Methods, devices, equipment and media for multi-entity source-load interval matching control within the alliance

Abstract

This invention discloses a method, apparatus, equipment, and medium for multi-entity source-load interval matching control within a consortium. The method includes: determining the source-load power purchase / sale type based on the net output power of the source-loads; introducing a distance parameter α to limit the distance between cooperating source-loads; dividing cooperating source-load consortia according to consortium formation rules; establishing a multi-entity source-load interval matching control mechanism within the consortium, constructing an objective function for consortium source-load interval matching and constraints on the quantity and price of power purchase / sale during the matching process, calculating the final consortium utility for each effective consortium; and using the interval Shapley value method to achieve a fair distribution of consortium utility among cooperating source-load members. This method can ensure good economic efficiency for multi-entity source-loads while satisfying power system constraints and can be widely applied in multi-entity source-load groups.

Description

Technical Field

[0001] This invention belongs to the field of new energy consumption and power market transaction optimization technology, specifically involving a method, device, equipment and medium for multi-entity source-load interval matching control within an alliance. Background Technology

[0002] The penetration rate of power systems is gradually increasing. Sources and loads can be defined as a group of interconnected loads and distributed energy sources, potentially consisting of a power generation-consumption system comprised of photovoltaic power generation, wind power generation, battery storage, and electricity users. Although the concept of sources and loads is becoming increasingly generalized, their impact on the electricity market is becoming more profound as their volume increases year by year. First, the different stakeholders belonging to sources and loads have a strong desire to profit from selling electricity to the grid and to meet their own needs by purchasing electricity. The complex grid-connection and purchase behaviors (uneven time distribution and large fluctuations in electricity volume) pose a significant challenge to the stable operation of the electricity market. Second, the State Grid Corporation's electricity market reform action plan has created competition among different sources and loads, increasing the difficulty of electricity market management. These problems make it difficult for sources and loads to achieve optimal operational efficiency. Therefore, unified coordination and guidance of multi-entity sources and loads from the perspective of the electricity market is key to solving these problems.

[0003] Current research largely focuses on the trading control methods and operational issues of independent power sources and loads within power systems and markets, lacking research on matching control among multiple power sources and loads. Although some cooperative game theory-based methods have been applied to the cooperative matching operation of multiple power sources and loads, they do not consider the uncertainties in the matching process. That is, affected by the random disturbances of new energy sources and loads, it is difficult to focus on a precise point in the matching process. Even if the matching quantity and price are estimated, deviations will still occur in the actual matching control process, causing matching instability and imbalance. Summary of the Invention

[0004] The purpose of this invention is to provide a method, apparatus, equipment and medium for multi-entity source-load interval matching control within an alliance, so as to solve the problem that source-load is difficult to achieve optimal efficiency operation in the prior art.

[0005] To achieve the above objectives, the present invention adopts the following technical solution:

[0006] Firstly, a method for controlling the matching of multiple source load intervals within a consortium includes the following steps:

[0007] The power purchase and sale type of the source load is determined based on the net output power of the source load; wherein, the power purchase and sale type of the source load includes power sale load and power purchase load;

[0008] Source loads within a distance range α form alliances, and each alliance contains at least one purchasing power load and one selling power load. The source loads within the alliances are divided into a purchasing power load set D and a selling power load set S.

[0009] Each power supply load group is selected for its ranking. The highest bid price range and bid quantity range for the power supply load relative to the power supply load are determined, along with the price range for the power supply load. When the bid price of the power supply load is not lower than the price quoted by the power supply load, both the buyer and seller agree to proceed.

[0010] Successful matching means that the power purchase load that meets all electricity demand or the power sales load that supplies all remaining electricity will be removed from the corresponding power source set. This power source matching process is repeated until the power purchase or power sales load set is empty or no more power purchase or power sales load pairs can be matched. The utility increment of each power source load pair is accumulated to obtain the total alliance utility. The order of each member in the power purchase and power sales load sets will be combined and tried. The total alliance utility of each alliance will be calculated, and the largest total alliance utility will be taken as the final alliance utility.

[0011] Based on the ultimate utility of the alliance, the interval Shapley value method is used to achieve a fair distribution of alliance utility among cooperative source loads.

[0012] Furthermore, the step of determining the power purchase / sale type of the source load based on the net output power of the source load specifically includes:

[0013] A source load is defined as a power-selling load with surplus power if its expected net power output is greater than zero; a source load is defined as a power-purchasing load with demand power if its expected net power output is less than zero.

[0014] Furthermore, the source loads within the distance range α are connected via dedicated power lines.

[0015] Furthermore, the method for calculating the total alliance utility of each alliance is as follows: construct the source-load interval matching objective function within the alliance and the quantity constraints and price constraints of electricity purchase and sale during the matching process, and calculate the total alliance utility of each alliance.

[0016] Furthermore, the objective function for matching the source load interval within the alliance is as follows:

[0017]

[0018] Where Λ and θ are the sums of all random permutations of the members in the power supply load set S and the power supply load set D, respectively. In alliance C, the current member sequences of S and D are ζ and ζ, respectively. The effectiveness of alliances at that time.

[0019] Furthermore, the step of achieving a fair allocation of coalition utility among cooperative source loads based on the coalition's final utility using the interval Shapley value method specifically includes:

[0020] For a coalition C corresponding to the coalition's final utility, the coalition's final utility is distributed among any source loads that form coalition C, with each source load receiving a lower and upper bound of the shapley value that satisfies the utility distribution.

[0021] Furthermore, the lower and upper bounds of the Shapley value are as follows:

[0022]

[0023]

[0024] In the formula, C = {1, 2, ..., n} represents the k-th source load in the consortium C and k ∈ C, and |C| is the number of source loads in the consortium C. The utility allocated to the k-th source load participating in the alliance C is [x] k Let c be a subset of consortium C, representing all sub-consolidations that source charges in C can form. Let |c| be the number of MGs in sub-consolidation c, and let [v(c)] be the utility of sub-consolidation c, where [ν(c)] = [ν(c)]. - ,ν(c) + ].

[0025] Secondly, a multi-entity source-load interval matching control device within an alliance includes:

[0026] The classification module is used to determine the power purchase and sale type of the source load based on the net output power of the source load; wherein, the power purchase and sale type of the source load includes power sale load and power purchase load;

[0027] The combination module is used to form alliances of source loads within a distance range α, and each alliance contains at least one purchasing power load and one selling power load, and divides the source loads in the alliance into a purchasing power load set D and a selling power load set S.

[0028] The calculation module is used to select the order of one member of each power source set, determine the highest bid price range and bid quantity range for each power source set, and the bid price range for each power source set. When the bid price of the power source set is not lower than the bid price of the power source set, the buyer and seller are successfully matched. The power source set that meets all electricity demand or the power source set that supplies all remaining electricity will be removed from the corresponding power source set. This power source set matching process is repeated until the power source set is empty or no more power source set can be matched. The utility increment of each power source set is accumulated to obtain the total alliance utility. The order of each member in the power source set and the power source set will be combined and tried. The total alliance utility of each alliance will be calculated, and the maximum total alliance utility will be taken as the final alliance utility.

[0029] The allocation module is used to achieve fair allocation of coalition utility among cooperative source loads based on the coalition's final utility and employs the interval Shapley value method.

[0030] Thirdly, an electronic device includes a processor and a memory, the processor being configured to execute a computer program stored in the memory to implement the multi-subject source-load interval matching control method within the alliance as described above.

[0031] Fourthly, a computer-readable storage medium stores at least one instruction that, when executed by a processor, implements the multi-subject source-load interval matching control method within a consortium as described above.

[0032] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0033] 1) The multi-entity source-load interval matching control method within an alliance provided by this invention considers multiple source-load entities and can achieve matching control between source-load entities in the form of a cooperative alliance. It establishes a multi-entity source-load interval matching control mechanism within the alliance, builds an interval matching model within the alliance, and formulates a source-load alliance utility allocation scheme based on the interval Shapley value method to achieve fair allocation of source-load utility. The method involved in this invention can ensure good economic efficiency for multi-entity source-load entities under power system constraints and can be widely applied in multi-entity source-load groups (rural multi-user photovoltaic poverty alleviation power stations, industrial park interconnected source-load groups).

[0034] 2) The multi-entity source-load interval matching control method within the alliance provided by this invention differs from the single-source-load electricity purchase and sale method in the electricity market. This scheme allows source loads to match with their neighboring source loads, promoting mutual cooperation among source loads and realizing regional energy complementary utilization, which can effectively reduce their dependence on the upper-level power grid. Unlike deterministic matching control methods between source loads, the proposed method considers the impact of random disturbances in new energy sources and loads, as well as the uncertainty of the purchase and sale power load matching price. It uses interval numbers to represent the matching quantity and price of source loads, expanding the redundancy and correlation of alliance transactions, and reducing the impact of uncertainties on the source-load matching control effect.

[0035] 3) The multi-entity source-load interval matching control method provided by the present invention can effectively reduce power transmission loss, increase the electricity sales revenue of power selling loads, and reduce the electricity purchase cost of power purchasing loads, so that the source-loads in the alliance can obtain higher expected individual utility and achieve win-win cooperation among multiple source-loads. Attached Figure Description

[0036] The accompanying drawings, which form part of this application, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an undue limitation of the invention. In the drawings:

[0037] Figure 1 This is a flowchart illustrating a multi-entity source-load interval matching control method within an alliance according to the present invention.

[0038] Figure 2 This is a structural block diagram of a multi-entity source load interval matching control device within an alliance according to the present invention;

[0039] Figure 3 This is a structural block diagram of an electronic device according to the present invention. Detailed Implementation

[0040] The present invention will now be described in detail with reference to the accompanying drawings and embodiments. It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other.

[0041] The following detailed description is exemplary and intended to provide further detailed explanation of the invention. Unless otherwise specified, all technical terms used in this invention have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains. The terminology used in this invention is for the purpose of describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention.

[0042] Example 1

[0043] This invention provides a multi-entity source-load interval matching control method within an alliance. By considering the possibility of adjacent source loads forming alliances and cooperating with each other, it achieves complementary regional energy utilization. First, the source load's power purchase / sale type is determined based on the net output power of the source load; a source-load alliance formation rule is established, and the alliance is divided into power purchase load sets and power sale load sets; second, an interval matching mechanism within the alliance is established to determine successfully matched power purchase / sale load pairs and the final alliance utility; finally, a fair allocation scheme for alliance utility among cooperating source loads based on the interval Shapley value method is established. This method can consider the uncertainty of matching quantity and matching price during the multi-entity source-load matching control process, achieve complementary energy utilization among cooperating source loads, reduce power transmission losses, and improve the individual utility of cooperating source loads. It can be widely applied in multi-entity source-load groups (rural multi-user photovoltaic poverty alleviation power stations, industrial park interconnected microgrid groups).

[0044] like Figure 1 As shown, a multi-entity source load interval matching control method within a consortium includes the following steps:

[0045] S1. Determine the power purchase / sale type of the source load based on the net output power of the source load; wherein, the power purchase / sale type of the source load includes power sale load and power purchase load.

[0046] Specifically, the step of determining the power purchase / sale type of the source load based on the net output power of the source load includes:

[0047] If a source load has a expected net power output greater than zero, it is defined as a power-selling load with surplus power, and its surplus power is represented as an interval variable. If the expected net power output of a source load is less than zero, it is defined as a purchasing power load with power demand, and its power demand is expressed as an interval variable.

[0048] S2. Source loads within a distance range α form an alliance, and each alliance contains at least one purchasing power load and one selling power load. The source loads within the alliance are divided into a purchasing power load set D and a selling power load set S.

[0049] The source loads within the distance range α are connected by dedicated power lines.

[0050] Specifically, a distance range α is set to limit the distance between cooperative source loads, so that the distance between the connecting lines between cooperative source loads is kept within a reasonable range, avoiding unreasonable source load alliances.

[0051] S3. Matching of source load intervals and calculation of coalition utility based on exhaustive bilateral auction theory.

[0052] The order of one member from each power source set is selected, and the highest bid price range and bid quantity range for each power source set are determined. The price range for each power source set is also determined. When the bid price of the power source set is not lower than the price of the power source set, the buyer and seller are successfully matched. The power source set that satisfies all electricity demand or supplies all remaining electricity is removed from the corresponding power source set. This power source set matching process is repeated until the power source set is empty or no more power source sets can be matched. The utility increment of each power source set is accumulated to obtain the total alliance utility. Each member order in both the power source set and the power source set is combined and tested. The total alliance utility of each alliance is calculated, and the largest total alliance utility is taken as the final alliance utility.

[0053] The method for calculating the total alliance utility of each alliance is as follows: Construct an objective function for matching source-load intervals within the alliance, and define the constraints on electricity purchase and sale quantities and prices during the matching process, to calculate the total alliance utility of each alliance. The specific steps are as follows:

[0054] 1) Establish the objective function for multi-subject source-load interval matching within the alliance:

[0055]

[0056] Where Λ and θ are the sums of all random permutations of the members in the power supply load set S and the power supply load set D, respectively. In alliance C, the current member sequences of S and D are ζ and ζ, respectively. The utility of the alliance at that time can be calculated by equation (2), which sums the individual utility increment of each successfully matched source-load pair from independent power purchase and sale to matching with source-loads within the alliance and purchasing and selling the same amount of power. It is then expressed as the standard form of interval numbers by equation (3).

[0057]

[0058]

[0059] In the formula W g The unit electricity price for a distribution station (DS); Assuming that power supply load j supplies the same amount of electricity as power purchase load i to DS, the actual amount of electricity received by DS is [P]. oj，R The interval boundary value; The amount of electricity supplied by DS to source load i [P] oi，R The interval boundary value is determined so that the actual power received by source load i is equal to the actual power received by source load j.

[0060] 2) Power supply load and corresponding power transmission losses

[0061] Purchase power supply to meet your own power needs [d] i ], should be obtained from areas with surplus electricity [e j The amount of electricity purchased by the power supply load j [P] ij and line losses caused during power transmission [P] ij，L It can be calculated using equations (4) and (5).

[0062]

[0063]

[0064] In the formula U M It is the voltage level of the source load, R ij It is the resistance between the seller's source charge j and the buyer's source charge i.

[0065] 3) Actual power supply and corresponding power transmission losses

[0066] Since the surplus power of source load j may not be able to fully meet the power demand of source load i, the total amount of power that source load j can actually supply to source load i [P] is limited. ij，S It can be expressed as the following formula:

[0067]

[0068] Substitute [P] into formula (5) ij，S The actual amount of electricity received by source load i from source load j [P] ij，R] can be calculated as [P] ij，S The corresponding line loss during power transmission [P] ij，L The difference between:

[0069]

[0070] 4) Source charge i in order to actually receive [P] ij，R The amount of electricity that needs to be purchased from DS [P] oi，R ]:

[0071]

[0072] In the formula, Roi is the resistance from the power supply charge i to DS; U D β is the voltage level on the DS side; β is the transformer loss fraction on the DS side.

[0073] 5) The amount of electricity that power supplier j will actually supply to power purchaser i [P] ij，S The electricity supplied to DS, and the actual electricity received by DS [P] oj，R ], for [P ij，S And the corresponding line loss during circuit transmission [P] oj，L The difference between:

[0074]

[0075]

[0076] In the formula R oj It is the resistor from the power supply charge j to DS.

[0077] 6) The highest bid [Hi] of power purchase load i against the corresponding power supply load j:

[0078] Source i is to obtain the corresponding [P] ij，R [H] is the highest bid willing to pay per unit of electricity for source load j. i As shown in (11):

[0079]

[0080] The highest bid of source load i [H] i Transform into the standard form of interval numbers:

[0081]

[0082] 7) The lowest acceptable price for the power supply load [L] j ]:

[0083] The lowest acceptable price for any purchased power load [L] j As shown in the calculation by formula (13):

[0084]

[0085] The lowest acceptable bid for source load j [L] j Transform into the standard form of interval numbers:

[0086]

[0087] Only when the bid price of the power supply load i is [H] i [L] The lowest acceptable price not lower than the power supply load (j) j Only when source load i and source load j are matched can the complementary use of electricity between source loads be realized.

[0088] The above model reflects the matching of source and load intervals within the coalition and determines the maximum coalition utility.

[0089] S4. After obtaining the maximum utility of each coalition, based on the coalition's final utility, the interval Shapley value method is used to achieve a fair allocation of coalition utility among cooperative source loads. Specifically, for coalition C corresponding to the coalition's final utility, the coalition's final utility is allocated among any source loads that form coalition C, and the lower and upper bounds of the Shapley value obtained by each source load satisfying the utility allocation are determined.

[0090] The lower and upper bounds of the Shapley value are as follows:

[0091]

[0092]

[0093] in

[0094] In the formula, C = {1, 2, ..., n} represents the k-th source load in the consortium C and k ∈ C, and |C| is the number of source loads in the consortium C. The utility allocated to the k-th source load participating in the alliance C is [x] k Let c be a subset of consortium C, representing all sub-consolidations that source charges in C can form. Let |c| be the number of MGs in sub-consolidation c, and let [v(c)] be the utility of sub-consolidation c, where [v(c)] = [v(c)]. - , v(c) + ].

[0095] The Shapley values ​​used are set with the lower bound being the left endpoint minus the right endpoint, and the upper bound being the right endpoint minus the left endpoint, effectively avoiding the unreasonable phenomenon that the right endpoint of the interval value is less than the left endpoint.

[0096] The following specific implementation examples will be used to verify this solution.

[0097] Experiment 1:

[0098] This invention was implemented in a matching control scenario among 12 randomly generated source-loads within a 60 km × 60 km distribution network area, where DS is located at the center of the area. The proposed method was compared with a method that allows source-loads to independently purchase and sell electricity to DS to verify the performance of the proposed multi-entity source-load interval matching control method within a consortium.

[0099] The output power information and location information of 12 randomly generated source loads in the power distribution network are shown in Table 1.

[0100] Table 1

[0101] League 1

[0102] Source number Position coordinates Power Information Purchase power supply 1 (16，-7.2) [35，40] Purchase power supply 7 (22，-4.5) [20，25] Power supply load 10 (24，-9.5) [81，91]

[0103] League 2

[0104] Source number Position coordinates Power Information Power supply load 6 (-3.5，-15.5) [43，48] Purchase power supply 12 (-7.8，-10.2) [66，72]

[0105] League of Legends 3

[0106] Source number Position coordinates Power Information Power supply load 8 (-13，-18.9) [71，76] Purchase power supply 4 (-5.1，22.3) [36，45] Purchase power supply 11 (-8，13.1) [34，40]

[0107] League 4

[0108] Source number Position coordinates Power Information Purchase power supply 9 (20.5，19) [30，34] Power supply load 5 (15.3，20.7) [15，23] Power supply load 2 (16.3，14.3) [31，37]

[0109] After applying the proposed coalition partitioning method, a total of 4 coalitions were generated. Coalition 1 consists of source payload 1, source payload 7, and source payload 10; coalition 2 consists of source payload 6 and source payload 12; coalition 3 consists of source payload 4, source payload 8, and source payload 11; and finally, coalition 4 consists of source payload 2, source payload 5, and source payload 9.

[0110] After applying the exhaustive bilateral auction theory-based source-load interval matching algorithm to each valid alliance and obtaining the final alliance utility, the interval Shapley value method is used to allocate utility among the source-load members within the alliance. Compared with traditional source-loads purchasing and selling electricity with DS individually, the reduction in line transmission losses, the increase in individual utility, and the purchase-and-sell ratio of participating source-loads are shown in Table 2.

[0111] Table 2

[0112] Source Load Index Line loss reduction ratio Increase in utility Electricity purchase and sale ratio 1 8.81％ 6.158％ 100％ 2 49.05％ 7.02％ 54.99％ 3 0％ 0％ 0％ 4 15.78％ 10.99％ 100％ 5 53.11％ 13..94％ 100％ 6 15.04％ 8.55％ 100％ 7 70.88％ 10.77％ 100％ 8 42.2％ 14.27％ 14.27％ 9 77.15％ 11.09％ 100％ 10 60.02％ 12.41％ 79.43％ 11 40.94％ 4.67％ 56.70％ 12 18.69％ 8.07％ 77.25％

[0113] It can be seen that the proposed method (multi-entity source-load interval matching control method within the alliance) significantly reduces power transmission losses during the source-load power purchase and sale process, and increases the individual utility of participating source-loads. In addition, the power purchase and sale ratio of cooperating source-loads shows that the source-load matching control method can effectively reduce the dependence of source-loads on the upper-level power grid and reduce the burden on the upper-level power grid.

[0114] To verify the effectiveness of the proposed multi-entity source-load interval matching control method within the alliance, interval matching control was studied for distribution networks containing different numbers of source loads. For different scenarios with 5 to 18 source loads in the network, the average reduction ratio of line loss and the average individual utility increment ratio of the proposed multi-entity source-load interval matching control method within the alliance are shown in Table 3.

[0115] Table 3

[0116]

[0117] As can be seen from the table, compared with the traditional independent source load and DS to purchase and sell electricity, the proposed multi-subject source load interval matching control method in the alliance can effectively reduce the power transmission loss of source load and improve the individual utility of source load when the distribution network contains different numbers of source loads.

[0118] Example 2

[0119] like Figure 2 As shown, a multi-entity source-load interval matching control device within a consortium includes:

[0120] The classification module is used to determine the power purchase and sale type of the source load based on the net output power of the source load; wherein, the power purchase and sale type of the source load includes power sale load and power purchase load;

[0121] The classification module specifically includes:

[0122] A source load is defined as a power-selling load with surplus power if its expected net power output is greater than zero; a source load is defined as a power-purchasing load with demand power if its expected net power output is less than zero.

[0123] The combination module is used to form alliances of source loads within a distance range α, and each alliance contains at least one purchasing power load and one selling power load, and divides the source loads in the alliance into a purchasing power load set D and a selling power load set S.

[0124] The calculation module is used to select the order of one member of each power source set, determine the highest bid price range and bid quantity range for each power source set, and the bid price range for each power source set. When the bid price of the power source set is not lower than the bid price of the power source set, the buyer and seller are successfully matched. The power source set that meets all electricity demand or the power source set that supplies all remaining electricity will be removed from the corresponding power source set. This power source set matching process is repeated until the power source set is empty or no more power source set can be matched. The utility increment of each power source set is accumulated to obtain the total alliance utility. The order of each member in the power source set and the power source set will be combined and tried. The total alliance utility of each alliance will be calculated, and the maximum total alliance utility will be taken as the final alliance utility.

[0125] In the calculation module, the objective function for matching source-load intervals within the alliance is constructed, along with constraints on the quantity and price of electricity purchased and sold during the matching process. The total alliance utility for each alliance is then calculated. The objective function for matching source-load intervals within the alliance is as follows:

[0126]

[0127] Where Λ and θ are the sums of all random permutations of the members in the power supply load set S and the power supply load set D, respectively. In alliance C, the current member sequences of S and D are ζ and ζ, respectively. The effectiveness of alliances at that time.

[0128] The allocation module is used to achieve fair allocation of coalition utility among cooperative source loads based on the coalition's final utility and employs the interval Shapley value method.

[0129] In the allocation module, for a coalition C corresponding to the coalition's final utility, the coalition's final utility is allocated among any source payloads that form coalition C, with each source payload receiving a lower and upper bound of the shapley value that satisfies the utility allocation.

[0130] Example 3

[0131] like Figure 3As shown, the present invention also provides an electronic device 100 for implementing a multi-entity source-load interval matching control method within a consortium; the electronic device 100 includes a memory 101, at least one processor 102, a computer program 103 stored in the memory 101 and executable on the at least one processor 102, and at least one communication bus 104. The memory 101 can be used to store the computer program 103, and the processor 102 implements the steps of the multi-entity source-load interval matching control method within a consortium according to Embodiment 1 by running or executing the computer program stored in the memory 101 and calling data stored in the memory 101. The memory 101 may mainly include a program storage area and a data storage area, wherein the program storage area may store the operating system, at least one application program required for a function (such as sound playback function, image playback function, etc.), etc.; the data storage area may store data created according to the use of the electronic device 100 (such as audio data), etc. In addition, memory 101 may include non-volatile memory, such as hard disk, memory, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one disk storage device, flash memory device, or other non-volatile solid-state storage device.

[0132] At least one processor 102 may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Processor 102 may be a microprocessor or any conventional processor. Processor 102 is the control center of electronic device 100, connecting various parts of electronic device 100 via various interfaces and lines.

[0133] The memory 101 in the electronic device 100 stores multiple instructions to implement a multi-subject source-load interval matching control method within a consortium, and the processor 102 can execute multiple instructions to achieve the following:

[0134] The power purchase and sale type of the source load is determined based on the net output power of the source load; wherein, the power purchase and sale type of the source load includes power sale load and power purchase load;

[0135] Source loads within a distance range α form alliances, and each alliance contains at least one purchasing power load and one selling power load. The source loads within the alliances are divided into a purchasing power load set D and a selling power load set S.

[0136] The order of one member in each power source set is selected to determine the highest bid price range and bid quantity range for the power source set and the bid price range for the power source set. When the bid price of the power source set is not lower than the bid price of the power source set, the buyer and seller are successfully matched. The power source set that meets all power demand or the power source set that supplies all remaining power will be removed from the corresponding power source set. This power source set matching process is repeated until the power source set or the power source set is empty or no more power source set can be matched. The utility increment of each power source set is accumulated to obtain the total alliance utility. The order of each member in the power source set and the power source set will be combined and tried. The total alliance utility of each alliance will be calculated, and the largest total alliance utility will be taken as the final alliance utility.

[0137] Based on the ultimate utility of the alliance, the interval Shapley value method is used to achieve a fair distribution of alliance utility among cooperative source loads.

[0138] Example 4

[0139] If the modules / units integrated in the electronic device 100 are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of the present invention can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, and read-only memory (ROM).

[0140] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0141] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0142] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0143] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0144] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A multi-entity source-load interval matching control method within an alliance, characterized in that, Includes the following steps: The power purchase and sale type of a source load is determined based on its net power output. This type includes both power sales loads and power purchase loads. If a source load's expected net power output is greater than zero, it is defined as a power sales load with surplus power, and its surplus power is represented as an interval variable. If the expected net power output of a source load is less than zero, it is defined as a purchasing load with power demand, and its power demand is expressed as an interval variable. ; Distance range The source loads within the region form alliances, and each alliance contains at least one purchasing power load and one selling power load. The source loads within each alliance are divided into a purchasing power load set and a selling power load set; further, the source loads within each alliance are divided into a purchasing power load set D and a selling power load set S; where the distance range... The source and load within the area are connected via dedicated power lines; specifically, a distance range is set. Limit the distance between cooperating source loads to keep the distance between the connecting lines between cooperating source loads within a reasonable range and avoid unreasonable source load alliances; The order of one member from each of the power purchase and power sale load sets is selected to determine the highest bid price range and bid quantity range for the power purchase load to the power sale load, as well as the price range for the power sale load. When the bid price of the power purchase load is not lower than the price of the power sale load, the buyer and seller are successfully matched. The power purchase load that meets all electricity demand or the power sale load that supplies all remaining electricity will be removed from the corresponding power source set. This power source matching process is repeated until the power purchase or power sale load set is empty or no more power purchase and power sale load pairs can be matched. The utility increment of each power source load pair is accumulated to obtain the total alliance utility. The order of each member in the power purchase and power sale load sets will be combined and tried, and the total alliance utility of each alliance will be calculated. The largest total alliance utility will be taken as the final alliance utility. Based on the ultimate utility of the alliance, the interval Shapley value method is used to achieve a fair distribution of alliance utility among cooperative source loads; The method for calculating the total coalition utility for each coalition is as follows: 1) Establish the objective function for multi-subject source-load interval matching within the alliance: in Let S and D be the sum of all random permutations of the members in the power supply load set S and the power supply load set D, respectively. In the alliance C, the current member sequences of S and D are respectively and The effectiveness of alliances at that time; 2) Calculate the bid quantity of the purchased power load and the corresponding power transmission losses, including: the purchased power load i to meet its own power demand. From having surplus power The amount of electricity purchased by the power supplier j Line loss caused during power transmission From the formula and Calculate; where It is the voltage level of the source load. It is the resistance between the seller's source charge j and the buyer's source charge i; 3) Calculate the actual power supply of the power source and the corresponding power transmission losses, including: the total amount of power that source load j can actually supply to source load i. Represented as: In the formula Substitution The actual power received by source load i from source load j It can be calculated as Corresponding line losses during power transmission The difference between them: 4) Source charge i is actually received The amount of electricity that needs to be purchased from DS : In the formula, Roi is the resistance from the power supply charge i to DS; β is the voltage level on the DS side; β is the transformer loss fraction on the DS side. 5) The amount of electricity that power supplier j will actually supply to power purchaser i. The actual power received by DS ,for and the corresponding line loss during circuit transmission The difference between them: In the formula It is the resistor from the power supply charge j to DS; 6) The highest bid from power purchaser i to corresponding power seller j : Source i is to obtain the corresponding The highest bid is willing to pay per unit of electricity for source load j. for: ; The highest bid of source carrier i Transform into the standard form of interval numbers: 7) The lowest acceptable price for selling power load j : Source load j's lowest acceptable quote for any purchased power load for: ; The lowest acceptable quote for source load j Transform into the standard form of interval numbers: Only when the bid price of the power supply unit is available. The lowest acceptable price is no less than the power supply load (j). Only when source load i and source load j are matched can the complementary use of electricity between source loads be realized. The interval Shapley value method is used to achieve a fair allocation of coalition utility among cooperative source loads. Specifically, this includes: for the coalition's final utility corresponding to the coalition... The ultimate benefit of an alliance will be to any alliance that is formed. The distribution among the source loads, and the lower and upper bounds of the Shapley values ​​that satisfy the utility distribution for each source load; The lower and upper bounds of the Shapley value are: in ; In the formula, , indicating the alliance The Middle Individual source load and , For the alliance The number of intermediate source loads; The first Individual Source Lotus Participation Alliance The allocated utility upper and lower boundaries, It is an alliance A subset of, indicating All the sub-alliances that Zhongyuanhe can form, For the Alliance The number of MGs in the middle Is the Alliance The utility and .

2. A multi-entity source-load interval matching control device within a consortium, used to implement the multi-entity source-load interval matching control method within a consortium as described in claim 1, characterized in that, include: The classification module is used to determine the power purchase and sale type of the source load based on the net output power of the source load; wherein, the power purchase and sale type of the source load includes power sale load and power purchase load; Combined modules for distance range The source loads within the alliance form an alliance, and each alliance contains at least one purchasing power load and one selling power load. The source loads within the alliance are divided into a purchasing power load set D and a selling power load set S. The calculation module is used to select the order of one member of each power source set, determine the highest bid price range and bid quantity range for each power source set, and the bid price range for each power source set. When the bid price of the power source set is not lower than the bid price of the power source set, the buyer and seller are successfully matched. The power source set that meets all electricity demand or the power source set that supplies all remaining electricity will be removed from the corresponding power source set. This power source set matching process is repeated until the power source set is empty or no more power source set can be matched. The utility increment of each power source set is accumulated to obtain the total alliance utility. The order of each member in the power source set and the power source set will be combined and tried. The total alliance utility of each alliance will be calculated, and the maximum total alliance utility will be taken as the final alliance utility. The allocation module is used to achieve fair allocation of coalition utility among cooperative source loads based on the coalition's final utility and employs the interval Shapley value method.

3. An electronic device, characterized in that, It includes a processor and a memory, the processor being used to execute a computer program stored in the memory to implement the multi-subject source-load interval matching control method within the consortium as described in claim 1.

4. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores at least one instruction, which, when executed by a processor, implements the multi-subject source-load interval matching control method within the alliance as described in claim 1.

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