Two-stage optimization method for power distribution network of super high-rise building considering load characteristics

Abstract

The application discloses a two-stage optimization method for an ultrahigh-rise building power distribution network considering load characteristics, and is performed according to the following steps: 1, counting load information of the ultrahigh-rise building; 2, building an optimal division model of a power supply area of the ultrahigh-rise building; and 3, building a multi-objective planning model of a main line of the ultrahigh-rise building power distribution network. The application can realize planning of the ultrahigh-rise building power distribution network, wherein the power supply area division considering the load characteristics can not only increase stability of system operation, but also reduce capacity configuration requirements of a transformer and reduce operation loss of the system.

Description

Technical Field

[0001] This invention relates to the field of power distribution network planning research for super high-rise buildings, specifically a two-stage optimization method for power distribution networks of super high-rise buildings that takes into account load characteristics. Background Technology

[0002] Super high-rise buildings typically integrate residential and commercial buildings, office buildings, high-end apartments, hotels, entertainment venues, large shopping malls, department stores, and underground parking garages. They exhibit diverse and high-density loads, with significant differences in the characteristics of loads from different business types. Therefore, the scientific and rational configuration of transformers and their power supply lines within the building plays a crucial role in improving the safety, reliability, and stability of the power supply and distribution system in super high-rise buildings. The planning of the power supply and distribution system within super high-rise buildings falls under the medium- and low-voltage distribution network level. Current research has analyzed and discussed the site selection and capacity determination of transformers in super high-rise buildings. However, simply determining the final transformer configuration scheme based on a simple comparison of operating parameters between different schemes, based solely on meeting the power design specifications for super high-rise buildings, cannot guarantee the optimality of the selected scheme.

[0003] Optimizing transformer configuration begins with determining its power supply range. Power supply zones defined solely by land use and load volume often exhibit high peak load rates but low average load rates, large peak-to-valley differences, and low equipment utilization. Therefore, current research considers load characteristics when defining power supply zones. However, multi-functional high-rise buildings, with their diverse business types, varying load characteristics, and geographical overlap, present optimization conditions and opportunities for dividing power supply zones based on load characteristics. Once the power supply zones are determined, an optimization model can be established to obtain the distribution network configuration scheme. To balance equipment capacity and operational efficiency, distribution network planning is typically divided into multiple stages or integrates planning and operation. However, existing research largely focuses on urban distribution network planning, lacking studies on distribution network planning for high-rise buildings.

[0004] The power distribution network planning for super high-rise buildings differs significantly from traditional "planar" power distribution network planning. On one hand, transformers in super high-rise buildings can only be placed on refuge floors or equipment floors, and the division of power supply zones must consider the location constraints of the transformers. On the other hand, during the network planning stage, "vertical" power distribution lines have a fixed extension direction, extending only from the transformer outlet to the end of the power supply zone. Based on these factors, traditional "planar" power distribution network planning methods are difficult to apply. Summary of the Invention

[0005] To avoid the shortcomings of the prior art, this invention provides a two-stage optimization method for power distribution networks of super high-rise buildings that takes into account load characteristics. The aim is to find the optimal power distribution scheme for super high-rise buildings through optimization, which can not only reduce the capacity of transformers, but also further improve the safety and stability of the power distribution network operation of super high-rise buildings.

[0006] The present invention adopts the following technical solution to solve the technical problem:

[0007] This invention provides a two-stage optimization method for a power distribution network of a super high-rise building that takes into account load characteristics. The power distribution network of the super high-rise building is supplied with 10kV power from the city substation, and then connected to the substation on each floor via cable. A 0.4kV dense busbar trunking is then configured to supply power to each floor.

[0008] The components in the power distribution network of the super high-rise building include: 10kV distribution cabinets, 10kV cables, 10 / 0.4kV transformers, and 0.4kV high-density busbar trunking; its characteristic is that the two-stage optimization method is carried out according to the following steps:

[0009] Step 1: Compile the load information of the super high-rise building, including: the load of each floor and the daily load curve of each floor on typical weekdays in all four seasons; Let S c,k Let S be the total load of the k-th floor; c,k,j,t Let t be the load of the k-th floor at time t on a typical workday in season j; 1≤t≤24 represents the 24 times of day; j=1,2,3,4 represent spring, summer, autumn, and winter, respectively.

[0010] Step 2: Construct the optimal partitioning model for the power supply zone of super high-rise buildings;

[0011] Step 2.1: Divide the power supply zones within the super high-rise building; combine the loads of the super high-rise building with the standard specifications of 10 / 0.4kV transformer capacity to form power supply zones, and the load of each power supply zone shall not exceed the capacity of the 10 / 0.4kV transformer.

[0012] Let S T,i Let {S} be the capacity of the 10 / 0.4kV transformer in the i-th power supply zone. Then, the capacity of the 10 / 0.4kV transformer in each power supply zone is denoted as {S}. T,1 ,S T,2 ,...,S T,i ,...,S T,N} 1×N Where N represents the maximum number of power supply zones, and N is equal to the total building load divided by the minimum transformer configuration specification and rounded down.

[0013] Step 2.2: The optimal division model for the power supply area of ​​the super high-rise building is based on the 10 / 0.4kV transformer capacity S of the i-th power supply area. T，iTo optimize the variables, the average load saturation f1, average daily load rate f2, and average peak-to-valley difference f3 of N power supply zones are used as evaluation indicators for the division. The maximum weighted sum of the evaluation indicators is used as the optimization objective F of the optimal division model for the power supply zones of the super high-rise building. Simultaneously, constraints are constructed for the optimal division model of the power supply zones of the super high-rise building. Under these constraints, after solving the optimization objective F, the optimal power supply zone division parameters are output, including: the starting floor number Start of the i-th power supply zone. i End of the terminus of the i-th power supply zone i The total load S of the i-th power supply zone D,i ;

[0014] Step 3: Construct a multi-objective planning model for the main power distribution network of the super high-rise building, and combine it with the optimal partitioning model of the power supply area of ​​the super high-rise building to form a two-stage optimization model for the power distribution network of the super high-rise building.

[0015] Step 3.1: Calculate the load simultaneity factor K for the i-th power supply zone based on the power supply zone division parameters. i and calculated load S Z,i And, under the condition of meeting the configuration constraints of 10 / 0.4kV transformers, select the model of 10 / 0.4kV transformers in each power supply area;

[0016] Step 3.2: Select the installation location of the transformer in each power supply area {W} T,1 W T,2 ,...,W T,i ,...,W T,N} 1×N Among them, W T,i This represents the floor number where the 10 / 0.4kV transformer is located in the i-th power supply zone;

[0017] A dense busbar trunking system is configured for the 10kV incoming cable and 0.4kV outgoing line of the 10 / 0.4kV transformer, based on the current carrying capacity.

[0018] The multi-objective programming model for the main power distribution line of the super high-rise building is based on the installation location {W} of the 10 / 0.4kV transformer. T,1 W T,2 ,...,W T,i ,...,W T,N} 1×NTo optimize the variables, the 10 / 0.4kV transformer capacity g1, 10kV cable length g2, 10kV cable annual network loss g3, 0.4kV busbar length g4, and 0.4kV busbar annual network loss g5 of N power supply areas are used as the multiple optimization objectives of the multi-objective programming model. The constraints of the multi-objective programming model of the main line of the power distribution network of the super high-rise building are constructed. Under these constraints, after solving the multi-objective programming model, the Pareto optimal solution set G that makes the multiple optimization objectives smaller is obtained.

[0019] Step 3.3: Use the entropy weight method to select a compromise optimal solution G' from the Pareto optimal solution set G, which is the optimal planning scheme for the power distribution network of super high-rise buildings.

[0020] The two-stage optimization method for the power distribution network of super high-rise buildings that takes into account load characteristics, as described in this invention, is characterized in that, in step 2.2, the average load saturation f1 is calculated using equation (1):

[0021]

[0022] Calculate the average daily load factor f2 using equations (2) to (5):

[0023]

[0024]

[0025]

[0026]

[0027] In equations (2) to (5), S D,i,j,t S represents the load at time t on a typical weekday in season j for the i-th power supply area; av,i,j S represents the average load of the i-th power supply area on a typical weekday in the j-th season. max,i,j Let be the maximum load of the i-th power supply area on a typical working day in the j-th season;

[0028] Calculate the average peak-to-valley difference f3 using equations (6) and (7):

[0029]

[0030]

[0031] In equation (7), S min,i,j Let be the minimum load of the i-th power supply area on a typical working day in the j-th season;

[0032] The optimization objective F for the division of the power supply area is calculated using equation (8):

[0033] max F=w1f1+w2f2+w3f3 (8)

[0034] In equation (8), w1, w2, and w3 are the weights of each positive indicator, respectively;

[0035] The constraints of the optimal power supply zone division model for super high-rise buildings include:

[0036] 1) Obtain the load constraint of the power supply area using equation (9):

[0037]

[0038] In equation (9), S T,i The specification of the transformer capacity for the i-th power supply zone; power supply zones are allocated starting from the ground floor of the building, with the transformers for the first m power supply zones placed in the podium and basement, and the transformers for power supply zones m to N placed in the refuge floors or equipment floors on the upper floors of the building;

[0039] 2) Obtain the load saturation rate constraint of the power supply area using equation (10):

[0040]

[0041] In equation (10), β L The load factor of the transformer;

[0042] 3) Obtain the power supply demand constraint using equation (11):

[0043]

[0044] In equation (11), Start i Indicates the starting floor number of the i-th power supply zone, End i Let represent the number of the terminating floors of the i-th power supply zone, which is obtained from equation (12);

[0045]

[0046] The total load S of the i-th power supply zone is obtained using equation (13). D,i :

[0047]

[0048] In step 3.1, the load simultaneity factor K of the i-th power supply zone is calculated using equation (14). i :

[0049]

[0050] The calculated load S of the i-th power supply zone is calculated using equation (15). Z,i:

[0051] S Z,i =K i ×S D,i (15)

[0052] Using equations (16) and (17), configure the constraints for a 10 / 0.4kV transformer:

[0053] α Z ×S Z,i ≤S T,i (16)

[0054] S D,i(Ⅰ,Ⅱ) ≤S T,i (17)

[0055] In equations (16) and (17), α Z S represents the percentage of the total computational load. D,i(Ⅰ，Ⅱ) This represents all primary and secondary loads in the i-th power supply zone.

[0056] In step 3.2, the total capacity g1 of the 10 / 0.4kV transformers of the main line is calculated using equation (18):

[0057]

[0058] Calculate the length g2 of the 10kV cable using equation (19):

[0059]

[0060] In equation (19), W T,i W represents the floor where the transformer for the i-th power supply zone is located. T10,i Let this be the floor number of the 10kV incoming substation in the i-th power supply zone. The average floor height of a super high-rise building;

[0061] Calculate the annual network loss g3 of a 10kV cable using equation (20):

[0062]

[0063] In equation (20), I L10,i Let r be the current of the incoming line of the transformer in the i-th power supply area, which is obtained from equation (21). L10，i Let T be the unit resistance of the 10kV incoming cable of the i-th power supply zone. max Maximum load utilization hours;

[0064]

[0065] In equation (21), U N Indicates the rated voltage;

[0066] Calculate the length g4 of the 0.4kV busbar using equation (22):

[0067]

[0068] In equation (22), L up,i L down,i These represent the maximum upstream and downstream supply distances of the dense busbars in the i-th power supply zone;

[0069] Based on the location relationship between the transformer and the power supply area, the power supply mode of the transformer is divided into top-supply, bottom-supply, and top-and-bottom-supply, and the annual network loss g5 of the 0.4kV dense busbar is calculated using equations (23) to (26):

[0070]

[0071]

[0072]

[0073]

[0074] In equations (23) to (26), eP up,i eP down,i These represent the upstream and downstream power losses of the dense busbar in the i-th power supply zone, respectively, eU up,i eU down,i These represent the percentages of upstream and downstream voltage losses for the dense busbar in the i-th power supply zone, respectively. up,i I down,i S represents the upstream and downstream supply currents of the dense busbar in the i-th power supply zone, respectively. up,i S down,i These are the upstream and downstream loads supplied by the dense busbar in the i-th power supply zone, respectively.

[0075] Using equation (27), calculate the load S supplied from the source and the load supplied from the source when the transformer supplies power upwards. up,i S down,i Maximum power supply distance L between upstream and downstream power supply up,i L down,i ;

[0076]

[0077] Using equation (28), calculate the load S supplied by the transformer when supplying power to the upper and lower parts of the transformer. up,i S down,i Maximum power supply distance L between upstream and downstream power supply up,i L down,i ;

[0078]

[0079] Using equation (29), calculate the load S supplied from the upper and lower levels when the transformer supplies power downwards. up,i S down,i Maximum power supply distance L between upstream and downstream power supply up,i L down,i ;

[0080]

[0081] The Pareto optimal solution set G of the multi-objective programming model for the main power distribution network of super high-rise buildings is calculated using equation (30):

[0082] minG=min{g1,g2,g3,g4,g5} (30)

[0083] The constraints of the multi-objective programming model for the main power distribution network of the super high-rise building include:

[0084] 1) The transformer position constraint is: W T,i ∈{equipment layer or refuge layer};

[0085] 2) The maximum capacity constraint of the line is obtained using equation (31):

[0086] S D,i ≤η0C L，i (31)

[0087] In equation (31), C L,i Let η0 be the transmission capacity of the line in the i-th power supply zone, and η0 be the upper limit of the line load rate.

[0088] 3) Using equation (32), the voltage drop constraint is obtained:

[0089]

[0090] In equation (32), U0 is the allowable deviation of the three-phase power supply voltage of 20kV and below.

[0091] The present invention provides an electronic device, comprising a memory and a processor, wherein the memory is used to store a program that supports the processor in executing the two-stage optimization method for the power distribution network of the super high-rise building, and the processor is configured to execute the program stored in the memory.

[0092] The present invention discloses a computer-readable storage medium on which a computer program is stored, wherein the computer program, when executed by a processor, performs the steps of the two-stage optimization method for the power distribution network of super high-rise buildings.

[0093] Compared with existing technologies, the beneficial effects of this invention are reflected in:

[0094] 1. Under the constraint of multiple transformer capacities, this invention proposes a method for dividing power supply zones for super high-rise buildings. The load of super high-rise buildings is divided according to the standard specifications of building transformer capacity. In essence, the load of super high-rise buildings is combined according to the standard specifications of building transformer capacity. In the evaluation index of power supply zone division, the average load saturation is used to represent the average level of load saturation of each power supply zone, thereby avoiding unreasonable zoning results such as the load of a certain power supply zone being small after dividing according to the standard specifications of transformer capacity.

[0095] 2. This invention fully considers the load characteristics of different business types when dividing power supply zones. Power supply zones with complementary load characteristics have lower load simultaneity coefficients on different floors. Configuring transformer equipment according to this coefficient can reduce the transformer capacity, thus reducing waste of transformer installed capacity and operating resources. On the other hand, considering load characteristics when dividing power supply zones can reduce the peak-valley difference in power supply zones and improve the daily load factor of the power supply zones.

[0096] 3. This invention proposes a method for planning the main power lines of super high-rise buildings. Based on the location relationship between the transformer and the power supply area, the unilateral load and maximum power supply distance of the transformer are calculated, and then the rated current carrying capacity of each line segment is calculated and the line type is selected. This optimized method yields a planning scheme for transformers and lines, balancing system construction resources and operational efficiency.

[0097] 4. This invention divides the power distribution network planning of super high-rise buildings into two stages. Stage I finds the optimal division parameters of the power supply area based on load and load operation stability. Stage II finds the optimal scheme for transformer location and line configuration in the power distribution network planning. The two-stage optimization method can not only reduce the transformer capacity, but also further improve the safety and stability of the power distribution network operation of super high-rise buildings. Attached Figure Description

[0098] Figure 1 A schematic diagram of the main power supply and distribution scheme for super high-rise buildings in existing technologies;

[0099] Figure 2 This is a flowchart of the two-stage optimization method for power distribution networks of super high-rise buildings that takes into account load characteristics in this invention.

[0100] Figure 3a This is a typical weekday load curve of an apartment (residential) in all four seasons in this invention;

[0101] Figure 3b This is a typical workday load curve for the office in all four seasons in this invention;

[0102] Figure 3c This is a typical weekday load curve of a hotel throughout the four seasons in this invention;

[0103] Figure 3dThis is a typical weekday load curve of the garage in all four seasons according to the present invention;

[0104] Figure 3e This is a typical weekday load curve of the commercial (podium) building in all four seasons in this invention;

[0105] Figure 4 This is a flowchart of the particle swarm optimization algorithm used in this invention to solve the power supply zone division model for super high-rise buildings;

[0106] Figure 5 This is a flowchart of the particle swarm optimization algorithm for solving the power distribution network planning model of super high-rise buildings in this invention;

[0107] Figure 6 This is a schematic diagram of the main power supply and distribution scheme for super high-rise buildings in this invention. Detailed Implementation

[0108] In this embodiment, a two-stage optimization method for the power distribution network of super high-rise buildings that takes into account load characteristics is proposed for the common power distribution network planning and renovation scheme of transformer and grid design for super high-rise buildings. It takes into account the complementary influence of load characteristics of users of different business types, divides the power supply area of ​​super high-rise buildings, and then calculates the transformer capacity and system operating parameters under each power distribution scheme based on the power supply area division parameters. The optimal evaluation index planning result is selected as the power distribution network design scheme for super high-rise buildings.

[0109] The power distribution network of a high-rise building starts with 10kV power from the city substation, which is then supplied to the substations on each floor via cables. A 0.4kV high-density busbar trunking system is then configured to supply power to each floor. Its topology is as follows: Figure 1 As shown;

[0110] The components in the power distribution network of super high-rise buildings include: 10kV distribution cabinets, 10kV cables, 10 / 0.4kV transformers, and 0.4kV high-density busbar trunking; the method flow is as follows: Figure 2 As shown, the two-stage optimization method is carried out according to the following steps:

[0111] Step 1: Compile the load information of the super high-rise building, including: the load of each floor and the daily load curve of each floor on typical weekdays in all four seasons; This example is an architectural complex consisting of a high-end shopping mall, Grade A office space, apartments, and a super five-star hotel, including a super high-rise tower and a high-rise commercial podium, with a total construction area of ​​270,065.42 m². 2The building has a total height of 431m. The underground floors 1-8 house commercial space, equipment rooms, logistical support services, and a parking garage; the above-ground floors 1-6 contain offices, a five-star hotel, apartment entrances, and commercial and dining facilities; the 7th floor and mezzanine floor house the five-star hotel's banquet hall and conference center; the tower itself comprises offices (floors 10-39), apartments (floors 40-62), and a five-star hotel (floors 65-88) from bottom to top. The super high-rise building has 88 floors above ground and 8 floors underground, with floor numbers starting from floor 8 underground (1) and floor 88 (96). The transformer capacity of the super high-rise building in the original plan is shown in Table 1. This embodiment also includes power distribution for the refrigeration rooms of the commercial and apartment buildings. This type of load requires separate power distribution in the power distribution plan; therefore, the optimized method of this invention does not include special power supply planning.

[0112] Table 1 shows the installed capacity of transformers in the original plan for super high-rise buildings.

[0113]

[0114] In this embodiment, it is assumed that there is a 10kV substation on the 2nd underground floor and the 41st floor above ground. The outgoing lines from the 10kV substations to each 10 / 0.4kV transformer are 10kV cable lines, and the outgoing lines from the 10 / 0.4kV transformers to the distribution cabinets on each floor are 0.4kV busbar lines.

[0115] Different types of buildings have different load characteristics, mainly reflected in the varying load amounts at different times within the same day, and the different maximum load values ​​in different seasons or on different workdays. For the mixed-use high-rise building in this example, its load types can be categorized as residential (apartment) load, office (administrative) load, commercial load, hotel load, and parking garage load. Typical daily load curves for different types of buildings on weekdays throughout the four seasons are shown below. Figure 3a , Figure 3b , Figure 3c , Figure 3d , Figure 3e As shown. Figure 3a , Figure 3b , Figure 3c , Figure 3d , Figure 3e This illustrates the electricity consumption behavior of building users across different business types. Taking residential and office users as examples, [the data shows that...] Figure 3a and Figure 3bIt can be seen that there is a significant time difference between peak electricity consumption for residents and office users. Residential peak consumption occurs from 6 PM to 10 PM, while office peak consumption occurs from 8 AM to 12 PM and 2 PM to 6 PM. The above analysis shows that multi-functional high-rise buildings have diverse business types, varying load characteristics, and are geographically adjacent, presenting opportunities for optimizing power supply zones based on load characteristics. Power supply zones with complementary load characteristics have lower load simultaneity coefficients across different floors; configuring transformer equipment according to this coefficient can reduce transformer capacity. Furthermore, considering load characteristics when dividing power supply zones can reduce peak-to-valley differences and improve the daily load factor of the power supply area.

[0116] Let S c,k Let S be the total load of the k-th floor; c,k,j,t Let t be the load of the k-th floor at time t on a typical workday in season j; 1≤t≤24 represents the 24 times of day; j=1,2,3,4 represent spring, summer, autumn, and winter, respectively.

[0117] Step 2: Construct the optimal partitioning model for the power supply zone of super high-rise buildings;

[0118] Step 2.1: Divide the power supply zones within the super high-rise building; combine the loads of the super high-rise building with the standard specifications of 10 / 0.4kV transformer capacity to form power supply zones, and the load of each power supply zone shall not exceed the capacity of the 10 / 0.4kV transformer.

[0119] Let S T,i Let {S} be the capacity of the 10 / 0.4kV transformer in the i-th power supply zone. Then, the capacity of the 10 / 0.4kV transformer in each power supply zone is denoted as {S}. T,1 ,S T,2 ,...,S T,i ,...,S T,N} 1×N Where N represents the maximum number of power supply zones, and N is equal to the total building load divided by the minimum transformer configuration specification and rounded down.

[0120] Step 2.2, the optimal division model for power supply areas of super high-rise buildings, is based on the 10 / 0.4kV transformer capacity S of the i-th power supply area. T，i To optimize the variables, the average load saturation f1, average daily load rate f2, and average peak-to-valley difference f3 of N power supply zones are used as evaluation indicators for the division. The maximum weighted sum of the evaluation indicators is used as the optimization objective F of the optimal division model for power supply zones of super high-rise buildings. Simultaneously, constraints are constructed for the optimal division model of power supply zones of super high-rise buildings. Under these constraints, after solving the optimization objective F, the optimal power supply zone division parameters are output, including: the starting floor number Start of the i-th power supply zone. iEnd of the terminus of the i-th power supply zone i The total load S of the i-th power supply zone D,i ;

[0121] Step 2.2 involves using equation (1) to calculate the average load saturation f1:

[0122]

[0123] In equation (1), the average load saturation f1 represents the average level of load saturation in each power supply area, which can avoid unreasonable zoning results such as a small load in a certain power supply area after zoning according to the standard specifications of transformer capacity.

[0124] Calculate the average daily load factor f2 using equations (2) to (5):

[0125]

[0126]

[0127]

[0128]

[0129] In equations (2) to (5), S D,i,j,t S represents the load at time t on a typical weekday in season j for the i-th power supply area; av,i,j S represents the average load of the i-th power supply area on a typical weekday in the j-th season. max,i,j Let be the maximum load of the i-th power supply area on a typical working day in the j-th season;

[0130] Calculate the average peak-to-valley difference f3 using equations (6) and (7):

[0131]

[0132]

[0133] In equation (6), the average peak-to-valley difference f3 is converted from a negative indicator to a positive indicator by subtracting the peak-to-valley difference rate, thus maintaining consistency with indicators f1 and f2; in equation (7), S min,i,j Let be the minimum load of the i-th power supply area on a typical working day in the j-th season;

[0134] The optimization objective F for power supply zone division is calculated using equation (8):

[0135] max F=w1f1+w2f2+w3f3 (8)

[0136] In equation (8), w1, w2, and w3 are the weights of each positive indicator, respectively;

[0137] The constraints of the optimal power supply zone division model for super high-rise buildings include:

[0138] 1) Obtain the load constraint of the power supply area using equation (9):

[0139]

[0140] In equation (9), S T,i The specification of the transformer capacity for the i-th power supply zone; power supply zones are allocated starting from the ground floor of the building. The transformers for the first m power supply zones are placed in the podium and basement. The transformers for the m to N power supply zones are placed in the refuge floor or equipment floor of the upper floors of the building. Due to transportation restrictions on transformers, the transformer capacity configured in the upper floors shall not exceed 1250kVA.

[0141] 2) Obtain the load saturation rate constraint of the power supply area using equation (10):

[0142]

[0143] In equation (10), β L The load rate of a transformer is generally taken as 70% to 85%, considering energy saving and margin.

[0144] 3) Obtain the power supply demand constraint using equation (11):

[0145]

[0146] In equation (11), Start i Indicates the starting floor number of the i-th power supply zone, End i Let represent the number of the terminating floors of the i-th power supply zone, which is obtained from equation (12);

[0147]

[0148] The total load S of the i-th power supply zone is obtained using equation (13). D,i :

[0149]

[0150] This embodiment uses the particle swarm optimization algorithm to solve the power supply zone division model for super high-rise buildings. The flowchart of the particle swarm optimization algorithm for solving the power supply zone division model for super high-rise buildings is as follows: Figure 4 As shown, the specific process is as follows:

[0151] Step 1: Estimate the load S per floor based on various building electricity consumption indicators and land area. c,k Statistically analyze the typical weekday load curves of various types of buildings throughout the four seasons and initialize the particle swarm parameters;

[0152] Step 2: Calculate the power supply area partitioning parameters Start for each particle. i and End i Calculate the evaluation indicators for the division of power supply zones;

[0153] Step 3: Update the individual historical optimal fitness value of each particle, and update the particle velocity and position;

[0154] Step 4: Repeat Step 2 and Step 3 until the maximum number of iterations is reached, then output the optimal power supply area division parameters and evaluation indicators for the particles.

[0155] The optimization results of the power supply zone division for super high-rise buildings considering load characteristics are shown in Table 2. Compared with the original scheme, the optimized scheme reduces one power supply zone and increases the load of some power supply zones.

[0156] Table 2 Comparison of Power Supply Area Division Results

[0157]

[0158] The load characteristics of the power supply area for the two schemes are shown in Table 3. It can be clearly seen that the load assessment indicators of the power supply area of ​​the optimized scheme have been improved, including an increase of 9.19% in average load saturation, an increase of 3.47% in average daily load rate, and an increase of 11.13% in average peak-valley difference rate.

[0159] Table 3 Comparison of Load Characteristics of Power Supply Areas

[0160]

[0161] Step 3: Build a multi-objective programming model for the main power distribution network of super high-rise buildings, and combine it with the optimal partitioning model of the power supply area of ​​super high-rise buildings to form a two-stage optimization model for the power distribution network of super high-rise buildings;

[0162] Step 3.1: Calculate the load simultaneity factor K for the i-th power supply zone based on the power supply zone division parameters. i and calculated load S Z,i And, under the condition of meeting the configuration constraints of 10 / 0.4kV transformers, select the model of 10 / 0.4kV transformers in each power supply area;

[0163] In step 3.1, the load simultaneity factor K of the i-th power supply area is calculated using equation (14). i :

[0164]

[0165] The calculated load S of the i-th power supply zone is calculated using equation (15). Z,i :

[0166] SZ,i =K i ×S D,i (15)

[0167] Using equations (16) and (17), configure the constraints for a 10 / 0.4kV transformer:

[0168]

[0169] In equations (16) and (17), α Z S represents the percentage of the total computational load. D,i(Ⅰ，Ⅱ) This represents all primary and secondary loads in the i-th power supply zone.

[0170] The transformer configuration results for the two schemes are shown in Table 4.

[0171] Table 4 Comparison of Transformer Configuration Results

[0172]

[0173] Step 3.2: Select the installation location of the transformer in each power supply area {W} T,1 W T,2 ,...,W T,i ,...,W T,N} 1×N Among them, W T,i This represents the floor number where the 10 / 0.4kV transformer is located in the i-th power supply zone;

[0174] A dense busbar trunking system is configured for the 10kV incoming cable and 0.4kV outgoing line of the 10 / 0.4kV transformer, based on the current carrying capacity.

[0175] The multi-objective programming model for the main power distribution network of super high-rise buildings is based on the installation location {W} of the 10 / 0.4kV transformer. T,1 W T,2 ,...,W T,i ,...,W T,N} 1×N To optimize the variables, the 10 / 0.4kV transformer capacity g1, 10kV cable length g2, 10kV cable annual network loss g3, 0.4kV busbar length g4, and 0.4kV busbar annual network loss g5 of N power supply areas are used as the multiple optimization objectives of the multi-objective programming model. The constraints of the multi-objective programming model of the main line of the power distribution network of super high-rise buildings are constructed. Under these constraints, after solving the multi-objective programming model, the Pareto optimal solution set G that makes the multiple optimization objectives smaller is obtained.

[0176] Step 3.2 uses equation (18) to calculate the total capacity g1 of the 10 / 0.4kV transformers on the main line:

[0177]

[0178] Calculate the length g2 of the 10kV cable using equation (19):

[0179]

[0180] In equation (19), W T,i W represents the floor where the transformer for the i-th power supply zone is located. T10,i Let this be the floor number of the 10kV incoming substation in the i-th power supply zone. The average floor height of a super high-rise building;

[0181] Calculate the annual network loss g3 of a 10kV cable using equation (20):

[0182]

[0183] In equation (20), I L10,i Let r be the current of the incoming line of the transformer in the i-th power supply area, which is obtained from equation (21). L10，i Let T be the unit resistance of the 10kV incoming cable of the i-th power supply zone. max Maximum load utilization hours;

[0184]

[0185] In equation (21), U N Indicates the rated voltage;

[0186] Calculate the length g4 of the 0.4kV busbar using equation (22):

[0187]

[0188] In equation (22), L up,i L down,i These represent the maximum upstream and downstream supply distances of the dense busbars in the i-th power supply zone;

[0189] Based on the location relationship between the transformer and the power supply area, the power supply mode of the transformer is divided into top-supply, bottom-supply, and top-and-bottom-supply, and the annual network loss g5 of the 0.4kV dense busbar is calculated using equations (23) to (26):

[0190]

[0191]

[0192]

[0193]

[0194] In equations (23) to (26), eP up,i eP down,i These represent the upstream and downstream power losses of the dense busbar in the i-th power supply zone, respectively, eU up,i eU down,i These represent the percentages of upstream and downstream voltage losses for the dense busbar in the i-th power supply zone, respectively. up,i I down,i S represents the upstream and downstream supply currents of the dense busbar in the i-th power supply zone, respectively. up,i S down,i These are the upstream and downstream loads supplied by the dense busbar in the i-th power supply zone, respectively.

[0195] Using equation (27), calculate the load S supplied from the source and the load supplied from the source when the transformer supplies power upwards. up,i S down,i Maximum power supply distance L between upstream and downstream power supply up,i L down,i ;

[0196]

[0197] Using equation (28), calculate the load S supplied by the transformer when supplying power to the upper and lower parts of the transformer. up,i S down,i Maximum power supply distance L between upstream and downstream power supply up,i L down,i ;

[0198]

[0199] Using equation (29), calculate the load S supplied from the upper and lower levels when the transformer supplies power downwards. up,i S down,i Maximum power supply distance L between upstream and downstream power supply up,i L down,i ;

[0200]

[0201] The Pareto optimal solution set G of the multi-objective programming model for the main power distribution network of super high-rise buildings is calculated using equation (30):

[0202] minG=min{g1,g2,g3,g4,g5} (30)

[0203] The constraints of the multi-objective programming model for the main power distribution network lines of super high-rise buildings include:

[0204] 1) The transformer position constraint is: W T,i ∈{equipment layer or refuge layer};

[0205] 2) The maximum capacity constraint of the line is obtained using equation (31):

[0206] S D,i ≤η0C L，i (31)

[0207] In equation (31), C L,i Let η0 be the transmission capacity of the line in the i-th power supply zone, and η0 be the upper limit of the line load rate.

[0208] 3) Using equation (32), the voltage drop constraint is obtained:

[0209]

[0210] In equation (32), U0 is the allowable deviation of the three-phase power supply voltage of 20kV and below.

[0211] In this embodiment, the 10kV cable line of the power distribution network of the super high-rise building is selected as YJV22 three-core power cable, and the 0.4kV busbar is selected as a compact busbar trunking. The line parameters are shown in Tables 5 and 6.

[0212] Table 5 Parameters of 10kV Cable YJV22

[0213]

[0214] Table 6 Parameters of 0.4kV Compact Busbar Trunking

[0215]

[0216] Step 3.3: Use the entropy weight method to select a compromise optimal solution G' from the Pareto optimal solution set G, which is the optimal planning scheme for the power distribution network of super high-rise buildings.

[0217] In step 3.3, the compromise optimal solution G' in the Pareto optimal solution set G is selected using equations (33) to (37);

[0218] The function value h of the b-th index in the dimensionless scheme a-th scheme is calculated using equation (33). ab :

[0219]

[0220] In equation (33), g ab Let nps be the function value of the b-th index in the a-th scheme of the Pareto optimal solution set G, where nps is the particle swarm size and m is the number of indices.

[0221] Calculate the weight p of the b-th indicator in scheme a using equation (34). ab :

[0222]

[0223] Calculate the information entropy E of the b-th indicator in the a-th scheme using equation (35). b :

[0224]

[0225] The weight ω of the b-th indicator is calculated using equation (36). b :

[0226]

[0227] Calculate the compromise optimal solution G' in the Pareto optimal solution set G using equation (37):

[0228]

[0229] This embodiment uses the multi-objective particle swarm optimization algorithm to solve the power distribution network planning model for super high-rise buildings. The flowchart of the multi-objective particle swarm optimization algorithm for solving the power distribution network planning model for super high-rise buildings is as follows: Figure 5 As shown, the specific process is as follows:

[0230] Step 1: Input initial parameters into the optimization algorithm, including the starting floor number, ending floor number, and load of each power supply zone, and initialize the particle swarm.

[0231] Step 2: Based on the transformer location represented by each particle, calculate the current carrying capacity, power supply distance, and voltage drop of the 10kV incoming cable and the 0.4kV upper and lower busbars, and select the cable and busbar models according to the current carrying capacity.

[0232] Step 3: Calculate the appropriate value for each particle and update the external archive.

[0233] Step 4: Select the best historical humidity value for each individual from the external archive, update the velocity and position of each particle, and update the external archive.

[0234] Step 5: Repeat Step 2, Step 3, and Step 4 until the iteration is complete, and select the solutions from Sequence 1 to form the Pareto optimal solution set;

[0235] Step 6: Output the optimal planning scheme and various economic indicators for the power distribution network of super high-rise buildings.

[0236] The evaluation indicators for the two power distribution network planning schemes for super high-rise buildings are shown in Table 7. A schematic diagram of the main lines for the optimized power supply and distribution scheme for super high-rise buildings is shown below. Figure 6 As shown.

[0237] Table 7 Evaluation Indicators for Two Power Distribution Network Planning Schemes for Super High-Rise Buildings

[0238]

[0239]

[0240] In the results comparison, the optimized scheme increased the length of the 10kV cable line but reduced the annual network loss. The statistical results of the network loss of each section of the 10kV cable line are shown in Table 8.

[0241] Table 8. Statistics on Power Loss of 10kV Cables

[0242]

[0243] The original scheme had a total line length of 568.4m and a total loss of 1.6551kWh. The optimized scheme had a total line length of 784m and a total annual loss of 1.456kWh. The optimized scheme had a longer total 10kV line length, but the capacity of the high-rise transformer was smaller, resulting in less power loss during long-distance transmission. Therefore, the optimized scheme had a lower network loss in the 10kV cable line.

[0244] In this embodiment, an electronic device includes a memory and a processor. The memory stores a program that supports the processor in executing the above-described method, and the processor is configured to execute the program stored in the memory.

[0245] In this embodiment, a computer-readable storage medium stores a computer program, which is executed by a processor to perform the steps of the above method.

Claims

1. A two-stage optimization method for a power distribution network of a super high-rise building that takes into account load characteristics, wherein the power distribution network of the super high-rise building is supplied with 10kV power from the city substation, and then supplied to the substations on each floor through cables, and then 0.4kV dense busbar trunking is configured to supply power to each floor. The components in the power distribution network of the super high-rise building include: 10kV distribution cabinet, 10kV cable, 10 / 0.4kV transformer and 0.4kV compact busbar trunking; characterized in that the two-stage optimization method is carried out according to the following steps: Step 1: Compile the load information of the super high-rise building, including: the load of each floor and the daily load curve of each floor on typical weekdays in all four seasons; Let S c,k Let S be the total load of the k-th floor; c,k,j,t Let t be the load of the k-th floor at time t on a typical workday in season j; 1≤t≤24 represents the 24 times of day; j=1,2,3,4 represent spring, summer, autumn, and winter, respectively. Step 2: Construct the optimal partitioning model for the power supply zone of super high-rise buildings; Step 2.1: Divide the power supply zones within the super high-rise building; combine the loads of the super high-rise building with the standard specifications of 10 / 0.4kV transformer capacity to form power supply zones, and the load of each power supply zone shall not exceed the capacity of the 10 / 0.4kV transformer. Let S T,i Let {S} be the capacity of the 10 / 0.4kV transformer in the i-th power supply zone. Then, the capacity of the 10 / 0.4kV transformer in each power supply zone is denoted as {S}. T,1 ,S T,2 ,...,S T,i ,...,S T,N } 1×N Where N represents the maximum number of power supply zones, and N is equal to the total building load divided by the minimum transformer configuration specification and rounded down. Step 2.2: The optimal division model for the power supply area of ​​the super high-rise building is based on the 10 / 0.4kV transformer capacity S of the i-th power supply area. T，i To optimize the variables, the average load saturation f1, average daily load rate f2, and average peak-to-valley difference f3 of N power supply zones are used as evaluation indicators for the division. The maximum weighted sum of the evaluation indicators is used as the optimization objective F of the optimal division model for the power supply zones of the super high-rise building. Simultaneously, constraints are constructed for the optimal division model of the power supply zones of the super high-rise building. Under these constraints, after solving the optimization objective F, the optimal power supply zone division parameters are output, including: the starting floor number Start of the i-th power supply zone. i End of the terminus of the i-th power supply zone i The total load S of the i-th power supply zone D,i ; Step 3: Construct a multi-objective planning model for the main power distribution network of the super high-rise building, and combine it with the optimal partitioning model of the power supply area of ​​the super high-rise building to form a two-stage optimization model for the power distribution network of the super high-rise building. Step 3.1: Calculate the load simultaneity factor K for the i-th power supply zone based on the power supply zone division parameters. i and calculated load S Z,i And, under the condition of meeting the configuration constraints of 10 / 0.4kV transformers, select the model of 10 / 0.4kV transformers in each power supply area; Step 3.2: Select the installation location of the transformer in each power supply area {W} T,1 W T,2 ,...,W T,i ,...,W T,N } 1×N Among them, W T,i This represents the floor number where the 10 / 0.4kV transformer is located in the i-th power supply zone; A dense busbar trunking system is configured for the 10kV incoming cable and 0.4kV outgoing line of the 10 / 0.4kV transformer, based on the current carrying capacity. The multi-objective programming model for the main power distribution line of the super high-rise building is based on the installation location {W} of the 10 / 0.4kV transformer. T,1 W T,2 ,...,W T,i ,...,W T,N } 1×N To optimize the variables, the 10 / 0.4kV transformer capacity g1, 10kV cable length g2, 10kV cable annual network loss g3, 0.4kV busbar length g4, and 0.4kV busbar annual network loss g5 of N power supply areas are used as the multiple optimization objectives of the multi-objective programming model. The constraints of the multi-objective programming model of the main line of the power distribution network of the super high-rise building are constructed. Under these constraints, after solving the multi-objective programming model, the Pareto optimal solution set G that makes the multiple optimization objectives smaller is obtained. Step 3.3: Use the entropy weight method to select a compromise optimal solution G' from the Pareto optimal solution set G, which is the optimal planning scheme for the power distribution network of super high-rise buildings.

2. The two-stage optimization method for power distribution networks of super high-rise buildings considering load characteristics as described in claim 1, characterized in that, Step 2.2 involves using equation (1) to calculate the average load saturation f1: Calculate the average daily load factor f2 using equations (2) to (5): In equations (2) to (5), S D,i,j,t S represents the load at time t on a typical weekday in season j for the i-th power supply area; av,i,j S represents the average load of the i-th power supply area on a typical weekday in the j-th season. max,i,j Let be the maximum load of the i-th power supply area on a typical working day in the j-th season; Calculate the average peak-to-valley difference f3 using equations (6) and (7): In equation (7), S min,i,j Let be the minimum load of the i-th power supply area on a typical working day in the j-th season; The optimization objective F for the division of the power supply area is calculated using equation (8): max F=w1f1+w2f2+w3f3 (8) In equation (8), w1, w2, and w3 are the weights of each positive indicator, respectively; The constraints of the optimal power supply zone division model for super high-rise buildings include: 1) Obtain the load constraint of the power supply area using equation (9): In equation (9), S T,i The specification of the transformer capacity for the i-th power supply zone; power supply zones are allocated starting from the ground floor of the building, with the transformers for the first m power supply zones placed in the podium and basement, and the transformers for power supply zones m to N placed in the refuge floors or equipment floors on the upper floors of the building; 2) Obtain the load saturation rate constraint of the power supply area using equation (10): In equation (10), β L The load factor of the transformer; 3) Obtain the power supply demand constraint using equation (11): In equation (11), Start i Indicates the starting floor number of the i-th power supply zone, End i Let represent the number of the terminating floors of the i-th power supply zone, which is obtained from equation (12); The total load S of the i-th power supply zone is obtained using equation (13). D,i :

3. The two-stage optimization method for power distribution networks of super high-rise buildings considering load characteristics as described in claim 2, characterized in that, In step 3.1, the load simultaneity factor K of the i-th power supply zone is calculated using equation (14). i : The calculated load S of the i-th power supply zone is calculated using equation (15). Z,i : S Z，i =K i ×S D，i (15) Using equations (16) and (17), configure the constraints for a 10 / 0.4kV transformer: a Z ×S Z,i ≤S T,i (16) S D,i(Ⅰ,Ⅱ) ≤S T,i (17) In equations (16) and (17), α Z S represents the percentage of the total computational load. D,i(Ⅰ，Ⅱ) This represents all primary and secondary loads in the i-th power supply zone.

4. The two-stage optimization method for power distribution networks of super high-rise buildings considering load characteristics as described in claim 3, characterized in that, In step 3.2, the total capacity g1 of the 10 / 0.4kV transformers of the main line is calculated using equation (18): Calculate the length g2 of the 10kV cable using equation (19): In equation (19), W T,i W represents the floor where the transformer for the i-th power supply zone is located. T10,i Let this be the floor number of the 10kV incoming substation in the i-th power supply zone. The average floor height of a super high-rise building; Calculate the annual network loss g3 of a 10kV cable using equation (20): In equation (20), I L10,i Let r be the current of the incoming line of the transformer in the i-th power supply area, which is obtained from equation (21). L10，i Let T be the unit resistance of the 10kV incoming cable of the i-th power supply zone. max Maximum load utilization hours; In equation (21), U N Indicates the rated voltage; Calculate the length g4 of the 0.4kV busbar using equation (22): In equation (22), L up,i L down,i These represent the maximum upstream and downstream supply distances of the dense busbars in the i-th power supply zone; Based on the location relationship between the transformer and the power supply area, the power supply mode of the transformer is divided into top-supply, bottom-supply, and top-and-bottom-supply, and the annual network loss g5 of the 0.4kV dense busbar is calculated using equations (23) to (26): In equations (23) to (26), eP up,i eP down,i These represent the upstream and downstream power losses of the dense busbar in the i-th power supply zone, respectively, eU up,i eU down,i These represent the percentages of upstream and downstream voltage losses for the dense busbar in the i-th power supply zone, respectively. up,i I down,i S represents the upstream and downstream supply currents of the dense busbar in the i-th power supply zone, respectively. up,i S down,i These are the upstream and downstream loads supplied by the dense busbar in the i-th power supply zone, respectively. Using equation (27), calculate the load S supplied from the source and the load supplied from the source when the transformer supplies power upwards. up,i S down,i Maximum power supply distance L between upstream and downstream power supply up,i L down,i ; Using equation (28), calculate the load S supplied by the transformer when supplying power to the upper and lower parts of the transformer. up,i S down,i Maximum power supply distance L between upstream and downstream power supply up,i L down,i ; Using equation (29), calculate the load S supplied from the upper and lower levels when the transformer supplies power downwards. up,i S down,i Maximum power supply distance L between upstream and downstream power supply up,i L down,i ; The Pareto optimal solution set G of the multi-objective programming model for the main power distribution network of super high-rise buildings is calculated using equation (30): min G=min{g1,g2,g3,g4,g5} (30) The constraints of the multi-objective programming model for the main power distribution network of the super high-rise building include: 1) The transformer position constraint is: W T,i ∈{equipment layer or refuge layer}; 2) The maximum capacity constraint of the line is obtained using equation (31): S D,i ≤η0C L，i (31) In equation (31), C L,i Let η0 be the transmission capacity of the line in the i-th power supply zone, and η0 be the upper limit of the line load rate. 3) Using equation (32), the voltage drop constraint is obtained: In equation (32), U0 is the allowable deviation of the three-phase power supply voltage of 20kV and below.

5. An electronic device, comprising a memory and a processor, characterized in that, The memory is used to store programs that support the processor in executing the two-stage optimization method for the power distribution network of any one of claims 1-4 for high-rise buildings, and the processor is configured to execute the programs stored in the memory.

6. A computer-readable storage medium storing a computer program thereon, characterized in that, When the computer program is run by the processor, it executes the steps of the two-stage optimization method for the power distribution network of any one of claims 1-4 for super high-rise buildings.

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