CN116805788A - Two-stage optimization method for super high-rise building power distribution network considering load characteristics - Google Patents
Two-stage optimization method for super high-rise building power distribution network considering load characteristics Download PDFInfo
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/12—Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load
- H02J3/14—Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load by switching loads on to, or off from, network, e.g. progressively balanced loading
- H02J3/144—Demand-response operation of the power transmission or distribution network
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2310/00—The network for supplying or distributing electric power characterised by its spatial reach or by the load
- H02J2310/50—The network for supplying or distributing electric power characterised by its spatial reach or by the load for selectively controlling the operation of the loads
- H02J2310/56—The network for supplying or distributing electric power characterised by its spatial reach or by the load for selectively controlling the operation of the loads characterised by the condition upon which the selective controlling is based
- H02J2310/58—The condition being electrical
- H02J2310/60—Limiting power consumption in the network or in one section of the network, e.g. load shedding or peak shaving
Abstract
The invention discloses a two-stage optimization method of an ultra-high-rise building power distribution network considering load characteristics, which comprises the following steps: 1. counting load information of the super high-rise building; 2. building an optimal division model of a super high-rise building power supply area; 3. and (5) constructing a multi-target planning model of the main line of the power distribution network of the super high-rise building. The invention can realize the planning of the super high-rise building distribution network, wherein the power supply area division considering the load characteristic can not only increase the running stability of the system, but also reduce the capacity configuration requirement of the transformer and reduce the running loss of the system.
Description
Technical Field
The invention relates to the field of planning and research of super high-rise building power distribution networks, in particular to a two-stage optimization method of a super high-rise building power distribution network considering load characteristics.
Background
Super high-rise buildings usually integrate commercial buildings, office buildings, high-grade apartments, hotels, entertainment venues, large-scale malls, department stores, supermarkets and underground garages, and have various load types, high density and obvious differences in different industrial load characteristics. How to scientifically and reasonably configure the transformer in the building and the power supply circuit thereof has important function for improving the safe and reliable operation and the stable operation of the power supply and distribution system of the super high-rise building. The power supply and distribution system planning in the super high-rise building belongs to the middle-low voltage distribution network layer. At present, the analysis and discussion of the problem of locating and sizing the transformers in the super high-rise building are developed, but the configuration scheme of the final transformer is determined after operation parameters among different schemes are simply compared only from the aspect of meeting the power consumption design specification of the super high-rise building, so that the optimality of the selected scheme cannot be ensured.
For the optimal configuration of the transformer, the power supply range of the transformer is first determined. The highest load rate of the power supply area line divided according to the land property and the load quantity is high, the average load rate is low, the peak-valley difference is large, and the equipment utilization rate is low. Therefore, it is studied that the characteristics of the load are considered when the power supply area is divided, and the comprehensive super high-rise building has various states and different load characteristics, and has borders on geographic positions, and the optimization conditions and spaces for dividing the power supply area by the load characteristics exist. After the power supply area is determined, an optimization model can be established to obtain a configuration scheme of the power distribution network. To achieve both equipment capacity and operational efficiency, power distribution network planning is typically divided into multiple phases or the planning and operation are considered cooperatively. However, most of the existing research results are aimed at urban power distribution network planning, and the research on super high-rise building power distribution network planning is lacked.
The power distribution network planning of super high-rise buildings is very different from the traditional planar power distribution network planning. On the one hand, the transformer of the super high-rise building can only be placed on the refuge layer or the equipment layer, and the position constraint of the transformer needs to be considered for the power supply area division. On the other hand, in the grid planning stage, the 'vertical' power distribution network line has a fixed extending direction, and only the outgoing line of the transformer reaches the tail end of the power supply area. Based on the above, the traditional "planar" power distribution network planning method is difficult to apply.
Disclosure of Invention
In order to avoid the defects of the prior art, the invention provides a two-stage optimization method of the power distribution network of the super high-rise building, which takes the load characteristics into consideration, so that the optimal power distribution scheme of the super high-rise building can be searched by the optimization method, the capacity of a transformer can be reduced, and the running safety and stability of the power distribution network of the super high-rise building can be further improved.
The invention adopts the following technical scheme for solving the technical problems:
the invention relates to a two-stage optimization method of an ultra-high-rise building power distribution network considering load characteristics, wherein the ultra-high-rise building power distribution network is formed by introducing a 10kV power supply from an urban substation, and after the 10kV power supply is led into substations of all floors through cables, a 0.4kV intensive bus duct is configured for supplying power to each floor;
the device in the super high-rise building power distribution network comprises: 10kV power distribution cabinet, 10kV cable, 10/0.4kV transformer and 0.4kV intensive bus duct; the method is characterized in that the two-stage optimization method is carried out according to the following steps:
step1, counting load information of a super high-rise building, which comprises the following steps: the load of each floor and the daily load curve of each floor on typical workdays in four seasons; let S c,k Is the total load of the k-th floor; let S c,k,j,t The load quantity of the k-th floor at t time of a typical working day of the j-th season; 1.ltoreq.t.ltoreq.24 represents the course of the day24 moments; j=1, 2,3,4 respectively represent spring, summer, autumn, winter;
step2, building an optimal division model of a super high-rise building power supply area;
step 2.1, dividing a power supply area in the super high-rise building; combining the load of the super high-rise building with the standard specification of 10/0.4kV transformer capacity to form power supply areas, wherein the load capacity of each power supply area is not more than the capacity of the 10/0.4kV transformer;
let S T,i For the 10/0.4kV transformer capacity of the ith power supply area, the 10/0.4kV transformer capacity of each power supply area is recorded as { S } T,1 ,S T,2 ,...,S T,i ,...,S T,N } 1×N Wherein N represents the maximum number of power supply areas, and N is equal to the overall load of the building divided by the rounding result of the minimum transformer configuration specification;
step 2.2, the optimal division model of the super high-rise building power supply area is based on the 10/0.4kV transformer capacity S of the ith power supply area T，i To optimize the variables, the average load saturation f of N power supply areas 1 Average daily load rate f 2 Average inverse peak-to-valley difference f 3 As the evaluation index of division, and taking the maximum weighted sum of the evaluation index as the optimization target F of the optimal division model of the super high-rise building power supply area, and constructing the constraint condition of the optimal division model of the super high-rise building power supply area, so that after solving the optimization target F under the constraint condition, the power supply area division parameters with the optimal evaluation index are output, and the method comprises the following steps: initial floor number Start of ith power supply area i Terminating floor number End of ith power supply zone i And the total load amount S of the ith power supply area D,i ；
Step3, constructing a multi-target planning model of a main line of the power distribution network of the super high-rise building, and forming a two-stage optimization model of the power distribution network of the super high-rise building with an optimal division model of a power supply area of the super high-rise building;
step 3.1, calculating the load simultaneous coefficient K of the ith power supply area according to the power supply area dividing parameters i And a calculation load S Z,i And under the condition of meeting the configuration constraint of the 10/0.4kV transformer, each is selectedThe model of the 10/0.4kV transformer in the power supply area;
step 3.2, selecting the installation position { W ] of the transformers in each power supply area T,1 ,W T,2 ,...,W T,i ,...,W T,N } 1×N Wherein W is T,i The number of floors where the 10/0.4kV transformer is located in the ith power supply area;
a 10kV incoming cable and a 0.4kV outgoing intensive bus duct of a 10/0.4kV transformer are configured according to the current-carrying capacity;
the multi-objective planning model of the main line of the power distribution network of the super high-rise building is based on the installation position { W (W) of a 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 g of N power supply areas 1 Length g of 10kV cable 2 Annual loss g of 10kV cable 3 Length g of 0.4kV dense bus 4 Annual grid loss g of 0.4kV dense bus 5 As a multi-optimization target of the multi-target planning model, constructing constraint conditions of the multi-target planning model of the main line of the power distribution network of the super high-rise building, and solving the multi-target planning model under the constraint conditions to obtain a Pareto optimal solution set G for enabling the multi-optimization target to obtain a smaller value;
and 3.3, screening a compromise optimal solution G' from the Pareto optimal solution set G by adopting an entropy weight method, namely the optimal planning scheme of the power distribution network of the super high-rise building.
The two-stage optimization method of the super high-rise building distribution network considering the load characteristics is also characterized in that in the step 2.2, the average load saturation f is calculated by using the formula (1) respectively 1 ：
Calculating the average daily load rate f by using the formulas (2) to (5) 2 ：
In the formulas (2) to (5), S D,i,j,t The load quantity of the ith power supply area at t moment of the typical working day of the jth season; s is S av,i,j For the average load amount of the ith power supply area on the typical working day of the jth season, S max,i,j Maximum load amount for typical workday of the ith power supply area in the jth season;
calculating the average inverse peak-valley difference f by using the formula (6) and the formula (7) 3 ：
In the formula (7), S min,i,j A minimum load amount for a typical workday of the ith power supply zone in the jth season;
calculating an optimization target F of the power supply section division using formula (8):
max F＝w 1 f 1 +w 2 f 2 +w 3 f 3 (8)
in formula (8), w 1 、w 2 、w 3 The weights of the forward indexes are respectively;
constraint conditions of the optimal partition model of the super high-rise building power supply area comprise:
1) Obtaining a supply region load constraint using equation (9):
in the formula (9), S T,i A specification of transformer capacity for the ith power supply zone; the power supply areas are distributed from the bottom layer of the building, transformers in the first m power supply areas are placed in a skirt room and a basement, and transformers in the m-th to N power supply areas are placed in a refuge layer or an equipment layer of a high-rise building;
2) Obtaining a power supply region load saturation rate constraint by using the formula (10):
in the formula (10), beta L Is the load factor of the transformer;
3) Obtaining a power demand constraint using formula (11):
in formula (11), start i Indicating the number of initial floors, end, of the ith power supply area i Represents the number of terminal floors of the ith power supply area and is obtained by formula (12);
obtaining the total load S of the ith power supply area by using the formula (13) D,i ：
In the step 3.1, the load simultaneous coefficient K of the ith power supply area is calculated by using the formula (14) i ：
Calculating the calculation load S of the ith power supply area by using formula (15) Z,i ：
S Z,i ＝K i ×S D,i (15)
The constraint of a 10/0.4kV transformer is configured by using the formula (16) and the formula (17):
α Z ×S Z,i ≤S T,i (16)
S D,i(Ⅰ,Ⅱ) ≤S T,i (17)
in the formulas (16) and (17), alpha Z S as a percentage of the total computation load D,i(Ⅰ，Ⅱ) For all one, two-stage loads of the ith power supply zone.
In the step 3.2, the total capacity g of the 10/0.4kV transformer of the main line is calculated by using the method (18) 1 ：
Calculating the length g of the 10kV cable by using the method (19) 2 ：
In the formula (19), W T,i For the floor where the transformer of the ith power supply area is located, W T10,i For the floor number of the 10kV incoming line transformer substation in the ith power supply area,the average floor height of the super high-rise building;
annual loss g of 10kV cable is calculated by using (20) 3 ：
In the formula (20), I L10,i Powering the ithThe current of the incoming line of the district transformer, and is obtained by a formula (21), r L10，i The unit resistance T of the 10kV incoming cable in the ith power supply area max Maximum load utilization hours;
in the formula (21), U N Representing a rated voltage;
calculating the length g of the 0.4kV dense bus by using the method (22) 4 ：
In the formula (22), L up,i 、L down,i The maximum distance between the upper supply and the lower supply of the intensive bus of the ith power supply area is respectively;
according to the position relation between the transformer and the power supply area, the power supply mode of the transformer is divided into upper power supply, lower power supply and upper power supply and lower power supply, so that the annual network loss g of the 0.4kV dense bus is calculated by using the formulas (23) to (26) 5 ：
In the formulas (23) to (26), eP up,i 、eP down,i The power loss of upper power supply and lower power supply of the i-th power supply area dense bus is respectively, and the power loss of the eU up,i 、eU down,i The power supply voltage loss percentages are respectively the upper power supply and the lower power supply voltage loss percentages of the I-th power supply area dense bus up,i 、I down,i Upper power supply and lower power supply of the i-th power supply area dense bus respectively, S up,i 、S down,i The upper supply and the lower supply loads of the i-th power supply area dense buses are respectively;
when the transformer is used for calculating upward power supply, the upper power supply and lower power supply loads S up,i 、S down,i Maximum power supply distance L from upper power supply and lower power supply up,i 、L down,i ；
When the transformer is powered up and down, the upper power supply and lower power supply loads S are calculated by using the method (28) up,i 、S down,i Maximum power supply distance L from upper power supply and lower power supply up,i 、L down,i ；
Calculating the upper supply and lower supply load S when the transformer supplies power downwards by using the method (29) up,i 、S down,i Maximum power supply distance L from upper power supply and lower power supply up,i 、L down,i ；
Calculating a Pareto optimal solution set G of a multi-objective planning model of the main line of the power distribution network of the super high-rise building by using the method (30):
minG＝min{g 1 ,g 2 ,g 3 ,g 4 ,g 5 } (30)
constraint conditions of the multi-objective planning model of the main line of the power distribution network of the super high-rise building comprise:
1) The transformer position constraints are: w (W) T,i E { device layer or refuge layer };
2) Obtaining a line maximum capacity constraint using equation (31):
S D,i ≤η 0 C L，i (31)
in the formula (31), C L,i For the transmission capacity, eta of the ith power supply zone line 0 Line load factor upper limit;
3) Obtaining a voltage drop constraint using equation (32):
in formula (32), U 0 Is a three-phase power supply voltage deviation allowable value of 20kV and below.
The invention relates to an electronic device comprising a memory and a processor, characterized in that the memory is used for storing a program for supporting the processor to execute the two-stage optimization method of the power distribution network of the super high-rise building, and the processor is configured to execute the program stored in the memory.
The invention relates to a computer readable storage medium, wherein a computer program is stored on the computer readable storage medium, and is characterized in that the computer program is executed by a processor to execute the steps of the two-stage optimization method of the power distribution network of the super high-rise building.
Compared with the prior art, the invention has the beneficial effects that:
1. under the condition of constraint of multiple transformer capacities, the invention provides a super high-rise building power supply division method, which divides the load of the super high-rise building by the standard specification of the building transformer capacity, and essentially combines the super high-rise load with the standard specification of the building transformer capacity; in the evaluation index of the power supply area division, the average load saturation is used for representing the average level of the load saturation of each power supply area, so that the unreasonable division result that the load of a certain power supply area is smaller after the power supply area is divided according to the standard specification of the transformer capacity is avoided.
2. The invention fully considers the load characteristics of users in different states when dividing the power supply area, has the power supply area with complementary load characteristics, has lower load coefficient of different floors, and can reduce the configuration capacity of the transformer by configuring the transformer equipment according to the coefficient, thereby reducing the waste of the installed capacity and operation resources of the transformer. On the other hand, when the power supply area is divided, the peak-valley difference of the power supply area can be reduced by considering the load characteristic, and the daily load rate of the power supply area is improved.
3. The invention provides a trunk road planning method of a super high-rise building, which calculates unilateral load and maximum power supply distance of a transformer according to the position relation between the transformer and a power supply area, further calculates rated current-carrying capacity of each section of line and selects line types. The planning scheme of the transformer and the line is obtained by an optimized method, and the construction resources and the operation effect of the system are considered.
4. According to the invention, the super high-rise building power distribution network is divided into two stages, the stage I searches the optimal dividing parameters of the power supply area according to the load quantity and the load operation stability, the stage II power distribution network is planned to search the optimal scheme of the position and the line configuration of the transformer, and the two-stage optimization method can not only reduce the capacity of the transformer, but also further improve the operation safety and stability of the super high-rise building power distribution network.
Drawings
FIG. 1 is a schematic diagram of a main circuit of a prior art super high-rise building power supply and distribution scheme;
FIG. 2 is a flow chart of a two-stage optimization method of the super high-rise building distribution network with calculated and load characteristics;
FIG. 3a is a graph of typical daily workload for an apartment (resident) in the present invention for four seasons;
FIG. 3b is a graph of typical daily workload for the four seasons of the office in the present invention;
FIG. 3c is a graph of typical workload at four seasons of a hotel in accordance with the present invention;
FIG. 3d is a graph of typical workload for four seasons of a garage according to the present invention;
FIG. 3e is a graph of a typical workload of a business (a house) for four seasons in accordance with the present invention;
FIG. 4 is a flow chart of a particle swarm algorithm for solving a super high-rise building power supply division model in the invention;
FIG. 5 is a flow chart of solving a planning model of an ultra-high-rise building power distribution network by a particle swarm algorithm in the invention;
fig. 6 is a schematic diagram of a main circuit of a power supply and distribution scheme of the super high-rise building in the present invention.
Detailed Description
In the embodiment, a two-stage optimization method of an ultra-high-rise building power distribution network considering load characteristics is to divide an ultra-high-rise building power supply area by considering the influence of complementation of load characteristics of users in different states according to a common power distribution network planning transformation scheme of an ultra-high-rise building transformer and a network frame design, and then calculate transformer capacity and system operation parameters under each power distribution scheme by using power supply area division parameters, and select an optimal evaluation index planning result as a power distribution network design scheme of the ultra-high-rise building.
The super high-rise building power distribution network is characterized in that a 10kV power supply is led in by an urban substation, and after the 10kV power supply is led in to substations of all floors through cables, a 0.4kV intensive bus duct is configured to supply power for each floor, and the topology structure of the super high-rise building power distribution network is shown in figure 1;
the device in the super high-rise building distribution network includes: 10kV power distribution cabinet, 10kV cable, 10/0.4kV transformer and 0.4kV intensive bus duct; the method flow is shown in fig. 2, and the two-stage optimization method is carried out according to the following steps:
step1, counting load information of a super high-rise building, which comprises the following steps: the load of each floor and the daily load curve of each floor on typical workdays in four seasons; the embodiment is a building complex consisting of a high-end shopping center, a class-A business office, an apartment and a super five-star hotel, comprising a super high-rise tower and a high-rise business skirt house, wherein the total building area is 270065.42m 2 The total height 431m. Wherein, the underground 1-8 layers are business, equipment room, logistic matched service and garage; 1-6 layers on the ground are offices, five-star hotels, apartment entrances and exits, businesses and catering; the 7 layers and 7 interlayers on the ground are five-star hotel banquet halls and conference centers; the tower is office (10-39 layers), apartment (40-62 layers) and five-star hotel (65-88 layers) from bottom to top. 88 layers on the ground, 8 layers on the ground and the floor number is 1 from 8 layers on the ground, and 88 layers on the groundNumbered 96. The installed capacity of the transformer of the super high-rise building in the original scheme is shown in table 1. The embodiment also comprises the power distribution of a refrigerating machine room of a business and an apartment, and the type of load needs to be independently distributed in the power distribution planning, so that the optimization method is the planning which does not comprise special power consumption.
Table 1 installed capacity of super high-rise building transformers in original scheme
In this example, it is assumed that there is one 10kV transformer substation for each of the underground 2 and above-ground 41 layers. The 10kV transformer substation outgoing line to each 10/0.4kV transformer is a 10kV cable line, and the 10/0.4kV transformer outgoing line to each floor power distribution cabinet is a 0.4kV dense bus line.
Different load characteristics of buildings in different business states are mainly shown by different load amounts at each moment in the same day, different seasons or different maximum load values in different working days. The load types of the comprehensive super high-rise building according to the present embodiment may be classified into residential (apartment) load, office (administrative) load, business load, hotel load, and garage load. Typical daily load curves of the user load in different business states at four seasons are shown in fig. 3a, 3b, 3c, 3d and 3 e. Fig. 3a, 3b, 3c, 3d, 3e show building user electricity usage behavior in different business states. Taking residents and office users as examples, the obvious time difference exists between the electricity consumption peaks of the residents and the office users, the electricity consumption peaks of the residents are 18 to 22 points, and the electricity consumption peaks of the office users are 8 to 12 points and 14 to 18 points, as can be seen from fig. 3a and 3 b. From the analysis, the comprehensive super high-rise building has various modes and different load characteristics, and has geographical borders, and the optimization conditions and spaces for dividing the power supply area by the load characteristics exist. The power supply area with complementary load characteristics is provided, the loads of different floors are low at the same time, and the transformer equipment is configured according to the low load coefficient, so that the configuration capacity of the transformer can be reduced. On the other hand, when the power supply area is divided, the peak-valley difference of the power supply area can be reduced by considering the load characteristic, and the daily load rate of the power supply area can be improved.
Let S c,k Is the total load of the k-th floor; let S c,k,j,t The load quantity of the k-th floor at t time of a typical working day of the j-th season; t is more than or equal to 1 and less than or equal to 24, and represents 24 moments in a day; j=1, 2,3,4 respectively represent spring, summer, autumn, winter;
step2, building an optimal division model of a super high-rise building power supply area;
step 2.1, dividing a power supply area in the super high-rise building; combining the load of the super high-rise building with the standard specification of 10/0.4kV transformer capacity to form power supply areas, wherein the load capacity of each power supply area is not more than the capacity of the 10/0.4kV transformer;
let S T,i For the 10/0.4kV transformer capacity of the ith power supply area, the 10/0.4kV transformer capacity of each power supply area is recorded as { S } T,1 ,S T,2 ,...,S T,i ,...,S T,N } 1×N Wherein N represents the maximum number of power supply areas, and N is equal to the overall load of the building divided by the rounding result of the minimum transformer configuration specification;
step 2.2, the optimal division model of the super high-rise building power supply area is based on the 10/0.4kV transformer capacity S of the ith power supply area T，i To optimize the variables, the average load saturation f of N power supply areas 1 Average daily load rate f 2 Average inverse peak-to-valley difference f 3 As the evaluation index of division, and the maximum weighted sum of the evaluation index is used as the optimization target F of the optimal division model of the super high-rise building power supply area, and meanwhile, the constraint condition of the optimal division model of the super high-rise building power supply area is constructed, so that after solving the optimization target F under the constraint condition, the power supply division parameters with the optimal evaluation index are output, and the method comprises the following steps: initial floor number Start of ith power supply area i Terminating floor number End of ith power supply zone i And the total load amount S of the ith power supply area D,i ；
In step 2.2, the average load saturation f is calculated by using the formula (1) 1 ：
In the formula (1), the average load saturation f 1 The average level of the load saturation of each power supply area is represented, and unreasonable partition results such as smaller load quantity of one power supply area after the power supply area is partitioned according to the standard specification of the transformer capacity can be avoided.
Calculating the average daily load rate f by using the formulas (2) to (5) 2 ：
In the formulas (2) to (5), S D,i,j,t The load quantity of the ith power supply area at t moment of the typical working day of the jth season; s is S av,i,j For the average load amount of the ith power supply area on the typical working day of the jth season, S max,i,j Maximum load amount for typical workday of the ith power supply area in the jth season;
calculating the average inverse peak-valley difference f by using the formula (6) and the formula (7) 3 ：
In the formula (6), the average inverse peak-valley difference f 3 Conversion of negative indicators to positive indicators using a subtraction peak Gu Chalv, and indicator f 1 、f 2 Keeping consistency; in the formula (7), S min,i,j A minimum load amount for a typical workday of the ith power supply zone in the jth season;
calculating an optimization target F of the power supply area division by using the formula (8):
max F＝w 1 f 1 +w 2 f 2 +w 3 f 3 (8)
in formula (8), w 1 、w 2 、w 3 The weights of the forward indexes are respectively;
constraint conditions of an optimal partition model of a super high-rise building power supply area comprise:
1) Obtaining a supply region load constraint using equation (9):
in the formula (9), S T,i A specification of transformer capacity for the ith power supply zone; the power supply areas are distributed from the bottom layer of the building, transformers in the first m power supply areas are placed in a skirt room and a basement, transformers in the m-th to N power supply areas are placed in a refuge layer or an equipment layer of a high-rise building, and the capacity of the transformers is configured to be not more than 1250kVA due to the transportation limitation of the transformers;
2) Obtaining a power supply region load saturation rate constraint by using the formula (10):
in the formula (10), beta L The load rate of the transformer is generally 70% -85% in consideration of energy conservation and allowance of the transformer;
3) Obtaining a power demand constraint using formula (11):
in formula (11), start i Indicating the number of initial floors, end, of the ith power supply area i Represents the number of terminal floors of the ith power supply area and is obtained by formula (12);
obtaining the total load S of the ith power supply area by using the formula (13) D,i ：
In this embodiment, the particle swarm algorithm is used to solve the super high-rise building power supply division model, and a flowchart of the particle swarm algorithm for solving the super high-rise building power supply division model is shown in fig. 4, and the specific flow is as follows:
step1: estimating the load quantity S of each layer according to various building electricity utilization indexes and land utilization areas c,k Counting four-season typical working day load curves of various buildings, and initializing particle swarm parameters;
step2: calculating a power supply region dividing parameter Start under each particle i And End i Calculating an evaluation index of power supply area division;
step3: updating individual historical optimal moderate values of each particle, and updating particle speed and position;
step4: and repeating Step2 and Step3, and outputting the power supply region dividing parameters and the evaluation indexes of the optimal particles after the maximum iteration times are reached.
The optimization results of the super high-rise building power supply area division considering the load characteristics are shown in table 2, and compared with the original scheme, the optimization scheme reduces one power supply area and increases the load quantity of part of the power supply areas.
Table 2 comparison of power supply division results
The load characteristics of the power supply areas of the two schemes are shown in table 3, and it can be seen that the load evaluation indexes of the power supply areas of the optimization scheme are improved, wherein the average load saturation is improved by 9.19%, the average daily load rate is improved by 3.47%, and the average peak-valley difference rate is improved by 11.13%.
TABLE 3 comparison of load characteristics in Power supply regions
Step3, constructing a multi-target planning model of a main line of the power distribution network of the super high-rise building, and forming a two-stage optimization model of the power distribution network of the super high-rise building with an optimal division model of a power supply area of the super high-rise building;
step 3.1, calculating the load simultaneous coefficient K of the ith power supply area according to the power supply area dividing parameters i And a calculation load S Z,i Under the condition of meeting the configuration constraint of the 10/0.4kV transformer, selecting the model of the 10/0.4kV transformer in each power supply area;
in step 3.1, the load simultaneous coefficient K of the ith power supply area is calculated by using the formula (14) i ：
Calculating the calculation load S of the ith power supply area by using formula (15) Z,i ：
S Z,i ＝K i ×S D,i (15)
The constraint of a 10/0.4kV transformer is configured by using the formula (16) and the formula (17):
in the formulas (16) and (17), alpha Z S as a percentage of the total computation load D,i(Ⅰ，Ⅱ) For all one, two-stage loads of the ith power supply zone.
The transformer configuration results of the two schemes are shown in table 4;
table 4 comparison of transformer configuration results
Step 3.2, selecting the installation position { W ] of the transformers in each power supply area T,1 ,W T,2 ,...,W T,i ,...,W T,N } 1×N Wherein W is T,i The number of floors where the 10/0.4kV transformer is located in the ith power supply area;
a 10kV incoming cable and a 0.4kV outgoing intensive bus duct of a 10/0.4kV transformer are configured according to the current-carrying capacity;
the multi-objective planning model of the main line of the power distribution network of the super high-rise building is based on the installation position { W { of 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 g of N power supply areas 1 Length g of 10kV cable 2 Annual loss g of 10kV cable 3 Length g of 0.4kV dense bus 4 Annual grid loss g of 0.4kV dense bus 5 As a multi-optimization target of the multi-target planning model, constructing constraint conditions of the multi-target planning model of the main line of the power distribution network of the super high-rise building, and solving the multi-target planning model under the constraint conditions to obtain a Pareto optimal solution set G for enabling the multi-optimization target to obtain a smaller value;
in step 3.2, the total capacity g of the 10/0.4kV transformer of the main line is calculated by using the method (18) 1 ：
Calculating the length g of the 10kV cable by using the method (19) 2 ：
In the formula (19), W T,i For the floor where the transformer of the ith power supply area is located, W T10,i For the floor number of the 10kV incoming line transformer substation in the ith power supply area,the average floor height of the super high-rise building;
annual loss g of 10kV cable is calculated by using (20) 3 ：
In the formula (20), I L10,i The current drawn into the transformer in the ith supply area is obtained by the formula (21), r L10，i The unit resistance T of the 10kV incoming cable in the ith power supply area max Maximum load utilization hours;
in the formula (21), U N Representing a rated voltage;
calculating the length g of the 0.4kV dense bus by using the method (22) 4 ：
In the formula (22), L up,i 、L down,i The maximum distance between the upper supply and the lower supply of the intensive bus of the ith power supply area is respectively;
according to the position relation between the transformer and the power supply area, the power supply mode of the transformer is divided into upper power supply, lower power supply and upper power supply and lower power supply, so that the annual network loss g of the 0.4kV dense bus is calculated by using the formulas (23) to (26) 5 ：
/>
In the formulas (23) to (26), eP up,i 、eP down,i The power loss of upper power supply and lower power supply of the i-th power supply area dense bus is respectively, and the power loss of the eU up,i 、eU down,i The power supply voltage loss percentages are respectively the upper power supply and the lower power supply voltage loss percentages of the I-th power supply area dense bus up,i 、I down,i Upper power supply and lower power supply of the i-th power supply area dense bus respectively, S up,i 、S down,i The upper supply and the lower supply loads of the i-th power supply area dense buses are respectively;
when the transformer is used for calculating upward power supply, the upper power supply and lower power supply loads S up,i 、S down,i Maximum power supply distance L from upper power supply and lower power supply up,i 、L down,i ；
When the transformer is powered up and down, the upper power supply and lower power supply loads S are calculated by using the method (28) up,i 、S down,i Maximum power supply distance L from upper power supply and lower power supply up,i 、L down,i ；
Calculating the upper supply and lower supply load S when the transformer supplies power downwards by using the method (29) up,i 、S down,i Maximum power supply distance L from upper power supply and lower power supply up,i 、L down,i ；
Calculating a Pareto optimal solution set G of a multi-objective planning model of the main line of the power distribution network of the super high-rise building by using the method (30):
minG＝min{g 1 ,g 2 ,g 3 ,g 4 ,g 5 } (30)
constraint conditions of the multi-objective planning model of the main line of the power distribution network of the super high-rise building comprise:
1) The transformer position constraints are: w (W) T,i E { device layer or refuge layer };
2) Obtaining a line maximum capacity constraint using equation (31):
S D,i ≤η 0 C L，i (31)
in the formula (31), C L,i For the transmission capacity, eta of the ith power supply zone line 0 Line load factor upper limit;
3) Obtaining a voltage drop constraint using equation (32):
in formula (32), U 0 Is a three-phase power supply voltage deviation allowable value of 20kV and below.
In the embodiment, a YJV22 three-core power cable is selected for a 10kV cable line of the super high-rise building power distribution network, a dense bus duct is selected for a 0.4kV bus, and line parameters are shown in tables 5 and 6.
TABLE 5 10kV Cable YJV22 parameters
TABLE 6 0.4kV dense bus duct parameters
And 3.3, screening a compromise optimal solution G' from the Pareto optimal solution set G by adopting an entropy weight method, namely the optimal planning scheme of the power distribution network of the super high-rise building.
In the step 3.3, a compromise optimal solution G' in the Pareto optimal solution set G is screened by utilizing formulas (33) to (37);
calculating the function value h of the b index in the a-th scheme of the dimensionalization processing by using the formula (33) ab ：
In the formula (33), g ab The function value of the b index in the a scheme in the Pareto optimal solution set G is given, nps is the particle swarm scale, and m is the index number;
calculating the weight p of the b index in the a scheme by using the formula (34) ab ：
Calculating the information entropy E of the b index in the a scheme by using the formula (35) b ：
Calculating the weight omega of the b-th index by using the formula (36) b ：
Calculating a compromise optimal solution G' in the Pareto optimal solution set G using formula (37):
in this embodiment, a multi-target particle swarm algorithm is used to solve a power distribution network planning model of a super high-rise building, a flowchart of the multi-target particle swarm algorithm for solving the power distribution network planning model of the super high-rise building is shown in fig. 5, and the specific flow is as follows:
step1: inputting initial parameters including the number of initial floors, the number of final floors and the load of each power supply area to an optimization algorithm, and initializing a particle swarm;
step2: according to the transformer position represented by each particle, calculating the current-carrying capacity, the power supply distance and the voltage drop of a 10kV incoming cable and a 0.4kV up-down dense bus, and selecting the types of the cable and the dense bus according to the current-carrying capacity;
step3: counting the moderate value of each particle, and updating the external Archive;
step4: selecting an optimal moderate value of individual histories from the external Archive, updating the speed and the position of each particle, and updating the external Archive;
step5: repeating Step2, step3 and Step4 until iteration is completed, and selecting the solution of the sequence 1 to form a Pareto optimal solution set;
step6: and outputting an optimal planning scheme and each economic index of the super high-rise building power distribution network.
The evaluation indexes of the two super high-rise building power distribution network planning schemes are shown in table 7. The schematic diagram of the main circuit of the power supply and distribution optimization scheme of the super high-rise building is shown in fig. 6.
Table 7 evaluation index for two super high-rise building distribution network planning schemes
In the comparison of the results, the length of the 10kV cable line of the optimization scheme is increased, but the annual network loss is reduced, the network loss of each section of the 10kV cable line is analyzed, and the statistical results are shown in table 8.
Meter 810kV cable power loss statistics
The total length of the original scheme line is 568.4m, the total loss is 1.6551kWh, the total length of the optimized scheme line is 784m, and the annual total loss is 1.456kWh. The total length of the 10kV line of the optimization scheme is more, but the capacity of the high-rise transformer is smaller, and the power loss during long-distance transmission is smaller, so that the network loss of the 10kV cable line of the optimization scheme is smaller.
In this embodiment, an electronic device includes a memory for storing a program supporting the processor to execute the above method, and a processor configured to execute the program stored in the memory.
In this embodiment, a computer-readable storage medium stores a computer program that, when executed by a processor, performs the steps of the method described above.
Claims (6)
1. A two-stage optimization method of a super high-rise building power distribution network considering load characteristics comprises the steps that a 10kV power supply is led in by an urban substation, and after the 10kV power supply is led in to substations of all floors through cables, a 0.4kV intensive bus duct is configured to supply power for each floor;
the device in the super high-rise building power distribution network comprises: 10kV power distribution cabinet, 10kV cable, 10/0.4kV transformer and 0.4kV intensive bus duct; the method is characterized by comprising the following steps of:
step1, counting load information of a super high-rise building, which comprises the following steps: the load of each floor and the daily load curve of each floor on typical workdays in four seasons; let S c,k Is the total load of the k-th floor; let S c,k,j,t The load quantity of the k-th floor at t time of a typical working day of the j-th season; t is more than or equal to 1 and less than or equal to 24, and represents 24 moments in a day; j=1, 2,3,4 respectively represent spring, summer, autumn, winter;
step2, building an optimal division model of a super high-rise building power supply area;
step 2.1, dividing a power supply area in the super high-rise building; combining the load of the super high-rise building with the standard specification of 10/0.4kV transformer capacity to form power supply areas, wherein the load capacity of each power supply area is not more than the capacity of the 10/0.4kV transformer;
let S T,i For the 10/0.4kV transformer capacity of the ith power supply area, the 10/0.4kV transformer capacity of each power supply area is recorded as { S } T,1 ,S T,2 ,...,S T,i ,...,S T,N } 1×N Wherein N represents the maximum number of power supply areas, and N is equal to the overall load of the building divided by the rounding result of the minimum transformer configuration specification;
step 2.2, the optimal division model of the super high-rise building power supply area is based on the 10/0.4kV transformer capacity S of the ith power supply area T，i To optimize the variables, the average load saturation f of N power supply areas 1 Average daily load rate f 2 Average inverse peak-to-valley difference f 3 As the evaluation index of division, and taking the maximum weighted sum of the evaluation index as the optimization target F of the optimal division model of the super high-rise building power supply area, and constructing the constraint condition of the optimal division model of the super high-rise building power supply area, so that after solving the optimization target F under the constraint condition, the power supply area division parameters with the optimal evaluation index are output, and the method comprises the following steps: initial floor number Start of ith power supply area i Terminating floor number End of ith power supply zone i And the total load amount S of the ith power supply area D,i ；
Step3, constructing a multi-target planning model of a main line of the power distribution network of the super high-rise building, and forming a two-stage optimization model of the power distribution network of the super high-rise building with an optimal division model of a power supply area of the super high-rise building;
step 3.1, calculating the load simultaneous coefficient K of the ith power supply area according to the power supply area dividing parameters i And a calculation load S Z,i Under the condition of meeting the configuration constraint of the 10/0.4kV transformer, selecting the model of the 10/0.4kV transformer in each power supply area;
step 3.2, selecting the installation position { W ] of the transformers in each power supply area T,1 ,W T,2 ,...,W T,i ,...,W T,N } 1×N Wherein W is T,i The number of floors where the 10/0.4kV transformer is located in the ith power supply area;
a 10kV incoming cable and a 0.4kV outgoing intensive bus duct of a 10/0.4kV transformer are configured according to the current-carrying capacity;
the multi-objective planning model of the main line of the power distribution network of the super high-rise building is based on the installation position { W (W) of a 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 g of N power supply areas 1 Length g of 10kV cable 2 Annual loss g of 10kV cable 3 Length g of 0.4kV dense bus 4 Annual grid loss g of 0.4kV dense bus 5 As a multi-optimization target of the multi-target planning model, constructing constraint conditions of the multi-target planning model of the main line of the power distribution network of the super high-rise building, and solving the multi-target planning model under the constraint conditions to obtain a Pareto optimal solution set G for enabling the multi-optimization target to obtain a smaller value;
and 3.3, screening a compromise optimal solution G' from the Pareto optimal solution set G by adopting an entropy weight method, namely the optimal planning scheme of the power distribution network of the super high-rise building.
2. The two-stage optimization method for super high-rise building distribution network according to claim 1, wherein in step 2.2, average load saturation f is calculated by using formula (1) respectively 1 ：
Calculating the average daily load rate f by using the formulas (2) to (5) 2 ：
In the formulas (2) to (5), S D,i,j,t The load quantity of the ith power supply area at t moment of the typical working day of the jth season; s is S av,i,j For the average load amount of the ith power supply area on the typical working day of the jth season, S max,i,j Maximum load amount for typical workday of the ith power supply area in the jth season;
calculating the average inverse peak-valley difference f by using the formula (6) and the formula (7) 3 ：
In the formula (7), S min,i,j A minimum load amount for a typical workday of the ith power supply zone in the jth season;
calculating an optimization target F of the power supply section division using formula (8):
max F＝w 1 f 1 +w 2 f 2 +w 3 f 3 (8)
in formula (8), w 1 、w 2 、w 3 The weights of the forward indexes are respectively;
constraint conditions of the optimal partition model of the super high-rise building power supply area comprise:
1) Obtaining a supply region load constraint using equation (9):
in the formula (9), S T,i A specification of transformer capacity for the ith power supply zone; the power supply areas are distributed from the bottom layer of the building, transformers in the first m power supply areas are placed in a skirt room and a basement, and transformers in the m-th to N power supply areas are placed in a refuge layer or an equipment layer of a high-rise building;
2) Obtaining a power supply region load saturation rate constraint by using the formula (10):
in the formula (10), beta L Is the load factor of the transformer;
3) Obtaining a power demand constraint using formula (11):
in formula (11), start i Indicating the number of initial floors, end, of the ith power supply area i Represents the number of terminal floors of the ith power supply area and is obtained by formula (12);
obtaining the total load S of the ith power supply area by using the formula (13) D,i ：
3. The load-characteristic-accounting super high-rise building of claim 2A two-stage optimization method for a building power distribution network is characterized in that in the step 3.1, the load simultaneous coefficient K of an ith power supply area is calculated by using a meter (14) i ：
Calculating the calculation load S of the ith power supply area by using formula (15) Z,i ：
S Z，i ＝K i ×S D，i (15)
The constraint of a 10/0.4kV transformer is configured by using the formula (16) and the formula (17):
α Z ×S Z,i ≤S T,i (16)
S D,i(Ⅰ,Ⅱ) ≤S T,i (17)
in the formulas (16) and (17), alpha Z S as a percentage of the total computation load D,i(Ⅰ，Ⅱ) For all one, two-stage loads of the ith power supply zone.
4. The two-stage optimization method for super high-rise building distribution network according to claim 3, wherein said step 3.2 is to calculate the total 10/0.4kV transformer capacity g of the main line by using formula (18) 1 ：
Calculating the length g of the 10kV cable by using the method (19) 2 ：
In the formula (19), W T,i For the floor where the transformer of the ith power supply area is located, W T10,i For the floor number of the 10kV incoming line transformer substation in the ith power supply area,the average floor height of the super high-rise building;
annual loss g of 10kV cable is calculated by using (20) 3 ：
In the formula (20), I L10,i The current drawn into the transformer in the ith supply area is obtained by the formula (21), r L10，i The unit resistance T of the 10kV incoming cable in the ith power supply area max Maximum load utilization hours;
in the formula (21), U N Representing a rated voltage;
calculating the length g of the 0.4kV dense bus by using the method (22) 4 ：
In the formula (22), L up,i 、L down,i The maximum distance between the upper supply and the lower supply of the intensive bus of the ith power supply area is respectively;
according to the position relation between the transformer and the power supply area, the power supply mode of the transformer is divided into upper power supply, lower power supply and upper power supply and lower power supply, so that the annual network loss g of the 0.4kV dense bus is calculated by using the formulas (23) to (26) 5 ：
In the formulas (23) to (26), eP up,i 、eP down,i The power loss of upper power supply and lower power supply of the i-th power supply area dense bus is respectively, and the power loss of the eU up,i 、eU down,i The power supply voltage loss percentages are respectively the upper power supply and the lower power supply voltage loss percentages of the I-th power supply area dense bus up,i 、I down,i Upper power supply and lower power supply of the i-th power supply area dense bus respectively, S up,i 、S down,i The upper supply and the lower supply loads of the i-th power supply area dense buses are respectively;
when the transformer is used for calculating upward power supply, the upper power supply and lower power supply loads S up,i 、S down,i Maximum power supply distance L from upper power supply and lower power supply up,i 、L down,i ；
When the transformer is powered up and down, the upper power supply and lower power supply loads S are calculated by using the method (28) up,i 、S down,i Maximum power supply distance L from upper power supply and lower power supply up,i 、L down,i ；
Calculating the upper supply and lower supply load S when the transformer supplies power downwards by using the method (29) up,i 、S down,i Maximum power supply distance L from upper power supply and lower power supply up,i 、L down,i ；
Calculating a Pareto optimal solution set G of a multi-objective planning model of the main line of the power distribution network of the super high-rise building by using the method (30):
min G＝min{g 1 ,g 2 ,g 3 ,g 4 ,g 5 } (30)
constraint conditions of the multi-objective planning model of the main line of the power distribution network of the super high-rise building comprise:
1) The transformer position constraints are: w (W) T,i E { device layer or refuge layer };
2) Obtaining a line maximum capacity constraint using equation (31):
S D,i ≤η 0 C L，i (31)
in the formula (31), C L,i For the transmission capacity, eta of the ith power supply zone line 0 Line load factor upper limit;
3) Obtaining a voltage drop constraint using equation (32):
in formula (32), U 0 Is a three-phase power supply voltage deviation allowable value of 20kV and below.
5. An electronic device comprising a memory and a processor, wherein the memory is configured to store a program for supporting the processor to perform the two-stage optimization method of the super high-rise building distribution network of any one of claims 1-4, the processor being configured to execute the program stored in the memory.
6. A computer readable storage medium having stored thereon a computer program, characterized in that the computer program when executed by a processor performs the steps of the two-stage optimization method of an electricity distribution network of a super high-rise building according to any one of claims 1-4.
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