A source-grid-load-storage integrated collaborative optimization method and system under a power system

Abstract

The application relates to the technical field of power system optimization, and discloses a source-grid-load-storage integrated collaborative optimization method and system under a power system, which extracts power grid power supply layout parameters and power grid operation parameters in power grid parameter information of a target region, predicts power grid operation prediction parameters of a target scheduling period by using a power grid operation parameter prediction model, constructs a scheduling priority list according to the power grid power supply layout parameters, obtains geographical position parameters and emergency power supply deployment information of each scheduling sub-region in the scheduling priority list, considers multiple different influence factors for long-term and overall optimal scheduling according to the emergency power supply access positions in different scheduling sub-regions and the deployment conditions of fixed emergency power supplies and mobile emergency power supplies, generates an emergency power supply scheduling strategy, and executes scheduling of a mobile emergency power supply of the power system, so that the emergency power supply scheduling effect is improved, and the situation that the regional load of the power system is unbalanced and the user experience is poor is relieved.

Description

Technical Field

[0001] This invention relates to the field of power system optimization technology, and in particular to a novel integrated collaborative optimization method and system for power system sources, grid, load and storage. Background Technology

[0002] Power system source-grid-load-storage synergy technology refers to the deep integration and coordinated interaction of various links in the power system by optimizing the resource allocation and operation control of power sources, grids, loads, and energy storage, thereby improving the power system's security, reliability, flexibility, and economy. Specifically, in power system source-grid-load-storage synergy technology, "source" refers to power sources, including traditional thermal power, hydropower, nuclear power, and new energy power generation such as wind power and photovoltaics. "Grid" refers to the power grid, responsible for the transmission and distribution of electricity. "Load" refers to the power load, including the electricity demand of various users such as industry, commerce, and residential users. "Storage" refers to energy storage, including various forms such as battery energy storage, pumped hydro storage, and compressed air energy storage. The integrated source-grid-load-storage synergy aims to break down barriers between various links, achieving efficient interaction of energy flow and information flow, enabling the power system to better adapt to the large-scale integration of new energy sources and dynamic load changes.

[0003] In practical applications, the deployment and application of emergency power sources in power systems can improve the ability of urban power grids to respond to emergencies and meet the power supply demands of various emergencies. It is an indispensable part of the integrated coordination of power generation, grid, load, and storage in power systems. However, in the current deployment of emergency power sources in urban power grids, due to the different electricity demands of different users at different times, the different power supply capabilities of different grid lines, and the different emergency power supply deployment situations in different regions, the deployment and dispatch of emergency power sources in urban power grids can only rely on manual experience for short-term, individual-optimal dispatching. It is impossible to consider multiple different influencing factors for long-term, overall-optimal dispatching. This results in problems such as unsatisfactory dispatching effects, regional load imbalances in the power system, and poor user experience for electricity users.

[0004] Therefore, how to improve the emergency power dispatching effect of the urban power grid, ensure the regional load balance of the power system, improve the power transmission quality of the power grid, and ensure the user experience of electricity users is a technical problem that urgently needs to be solved. Summary of the Invention

[0005] This invention provides a novel integrated source-grid-load-storage collaborative optimization method and system for power systems, aiming to solve at least one of the above-mentioned technical problems.

[0006] This invention provides a novel integrated collaborative optimization method for power generation, grid, load, and storage systems, comprising:

[0007] Obtain the power grid parameter information of the target area, and extract the power grid power supply layout parameters and power grid operation parameters for the reference time period from the power grid parameter information of the target area;

[0008] Based on the power grid operation parameters of the reference period, the power grid operation parameter prediction model is used to predict the power grid operation prediction parameters of the target area in the target scheduling cycle. Based on the power grid operation prediction parameters and the power grid power supply layout parameters, a scheduling priority list containing several scheduling sub-regions is constructed.

[0009] Obtain the geographic location parameters and emergency power deployment information for each dispatch sub-region; wherein, the emergency power deployment information includes the first deployment information of fixed emergency power in each dispatch sub-region and the second deployment information of mobile emergency power in each dispatch sub-region;

[0010] Based on geographical location parameters, first deployment information, and second deployment information, an emergency power dispatch strategy is generated. The emergency power dispatch strategy is then converted into dispatch instructions and sent to the emergency power dispatch execution terminal, so that dispatchers can execute dispatch actions according to the dispatch instructions received by the emergency power dispatch execution terminal.

[0011] Optionally, the steps of obtaining power grid parameter information for the target area and extracting power grid power supply layout parameters and power grid operation parameters for a reference time period from the power grid parameter information specifically include:

[0012] Upon receiving a coordinated scheduling request, extract the target scheduling period and scheduling area identifier of the target area from the coordinated scheduling request;

[0013] Using the dispatch area identifier, the power grid database is accessed, and the power grid parameter information of the target area stored in the power grid database is matched; wherein, the power grid parameter information includes the power grid power supply layout parameters of each power user and the power grid operation parameters for the reference time period.

[0014] Optionally, the step of predicting the power grid operation parameters of the target area during the target scheduling cycle based on the power grid operation parameters of the reference time period and using a power grid operation parameter prediction model specifically includes:

[0015] Extract the power consumption characteristics of each electricity user from the power grid operation parameters of the reference time period; wherein, the reference time period is configured as the first target number of scheduling cycles before the target scheduling cycle;

[0016] The power consumption characteristics of each electricity user in the reference period are input into a pre-built and trained power grid operation parameter prediction model to obtain the predicted power consumption value of each electricity user in the target area during the target scheduling cycle.

[0017] Optionally, before the step of predicting the power grid operation parameters of the target area during the target scheduling cycle based on the power grid operation parameters of the reference time period using a power grid operation parameter prediction model, the method further includes:

[0018] Obtain historical power grid operation parameters for the target area, extract power grid operation data for the training period from the historical power grid operation parameters, and establish a power consumption prediction sample for each electricity user;

[0019] Each power consumption prediction sample includes the power consumption parameters of the power user in each scheduling cycle and the power consumption characteristics of the first target number of scheduling cycles before that scheduling cycle.

[0020] The power consumption prediction sample of each electricity user is input into the pre-built recurrent neural network model of that electricity user for training, so as to obtain the power grid operation parameter prediction model of each electricity user in the target area after training.

[0021] Optionally, the step of constructing a scheduling priority list comprising several scheduling sub-regions based on power grid operation prediction parameters and the power grid power supply layout parameters specifically includes:

[0022] Extract the grid topology line location and the standard power value of each grid topology line for each electricity user from the grid power supply layout parameters of the reference time period;

[0023] Based on the location of each electricity user's grid topology and the predicted power consumption during the target scheduling period, calculate the actual power value of each grid topology line in the target area.

[0024] Based on the standard power value and the actual power value of the line, the line power load of each power grid topology line is determined;

[0025] Based on the line power load in descending order, a scheduling priority list is constructed for the scheduling sub-regions corresponding to several power grid topology lines.

[0026] Optionally, the steps to obtain the geographic location parameters and emergency power deployment information for each dispatch sub-region include:

[0027] Obtain the geographic location parameters of each scheduling sub-region, and extract the substation location information of the power grid topology lines from the geographic location parameters;

[0028] Based on the substation location information, an electronic map of the target area is invoked to extract road route information from the electronic map;

[0029] Access the emergency power deployment information database and extract the first deployment information of fixed emergency power and the second deployment information of mobile emergency power in each dispatch sub-region;

[0030] The first deployment information includes the first deployment location and the first power supply value of each fixed emergency power supply deployment, and the second deployment information includes the second deployment location, the second power supply value, and the moving speed of each mobile emergency power supply in its current deployment.

[0031] Optionally, based on geographical location parameters, first deployment information, and second deployment information, the steps for generating an emergency power dispatch strategy are as follows:

[0032] Based on the line power load of each dispatch sub-region in the dispatch priority list and the first power supply value of the fixed emergency power supply at the first deployment location in the dispatch sub-region, calculate the line power demand value of each dispatch sub-region in the dispatch priority list;

[0033] Based on the line power demand value of each dispatch sub-region, the second deployment location of the mobile emergency power supply in each dispatch sub-region, the substation location information, and the road route information, an emergency power supply dispatch strategy for the target region is generated for the target dispatch cycle and the second target number of dispatch cycles thereafter.

[0034] Optionally, based on the line power demand value of each dispatch sub-region, the second deployment location of the mobile emergency power supply in each dispatch sub-region, substation location information, and road route information, the emergency power supply dispatch strategy steps for the target region in the target dispatch cycle and the second target number of dispatch cycles thereafter are generated, specifically including:

[0035] By utilizing the power consumption characteristics of each electricity user in the power grid operation parameters during the reference period and the predicted power consumption value of the target scheduling cycle, and based on the power grid operation parameter prediction model, the predicted power consumption value of each electricity user in the second target number of scheduling cycles after the target scheduling cycle is obtained.

[0036] The first constraint is that the second power supply value of each dispatch sub-area after accessing the mobile emergency power supply is greater than the line power demand. The second constraint is that the movement time of each emergency power supply in each dispatch cycle within the target dispatch cycle and the second target number of dispatch cycles thereafter is less than the preset time. The objective is to minimize the overall movement distance of all emergency power supplies within the target dispatch cycle and the second target number of dispatch cycles thereafter. The mobile emergency power supply allocation scheme for the target area in each dispatch cycle within the target dispatch cycle and the second target number of dispatch cycles thereafter is then solved.

[0037] The dispatching actions of mobile emergency power supplies between each adjacent dispatching cycle are output as the emergency power supply dispatching strategy for the target area in the target dispatching cycle and the second target number of dispatching cycles thereafter.

[0038] Optionally, the emergency power dispatching strategy is converted into dispatching instructions and sent to the emergency power dispatching execution terminal, so that dispatchers can execute dispatching actions according to the dispatching instructions received by the emergency power dispatching execution terminal, specifically including:

[0039] The scheduling actions of each scheduling cycle in the emergency power scheduling strategy for the target area during the target scheduling cycle and the second target number of scheduling cycles thereafter are converted into scheduling instructions, and the scheduling instructions are sent to the emergency power scheduling execution terminal when the scheduling task of the scheduling cycle is executed.

[0040] The dispatcher executes the dispatching actions for the current dispatching period based on the dispatching instructions received by the emergency power dispatching terminal.

[0041] This invention also provides a novel integrated source-grid-load-storage collaborative optimization system for power systems, comprising:

[0042] The extraction module is used to obtain power grid parameter information of the target area, and extract the power grid power supply layout parameters and power grid operation parameters of the target area and the reference time period from the power grid parameter information;

[0043] The construction module is used to predict the power grid operation parameters of the target area in the target scheduling cycle based on the power grid operation parameters of the reference time period and the power grid operation parameter prediction model, and to construct a scheduling priority list containing several scheduling sub-regions according to the power grid operation prediction parameters and the power grid power supply layout parameters.

[0044] The acquisition module is used to acquire the geographical location parameters and emergency power deployment information of each scheduling sub-region; wherein, the emergency power deployment information includes the first deployment information of fixed emergency power in each scheduling sub-region and the second deployment information of mobile emergency power in each scheduling sub-region;

[0045] The execution module is used to generate an emergency power dispatching strategy based on geographical location parameters, first deployment information, and second deployment information, and to convert the emergency power dispatching strategy into dispatching instructions and send them to the emergency power dispatching execution terminal so that dispatchers can execute dispatching actions according to the dispatching instructions received by the emergency power dispatching execution terminal.

[0046] The beneficial effects of this invention are as follows: It proposes a novel integrated source-grid-load-storage collaborative optimization method and system for power systems. By extracting grid power supply layout parameters and grid operation parameters from the grid parameter information of the target area, and using a grid operation parameter prediction model to predict the grid operation prediction parameters for the target scheduling period based on the grid operation parameters, a scheduling priority list is constructed according to the grid operation prediction parameters and grid power supply layout parameters. Subsequently, by obtaining the geographical location parameters and emergency power supply deployment information of each scheduling sub-region in the scheduling priority list, and considering the emergency power supply access location and the deployment of fixed and mobile emergency power supplies in different scheduling sub-regions, a long-term, overall optimal scheduling is performed considering multiple different influencing factors. This generates a scheduling strategy for executing emergency power supplies within the power system, thereby executing the scheduling of mobile emergency power supplies in the target area, improving the scheduling effect of emergency power supply scheduling in the power system, alleviating regional load imbalance in the power system, and solving problems such as poor user experience for electricity users. Attached Figure Description

[0047] Figure 1 This is a flowchart illustrating the novel integrated source-grid-load-storage collaborative optimization method for power systems in an embodiment of the present invention.

[0048] Figure 2 This is a schematic diagram of the structure of a novel power system source-grid-load-storage integrated collaborative optimization system in an embodiment of the present invention.

[0049] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings.

[0050] Figure label:

[0051] 10 - Extraction module; 20 - Construction module; 30 - Acquisition module; 40 - Execution module. Detailed Implementation

[0052] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0053] Example 1:

[0054] like Figure 1 As shown, a novel integrated source-grid-load-storage collaborative optimization method for power systems includes:

[0055] S1: Obtain the power grid parameter information of the target area, and extract the power grid power supply layout parameters of the target area and the power grid operation parameters for the reference time period from the power grid parameter information;

[0056] S2: Based on the power grid operation parameters of the reference period, use the power grid operation parameter prediction model to predict the power grid operation prediction parameters of the target area in the target scheduling cycle, and construct a scheduling priority list containing several scheduling sub-regions according to the power grid operation prediction parameters and the power grid power supply layout parameters.

[0057] S3: Obtain the geographical location parameters and emergency power deployment information for each dispatch sub-region; wherein, the emergency power deployment information includes the first deployment information of fixed emergency power in each dispatch sub-region and the second deployment information of mobile emergency power in each dispatch sub-region;

[0058] S4: Based on the geographical location parameters, the first deployment information, and the second deployment information, generate an emergency power dispatching strategy, convert the emergency power dispatching strategy into dispatching instructions, and send them to the emergency power dispatching execution terminal so that dispatchers can execute dispatching actions according to the dispatching instructions received by the emergency power dispatching execution terminal.

[0059] It should be noted that in practical applications, the deployment and application of emergency power sources in the power system can improve the ability of urban power grids to respond to emergencies and meet the power supply needs of various emergencies. It is an indispensable part of the integrated coordination of power generation, grid, load, and storage in the power system. However, in the current process of emergency power source deployment in urban power grids, due to the different electricity demands of different users at different times, the different power supply capabilities of different grid lines, and the different emergency power source deployment situations in different regions, the deployment and dispatch of emergency power sources in urban power grids can only be carried out through short-term, individual-optimal dispatch based on manual experience. It is impossible to consider multiple different influencing factors for long-term, overall-optimal dispatch, resulting in problems such as unsatisfactory dispatching effect, regional load imbalance in the power system, and poor user experience.

[0060] To address the aforementioned issues, this embodiment extracts power grid supply layout parameters and power grid operation parameters from the power grid parameter information of the target area. Based on the power grid operation parameters, a power grid operation parameter prediction model is used to predict the power grid operation prediction parameters for the target scheduling period. Then, based on the power grid operation prediction parameters and power grid supply layout parameters, a scheduling priority list is constructed. Subsequently, by obtaining the geographical location parameters and emergency power supply deployment information of each scheduling sub-region in the scheduling priority list, and considering the emergency power supply access location and the deployment status of fixed and mobile emergency power supplies in different scheduling sub-regions, a long-term, overall optimal scheduling is performed considering multiple different influencing factors. This generates a scheduling strategy for executing emergency power supplies within the power system, thereby executing the scheduling of mobile emergency power supplies in the target area. This improves the scheduling effect of emergency power supply scheduling in the power system, alleviates regional load imbalance in the power system, and solves problems such as poor user experience for electricity users.

[0061] In a preferred embodiment, the steps of obtaining power grid parameter information for the target area and extracting power grid power supply layout parameters and power grid operation parameters for a reference time period from the power grid parameter information specifically include:

[0062] S11: Upon receiving a coordinated scheduling request, extract the target scheduling period and scheduling area identifier of the target area from the coordinated scheduling request;

[0063] S12: Using the dispatch area identifier, access the power grid database and match the power grid parameter information of the target area stored in the power grid database; wherein, the power grid parameter information includes the power grid power supply layout parameters of each power user and the power grid operation parameters for the reference time period.

[0064] Based on this, and using the power grid operation parameters for the reference period, the steps for predicting the power grid operation parameters for the target area during the target scheduling cycle using a power grid operation parameter prediction model specifically include:

[0065] S23: Extract the power consumption characteristics of each electricity user from the power grid operation parameters of the reference time period; wherein, the reference time period is configured as the first target number of scheduling cycles before the target scheduling cycle;

[0066] S24: Input the power consumption characteristics of each power user in the reference period into the pre-built and trained power grid operation parameter prediction model to obtain the predicted power consumption value of each power user in the target area during the target scheduling period.

[0067] Based on this, prior to the step of predicting the power grid operation parameters of the target area during the target scheduling cycle using the power grid operation parameter prediction model based on the power grid operation parameters of the reference period, the method further includes:

[0068] S21: Obtain historical power grid operation parameters for the target area, extract power grid operation data for the training period from the historical power grid operation parameters, and establish a power consumption prediction sample for each electricity user;

[0069] Each power consumption prediction sample includes the power consumption parameters of the power user in each scheduling cycle and the power consumption characteristics of the first target number of scheduling cycles before that scheduling cycle.

[0070] S22: Input the power consumption prediction sample of each electricity user into the pre-built recurrent neural network model of that electricity user for training, and obtain the power grid operation parameter prediction model of each electricity user in the target area after training.

[0071] In this embodiment, upon receiving a coordinated scheduling request, the target scheduling period and scheduling area identifier are extracted. Then, the scheduling area identifier is used to match the power grid parameter information of the target area in the power grid database. The power grid parameter information is then input into a pre-built and trained power grid operation parameter prediction model to predict the power consumption prediction value of each electricity user in the target area during the target scheduling period. This power consumption prediction value is used to determine the power load of each scheduling sub-area, providing data support for constructing a scheduling priority list.

[0072] In a preferred embodiment, the step of constructing a scheduling priority list comprising several scheduling sub-regions based on power grid operation prediction parameters and the power grid power supply layout parameters specifically includes:

[0073] S25: Extract the grid topology line location and the standard power value of each grid topology line for each power user from the grid power supply layout parameters of the reference time period;

[0074] S26: Based on the location of the power grid topology lines for each electricity user and the predicted power consumption during the target scheduling period, calculate the actual power value of each power grid topology line in the target area;

[0075] S27: Based on the standard power value of the line and the actual power value of the line, determine the line power load of each power grid topology line;

[0076] S28: Sort the lines according to their power load from largest to smallest, and construct a scheduling priority list for the scheduling sub-regions corresponding to several power grid topology lines.

[0077] Furthermore, the steps to obtain the geographic location parameters and emergency power deployment information for each dispatch sub-region specifically include:

[0078] S31: Obtain the geographical location parameters of each scheduling sub-region, and extract the substation location information of the power grid topology lines from the geographical location parameters;

[0079] S32: Based on the substation location information, call up the electronic map of the target area and extract the road route information from the electronic map;

[0080] S33: Access the emergency power deployment information database and extract the first deployment information of fixed emergency power and the second deployment information of mobile emergency power in each dispatch sub-region;

[0081] The first deployment information includes the first deployment location and the first power supply value of each fixed emergency power supply deployment, and the second deployment information includes the second deployment location, the second power supply value, and the moving speed of each mobile emergency power supply in its current deployment.

[0082] In this embodiment, after obtaining the predicted power consumption value for each electricity user during the target scheduling period, the actual power value of each power grid topology line is calculated using this predicted power consumption value. Then, based on the difference between the standard power value and the actual power value of each power grid topology line, the power load of each power grid topology line is determined. Following this, by acquiring the geographical location parameters and emergency power deployment information of each scheduling sub-region, the substation location information of the power grid topology lines, the road route information in the target area, and the first deployment information of fixed emergency power sources and the second deployment information of mobile emergency power sources are extracted, providing data support for subsequently solving the optimal emergency power dispatch strategy.

[0083] In a preferred embodiment, the step of generating an emergency power dispatch strategy based on geographical location parameters, first deployment information, and second deployment information specifically includes:

[0084] S41: Based on the line power load of each dispatch sub-region in the dispatch priority list and the first power supply value of the fixed emergency power supply at the first deployment location in the dispatch sub-region, calculate the line power demand value of each dispatch sub-region in the dispatch priority list;

[0085] S42: Based on the line power demand value of each dispatch sub-region, the second deployment location of the mobile emergency power supply in each dispatch sub-region, the substation location information, and the road route information, generate an emergency power supply dispatch strategy for the target region in the target dispatch cycle and the second target number of dispatch cycles thereafter.

[0086] Furthermore, based on the line power demand value of each dispatch sub-region, the second deployment location of the mobile emergency power supply in each dispatch sub-region, substation location information, and road route information, the emergency power supply dispatch strategy steps for the target area in the target dispatch cycle and the second target number of dispatch cycles thereafter are generated, specifically including:

[0087] S421: Using the power consumption characteristics of each power user in the power grid operation parameters of the reference period and the predicted power consumption value of the target scheduling period, based on the power grid operation parameter prediction model, obtain the predicted power consumption value of the second target number of scheduling periods after the target scheduling period for each power user;

[0088] S422: The first constraint is that the second power supply value of each dispatch sub-area after accessing the mobile emergency power supply is greater than the line power demand. The second constraint is that the movement time of each emergency power supply in each dispatch cycle within the target dispatch cycle and the second target number of dispatch cycles thereafter is less than the preset time. The objective is to minimize the overall movement distance of all emergency power supplies within the target dispatch cycle and the second target number of dispatch cycles thereafter. The mobile emergency power supply allocation scheme for the target area in each dispatch cycle within the target dispatch cycle and the second target number of dispatch cycles thereafter is then solved.

[0089] S423: Output the dispatching actions of the mobile emergency power supply between each adjacent dispatching cycle as the emergency power supply dispatching strategy for the target area in the target dispatching cycle and the second target number of dispatching cycles thereafter.

[0090] Based on this, the emergency power dispatch strategy is converted into dispatch instructions and sent to the emergency power dispatch execution terminal, so that dispatchers can execute dispatch actions according to the dispatch instructions received by the emergency power dispatch execution terminal, specifically including:

[0091] S43: Convert the scheduling action of each scheduling cycle in the emergency power scheduling strategy of the target area in the target scheduling cycle and the second target number of scheduling cycles thereafter into a scheduling instruction, and send the scheduling instruction to the emergency power scheduling execution terminal when executing the scheduling task of the scheduling cycle;

[0092] S44: The dispatcher executes the dispatching actions for the current dispatching period based on the dispatching instructions received by the emergency power dispatching terminal for the current dispatching period.

[0093] In this embodiment, by extracting the power grid supply layout parameters and power grid operation parameters from the power grid parameter information of the target area, and based on the power grid operation parameters, a power grid operation parameter prediction model is used to predict the power grid operation prediction parameters for the target scheduling period. Then, based on the power grid operation prediction parameters and the power grid supply layout parameters, a scheduling priority list is constructed. Subsequently, by obtaining the geographical location parameters and emergency power supply deployment information of each scheduling sub-region in the scheduling priority list, and considering the emergency power supply access location and the deployment of fixed and mobile emergency power supplies in different scheduling sub-regions, a long-term, overall optimal scheduling is performed considering multiple different influencing factors, with each scheduling sub-region after the mobile emergency power supply is scheduled. The first constraint is that the second power supply value of the region after connecting to the mobile emergency power supply is greater than the line power demand. The second constraint is that the movement time of each emergency power supply in each scheduling cycle within the target scheduling cycle and the subsequent second target number of scheduling cycles is less than the preset time. The objective is to minimize the overall movement distance of all emergency power supplies within the target scheduling cycle and the subsequent second target number of scheduling cycles. This generates a scheduling strategy for emergency power supplies within the power system to execute the scheduling of mobile emergency power supplies in the target region, thereby improving the scheduling effect of emergency power supply scheduling in the power system, alleviating regional load imbalance in the power system, and solving problems such as poor user experience.

[0094] This invention also provides a novel integrated source-grid-load-storage collaborative optimization system for power systems, the system comprising:

[0095] Example 2:

[0096] Reference Figure 2 , Figure 2 This is a schematic diagram of a novel integrated power system source-grid-load-storage collaborative optimization system provided in an embodiment of the present invention.

[0097] like Figure 2 As shown, a novel integrated source-grid-load-storage collaborative optimization system for a power system, used in the aforementioned novel integrated source-grid-load-storage collaborative optimization method for a power system, includes:

[0098] Extraction module 10 is used to obtain power grid parameter information of the target area, and extract the power grid power supply layout parameters of the target area and the power grid operation parameters of the reference time period from the power grid parameter information;

[0099] The construction module 20 is used to predict the power grid operation prediction parameters of the target area in the target scheduling cycle based on the power grid operation parameters of the reference time period and the power grid operation prediction model, and to construct a scheduling priority list containing several scheduling sub-regions according to the power grid operation prediction parameters and the power grid power supply layout parameters.

[0100] The acquisition module 30 is used to acquire the geographical location parameters and emergency power deployment information of each scheduling sub-region; wherein, the emergency power deployment information includes the first deployment information of fixed emergency power in each scheduling sub-region and the second deployment information of mobile emergency power in each scheduling sub-region;

[0101] The execution module 40 is used to generate an emergency power dispatch strategy based on geographical location parameters, first deployment information, and second deployment information, and to convert the emergency power dispatch strategy into dispatch instructions and send them to the emergency power dispatch execution terminal so that dispatchers can perform dispatch actions according to the dispatch instructions received by the emergency power dispatch execution terminal.

[0102] The specific implementation method of the new power system source-grid-load-storage integrated collaborative optimization system of this application is basically the same as the above-mentioned new power system source-grid-load-storage integrated collaborative optimization method embodiment, and will not be repeated here.

[0103] In the description of the embodiments of the present invention, it should be understood that the terms "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "center," "top," "bottom," "top," "bottom," "inner," "outer," "inner side," and "outer side," etc., indicating the orientation or positional relationship, are based on the orientation or positional relationship shown in the accompanying drawings and are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the present invention. "Inner side" refers to the interior or enclosed area or space. "Outer perimeter" refers to the area surrounding a specific component or specific area.

[0104] In the description of embodiments of the present invention, the terms "first," "second," "third," and "fourth" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first," "second," "third," or "fourth" may explicitly or implicitly include one or more of that feature. In the description of the present invention, unless otherwise stated, "a plurality of" means two or more.

[0105] In the description of the embodiments of the present invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," "joining," and "assembly" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal communication between two components. Those skilled in the art can understand the specific meaning of the above terms in the present invention based on the specific circumstances.

[0106] In the description of embodiments of the present invention, specific features, structures, materials or characteristics may be combined in any suitable manner in one or more embodiments or examples.

[0107] In the description of the embodiments of the present invention, it should be understood that "-" and "~" represent a range between two numerical values, and this range includes the endpoints. For example, "AB" represents a range greater than or equal to A and less than or equal to B. "A~B" represents a range greater than or equal to A and less than or equal to B.

[0108] In the description of embodiments of the present invention, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this document generally indicates that the preceding and following related objects have an "or" relationship.

[0109] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for source-grid-load-storage integrated collaborative optimization in a power system, characterized in that, The method comprises the following steps: Obtaining power grid parameter information of a target area, extracting power grid power supply layout parameters of the target area and power grid operation parameters of a reference period from the power grid parameter information; Based on the power grid operation parameters of the reference period, using a power grid operation parameter prediction model to predict power grid operation prediction parameters of the target area in a target scheduling period, and constructing a scheduling priority list comprising a plurality of scheduling sub-areas according to the power grid operation prediction parameters and the power grid power supply layout parameters; wherein the scheduling priority list of the plurality of scheduling sub-areas is sorted according to the line power load of each power grid topology line in descending order of line power load, thereby constructing the scheduling priority list; Obtaining geographical location parameters and emergency power supply deployment information of each scheduling sub-area; wherein the emergency power supply deployment information comprises first deployment information of fixed emergency power supplies in each scheduling sub-area and second deployment information of mobile emergency power supplies in each scheduling sub-area; wherein the first deployment information comprises a first deployment position and a first power supply power value of each fixed emergency power supply, and the second deployment information comprises a second deployment position, a second power supply power value and a moving speed of each mobile emergency power supply in the current deployment; Generating an emergency power supply scheduling strategy according to the geographical location parameters, the first deployment information and the second deployment information, and converting the emergency power supply scheduling strategy into scheduling instructions and sending the scheduling instructions to an emergency power supply scheduling execution terminal, so that the scheduling personnel perform scheduling actions according to the scheduling instructions received by the emergency power supply scheduling execution terminal; the emergency power supply scheduling strategy is also associated with the line power demand of each scheduling sub-area.

2. The power system source-grid-load-storage integrated collaborative optimization method according to claim 1, characterized in that, The step of obtaining power grid parameter information of a target area and extracting power grid power supply layout parameters of the target area and power grid operation parameters of a reference period from the power grid parameter information comprises: Upon receiving a cooperative scheduling request, extracting a target scheduling period and a scheduling area identifier of the target area in the cooperative scheduling request; Using the scheduling area identifier to access a power grid database and matching power grid parameter information of the target area stored in the power grid database; wherein the power grid parameter information comprises power grid power supply layout parameters of each power user and power grid operation parameters of a reference period.

3. The power system source-grid-load-storage integrated collaborative optimization method according to claim 2, characterized in that, The step of predicting power grid operation prediction parameters of the target area in a target scheduling period based on the power grid operation parameters of the reference period using a power grid operation parameter prediction model comprises: Extracting power consumption power characteristics of each power user in the reference period; wherein the reference period is configured as a first target number of scheduling periods before the target scheduling period; Inputting the power consumption power characteristics of each power user in the reference period into a pre-constructed and trained power grid operation parameter prediction model to obtain power consumption power prediction values of each power user in the target area in the target scheduling period.

4. The power system source-grid-load-storage integrated collaborative optimization method according to claim 3, characterized in that, Before the step of predicting power grid operation prediction parameters of the target area in a target scheduling period based on the power grid operation parameters of the reference period using a power grid operation parameter prediction model, it further comprises: The historical power grid operation parameters of the target area are acquired, the power grid operation data of a training period in the historical power grid operation parameters is extracted, and power consumption power prediction samples of each power consumption user are established; Each power consumption power prediction sample includes power consumption power parameters of the power consumption user in each scheduling period and power consumption power features of the first target number of scheduling periods before the scheduling period; The power consumption power prediction sample of each power consumption user is input into a recurrent neural network model previously constructed for the power consumption user for training, and a power grid operation parameter prediction model of each power consumption user in the target area is obtained after training.

5. The power system source-grid-load-storage integrated collaborative optimization method according to claim 1, characterized in that, According to the power grid operation prediction parameters and the power grid power supply layout parameters, a scheduling priority list of a plurality of scheduling sub-areas is constructed, specifically including: The power grid topology line position of each power consumption user and the line standard power value of each power grid topology line in the power grid power supply layout parameters of the reference period are extracted; According to the power grid topology line position of each power consumption user and the power consumption power prediction value in the target scheduling period, the line actual power value of each power grid topology line in the target area is calculated; Based on the line standard power value and the line actual power value, the line power load of each power grid topology line is determined; The scheduling priority list of the scheduling sub-area corresponding to the plurality of power grid topology lines is constructed in the order of the line power load from large to small.

6. The power system source-grid-load-storage integrated collaborative optimization method according to claim 5, characterized in that, The geographic position parameters and emergency power supply deployment information of each scheduling sub-area are acquired, specifically including: The geographic position parameters of each scheduling sub-area are acquired, and the substation position information of the power grid topology line in the geographic position parameters is extracted; Based on the substation position information, an electronic map of the target area is called, and road route information in the electronic map is extracted; The first deployment information of the fixed emergency power supply and the second deployment information of the mobile emergency power supply deployment in each scheduling sub-area are extracted by accessing an emergency power supply deployment information library.

7. The power system source-grid-load-storage integrated collaborative optimization method according to claim 6, characterized in that, According to the geographic position parameters, the first deployment information and the second deployment information, an emergency power supply scheduling strategy is generated, specifically including: Based on the line power load of each scheduling sub-area in the scheduling priority list and the first power supply power value of the fixed emergency power supply in the first deployment position in the scheduling sub-area, the line power demand value of each scheduling sub-area in the scheduling priority list is calculated; According to the line power demand value of each scheduling sub-area, the second deployment position of the mobile emergency power supply deployment in each scheduling sub-area, the substation position information and the road route information, an emergency power supply scheduling strategy of the target area in the target scheduling period and the second target number of scheduling periods thereafter is generated.

8. The power system source-grid-load-storage integrated collaborative optimization method according to claim 7, characterized in that, According to the line power demand value of each scheduling sub-area, the second deployment position of the mobile emergency power supply deployment in each scheduling sub-area, the substation position information and the road route information, an emergency power supply scheduling strategy of the target area in the target scheduling period and the second target number of scheduling periods thereafter is generated. The power consumption feature of each power user in the grid operation parameter of the reference period and the power consumption prediction value of the target scheduling period are used to obtain the power consumption prediction value of each power user in the second target number of scheduling periods after the target scheduling period based on a grid operation parameter prediction model; A first constraint condition is that the second power supply value of each scheduling sub-region after accessing the mobile emergency power supply is greater than the line power demand value, a second constraint condition is that the mobile time of each emergency power supply in each scheduling period in the target scheduling period and the second target number of scheduling periods thereafter is less than a preset time value, and a target is that the overall mobile distance of all emergency power supplies in the target scheduling period and the second target number of scheduling periods thereafter is the shortest. A mobile emergency power supply distribution scheme of the target region in each scheduling period in the target scheduling period and the second target number of scheduling periods thereafter is solved. The scheduling action of the mobile emergency power supply between each adjacent scheduling period is output as the emergency power supply scheduling strategy of the target region in the target scheduling period and the second target number of scheduling periods thereafter. 9.The power system source-grid-load-storage integrated collaborative optimization method of claim 5, wherein, The emergency power supply scheduling strategy is converted into a scheduling instruction and sent to an emergency power supply scheduling execution terminal, so that the scheduling personnel perform the scheduling action step according to the scheduling instruction received by the emergency power supply scheduling execution terminal, specifically including: The scheduling action of each scheduling period in the emergency power supply scheduling strategy of the target region in the target scheduling period and the second target number of scheduling periods thereafter is converted into a scheduling instruction, and the scheduling instruction is sent to the emergency power supply scheduling execution terminal when the scheduling task of the scheduling period is performed; The scheduling personnel perform the scheduling action of the current scheduling period according to the scheduling instruction of the current scheduling period received by the emergency power supply scheduling execution terminal.

10. A source-grid-load-storage integrated collaborative optimization system under a power system, characterized in that, It includes: An extraction module is configured to obtain grid parameter information of a target region, and extract grid power supply layout parameters of the target region and grid operation parameters of a reference period from the grid parameter information; A construction module is configured to predict grid operation prediction parameters of the target region in a target scheduling period based on the grid operation parameters of the reference period and using a grid operation parameter prediction model, and construct a scheduling priority list including a plurality of scheduling sub-regions according to the grid operation prediction parameters and the grid power supply layout parameters; wherein the scheduling priority list of the plurality of scheduling sub-regions is sorted in descending order of line power load according to the line power load of each grid topology line, thereby constructing the scheduling priority list; An acquisition module is configured to obtain geographical location parameters and emergency power supply deployment information of each scheduling sub-region; wherein the emergency power supply deployment information includes first deployment information of fixed emergency power supplies in each scheduling sub-region and second deployment information of mobile emergency power supplies in each scheduling sub-region; wherein the first deployment information includes a first deployment location and a first power supply value of each fixed emergency power supply, and the second deployment information includes a second deployment location, a second power supply value, and a moving speed of each mobile emergency power supply in the current deployment. The execution module is configured to generate an emergency power supply scheduling strategy according to the geographic position parameter, the first deployment information and the second deployment information, and convert the emergency power supply scheduling strategy into a scheduling instruction and send the scheduling instruction to an emergency power supply scheduling execution terminal, so that a dispatcher performs a scheduling action according to the scheduling instruction received by the emergency power supply scheduling execution terminal; the emergency power supply scheduling strategy is further associated with the line power demand of each scheduling sub-region.

Images