CN106786719B - New energy power generation operation optimization method and device in multi-terminal flexible direct current power grid - Google Patents

New energy power generation operation optimization method and device in multi-terminal flexible direct current power grid Download PDF

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CN106786719B
CN106786719B CN201611224474.XA CN201611224474A CN106786719B CN 106786719 B CN106786719 B CN 106786719B CN 201611224474 A CN201611224474 A CN 201611224474A CN 106786719 B CN106786719 B CN 106786719B
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station
new energy
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CN106786719A (en
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刘纯
李湃
王伟胜
黄越辉
王跃峰
张琳
张楠
高云峰
许晓艳
潘霄锋
李丽
唐林
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State Grid Corp of China SGCC
China Electric Power Research Institute Co Ltd CEPRI
State Grid Shandong Electric Power Co Ltd
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State Grid Corp of China SGCC
China Electric Power Research Institute Co Ltd CEPRI
State Grid Shandong Electric Power 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
    • H02J3/36—Arrangements for transfer of electric power between ac networks via a high-tension dc link
    • H02J3/383—
    • H02J3/386—
    • 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
    • H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
    • 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]
    • 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
    • Y02E10/50—Photovoltaic [PV] energy
    • Y02E10/56—Power conversion systems, e.g. maximum power point trackers
    • 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
    • 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
    • Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
    • Y02E60/60—Arrangements for transfer of electric power between AC networks or generators via a high voltage DC link [HVCD]

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  • Engineering & Computer Science (AREA)
  • Power Engineering (AREA)
  • Supply And Distribution Of Alternating Current (AREA)
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Abstract

The invention provides a new energy power generation operation optimization method and device in a multi-terminal flexible direct current power grid, wherein the method comprises the steps of establishing a new energy power generation operation optimization model in the multi-terminal flexible direct current power grid according to pre-acquired topological structure information of the multi-terminal flexible direct current power grid, and determining an optimal power generation mode according to a commercial optimization packet solving optimization model; the device comprises a solving unit and a modeling unit; the technical scheme provided by the invention relates to the operation restriction of new energy power generation, a multi-end flexible direct current network system, a conventional thermal power generating unit and a pumped storage power station, and the maximum receiving capacity of new energy and the corresponding optimal power generation operation mode of the new energy, the conventional thermal power generating unit and the pumped storage power station in a scheduling period are obtained by the optimization model.

Description

New energy power generation operation optimization method and device in multi-terminal flexible direct current power grid
Technical Field
The invention relates to the field of new energy power generation operation optimization accessed to a multi-terminal flexible direct-current power grid, in particular to a new energy power generation operation optimization method and device in the multi-terminal flexible direct-current power grid.
Background
The new energy power generation mainly based on wind energy and light energy is rapidly developed in China, but because the output randomness and the intermittence of the new energy are very strong, the large-scale grid connection of the new energy brings huge pressure to the safe operation of a power system in China, and is influenced by insufficient local absorption capacity, the limitation of an outgoing channel and the like, the problem of wind abandoning and light abandoning and electricity limiting in a new energy enrichment area is increasingly prominent, and resources are seriously wasted.
With the development of power system technology, multi-terminal flexible direct current transmission gradually becomes an important technical means for solving the problems of wind power integration and energy consumption. The flexible direct current transmission has no problems of voltage fluctuation and reactive compensation after new energy is accessed, can quickly, flexibly and independently control active power and reactive power, and has a network formation condition. The multi-end flexible direct-current power grid formed on the basis has the advantages of multiple power supplies and multiple ground power supplies, flexible interaction of new energy, a conventional thermal power generating unit and a pumped storage power station can be realized, and the utilization efficiency is improved; and the power flow reversal is convenient and quick, the operation mode is flexible to change, and the reliability is high.
At present, research on new energy access of a multi-terminal flexible direct-current power grid mainly focuses on the aspects of a grid-connected control strategy of the flexible direct-current power grid after new energy access, analysis of dynamic characteristics of an alternating-current and direct-current power grid and the like, and research on optimization of a new energy power generation operation mode of the multi-terminal flexible direct-current power grid is little. The research in this aspect needs to establish a corresponding optimization model, and two problems mainly face during optimization modeling: firstly, the adaptability of the method is improved, the operation limit of a conventional thermal power generating unit and a pumped storage power station and the loss of lines need to be considered in an optimization model, and the physical constraint condition with obvious nonlinear characteristics undoubtedly increases the difficulty of optimization solution; secondly, because the power flow circularly flows in the flexible direct current power grid with the annular structure, the optimization problem has multiple solutions which are not consistent with the actual physical condition, and therefore a certain modeling skill is required to be adopted for elimination.
In order to solve the above problems, it is necessary to provide a new energy power generation operation optimization method in a multi-terminal flexible direct current power grid, so that the established optimization model is convenient to solve.
Disclosure of Invention
In order to meet the technical development requirement, the invention provides a new energy power generation operation optimization method in a multi-terminal flexible direct-current power grid.
The invention provides a new energy power generation operation optimization method in a multi-terminal flexible direct current power grid, which is improved in that the optimization method comprises the following steps:
acquiring a new energy optimal power generation mode according to an operation optimization model solved by the commercial optimization package; the operation optimization model is an operation optimization model for establishing a new energy power generation mode according to pre-collected topological structure information of the direct current power grid;
further, the topology structure information of the multi-terminal flexible dc power grid collected in advance includes:
the method comprises the following steps that new energy, node position information of a transmitting end converter station connected with a thermal power generating unit and a pumped storage power station and node position information of a receiving end converter station connected with a load are obtained;
the method comprises the steps of predicting a power output value and a load predicted value of a new energy source in a scheduling period, setting an initial state of a conventional unit in a scheduling starting period, setting an initial water storage amount of a reservoir on a pumped storage power station, and setting the maximum current conversion capacity, the line length and the line loss rate of a direct-current power grid current conversion station.
Further, the operation optimization model is shown as the following formula (1):
Figure BDA0001193319250000021
in the formula (I), the compound is shown in the specification,
Figure BDA0001193319250000022
representing the total power generation amount of the new energy accessed to the flexible direct-current power grid; t: the total number of scheduling time segments; i isRN(ii) a A node set of a transmitting end converter station for accessing new energy in a direct current power grid;
Figure BDA0001193319250000023
and
Figure BDA0001193319250000024
wind power and photovoltaic power generation output power of a node i of the sending end converter station are respectively accessed at the moment t;
Figure BDA0001193319250000026
: a penalty item of the total loss of the line; a: a penalty factor; epsiloni,j(t): loss of power on line (i, j) at time t; epsilonj,i(t): loss of power on line (j, i) at time t; i is a node set in the direct current power grid: j. the design is a squarei: and all nodes connected with the node i are collected.
Further, the constraints of the running optimization model include:
the method comprises the following steps of new energy output restriction, thermal power generating unit operation restriction, extraction and storage power station operation restriction, transmission line restriction, transmitting end converter station and receiving end converter station conversion restriction.
Further, the new energy output constraint is as follows:
Figure BDA0001193319250000025
in the formula, Pi W(t) and Pi V(t): the maximum output of wind power and photovoltaic power generation at the moment t respectively;
the thermal power generating unit operation constraint comprises:
<1>unit output restraint: xi(t)·Pi min≤pi(t)≤Xi(t)·Pi max,i∈ITH(3)
In the formula ITH: accessing a direct-current power grid node set of the thermal power generating unit; p is a radical ofi(t): the thermal power generating unit accessed by the node i outputs power at the moment t; pi minAnd Pi max: the minimum and maximum technical output of the thermal power generating unit at the node i; xi(t) the operation state of the thermal power generating unit at the moment t is represented as 0 or 1 integer variable, 1 represents that the thermal power generating unit is in operation, and 0 represents that the thermal power generating unit is not in operation;
<2>and (3) climbing restraint:
Figure BDA0001193319250000031
in the formula (I), the compound is shown in the specification,
Figure BDA0001193319250000032
and
Figure BDA0001193319250000033
respectively representing the maximum climbing and descending power of the unit; p is a radical ofi(t + 1): representing the output of the thermal power generating unit accessed to the node i at the moment t + 1;
<3>minimum on-off time constraint:
Figure BDA0001193319250000034
in the formula, Yi(t) and Zi(t) is the starting state and the stopping state of the unit in the time period t, and both are integer variables of 0-1; for Yi(t) ═ 0 means nothingStarting state, Yi(t) ═ 1 indicates that startup is in progress; zi(t) ═ 0 indicates that the engine is not in a stopped state, Zi(t) ═ 1 indicates that shutdown is underway; k is a radical ofiRepresenting a minimum start-up time or a minimum shut-down time of the unit;
<4>and (3) starting and stopping state constraint:
Figure BDA0001193319250000035
further, the pumped storage power plant operating constraints include:
1) and (3) generating power constraint:
Figure BDA0001193319250000036
in the formula ICX: a node set of a pumped storage power station is accessed into a direct current power grid;
Figure BDA0001193319250000037
the generated power of the pumped storage power station in a time period t;
Figure BDA0001193319250000038
and
Figure BDA0001193319250000039
respectively the minimum and maximum generating power of the pumped storage power station; SXi(t) is an integer variable of 0-1, representing the operating state of the pumped storage power station, SXi(t) '1' indicates that the extraction and storage power station is in a power generation state, and SXi(t) ═ 0 indicates that the extraction power station is not generating power;
2) and (3) water pumping power constraint:
Figure BDA00011933192500000310
in the formula (I), the compound is shown in the specification,
Figure BDA00011933192500000311
pumping power of the pumping power station in a time period t;
Figure BDA00011933192500000312
and
Figure BDA00011933192500000313
respectively the minimum and maximum pumping power of the pumping power station; SY (simple and easy) to usei(t) is an integer variable from 0 to 1, representing the operating state of the station, SYi(t) < 1 > indicates that the pumping station is in a pumping state, SYi(t) ═ 0 indicates that the extraction power station is not extracting water;
3) and (4) constraint of the running state: SX is more than or equal to 0i(t)+SYi(t)≤1,i∈ICX(9)；
4) And (4) library capacity constraint:
Figure BDA0001193319250000041
in the formula, Wi 0(t): the initial water storage capacity of a reservoir on the pumping power station in a time period t; wi end(t): the water storage capacity of an upper reservoir of the pumped storage power station at the end of the t period; wi end(t-1): representing the water storage capacity of a reservoir on the pumped storage power station at the end of the t-1 period; wi InitialInitial water storage of the upper reservoir of the station during a first period ηGAnd ηS: the average water quantity/electric quantity conversion coefficients of the pumped storage power station during power generation and water pumping are respectively.
Further, the transmission line constraints include:
<1>and (3) line loss constraint:
Figure BDA0001193319250000042
in the formula (I), the compound is shown in the specification,
Figure BDA0001193319250000043
is the power on line (i, j) flowing from node i;
Figure BDA0001193319250000044
power flowing on line (i, j) into node j; epsiloni,j(t) line loss power on line (i, j) αi,jIs the line loss rate of line (i, j); l isi,j: the transmission distance of the line (i, j);
Figure BDA0001193319250000045
is the power on line (j, i) flowing from node j;
Figure BDA0001193319250000046
power flowing on line (j, i) to node i; epsilonj,i(t) line loss power on line (j, i) αj,iIs the line loss rate of the line (j, i); l isj,i: the transmission distance of the line (j, i);
<2>transmission security constraints:
Figure BDA0001193319250000047
in the formula (I), the compound is shown in the specification,
Figure BDA0001193319250000048
is the maximum work transmitted on line (i, j);
Figure BDA0001193319250000049
is the maximum transmission power on the line (j, i).
Further, the constraints of the sending end converter station and the receiving end converter station include:
1) and (3) limiting the current conversion capacity of the sending end converter station:
Figure BDA00011933192500000410
in the formula, Pi binThe maximum current conversion capacity of the sending end current conversion station;
2) and (3) the current conversion capacity of the receiving end current conversion station is restricted:
Figure BDA0001193319250000051
in the formula, Pi boutFor the maximum conversion capacity of the receiving end converter station,
Figure BDA0001193319250000052
for power off-line, IoutThe method comprises the steps of collecting receiving end converter stations in a direct current network system;
3) and (3) power balance constraint of the sending end converter station:
Figure BDA0001193319250000053
in the formula (I), the compound is shown in the specification,
Figure BDA0001193319250000054
and
Figure BDA0001193319250000055
wind power and photovoltaic power generation output power of a sending end converter station i are respectively accessed at the moment t; p is a radical ofi(t) the output of the thermal power generating unit connected to the node i at the moment t;
Figure BDA0001193319250000056
generating power of the pumped storage power station in a time period t;
Figure BDA0001193319250000057
pumping water power of the pumping power station in a time period t; i isRN(ii) a A node set of a transmitting end converter station for accessing new energy in a direct current power grid; i isTH: accessing a direct-current power grid node set of the thermal power generating unit; i isCX: a node set of a pumped storage power station is accessed into a direct current power grid; j. the design is a squarei: representing a set of all neighboring nodes connected to node i;
Figure BDA0001193319250000058
represents the total power flowing into node i from other neighboring nodes;
Figure BDA0001193319250000059
represents the total power flowing out from node i to other neighboring nodes;
4) and load balance constraint of the receiving end converter station:
Figure BDA00011933192500000510
in the formula (I), the compound is shown in the specification,
Figure BDA00011933192500000511
is the power of the network; di(t) a receiving end load for a period of t; i isoutIs a collection of receiving end converter stations in a direct current network system.
Further, the operation optimization model is substituted into the commercial optimization solving package CPLEX, and the maximum receiving capacity of the new energy in the dispatching time period and the optimal power generation operation mode of the new energy, the conventional thermal power generating unit and the pumped storage power station are obtained.
A new energy power generation operation optimization device in a multi-terminal flexible direct current power grid, the device comprising:
the modeling unit is used for establishing a new energy power generation mode operation optimization model according to the pre-acquired topological structure information of the multi-terminal flexible direct-current power grid;
and the solving unit is used for obtaining the optimal power generation mode according to the operation optimization model solved by the commercial optimization solving package.
Further, the modeling unit includes:
the system comprises an information acquisition unit, a storage unit and a management unit, wherein the information acquisition unit is used for acquiring node position information of a transmitting end converter station connected with a new energy, a thermal power generating unit and a pumped storage power station and node position information of a receiving end converter station connected with a load; acquiring a predicted output value and a load predicted value of new energy in a scheduling period, an initial state of a conventional unit, an initial water storage amount of a reservoir on a pumped storage power station and the maximum current conversion capacity, the line length and the line loss rate of a direct-current power grid current conversion station in a scheduling starting period;
and the constraint module is used for formulating new energy output constraint, thermal power unit operation constraint, pumped storage power station operation constraint, transmission line constraint, transmitting end conversion and receiving end conversion station conversion constraint.
Compared with the closest prior art, the technical scheme provided by the invention has the following excellent effects:
1. the technical scheme provided by the invention is based on a network flow optimization principle, and the line loss penalty term is introduced into the objective function, so that the condition that the power flow circularly flows in the flexible direct-current power grid with the annular structure is effectively avoided, unnecessary integer variables are prevented from being introduced to judge the flow direction of the power flow on a line, and the solving difficulty of an optimization model is further reduced.
2. According to the technical scheme provided by the invention, the optimization model performs equivalent linearization treatment on nonlinear operation constraint in a physical system by introducing 0-1 integer variable, so that the solving difficulty of the optimization model is greatly reduced.
3. According to the technical scheme, the operation limits of new energy power generation, a multi-terminal flexible direct current network system, a conventional thermal power generating unit and a pumped storage power station are considered in the optimization model, and the maximum receiving capacity of the new energy and the corresponding new energy in the scheduling period, and the optimal power generation operation mode of the conventional thermal power generating unit and the pumped storage power station are obtained by solving the optimization model.
4. The technical scheme provided by the invention can meet the requirement of system optimization scheduling, optimizes the new energy power generation operation mode in the multi-end flexible direct-current power grid by performing mixed modeling on the new energy power generation and the multi-end flexible direct-current power grid, fully utilizes the flexible power flow control capability of the multi-end flexible direct-current power grid, plays the adjusting role of a conventional unit and a pumped storage power station, realizes the maximum consumption of new energy, and provides guidance for the scheduling operation of the power grid.
Drawings
FIG. 1 is a schematic diagram of a transmission line provided by the present invention;
FIG. 2 is a schematic diagram of a sending end converter station provided by the present invention;
fig. 3 is a schematic diagram of a receiving end converter station provided by the present invention.
Detailed Description
The technical solution provided by the present invention will be described in detail by way of specific embodiments in conjunction with the accompanying drawings of the specification.
The invention provides a new energy power generation operation optimization method in a multi-terminal flexible direct current power grid, wherein 0-1 integer variable is introduced into a model and used for linearizing nonlinear physical limiting factors in an operation optimization model, and a penalty term of line loss is added into a target function to avoid power flow from circularly flowing in the multi-terminal flexible direct current power grid with an annular structure, so that the optimization model is quickly and effectively solved; the optimization model provided by the invention is also suitable for a multi-end flexible direct-current power grid of a non-ring network structure.
The optimization method of the hybrid power generation mode provided by the invention specifically comprises the following steps:
1. reading a topological structure of a current multi-terminal flexible direct-current power grid;
determining new energy, node position information of a transmitting end converter station connected with a thermal power generating unit and a pumped storage power station and node position information of a receiving end converter station connected with a load;
reading a predicted output value and a load predicted value of the new energy in a scheduling time period, an initial state of a conventional unit in a scheduling starting time period, an initial water storage amount of a reservoir on a pumped storage power station, and the maximum current conversion capacity, the line length and the line loss rate of a direct-current power grid current conversion station;
2. establishing a new energy power generation operation optimization model in the multi-terminal flexible direct-current power grid;
the optimization target of the model is that the difference between the new energy generating capacity and the line loss penalty term of the multi-terminal flexible direct current system in the whole scheduling period is maximum:
Figure BDA0001193319250000071
in the formula (I), the compound is shown in the specification,
Figure BDA0001193319250000072
representing the total power generation amount of the new energy accessed to the flexible direct-current power grid; t: is the number of time periods considered; i isRN(ii) a A node set of a transmitting end converter station for accessing new energy in a multi-end flexible direct current power grid;
Figure BDA0001193319250000073
and
Figure BDA0001193319250000074
wind power and photovoltaic power generation output power of a sending end converter station i are respectively accessed at the moment t;
Figure BDA0001193319250000076
Figure BDA0001193319250000077
: a penalty item of the total loss of the line; a: a penalty factor; epsiloni,j(t): on line (i, j) at time tLoss of power; epsilonj,i(t): loss of power on line (j, i) at time t; i is a node set in the direct current power grid: j. the design is a squarei: and all nodes connected with the node i are collected.
Through the objective function, the maximum new energy acceptance of the multi-end flexible direct-current power grid in the whole scheduling period can be realized, and meanwhile, the loss of the lines in the power grid can be reduced to the maximum extent through the line loss penalty term, so that the situation that the tide circularly flows in the flexible direct-current power grid with the annular structure is avoided.
The constraints of the optimization model include: the method comprises the following steps of new energy output constraint, thermal power generating unit operation constraint, pumped storage power station operation constraint, transmission line constraint, transmitting end and receiving end converter station conversion capacity constraint, transmitting end converter station power balance constraint and receiving end converter station load balance constraint. The specific form is as follows:
1) the new energy output constraint is shown as follows:
Figure BDA0001193319250000075
in the formula, Pi W(t) and Pi V(t): the maximum output of wind power and photovoltaic power generation at the moment t is respectively.
2) The thermal power generating unit operation constraint is as follows:
the thermal power unit operation constraint comprises unit output constraint, climbing constraint, minimum startup and shutdown time constraint and startup and shutdown state constraint, and specifically comprises the following steps:
(2-1) Unit output constraint
Xi(t)·Pi min≤pi(t)≤Xi(t)·Pi max,i∈ITH
In the formula ITHA multi-end flexible direct-current power grid node set accessed to a thermal power generating unit; p is a radical ofi(t) the output of the thermal power generating unit connected to the node i at the moment t; pi minAnd Pi maxThe minimum and maximum technical output of the thermal power generating unit is obtained; xi(t) is an integer variable from 0 to 1 and represents the operating state of the thermal power generating unit at the moment t1 means the unit is running and 0 means no running.
(2-2) climbing restraint
Figure BDA0001193319250000081
In the formula (I), the compound is shown in the specification,
Figure BDA0001193319250000082
and
Figure BDA0001193319250000083
respectively representing the maximum climbing and descending power of the unit.
(2-3) minimum Start-stop time constraint
Figure BDA0001193319250000084
In the formula, Yi(t) and ZiAnd (t) is the starting state and the stopping state of the unit in the period t, and both are integer variables of 0-1. For Yi(t) ═ 0 indicates no start-up, Yi(t) ═ 1 indicates that startup is in progress; zi(t) ═ 0 indicates that the engine is not in a stopped state, Zi(t) ═ 1 indicates that shutdown is underway; k is a radical ofiRepresenting a minimum start-up time or a minimum shut-down time of the unit.
(2-4) Start-stop State constraint
Figure BDA0001193319250000085
The above set of equality and inequality jointly form the logic constraint for the start-stop and running states of the unit, so as to ensure that each state variable of the unit is in accordance with the logic.
3) Pumped storage power station operation constraints
Operational constraints of pumped storage power stations include: the system comprises a power generation power constraint, a pumping power constraint, an operation state constraint and a storage capacity constraint. The method comprises the following specific steps:
(3-1) generated Power constraint
Figure BDA0001193319250000086
In the formula ICXFor a node set which is connected to a pumped storage power station in a multi-terminal flexible direct current power grid,
Figure BDA0001193319250000087
in order to pump the generated power of the power station during the time period t,
Figure BDA0001193319250000088
and
Figure BDA0001193319250000089
for minimum and maximum generated power in pumped storage plants, SXi(t) is an integer variable of 0-1, representing the operating state of the pumped storage power station, SXi(t) '1' indicates that the extraction and storage power station is in a power generation state, and SXiAnd (t) — (0) indicates that the extraction power station is not generating power.
(3-2) Water Pumping Power constraint
Figure BDA0001193319250000091
In the formula (I), the compound is shown in the specification,
Figure BDA0001193319250000092
for pumping the water power of the power station in the time period t,
Figure BDA0001193319250000093
and
Figure BDA0001193319250000094
for minimum and maximum pumping power, SY, of a pumped storage power stationi(t) is an integer variable from 0 to 1, representing the operating state of the station, SYi(t) < 1 > indicates that the pumping station is in a pumping state, SYiAnd (t) ═ 0 represents that the pumping power station does not pump water.
(3-3) operating State constraint
0≤SXi(t)+SYi(t)≤1,i∈ICX
This constraint indicates that the pumped storage power station can only be in one state of pumping water or generating electricity at most.
(3-4) storage capacity constraint
Figure BDA0001193319250000095
In the formula, Wi 0(t): the initial water storage capacity of a reservoir on the pumping power station in a time period t; wi end(t): the water storage capacity of an upper reservoir of the pumped storage power station at the end of the t period; wi end(t-1): representing the water storage capacity of a reservoir on the pumped storage power station at the end of the t-1 period; wi InitialInitial water storage of the upper reservoir of the station during a first period ηGAnd ηS: the average water quantity/electric quantity conversion coefficients of the pumped storage power station during power generation and water pumping are respectively.
4) Transmission line restraint
The structure schematic diagram of the transmission line is shown in the attached figure 1, and the transmission line constraint specifically comprises a line loss constraint and a transmission safety constraint:
(4-1) line loss constraint
Figure BDA0001193319250000096
In the formula (I), the compound is shown in the specification,
Figure BDA0001193319250000097
is the power on line (i, j) flowing from node i;
Figure BDA0001193319250000098
power flowing on line (i, j) into node j; epsiloni,j(t) line loss power on line (i, j) αi,jIs the line loss rate of line (i, j); l isi,j: the transmission distance of the line (i, j);
Figure BDA0001193319250000099
is the power on line (j, i) flowing from node j;
Figure BDA00011933192500000910
power flowing on line (j, i) to node i; epsilonj,i(t) line loss power on line (j, i) αj,iIs the line loss rate of the line (j, i); l isj,i: the transmission distance of the line (j, i);
(4-2) Transmission safety constraint
Figure BDA00011933192500000911
In the formula (I), the compound is shown in the specification,
Figure BDA0001193319250000101
is the maximum work transmitted on line (i, j);
Figure BDA0001193319250000102
is the maximum transmission power on the line (j, i).
As shown in FIG. 1, the lines (i, j) and (j, i) belong essentially to the same physical line, i.e., there is a line between node i and node j
Figure BDA0001193319250000103
And
Figure BDA0001193319250000104
two groups of power flow variables with opposite flow directions can automatically change one group of power flow variables in the optimal solution into 0 according to the network flow optimization principle due to the fact that a penalty item of line loss exists in the optimization target, and therefore an integer variable does not need to be introduced to force one group of power flow to be 0.
5) Transmit end converter station converter capacity constraints
A schematic diagram of a sending end converter station is shown in fig. 2. For the sending end converter station, the network access power should not be larger than the maximum converter capacity, that is:
Figure BDA0001193319250000105
in the formula, Pi binIs the maximum commutation capacity of the sending end converter station.
6) Current conversion capacity constraint of receiving end current conversion station
A schematic diagram of the receiving end converter station is shown in fig. 3. For the receiving end converter station, the down-grid power should not be larger than the maximum conversion capacity thereof, namely:
Figure BDA0001193319250000106
in the formula, Pi boutFor the maximum conversion capacity of the receiving end converter station,
Figure BDA0001193319250000107
for power off-line, IoutIs a set of receiving end converter stations in a multi-end flexible direct current grid system.
7) Transmit end converter station power balance constraints
Figure BDA0001193319250000108
8) Load balancing constraint of receiving end converter station
Figure BDA0001193319250000109
In the formula, Di(t) is the terminating load for the period t.
The above formulas form a new energy and multi-end flexible direct current power grid hybrid power generation operation mode optimization model, and the optimization variables in the mathematical model are as follows:
Figure BDA00011933192500001010
εi,j(t)、pi(t)、Xi(t)、Yi(t)、Zi(t)、
Figure BDA00011933192500001011
SXi(t)、
Figure BDA00011933192500001012
SYi(t)、
Figure BDA00011933192500001013
and
Figure BDA00011933192500001014
3. and solving the optimization model by adopting a commercial optimization solution packet based on the boundary condition information to obtain the maximum admission capacity of the new energy in the scheduling period and the corresponding new energy, and the optimal power generation operation mode of the conventional thermal power generating unit and the pumped storage power station.
The optimization model is a typical mixed integer linear programming model, can be directly solved by utilizing a commercial optimization package, and can obtain the optimal power generation operation mode of new energy, a conventional unit and a pumped storage power station and the maximum power generation amount of the new energy in a scheduling period by solving the model.
A new energy power generation operation optimization device in a multi-terminal flexible direct current power grid, the device comprising:
the modeling unit is used for establishing a new energy power generation mode operation optimization model according to the pre-collected topological structure information of the direct current power grid;
and the solving unit is used for obtaining the optimal power generation mode according to the operation optimization model solved by the commercial optimization solving package.
Further, the modeling unit includes:
the system comprises an information acquisition unit, a storage unit and a management unit, wherein the information acquisition unit is used for acquiring node position information of a transmitting end converter station connected with a new energy, a thermal power generating unit and a pumped storage power station and node position information of a receiving end converter station connected with a load; acquiring a predicted output value and a load predicted value of new energy in a scheduling period, an initial state of a conventional unit, an initial water storage amount of a reservoir on a pumped storage power station in a scheduling starting period, and the maximum current conversion capacity, the line length and the line loss rate of a current conversion station of a direct-current power grid;
and the constraint module is used for formulating new energy output constraint, thermal power unit operation constraint, pumped storage power station operation constraint, transmission line constraint, transmitting end conversion and receiving end conversion station conversion constraint.
Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art can make modifications and equivalents to the embodiments of the present invention without departing from the spirit and scope of the present invention, which is set forth in the claims of the present application.

Claims (11)

1. A new energy power generation operation optimization method in a multi-terminal flexible direct current power grid is characterized by comprising the following steps:
solving an operation optimization model according to a commercial optimization solving package CPLEX to obtain an optimal new energy power generation mode; the operation optimization model is an operation optimization model of a new energy power generation mode established according to the pre-collected topological structure information of the multi-terminal flexible direct current power grid;
the objective function of the running optimization model is as follows:
Figure FDA0002255322400000011
wherein the content of the first and second substances,
Figure FDA0002255322400000012
representing the total power generation amount of the new energy accessed to the flexible direct-current power grid; t: the total number of scheduling time segments; i isRN(ii) a A node set of a transmitting end converter station for accessing new energy in a direct current power grid;
Figure FDA0002255322400000013
and
Figure FDA0002255322400000014
wind power and photovoltaic power generation output power of a node i of the sending end converter station are respectively accessed at the moment t;
Figure FDA0002255322400000015
a penalty item of the total loss of the line; a: a penalty factor; epsiloni,j(t): power loss on line (i, j) at time t; epsilonj,i(t): work on line (j, i) at time tRate loss; i is a node set in the direct current power grid: j. the design is a squarei: and all nodes connected with the node i are collected.
2. The method of claim 1, wherein the topology information of a multi-terminal flexible direct current power grid collected in advance comprises:
the method comprises the following steps that new energy, node position information of a transmitting end converter station connected with a thermal power generating unit and a pumped storage power station and node position information of a receiving end converter station connected with a load are obtained;
the method comprises the steps of predicting a power output value and a load predicted value of new energy in a scheduling period, setting an initial state of a conventional unit in a scheduling starting period, setting an initial water storage amount of a reservoir on a pumped storage power station, and setting the maximum current conversion capacity, the line length and the line loss rate of a direct-current power grid current conversion station.
3. The method of claim 1, wherein the constraints for running the optimization model include:
the method comprises the following steps of new energy output restriction, thermal power generating unit operation restriction, extraction and storage power station operation restriction, transmission line restriction, transmitting end converter station and receiving end converter station conversion restriction.
4. The method of claim 1, wherein the new energy output constraint is represented by:
Figure FDA0002255322400000016
in the formula, Pi W(t) and Pi V(t): the maximum output of wind power and photovoltaic power generation at the moment t is respectively.
5. The method of claim 3, wherein the thermal power unit operating constraints comprise:
<1>unit output restraint: xi(t)·Pi min≤pi(t)≤Xi(t)·Pi max,i∈ITH(3)
In the formula (I), the compound is shown in the specification,ITH: accessing a direct-current power grid node set of the thermal power generating unit; p is a radical ofi(t): the thermal power generating unit accessed by the node i outputs power at the moment t; pi minAnd Pi max: the minimum and maximum technical output of the thermal power generating unit at the node i; xi(t) the operation state of the thermal power generating unit at the moment t is represented as 0 or 1 integer variable, 1 represents that the thermal power generating unit is in operation, and 0 represents that the thermal power generating unit is not in operation;
<2>and (3) climbing restraint:
Figure FDA0002255322400000021
in the formula (I), the compound is shown in the specification,
Figure FDA0002255322400000022
and
Figure FDA0002255322400000023
respectively representing the maximum climbing and descending power of the unit; p is a radical ofi(t + 1): representing the output of the thermal power generating unit accessed to the node i at the moment t + 1;
<3>minimum on-off time constraint:
Figure FDA0002255322400000024
in the formula, Yi(t) and Zi(t) is the starting state and the stopping state of the unit in the time period t, and both are integer variables of 0-1; for Yi(t) ═ 0 indicates no start-up, Yi(t) ═ 1 indicates that startup is in progress; zi(t) ═ 0 indicates that the engine is not in a stopped state, Zi(t) ═ 1 indicates that shutdown is underway; k is a radical ofiRepresenting a minimum start-up time or a minimum shut-down time of the unit;
<4>and (3) starting and stopping state constraint:
Figure FDA0002255322400000026
6. the method of claim 3, wherein the pumped storage power station operating constraints comprise:
1) and (3) generating power constraint:
Figure FDA0002255322400000028
in the formula ICX: a node set of a pumped storage power station is accessed into a direct current power grid;
Figure FDA0002255322400000029
the generated power of the pumped storage power station in a time period t;
Figure FDA00022553224000000210
and
Figure FDA00022553224000000211
respectively the minimum and maximum generating power of the pumped storage power station; SXi(t) is an integer variable of 0-1, representing the operating state of the pumped storage power station, SXi(t) '1' indicates that the extraction and storage power station is in a power generation state, and SXi(t) ═ 0 indicates that the extraction power station is not generating power;
2) and (3) water pumping power constraint:
Figure FDA0002255322400000031
in the formula (I), the compound is shown in the specification,
Figure FDA0002255322400000032
pumping power of the pumping power station in a time period t;
Figure FDA0002255322400000033
and
Figure FDA0002255322400000034
respectively the minimum and maximum pumping power of the pumping power station; SY (simple and easy) to usei(t) is an integer variable from 0 to 1, representing the operating state of the station, SYi(t) < 1 > indicates that the pumping station is in a pumping state, SYi(t) ═ 0 indicates that the extraction power station is not extracting water;
3) and (4) constraint of the running state:0≤SXi(t)+SYi(t)≤1,i∈ICX(9)；
4) and (4) library capacity constraint:
Figure FDA0002255322400000035
in the formula, Wi 0(t): the initial water storage capacity of a reservoir on the pumping power station in a time period t; wi end(t): the water storage capacity of an upper reservoir of the pumped storage power station at the end of the t period; wi end(t-1): representing the water storage capacity of a reservoir on the pumped storage power station at the end of the t-1 period; wi InitialInitial water storage of the upper reservoir of the station during a first period ηGAnd ηS: the average water quantity/electric quantity conversion coefficients of the pumped storage power station during power generation and water pumping are respectively.
7. The method of claim 3, wherein the transmission line constraints comprise:
1>and line loss constraint:
Figure FDA0002255322400000036
in the formula (I), the compound is shown in the specification,
Figure FDA0002255322400000037
is the power on line (i, j) flowing from node i;
Figure FDA0002255322400000038
power flowing on line (i, j) into node j; epsiloni,j(t) line loss power on line (i, j) αi,jIs the line loss rate of line (i, j); l isi,j: the transmission distance of the line (i, j);
Figure FDA0002255322400000039
is the power on line (j, i) flowing from node j;
Figure FDA00022553224000000310
is a circuit (j, i) power flowing on node i; epsilonj,i(t) line loss power on line (j, i) αj,iIs the line loss rate of the line (j, i); l isj,i: the transmission distance of the line (j, i);
2>and transmission safety constraint:
Figure FDA0002255322400000041
in the formula (I), the compound is shown in the specification,
Figure FDA0002255322400000042
is the maximum transmission power on line (i, j);
Figure FDA0002255322400000043
is the maximum transmission power on the line (j, i).
8. The method according to claim 3, wherein the constraining of the sending end converter station and the receiving end converter station comprises:
1) and (3) limiting the current conversion capacity of the sending end converter station:
Figure FDA0002255322400000044
in the formula, Pi binThe maximum current conversion capacity of the sending end current conversion station;
2) and (3) the current conversion capacity of the receiving end current conversion station is restricted:
Figure FDA0002255322400000045
in the formula, Pi boutFor the maximum conversion capacity of the receiving end converter station,
Figure FDA0002255322400000046
for power off-line, IoutThe method comprises the steps of collecting receiving end converter stations in a direct current network system;
3) and (3) power balance constraint of the sending end converter station:
Figure FDA0002255322400000047
in the formula (I), the compound is shown in the specification,
Figure FDA0002255322400000048
and
Figure FDA0002255322400000049
wind power and photovoltaic power generation output power of a sending end converter station i are respectively accessed at the moment t; p is a radical ofi(t) the output of the thermal power generating unit connected to the node i at the moment t;
Figure FDA00022553224000000410
generating power of the pumped storage power station in a time period t;
Figure FDA00022553224000000411
pumping water power of the pumping power station in a time period t; i isRN(ii) a A node set of a transmitting end converter station for accessing new energy in a direct current power grid; i isTH: accessing a direct-current power grid node set of the thermal power generating unit; i isCX: a node set of a pumped storage power station is accessed into a direct current power grid; j. the design is a squarei: representing a set of all neighboring nodes connected to node i;
Figure FDA00022553224000000412
represents the total power flowing into node i from other neighboring nodes;
Figure FDA00022553224000000413
is the total power flowing out from node i to other neighboring nodes;
4) and load balance constraint of the receiving end converter station:
Figure FDA0002255322400000051
(16)
in the formula (I), the compound is shown in the specification,
Figure FDA0002255322400000052
is the power of the network; di(t) is a period of tReceiving end load; i isoutIs a collection of receiving end converter stations in a direct current network system.
9. The method as claimed in claim 1, wherein the operation optimization model is substituted into a commercial optimization package CPLEX for solving, and the maximum receiving capacity of the new energy in the dispatching period and the optimal power generation operation mode of the new energy, the conventional thermal power generating unit and the pumped storage power station are obtained.
10. An apparatus for optimizing new energy generation operation in a multi-terminal flexible dc grid according to the method of claim 1, wherein the apparatus comprises:
the modeling unit is used for establishing a new energy power generation mode operation optimization model according to the pre-acquired topological structure information of the multi-terminal flexible direct-current power grid;
and the solving unit is used for obtaining the optimal power generation mode according to the operation optimization model solved by the commercial optimization solving package CPLEX.
11. The apparatus of claim 10, wherein the modeling unit comprises:
the system comprises an information acquisition unit, a storage unit and a management unit, wherein the information acquisition unit is used for acquiring node position information of a transmitting end converter station connected with a new energy, a thermal power generating unit and a pumped storage power station and node position information of a receiving end converter station connected with a load; acquiring a predicted output value and a load predicted value of new energy in a scheduling period, an initial state of a conventional unit, an initial water storage amount of a reservoir on a pumped storage power station in a scheduling starting period, and a maximum current conversion capacity, a line length and a line loss rate of a current conversion station of a direct-current power grid;
and the constraint unit is used for formulating the logic constraint of the unit start-stop and running state of the running optimization model, the running constraint of the pumped storage power station, the transmission line constraint, the converter capacity constraint of the transmitting end converter station and the receiving end converter station, the power balance constraint of the transmitting end converter station and the load balance constraint of the receiving end converter station.
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