data structures, program modules, or other data. Computer storage media include RAM, ROM, EPROM (Erasable Programmable Read Only Memory), EEPROM (Electrically Erasable Programmable Read Only Memory), flash memory or other solid-state storage, CD-ROM, DVD (Digital Video Disc) or other optical storage, magnetic tape cassettes, magnetic tape, disk storage, or other magnetic storage devices. Of course, those skilled in the art will recognize that the computer storage media are not limited to the above-mentioned types. The system memory 804 and mass storage device 807 described above can be collectively referred to as memory.
[0153] According to various embodiments of this application, the computer device 800 can also be connected to a remote computer on a network, such as the Internet. That is, the computer device 800 can be connected to a network 812 via a network interface unit 811 connected to the system bus 805, or the network interface unit 811 can be used to connect to other types of networks or remote computer systems (not shown).
[0154] In an exemplary embodiment, a computer-readable storage medium is also provided, wherein a computer program is stored therein, which, when executed by a processor, implements the above-described method for optimizing the power grid.
[0155] In an exemplary embodiment, a computer program product is also provided, which is loaded and executed by a processor to implement the above-described power grid optimization method.
[0156] It should be understood that "multiple" as used in this article refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. The character " / " generally indicates that the preceding and following related objects have an "or" relationship.
[0157] The above description is merely an exemplary embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.
Claims
1. A method for optimizing a power grid, characterized in that, The method includes: A first power carbon intensity graph model is obtained. The first power carbon intensity graph model refers to a graph model of the topology graph constructed based on the power grid information and carbon flow information in the target power grid. The first power carbon intensity graph model stores the carbon intensity information of the target power grid in the form of a graph database. The first power carbon intensity graph model includes n power generation nodes, where n is a positive integer. While maintaining the n power generation nodes in the first power carbon intensity map model, at least one simulated generator unit is added to simulate the generator set, and the at least one simulated generator unit is associated with the associated nodes in the first power carbon intensity map to construct a second power carbon intensity map model; or... Replace at least one of the n power generation nodes in the first power carbon intensity map model with a simulation unit used to simulate a generator set, and construct a second power carbon intensity map model. By adjusting the output power of the simulation unit, the power carbon intensity of the second power carbon intensity diagram model is calculated, and the power carbon intensity calculation result of the second power carbon intensity diagram model is obtained. Based on the calculation results of the power carbon intensity of the second power carbon intensity map model, the second power carbon intensity map model is analyzed to determine the optimization scheme of the target power grid. The calculation results of the power carbon intensity of the optimization scheme of the target power grid are better than the calculation results of the power carbon intensity corresponding to the first power carbon intensity map model.
2. The method according to claim 1, characterized in that, The method for obtaining the first electricity carbon intensity map model includes: Obtain the grid information of the target power grid, wherein the grid information is used to indicate the equipment information and connection information between the equipment in the target power grid; Based on the power grid information, a power grid diagram model is constructed; Obtain the carbon intensity information of the target power grid, and construct the first carbon intensity graph model based on the power grid graph model and the carbon intensity information of the target power grid. The carbon intensity information of the target power grid includes current information and carbon flow information in the target power grid.
3. The method according to claim 1, characterized in that, For the power generation nodes in the first or second power carbon intensity map model: In the case where the power generation node is used to represent a generator set of the transmission network, the power generation node is associated with other equipment nodes, which are used to represent other generator sets, switches, and buses; In the case where the generator node is used to simulate a generator set in a distribution network, the generator node is associated with a feeder node and, through the feeder node, with a substation node.
4. The method according to claim 1, characterized in that, The target power grid is divided into multiple regions, and the method further includes: Determine the compensation area corresponding to the simulation unit; If a thermal power unit exists within the compensation area and the power generation capacity of the thermal power unit is greater than that of the simulated unit, the thermal power unit is used to compensate for the simulated unit. If there are no thermal power units within the compensation area, the area range of the compensation area is updated until there are thermal power units within the compensation area and the power generation capacity of the thermal power units is greater than the power generation capacity of the simulated unit; the thermal power units are used to compensate the simulated unit.
5. The method according to claim 1, characterized in that, The calculation results of the electricity carbon intensity based on the second electricity carbon intensity map model are used to analyze the second electricity carbon intensity map model and determine the optimization scheme of the target power grid, including: Obtain the calculation results of the electric carbon intensity of the first electric carbon intensity map model; If the calculation result of the power carbon intensity of the second power carbon intensity map model is better than the calculation result of the power carbon intensity of the first power carbon intensity map model, the target power grid is optimized based on the second power carbon intensity map model.
6. A power grid optimization device, characterized in that, The device includes: The model acquisition module is used to acquire a first power carbon intensity map model. The first power carbon intensity map model is a graph model of the topology graph constructed based on the power grid information and carbon flow information in the target power grid. The first power carbon intensity map model stores the carbon intensity information of the target power grid in the form of a graph database. The first power carbon intensity map model includes n power generation nodes, where n is a positive integer. The model building module is used to add at least one simulation unit for simulating generator sets while maintaining the n power generation nodes in the first power carbon intensity map model, and associate the at least one simulation unit with the associated nodes in the first power carbon intensity map to build a second power carbon intensity map model; or, replace at least one of the n power generation nodes in the first power carbon intensity map model with a simulation unit for simulating generator sets to build a second power carbon intensity map model. The carbon intensity calculation module is used to calculate the carbon intensity of the second power carbon intensity diagram model by adjusting the output power of the simulation unit, and obtain the carbon intensity calculation result of the second power carbon intensity diagram model. The scheme determination module is used to analyze the second power carbon intensity map model based on the power carbon intensity calculation results of the second power carbon intensity map model, and determine the optimization scheme of the target power grid. The power carbon intensity calculation results of the optimization scheme of the target power grid are better than the power carbon intensity calculation results corresponding to the first power carbon intensity map model.
7. A computer device, characterized in that, The computer device includes a processor and a memory, the memory storing a computer program, which is loaded and executed by the processor to implement the power grid optimization method according to any one of claims 1 to 5.
8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, which is loaded and executed by a processor to implement the power grid optimization method according to any one of claims 1 to 5.
9. A computer program product, characterized in that, The computer program product is loaded and executed by a processor to implement the power grid optimization method according to any one of claims 1 to 5.