Method and system for judging application effect of distributed mobile energy storage system

Abstract

The invention discloses an application effect judgment method for a distributed mobile energy storage system. The method comprises the following steps: acquiring data information of a to-be-judged distributed mobile energy storage system and data information of a novel power system; constructing to obtain a problem set; determining a mixed problem scene set and representing the mixed problem scene set by using a function vector; calculating a power calculation value and a capacity calculation value of the distributed mobile energy storage system; an application effect judgment index of the distributed mobile energy storage system is obtained through calculation, and application effect judgment of the distributed mobile energy storage system is completed. The invention also discloses a system for realizing the application effect judgment method of the distributed mobile energy storage system. According to the method, the application effect of the distributed mobile energy storage system can be judged, the reliability is higher, the accuracy is better, and the method is more objective and scientific.

Description

Technical Field

[0001] The present invention belongs to the field of electrical automation, and in particular relates to a method and system for determining the application effect of a distributed mobile energy storage system. Background Art

[0002] With the development of economy and technology and the improvement of people's living standards, electricity has become an indispensable secondary energy source in people's production and life, bringing endless convenience to people's production and life. Therefore, ensuring the stable and reliable supply of electricity has become one of the most important tasks of the power system.

[0003] At present, with the rapid growth of conventional power loads and electric vehicle charging loads, as well as the large-scale access of renewable energy distributed generation systems to medium and low voltage distribution networks, at the medium and low voltage distribution network level, the power system needs to face many challenges, such as branch overload problems, node voltage over-limit problems, local network renewable energy distributed generation nearby and efficient consumption problems, local network electric vehicle charging load surge problems, and local network high reliability power supply demand problems. Moreover, the medium and low voltage distribution network under the conditions of the new power system, its load and renewable energy distributed generation system access situation will change frequently, and its network / equipment transformation and new investment also occur frequently, resulting in the existence / appearance of the above problems in the space-time distribution with drift, sparseness, randomness and volatility. Therefore, the new power system adopts the technical solution of distribution network transformation / new construction to solve some problems according to the established principles / plans, and adopts distributed mobile energy storage systems to deal with the remaining problems.

[0004] At present, new power systems have gradually begun to adopt distributed mobile energy storage systems. However, current research programs generally focus on the site selection and capacity determination of distributed mobile energy storage systems, and have not determined the application effect of distributed mobile energy storage systems. At the same time, the cost of distributed mobile energy storage systems is high. If the application effect of distributed mobile energy storage systems cannot be scientifically and accurately determined, the effect of distributed mobile energy storage systems may not be reflected, and it may also cause a large amount of resource waste or idleness. Summary of the invention

[0005] One of the purposes of the present invention is to provide a method for determining the application effect of a distributed mobile energy storage system which is highly reliable, accurate, objective and scientific.

[0006] A second objective of the present invention is to provide a system for implementing the method for determining the application effect of the distributed mobile energy storage system.

[0007] The method for determining the application effect of the distributed mobile energy storage system provided by the present invention comprises the following steps:

[0008] S1. Obtaining data information of the distributed mobile energy storage system to be determined, and data information of the corresponding new power system;

[0009] S2. Based on the data information obtained in step S1, a problem set is constructed for the problems existing in the new power system and the problems that the distributed mobile energy storage system can solve;

[0010] S3. According to the problem set obtained in step S2, based on the problems that the distributed mobile energy storage system can solve and the relationship between the problems, determine a set of mixed problem scenarios and represent them using a function vector;

[0011] S4. According to the hybrid problem scenario set obtained in step S3, based on the operating requirements of the distributed mobile energy storage system and the new power system, the power calculation value and capacity calculation value of the distributed mobile energy storage system are calculated;

[0012] S5. Based on the power calculation value and capacity calculation value of the distributed mobile energy storage system obtained in step S4, and the ratio of the power design value and capacity design value of the distributed mobile energy storage system, the application effect determination index of the distributed mobile energy storage system is calculated;

[0013] S6. According to the application effect determination index of the distributed mobile energy storage system obtained in step S5, the application effect determination of the distributed mobile energy storage system is completed.

[0014] The step S2 comprises the following steps:

[0015] According to the problems that appear or exist in the new power system, as well as the technical solutions for the transformation or construction of the new power system, a total problem set, a planned problem set and a storage problem set are constructed;

[0016] Using the ordinal vector scheme, a value is assigned to each element in the energy storage problem set;

[0017] According to the specific location of the new power system corresponding to each element in the energy storage problem set, the positioning domain of the energy storage problem set is determined.

[0018] The step S2 specifically includes the following steps:

[0019] Construct the total problem set, the planned problem set, and the energy storage problem set:

[0020] The power supply area of ​​the new power system is divided into n z There are 100 regions, where the jth region is represented by Z j ,j=1,2,...,n z ; For each patch Z j , define the total problem set Plan to solve the problem set and energy storage problem solving set

[0021] Set the inspection time interval to n d days, where the dth day is represented by L d , d=1,2,...,n d ;

[0022] Each day in the observation time interval is divided into n time periods. k time periods, where the kth time period is denoted as T k ,k=1,2,3,...,n k ;

[0023] Sorting out the power supply area:

[0024] If the area Z j In the time interval L d T k If there is a branch overload problem during the time period, the corresponding branch will form the first problem subset

[0025] If the area Z j In the time interval L d T k If there is or occurs a node voltage over-limit problem during the time period, the corresponding nodes will form the second problem subset

[0026] If the area Z j In the time interval L d T k If there is a problem of local network renewable energy distributed generation and efficient consumption nearby during the period, the corresponding sub-scenario will form the third problem subset

[0027] If the area Z j In the time interval L d T k If there is a sudden increase in the charging load of electric vehicles in the local network during the period, the corresponding sub-scenario will form the fourth problem subset

[0028] If the area Z j In the time interval L d T k If there is a problem of high-reliability power supply demand in the local network during the period, the corresponding sub-scenario will form the fifth problem subset.

[0029] Will and Find the union and get the total problem set

[0030] In the total problem set To sort out:

[0031] If the target power system adopts the technical solution of distribution network transformation or new construction to solve the problem of area Z j In the time interval L d T k If there are several heavy overload problems in the time period, the corresponding branches will be planned to solve the first problem subset

[0032]

[0033] If the target power system adopts the technical solution of distribution network transformation or new construction to solve the problem of area Z j In the time interval L d T k If there are or appear several node voltage exceeding limit problems in the time period, the corresponding several nodes will be planned to solve the second problem subset

[0034] If the target power system adopts the technical solution of distribution network transformation or new construction to solve the problem of area Z j In the time interval L d T k If there are several local network renewable energy distributed generation problems that exist or appear in the period, the corresponding sub-scenarios will be used to plan and solve the third problem subset

[0035] If the target power system adopts the technical solution of distribution network transformation or new construction to solve the problem of area Z j In the time interval L d T k If there are several local network electric vehicle charging load surge problems that exist or appear during the period, the corresponding sub-scenarios will constitute a plan to solve the fourth problem subset

[0036] If the target power system adopts the technical solution of distribution network transformation or new construction to solve the problem of area Z j In the time interval L d T k If there are several local network high reliability power supply demand problems that exist or appear in the period, the corresponding sub-scenarios will constitute the fifth problem subset

[0037] Will and Find the union and get the set of problems to be solved

[0038] According to the total question set and plan to solve the problem set The energy storage problem set is calculated using the following formula

[0039]

[0040] In the formula Solve the first subset of problems for energy storage; Solve the second subset of problems for energy storage; Solve the third subset of problems for energy storage; Solve the fourth subset of problems for energy storage; Solve the fifth subset of problems for energy storage; p is the number of the subset of problems;

[0041] Determine the sequence vector of the energy storage problem set:

[0042] Problem Solving Set for Energy Storage Each element in is assigned a sequence vector of energy storage problem solving as shown below

[0043]

[0044] In the formula for The natural serial number of the elements in; The number of elements in the first subset of problems solved for energy storage; The number of elements in the second subset of problems solved for energy storage; Solve the element numbers in the third subset of the problem for energy storage; Solve the element numbers in the fourth subset of the problem for energy storage; Solve the element numbers in the fifth subset of the problem for energy storage;

[0045] Determine the location domain of the energy storage problem set:

[0046] The following formula is used to represent the location domain of the energy storage problem set:

[0047]

[0048] Among them, the site name is used to indicate the source of the grid-side power supply of the branch, node or sub-scenario that the energy storage solves the problem. When the grid-side power supply comes from the medium-voltage bus of the substation, the site name uses the corresponding substation name; when the grid-side power supply comes from the low-voltage bus of the distribution station, the site name uses the corresponding distribution station name; when the grid-side power supply comes from the switchgear bus, the site name uses the corresponding switchgear name; when the grid-side power supply comes from the distribution transformer, the site name uses the corresponding distribution point transformer name; when the grid-side power supply comes from the distribution line section, the site name uses the corresponding distribution line section name.

[0049] The step S3 comprises the following steps:

[0050] Define a set of mixed problem scenarios;

[0051] According to the topological structure of the new power system, a general wiring model is constructed;

[0052] According to the elements in the first problem subset to the fifth problem subset solved by energy storage, the corresponding branches and specific wirings are determined in the constructed general wiring model, and compared and integrated to obtain a set of mixed problem scenarios;

[0053] For each element in the obtained mixed problem scenario set, a function vector of the mixed problem scenario is calculated according to the existing or occurring problems.

[0054] The step S3 specifically includes the following steps:

[0055] Define a set of mixed problem scenarios:

[0056] Solving Problems with Energy Storage Based on the connection, set the area Z j In the time interval L d T k The time period adopts a connection of the existence or emergence of energy storage to solve the first problem subset ~ energy storage to solve one or more problems in the fifth problem subset as a mixed problem scenario; j In the time interval L d T k The set of all mixed problem scenarios in the time period is called the mixed problem scenario set

[0057] Construct a general wiring model:

[0058] The general wiring model includes the main grid, main transformer, distribution line, distribution transformer, low-voltage incoming line circuit breaker, low-voltage busbar, new energy power station, distributed mobile energy storage system, conventional load, high-reliability power supply load and electric vehicle charging load; the main grid, main transformer and distribution line are connected in series in sequence; the distribution transformer is connected to the distribution line and connected to the low-voltage busbar through the low-voltage incoming line circuit breaker; the new energy power station, distributed mobile energy storage system, conventional load, high-reliability power supply load and electric vehicle charging load are all connected to the low-voltage busbar;

[0059] Among them, the main power grid includes the AC transmission network or the AC high-voltage distribution network; the main transformer includes the main transformer in the substation; the distribution line includes the medium-voltage distribution line; the distribution transformer includes a step-down transformer that converts medium-voltage AC power into low-voltage AC power; the low-voltage incoming line circuit breaker is the grid power circuit breaker of the low-voltage bus, which is used to protect the low-voltage bus; the conventional load is all loads that have no requirements for power supply reliability except for the electric vehicle charging load; the high-reliability power supply load is all loads that require power supply reliability greater than the set value;

[0060] Construction of a mixed problem scenario collection:

[0061] A. Solving the first subset of problems for energy storage Get the first subset of questions The i1th element in , obtains the branch corresponding to the i1th element on the general wiring model, determines the wiring of the branch on the general wiring model, and represents the wiring as right Make a judgment: If the wiring With any wiring If they are the same, the i1th element is included in the wiring Subset of wiring problems If the wiring With all wiring If they are all different, the i1th element is classified as a connection Subset of wiring problems The value of j1 is 1 to (i1-1);

[0062] B. Solving the second subset of problems for energy storage Get the second subset of questions The i2th element in , obtains the branch corresponding to the i2th element on the general wiring model, determines the wiring of the branch on the general wiring model, and represents the wiring as right Make a judgment: If the wiring With any wiring If they are the same, the i2th element is included in the wiring Subset of wiring problems If the wiring With any wiring If they are the same, the i2th element is included in the wiring Subset of wiring problems If the wiring With all wiring and all wiring If they are different, the i2th element will be classified as a connection Subset of wiring problems The value of jj1 ranges from 1 to n1, where n1 is the number of elements in the first problem subset solved by energy storage; the value of j2 ranges from 1 to (i2-1);

[0063] C. Solving the third subset of problems for energy storage Get the third subset of questions The i3th element in , obtains the branch corresponding to the i3th element on the general wiring model, determines the wiring of the branch on the general wiring model, and represents the wiring as right Make a judgment: If the wiring With any wiring If the same, the i3th element is included in the wiring Subset of wiring problems If the wiring With any wiring If the same, the i3th element is included in the wiring Subset of wiring problems If the wiring With any wiring If the same, the i3th element is included in the wiring Subset of wiring problems If the wiring With all wiring All wiring and all wiring If they are all different, the i3th element is classified as a connection Subset of wiring problems jj2 is the number of elements in the second problem subset solved by energy storage; j3 has a value of 1 to (i3-1);

[0064] D. Solve the fourth subset of problems for energy storage Get the fourth question subset The i4th element in , obtains the branch corresponding to the i4th element on the general wiring model, determines the wiring of the branch on the general wiring model, and represents the wiring as right Make a judgment: If the wiring With any wiring If the same, the i4th element is included in the wiring Subset of wiring problems If the wiring With any wiring If the same, the i4th element is included in the wiring Subset of wiring problems If the wiring With any wiring If the same, the i4th element is included in the wiring Subset of wiring problems If the wiring With any wiring If the same, the i4th element is included in the wiring Subset of wiring problems If the wiring With all wiring All wiring All wiring and all wiring If they are all different, the i4th element is classified as a wiring Subset of wiring problems jj3 is the number of elements in the subset of the third problem solved by energy storage; j4 has a value of 1 to (i4-1);

[0065] E. Solving the fifth subset of problems for energy storage Get the fourth question subset The i5th element in , obtains the branch corresponding to the i5th element on the general wiring model, determines the wiring of the branch on the general wiring model, and represents the wiring as right Make a judgment: If the wiring With any wiring If the same, the i5th element is included in the wiring Subset of wiring problems If the wiring With any wiring If the same, the i5th element is included in the wiring Subset of wiring problems If the wiring With any wiring If the same, the i5th element is included in the wiring Subset of wiring problems If the wiring With any wiring If the same, the i5th element is included in the wiring Subset of wiring problems If the wiring With any wiring If the same, the i5th element is included in the wiring Subset of wiring problems If the wiring With all wiring All wiring All wiring All wiring and all wiring If they are all different, the i5th element is classified as a connection Subset of wiring problems Jj4 is the number of elements in the subset of the fourth problem solved by energy storage; the value of j5 is 1 to (i5-1);

[0066] F. Take the union of all the wiring problem sub-subsets obtained from step A to step E to obtain the mixed problem scenario set

[0067]

[0068] Calculation of function vectors for mixed problem scenarios:

[0069] Area Z j In the time interval L d T k Time There are n w Mixed problem scenarios, n w is the number of mixed problem scenarios, the following formula is used to calculate the 5-dimensional function vector of each mixed problem scenario:

[0070]

[0071] In the formula is the dimension element of the function vector of the sth hybrid problem scenario, corresponding to the function that the distributed mobile energy storage system needs to configure when eliminating the problem corresponding to the oth problem subset in the sth hybrid problem scenario; the value of o is 1 to 5; if the sth hybrid problem scenario exists or appears, the problem in the oth problem subset is solved by energy storage otherwise

[0072] The power matrix of the function vector of the mixed problem scenario is set to determine the power of each dimension element of the function vector; the power matrix Expressed as

[0073]

[0074] In the formula is the power variable element corresponding to the energy storage solving the oth problem subset;

[0075] Calculate the function vector of the mixed problem scenario for

[0076]

[0077] The step S4 comprises the following steps:

[0078] According to the hybrid problem scenario set obtained in step S3, based on the operation requirements of the distributed mobile energy storage system and the new power system, the required power and capacity of the mobile energy storage are calculated;

[0079] The required power and capacity of the mobile energy storage are optimized using a proportional coefficient scheme to obtain the power calculation value and capacity calculation value of the distributed mobile energy storage system.

[0080] The step S4 specifically comprises the following steps:

[0081] Calculation of the required power and capacity of mobile energy storage:

[0082] According to the mixed problem scenario set obtained in step S3 The following formula is used to calculate the area Z j In the time interval L d T k Mixed problem scenario for period s The power required for mobile energy storage

[0083]

[0084] In the formula is the power contraction vector, and Solve the power shrinkage factor of the oth problem subset for energy storage;

[0085] Use the following formula to To obtain the value:

[0086]

[0087] according to The value selection rule of the area Z j The sth mixed problem scenario The power required for mobile energy storage within the time interval for:

[0088]

[0089] Where counter[·] represents the count of situations that satisfy the conditions in the square brackets; For area Z j The sth mixed problem scenario In the time interval L d The maximum daily power adjustment factor of mobile energy storage, Used to ensure the storage and release cycle of mobile energy storage system within 24 hours a day; kis the number of time periods in a 24-hour day. If 1 hour is 1 time period, then n k =24, if 15 minutes is one period, then n k =96; It is the number of periods in a 24-hour day when the energy storage power is greater than or equal to the maximum energy storage power of the day.

[0090] The following formula is used to calculate the area Z j The sth mixed problem scenario Required capacity of mobile energy storage within the time interval

[0091]

[0092] In the formula for The mobile energy storage required is L d Number of periods of 25% or more of exchange power per day;

[0093] Calculate the required power of mobile energy storage for Required capacity of mobile energy storage for

[0094] Calculation of power and capacity calculation values ​​of distributed mobile energy storage systems:

[0095] The power calculation value of the distributed mobile energy storage system is calculated using the following formula: and capacity calculation value

[0096]

[0097] In the formula Power optimization coefficient for mobile energy storage systems in regional power supply applications; It is the capacity optimization factor for the systematic application of mobile energy storage in the power supply area.

[0098] The step S5 specifically includes the following steps:

[0099] The first judgment index a and the second judgment index b of the application effect of the distributed mobile energy storage system are calculated using the following formula:

[0100]

[0101] In the formula It is the power design value of the distributed mobile energy storage system; It is the capacity design value of distributed mobile energy storage system.

[0102] The step S6 specifically includes the following steps:

[0103] According to the application effect determination index of the distributed mobile energy storage system obtained in step S5, the application effect determination of the distributed mobile energy storage system is performed using the following rules:

[0104] like Then it is determined that the application effect of the distributed mobile energy storage system is optimal;

[0105] like Then the application effect of the distributed mobile energy storage system is judged to be suboptimal;

[0106] like Then the application effect of the distributed mobile energy storage system is judged to be feasible;

[0107] like Then it is determined that the application effect of the distributed mobile energy storage system is too high;

[0108] like It is determined that the application effect of the distributed mobile energy storage system is too difficult to achieve;

[0109] like It is then determined that the application effect of the distributed mobile energy storage system is power-capacity imbalance.

[0110] The present invention also provides a system for implementing the method for determining the application effect of the distributed mobile energy storage system, comprising a data acquisition module, a set construction module, a scenario construction module, a data calculation module, an index calculation module and an effect determination module; the data acquisition module, the set construction module, the scenario construction module, the data calculation module, the index calculation module and the effect determination module are connected in series in sequence; the data acquisition module is used to obtain data information of the distributed mobile energy storage system to be determined, and data information of the corresponding new power system, and upload the data information to the set construction module; the set construction module is used to construct a problem set based on the received data information, for the problems existing in the new power system and the problems that the distributed mobile energy storage system can solve, and upload the data information to the scenario construction module; the scenario construction module is used to construct a problem set based on the received data information and the obtained problem set, based on the problems that the distributed mobile energy storage system can solve and the problems The relationship between them is used to determine the hybrid problem scenario set, and it is represented by a function vector, and the data information is uploaded to the data calculation module; the data calculation module is used to calculate the power calculation value and capacity calculation value of the distributed mobile energy storage system based on the received data information, the obtained hybrid problem scenario set, and the operation requirements of the distributed mobile energy storage system and the new power system, and upload the data information to the indicator calculation module; the indicator calculation module is used to calculate the application effect judgment index of the distributed mobile energy storage system based on the received data information, the obtained power calculation value and capacity calculation value of the distributed mobile energy storage system, and the ratio of the power design value and capacity design value of the distributed mobile energy storage system, and upload the data information to the effect judgment module; the effect judgment module is used to complete the application effect judgment of the distributed mobile energy storage system based on the received data information and the obtained application effect judgment index of the distributed mobile energy storage system.

[0111] The method and system for determining the application effect of a distributed mobile energy storage system provided by the present invention acquire data of a target distributed mobile energy storage system and a new power system, construct a corresponding problem set and a scenario set, and calculate the power value and capacity value of the distributed mobile energy storage system based on the problem set and the scenario set, and finally determine the application effect based on the calculation results and design results of the power value and capacity value of the distributed mobile energy storage system; therefore, the present invention can not only realize the determination of the application effect of a distributed mobile energy storage system, but also has higher reliability, better accuracy, and is more objective and scientific. BRIEF DESCRIPTION OF THE DRAWINGS

[0112] Figure 1 The figure is a schematic diagram of the method flow of the present invention.

[0113] Figure 2 Schematic diagram of a general wiring model in the method of the present invention.

[0114] Figure 3 Schematic diagram of the functional modules of the system of the present invention. DETAILED DESCRIPTION

[0115] like Figure 1 The method flow diagram of the method of the present invention is shown as follows: The method for determining the application effect of the distributed mobile energy storage system provided by the present invention comprises the following steps:

[0116] S1. Obtaining data information of the distributed mobile energy storage system to be determined, and data information of the corresponding new power system;

[0117] S2. Based on the data information obtained in step S1, a problem set is constructed for the problems existing in the new power system and the problems that the distributed mobile energy storage system can solve; comprising the following steps:

[0118] According to the problems that appear or exist in the new power system, as well as the technical solutions for the transformation or construction of the new power system, a total problem set, a planned problem set and a storage problem set are constructed;

[0119] Using the ordinal vector scheme, a value is assigned to each element in the energy storage problem set;

[0120] Determine the location domain of the energy storage problem set based on the specific location of the new power system corresponding to each element in the energy storage problem set;

[0121] When implementing it, you can take the following steps:

[0122] Construct the total problem set, the planned problem set, and the energy storage problem set:

[0123] The power supply area of ​​the new power system is divided into n z There are 100 regions, where the jth region is represented by Z j ,j=1,2,...,n z ; For each patch Z j , define the total problem set Plan to solve the problem set and energy storage problem solving set

[0124] Set the inspection time interval to n d days, where the dth day is represented by L d , d=1,2,...,n d ;

[0125] Each day in the observation time interval is divided into n time periods. k time periods, where the kth time period is denoted as T k ,k=1,2,3,...,nk ;

[0126] Sorting out the power supply area:

[0127] If the area Z j In the time interval L d T k If there is a branch overload problem during the time period, the corresponding branch will form the first problem subset

[0128] If the area Z j In the time interval L d T k If there is or occurs a node voltage over-limit problem during the time period, the corresponding nodes will form the second problem subset

[0129] If the area Z j In the time interval L d T k If there is a problem of local network renewable energy distributed generation and efficient consumption nearby during the period, the corresponding sub-scenario will form the third problem subset

[0130] If the area Z j In the time interval L d T k If there is a sudden increase in the charging load of electric vehicles in the local network during the period, the corresponding sub-scenario will form the fourth problem subset

[0131] If the area Z j In the time interval L d T k If there is a problem of high-reliability power supply demand in the local network during the period, the corresponding sub-scenario will form the fifth problem subset.

[0132] Will and Find the union and get the total problem set

[0133] In the total problem set To sort out:

[0134] If the target power system adopts the technical solution of distribution network transformation or new construction to solve the problem of area Z j In the time interval L d T k If there are several heavy overload problems in the time period, the corresponding branches will be planned to solve the first problem subset

[0135]

[0136] If the target power system adopts the technical solution of distribution network transformation or new construction to solve the problem of area Z j In the time interval L d T k If there are or appear several node voltage exceeding limit problems in the time period, the corresponding several nodes will be planned to solve the second problem subset

[0137] If the target power system adopts the technical solution of distribution network transformation or new construction to solve the problem of area Z j In the time interval L d T k If there are several local network renewable energy distributed generation problems that exist or appear in the period, the corresponding sub-scenarios will be used to plan and solve the third problem subset

[0138] If the target power system adopts the technical solution of distribution network transformation or new construction to solve the problem of area Z j In the time interval L d T k If there are several local network electric vehicle charging load surge problems that exist or appear during the period, the corresponding sub-scenarios will constitute a plan to solve the fourth problem subset

[0139] If the target power system adopts the technical solution of distribution network transformation or new construction to solve the problem of area Z j In the time interval L d T k If there are several local network high reliability power supply demand problems that exist or appear in the period, the corresponding sub-scenarios will constitute the fifth problem subset

[0140] Will and Find the union and get the set of problems to be solved

[0141] According to the total question set and plan to solve the problem set The energy storage problem set is calculated using the following formula

[0142]

[0143] In the formula Solve the first subset of problems for energy storage; Solve the second subset of problems for energy storage; Solve the third subset of problems for energy storage; Solve the fourth subset of problems for energy storage; Solve the fifth subset of problems for energy storage; p is the number of the subset of problems;

[0144] Determine the sequence vector of the energy storage problem set:

[0145] Problem Solving Set for Energy Storage Each element in is assigned a sequence vector of energy storage problem solving as shown below

[0146]

[0147] In the formula for The natural serial number of the elements in; The number of elements in the first subset of problems solved for energy storage; The number of elements in the second subset of problems solved for energy storage; Solve the element numbers in the third subset of the problem for energy storage; Solve the element numbers in the fourth subset of the problem for energy storage; The sequence number of the elements in the fifth problem subset for energy storage solution; since the elements in the problem set are listed independently, the sequence number vector Only one element is non-0, and the other four elements are all 0; for example, [0,6,0,0,0] is The sequence number vector of the sixth element in the sequence is arranged in order; it is easy to know that because the elements in the problem set are listed independently, there is Established;

[0148] Determine the location domain of the energy storage problem set:

[0149] The following formula is used to represent the location domain of the energy storage problem set:

[0150]

[0151] Among them, the location domain for the third to fifth questions is represented by the node name because distributed renewable energy power generation systems, electric vehicle charging piles / stations, and high-reliability power supply loads are always connected to a certain group of buses or a branch node of a distribution line; the site name is used to indicate the source of the grid-side power supply of the branch, node, or sub-scenario that the energy storage solves the problem. When the grid-side power supply comes from the medium-voltage bus of the substation, the site name uses the corresponding substation name; when the grid-side power supply comes from the low-voltage bus of the distribution station, the site name uses the corresponding distribution station name; when the grid-side power supply comes from the switch station bus, the site name uses the corresponding switch station name; when the grid-side power supply comes from the distribution transformer, the site name uses the corresponding distribution transformer name; when the grid-side power supply comes from the distribution line segment, the site name uses the corresponding distribution line segment name;

[0152] S3. According to the problem set obtained in step S2, based on the problems that the distributed mobile energy storage system can solve and the relationship between the problems, determine a set of mixed problem scenarios and represent them using a function vector; comprising the following steps:

[0153] For a specific connection of the medium and low voltage distribution network, any of the problems from the first to the fifth problem may not exist or will not occur, or one or some of the problems from the first to the fifth problem may exist or occur, so it is necessary to consider mixed problem scenarios;

[0154] Define a set of mixed problem scenarios;

[0155] According to the topological structure of the new power system, a general wiring model is constructed;

[0156] According to the elements in the first problem subset to the fifth problem subset solved by energy storage, the corresponding branches and specific wirings are determined in the constructed general wiring model, and compared and integrated to obtain a set of mixed problem scenarios;

[0157] For each element in the obtained mixed problem scenario set, a function vector of the mixed problem scenario is calculated according to the existing or occurring problems;

[0158] When implementing it, you can take the following steps:

[0159] Define a set of mixed problem scenarios:

[0160] Solving Problems with Energy Storage Based on the connection, set the area Z j In the time interval L d T k The time period adopts a connection of the existence or emergence of energy storage to solve the first problem subset ~ energy storage to solve one or more problems in the fifth problem subset as a mixed problem scenario; j In the time interval L d T k The set of all mixed problem scenarios in the time period is called the mixed problem scenario set

[0161] Construct a general wiring model:

[0162] General wiring model such as Figure 2 As shown, it includes a main grid 1, a main transformer 2, a distribution line 3, a distribution transformer 4, a low-voltage incoming circuit breaker 5, a low-voltage bus 6, and a new energy power station 7 ( Figure 2PV power station is used to represent), distributed mobile energy storage system 8, conventional load 9, high reliability power supply load 10 and electric vehicle charging load 11; the main power grid, main transformer and distribution line are connected in series in sequence; the distribution transformer is connected to the distribution line and connected to the low voltage bus through the low voltage incoming circuit breaker; the new energy power station, distributed mobile energy storage system, conventional load, high reliability power supply load and electric vehicle charging load are all connected to the low voltage bus;

[0163] The main power grid includes an AC transmission network or an AC high-voltage distribution network; the main transformer includes a main transformer in a substation, which may be a double-winding transformer or a three-winding transformer. Figure 2 A double-winding transformer is used to represent it; the distribution line includes a medium-voltage distribution line, which may be an overhead distribution line or a cable distribution line; the distribution transformer includes a step-down transformer that converts medium-voltage AC power into low-voltage AC power; the low-voltage incoming line circuit breaker is the grid power circuit breaker of the low-voltage bus, which is used to protect the low-voltage bus; the conventional load is all loads except the electric vehicle charging load that have no requirements for power supply reliability; the high-reliability power supply load is all loads that require power supply reliability greater than the set value; and the new energy power station, conventional load, high-reliability power supply load and electric vehicle charging load in the general wiring model may not appear at the same time. If they do not appear, the active and reactive power of the corresponding load or power station can be set to 0;

[0164] Construction of a mixed problem scenario collection:

[0165] A. Solving the first subset of problems for energy storage Get the first subset of questions The i1th element in , obtains the branch corresponding to the i1th element on the general wiring model, determines the wiring of the branch on the general wiring model, and represents the wiring as right Make a judgment: If the wiring With any wiring If they are the same, the i1th element is included in the wiring Subset of wiring problems If the wiring With all wiring If they are all different, the i1th element is classified as a connection Subset of wiring problems The value of j1 is 1 to (i1-1);

[0166] B. Solving the second subset of problems for energy storage Get the second subset of questions The i2th element in , obtains the branch corresponding to the i2th element on the general wiring model, determines the wiring of the branch on the general wiring model, and represents the wiring as right Make a judgment: If the wiring With any wiring If they are the same, the i2th element is included in the wiring Subset of wiring problems If the wiring With any wiring If they are the same, the i2th element is included in the wiring Subset of wiring problems If the wiring With all wiring and all wiring If they are different, the i2th element will be classified as a connection Subset of wiring problems The value of jj1 ranges from 1 to n1, where n1 is the number of elements in the first problem subset solved by energy storage; the value of j2 ranges from 1 to (i2-1);

[0167] C. Solving the third subset of problems for energy storage Get the third subset of questions The i3th element in , obtains the branch corresponding to the i3th element on the general wiring model, determines the wiring of the branch on the general wiring model, and represents the wiring as right Make a judgment: If the wiring With any wiring If the same, the i3th element is included in the wiring Subset of wiring problems If the wiring With any wiring If the same, the i3th element is included in the wiring Subset of wiring problems If the wiring With any wiring If the same, the i3th element is included in the wiring Subset of wiring problems If the wiring With all wiring All wiring and all wiring If they are all different, the i3th element is classified as a connection Subset of wiring problems jj2 is the number of elements in the second problem subset solved by energy storage; j3 has a value of 1 to (i3-1);

[0168] D. Solve the fourth subset of problems for energy storage Get the fourth question subset The i4th element in , obtains the branch corresponding to the i4th element on the general wiring model, determines the wiring of the branch on the general wiring model, and represents the wiring as right Make a judgment: If the wiring With any wiring If the same, the i4th element is included in the wiring Subset of wiring problems If the wiring With any wiring If the same, the i4th element is included in the wiring Subset of wiring problems If the wiring With any wiring If the same, the i4th element is included in the wiring Subset of wiring problems If the wiring With any wiring If the same, the i4th element is included in the wiring Subset of wiring problems If the wiring With all wiring All wiring All wiring and all wiring If they are all different, the i4th element is classified as a wiring Subset of wiring problems jj3 is the number of elements in the subset of the third problem solved by energy storage; j4 has a value of 1 to (i4-1);

[0169] E. Solving the fifth subset of problems for energy storage Get the fourth question subset The i5th element in , obtains the branch corresponding to the i5th element on the general wiring model, determines the wiring of the branch on the general wiring model, and represents the wiring as right Make a judgment: If the wiring With any wiring If the same, the i5th element is included in the wiring Subset of wiring problems If the wiring With any wiring If the same, the i5th element is included in the wiring Subset of wiring problems If the wiring With any wiring If the same, the i5th element is included in the wiring Subset of wiring problems If the wiring With any wiring If the same, the i5th element is included in the wiring Subset of wiring problems If the wiring With any wiring If the same, the i5th element is included in the wiring Subset of wiring problems If the wiring With all wiring All wiring All wiring All wiring and all wiring If they are all different, the i5th element is classified as a connection Subset of wiring problems Jj4 is the number of elements in the subset of the fourth problem solved by energy storage; the value of j5 is 1 to (i5-1);

[0170] F. Take the union of all the wiring problem sub-subsets obtained from step A to step E to obtain the mixed problem scenario set

[0171]

[0172] Calculation of function vectors for mixed problem scenarios:

[0173] Area Z j In the time interval L d T k Time There are n w Mixed problem scenarios, n w is the number of mixed problem scenarios, the following formula is used to calculate the 5-dimensional function vector of each mixed problem scenario:

[0174]

[0175] In the formula is the dimension element of the function vector of the sth hybrid problem scenario, corresponding to the function that the distributed mobile energy storage system needs to configure when eliminating the problem corresponding to the oth problem subset in the sth hybrid problem scenario; the value of o is 1 to 5; if the sth hybrid problem scenario exists or appears, the problem in the oth problem subset is solved by energy storage otherwise

[0176] The power matrix of the function vector of the mixed problem scenario is set to determine the power of each dimension element of the function vector; the power matrix Expressed as

[0177]

[0178] In the formula is the power variable element corresponding to the energy storage solving the oth problem subset;

[0179] When implementing it specifically, The value of is:

[0180] The first problem corresponds to the branch overload problem, the second problem corresponds to the node voltage over-limit problem, the third problem corresponds to the local network renewable energy distributed generation efficient consumption problem, the fourth problem corresponds to the local network electric vehicle charging load sudden increase problem, the fifth problem corresponds to the local network high reliability power supply demand problem;

[0181] For the first question, main transformer 2 is recorded as branch2, and branch2=1 indicates that the branch is heavily overloaded, and branch2=0 indicates that the branch is not heavily overloaded; distribution line 3 is recorded as branch3, and branch3=1 indicates that the branch is heavily overloaded, and branch3=0 indicates that the branch is not heavily overloaded; distribution transformer 4 is recorded as branch4, and branch4=1 indicates that the branch is heavily overloaded, and branch4=0 indicates that the branch is not heavily overloaded. Figure 2 , encode the first question: when only the main transformer 2 is heavily overloaded, it is coded as branch2:branch3:branch4=100; when only the distribution line 3 is heavily overloaded, it is coded as branch2:branch3:branch4=010; when only the distribution transformer 4 is heavily overloaded, it is coded as branch2:branch3:branch4=001; when the main transformer 2 and the distribution line 3 are heavily overloaded, but the distribution transformer 4 is not heavily overloaded, it is coded as branch2:branch3:br anch4=110; when the main transformer 2 and the distribution transformer 4 are overloaded, but the distribution line 3 is not overloaded, the code is branch2:branch3:branch4=101; when the main transformer 2 is not overloaded, but the distribution line 3 and the distribution transformer 4 are overloaded, the code is branch2:branch3:branch4=011; when the main transformer 2, the distribution line 3 and the distribution transformer 4 are all overloaded, the code is branch2:branch3:branch4=111;

[0182] right Figure 2From the analysis, it can be seen that because the capacity of the main transformer 2 and the capacity of the distribution line 3 are much larger than the capacity of the distribution transformer 4, it is impossible to eliminate the first problem coded as branch2:branch3:branch4=100 / 010 / 110 using the distributed mobile energy storage 8 alone, so the distributed mobile energy storage 8 plays an assisting role; at this time, the power of the distributed mobile energy storage 8 is selected to be about 10% of the rated power of the distribution transformer 4 (in specific implementation, the ratio of 10% can be adjusted according to specific circumstances). Considering that the power factor of the distribution network usually reaches above 0.9, the power of the distributed mobile energy storage 8 is selected to be 0.1×0.9S 4N , S 4N is the rated capacity of the distribution transformer 4 and the unit is kVA; thus, The unit is kW;

[0183] For the first problem coded as branch2:branch3:branch4=001 / 101 / 011 / 111, the focus is on solving the heavy overload problem of the distribution transformer 4, which is also beneficial to alleviating the heavy overload problem of the main transformer 2 and the distribution line 3; considering that the distribution transformer can operate at 120% of the rated capacity for a short time, the heavy overload of the distribution transformer 4 may be overloaded to 120% of the rated capacity; at this time, the power selection of the distributed mobile energy storage 8 is about 30% of the rated power of the distribution transformer 4 (in specific implementation, the ratio of 30% can be adjusted according to specific circumstances) is more appropriate. Considering that the power factor of the distribution network usually reaches above 0.9, the power selection of the distributed mobile energy storage 8 is 0.3×0.9S 4N ;in this way, The unit is kW;

[0184] For the second question: let the node of the low-voltage side busbar of main transformer 2 (the busbar connected to the head end of distribution line 3) be node2, and node2=1 means that the voltage at this node is over-limit, and node2=0 means that the voltage at this node is not over-limit; let the connection point between distribution line 3 and distribution transformer 4 be node3, and node3=1 means that the voltage at this node is over-limit, and node3=0 means that the voltage at this node is not over-limit; let the low-voltage busbar 6 be node4, and node4=1 means that the voltage at this node is over-limit, and node4=0 means that the voltage at this node is not over-limit. Figure 1QA-2 question is coded as follows: when only node2 has voltage over-limit, it is coded as node2:node3:node4=100; when only node3 has voltage over-limit, it is coded as node2:node3:node4=010; when only node4 has voltage over-limit, it is coded as node2:node3:node4=001; when node2 and node3 have voltage over-limit, but node4 has no voltage over-limit, it is coded as node2:node3:node4=110; when node2 and node4 have voltage over-limit, but node3 has no voltage over-limit, it is coded as node2:node3:node4=101; when node2 has no voltage over-limit, but node3 and node4 have voltage over-limit, it is coded as node2:node3:node4=011; when node2, node3 and node4 all have voltage over-limit, it is coded as node2:node3:node4=111;

[0185] right Figure 2 Analysis shows that, because the capacity of the main transformer 2 and the capacity of the distribution line 3 are much larger than the capacity of the distribution transformer 4, it is impossible to eliminate the QA-2 problem coded as node2:node3:node4=100 / 010 / 110 using the distributed mobile energy storage 8 alone, so the distributed mobile energy storage 8 plays an assisting role. At this time, whether the voltage is higher than the lower limit or the upper limit, the power selection of the distributed mobile energy storage 8 is about 10% of the rated power of the distribution transformer 4 (in specific implementation, the ratio of 10% can be adjusted according to specific circumstances). Considering that the power factor of the distribution network usually reaches above 0.9, the power selection of the distributed mobile energy storage 8 is 0.1×0.9S 4N ;in this way, The unit is kW;

[0186] For the second problem coded as node2:node3:node4=001 / 101 / 011 / 111, the focus is on solving the voltage over-limit problem of node4, which is also beneficial to alleviating the voltage over-limit problem of node2 and node3; at this time, if it is a voltage under-limit problem, it should also be considered that the distribution transformer can operate at 120% of the rated capacity for a short time, and the heavy overload of the distribution transformer 4 may be overloaded to 120% of the rated capacity. The voltage under-limit problem may occur under the heavy overload situation of the distribution transformer 4. The power selection of the distributed mobile energy storage 8 is about 30% of the rated power of the distribution transformer 4 (in specific implementation, the ratio of 30% can be adjusted according to specific circumstances). Considering that the power factor of the distribution network usually reaches above 0.9, the power selection of the distributed mobile energy storage 8 is 0.3×0.9S 4N ,in this way, The unit is kW;

[0187] If the voltage exceeds the upper limit, the renewable energy generation system should be considered ( Figure 1 The output of the photovoltaic power station 7 in the figure significantly exceeds the total load power on the low-voltage bus 6. The distribution transformer 4 reverses power from the low-voltage side to the high-voltage side, causing the voltage of the low-voltage bus 6 to exceed the upper limit. At the same time, it should also be considered that the distribution transformer can operate at 120% of the rated capacity for a short time. The heavy overload of the distribution transformer 4 may be overloaded to 120% of the rated capacity. The problem of voltage exceeding the upper limit may occur when the distribution transformer 4 is overloaded with reverse power. Therefore, in the above situation, the power selection of the distributed mobile energy storage 8 is the renewable energy power generation system ( Figure 1 The power of the distributed mobile energy storage 8 is selected to be about 0.45P, which is about 45% of the rated power of the photovoltaic power station 7 (in specific implementation, the proportion of 45% can be adjusted according to specific circumstances). 7N , P 7N is the rated power of the renewable energy power generation system and the unit is kW; thus, The unit is kW;

[0188] For the third question: For shard Z j In the Lth time interval under investigation d Day T k The sth mixed problem scenario in the period Low voltage bus 6, P 7N is the rated power of its renewable energy power generation system in kW; its total load, i.e. the sum of conventional load 9, high reliability power supply load 10 and electric vehicle charging load 11, is recorded as The unit is kW. Then take the margin factor as 1.15, otherwise,

[0189] For the fourth question: For shard Z j In the Lth time interval under investigation d Day T k The sth mixed problem scenario in the period Low voltage bus 6, P 11N is the rated power of the electric vehicle charging load 11 in kW, and the sharing coefficient is 0.65.

[0190] For the fifth question: For shard Z j In the Lth time interval under investigation d Day T k The sth mixed problem scenario in the period Low voltage bus 6, P 10NThe rated power of the high reliability power supply load is 10 and the unit is kW, and the margin factor is 1.2.

[0191] Calculate the function vector of the mixed problem scenario for

[0192]

[0193] S4. According to the hybrid problem scenario set obtained in step S3, based on the operating requirements of the distributed mobile energy storage system and the new power system, the power calculation value and capacity calculation value of the distributed mobile energy storage system are calculated; comprising the following steps:

[0194] According to the hybrid problem scenario set obtained in step S3, based on the operation requirements of the distributed mobile energy storage system and the new power system, the required power and capacity of the mobile energy storage are calculated;

[0195] The required power and capacity of the mobile energy storage are optimized by using a proportional coefficient scheme to obtain the power calculation value and capacity calculation value of the distributed mobile energy storage system;

[0196] When implementing it, you can take the following steps:

[0197] Calculation of the required power and capacity of mobile energy storage:

[0198] According to the mixed problem scenario set obtained in step S3 The following formula is used to calculate the area Z j In the time interval L d T k Mixed problem scenario for period s The power required for mobile energy storage

[0199]

[0200] In the formula is the power contraction vector, and Solve the power shrinkage factor of the oth problem subset for energy storage;

[0201] The principle of designing the power shrinkage vector is: Figure 1 The general wiring model shown in the figure uses mobile energy storage to solve multiple problems in QA-1 to QA-5. The mobile energy storage power obtained may be too large, because when one of the first to fifth problems is solved, other problems that exist or appear in the first to fifth problems may also be alleviated or even completely solved. Therefore, for the optimization technical solution, All elements in may be less than 1;

[0202] Considering that the present invention provides a systematic application effect evaluation method, it does not provide the optimal solution but a reference feasible solution. Therefore, according to the strength of the correlation, the following formula is used to evaluate the To obtain the value:

[0203]

[0204] according to The value selection rule of the area Z j The sth mixed problem scenario The power required for mobile energy storage within the time interval for:

[0205]

[0206] Where counter[·] represents the count of situations that satisfy the conditions in the square brackets; For area Z j The sth mixed problem scenario In the time interval L d The maximum daily power adjustment factor of mobile energy storage, Used to ensure the storage and release cycle of mobile energy storage system within 24 hours a day; k is the number of time periods in a 24-hour day. If 1 hour is 1 time period, then n k =24, if 15 minutes is one period, then n k =96; The number of periods in a 24-hour day when the energy storage power is greater than or equal to the maximum energy storage power of the day;

[0207] The following formula is used to calculate the area Z j The sth mixed problem scenario Required capacity of mobile energy storage within the time interval

[0208]

[0209] In the formula for The mobile energy storage required is L d Number of periods of 25% or more of exchange power per day; The calculation formula takes into account the operating conditions that the state of charge SOC of the mobile energy storage system is from 10% to 90% as the effective operating range and 50% in the ready state; therefore, the calculated Ability to meet the capacity demand for mobile energy storage within the time period under consideration;

[0210] Calculate the required power of mobile energy storage for Required capacity of mobile energy storage for

[0211] Calculation of power and capacity calculation values ​​of distributed mobile energy storage systems:

[0212] Considering the differences in network structure, load characteristics and output characteristics of distributed renewable energy generation systems between different slices in the power supply area during the time period under consideration, the mobile energy storage is systematically applied in the power supply area, and the solution can be optimized through optimal design and optimal scheduling; therefore, the sum of the power and capacity of the mobile energy storage required by each slice cannot be directly used as the total power demand and capacity demand of the power supply area for mobile energy storage;

[0213] Therefore, the power calculation value of the distributed mobile energy storage system is calculated using the following formula: and capacity calculation value

[0214]

[0215] In the formula The power optimization coefficient of the mobile energy storage system in the regional power supply application is preferably in the range of 0.5 to 1.0; It is the capacity optimization coefficient of the systematic application of mobile energy storage in the power supply area, and the value range is preferably 0.5 to 1.

[0216] It is obvious that the upper bound of the above two optimization coefficients is 1.0, that is, the sum of the power and capacity of the mobile energy storage required by each shard is directly used as the total power demand and capacity demand of the power supply area for mobile energy storage. The corresponding technical solution of using mobile energy storage to eliminate the first to fifth problems in the power supply area is definitely feasible;

[0217] In addition, considering the differences in network structure, load characteristics and output characteristics of distributed renewable energy generation systems between different slices in the power supply area, a certain degree of complementarity can be obtained. The best case is that different slices are fully complementary to each other, so the lower bounds of the above two optimization coefficients are 0.5;

[0218] Considering that the present invention provides a method for evaluating the systematic application effect of distributed mobile energy storage, it does not provide an optimal solution but a reference feasible solution. Therefore, the preferred value of the method of the present invention is

[0219] S5. Based on the power calculation value and capacity calculation value of the distributed mobile energy storage system obtained in step S4, and the ratio of the power design value and capacity design value of the distributed mobile energy storage system, the application effect determination index of the distributed mobile energy storage system is calculated; specifically comprising the following steps:

[0220] The first judgment index a and the second judgment index b of the application effect of the distributed mobile energy storage system are calculated using the following formula:

[0221]

[0222] In the formula It is the power design value of the distributed mobile energy storage system; is the capacity design value of the distributed mobile energy storage system; the above two design values ​​should have been demonstrated to be feasible (including the complete elimination of the first to fifth problems in the power supply area within the time interval under investigation and the feasibility of the operation of the distributed energy storage system of each specific connection);

[0223] S6. According to the application effect determination index of the distributed mobile energy storage system obtained in step S5, the application effect determination of the distributed mobile energy storage system is completed; specifically comprising the following steps:

[0224] According to the application effect determination index of the distributed mobile energy storage system obtained in step S5, the application effect determination of the distributed mobile energy storage system is performed using the following rules:

[0225] like Then it is determined that the application effect of the distributed mobile energy storage system is optimal;

[0226] like Then the application effect of the distributed mobile energy storage system is judged to be suboptimal;

[0227] like Then the application effect of the distributed mobile energy storage system is judged to be feasible;

[0228] like Then it is determined that the application effect of the distributed mobile energy storage system is too high;

[0229] like It is determined that the application effect of the distributed mobile energy storage system is too difficult to achieve;

[0230] like It is then determined that the application effect of the distributed mobile energy storage system is power-capacity imbalance.

[0231] The method of the present invention is further described below in conjunction with an embodiment:

[0232] Taking a certain power supply area as an example, there are 6 shards in the power supply area with / having problems from the first problem (hereinafter represented by QA-1) to the fifth problem (hereinafter represented by QA-5), that is, n z =6. These 6 slices are recorded as Z1 to Z6. Among them, Z1 has 2 specific connections with QA-1 to QA-5 problems; Z2 has 3 specific connections with QA-1 to QA-5 problems; Z3 has 1 specific connection with QA-1 to QA-5 problems; Z4 has 3 specific connections with QA-1 to QA-5 problems; Z5 has 1 specific connection with QA-1 to QA-5 problems; Z6 has 2 specific connections with QA-1 to QA-5 problems. The inspection time interval is 1 week, that is, n d =7; each day is divided into 24 periods, that is, n k = 24. The time periods when the specific wiring in each of the above-mentioned segments has / occurs QA-1 to QA-5 problems are listed in Tables 1 to 6.

[0233] Table 1 The period during which QA-1 to QA-5 issues existed / occurred in Z1 shard

[0234]

[0235] Table 2 The period during which QA-1 to QA-5 issues exist / appear in Z2 shards

[0236]

[0237] Table 3. The period during which QA-1 to QA-5 issues existed / occurred in Z3 shards

[0238]

[0239] Table 4: The period during which QA-1 to QA-5 issues exist / appear in Z4 shards

[0240]

[0241] Table 5 The period during which QA-1 to QA-5 problems exist / occur in the Z5 shard

[0242]

[0243] Table 6 The period during which QA-1 to QA-5 problems exist / occur in the Z6 shard

[0244]

[0245] Assume that for each specific connection in the six slices where the problems QA-1 to QA-5 exist / occur in the power supply area of ​​the embodiment, the distribution of the load power and the output of distributed renewable energy in the time period of each day on the days when the problems exist / occur in the investigated time interval is the same. For example, if a specific connection has / occurs problems on Saturday and Sunday, it is considered that the distribution of the load power and the output of the distributed renewable energy generation system of the specific connection in the time period is the same on Sunday and Saturday. Therefore, the distribution transformer capacity, load power and output of the distributed renewable energy generation system of each specific connection in the embodiment are listed respectively as shown in Tables 7 to 18.

[0246] Table 7Z1 Slice Specific Wiring Power parameters during the period when QA-1 to QA-5 problems exist / occur

[0247]

[0248] Table 8Z1 Slice Specific Wiring Power parameters during the period when QA-1 to QA-5 problems exist / occur

[0249]

[0250] Table 9Z2 slicing specific wiring Power parameters during the period when QA-1 to QA-5 problems exist / occur

[0251]

[0252] Table 10Z2 Segment Specific Wiring Power parameters during the period when QA-1 to QA-5 problems exist / occur

[0253]

[0254] Table 11Z2 slicing specific wiring Power parameters during the period when QA-1 to QA-5 problems exist / occur

[0255]

[0256] Table 12Z3 slicing specific wiring Power parameters during the period when QA-1 to QA-5 problems exist / occur

[0257]

[0258] Table 13Z4 slicing specific wiring Power parameters during the period when QA-1 to QA-5 problems exist / occur

[0259]

[0260] Table 14Z4 slicing specific wiring Power parameters during the period when QA-1 to QA-5 problems exist / occur

[0261]

[0262] Table 15Z4 slicing specific wiring Power parameters during the period when QA-1 to QA-5 problems exist / occur

[0263]

[0264] Table 16Z5 slicing specific wiring Power parameters during the period when QA-1 to QA-5 problems exist / occur

[0265]

[0266] Table 17Z6 Segment Specific Wiring Power parameters during the period when QA-1 to QA-5 problems exist / occur

[0267]

[0268] Table 18Z6 slicing specific wiring Power parameters during the period when QA-1 to QA-5 problems exist / occur

[0269]

[0270] The following are the specific connections of the six slices in the power supply area of ​​the embodiment and the power demand and capacity demand of each slice for mobile energy storage:

[0271] (I) Power supply area Z1 segmentation:

[0272] (1) Specific wiring of Z1 shards

[0273] Seek The initial value of the function vector at different time periods is

[0274] S 4N =630kVA;

[0275] max(P 7N )=1300kW; P 11N =240kW; get No

[0276] The power matrix of the same period is

[0277]

[0278] Therefore, the function vectors of different time periods can be obtained as

[0279]

[0280] Seek The power contraction vector at different time periods is

[0281]

[0282] Thus we can get Power demand for mobile energy storage at different times

[0283]

[0284] The maximum power adjustment factor on different dates during the investigation time period is:

[0285] Therefore, the specific wiring of shard Z1 The power demand for mobile energy storage during the time period under consideration is

[0286]

[0287] Find out the specific wiring of the slice Z1 Number of periods of 25% or more exchange power per day during the time period under consideration The corresponding shard Z1 specific wiring The capacity demand for mobile energy storage during the time period under consideration is

[0288]

[0289] (2) Specific wiring of Z1 shards

[0290] Seek The initial value of the function vector at different time periods is

[0291] S 4N =500kVA;

[0292] P 11N =260kW;

[0293] Seek The power matrix at different time periods is:

[0294]

[0295] Therefore, the function vectors of different time periods can be obtained

[0296]

[0297] Seek Power contraction vector at different time periods

[0298]

[0299] Thus we can get Power demand for mobile energy storage at different times

[0300]

[0301] The maximum power adjustment factor on different dates during the investigation time period is: Therefore, the specific wiring of shard Z1 The power demand for mobile energy storage during the time period under consideration is

[0302]

[0303] Find out the specific wiring of the slice Z1 The number of periods with 25% or more exchange power per day during the investigated time interval is The corresponding shard Z1 specific wiring The capacity demand for mobile energy storage during the time period under consideration is

[0304]

[0305] (3) Z1 shard’s combined power and capacity requirements for mobile energy storage

[0306] The total power and capacity demand for mobile energy storage in all mixed problem scenarios in power supply area segment Z1 during the investigated time interval is

[0307]

[0308] That is, the total power demand is 1216.6kW and the total capacity demand is 32696.5kWh;

[0309] (II) Power supply area Z2 segmentation in the embodiment

[0310] (1) Specific wiring of Z2 shards

[0311] Seek The initial value of the function vector at different time periods is

[0312] S 4N =800kVA;

[0313] Seek The power matrix at different time periods is:

[0314]

[0315] Therefore, the function vectors of different time periods can be obtained as

[0316]

[0317] Seek The power contraction vector at different time periods is

[0318]

[0319] Thus we can get The power demand for mobile energy storage at different times is

[0320]

[0321] The maximum power adjustment factor on different dates during the investigation time period is:

[0322] Therefore, the specific wiring of shard Z2 The power demand for mobile energy storage during the time period under consideration is

[0323]

[0324] Find out the specific wiring of the Z2 slice The number of periods with 25% or more exchange power per day during the investigated time interval is The corresponding shard Z2 specific wiring The capacity demand for mobile energy storage during the time period under consideration is

[0325]

[0326] (2) Specific wiring of Z2 shards

[0327] Seek The initial value of the function vector at different time periods is S 4N =800kVA; max(P 7N )=980kW;

[0328] Seek The power matrix at different time periods is:

[0329] Therefore, the function vectors of different time periods can be obtained as

[0330]

[0331] Seek The power contraction vector at different time periods is

[0332]

[0333] Thus we can get The power demand for mobile energy storage at different times is

[0334]

[0335] The maximum power adjustment factor on different dates during the investigation time period is:

[0336] Therefore, the specific wiring of shard Z2 The power demand for mobile energy storage during the time period under consideration is

[0337]

[0338] Find out the specific wiring of the Z2 slice The number of periods with 25% or more exchange power per day during the investigated time interval is

[0339]

[0340] The corresponding shard Z2 specific wiring The capacity demand for mobile energy storage during the time period under consideration is

[0341]

[0342] (3) Specific wiring of Z2 shards

[0343] Seek The initial value of the function vector at different time periods is

[0344] S 4N =800kVA;

[0345] P 10N =160kW;

[0346] Seek The power matrix at different time periods is:

[0347]

[0348] Therefore, the function vectors of different time periods can be obtained as

[0349]

[0350] Seek The power contraction vector at different time periods is

[0351]

[0352] Thus we can get The power demand for mobile energy storage at different times is

[0353]

[0354] The maximum power adjustment factor on different dates during the investigation time period is:

[0355] Therefore, the specific wiring of shard Z2 The power demand for mobile energy storage during the time period under consideration is

[0356]

[0357] Find out the specific wiring of the Z2 slice The number of periods with 25% or more exchange power per day during the investigated time interval is

[0358]

[0359] The corresponding shard Z2 specific wiring The capacity demand for mobile energy storage during the time period under consideration is

[0360]

[0361] (4) Z2 shard’s combined power and capacity requirements for mobile energy storage

[0362] The total power and capacity demand for mobile energy storage in all mixed problem scenarios in power supply area segment Z2 during the investigated time interval is

[0363] (III) Example Power Supply Area Z3 Slicing

[0364] (1) Specific wiring of Z3 shards Seek The initial value of the function vector at different time periods is

[0365] S 10N =96kW;

[0366] Seek The power matrix at different time periods is:

[0367]

[0368] Therefore, the function vectors of different time periods can be obtained as

[0369]

[0370] Seek The power contraction vector at different time periods is

[0371]

[0372] Thus we can get The power demand for mobile energy storage at different times is

[0373]

[0374] The maximum power adjustment factor on different dates during the investigation time period is:

[0375]

[0376] Therefore, the specific wiring of shard Z3 The power demand for mobile energy storage during the time period under consideration is

[0377]

[0378] The specific wiring of the Z3 slice can be obtained The number of periods with 25% or more exchange power per day during the investigated time interval is The corresponding shard Z3 specific wiring The capacity demand for mobile energy storage during the time period under consideration is

[0379]

[0380] (2) Total power and capacity requirements of mobile energy storage in Z3 segment

[0381] The total power and capacity demand for mobile energy storage in all mixed problem scenarios of power supply area segment Z3 during the investigated time interval is

[0382] (IV) Power supply area Z4 segmentation in the embodiment

[0383] (1) Specific wiring of Z4 shards

[0384] Seek The initial value of the function vector at different time periods is

[0385] S 4N =630kVA;

[0386] Seek The power matrix at different time periods is:

[0387]

[0388] Therefore, the function vectors of different time periods can be obtained as

[0389]

[0390] Seek The power contraction vector at different time periods is

[0391]

[0392] Thus we can get The power demand for mobile energy storage at different times is

[0393]

[0394] The maximum power adjustment factor on different dates during the investigation time period is:

[0395] Therefore, the specific wiring of shard Z4 The power demand for mobile energy storage during the time period under consideration is

[0396]

[0397] The specific wiring of the Z4 chip can be obtained The number of periods with 25% or more exchange power per day during the investigated time interval is Corresponding shard Z4 specific wiring The capacity demand for mobile energy storage during the time period under consideration is

[0398]

[0399] (2) Specific wiring of Z4 shards

[0400] Seek The initial value of the function vector at different time periods is

[0401] S 4N =630kVA; find No

[0402] The power matrix of the same period is

[0403]

[0404] Therefore, the function vectors of different time periods can be obtained as

[0405]

[0406] Seek The power contraction vector at different time periods is

[0407]

[0408] Thus we can get The power demand for mobile energy storage at different times is

[0409]

[0410] The maximum power adjustment factor on different dates during the investigation time period is: Therefore, the specific wiring of shard Z4 The power demand for mobile energy storage during the time period under consideration is

[0411]

[0412] Find out the specific wiring of the Z4 chip The number of periods with 25% or more exchange power per day during the investigated time interval is Corresponding shard Z4 specific wiring The capacity demand for mobile energy storage during the time period under consideration is

[0413]

[0414] (3) Specific wiring of Z4 shards

[0415] Seek The initial value of the function vector at different time periods is

[0416] S 4N =630kVA;

[0417] P 11N =230kW;

[0418] Seek The power matrix at different time periods is:

[0419]

[0420] Therefore, the function vectors of different time periods can be obtained as

[0421]

[0422] Seek The power contraction vector at different time periods is

[0423]

[0424] Thus we can get The power demand for mobile energy storage at different times is

[0425]

[0426] The maximum power adjustment factor on different dates during the investigation time period is:

[0427] Therefore, the specific wiring of shard Z4 The power demand for mobile energy storage during the time period under consideration is

[0428]

[0429] Find out the specific wiring of the Z4 chip The number of periods with 25% or more exchange power per day during the investigated time interval is Corresponding shard Z4 specific wiring The capacity demand for mobile energy storage during the time period under consideration is

[0430]

[0431] (4) Total power and capacity requirements of the Z4 segment for mobile energy storage

[0432] The total power and capacity requirements of all mixed problem scenarios in power supply area segment Z4 for mobile energy storage within the investigated time interval are:

[0433] (V) Example Power Supply Area Z5 Slicing

[0434] Seek The initial value of the function vector at different time periods is S 4N =630kVA; max(P 7N )=570kW;

[0435] Seek The power matrix at different time periods is:

[0436]

[0437] Therefore, the function vectors of different time periods can be obtained as

[0438]

[0439] Seek The power contraction vector at different time periods is

[0440]

[0441] Thus we can get The power demand for mobile energy storage at different times is

[0442]

[0443] The maximum power adjustment factor on different dates during the investigation time period is:

[0444] Therefore, the specific wiring of shard Z5 The power demand for mobile energy storage during the time period under consideration is

[0445]

[0446] Please find the specific wiring of the Z5 chip The number of periods with 25% or more exchange power per day during the investigated time interval is Corresponding shard Z5 specific wiring The capacity demand for mobile energy storage during the time period under consideration is

[0447]

[0448] (2) Total power and capacity requirements of mobile energy storage in Z5 segment

[0449] The total power and capacity requirements of all mixed problem scenarios in power supply area segment Z5 for mobile energy storage within the investigated time interval are:

[0450] (VI) Example Power Supply Area Z6 Slicing

[0451] (1) Specific wiring of Z6 segment

[0452] Seek The initial value of the function vector at different time periods is

[0453] S 4N =500kVA;

[0454] Seek The power matrix at different time periods is:

[0455]

[0456] Therefore, the function vectors of different time periods can be obtained as

[0457]

[0458] Seek The power contraction vector at different time periods is

[0459]

[0460] Thus we can get The power demand for mobile energy storage at different times is

[0461]

[0462] The maximum power adjustment factor on different dates during the investigation time period is: Therefore, the specific wiring of shard Z6 The power demand for mobile energy storage during the time period under consideration is

[0463]

[0464] Find out the specific wiring of the Z6 chip The number of periods with 25% or more exchange power per day during the investigated time interval is Corresponding shard Z6 specific wiring The capacity demand for mobile energy storage during the time period under consideration is

[0465]

[0466] (2) Specific wiring of Z6 segments

[0467] Seek The initial value of the function vector at different time periods is S 4N =630kVA; max(P 7N )=590kW; P 11N =270kW; find The power matrix at different time periods is:

[0468]

[0469] Therefore, the function vectors of different time periods can be obtained as

[0470]

[0471] Seek The power contraction vector at different time periods is

[0472]

[0473] Thus we can get The power demand for mobile energy storage at different times is

[0474]

[0475] The maximum power adjustment factor on different dates during the investigation time period is:

[0476] Therefore, the specific wiring of shard Z6 The power demand for mobile energy storage during the time period under consideration is

[0477]

[0478] Find out the specific wiring of the Z6 chip The number of periods with 25% or more exchange power per day during the investigated time interval is Corresponding shard Z6 specific wiring The capacity demand for mobile energy storage during the time period under consideration is

[0479]

[0480] (3) Total power and capacity requirements of the Z6 segment for mobile energy storage

[0481] The total power and capacity demand for mobile energy storage in all mixed problem scenarios of power supply area segment Z6 during the investigated time interval is

[0482] Calculate the total power demand and capacity demand for mobile energy storage in the entire power supply area:

[0483] The total power demand for mobile energy storage in the entire power supply area is obtained as

[0484]

[0485] Evaluate the solutions in different tiers:

[0486] The design scheme using mobile energy storage to eliminate the problems QA-1 to QA-5 in the power supply area is given as 2971.6kW and 82842.4kWh respectively. According to the evaluation rules,

[0487]

[0488] Therefore, the design scheme of the embodiment planning and designing personnel is an optimized solution. Therefore, the power supply area of ​​the embodiment adopts the design scheme to eliminate the problems QA-1 to QA-5, which will have a superior systematic application effect.

[0489] like Figure 3 The functional module schematic diagram of the system of the present invention is shown as follows: the system disclosed in the present invention for realizing the method for determining the application effect of the distributed mobile energy storage system comprises a data acquisition module, a set construction module, a scenario construction module, a data calculation module, an index calculation module and an effect determination module; the data acquisition module, the set construction module, the scenario construction module, the data calculation module, the index calculation module and the effect determination module are connected in series in sequence; the data acquisition module is used to obtain data information of the distributed mobile energy storage system to be determined, and data information of the corresponding new power system, and upload the data information to the set construction module; the set construction module is used to construct a problem set based on the received data information, for the problems existing in the new power system and the problems that can be solved by the distributed mobile energy storage system, and upload the data information to the scenario construction module; the scenario construction module is used to construct a problem set based on the received data information and the obtained problem set, based on the distributed mobile energy storage system that can be solved The problems to be solved and the relationships between the problems are determined, a mixed problem scenario set is determined, and a function vector is used to represent it, and the data information is uploaded to the data calculation module; the data calculation module is used to calculate the power calculation value and capacity calculation value of the distributed mobile energy storage system based on the received data information, the obtained mixed problem scenario set, and the operating requirements of the distributed mobile energy storage system and the new power system, and upload the data information to the indicator calculation module; the indicator calculation module is used to calculate the application effect judgment index of the distributed mobile energy storage system based on the received data information, the obtained power calculation value and capacity calculation value of the distributed mobile energy storage system, and the ratio of the power design value and capacity design value of the distributed mobile energy storage system, and upload the data information to the effect judgment module; the effect judgment module is used to complete the application effect judgment of the distributed mobile energy storage system based on the received data information and the obtained application effect judgment index of the distributed mobile energy storage system.

Claims

1. A method for determining the application effect of a distributed mobile energy storage system, characterized in that The steps include: S1. Obtaining data information of the distributed mobile energy storage system to be determined, and data information of the corresponding new power system; S2. Based on the data information obtained in step S1, a problem set is constructed for the problems existing in the new power system and the problems that the distributed mobile energy storage system can solve; S3. According to the problem set obtained in step S2, based on the problems that the distributed mobile energy storage system can solve and the relationship between the problems, determine a set of mixed problem scenarios and represent them using a function vector; S4. According to the hybrid problem scenario set obtained in step S3, based on the operating requirements of the distributed mobile energy storage system and the new power system, the power calculation value and capacity calculation value of the distributed mobile energy storage system are calculated; S5. Based on the power calculation value and capacity calculation value of the distributed mobile energy storage system obtained in step S4, and the ratio of the power design value and capacity design value of the distributed mobile energy storage system, the application effect determination index of the distributed mobile energy storage system is calculated; S6. According to the application effect determination index of the distributed mobile energy storage system obtained in step S5, the application effect determination of the distributed mobile energy storage system is completed.

2. The method for determining the application effect of a distributed mobile energy storage system according to claim 1, characterized in that The step S2 comprises the following steps: According to the problems that appear or exist in the new power system, as well as the technical solutions for the transformation or construction of the new power system, a total problem set, a planned problem set and a storage problem set are constructed; Using the ordinal vector scheme, a value is assigned to each element in the energy storage problem set; According to the specific location of the new power system corresponding to each element in the energy storage problem set, the positioning domain of the energy storage problem set is determined.

3. The method for determining the application effect of a distributed mobile energy storage system according to claim 2, characterized in that The step S2 specifically includes the following steps: Construct the total problem set, the planned problem set, and the energy storage problem set: The power supply area of ​​the new power system is divided into n z There are 100 regions, where the jth region is represented by Z j , j=1,2,...,n z ; For each patch Z j , define the total problem set Plan to solve the problem set and energy storage problem solving set Set the inspection time interval to n d days, where the dth day is represented by L d , d=1,2,...,n d ; On each day of the observation time interval, the time period is divided into n k time periods, where the kth time period is denoted as T k ,k=1,2,3,...,n k ; Sorting out the power supply area: If the area Z j In the time interval L d T k If there is a branch overload problem during the time period, the corresponding branch will form the first problem subset If the area Z j In the time interval L d T k If there is or occurs a node voltage over-limit problem during a period, the corresponding nodes will form a second problem subset If the area Z j In the time interval L d T k If there is a problem of local network renewable energy distributed generation and efficient consumption nearby during the period, the corresponding sub-scenario will form the third problem subset If the area Z j In the time interval L d T k If there is a sudden increase in the charging load of electric vehicles in the local network during the period, the corresponding sub-scenario will form the fourth problem subset If the area Z j In the time interval L d T k If there is a problem of high-reliability power supply demand in the local network during the period, the corresponding sub-scenario will form the fifth problem subset. Will and Find the union and get the total problem set In the total problem set To sort out: If the target power system adopts the technical solution of distribution network transformation or new construction to solve the problem of area Z j In the time interval L d T k If there are several heavy overload problems in the time period, the corresponding branches will be planned to solve the first problem subset If the target power system adopts the technical solution of distribution network transformation or new construction to solve the problem of area Z j In the time interval L d T k If there are or appear several node voltage exceeding limit problems in the time period, the corresponding several nodes will be planned to solve the second problem subset If the target power system adopts the technical solution of distribution network transformation or new construction to solve the problem of area Z j In the time interval L d T k If there are several local network renewable energy distributed generation problems that exist or appear in the period, the corresponding sub-scenarios will be used to plan and solve the third problem subset If the target power system adopts the technical solution of distribution network transformation or new construction to solve the problem of area Z j In the time interval L d T k If there are several local network electric vehicle charging load surge problems that exist or appear during the period, the corresponding sub-scenarios will constitute a plan to solve the fourth problem subset If the target power system adopts the technical solution of distribution network transformation or new construction to solve the problem of area Z j In the time interval L d T k If there are several local network high reliability power supply demand problems that exist or appear in the period, the corresponding sub-scenarios will constitute the fifth problem subset Will and Find the union and get the set of problems to be solved According to the total set of questions and plan to solve the problem set The energy storage problem set is calculated using the following formula In the formula Solve the first subset of problems for energy storage; Solve the second subset of problems for energy storage; Solve the third subset of problems for energy storage; Solve the fourth subset of problems for energy storage; Solve the fifth subset of problems for energy storage; p is the number of the subset of problems; Determine the sequence vector of the energy storage problem set: Problem Solving Set for Energy Storage Each element in is assigned a sequence vector of energy storage problem solving as shown below In the formula for The natural serial number of the elements in; The number of elements in the first subset of problems solved for energy storage; The number of elements in the second subset of problems solved for energy storage; Solve the element numbers in the third subset of the problem for energy storage; Solve the element numbers in the fourth subset of the problem for energy storage; Solve the element numbers in the fifth subset of the problem for energy storage; Determine the location domain of the energy storage problem set: The following formula is used to represent the location domain of the energy storage problem set: Among them, the site name is used to indicate the source of the grid-side power supply of the branch, node or sub-scenario that the energy storage solves the problem. When the grid-side power supply comes from the medium-voltage bus of the substation, the site name uses the corresponding substation name; when the grid-side power supply comes from the low-voltage bus of the distribution station, the site name uses the corresponding distribution station name; when the grid-side power supply comes from the switchgear bus, the site name uses the corresponding switchgear name; when the grid-side power supply comes from the distribution transformer, the site name uses the corresponding distribution point transformer name; when the grid-side power supply comes from the distribution line section, the site name uses the corresponding distribution line section name.

4. The method for determining the application effect of a distributed mobile energy storage system according to claim 2, characterized in that The step S3 comprises the following steps: Define a set of mixed problem scenarios; According to the topological structure of the new power system, a general wiring model is constructed; According to the elements in the first problem subset to the fifth problem subset solved by energy storage, the corresponding branches and specific wirings are determined in the constructed general wiring model, and compared and integrated to obtain a set of mixed problem scenarios; For each element in the obtained mixed problem scenario set, a function vector of the mixed problem scenario is calculated according to the existing or occurring problems.

5. The method for determining the application effect of a distributed mobile energy storage system according to claim 3 is characterized in that The step S3 specifically includes the following steps: Define a set of mixed problem scenarios: Solving Problems with Energy Storage Based on the connection, set the area Z j In the time interval L d T k The time period adopts a connection of the existence or emergence of energy storage to solve the first problem subset ~ energy storage to solve one or more problems in the fifth problem subset as a mixed problem scenario; j In the time interval L d T k The set of all mixed problem scenarios in the time period is called the mixed problem scenario set Construct a general wiring model: The general wiring model includes the main grid, main transformer, distribution line, distribution transformer, low-voltage incoming line circuit breaker, low-voltage busbar, new energy power station, distributed mobile energy storage system, conventional load, high-reliability power supply load and electric vehicle charging load; the main grid, main transformer and distribution line are connected in series in sequence; the distribution transformer is connected to the distribution line and connected to the low-voltage busbar through the low-voltage incoming line circuit breaker; the new energy power station, distributed mobile energy storage system, conventional load, high-reliability power supply load and electric vehicle charging load are all connected to the low-voltage busbar; Among them, the main power grid includes the AC transmission network or the AC high-voltage distribution network; the main transformer includes the main transformer in the substation; the distribution line includes the medium-voltage distribution line; the distribution transformer includes a step-down transformer that converts medium-voltage AC power into low-voltage AC power; the low-voltage incoming line circuit breaker is the grid power circuit breaker of the low-voltage bus, which is used to protect the low-voltage bus; the conventional load is all loads that have no requirements for power supply reliability except for the electric vehicle charging load; the high-reliability power supply load is all loads that require power supply reliability greater than the set value; Construction of a mixed problem scenario collection: A. Solving the first subset of problems for energy storage Get the first subset of questions The i1th element in , obtains the branch corresponding to the i1th element on the general wiring model, determines the wiring of the branch on the general wiring model, and represents the wiring as right Make a judgment: If the wiring With any wiring If they are the same, the i1th element is included in the wiring Subset of wiring problems If the wiring With all wiring If they are all different, the i1th element is classified as a connection Subset of wiring problems The value of j1 is 1 to (i1-1); B. Solving the second subset of problems for energy storage Get the second subset of questions The i2th element in , obtains the branch corresponding to the i2th element on the general wiring model, determines the wiring of the branch on the general wiring model, and represents the wiring as right Make a judgment: If the wiring With any wiring If they are the same, the i2th element is included in the wiring Subset of wiring problems If the wiring With any wiring If they are the same, the i2th element is included in the wiring Subset of wiring problems If the wiring With all wiring And all the wiring If they are different, the i2th element will be classified as a connection Subset of wiring problems The value of jj1 ranges from 1 to n1, where n1 is the number of elements in the first problem subset solved by energy storage; the value of j2 ranges from 1 to (i2-1); C. Solving the third subset of problems for energy storage Get the third subset of questions The i3th element in , obtains the branch corresponding to the i3th element on the general wiring model, determines the wiring of the branch on the general wiring model, and represents the wiring as right Make a judgment: If the wiring With any wiring If the same, the i3th element is included in the wiring Subset of wiring problems If the wiring With any wiring If the same, the i3th element is included in the wiring Subset of wiring problems If the wiring With any wiring If the same, the i3th element is included in the wiring Subset of wiring problems If the wiring With all wiring All wiring And all the wiring If they are all different, the i3th element is classified as a connection Subset of wiring problems jj2 is the number of elements in the second problem subset solved by energy storage; j3 has a value of 1 to (i3-1); D. Solve the fourth subset of problems for energy storage Get the fourth question subset The i4th element in , obtains the branch corresponding to the i4th element on the general wiring model, determines the wiring of the branch on the general wiring model, and represents the wiring as right Make a judgment: If the wiring With any wiring If the same, the i4th element is included in the wiring Subset of wiring problems If the wiring With any wiring If the same, the i4th element is included in the wiring Subset of wiring problems If the wiring With any wiring If the same, the i4th element is included in the wiring Subset of wiring problems If the wiring With any wiring If the same, the i4th element is included in the wiring Subset of wiring problems If the wiring With all wiring All wiring All wiring And all the wiring If they are all different, the i4th element is classified as a wiring Subset of wiring problems jj3 is the number of elements in the subset of the third problem solved by energy storage; j4 has a value of 1 to (i4-1); E. Solving the fifth subset of problems for energy storage Get the fourth question subset The i5th element in , obtains the branch corresponding to the i5th element on the general wiring model, determines the wiring of the branch on the general wiring model, and represents the wiring as right Make a judgment: If the wiring With any wiring If the same, the i5th element is included in the wiring Subset of wiring problems If the wiring With any wiring If the same, the i5th element is included in the wiring Subset of wiring problems If the wiring With any wiring If the same, the i5th element is included in the wiring Subset of wiring problems If the wiring With any wiring If the same, the i5th element is included in the wiring Subset of wiring problems If the wiring With any wiring If the same, the i5th element is included in the wiring Subset of wiring problems If the wiring With all wiring All wiring All wiring All wiring And all the wiring If they are all different, the i5th element is classified as a connection Subset of wiring problems Jj4 is the number of elements in the subset of the fourth problem solved by energy storage; the value of j5 is 1 to (i5-1); F. Take the union of all the connection problem sub-sets obtained from step A to step E to obtain the mixed problem scenario set Calculation of function vectors for mixed problem scenarios: Area Z j In the time interval L d T k Time There are n w Mixed problem scenarios, n w is the number of mixed problem scenarios, the following formula is used to calculate the 5-dimensional function vector of each mixed problem scenario: In the formula is the dimension element of the function vector of the sth hybrid problem scenario, corresponding to the function that the distributed mobile energy storage system needs to configure when eliminating the problem corresponding to the oth problem subset in the sth hybrid problem scenario; the value of o is 1 to 5; if the sth hybrid problem scenario exists or appears, the problem in the oth problem subset is solved by energy storage otherwise The power matrix of the function vector of the mixed problem scenario is set to determine the power of each dimension element of the function vector; Power Matrix Expressed as In the formula is the power variable element corresponding to the energy storage solving the oth problem subset; Calculate the function vector of the mixed problem scenario for 6. The method for determining the application effect of a distributed mobile energy storage system according to claim 4, characterized in that The step S4 comprises the following steps: According to the hybrid problem scenario set obtained in step S3, based on the operation requirements of the distributed mobile energy storage system and the new power system, the required power and capacity of the mobile energy storage are calculated; The required power and capacity of the mobile energy storage are optimized using a proportional coefficient scheme to obtain the power calculation value and capacity calculation value of the distributed mobile energy storage system.

7. The method for determining the application effect of a distributed mobile energy storage system according to claim 5, characterized in that The step S4 specifically comprises the following steps: Calculation of the required power and capacity of mobile energy storage: According to the mixed problem scenario set obtained in step S3 The following formula is used to calculate the area Z j In the time interval L d T k Mixed problem scenario for period s The power required for mobile energy storage In the formula is the power contraction vector, and Solve the power shrinkage factor of the oth problem subset for energy storage; Use the following formula to To obtain the value: according to The value selection rule of the area Z j The sth mixed problem scenario The power required for mobile energy storage within the time interval for: Where counter[·] represents the count of situations that satisfy the conditions in the square brackets; For area Z j The sth mixed problem scenario In the time interval L d The maximum daily power adjustment factor of mobile energy storage is Used to ensure the storage and release cycle of mobile energy storage system within 24 hours a day; k is the number of time periods in a 24-hour day. If 1 hour is 1 time period, then n k =24, if 15 minutes is one period, then n k =96; The number of periods in a 24-hour day when the energy storage power is greater than or equal to the maximum energy storage power of the day; The following formula is used to calculate the area Z j The sth mixed problem scenario Required capacity of mobile energy storage within the time interval In the formula for The mobile energy storage required is L d Number of periods of 25% or more of exchange power per day; Calculate the required power of mobile energy storage for Required capacity of mobile energy storage for Calculation of power and capacity calculation values ​​of distributed mobile energy storage systems: The power calculation value of the distributed mobile energy storage system is calculated using the following formula: and capacity calculation value In the formula Power optimization coefficient for mobile energy storage systems in regional power supply applications; It is the capacity optimization factor for the systematic application of mobile energy storage in the power supply area.

8. The method for determining the application effect of the distributed mobile energy storage system according to claim 7, characterized in that The step S5 specifically includes the following steps: The first judgment index a and the second judgment index b of the application effect of the distributed mobile energy storage system are calculated using the following formula: In the formula It is the power design value of the distributed mobile energy storage system; It is the capacity design value of distributed mobile energy storage system.

9. The method for determining the application effect of the distributed mobile energy storage system according to claim 8, characterized in that The step S6 specifically includes the following steps: According to the application effect determination index of the distributed mobile energy storage system obtained in step S5, the application effect determination of the distributed mobile energy storage system is performed using the following rules: like Then it is determined that the application effect of the distributed mobile energy storage system is optimal; like Then the application effect of the distributed mobile energy storage system is judged to be suboptimal; like Then the application effect of the distributed mobile energy storage system is judged to be feasible; like Then it is determined that the application effect of the distributed mobile energy storage system is too high; like It is determined that the application effect of the distributed mobile energy storage system is too difficult to achieve; like It is then determined that the application effect of the distributed mobile energy storage system is power-capacity imbalance.

10. A system for implementing the method for determining the application effect of the distributed mobile energy storage system according to any one of claims 1 to 9, characterized in that It includes a data acquisition module, a collection construction module, a scenario construction module, a data calculation module, an index calculation module and an effect determination module; the data acquisition module, the collection construction module, the scenario construction module, the data calculation module, the index calculation module and the effect determination module are connected in series in sequence; the data acquisition module is used to obtain the data information of the distributed mobile energy storage system to be determined, as well as the data information of the corresponding new power system, and upload the data information to the collection construction module; The set construction module is used to construct a problem set based on the received data information, targeting the problems existing in the new power system and the problems that the distributed mobile energy storage system can solve, and upload the data information to the scenario construction module; The scenario construction module is used to determine the mixed problem scenario set based on the received data information, the obtained problem set, the problems that the distributed mobile energy storage system can solve and the relationship between the problems, and express it using a function vector, and upload the data information to the data calculation module; The data calculation module is used to calculate the power calculation value and capacity calculation value of the distributed mobile energy storage system based on the received data information, the obtained mixed problem scenario set, and the operation requirements of the distributed mobile energy storage system and the new power system, and upload the data information to the indicator calculation module; The index calculation module is used to calculate the application effect judgment index of the distributed mobile energy storage system based on the received data information, based on the obtained power calculation value and capacity calculation value of the distributed mobile energy storage system, and the ratio of the power design value and capacity design value of the distributed mobile energy storage system, and upload the data information to the effect judgment module; the effect judgment module is used to complete the application effect judgment of the distributed mobile energy storage system based on the received data information and the obtained application effect judgment index of the distributed mobile energy storage system.

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