CN107968408B - Asynchronous networking direct-current power plan optimization method, system and device - Google Patents

Asynchronous networking direct-current power plan optimization method, system and device Download PDF

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CN107968408B
CN107968408B CN201711147638.8A CN201711147638A CN107968408B CN 107968408 B CN107968408 B CN 107968408B CN 201711147638 A CN201711147638 A CN 201711147638A CN 107968408 B CN107968408 B CN 107968408B
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power
constraint
direct current
direct
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CN107968408A (en
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陈亦平
郑晓东
侯君
张勇
杜旭
王巍
莫维科
高琴
杨荣照
陈静鹏
陈巨龙
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China Southern Power Grid Co Ltd
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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
    • H02J3/02—Circuit arrangements for ac mains or ac distribution networks using a single network for simultaneous distribution of power at different frequencies; using a single network for simultaneous distribution of ac power and of dc power
    • 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
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Abstract

The invention discloses a method, a system and a device for optimizing a DC power plan of asynchronous networking, wherein the method comprises the following steps: establishing a target function of a direct-current power planning model by taking the minimum maximum direct-current power deviation as an optimization target at a direct-current sending end of the alternating-current and direct-current asynchronous networking; establishing linear constraint of a direct-current power planning model without integer variables; establishing a linear constraint containing 0-1 integer variables of a direct current power planning model; and obtaining an optimized direct-current power plan according to an objective function of the direct-current power plan model, a conventional constraint condition without an integer variable and a linear constraint condition with an integer variable of 0-1. According to the invention, by establishing a linear optimization target of minimizing the maximum DC power deviation of the sending end and combining 2 types of linear constraint conditions, the asynchronous networking DC power planning is classified into a unified large-scale integer linear programming problem, and the method has higher accuracy, reliability and high efficiency. The method can be widely applied to the field of scheduling optimization of the power system.

Description

Asynchronous networking direct-current power plan optimization method, system and device
Technical Field
The invention relates to the field of power system scheduling optimization, in particular to a method, a system and a device for optimizing a DC power plan of asynchronous networking.
Background
The power system is a high-dimensional and strong nonlinear complex dynamic system, and the operation stability of the power system is the first problem of safe production of a power grid. For a long time, the day-ahead operation planning of the power grid is the main basis for determining the future operation mode of the power grid and guiding power production by a power grid dispatching department, and develops in the direction of combining the operation planning with static and transient safety checks. The reasonable day-ahead scheduling operation plan is directly related to the safe and economic operation of the power grid in the future.
Due to uneven distribution of energy and load, long-distance, large-capacity and ultrahigh-voltage power transmission becomes the development trend of power grids in China, and regional power grids such as southern power grids, China power grids and China east power grids form a large-scale alternating current-direct current interconnected power grid (namely alternating current-direct current asynchronous networking) pattern. The day-ahead power dispatching plan between regions (i.e., across regions) is an important component in the day-ahead dispatching operation plan, and has a great significance in playing a complementary role of power resources and loads of each region.
Currently, a dc power plan in an inter-regional day-ahead power dispatching plan is determined by an inter-regional (e.g., provincial) power transmission and reception plan from a transmitting end (e.g., a Yunnan provincial power grid) to a receiving end (e.g., a Guangdong provincial power grid), and the inter-regional (e.g., provincial) power transmission and reception plan depends on load prediction of the transmitting end (e.g., a Yunnan provincial power grid) and the receiving end (e.g., a Guangdong provincial power grid) on the next day. Because the load prediction changes of two adjacent days are not large, the direct current plan curve is generally realized by manually compiling a daily increment plan, and safety check of relevant power and electric quantity and tidal current sections is implemented after the compilation is finished. However, an inter-provincial direct current plan curve is manually compiled according to an incremental power transmission and reception plan, and it is difficult to comprehensively consider the lifting characteristic of the direct current transmitted by the transmitting end (such as a Yunnan province power grid) and the peak shaving characteristic matched with the receiving end (such as a Guangdong province power grid), so a new method must be explored to re-plan the trans-regional transmitting end (such as a Yunnan province power grid) direct current transmission plan.
The existing cross-region direct current power planning algorithm mainly has the following problems: (1) the direct current power can be operated at any level in an interval as required, but the power of a power transmission unit of the direct current power transmission unit has a multiplication term of an integer variable in the shortest duration constraint, so that the model is a mixed integer nonlinear programming problem, and the problem that a day-ahead scheduling model containing hundreds of integer variables and thousands of continuous variables is difficult to solve reliably and efficiently is solved. (2) In consideration of the actual operation requirement of the direct current connecting line, constraint conditions such as direct current power curve stepped constraint, power regulation frequency constraint, power non-backward regulation in a short time and the like are added, but the direct current power is required to operate in discrete gears, and the characteristic of high regulation precision of a direct current system cannot be exerted.
Disclosure of Invention
To solve the above technical problems, the present invention aims to: the method, the system and the device for optimizing the asynchronous networking direct current power plan are reliable, efficient and accurate.
The first technical scheme adopted by the invention is as follows:
a method for optimizing a DC power plan of asynchronous networking comprises the following steps:
establishing a target function of a direct-current power planning model by taking the minimum maximum direct-current power deviation as an optimization target at a direct-current sending end of the alternating-current and direct-current asynchronous networking;
establishing linear constraint of a direct-current power planning model without integer variables;
establishing linear constraints containing 0-1 integer variables of a direct current power planning model, wherein the linear constraints containing 0-1 integer variables comprise power smooth running constraints, non-back regulation constraints in a short time, power regulation frequency constraints and power regulation process curve shape constraints;
and obtaining an optimized direct-current power plan according to an objective function of the direct-current power plan model, a conventional constraint condition without an integer variable and a linear constraint condition with an integer variable of 0-1.
Further, the step of establishing an objective function of the direct-current power planning model at the direct-current sending end of the alternating-current/direct-current asynchronous networking by taking the minimum maximum direct-current power deviation as an optimization objective specifically comprises:
at a direct current sending end of the alternating current-direct current asynchronous networking, establishing an objective function of a direct current power plan model by taking the minimum maximum direct current power deviation of the sending end as an optimization target, wherein the objective function expression of the direct current power plan model is as follows:
Figure BDA0001472816760000021
wherein minimize and max are respectively a minimum function and a maximum function, T is a set of scheduling time periods, T is any time period of T, DC is a set of direct current lines, i is any return direct current in DC, and PDCi,tFor the direct current power of the ith return direct current in the alternating current-direct current asynchronous network in the time period t, PTtAnd (4) carrying out power plan for total power transmission and reception of the AC-DC asynchronous networking in a time period t.
Further, the step of establishing a linear constraint that the direct current power planning model does not contain integer variables specifically includes:
establishing a maximum power deviation constraint;
establishing power transmission and reception electric quantity constraint;
establishing direct current operation constraint;
establishing power plant operation constraints;
establishing local section constraint;
establishing AGC gateway power constraint;
and establishing direct current power balance constraints of each loop.
Further, the maximum power deviation constraint expression is:
Figure BDA0001472816760000031
wherein, Δ PTminAnd Δ PTmaxRespectively minimum power deviation and maximum power deviation;
the expression of the power transmission and reception capacity constraint is as follows:
Figure BDA0001472816760000032
wherein E isTFor daily exchange of planned values of electric power between zones, ∈TThe inter-regional daily exchange electric quantity deviation coefficient;
the direct current operation constraint comprises a direct current operation power constraint, and the expression of the direct current operation power constraint is as follows:
PDCimin≤PDCi,t≤PDCimax,
Figure BDA0001472816760000033
t∈T，
wherein, PDCimaxAnd PDCiminRespectively setting a maximum power limit value and a minimum power limit value of the ith return direct current in the alternating current-direct current asynchronous networking;
the direct current operation constraint further comprises a direct current regulation speed constraint, and an expression of the direct current regulation speed constraint is as follows:
Figure BDA0001472816760000034
t and(t+1)∈T，
wherein, PDCi,(t+1)For the direct current power of the ith return direct current in the alternating current-direct current asynchronous networking in a time period (t +1),
Figure BDA0001472816760000035
and
Figure BDA0001472816760000036
the upper regulation rate limit value and the lower regulation rate limit value of the ith return direct current in the alternating current-direct current asynchronous networking are respectively;
the power plant operation constraint comprises a power plant power constraint, and the power plant power constraint has the expression:
PGjmin≤PGj,t≤PGjmax,
Figure BDA0001472816760000037
t∈T，
wherein G is electricitySubscript set of plant, PGj,tFor the power, P, of the jth power plant in the AC-DC asynchronous network in the time period tGjmaxAnd PGjminThe maximum power limit value and the minimum power limit value of the jth power plant in the AC-DC asynchronous networking are respectively set;
the power plant operation constraint further comprises a power plant regulation speed constraint, and the expression of the power plant regulation speed constraint is as follows:
Figure BDA0001472816760000038
t and(t+1)∈T，
wherein, PGj,(t+1)For the power of the jth power plant in the AC-DC asynchronous networking in the time period (t +1),
Figure BDA0001472816760000041
and
Figure BDA0001472816760000042
the downward climbing speed limit value and the upward climbing speed limit value of the jth power plant in the AC-DC asynchronous networking are respectively set;
the power plant operation constraint further comprises power plant electric quantity constraint, and the expression of the power plant electric quantity constraint is as follows:
Figure BDA0001472816760000043
wherein E isijFor the daily generated energy planning value of the jth power plant in AC-DC asynchronous networkingijOperating deviation coefficients for the daily generated energy of the jth power plant in the AC-DC asynchronous networking;
the expression of the local section constraint is as follows:
PLkmin≤PLk,t≤PLkmax,
Figure BDA0001472816760000044
t∈T，
wherein L is a subscript set of a local cross section, PLk,tFor the power of the kth local slice at time period t,PLkmaxand PLkminRespectively setting a forward maximum power flow limit value and a reverse maximum power flow limit value of the kth local section;
the expression of the AGC gateway power constraint is as follows:
Figure BDA0001472816760000045
wherein, PAGCmaxAnd PAGCminMaximum power constraint and minimum power constraint of an AGC gateway are respectively, and the AGC gateway is the sum of all local sections;
the expression of the DC power balance constraint of each loop is as follows:
Figure BDA0001472816760000046
wherein p iseqIs a constant representing the degree of dc power balance.
Further, the expression of the power smooth operation constraint is as follows:
Figure BDA0001472816760000047
wherein the content of the first and second substances,
Figure BDA0001472816760000048
and
Figure BDA0001472816760000049
an upper regulation rate limit value and a lower regulation rate limit value of the ith return direct current in the alternating current-direct current asynchronous networking are respectively,
Figure BDA0001472816760000051
and
Figure BDA0001472816760000052
are all variables of integers from 0 to 1,
Figure BDA0001472816760000053
the power representing the time period (t +1) is adjusted downward,
Figure BDA0001472816760000054
the power representing the time period (t +1) is adjusted upward,
Figure BDA0001472816760000055
or
Figure BDA0001472816760000056
The power level representing the time period (t +1) does not change, PDCi,(t+1)For the direct current power of the ith return direct current in the alternating current-direct current asynchronous networking in a time period (t +1),
Figure BDA0001472816760000057
represents the upper limit of the number of power non-stationary operating time segments.
Further, the expression of the short-time non-retuning constraint is as follows:
Figure BDA0001472816760000058
wherein the content of the first and second substances,
Figure BDA0001472816760000059
and
Figure BDA00014728167600000510
are all variables of integers from 0 to 1,
Figure BDA00014728167600000511
the power representing the time period (t +2) is adjusted downward,
Figure BDA00014728167600000512
the power representing the time period (t +2) is adjusted upward,
Figure BDA00014728167600000513
or
Figure BDA00014728167600000514
Indicating that the power level for time period (T +2) did not change, both (T +2) and (T +1) are a time period within T.
Further, the power adjustment times constraint specifically includes: there are minimum integer variables of 0-1
Figure BDA00014728167600000515
And the smallest variable of 0-1 integer
Figure BDA00014728167600000516
Enabling a set power regulation frequency constraint equation to be established, wherein the set power regulation frequency constraint equation is as follows:
Figure BDA00014728167600000517
wherein, the variable is an integer of 0 to 1
Figure BDA00014728167600000518
Representing whether the direct current power of the ith return direct current in the alternating current-direct current asynchronous networking is changed from smooth operation to adjustment, wherein the integral variable is 0-1
Figure BDA00014728167600000519
Representing whether the direct current power of the ith return direct current in the alternating current-direct current asynchronous networking is changed into smooth operation from the end of adjustment or not in a time period t, xi,tAnd xi,t+1All are integer variables from 0 to 1, xi,tIndicating whether the direct current power of the time period (t +1) is changed compared with the time period t; x is the number ofi,t+1Indicating whether the dc power of the time period (T +2) is changed or not compared with the time period (T +1), where (T +2) and (T +1) are both a time period within T, NmaxRepresents the upper limit of the number of power steps.
Further, the curve shape constraint of the power adjustment process specifically includes: there are minimum integer variables of 0-1
Figure BDA0001472816760000061
So that the shape of the set power regulating curve is aboutThe beam equation is established, and the set power regulation curve shape constraint equation is as follows:
Figure BDA0001472816760000062
wherein the content of the first and second substances,
Figure BDA0001472816760000063
and
Figure BDA0001472816760000064
respectively providing a maximum limit value and a minimum limit value of the regulation rate change rate of the ith return direct current in the alternating current-direct current asynchronous networking;
Figure BDA0001472816760000065
representing the upper limit of the change times of the power regulation process or the maximum number of curve inflection points; pDCi,(t+1)And PDCi,(t+2)The direct current power of the ith return direct current in the alternating current-direct current asynchronous networking in a time period (T +1) and a time period (T +2) respectively, wherein (T +1) and (T +2) are both a time period in T, and P isDCi,(t+2)-2PDCi,(t+1)+PDCi,tIs the differential value of the rate of change of power,
Figure BDA0001472816760000066
is an auxiliary variable introduced for representing whether the power change rate of the time interval adjacent to the time interval (t +1) is changed, when the power change rate of the time interval adjacent to the time interval (t +1) is not changed, PDCi,(t+2)-2PDCi,(t+1)+PDCi,tIs zero, when
Figure BDA0001472816760000067
Is 0; when the power change rate of the time section adjacent to the time section (t +1) is changed, PDCi,(t+2)-2PDCi,(t+1)+PDCi,tIs not zero, when
Figure BDA0001472816760000068
Is 1.
The second technical scheme adopted by the invention is as follows:
an asynchronously networked direct current power plan optimization system, comprising the following modules:
the objective function establishing module is used for establishing an objective function of a direct-current power plan model at a direct-current sending end of the alternating-current/direct-current asynchronous networking by taking the minimum maximum direct-current power deviation as an optimization target;
the constraint establishing module is used for establishing a linear constraint of the direct current power planning model, wherein the linear constraint does not contain integer variables;
the linear constraint building module is used for building a linear constraint containing 0-1 integer variables of the direct current power plan model, and the linear constraint containing 0-1 integer variables comprises a power stable operation constraint, a non-back regulation constraint in a short time, a power regulation frequency constraint and a power regulation process curve shape constraint;
and the optimized direct current power plan obtaining module is used for obtaining an optimized direct current power plan according to the objective function of the direct current power plan model, the conventional constraint condition without the integer variable and the linear constraint condition with the integer variable of 0-1.
The third technical scheme adopted by the invention is as follows:
an asynchronously networked direct current power plan optimization apparatus, comprising:
a memory for storing a program;
a processor, configured to load the program to perform the method for optimizing an asynchronous networked dc power plan according to the first technical solution.
The invention has the beneficial effects that: the invention relates to a method, a system and a device for optimizing a DC power plan of an asynchronous networking, wherein at a DC sending end of an AC-DC asynchronous networking, a target function of a DC power plan model is established by taking the minimum maximum DC power deviation as an optimization target, the DC power plan of the asynchronous networking is classified into a unified large-scale integer linear programming problem by establishing a linear optimization target of the minimum maximum DC power deviation of the sending end and combining a linear constraint condition without an integer variable and a linear constraint condition with an integer variable of 0-1, and the optimized DC power plan is finally obtained. The advantage of high adjustment precision of the direct current system is fully exerted through the linear constraint condition without integer variables, the direct current power is not required to operate at discrete gears, and the method has high precision, reliability and high efficiency.
Drawings
FIG. 1 is an overall flow chart of a method for DC power plan optimization for asynchronous networking in accordance with the present invention;
FIG. 2 is a flowchart illustrating a first embodiment of the present invention;
FIG. 3 is a comparison graph of power curves obtained by applying the method of the present invention and an artificial method to Chu ear direct current respectively;
FIG. 4 is a graph comparing power curves obtained from cattle using DC power by the method of the present invention and artificial method, respectively;
FIG. 5 is a comparison graph of power curves obtained by applying the method of the present invention to a direct current of a general public key and by applying the manual method to the direct current of the general public key, respectively;
Detailed Description
Referring to fig. 1, a method for optimizing an asynchronous networked dc power plan includes the following steps:
establishing a target function of a direct-current power planning model by taking the minimum maximum direct-current power deviation as an optimization target at a direct-current sending end of the alternating-current and direct-current asynchronous networking;
establishing linear constraint of a direct-current power planning model without integer variables;
establishing linear constraints containing 0-1 integer variables of a direct current power planning model, wherein the linear constraints containing 0-1 integer variables comprise power smooth running constraints, non-back regulation constraints in a short time, power regulation frequency constraints and power regulation process curve shape constraints;
and obtaining an optimized direct-current power plan according to an objective function of the direct-current power plan model, a conventional constraint condition without an integer variable and a linear constraint condition with an integer variable of 0-1.
The objective function of the direct-current power planning model enables the superposed direct-current power to fit the planned power among the regions as much as possible and minimize the maximum power deviation through a direct-current power planning algorithm, so that the existing power transmission and reception plan among the regions is decomposed to each return direct-current connecting line.
The direct current power plan model does not contain linear constraints of integer variables, and the direct current power is matched with a power and electric quantity plan at the day before under the condition that the direct current power meets the local section and AGC gateway power and the like by establishing linear constraint conditions such as maximum power deviation constraint, transmission and receiving electric quantity constraint, direct current operation power constraint, power plant operation power constraint, local section constraint, AGC gateway power constraint and the like.
The direct current power plan model contains linear constraints of 0-1 integer variables and is used for enabling the direct current power plan to meet the constraints of actual operation requirements of stable operation, no inverse regulation in a short time, few power regulation times, stepped direct current power curves and the like, and the constraints need to introduce 0-1 discrete variables.
The invention integrates the linear optimization target of the minimum maximum direct current power deviation of a transmitting end, linear constraint conditions which do not contain integer variables, such as single maximum direct current power deviation constraint, power transmission and receiving electric quantity constraint, direct current operation power constraint, power plant operation power constraint, local section constraint, AGC gateway power constraint and the like, and 0-1 integer variable linear conditions which meet the requirements of stable direct current power operation, no inverse regulation in a short time, few power regulation times and the like, and integrates asynchronous networking direct current power planning (DCPS) into a unified large-scale integer linear programming problem. The invention comprehensively considers the discrete characteristic of the direct current power curve and various operation constraints of the system, establishes the direct current power planning model and has higher accuracy, safety and high efficiency. When the method is applied to the establishment work of the direct-current power plan of the dispatching center, the executable direct-current connecting line plan and the power plant power generation plan can be quickly formed, and the rationality of the power transmission and receiving plan of the asynchronous power grid is improved.
Further as a preferred embodiment, the step of establishing an objective function of the dc power planning model at the dc sending end of the ac/dc asynchronous networking with the minimum dc maximum power deviation as an optimization objective specifically includes:
at a direct current sending end of the alternating current-direct current asynchronous networking, establishing an objective function of a direct current power plan model by taking the minimum maximum direct current power deviation of the sending end as an optimization target, wherein the objective function expression of the direct current power plan model is as follows:
Figure BDA0001472816760000081
wherein minize and max are respectively a minimum function and a maximum function, T is a set of scheduling time periods, T is any time period of T, DC is a set of direct current lines (i.e. a subscript set of a direct current loop), i is any direct current in DC, and P isDCi,tFor the direct current power of the ith return direct current in the alternating current-direct current asynchronous network in the time period t, PTtAnd (4) carrying out power plan for total power transmission and reception of the AC-DC asynchronous networking in a time period t.
Where T may be obtained by dividing 24 hours a day into several scheduled time periods (e.g., 96 time periods).
Further as a preferred embodiment, the step of establishing a linear constraint that the direct current power planning model does not contain integer variables specifically includes:
establishing a maximum power deviation constraint;
establishing power transmission and reception electric quantity constraint;
establishing direct current operation constraint;
establishing power plant operation constraints;
establishing local section constraint;
establishing AGC gateway power constraint;
and establishing direct current power balance constraints of each loop.
Further preferably, the maximum power deviation constraint is expressed by:
Figure BDA0001472816760000091
wherein, Δ PTminAnd Δ PTmaxRespectively minimum power deviation and maximum power deviation;
the expression of the power transmission and reception capacity constraint is as follows:
Figure BDA0001472816760000092
wherein E isTFor daily exchange of planned values of electric power between zones, ∈TThe inter-regional daily exchange electric quantity deviation coefficient;
the direct current operation constraint comprises a direct current operation power constraint, and the expression of the direct current operation power constraint is as follows:
PDCimin≤PDCi,t≤PDCimax,
Figure BDA0001472816760000093
t∈T，
wherein, PDCimaxAnd PDCiminRespectively setting a maximum power limit value and a minimum power limit value of the ith return direct current in the alternating current-direct current asynchronous networking;
the direct current operation constraint further comprises a direct current regulation speed constraint, and an expression of the direct current regulation speed constraint is as follows:
Figure BDA0001472816760000094
t and(t+1)∈T，
wherein, PDCi,(t+1)For the direct current power of the ith return direct current in the alternating current-direct current asynchronous networking in a time period (t +1),
Figure BDA0001472816760000095
and
Figure BDA0001472816760000101
the upper regulation rate limit value and the lower regulation rate limit value of the ith return direct current in the alternating current-direct current asynchronous networking are respectively.
The power plant operation constraint comprises a power plant power constraint, and the power plant power constraint has the expression:
PGjmin≤PGj,t≤PGjmax,
Figure BDA0001472816760000102
t∈T，
wherein G is a subscript set of the power plant, PGj,tFor the power, P, of the jth power plant in the AC-DC asynchronous network in the time period tGjmaxAnd PGjminThe maximum power limit value and the minimum power limit value of the jth power plant in the AC-DC asynchronous networking are respectively set;
the power plant operation constraint further comprises a power plant regulation speed constraint, and the expression of the power plant regulation speed constraint is as follows:
Figure BDA0001472816760000103
t and(t+1)∈T，
wherein, PGj,(t+1)For the power of the jth power plant in the AC-DC asynchronous networking in the time period (t +1),
Figure BDA0001472816760000104
and
Figure BDA0001472816760000105
the downward climbing speed limit value and the upward climbing speed limit value of the jth power plant in the AC-DC asynchronous networking are respectively set;
the power plant operation constraint further comprises power plant electric quantity constraint, and the expression of the power plant electric quantity constraint is as follows:
Figure BDA0001472816760000106
wherein E isGjFor the daily generated energy planning value, epsilon, of the jth power plant in AC-DC asynchronous networkingGjOperating deviation coefficients for the daily generated energy of the jth power plant in the AC-DC asynchronous networking;
the expression of the local section constraint is as follows:
PLkmin≤PLk,t≤PLkmax,
Figure BDA0001472816760000107
t∈T，
wherein L is a subscript set of a local cross section, PLk,tFor the power of the kth local section in time period t, PLkmaxAnd PLkminRespectively setting a forward maximum power flow limit value and a reverse maximum power flow limit value of the kth local section;
the expression of the AGC gateway power constraint is as follows:
Figure BDA0001472816760000108
wherein, PAGCmaxAnd PAGCminMaximum power constraint and minimum power constraint of an AGC gateway are respectively, and the AGC gateway is the sum of all local sections;
the expression of the DC power balance constraint of each loop is as follows:
Figure BDA0001472816760000111
wherein p iseqIs a constant representing the degree of dc power balance.
Further as a preferred embodiment, the expression of the power soft-running constraint is:
Figure BDA0001472816760000112
wherein the content of the first and second substances,
Figure BDA0001472816760000113
and
Figure BDA0001472816760000114
an upper regulation rate limit value and a lower regulation rate limit value of the ith return direct current in the alternating current-direct current asynchronous networking are respectively,
Figure BDA0001472816760000115
and
Figure BDA0001472816760000116
are all variables of integers from 0 to 1,
Figure BDA0001472816760000117
the power representing the time period (t +1) is adjusted downward,
Figure BDA0001472816760000118
the power representing the time period (t +1) is adjusted upward,
Figure BDA0001472816760000119
or
Figure BDA00014728167600001110
The power level representing the time period (t +1) does not change, PDCi,(t+1)For the direct current power of the ith return direct current in the alternating current-direct current asynchronous networking in a time period (t +1),
Figure BDA00014728167600001111
represents the upper limit of the number of power non-stationary operating time segments.
Further as a preferred embodiment, the expression of the short-time non-retuning constraint is:
Figure BDA00014728167600001112
wherein the content of the first and second substances,
Figure BDA00014728167600001113
and
Figure BDA00014728167600001114
are all variables of integers from 0 to 1,
Figure BDA00014728167600001115
the power representing the time period (t +2) is adjusted downward,
Figure BDA00014728167600001116
the power representing the time period (t +2) is adjusted upward,
Figure BDA00014728167600001117
or
Figure BDA00014728167600001118
Indicating that the power level for time period (T +2) did not change, both (T +2) and (T +1) are a time period within T.
Further as a preferred embodiment, the power adjustment number constraint specifically is: there are minimum integer variables of 0-1
Figure BDA00014728167600001119
And the smallest variable of 0-1 integer
Figure BDA00014728167600001120
Enabling a set power regulation frequency constraint equation to be established, wherein the set power regulation frequency constraint equation is as follows:
Figure BDA0001472816760000121
wherein, the variable is an integer of 0 to 1
Figure BDA0001472816760000122
Representing whether the direct current power of the ith return direct current in the alternating current-direct current asynchronous networking is changed from smooth operation to adjustment, wherein the integral variable is 0-1
Figure BDA0001472816760000123
Representing whether the direct current power of the ith return direct current in the alternating current-direct current asynchronous networking is changed into smooth operation from the end of adjustment or not in a time period t, xi,tAnd xi,t+1All are integer variables from 0 to 1, xi,tIndicating whether the direct current power of the time period (t +1) is changed compared with the time period t; x is the number ofi,t+1Denotes a time period (t +2) compared with the time period (t +1)Whether the DC power of (a) is changed or not, (T +2) and (T +1) are both a time period within T, NmaxRepresents the upper limit of the number of power steps.
Wherein, when the DC power of the time period (t +1) changes, xi,tIs 1, otherwise xi,tIs 0; when the DC power of the time period (t +2) changes, xi,t+1Is 1, otherwise xi,tIs 0.
Further as a preferred embodiment, the power adjustment process curve shape constraint is specifically: there are minimum integer variables of 0-1
Figure BDA0001472816760000124
Enabling a set power regulation curve shape constraint equation to be established, wherein the set power regulation curve shape constraint equation is as follows:
Figure BDA0001472816760000125
wherein the content of the first and second substances,
Figure BDA0001472816760000126
and
Figure BDA0001472816760000127
respectively providing a maximum limit value and a minimum limit value of the regulation rate change rate of the ith return direct current in the alternating current-direct current asynchronous networking;
Figure BDA0001472816760000128
representing the upper limit of the change times of the power regulation process or the maximum number of curve inflection points; pDCi,(t+1)And PDCi,(t+2)The direct current power of the ith return direct current in the alternating current-direct current asynchronous networking in a time period (T +1) and a time period (T +2) respectively, wherein (T +1) and (T +2) are both a time period in T, and P isDCi,(t+2)-2PDCi,(t+1)+PDCi,tIs the differential value of the rate of change of power,
Figure BDA0001472816760000131
is when the characteristic time periods (t +1) are adjacentAn auxiliary variable is introduced according to whether the interval power change rate is changed, when the interval power change rate adjacent to the interval (t +1) is not changed, PDCi,(t+2)-2PDCi,(t+1)+PDCi,tIs zero, when
Figure BDA0001472816760000132
Is 0; when the power change rate of the time section adjacent to the time section (t +1) is changed, PDCi,(t+2)-2PDCi,(t+1)+PDCi,tIs not zero, when
Figure BDA0001472816760000133
Is 1.
Corresponding to the method of fig. 1, the invention provides an asynchronous networked direct current power plan optimization system, which comprises the following modules:
the objective function establishing module is used for establishing an objective function of a direct-current power plan model at a direct-current sending end of the alternating-current/direct-current asynchronous networking by taking the minimum maximum direct-current power deviation as an optimization target;
the constraint establishing module is used for establishing a linear constraint of the direct current power planning model, wherein the linear constraint does not contain integer variables;
the linear constraint building module is used for building a linear constraint containing 0-1 integer variables of the direct current power plan model, and the linear constraint containing 0-1 integer variables comprises a power stable operation constraint, a non-back regulation constraint in a short time, a power regulation frequency constraint and a power regulation process curve shape constraint;
and the optimized direct current power plan obtaining module is used for obtaining an optimized direct current power plan according to the objective function of the direct current power plan model, the conventional constraint condition without the integer variable and the linear constraint condition with the integer variable of 0-1.
Corresponding to the method of fig. 1, the invention provides an asynchronous networked dc power plan optimization device, which includes:
a memory for storing a program;
and the processor is used for loading the program to execute the asynchronous networking direct current power plan optimization method.
The invention will be further explained and explained with reference to the drawings and the embodiments in the description.
Example one
In order to solve the problem of nonlinear programming of a large-scale inter-regional Power transmission and reception direct current Power plan and the problem of discrete step of direct current Power operation, the invention provides a linear direct current Power plan (DCPS) model algorithm to optimize an asynchronous networking direct current Power plan.
Taking the southwest power grid outgoing power plan of the southwest power grid as an example, as shown in fig. 2, the method for optimizing the southwest power grid direct current power plan specifically includes the following steps:
s1, planning the direct current power delivered from Yunnan into a large-scale linear programming problem by taking the minimum maximum direct current power deviation as an optimization target;
s2, establishing conventional constraint conditions without integer variables, such as power deviation, adjusting speed, coulometric planning and local section;
s3, establishing constraints containing 0-1 integer variables, such as stable operation, reverse regulation, regulation times and the like of a direct current power curve;
and S4, obtaining an optimized Yunnan power grid outgoing power plan according to the conventional constraint without the integer variable and the constraint with the integer variable of 0-1.
The step S1 combines the characteristics of the yunnan power grid dc asynchronous networking, and puts the minimization of the power transmission plan power deviation of the yunnan power grid into a linear optimization target problem, to obtain a target function of the yunnan power grid power transmission dc power plan model:
Figure BDA0001472816760000141
the step S2 considers the operation constraints of dc, power plant, local ac tie line, etc. (these constraints may be expressed by linear inequalities containing continuous variables), and establishes a general constraint without integer variables. As shown in fig. 2, the conventional constraint without integer variables specifically includes:
(1) maximum power deviation constraint
The expression of the maximum power deviation constraint of the present embodiment is:
Figure BDA0001472816760000142
wherein, Δ PTminAnd Δ PTmaxThe minimum power deviation and the maximum power deviation can be set as the maximum total transmission and reception power PTmax0.02 times of the total weight of the powder.
(2) Constrained by transmission and reception electric quantity
The expression of the power transmission and reception constraint of the present embodiment is:
Figure BDA0001472816760000143
wherein E isTExchanging planned values of electric quantity, epsilon, for the days of the provincesTThe difference coefficient of the electric quantity is exchanged between the provinces and the days. EpsilonTTypically 2%.
(3) Direct current operation constraint
The dc operating constraints of the present embodiment include dc operating power constraints and dc regulation speed constraints.
The expression of the direct current operating power constraint is as follows:
PDCimin≤PDCi,t≤PDCimax,
Figure BDA0001472816760000144
t∈T，
wherein, PDCimaxAnd PDCiminThe maximum power limit value and the minimum power limit value of the ith return direct current are respectively.
The expression of the direct current regulation speed constraint is as follows:
Figure BDA0001472816760000145
t and(t+1)∈T，
wherein, PDCi,(t+1)The dc power of the i-th return dc in the time period (t +1),
Figure BDA0001472816760000151
and
Figure BDA0001472816760000152
an upper regulation rate limit value and a lower regulation rate limit value of the ith return current are respectively.
(4) Power plant operation constraints
The plant operating constraints of the present embodiment include a plant power constraint, a plant regulation speed constraint, and a plant capacity constraint.
The power plant power constraint expression is:
PGjmin≤PGj,t≤PGjmax,
Figure BDA0001472816760000153
t∈T，
wherein G is a subscript set of the power plant, PGj,tFor the power of the jth plant during the time period t, PGjmaxAnd PGjminMaximum and minimum power limits for the jth plant, respectively.
The expression of the power plant regulation speed constraint is as follows:
Figure BDA0001472816760000154
t and(t+1)∈T，
wherein, PGj,(t+1)For the power of the jth plant during time period (t +1),
Figure BDA0001472816760000155
and
Figure BDA0001472816760000156
respectively a downward climbing rate limit value and an upward climbing rate limit value of the jth power plant.
The expression of the power plant electric quantity constraint is as follows:
Figure BDA0001472816760000157
wherein E isGjFor the daily generated energy plan value of the jth power plant, ∈GjThe deviation factor is operated for the daily power generation of the jth power plant.
(5) Local cross-sectional constraint
The expression of the local section constraint of this embodiment is:
PLkmin≤PLk,t≤PLkmax,
Figure BDA0001472816760000158
t∈T，
wherein L is a subscript set of a local cross section, PLk,tFor the power of the kth local section in time period t, PLkmaxAnd PLkminThe positive maximum power flow limit and the reverse maximum power flow limit of the kth local section are respectively. The local cross-section is a part of ac lines in the synchronous power grid, and the power flow of these lines needs to be considered when planning the inter-regional power transmission and reception plan. And each loop of the Yunnan power grid at the sending end corresponds to 1 to 2 adjacent large-scale hydraulic power plants and is responsible for transmitting the electric power of the power plants to east provinces. Specifically, the cattle are responsible for the power delivery of the rivastigmine right bank power plant from direct current (direct current transmission engineering from the shin-shotong Yanjin cattle village converter station to the Guangdong subordinate west converter station), and the direct current and the power plant power are not completely matched, so that the Gancai line between the shinhai converter station and the Gancai substation of the Yunnan power grid is a local section to be considered. For a matched set of local sections, power plants and direct currents, the following coupling relationships apply: the power of the local section is the power of direct current-power plant power, namely: pL,t＝PDC,t-PG,t。
(6) AGC gateway power constraint
The expression of the AGC gateway power constraint of this embodiment is:
Figure BDA0001472816760000161
wherein, PAGCmaxAnd PAGCminMaximum and minimum power constraints, respectively, for the AGC gate, which is the sum of all local sections.
(7) DC power balance constraint of each loop
The expression of each loop of dc power balance constraint in this embodiment is:
Figure BDA0001472816760000162
wherein p iseqIs a constant representing the degree of dc power balance. According to historical operating data, peqMay be set to 30.
In order to not change the linear characteristic of the model, linearizing the quadratic term of each loop of the direct current power balance constraint expression: note the book
Figure BDA0001472816760000163
Let p bei,t＝Pi,t,1+Pi,t,2And p isi,t,1∈[0,pmt]，pi,t,2∈[0,1-pmt]With pi,t＝PmtFor piecewise point piecewise linearization, then (P)i,t-Pmt)2Can be written
Figure BDA0001472816760000165
To sum up, the dc power balance constraint can be rewritten as:
Figure BDA0001472816760000164
the step S3 combines the characteristics of the step and the discreteness of the direct-current transmission plan curve, and the constraint conditions of stable operation of the power curve, no inverse regulation in a short time, power regulation times and the like are classified into 0-1 discrete variable constraint, so that the solution optimization of the model is greatly simplified.
As shown in fig. 2, the constraint containing the integer variable from 0 to 1 specifically includes:
(1) power smooth running constraint
The specific expression of the power smooth operation constraint of the embodiment is as follows:
Figure BDA0001472816760000171
wherein the content of the first and second substances,
Figure BDA0001472816760000172
and
Figure BDA0001472816760000173
an upper regulation rate limit and a lower regulation rate limit of the ith return current,
Figure BDA0001472816760000174
and
Figure BDA0001472816760000175
are all variables of integers from 0 to 1,
Figure BDA0001472816760000176
represents the upper limit of the number of power non-stationary operating time segments.
Figure BDA0001472816760000177
The power representing the time period (t +1) is adjusted downward,
Figure BDA0001472816760000178
the power representing the time period (t +1) is adjusted upward,
Figure BDA0001472816760000179
or
Figure BDA00014728167600001710
The power level representing the time period (t +1) does not change. The time of the DC power in the non-steady process (i.e. the regulation process) is not more than 6 hours, so that
Figure BDA00014728167600001711
And may be set to 24 when T is equally divided into 96 periods.
(2) No back regulation in short time
The expression of the constraint not to be adjusted in a short time in the embodiment is as follows:
Figure BDA00014728167600001712
under the action of the constraint condition of no reverse regulation in the short time, the power regulating variable
Figure BDA00014728167600001713
No [ (1,0), (0,1) occurrence is allowed]Or [ (0,1), (1,0)]The value of (2) eliminates the condition that the direct current power is adjusted up and down in adjacent time intervals, namely, the direct current power curve is prevented from having a peak. The constraint expression without inverse adjustment in a short time has the advantages that the constraint expression is a linear inequality, a nonlinear equation is prevented from being introduced, and efficient solution of a model is facilitated.
(3) Power regulation times constraint
The power adjustment times constraint conditions of this embodiment are specifically:
there are minimum integer variables of 0-1
Figure BDA00014728167600001714
And the smallest variable of 0-1 integer
Figure BDA00014728167600001715
Enabling a set power regulation frequency constraint equation to be established, wherein the set power regulation frequency constraint equation is as follows:
Figure BDA0001472816760000181
wherein, the variable is an integer of 0 to 1
Figure BDA0001472816760000182
Indicating whether the direct current power of the ith return direct current in the alternating current-direct current asynchronous networking is changed from smooth operation to the direct current power of the ith return direct current in the time period tInitial adjustment, 0-1 integer variable
Figure BDA0001472816760000183
And the direct current power of the ith return direct current in the alternating current-direct current asynchronous networking in the time period t is changed from the end of adjustment to smooth operation. N is a radical ofmaxThe upper limit of the number of power stages is shown, and in actual operation, the number of stages of a direct current power curve in one day is generally required to be within 8, namely Nmax＝16。
(4) Power regulation process curve shape constraint
During the power adjustment process, the adjustment rate cannot be changed at will, and the present embodiment limits the curve shape of the power adjustment process by the curve shape constraint of the power adjustment process.
The curve shape constraint of the power adjustment process in this embodiment is specifically: there are minimum integer variables of 0-1
Figure BDA0001472816760000184
Enabling a set power regulation curve shape constraint equation to be established, wherein the set power regulation curve shape constraint equation is as follows:
Figure BDA0001472816760000185
wherein
Figure BDA0001472816760000186
And
Figure BDA0001472816760000187
respectively providing a maximum limit value and a minimum limit value of the regulation rate change rate of the ith return direct current in the alternating current-direct current asynchronous networking;
Figure BDA0001472816760000188
represents the upper limit of the change times of the power regulation process or the maximum number of curve inflection points. PDCi,(t+2)-2PDCi,(t+1)+PDCi,tIs the difference of the power change rate, when the power change rate of the time section adjacent to the time section (t +1) is not changedThe difference value is zero when
Figure BDA0001472816760000189
Is 0; similarly, when the power change rate of the time period adjacent to the time period (t +1) is changed, the difference value is 1, and at this time
Figure BDA00014728167600001810
And 1, the power curve inflection point occurs. Since the regulation rate is generally unchanged or changed at most 1 to 2 times in the DC power regulation process, the regulation rate is changed
Figure BDA00014728167600001811
Should be taken to be slightly larger than NmaxIs an integer of (1).
Fig. 3, fig. 4 and fig. 5 show a comparison graph of a power curve planned by chu sui direct current (a direct current transmission project from yunnan chu male converter station to guangdong sui dong converter station), a power curve planned by cow from direct current (a direct current transmission project from yunnan showtain oxford converter station to guangdong subordinate west converter station) and a power curve planned by general direct current (a direct current transmission project from yunnan pu converter station to guangdong qiao country converter station) respectively according to the direct current power planning optimization method (DCPS) of the present invention and a power curve planned by a Manual method (Manual).
As can be seen from fig. 3, fig. 4 and fig. 5 in combination with the DCPS model, the advantages of the direct current power planning (DCPS) algorithm of the present embodiment are as follows:
(1) the ideal power transmission and reception curve can be accurately fitted, so that the power transmission and reception deviation among areas is small, and the power plan is strictly executed; the modeling of the characteristics of the direct current power curve is accurate and complete, and the obtained curve completely meets the requirements of actual operation.
(2) Constraint conditions such as power plant operation and local section flow are comprehensively considered, the obtained scheme has strong performability and accords with safety constraint. However, it is difficult to ensure that all safety constraints are met by manual planning, as shown in fig. 3, according to the manual planning of the same day, the current of the local alternating current section corresponding to the chu-ear direct current has the highest value of 2300MW and exceeds the maximum limit value of 700 MW.
(3) Compared with the manual incremental curve, the direct-current power curve constrained by the stable power operation constraint, the inverse regulation constraint and the regulation process has a stable regulation speed and a step property of the regulation process, so that the power plan of each direct-current channel is reasonably arranged on the basis of ensuring the electric quantity of the power delivered by each power plant in Yunnan, and the aim of optimizing the peak regulation in Guangdong province by utilizing the direct current delivered by the Yunnan province is fulfilled.
According to the method, the system and the device for optimizing the asynchronous networked direct current power plan, disclosed by the invention, the asynchronous networked direct current power plan (DCPS) is classified into a unified large-scale integer linear programming problem by establishing a linear optimization target of minimizing the maximum direct current power deviation of a sending end and combining linear constraint conditions which do not contain integer variables, such as single maximum direct current power deviation constraint, power transmission and reception electric quantity constraint, direct current running power constraint, power plant running power constraint, local section constraint, AGC gateway power constraint and the like, and linear constraint conditions which meet the requirements of stable direct current power running, no reverse regulation in a short time and few power regulation times and contain 0-1 integer variables. The invention comprehensively considers the discrete characteristic of the direct current power curve and various operation constraints of the system, establishes the direct current power planning model, solves the problems of nonlinear programming and discrete step of direct current power operation, and has higher accuracy, safety and high efficiency. The method is applied to the establishment work of the direct-current power plan of the dispatching center, can quickly form an executable direct-current connecting line plan and a power plant power generation plan, and improves the rationality of the power transmission and receiving plan of the asynchronous power grid.
While the preferred embodiments of the present invention have been illustrated and described, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.

Claims (9)

1. A method for optimizing a DC power plan of asynchronous networking is characterized by comprising the following steps: the method comprises the following steps:
establishing a target function of a direct-current power planning model by taking the minimum maximum direct-current power deviation as an optimization target at a direct-current sending end of the alternating-current and direct-current asynchronous networking;
establishing linear constraint of a direct-current power planning model without integer variables;
establishing linear constraints containing 0-1 integer variables of a direct current power planning model, wherein the linear constraints containing 0-1 integer variables comprise power smooth running constraints, non-back regulation constraints in a short time, power regulation frequency constraints and power regulation process curve shape constraints;
obtaining an optimized direct-current power plan according to an objective function of the direct-current power plan model, a conventional constraint condition without an integer variable and a linear constraint condition with an integer variable of 0-1;
wherein, the curve shape constraint of the power regulation process specifically comprises: there are minimum integer variables of 0-1
Figure FDA0002808068380000011
Enabling a set power regulation curve shape constraint equation to be established, wherein the set power regulation curve shape constraint equation is as follows:
Figure FDA0002808068380000012
wherein the content of the first and second substances,
Figure FDA0002808068380000013
and
Figure FDA0002808068380000014
respectively providing a maximum limit value and a minimum limit value of the regulation rate change rate of the ith return direct current in the alternating current-direct current asynchronous networking;
Figure FDA0002808068380000015
representing the upper limit of the change times of the power regulation process or the maximum number of curve inflection points; PDCi, (t +1) and PDCi,(t+2)The direct current power of the ith return direct current in the alternating current-direct current asynchronous networking in a time period (t +1) and a time period (t +2) (t +1) and (t +2) respectivelyA time period, P, within TDCi,(t+2)-2PDCi,(t+1)+PDCi,tIs the differential value of the rate of change of power,
Figure FDA0002808068380000016
is an auxiliary variable introduced for representing whether the power change rate of the time interval adjacent to the time interval (t +1) is changed, when the power change rate of the time interval adjacent to the time interval (t +1) is not changed, PDCi,(t+2)-2PDCi,(t+1)+PDCi,tIs zero, when
Figure FDA0002808068380000017
Is 0; when the power change rate of the time section adjacent to the time section (t +1) is changed, PDCi,(t+2)-2PDCi,(t+1)+PDCi,tIs not zero, when
Figure FDA0002808068380000018
Is 1.
2. The asynchronous networked direct current power plan optimization method of claim 1, wherein: the method comprises the following steps of establishing an objective function of a direct-current power plan model by taking the minimum maximum direct-current power deviation as an optimization objective at a direct-current sending end of the alternating-current and direct-current asynchronous networking, and specifically comprises the following steps:
at a direct current sending end of the alternating current-direct current asynchronous networking, establishing an objective function of a direct current power plan model by taking the minimum maximum direct current power deviation of the sending end as an optimization target, wherein the objective function expression of the direct current power plan model is as follows:
Figure FDA0002808068380000021
wherein minimize and max are respectively a minimum function and a maximum function, T is a set of scheduling time periods, T is any time period of T, DC is a set of direct current lines, i is any return direct current in DC, and PDCi,tIs alternating current and direct currentDC power P of ith return DC in time period t in asynchronous networkTtAnd (4) carrying out power plan for total power transmission and reception of the AC-DC asynchronous networking in a time period t.
3. The asynchronous networked direct current power plan optimization method of claim 2, wherein: the step of establishing the linear constraint that the direct current power planning model does not contain integer variables specifically comprises the following steps:
establishing a maximum power deviation constraint;
establishing power transmission and reception electric quantity constraint;
establishing direct current operation constraint;
establishing power plant operation constraints;
establishing local section constraint;
establishing AGC gateway power constraint;
and establishing direct current power balance constraints of each loop.
4. The asynchronous networked direct current power plan optimization method of claim 3, wherein: the maximum power deviation constraint expression is:
Figure FDA0002808068380000022
wherein, Δ PTminAnd Δ PTmaxRespectively minimum power deviation and maximum power deviation;
the expression of the power transmission and reception capacity constraint is as follows:
Figure FDA0002808068380000023
wherein E isTFor daily exchange of planned values of electric power between zones, ∈TThe inter-regional daily exchange electric quantity deviation coefficient;
the direct current operation constraint comprises a direct current operation power constraint, and the expression of the direct current operation power constraint is as follows:
Figure FDA0002808068380000031
wherein, PDCimaxAnd PDCiminRespectively setting a maximum power limit value and a minimum power limit value of the ith return direct current in the alternating current-direct current asynchronous networking;
the direct current operation constraint further comprises a direct current regulation speed constraint, and an expression of the direct current regulation speed constraint is as follows:
Figure FDA0002808068380000032
wherein, PDCi,(t+1)For the direct current power of the ith return direct current in the alternating current-direct current asynchronous networking in a time period (t +1),
Figure FDA0002808068380000033
and
Figure FDA0002808068380000034
the upper regulation rate limit value and the lower regulation rate limit value of the ith return direct current in the alternating current-direct current asynchronous networking are respectively;
the power plant operation constraint comprises a power plant power constraint, and the power plant power constraint has the expression:
Figure FDA0002808068380000035
wherein G is a subscript set of the power plant, PGj,tFor the power, P, of the jth power plant in the AC-DC asynchronous network in the time period tGjmaxAnd PGjminThe maximum power limit value and the minimum power limit value of the jth power plant in the AC-DC asynchronous networking are respectively set;
the power plant operation constraint further comprises a power plant regulation speed constraint, and the expression of the power plant regulation speed constraint is as follows:
Figure FDA0002808068380000036
wherein, PGj,(t+1)For the power of the jth power plant in the AC-DC asynchronous networking in the time period (t +1),
Figure FDA0002808068380000037
and
Figure FDA0002808068380000038
the downward climbing speed limit value and the upward climbing speed limit value of the jth power plant in the AC-DC asynchronous networking are respectively set;
the power plant operation constraint further comprises power plant electric quantity constraint, and the expression of the power plant electric quantity constraint is as follows:
Figure FDA0002808068380000039
wherein E isGjFor the daily generated energy planning value, epsilon, of the jth power plant in AC-DC asynchronous networkingGjOperating deviation coefficients for the daily generated energy of the jth power plant in the AC-DC asynchronous networking;
the expression of the local section constraint is as follows:
Figure FDA00028080683800000310
wherein L is a subscript set of a local cross section, PLk,tFor the power of the kth local section in time period t, PLkmaxAnd PLkminRespectively setting a forward maximum power flow limit value and a reverse maximum power flow limit value of the kth local section;
the expression of the AGC gateway power constraint is as follows:
Figure FDA0002808068380000041
wherein, PAGCmaxAnd PAGCminMaximum power constraint and minimum power constraint of an AGC gateway are respectively, and the AGC gateway is the sum of all local sections;
the expression of the DC power balance constraint of each loop is as follows:
Figure FDA0002808068380000042
wherein p iseqIs a constant representing the degree of dc power balance.
5. The asynchronous networked direct current power plan optimization method of claim 2, wherein: the expression of the power smooth operation constraint is as follows:
Figure FDA0002808068380000043
wherein the content of the first and second substances,
Figure FDA0002808068380000044
and
Figure FDA0002808068380000045
an upper regulation rate limit value and a lower regulation rate limit value of the ith return direct current in the alternating current-direct current asynchronous networking are respectively,
Figure FDA0002808068380000046
and
Figure FDA0002808068380000047
are all variables of integers from 0 to 1,
Figure FDA0002808068380000048
the power representing the time period (t +1) is adjusted downward,
Figure FDA0002808068380000049
the power representing the time period (t +1) is adjusted upward,
Figure FDA00028080683800000410
or
Figure FDA00028080683800000411
The power level representing the time period (t +1) does not change, PDCi,(t+1)For the direct current power of the ith return direct current in the alternating current-direct current asynchronous networking in a time period (t +1),
Figure FDA00028080683800000412
represents the upper limit of the number of power non-stationary operating time segments.
6. The asynchronous networked direct current power plan optimization method of claim 5, wherein: the expression of the non-retuning constraint in the short time is as follows:
Figure FDA0002808068380000051
wherein the content of the first and second substances,
Figure FDA0002808068380000052
and
Figure FDA0002808068380000053
are all variables of integers from 0 to 1,
Figure FDA0002808068380000054
the power representing the time period (t +2) is adjusted downward,
Figure FDA0002808068380000055
the power representing the time period (t +2) is adjusted upward,
Figure FDA0002808068380000056
or
Figure FDA0002808068380000057
Indicating that the power level for time period (T +2) did not change, both (T +2) and (T +1) are a time period within T.
7. The asynchronous networked direct current power plan optimization method of claim 2, wherein: the power regulation times constraint specifically includes: there are minimum integer variables of 0-1
Figure FDA0002808068380000058
And the smallest variable of 0-1 integer
Figure FDA0002808068380000059
Enabling a set power regulation frequency constraint equation to be established, wherein the set power regulation frequency constraint equation is as follows:
Figure FDA00028080683800000510
wherein, the variable is an integer of 0 to 1
Figure FDA00028080683800000511
Representing whether the direct current power of the ith return direct current in the alternating current-direct current asynchronous networking is changed from smooth operation to adjustment, wherein the integral variable is 0-1
Figure FDA00028080683800000512
Representing whether the direct current power of the ith return direct current in the alternating current-direct current asynchronous networking is changed into smooth operation from the end of adjustment or not in a time period t, xi,tAnd xi,t+1All are integer variables from 0 to 1, xi,tIndicating whether the direct current power of the time period (t +1) is changed compared with the time period t; x is the number ofi,t+1Indicates whether or not the DC power of the time period (t +2) is changed compared with the time period (t +1), and both (t +2) and (t +1)A time period within T, NmaxRepresents the upper limit of the number of power steps.
8. An asynchronously networked direct current power plan optimization system, characterized by: the system comprises the following modules:
the objective function establishing module is used for establishing an objective function of a direct-current power plan model at a direct-current sending end of the alternating-current/direct-current asynchronous networking by taking the minimum maximum direct-current power deviation as an optimization target;
the constraint establishing module is used for establishing a linear constraint of the direct current power planning model, wherein the linear constraint does not contain integer variables;
the linear constraint building module is used for building a linear constraint containing 0-1 integer variables of the direct current power plan model, and the linear constraint containing 0-1 integer variables comprises a power stable operation constraint, a non-back regulation constraint in a short time, a power regulation frequency constraint and a power regulation process curve shape constraint;
the optimized direct-current power plan obtaining module is used for obtaining an optimized direct-current power plan according to a target function of the direct-current power plan model, a conventional constraint condition without an integer variable and a linear constraint condition with an integer variable of 0-1;
wherein, the curve shape constraint of the power regulation process specifically comprises: there are minimum integer variables of 0-1
Figure FDA0002808068380000061
Enabling a set power regulation curve shape constraint equation to be established, wherein the set power regulation curve shape constraint equation is as follows:
Figure FDA0002808068380000062
wherein the content of the first and second substances,
Figure FDA0002808068380000063
and
Figure FDA0002808068380000064
respectively providing a maximum limit value and a minimum limit value of the regulation rate change rate of the ith return direct current in the alternating current-direct current asynchronous networking;
Figure FDA0002808068380000065
representing the upper limit of the change times of the power regulation process or the maximum number of curve inflection points; pDCi,(t+1)And PDCi,(t+2)The direct current power of the ith return direct current in the alternating current-direct current asynchronous networking in a time period (T +1) and a time period (T +2) respectively, wherein (T +1) and (T +2) are both a time period in T, and P isDCi,(t+2)-2PDCi,(t+1)+PDCi,tIs the differential value of the rate of change of power,
Figure FDA0002808068380000066
is an auxiliary variable introduced for representing whether the power change rate of the time interval adjacent to the time interval (t +1) is changed, when the power change rate of the time interval adjacent to the time interval (t +1) is not changed, PDCi,(t+2)-2PDCi,(t+1)+PDCi,tIs zero, when
Figure FDA0002808068380000067
Is 0; when the power change rate of the time section adjacent to the time section (t +1) is changed, PDCi,(t+2)-2PDCi,(t+1)+PDCi,tIs not zero, when
Figure FDA0002808068380000068
Is 1.
9. An asynchronous networked direct current power plan optimization device, characterized by: the method comprises the following steps:
a memory for storing a program;
a processor for loading the program to perform a method of asynchronous networked direct current power plan optimization as claimed in any one of claims 1 to 7.
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