CN112968441B - Power grid planning method applied to large-scale wind power base - Google Patents

Power grid planning method applied to large-scale wind power base Download PDF

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CN112968441B
CN112968441B CN202110269583.8A CN202110269583A CN112968441B CN 112968441 B CN112968441 B CN 112968441B CN 202110269583 A CN202110269583 A CN 202110269583A CN 112968441 B CN112968441 B CN 112968441B
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wind
wind power
cost
capacity
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CN112968441A (en
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张飞
亓豪
高鹭
任晓颖
刘麒
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Inner Mongolia University of Science and Technology
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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
    • 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
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/381—Dispersed generators
    • 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
    • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
    • 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
    • H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/20—The dispersed energy generation being of renewable origin
    • H02J2300/28—The renewable source being wind energy
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E10/00—Energy generation through renewable energy sources
    • Y02E10/70—Wind energy
    • Y02E10/76—Power conversion electric or electronic aspects

Abstract

The invention discloses a power grid planning method applied to a large-scale wind power base, which comprises the following steps of: carrying out gridding processing on a single wind power cluster region, establishing an optimization model by considering the cost of a wind field outlet substation, the cost of a collection station and the cost of a line, converting the model into a mixed integer linear optimization model by including the constraint condition of an actual grid-connected project, and calling cplex by using Matlab to solve; for the whole area, giving wind resource data of each point, converting wind measurement data into output data of an unfinished wind power plant, establishing a constraint condition including wind power admission level, wherein the constraint condition is the sum of investment cost and scheduling cost of a power grid in a planning period as an optimization target, and solving the optimization model by using a neural network to obtain a medium-term and long-term planning model of a large-scale wind power base; the invention can be used for planning the large-scale wind power base to be connected into a large power grid, and provides a more scientific and reasonable planning method for safely and economically connecting the output of the large-scale wind power base into the power grid.

Description

Power grid planning method applied to large-scale wind power base
Technical Field
The invention relates to the technical field of wind power plant planning, in particular to a power grid planning method applied to a large-scale wind power base.
Background
The planning design of the power grid comprising the wind power plant is used as an important work in the early decision-making stage of the power grid development, and is directly related to the safe and stable operation level of the power grid and the economic level of energy utilization and power grid investment. The power grid planning is divided into three phases of long-term, medium-term and short-term.
In order to integrate resources and reasonably adjust the energy supply ratio, a plurality of large-scale wind power bases are planned in each country. Except for the existing developed mode of more centralized wind power resources. There are also areas where large-scale wind resources are abundant that have not yet been developed. The main mode of the wind power base is not on-site consumption, but the generated electric energy is basically sent out. In the development process, the traditional scheme is that planning and later scheduling operation and maintenance are considered separately.
As shown by a large number of studies at present. And analyzing the uncertainty of the wind power resource. There is a correlation of output among wind farms in a certain area. The wind power output in the large-scale region has certain output complementarity, and the fluctuation of the regional wind power generation output can be reduced. In the early planning design, if the coupling characteristic between the wind power plant and the wind power electric field is added, the wind power plant with complementary wind resources is reasonably matched, and different wind resource regions are reasonably developed sequentially, so that the large-scale wind power output power grid or the cost of the later scheduling of the high-permeability power grid and the power line fluctuation of the output power can be greatly saved. When a large-scale external power transmission wind power base is designed and planned in the early period, if the time-space correlation characteristics of wind resources are reasonably considered, the sequential order of wind resource development is considered on the basis of the existing power grid planning. The operation cost can be reduced in the full life cycle of the power grid, so that the full life cycle cost is reduced. Therefore, how to integrate the power grid and the operation and maintenance scheduling becomes a topic with practical research value.
Disclosure of Invention
In order to solve the technical problems, the invention provides a power grid planning method applied to a large-scale wind power base, which can be used for constructing a cluster wind power planning model considering the cost of a transformer substation and the cost of a power transmission line and a medium-long term planning model of the large-scale wind power base comprehensively considering the planning cost and the scheduling operation cost by considering the actual problems of actual power transmission and transformation projects, and determining the site selection and the sequential development sequence of wind power clusters in a planning area.
A power grid planning method applied to a large-scale wind power base is characterized by comprising the following steps:
acquiring data of an existing power grid, load requirements in a planning period, wind resource evaluation results in a planning area, wind resource data in the planning area, planning cost parameters of each site, typical construction cost of a power transmission project, and rasterizing a research area;
and selecting the area of the wind power cluster according to the wind resource distribution condition of the research area, and then establishing an optimization model considering the cost of the transformer substation and the cost of the power transmission line for each wind power cluster area to obtain the site selection of the transformer substation, thereby obtaining the grid structure of the wind power cluster. Establishing a power grid optimization model considering planning cost and scheduling operation cost for the areas of the clusters, and ensuring that constraint conditions of actual grid connection are met;
and converting a mathematical optimization model of site selection of the transformer substation of the wind power cluster into a mixed integer linear model, solving by adopting a Matlab + Yalmip + CPLEX solver to obtain a final site selection of the transformer substation, and determining a grid structure. Solving a mathematical model of the sequential development of the electric field in the whole area through a neural network algorithm to obtain a final planning scheme of 4 periods, wherein each period is 5 years;
the target function expression of the site selection of the transformer substation is as follows:
Figure 650888DEST_PATH_IMAGE001
in the formula (I), the compound is shown in the specification,
Figure 555390DEST_PATH_IMAGE002
the construction and operation cost of the grid-connected process is reduced, the construction time of the grid-connected power transmission process is neglected,
Figure 795878DEST_PATH_IMAGE003
can be further defined as:
Figure 808834DEST_PATH_IMAGE004
wherein, the first and the second end of the pipe are connected with each other,
Figure 425760DEST_PATH_IMAGE005
to represent
Figure 184768DEST_PATH_IMAGE006
The construction cost of the wind farm outlet substation of (1),
Figure 924054DEST_PATH_IMAGE007
to represent
Figure 96410DEST_PATH_IMAGE006
The construction cost of the power transmission line at the outlet of the power station,
Figure 189131DEST_PATH_IMAGE008
of the representation
Figure 396121DEST_PATH_IMAGE009
The construction cost of the collection station of the wind farm group,
Figure 40729DEST_PATH_IMAGE010
represents the construction cost of the collection station grid-connected transmission line,
Figure 638063DEST_PATH_IMAGE011
as is the number of wind farm power stations,
Figure 534475DEST_PATH_IMAGE012
to be the number of the aggregation stations,
Figure 595972DEST_PATH_IMAGE013
incorporating collection stations for wind-farm power stations
Figure 411481DEST_PATH_IMAGE006
The number of the lines is set to be,
Figure 496112DEST_PATH_IMAGE014
for wind power plant to pass through node directly
Figure 992953DEST_PATH_IMAGE015
A 110kV line to be connected to the grid,
Figure 971273DEST_PATH_IMAGE016
passing nodes for sink stations
Figure 160946DEST_PATH_IMAGE015
A grid-connected line;
in actual engineering, the construction cost of a transformer substation of a wind power base is a function of the transformation capacity; therefore, the first and second electrodes are formed on the substrate,
Figure 744591DEST_PATH_IMAGE017
can be written as:
Figure 45123DEST_PATH_IMAGE018
Figure 877949DEST_PATH_IMAGE019
in order to correspond to the variable capacitance of the element,
Figure 238524DEST_PATH_IMAGE020
is that
Figure 297746DEST_PATH_IMAGE019
First, the
Figure 933127DEST_PATH_IMAGE021
Segment of
Figure 823723DEST_PATH_IMAGE022
The construction cost of (a) is a fixed parameter.
Figure 292881DEST_PATH_IMAGE023
To judge
Figure 901717DEST_PATH_IMAGE019
Whether or not in the interval
Figure 809630DEST_PATH_IMAGE022
0-1 decision variable within
Figure 617049DEST_PATH_IMAGE024
When the temperature of the water is higher than the set temperature,
Figure 991530DEST_PATH_IMAGE019
the constraint of (2) is established in the following way,
Figure 822083DEST_PATH_IMAGE025
；
Figure DEST_PATH_IMAGE026
a sufficiently large positive number, K is taken in this application as 1000;
in the same way, the method for preparing the composite material,
Figure 799266DEST_PATH_IMAGE027
can be written as:
Figure DEST_PATH_IMAGE028
and the construction cost of the unit grid-connected line of the wind power plant and the transmission capacity of the line present a functional relationship. Therefore, it is not only easy to use
Figure 336558DEST_PATH_IMAGE029
Can be written as:
Figure DEST_PATH_IMAGE030
Figure 6574DEST_PATH_IMAGE031
substation being a wind farm
Figure 262106DEST_PATH_IMAGE032
Whether to sort to a collection station of a group of wind farms
Figure 246242DEST_PATH_IMAGE033
The 0-1 decision variable of (a),
Figure 28253DEST_PATH_IMAGE034
is to judge
Figure 72433DEST_PATH_IMAGE035
Whether or not in the interval
Figure 815261DEST_PATH_IMAGE036
Of decision variables of
Figure 603088DEST_PATH_IMAGE037
Represent
Figure 239606DEST_PATH_IMAGE031
And
Figure 454687DEST_PATH_IMAGE034
the product of (a), linearizes the equation,
Figure 419231DEST_PATH_IMAGE038
representing wind-farm power stations
Figure 10750DEST_PATH_IMAGE032
To a collection station
Figure 501774DEST_PATH_IMAGE033
The distance of (a);
in the same way, the method for preparing the composite material,
Figure 294281DEST_PATH_IMAGE039
、
Figure 870755DEST_PATH_IMAGE040
can be written as:
Figure 938069DEST_PATH_IMAGE041
Figure 221282DEST_PATH_IMAGE042
further, the constraint conditions of the optimization objective function of the substation site selection are as follows:
(1) Determining the variable of the division of the wind power plant group for ensuring that each wind power plant can be operated in a grid-connected mode
Figure 106062DEST_PATH_IMAGE043
Variables for direct grid connection of wind farm power station to main grid node
Figure 107516DEST_PATH_IMAGE044
Satisfy the requirements of
Figure 712941DEST_PATH_IMAGE045
(2) In order to ensure grid-connected operation of the wind power station group, variables of a collection station grid-connected to a main network node are determined
Figure 116240DEST_PATH_IMAGE046
And satisfies the following conditions:
Figure 171921DEST_PATH_IMAGE047
(3) The capacity constraint of the grid-connected transmission project of the wind power plant generation base mainly comprises that the capacity of an outlet substation of a wind power plant power station is not less than the capacity of an outlet line of the wind power plant power station, the transformation capacity of a collection station of a wind power plant power station group is not less than the sum of the capacities of all outlet lines of the wind power plant power stations collected to the collection station, and the capacity of a grid-connected transmission line of the collection station is not more than the capacity of the collection station:
Figure 395092DEST_PATH_IMAGE048
(4) For the site selection range of the collection station of the wind power plant group, limiting a site selection feasible domain R:
Figure 69787DEST_PATH_IMAGE049
(5) The number of the collection station seats required to be built by planning is determined by the actual grid-connected requirement of the new energy power station, and two extreme conditions are considered, wherein each wind power station is directly connected with the grid, and each wind power station is matched with one collection station to build a collection station grid. Thus, the number of convergent stations required to be constructed is planned
Figure 327593DEST_PATH_IMAGE050
The constraints are as follows:
Figure 288596DEST_PATH_IMAGE051
cluster planning for the entire area: firstly, converting wind speed data into output data according to parameters of a fan and a wind speed-power formula, wherein the design capacity of each wind power cluster is 500MW, selecting the number N of the wind power clusters needing to be built according to the load requirement of a planning period, adding every N power of selected points to obtain total output power, and utilizing a relative standard deviation
Figure 264642DEST_PATH_IMAGE052
To measure the fluctuation of the output, wherein
Figure 477448DEST_PATH_IMAGE053
The functional expression of the mathematical model developed sequentially of the electric field within the region is:
Figure 589761DEST_PATH_IMAGE054
in the formula (I), the compound is shown in the specification,
Figure 987244DEST_PATH_IMAGE055
the investment and construction cost of the unit can be further defined as follows:
Figure 185007DEST_PATH_IMAGE056
t is the planning age, r is the discount rate,
Figure 201505DEST_PATH_IMAGE057
for the investment cost of the newly invested wind power cluster in the t year,
Figure 230641DEST_PATH_IMAGE058
in order to invest cost (yuan/MW) at the point i, the cost also includes the construction cost of the power transmission line caused by different distances between the wind power base and the load center at different points.
Figure 471129DEST_PATH_IMAGE059
The total installed capacity of the unit which needs to be newly input in the t year within the point i;
Figure 359451DEST_PATH_IMAGE060
in the economics, the characteristic that funds have time value for discount rate means that the current purchasing power of one unit of currency is different from the purchasing power of one unit of currency in the future, and the currency will increase in value over time. In economics, the discount rate, which is the rate at which future limited-term expected revenue is discounted to a realized value, is introduced to measure this time-value property of capital. Due to the time value attribute of the currency, the investment values of the wind power cluster in different years are different, and in order to evaluate the planning scheme more accurately, the investment costs in different years need to be converted to the same period for comparison. The discount rate is introduced, and all the expenses can be converted to be calculated at the beginning of the first year;
Figure 976377DEST_PATH_IMAGE061
a cost in actual operation is included, and the cost comprises the fuel expense of the thermal power generating unit, the system load shedding penalty cost and the wind abandoning cost. Namely:
Figure 125599DEST_PATH_IMAGE062
Figure 536988DEST_PATH_IMAGE063
for the fuel cost of the thermal power generating unit, the following can be further defined:
Figure 647027DEST_PATH_IMAGE064
the cost of fuel consumed by the thermal power unit mainly refers to the cost of fuel generated by the operation of the thermal power unit, and the operation of the thermal power unitAnd meanwhile, the fuel cost generated by the power generation unit is related to the power generation amount of the unit, and the fuel cost generated by the power generation amount in different scenes is calculated by adopting a linear programming method.
Figure 67644DEST_PATH_IMAGE065
The number of the scenes is referred to as the number,
Figure 71372DEST_PATH_IMAGE066
the consumed fuel coefficient is generated for the unit generating capacity of the thermal power generating unit,
Figure 919242DEST_PATH_IMAGE067
refers to the probability of each scene occurring,
Figure 516577DEST_PATH_IMAGE068
representing the length of time that the scene s is generating,
Figure 475306DEST_PATH_IMAGE069
represents the power generation time of thermal power under each scene in a year,
Figure 599119DEST_PATH_IMAGE070
representing the output power of the thermoelectric generator set in the s scene in the t year;
Figure DEST_PATH_IMAGE071
the penalty cost for system load shedding can be further defined as:
Figure 289995DEST_PATH_IMAGE072
in a power system containing wind power, due to the time sequence fluctuation and the incomplete prediction accuracy of the wind power, the situation that the system is forced to cut load can possibly occur in some extreme scenes, the system load cutting penalty cost is added into a model, and the load cutting amount of the system is reduced as much as possible;
Figure DEST_PATH_IMAGE073
for cutting loadThe penalty factor of (2) is determined,
Figure 968101DEST_PATH_IMAGE074
the load shedding amount of the system in a t-year scene s;
in order to improve the permeability of the wind power in the power system, the wind abandoning cost is added into the model.
Figure 730520DEST_PATH_IMAGE075
To curtail the cost of wind, it can be further defined as:
Figure 584207DEST_PATH_IMAGE076
Figure DEST_PATH_IMAGE077
cost coefficient for wind power abandonment;
Figure 570618DEST_PATH_IMAGE078
the method is characterized in that the method is the abandoned wind power of the system in a scene of t years s;
further, the constraint conditions of the optimization objective function are as follows:
(1) Total installed capacity equation:
Figure 876965DEST_PATH_IMAGE079
Figure 177496DEST_PATH_IMAGE080
the total installed capacity is a discrete variable, and in order to simplify calculation, a plurality of wind power plants can be built at the position with each point location as the center according to planning requirements, namely the total installed capacity in the position with each point location as the center can only be an integral multiple of the installed capacity of the optional wind power plants. In the equation
Figure 10323DEST_PATH_IMAGE081
Representing the total installed capacity of point i in year t.
Figure DEST_PATH_IMAGE082
Is a variable 0-1, which is used for selecting whether a unit is put into operation at the point, assuming that a plurality of capacity-level wind power clusters can be selected during planning, when the capacity of the first-level wind power cluster is selected to be built at the point i,
Figure 370897DEST_PATH_IMAGE083
on the contrary
Figure 164541DEST_PATH_IMAGE084
。
Figure 268763DEST_PATH_IMAGE085
A set of alternative construction capacities of the unit is represented,
Figure 221676DEST_PATH_IMAGE086
indicating the alternative capacity of the l-th unit (specifying the value of the expression for 1 for l as 0, i.e.
Figure 956414DEST_PATH_IMAGE087
)。
The total installed capacity expression restricts that each point location can only be selected by one capacity level at most, and the capacity level determines the total installed capacity which can be built by the point location. For example, if an alternate construction capacity of 500MW level is selected, then
Figure 299670DEST_PATH_IMAGE088
And so on.
(2) Active power balance constraint
Figure 879687DEST_PATH_IMAGE089
N is a node number, and k is a line number; s is a scene number;
Figure 624789DEST_PATH_IMAGE090
、
Figure 389483DEST_PATH_IMAGE091
respectively representing the output power (MW) of the thermal power generating unit and the wind power generating unit at the t moment of the scene s,
Figure 220036DEST_PATH_IMAGE092
Figure 603744DEST_PATH_IMAGE093
respectively representing incidence matrixes of the node-thermal power generating unit and the node-wind power generating unit, and representing the contact between the node and the wind power generating unit by using the matrixes;
Figure 468932DEST_PATH_IMAGE094
representing the load demand (MW) at node n at time t,
Figure 404527DEST_PATH_IMAGE095
representing the power flow on line k in scene s;
Figure 456796DEST_PATH_IMAGE096
is a node-branch incidence matrix;
Figure 644195DEST_PATH_IMAGE097
representing a set of power lines.
(3) Constraint of DC power flow equation
Figure 363889DEST_PATH_IMAGE098
In the formula (I), the compound is shown in the specification,
Figure 470386DEST_PATH_IMAGE099
represents the admittance of line k;
Figure 9951DEST_PATH_IMAGE100
representing the phase angle at node n in scene s;
Figure 735462DEST_PATH_IMAGE101
for node-branch offA joint matrix;
Figure 309663DEST_PATH_IMAGE102
represented as a set of nodes;
(4) Existing thermal power generating unit output constraint
Figure 587060DEST_PATH_IMAGE103
Figure 879501DEST_PATH_IMAGE104
Actual output (MW) of the generator set i in a scene s for the generator set in the t year;
Figure 143124DEST_PATH_IMAGE105
respectively representing the upper and lower output limits of the thermal power generating unit i,
Figure 837410DEST_PATH_IMAGE106
indicating that the thermal generator set is available.
(5) Newly-built wind power cluster output restraint:
Figure 285709DEST_PATH_IMAGE107
in the formula
Figure 799867DEST_PATH_IMAGE108
Represents the actual contribution ((MW) of the wind power cluster i in the scene in year t,
Figure 867180DEST_PATH_IMAGE109
the wind intensity coefficient at the point i in the scene s is represented, the size of the wind intensity coefficient is related to the distribution condition of wind resources, and the point with the richest wind resources in the planning area is taken
Figure 415973DEST_PATH_IMAGE110
The value is 1, and the coefficients of other point locations are determined according to the proportion of the wind intensity of the point location to the wind intensity of the point location with the most abundant wind resources。
(6) Line transmission capacity constraints
Figure 35173DEST_PATH_IMAGE111
Figure 36627DEST_PATH_IMAGE112
、
Figure 907631DEST_PATH_IMAGE113
Representing the maximum and minimum capacity of the line k.
(7) Constraint of phase angle:
Figure 310931DEST_PATH_IMAGE114
in the formula
Figure 101032DEST_PATH_IMAGE115
Representing the phase angle at the balancing node, the phase angle at the balancing node is 0, and the phase angles at other nodes are free variables.
The invention has the beneficial effects of disclosing a power grid planning method applied to a large-scale wind power base and a sequential development method of the large-scale wind power base. Aiming at a single wind power cluster, the cost of a transformer substation and the cost of a power transmission line are considered, an optimization model for addressing of the transformer substation is established, the complementarity between large-scale wind power bases is considered, the optimization model comprehensively considering the planning cost and the scheduling operation cost is established, the sequential development sequence of large-scale wind power base planning is obtained, the development direction of a power grid is determined, and the accurate investment of the power grid is realized. The method can be used for power grid planning and sequential development under large-scale wind power integration.
Drawings
Fig. 1 is a grid diagram of a research area according to the present invention.
Fig. 2 is a schematic diagram of a power grid planning result of the wind power base.
FIG. 3 is a schematic diagram of the system of the present invention.
FIG. 4 is a flow chart of the present invention.
FIG. 5 is a wind resource analysis display for a region of the present invention.
Fig. 6 is a schematic diagram of the wind farm cluster access grid of the research case.
Detailed Description
Referring to fig. 1-6, the present invention designs a power grid planning method applied to a large-scale wind power base, which mainly comprises the following steps:
1. grid planning for the cluster:
(1) Parameter setting
The planning region is defined as a two-dimensional space
Figure 589783DEST_PATH_IMAGE116
To characterize the geographical range, the grid is numbered using a two-dimensional coordinate system, as shown in fig. 1; each grid is
Figure 264477DEST_PATH_IMAGE117
Grid, obtaining 32 grids in total;
assuming that a 50MW wind power plant can be built in each grid area, wherein the total number of the wind power plants is 32, and the transformer substation of each wind power plant is assumed to be built in the center of a grid; specifically, as shown in table 1, the power grid of the wind power base is planned by using a mathematical optimization model for site selection of the substation in the specification, and the voltage levels of the substations at the outlet of the wind power plant are all 110kV.
TABLE 1 research area wind farm essential information
Figure 319021DEST_PATH_IMAGE118
The wind power base is provided with a 500kV/750kV cluster central station which is used for collecting the output of all wind power plants in the base; in this way, the cluster central station is used as a common connection point for grid connection of the wind power plant or the wind power plant group and is directly connected with the extra-high voltage backbone network frame in the grid connection area. Assume cluster hub location is 11 (45, 45); typical construction cost tables of the power transmission project involved in the method are shown in table 2;
note: the optimization of the planning scheme in the application is to build an MILP model of a wind power grid planning model on Matlab, call a CPLEX12.5 solver to solve the scheme, and configure a used calculator as an Intel (R) Core (TM) i5-4200H @3.40 GHz,8GB RAM.
TABLE 2 typical cost of transmission projects
Figure 217707DEST_PATH_IMAGE119
(2) Scheme analysis for power grid planning
In the power grid planning scheme, 32 wind power plants are directly connected with a cluster central station through 110kV lines. Meanwhile, the capacity configuration of the outlet transformer substation and the outlet line of each wind power plant is carried out in the manner mentioned in the scheme; according to the planning method of the wind power generation base access system, a planning scheme of the wind power generation base access system can be obtained, and simulation results show that:
according to the planning method for the access system of the wind power generation base, the planning scheme for the access system of the wind power generation base can be obtained, and simulation results show that:
the 32 wind power plants are divided into 3 groups for access, and the total cost is lowest. Grouping condition: 1. 2, 3, 7, 8,9, 13, 14, 15 and 19 are the wind farm group 1, and the site selection of the collection station 1 is (16.52, 43.87); 20. 21, 22 and 24-32 are a wind farm group 2, and the site selection of a gathering station 2 is (37.32, 14.58); 4.5, 6, 10, 11, 12, 16, 17, 18 and 23 are wind power plants 3 which are directly connected with a central substation; the line optimization configuration results are shown in table 3; the specific wiring form is shown in fig. 2.
TABLE 3 line configuration optimization results
Figure 131436DEST_PATH_IMAGE120
In addition, fig. 2 also shows that the site of the collection station is located at the middle position of each wind farm inside the wind farm group (the total length of 110k lines is shorter, and 220kV grid-connected lines are longer), but not at the middle position of the public connection point outside the wind farm group (the total length of 110kV lines is longer, and the 220kV lines are shorter). The construction cost of the unit capacity of the 220kV power transmission line is lower than that of the unit capacity of the 110kV power transmission line, and from the economical point of view, if a plurality of wind power plants need to be connected to the power grid through a collecting station, the length of the power transmission line with a lower voltage level is reduced as much as possible by the access system scheme, so that the total cost of the power transmission project is reduced, for example, each cost of the planning scheme of the wind power cluster access system is shown in table 4. Wind power plants with similar geographic positions are divided into the same wind power plant group, a gathering station of the wind power plant group is located in the middle of an area surrounded by the wind power plants, and a main network node closest to the gathering station is selected as a public connection point to be connected to the grid.
TABLE 4 costs of wind power cluster access system planning scheme
Figure 406560DEST_PATH_IMAGE121
2. And (3) medium-long term planning aiming at the large-area wind power cluster:
(1) Setting parameters:
the calculation example adopts the sales electricity quantity of a certain region in China as a load, the average sales electricity quantity growth rate of nearly five years as a load growth rate, actual measurement data of wind speed as calculation example basic data, sampling intervals are one hour, the load data of the first year is used as a reference year, the planning process is carried out by taking a period as a unit, the load growth rate is 9 percent per year, if the planning period is set to be 20 years in 4 periods, the planning internal load growth condition is shown in a table 5, a system standby unit is a 600MW thermal power unit, and the coal consumption is reduced
Figure 581189DEST_PATH_IMAGE122
，
Figure 916356DEST_PATH_IMAGE123
=800 yuan/MW,
Figure 51802DEST_PATH_IMAGE124
=500 yuan/MW;
TABLE 5 schematic diagram of system load change during planning period
Figure 130616DEST_PATH_IMAGE125
In order to verify the feasibility of the model accessing to the power grid, a system with 5 nodes is adopted as a test system, a system diagram is shown in fig. 3, thermal power generating units are respectively installed on the nodes 1 and 2, and the nodes 3,4 and 5 are respectively accessed to two wind power plant groups.
(2) Simulation result
First applying the relative standard deviation
Figure 159752DEST_PATH_IMAGE126
The combination with the least volatility was chosen at the selection points 3,4,6,8,9,11, and a mathematical model was developed according to the sequence described above, resulting in a phase 4 planning scheme as shown in table 6:
TABLE 6 planning scheme Table
Figure 665820DEST_PATH_IMAGE127
As can be seen from the planning results, the wind power clusters are invested in each planning period to meet the load demand of the system, wherein as the load increases year by year, 2 wind power clusters need to be built in 3,4 th period to meet the load demand.

Claims (2)

1. A power grid planning method applied to a large-scale wind power base is characterized by comprising the following steps:
for a single wind power cluster center, constructing a mathematical optimization model, wherein the optimization model takes the sum of the cost of a wind power plant transformer substation, the cost of a collection station and the cost of lines among all stages of transformer substations as the optimal target and contains engineering constraints in a power transmission project, converting the optimization model into a mixed integer linear programming model, and solving the model by using a mixed integer linear programming solver to obtain a grid structure of the single wind power cluster;
the optimization model is as follows:
an objective function:
Figure 512203DEST_PATH_IMAGE001
in the formula (I), the compound is shown in the specification,
Figure 898185DEST_PATH_IMAGE002
the construction and operation cost in the grid-connected process is reduced, the construction time in the grid-connected power transmission process is ignored,
Figure 615606DEST_PATH_IMAGE003
can be further defined as:
Figure 682919DEST_PATH_IMAGE004
wherein the content of the first and second substances,
Figure 231712DEST_PATH_IMAGE005
to represent
Figure 991857DEST_PATH_IMAGE006
The construction cost of the wind farm outlet substation of (a),
Figure 727732DEST_PATH_IMAGE007
to represent
Figure 595807DEST_PATH_IMAGE006
The construction cost of the power transmission line at the outlet of the power station,
Figure 999106DEST_PATH_IMAGE008
of the representation
Figure 930153DEST_PATH_IMAGE009
The construction cost of the collection station of the wind farm group,
Figure 153324DEST_PATH_IMAGE010
power transmission line for indicating collection station and connecting to power gridThe construction cost of the road is reduced,
Figure 562440DEST_PATH_IMAGE011
as is the number of wind farm power stations,
Figure 820246DEST_PATH_IMAGE012
to be the number of the aggregation stations,
Figure 922194DEST_PATH_IMAGE013
incorporating collection stations for wind-farm power stations
Figure 632661DEST_PATH_IMAGE006
The number of the lines is set to be,
Figure 642205DEST_PATH_IMAGE014
for wind power plant to pass through node directly
Figure 957780DEST_PATH_IMAGE015
A grid-connected 110kV line,
Figure 27367DEST_PATH_IMAGE016
passing nodes for sink stations
Figure 225130DEST_PATH_IMAGE015
A grid-connected line;
in actual engineering, the construction cost of a transformer substation of a wind power base is a function of the transformation capacity; therefore, the first and second electrodes are formed on the substrate,
Figure 262136DEST_PATH_IMAGE017
can be written as:
Figure 228955DEST_PATH_IMAGE018
Figure 672706DEST_PATH_IMAGE019
in order to correspond to the variable capacitance of the element,
Figure 561027DEST_PATH_IMAGE020
is that
Figure 177953DEST_PATH_IMAGE019
First, the
Figure 999279DEST_PATH_IMAGE021
Segment of
Figure 613931DEST_PATH_IMAGE022
The construction cost of (a) is a fixed parameter;
Figure 786286DEST_PATH_IMAGE023
to judge
Figure 879007DEST_PATH_IMAGE019
Whether or not in the interval
Figure 85998DEST_PATH_IMAGE022
0-1 decision variable within
Figure 868621DEST_PATH_IMAGE024
When the temperature of the water is higher than the set temperature,
Figure 528273DEST_PATH_IMAGE019
the constraint of (2) is established in the following way,
Figure 221422DEST_PATH_IMAGE025
；
Figure 955023DEST_PATH_IMAGE012
a positive number large enough, K is 1000;
in the same way, the method for preparing the composite material,
Figure 973795DEST_PATH_IMAGE026
can be written as:
Figure 855163DEST_PATH_IMAGE027
the construction cost of a unit grid-connected line of the wind power plant and the transmission capacity of the line present a functional relationship; therefore, it is not only easy to use
Figure 555266DEST_PATH_IMAGE028
Can be written as:
Figure 471269DEST_PATH_IMAGE029
Figure 333046DEST_PATH_IMAGE030
substation being a wind farm
Figure 967290DEST_PATH_IMAGE031
Whether to sort to a collection station of a group of wind farms
Figure 205504DEST_PATH_IMAGE032
The 0-1 decision variable of (a),
Figure 241593DEST_PATH_IMAGE033
is to judge
Figure 271341DEST_PATH_IMAGE034
Whether or not in the interval
Figure 392881DEST_PATH_IMAGE035
Of decision variables of
Figure 434787DEST_PATH_IMAGE036
Represents
Figure 59803DEST_PATH_IMAGE030
And
Figure 528962DEST_PATH_IMAGE033
the product of (a) and (b), linearizes the equation,
Figure 606639DEST_PATH_IMAGE037
representing wind-farm power stations
Figure 514552DEST_PATH_IMAGE031
To a collection station
Figure 462917DEST_PATH_IMAGE032
The distance of (d);
in the same way, the method for preparing the composite material,
Figure 899714DEST_PATH_IMAGE038
、
Figure 667950DEST_PATH_IMAGE039
can be written as:
Figure 848396DEST_PATH_IMAGE041
the constraint conditions of the objective function of the site selection of the transformer substation are as follows:
(1) Determining the variable of the division of the wind power plant group for ensuring that each wind power plant can be operated in a grid-connected mode
Figure 445074DEST_PATH_IMAGE030
Variable directly connected to main network node by new energy power station
Figure 256036DEST_PATH_IMAGE042
It must satisfy:
Figure 573885DEST_PATH_IMAGE043
(2) In order to ensure the grid-connected operation of the new energy power station group, a variable from a collection station to a main network node is determined
Figure 292442DEST_PATH_IMAGE044
It must satisfy:
Figure 949819DEST_PATH_IMAGE045
(3) The capacity constraint of the grid-connected power transmission project of the wind power generation base mainly comprises that the capacity of an outlet transformer substation of a wind power station is not less than the capacity of an outlet line of a new energy power station; the transformation capacity of a collection station of a wind power station group cannot be smaller than the sum of the capacities of outlet lines of all wind power stations collected to the collection station; the capacity of the collection station grid-connected power transmission line is not greater than the capacity of the collection station:
Figure 993999DEST_PATH_IMAGE046
(4) For the site selection range of the collection station of the wind power plant group, limiting a site selection feasible domain R:
Figure 533564DEST_PATH_IMAGE047
(5) The number of the collection stations required to be built by planning is determined by the actual grid-connected requirement of the wind power plant power stations, and two extreme conditions are considered, wherein each wind power plant power station is directly connected with the grid; thus, the number of convergent stations required to be constructed is planned
Figure 259075DEST_PATH_IMAGE048
The constraints are as follows:
Figure 833276DEST_PATH_IMAGE049
planning the wind power bases in the whole area, considering the space-time complementary characteristics and load requirements of each field group, establishing a medium-long term planning optimization model comprehensively considering planning cost and scheduling cost, and solving through a neural network to obtain a sequential development sequence of electric fields in the area;
firstly, converting wind speed data into output data according to parameters of a fan and a wind speed-power formula, wherein the design capacity of each wind power cluster is 500MW, selecting the number N of the wind power clusters needing to be built according to the load requirement of a planning period, adding every N power of selected points to obtain total output power, and utilizing a relative standard deviation
Figure 782777DEST_PATH_IMAGE050
To measure the fluctuation of the output, wherein
Figure 747322DEST_PATH_IMAGE051
By the relative standard deviation obtained
Figure 338840DEST_PATH_IMAGE050
Clustering the wind power output data through k-means to obtain a typical output scene; establishing an optimization model comprehensively considering planning cost and scheduling operation cost to obtain a sequential development sequence of the wind power clusters;
the sequential development model of the electric field in the region is as follows:
an objective function:
Figure 702301DEST_PATH_IMAGE052
in the formula (I), the compound is shown in the specification,
Figure 822704DEST_PATH_IMAGE053
the unit investment and construction cost can be further defined as:
Figure 805703DEST_PATH_IMAGE054
t is the planning age, r is the discount rate,
Figure 935333DEST_PATH_IMAGE053
for the investment cost of the newly invested wind power cluster in the t year,
Figure 156230DEST_PATH_IMAGE055
the investment cost is on the point i, the unit is yuan/MW, and the cost also comprises the construction cost of the power transmission line caused by different distances between the wind power base and the load center on different points;
Figure 978693DEST_PATH_IMAGE056
the total installed capacity of the unit which needs to be newly input in the t year within the point i;
Figure 917830DEST_PATH_IMAGE057
in the economics, the capital has the characteristic of time value, namely the purchasing power of one unit of currency in the present time is different from that of one unit of currency in the future, and the currency is increased with the time; in economics, discount rate, which is the rate of converting future limited-term expected revenue to realized value, is introduced to measure this time-value property of capital; due to the time value attribute of the currency, the investment values of the wind power cluster in different years are different, and in order to more accurately evaluate the planning scheme, the investment costs in different years need to be converted to the same period for comparison; the discount rate is introduced, and all the expenses can be converted to be calculated at the beginning of the first year;
Figure 851151DEST_PATH_IMAGE058
including a cost at actual runtime, includingFuel cost of a thermal power generating unit, system load shedding penalty cost and wind abandoning cost are reduced; namely:
Figure 926554DEST_PATH_IMAGE059
Figure 654339DEST_PATH_IMAGE060
for the fuel cost of the thermal power generating unit, the following can be further defined:
Figure 143089DEST_PATH_IMAGE061
the cost of fuel consumption of the thermal power unit mainly refers to the fuel cost generated by the operation of the thermal power unit, when the thermal power unit operates, the fuel cost generated by the thermal power unit is related to the generated energy of the thermal power unit, and the fuel cost generated by the generated energy of different scenes is calculated by adopting a linear programming method;
Figure 549275DEST_PATH_IMAGE062
the number of the scenes is referred to as the number,
Figure 807081DEST_PATH_IMAGE063
the consumed fuel coefficient is generated for the unit power generation amount of the thermal power generating unit,
Figure 909029DEST_PATH_IMAGE064
means the probability of occurrence of each scene, T S Representing the length of time that the scene s is generating,
Figure 619496DEST_PATH_IMAGE065
represents the power generation time of thermal power under each scene in a year,
Figure 97882DEST_PATH_IMAGE066
representing the output power of the thermoelectric generator set in the s scene in the t year;
Figure 413457DEST_PATH_IMAGE067
the penalty cost for system load shedding can be further defined as:
Figure 686307DEST_PATH_IMAGE068
in a power system containing wind power, due to the time sequence fluctuation and the incomplete prediction accuracy of the wind power, the situation that the system is forced to cut load can possibly occur in some extreme scenes, the system load cutting penalty cost is added into a model, and the load cutting amount of the system is reduced as much as possible;
Figure 149649DEST_PATH_IMAGE069
in order to make the penalty factor of load shedding,
Figure 900567DEST_PATH_IMAGE069
= 800-membered/MWh,
Figure 132966DEST_PATH_IMAGE070
the load shedding amount of the system in a t-year scene s;
in order to improve the permeability of the wind power in the power system, the wind abandoning cost is added into the model;
Figure 573787DEST_PATH_IMAGE071
to curtail the cost of wind, it can be further defined as:
Figure 462108DEST_PATH_IMAGE072
Figure 79034DEST_PATH_IMAGE073
in order to abandon the cost coefficient of the wind power,
Figure 103622DEST_PATH_IMAGE073
=500 yuan/MWh;
Figure 780591DEST_PATH_IMAGE074
the method is characterized in that the method is the abandoned wind power of the system in a scene of t years s;
the constraint conditions of the objective function are as follows:
(1) Total installed capacity equation:
Figure 890630DEST_PATH_IMAGE075
Figure 780088DEST_PATH_IMAGE076
the total installed capacity is a discrete variable, and in order to simplify calculation, a plurality of wind power plants can be built at the position with each point location as the center according to planning requirements, namely the total installed capacity in the position with each point location as the center can only be an integral multiple of the installed capacity of the selectable wind power plants; in the equation
Figure 190341DEST_PATH_IMAGE056
Representing the total installed capacity of the t year point position i;
Figure 772632DEST_PATH_IMAGE077
is a variable 0-1, which is used for selecting whether a unit is put into operation at the point, assuming that a plurality of capacity-level wind power clusters can be selected during planning, when the capacity of the first-level wind power cluster is selected to be built at the point i,
Figure 369967DEST_PATH_IMAGE078
on the contrary
Figure 325766DEST_PATH_IMAGE079
；
Figure 324946DEST_PATH_IMAGE080
Representing a set of unit alternative construction capacity,
Figure 343717DEST_PATH_IMAGE081
representing the alternative capacity of the l-th unit, specifying the value of the expression for 1, i.e. 0
Figure 428348DEST_PATH_IMAGE082
；
The total installed capacity expression restricts that each point location can only have one capacity level at most to be selected, and the capacity level determines the total installed capacity which can be built by the point location; if an alternative construction capacity of the 500MW level is selected, then
Figure 925188DEST_PATH_IMAGE083
And so on;
(2) Active power balance constraint
Figure 778875DEST_PATH_IMAGE084
N is a node number, and k is a line number; s is a scene number;
Figure 968548DEST_PATH_IMAGE085
、
Figure 806054DEST_PATH_IMAGE086
respectively representing the output power of the thermal power generating unit and the wind power generating unit at the moment t of the scene s, the unit is MW,
Figure 841006DEST_PATH_IMAGE087
respectively representing incidence matrixes of the node-thermal power generating unit and the node-wind power generating unit, and representing the contact between the node and the wind power generating unit by using the matrixes;
Figure 549199DEST_PATH_IMAGE088
representing the load demand at node n at time t, in MW,
Figure 909773DEST_PATH_IMAGE089
representing the power flow on line k in scene s;
Figure 989504DEST_PATH_IMAGE090
is a node-branch incidence matrix;
Figure 562567DEST_PATH_IMAGE091
representing a set of power lines;
(3) Constraint of DC power flow equation
Figure 453163DEST_PATH_IMAGE092
In the formula (I), the compound is shown in the specification,
Figure 922322DEST_PATH_IMAGE093
represents the admittance of line k;
Figure 468841DEST_PATH_IMAGE094
representing the phase angle at node n in scene s;
Figure 111175DEST_PATH_IMAGE090
is a node-branch incidence matrix;
Figure 856277DEST_PATH_IMAGE095
represented as a set of nodes;
(4) Existing thermal power generating unit output constraint
Figure 496337DEST_PATH_IMAGE096
Figure 326889DEST_PATH_IMAGE097
The actual output of the generator set i in the scene s in the t year of the generator set is MW;
Figure 445018DEST_PATH_IMAGE098
respectively representing the upper and lower output limits of the thermal power generating unit i,
Figure 310206DEST_PATH_IMAGE099
representing the existing thermal generator set;
(5) Newly-built wind power cluster output restraint:
Figure 914975DEST_PATH_IMAGE100
in the formula
Figure 170507DEST_PATH_IMAGE101
The actual output of the wind power cluster i in the scene in the t year is expressed in MW,
Figure 154644DEST_PATH_IMAGE102
representing the wind intensity coefficient at the point i in the scene s, the size of the coefficient is related to the distribution condition of the wind resources, and the point with the richest wind resources in the planning area is taken
Figure 608759DEST_PATH_IMAGE103
The value is 1, and the coefficients of other point locations are determined according to the proportion between the wind intensity of the point location and the wind intensity of the point location with the most abundant wind resources;
(6) Line transmission capacity constraints
Figure 590621DEST_PATH_IMAGE104
Figure 395766DEST_PATH_IMAGE105
、
Figure 121277DEST_PATH_IMAGE106
Represents the maximum and minimum capacity of line k;
(7) Constraint of phase angle:
Figure 695477DEST_PATH_IMAGE107
in the formula
Figure 848241DEST_PATH_IMAGE108
The phase angle at the balance node is represented, the phase angle at the balance node is 0, and the phase angles at other nodes are free variables.
2. The power grid planning method applied to the large-scale wind power base according to claim 1, wherein: the method comprises the steps of obtaining or planning data of a power grid of a given area in advance, typical construction cost data of a power transmission project of the planned area, unit cost data of the planned area, space-time complementary characteristics of the planned area, wind resource data of the planned area and load prediction data of the planned area.
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