A method and system for optimizing the topology of a large-scale offshore wind farm power collection system

Abstract

The present invention relates to a method and system for optimizing the topological structure of a large-scale offshore wind farm power collection system. The method comprises: constructing a full life cycle cost model that takes reliability and economy into consideration, including one-time investment cost, operation and maintenance cost, line power loss, fault power loss, and fault repair cost; using a topological structure that satisfies current carrying capacity constraints, completing the selection of submarine cables according to the generated topological structure, calculating the full life cycle cost of each topological structure, and using the full life cycle cost as the objective function of the improved genetic algorithm to obtain the optimal topological structure of the power collection system. The present invention is simple and practical, takes into account the current carrying capacity constraints of submarine cables in large-scale offshore wind farms, and uses the full life cycle cost as the optimization target, which is conducive to the economical and reliable operation of the offshore wind farm power collection system.

Description

Technical Field

[0001] The present invention relates to the field of wind power generation, and more specifically, in particular to a method and system for optimizing the topological structure of a power collection system of a large-scale offshore wind farm. Background Art

[0002] Wind power generation has the characteristics of low noise and no pollution, and has gradually become the main form of global renewable energy development. Offshore wind energy resources are abundant, and offshore wind turbines have the advantages of large power generation and not occupying land, which has become a hot topic in the field of new energy research. The offshore wind farm collection system collects the electric energy generated by wind turbines and sends it to the power grid through offshore substations. It is mainly composed of wind turbines, submarine cables, booster stations, etc. The collection system of an offshore wind farm is an important structure for the wind farm to collect wind energy from wind turbines and then centrally transmit power. The structural design of the collection system is directly related to the investment cost. The optimization design of the offshore wind farm collection system is to find a more economical electrical wiring topology.

[0003] At present, domestic and foreign experts have conducted some research on the optimization of the topological structure of the offshore wind farm collection system. However, with the continuous increase in the scale of offshore wind farms and the continuous increase in wind turbine capacity, the number of wind turbines that can be connected on a single feeder is getting smaller and smaller. Therefore, when optimizing the topological structure of the collection system, the current carrying capacity constraints of the collection line should be fully considered. At the same time, in order to take into account the economy and reliability of the collection system, it is more reasonable to establish a full life cycle cost optimization model to optimize the topological structure of the offshore wind farm collection system. Summary of the invention

[0004] The object of the present invention is to provide a method and system for optimizing the topological structure of a large-scale offshore wind farm power collection system. The optimization design method can effectively design a power collection system topological structure with the lowest full life cycle cost taking into account the selection of submarine cables.

[0005] To achieve the above object, the technical solution of the present invention is: a method for optimizing the topological structure of a large-scale offshore wind farm power collection system, comprising the following steps:

[0006] Step S1, sort the wind turbines, and input wind turbine capacity and current carrying capacity limits of different types of submarine cables;

[0007] Step S2, calculating the number of wind turbines that can be connected to submarine cables of different types according to the current carrying capacity limits of submarine cables of different types;

[0008] Step S3, running a partheno-genetic algorithm that improves the matrix of adjustment variables in the breakpoint chromosome generation formula to generate a collection system topology with the lowest life cycle cost taking into account the maximum wind turbine capacity that different submarine cable models can withstand.

[0009] In one embodiment of the present invention, in step S2, the calculation formula for the number of wind turbines that can be connected to submarine cables of different models is:

[0010]

[0011] Where: floor is the rounding function, S cmax It is the maximum capacity allowed for the collection submarine cable, and P is the rated capacity of the wind turbine.

[0012] In one embodiment of the present invention, step S3 is specifically implemented as follows:

[0013] Step S31, creating an initial population, the population coding method adopts integer coding: the initial population is directly generated to meet the current carrying capacity restriction constraint of the submarine cable, and the specific generation method is:

[0014] Two chromosomes are used to jointly represent the topological structure of the power collection system. One chromosome is the wind turbine sequence chromosome, denoted as XL, and its length is the total number of wind turbines in the wind farm. The other chromosome is the breakpoint chromosome, denoted as DD, and its length is the number of feeders of the power collection system minus 1, ensuring that the topological structure of the power collection system is divided into multiple feeders.

[0015] Step S32, calculating the objective function according to the topological structure represented by the two chromosomes, where the objective function is the full life cycle cost of the power collection system;

[0016] Step S33, judging whether the termination condition is met, and using the maximum genetic generation as the evolution termination condition;

[0017] Step S34, performing a selection operation, dividing the population individuals into groups of eight, and selecting a topological structure with the smallest objective function in each group;

[0018] Step S35, performing genetic operator operations to perform flipping, swapping and sliding operations on each selected minimum topological structure to generate a new population;

[0019] Step S36, repeat steps S33-S35, perform iterative operations, until the termination condition is reached, and output the optimal topological structure.

[0020] In one embodiment of the present invention, the breakpoint chromosome generation formula is:

[0021] DD=n max ×[1:N k -1]-cumsum(j)

[0022] Where: n max N is the maximum number of wind turbines that can be connected to a single feeder. k is the number of feeders in the collection system, and cumsum is the cumulative sum function.

[0023] In one embodiment of the present invention, when generating a breakpoint chromosome, two variables are set, namely, a free point variable d and a regulating variable j, wherein:

[0024] d=n max ×N k -N

[0025] Where: n max N is the maximum number of wind turbines that can be connected to a single feeder. k is the number of feeders in the collection system, and N is the total number of wind turbines;

[0026] By adjusting the variable j, the breakpoint interval is ensured to be smaller than the maximum number of wind turbines that can be connected to a single feeder, and the capacity of wind turbines connected to each feeder is controlled not to exceed the maximum capacity that the submarine cable can bear.

[0027] In one embodiment of the present invention, the adjustment variable j is a randomly generated N k A matrix with -1 columns.

[0028] In one embodiment of the present invention, the matrix of the adjustment variable j has the following two restrictions:

[0029] (1) The value range of each element is [0, n max );

[0030] (2) The cumulative sum of all elements is in the range [dn max +1, d].

[0031] In one embodiment of the present invention, in step S32, the objective function calculation formula is as follows:

[0032] C=C1+C2+C3+C4+C5

[0033] Among them, C is the full life cycle cost of the collection system, C1 is the one-time investment cost, C2 is the operation and maintenance cost, C3 is the line power loss, C4 is the fault power loss, and C5 is the fault repair cost.

[0034] The one-time investment cost is the total cost of the construction of the power collection system, including the purchase and construction costs of major equipment such as cables and switches. The calculation formula is:

[0035]

[0036] Where: N t is the number of feeders in the collection system, C S is the purchase and installation cost of circuit breakers (10,000 yuan / unit), is the number of collector cables connected to the kth feeder, is the purchase cost of the i-th collector cable of unit length (unit: 10,000 yuan / km); is the construction cost of the i-th collector cable per unit length (unit: 10,000 yuan / km), L i is the length of the i-th collector cable (unit: km).

[0037] The operation and maintenance cost of the power collection system mainly comes from the inspection and maintenance of the power collection cable. The calculation formula is:

[0038]

[0039] Where: N t is the number of feeders in the collection system, is the number of collector cables connected to the kth feeder, is the maintenance cost of the i-th collector cable per unit length (unit: 10,000 yuan / (km·a)); L i is the length of the ith collector cable (unit: km); T is the life cycle of the offshore wind farm (unit: year).

[0040] The power loss of the line mainly comes from the economic loss caused by the power loss during the operation of the power collection system. The calculation formula is as follows:

[0041]

[0042]

[0043] Where: N t is the number of feeders in the collection system, is the number of collector cables connected to the kth feeder, m is the additional loss coefficient of the submarine cable, and the three-core submarine cable is 1.4, I i is the current carrying capacity of the ith collector cable (unit: kA), R i is the resistance per unit length of the i-th collector cable (Ω / km), L i is the length of the i-th collector cable (unit: km), α is the on-grid electricity price (unit: yuan / kW·h), t is the annual utilization hours of the offshore wind farm (unit: h / year), and T is the life cycle of the offshore wind farm (unit: year). i is the total power of the wind turbine connected to the i-th collector cable (MW), U (unit: kV) is the voltage level of the collector line, is the power factor of the wind turbine.

[0044] Fault power loss refers to the economic loss caused by the inability to output power due to failure of circuit breakers, cables and other components, which is equivalent to the loss of the income that the wind farm should have received under normal working conditions. The calculation formula is as follows:

[0045]

[0046]

[0047] Where: N t is the number of feeders in the collection system, is the number of collector cables connected to the kth feeder, Q i is the probability that the subsequent wind turbine power cannot be delivered due to the failure of the i-th collector cable (unit: times / a), is the failure rate of the i-th collector cable (unit: times / (km*a)), L i is the length of the i-th collector cable (unit: km), is the average power output of the wind turbine connected to the i-th collector cable (MW), is the fault maintenance time of the ith submarine cable (unit: h), α is the on-grid electricity price (unit: yuan / kW*h), T is the life cycle of the offshore wind farm (unit: year), q s is the circuit breaker failure rate (unit: times / a), is the average total power output of the wind turbines connected to the kth collector feeder (MW), t s is the fault maintenance time of the circuit breaker (unit: h).

[0048] Fault repair cost refers to the cost of repairing components such as circuit breakers and cables after they fail. The formula for calculating fault repair cost is:

[0049]

[0050] Where: N t is the number of feeders in the collection system, is the number of collector cables connected to the kth feeder, is the failure rate of the i-th collector cable (unit: times / (km*a)), L i is the length of the i-th collector cable (unit: km), is the maintenance cost of the i-th collector cable per unit length (unit: 10,000 yuan / km), q s is the circuit breaker failure rate (unit: times / a), is the maintenance cost of circuit breaker (10,000 yuan / unit), and T is the life cycle of offshore wind farm (unit: year).

[0051] After the wind farm is scrapped, the submarine cable will have a certain residual value after recycling, but the recycling requires labor and corresponding equipment costs, and the two parts can be considered to offset each other to zero.

[0052] In one embodiment of the present invention, in step S34, the objective function is minimized, that is, the life cycle cost of the power collection system is minimized. Considering the current carrying capacity and laying cross conditions of the submarine cable in actual engineering as constraints, an optimization model is established as follows:

[0053]

[0054] Where: n is the number of wind turbines that can be connected to each feeder, S cmax is the maximum capacity allowed to be connected by the collecting submarine cable, P is the rated capacity of the wind turbine, A, B, C, and D are the points represented by any four wind turbines, represents the cross product calculation, and represents the dot product calculation.

[0055] The present invention also provides a large-scale offshore wind farm collection system topology optimization system, including a memory, a processor, and computer program instructions stored in the memory and capable of being executed by the processor. When the processor executes the computer program instructions, the method steps described above can be implemented.

[0056] Compared with the prior art, the present invention has the following beneficial effects: the method of the present invention is simple and practical, and takes into account the current-carrying capacity constraints of submarine cables in large-scale offshore wind farms. It takes the full life cycle cost as the optimization target, and can obtain a topological structure with the optimal full life cycle cost, which is conducive to the economic operation of the offshore wind farm collection system. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 A schematic diagram of a flow chart of a topology design method for an offshore wind farm power collection system according to the present invention;

[0058] Figure 2 A schematic diagram of a flow chart of an improved parthenogenetic algorithm of the present invention;

[0059] Figure 3 The coordinates of the wind turbines and booster station in the offshore wind farm in the embodiment;

[0060] Figure 4 A schematic diagram of a topological structure obtained with the lowest one-time investment cost in the embodiment;

[0061] Figure 5 It is a schematic diagram of the topological structure obtained with the lowest life cycle cost in the embodiment. DETAILED DESCRIPTION

[0062] The technical solution of the present invention is described in detail below in conjunction with the accompanying drawings.

[0063] The present invention provides a method for optimizing the topological structure of a large-scale offshore wind farm power collection system, comprising the following steps:

[0064] Step S1, sort and number the wind turbines, input the location coordinates of each wind turbine and the offshore booster station, wind turbine capacity, submarine cable model, and current carrying capacity limits of different submarine cable models;

[0065] Step S2, calculating the number of wind turbines that can be connected to submarine cables of different types according to the current carrying capacity limits of submarine cables of different types;

[0066] Step S3: Run the improved parthenogenetic algorithm to generate a collection system topology structure with the lowest cost in consideration of different submarine cable models and the entire life cycle.

[0067] The present invention also provides a large-scale offshore wind farm collection system topology optimization system, including a memory, a processor, and computer program instructions stored in the memory and capable of being executed by the processor. When the processor executes the computer program instructions, the method steps described above can be implemented.

[0068] The following are specific implementation examples of the present invention.

[0069] See also Figure 1 As shown, a topology design method for an offshore wind farm power collection system includes the following steps:

[0070] Step 1: Input the location coordinates of the wind turbine and the offshore booster station, the wind turbine capacity, the type of submarine cable planned to be used, and the current carrying capacity limit of different types of submarine cables.

[0071] Step 2: Calculate the number of wind turbines that can be connected to different types of submarine cables based on their current carrying capacity limits. The calculation formula is:

[0072]

[0073] Where: floor is the rounding function, S cmax It is the maximum capacity allowed for the collection submarine cable, and P is the rated capacity of the wind turbine.

[0074] Step 3: Run the improved single-parent genetic algorithm to generate the collector system topology with the lowest cost considering different submarine cable models and the entire life cycle.

[0075] The specific process of the improved parthenogenetic algorithm is described below:

[0076] like Figure 2 As shown, an improved one-parent genetic algorithm comprises the following steps:

[0077] Step 1: Create an initial population, set the population size to 400, use integer coding for population coding, and use two chromosomes to jointly represent the topological structure of the power collection system. One chromosome is the wind turbine sequence chromosome, denoted by XL, and its length is the total number of wind turbines in the wind farm. The other chromosome is the feeder breakpoint chromosome, denoted by DD, and its length is the number of feeders in the power collection system minus one, ensuring that the topological structure of the power collection system is divided into multiple feeders. For example, for a power collection system with 15 wind turbines, a path chromosome XL is:

[0078] [2-5-7-8-11-13-14-4-9-3-6-10-12-15-16]

[0079] The feeder breakpoint chromosome DD is:

[0080] [3-7-11]

[0081] The corresponding collection system topology has 4 feeders, and the specific connection methods are 1-2-5-7, 1-8-11-13-14, 1-4-9-3-6, and 1-10-12-15-16. No. 1 is the offshore booster station, and the sequence number in the chromosome XL of the wind turbine path means the wind turbine sequence number plus 1.

[0082] Set up two variables, namely the free point variable d and the adjustment variable j.

[0083] d=n max ×N k -N

[0084] Where: n max N is the maximum number of wind turbines that can be connected to a single feeder. k is the number of feeders in the collection system, and N is the total number of wind turbines.

[0085] By adjusting the variable j, we ensure that the breakpoint interval is less than the maximum number of wind turbines that can be connected to the single feeder, and control the wind turbine capacity connected to each feeder to not exceed the maximum capacity that the submarine cable can bear. The adjustment variable j is a randomly generated 1-row N k -1 column matrix, and add two restrictions to it: (1) the value range of each element is [0, n max ), (2) the cumulative sum of all elements is in the interval [dn max +1,n max ].

[0086] The formula for generating breakpoint chromosomes is:

[0087] DD=n max ×[1:N k -1]-cumsum(j)

[0088] Where: cumsum is the cumulative sum function.

[0089] For example:

[0090] Assume that a single feeder can connect a maximum of n wind turbines max =4, number of feeders N k =5, the total number of wind turbines N = 15. The chromosome matrix of a set of paths is [2-4-6-8-10-12-14-16-15-13-3-5-7-9-11].

[0091] Then the free point variable d = n max ×N k -N = 4 × 5-15 = 5;

[0092] j is 1 row N k -1 column matrix, the values ​​of each element must be in the interval [0, 4), and the tj matrix generated in a certain time is

[1012] ;

[0093] The value range of the sum of the j matrix elements is [dof-max+1, dof]=[2,5], and suppose a random value is 4.

[0094] but:

[0095] DD=n max ×[1:N k -1]-cumsum(j)=4×[1,2,3,4]-[1,1,2,4]

[0096] =[4,8,12,16]-[1,1,2,4]=[3,7,10,12]

[0097] The corresponding topological structure connection modes are 1-2-4-6, 1-8-10-12-14, 1-16-15-13, 1-3-5, 1-7-9-11. No. 1 is the offshore booster station.

[0098] Step 2: Calculate the objective function; the objective function is the total cost of the entire life cycle.

[0099] Step 3: Determine whether the termination condition is met and use the maximum genetic generation as the evolution termination condition.

[0100] Step 4: Perform a selection operation, divide the population into 50 groups, and select a topological structure with the smallest objective function in each group.

[0101] Step 5: Perform genetic operator operations to flip, exchange and slide each selected minimum topological structure to generate a new population.

[0102] Step 6: Repeat steps 3, 4, and 5, perform iterative operations, until the termination condition is reached, and output the optimal topological structure.

[0103] Figure 3 The coordinates of the wind turbines and booster stations in the offshore wind farm in the embodiment. The total capacity of the wind farm in the embodiment is 240MW, the capacity of a single wind turbine is 6.45MW, there are 38 wind turbines in total, and the voltage level of the power collection system is 35kV. There are 4 types of power collection submarine cables, namely 3*70mm 2 、3*150mm 2 、3*240mm 2 、3*500mm 2 The parameters of circuit breakers and various types of submarine cables are shown in Table 1 and Table 2.

[0104] Table 1 Circuit breaker parameters

[0105]

[0106]

[0107] The on-grid electricity price is α=0.85 yuan / kWh, the annual utilization hours are 4000h, and the design period is 25 years.

[0108] like Figure 4 As shown in Table 3, the various costs obtained by taking the one-time investment cost as the objective function are shown in Table 3

[0109] Table 3

[0110]

[0111] like Figure 5 As shown in Table 4, the various costs obtained by taking the total life cycle cost as the objective function are shown in Table 4

[0112] Table 4

[0113]

[0114] It can be seen from the above embodiments that the topological structure optimization method of the offshore wind farm collection system of the present invention saves 21.79 million yuan in total investment in the whole life cycle cost compared with the topological structure obtained by taking the shortest submarine cable length as the optimization target, and has good practical value.

[0115] The above-mentioned embodiment only expresses one implementation mode of the present invention, and its description is relatively specific and detailed, but it cannot be understood as limiting the scope of the patent of the present invention. It should be pointed out that for ordinary technicians in this field, several modifications and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be based on the attached claims.

[0116] The above are preferred embodiments of the present invention. Any changes made according to the technical solution of the present invention, as long as the resulting functions do not exceed the scope of the technical solution of the present invention, belong to the protection scope of the present invention.

Claims

1. A method for optimizing the topological structure of a large-scale offshore wind farm power collection system, characterized in that: The steps include: Step S1, sort the wind turbines, and input wind turbine capacity and current carrying capacity limits of different types of submarine cables; Step S2, calculating the number of wind turbines that can be connected to submarine cables of different types according to the current carrying capacity limits of submarine cables of different types; Step S3, running a partheno-genetic algorithm of a matrix of adjustment variables in an improved breakpoint chromosome generation formula to generate a collection system topology with the lowest life cycle cost taking into account the maximum wind turbine capacity that different submarine cable models can bear; The breakpoint chromosome generation formula is: DD=n max ×[1:N k −1]-cumsum(j) Where: n max N is the maximum number of wind turbines that can be connected to a single feeder. k is the number of feeders in the collection system, cumsum is the cumulative sum function; When generating breakpoint chromosomes, two variables are set up, namely the free point variable d and the adjustment variable j, where: d=n max ×N k -N Where: n max N is the maximum number of wind turbines that can be connected to a single feeder. k is the number of feeders in the collection system, and N is the total number of wind turbines; By adjusting the variable j, the breakpoint interval is ensured to be less than the maximum number of wind turbines that can be connected to a single feeder, and the wind turbine capacity connected to each feeder is controlled not to exceed the maximum capacity that the submarine cable can bear; The adjustment variable j is a randomly generated row N k -1 column matrix; The matrix of adjustment variables j has the following two restrictions: (1) The value range of each element is [0, n max ); (2) The cumulative sum of all elements is in the range [dn max +1, d].

2. A method for optimizing the topology structure of a large-scale offshore wind farm power collection system according to claim 1, characterized in that: In step S2, the calculation formula for the number of wind turbines that can be connected to different types of submarine cables is: Where: floor is the rounding function, S cmax It is the maximum capacity allowed for the collection submarine cable, and P is the rated capacity of the wind turbine.

3. A method for optimizing the topological structure of a large-scale offshore wind farm power collection system according to claim 1 or 2, characterized in that: The step S3 is specifically implemented as follows: Step S31, create an initial population, the population coding method adopts integer coding: the initial population is directly generated to meet the current carrying capacity restriction constraint of the submarine cable, and the specific generation method is: Two chromosomes are used to jointly represent the topological structure of the power collection system. One chromosome is the wind turbine sequence chromosome, denoted as XL, and its length is the total number of wind turbines in the wind farm. The other chromosome is the breakpoint chromosome, denoted as DD, and its length is the number of feeders of the power collection system minus 1, ensuring that the topological structure of the power collection system is divided into multiple feeders. Step S32, calculating the objective function according to the topological structure represented by the two chromosomes, where the objective function is the full life cycle cost of the power collection system; Step S33, judging whether the termination condition is met, and using the maximum genetic generation as the evolution termination condition; Step S34, performing a selection operation, dividing the population individuals into groups of eight, and selecting a topological structure with the smallest objective function in each group; Step S35, performing genetic operator operations to perform flipping, swapping and sliding operations on each selected minimum topological structure to generate a new population; Step S36, repeat steps S33-S35, perform iterative operations, until the termination condition is reached, and output the optimal topological structure.

4. A method for optimizing the topology structure of a large-scale offshore wind farm power collection system according to claim 3, characterized in that: In step S32, the objective function calculation formula is as follows: C=C1+C2+C3+C4+C5 Among them, C is the full life cycle cost of the collection system, C1 is the one-time investment cost, C2 is the operation and maintenance cost, C3 is the line power loss, C4 is the fault power loss, and C5 is the fault repair cost.

5. A method for optimizing the topology structure of a large-scale offshore wind farm power collection system according to claim 4, characterized in that: In step S34, the objective function is minimized, that is, the life cycle cost of the power collection system is minimized. Considering the current carrying capacity and laying cross conditions of the submarine cable in the actual project as constraints, the optimization model is established as follows: Where: n is the number of wind turbines that can be connected to each feeder, S cmax is the maximum capacity allowed to be connected by the collecting submarine cable, P is the rated capacity of the wind turbine, A, B, C, and D are the points represented by any four wind turbines, represents the cross product calculation, and represents the dot product calculation.

6. A large-scale offshore wind farm power collection system topology optimization system, characterized in that: The method comprises a memory, a processor and computer program instructions stored in the memory and executable by the processor. When the processor executes the computer program instructions, the method steps as claimed in any one of claims 1 to 5 can be implemented.

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