CN111030088B - Method and device for predicting capacity of power transmission channel for power transmission - Google Patents
Method and device for predicting capacity of power transmission channel for power transmission Download PDFInfo
- Publication number
- CN111030088B CN111030088B CN201911169497.9A CN201911169497A CN111030088B CN 111030088 B CN111030088 B CN 111030088B CN 201911169497 A CN201911169497 A CN 201911169497A CN 111030088 B CN111030088 B CN 111030088B
- Authority
- CN
- China
- Prior art keywords
- power transmission
- transmission channel
- capacity
- power
- statistical
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- 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
- H02J3/008—Circuit arrangements for ac mains or ac distribution networks involving trading of energy or energy transmission rights
-
- 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
-
- 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
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
Landscapes
- Engineering & Computer Science (AREA)
- Power Engineering (AREA)
- Supply And Distribution Of Alternating Current (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses a method and a device for predicting capacity of a power transmission channel for power transmission. And then establishing a power transmission channel capacity optimization model, minimizing the estimated capacity reduction value of the channel as an optimization target by reducing the power transmission capacity of the power transmission channel after the power transmission channel is overhauled, and optimizing and calculating to obtain the final power transmission channel capacity requirement by considering constraint conditions such as continuous overhaul time of equipment, influence of equipment overhaul on the power transmission channel capacity and the like. The method can predict and optimize the power transmission channel capacity, can reduce the phenomena of wind abandoning, light abandoning and water abandoning in the trans-regional new energy transaction, and promotes the consumption of renewable energy.
Description
Technical Field
The invention relates to a capacity prediction method of a power system, in particular to a capacity prediction method and a capacity prediction device of a power transmission channel considering medium-term and long-term power transaction.
Background
In order to solve the problems of wind abandonment, light abandonment and water abandonment of an energy base, a plurality of extra-high voltage direct current transmission channels are established in China, rich power of the energy base is transmitted to a load center, and a policy is issued to promote cross-regional power trading. In a non-market mode, the trans-regional power trading is performed by setting annual contract electric quantity every year to form a medium-long term contract, and then a dispatching mechanism ensures that the annual electric quantity is effectively executed. However, after a new round of power market reform, national grid companies respond to the strategic objective of further promoting the consumption of abundant renewable energy in energy output areas by the nation, and lead to the design of a cross-regional new energy trading mechanism, and establish trading systems in each grid province company to extend cross-regional power trading from the middle to the day ahead and in the day.
As a carrier of trans-regional power transmission, under a non-market mode, estimation of the capacity of a power transmission channel is relatively simple, only medium-term and long-term trading electric quantity needs to be reliably executed, and the method is generally simply decomposed according to annual contract electric quantity and a power load curve. However, after the short-term trans-regional new energy trading market is started, the power transmission channel not only needs to ensure reliable execution of medium and long-term trading electric quantity, but also needs to ensure that sufficient margins are reserved in wind power, photovoltaic and hydropower heavy-rise seasons, so that short-term trans-regional new energy trading is promoted, new energy is consumed to the maximum extent, and wind, light and water abandonment are reduced. In addition, in order to ensure safe and reliable operation of a power grid, power transmission channel equipment needs to be periodically overhauled, and equipment overhaul can cause the capacity of a power transmission channel to be reduced, and the maximum electric quantity of short-term transaction can be influenced.
Disclosure of Invention
The purpose of the invention is as follows: aiming at the problems, the invention provides a method and a device for predicting the capacity of a power transmission channel for power transmission, which are used for predicting the capacity of the power transmission channel on a medium-long time scale, comprehensively considering medium-long term power transaction, power output fluctuation of wind power, photovoltaic power and the like, and the influence of regular maintenance of power transmission equipment on the power transmission capacity, and improving the accuracy of the prediction of the capacity of the power transmission channel.
The technical scheme is as follows: the technical scheme adopted by the invention is a method for predicting the capacity of a power transmission channel for power transmission, which comprises the following steps:
(1) Respectively aiming at the units with different energy types, dividing annual statistical time into a plurality of statistical periods with medium and long time scales, and predicting the original power transmission channel capacity demand according to the historical measured data of the units with different energy types; wherein, the units of different energy types include wind power, photovoltaic, water and electricity, thermal power unit. Predicting an original power transmission channel capacity demand, comprising the following processes:
(11) And calculating the generated energy of each unit i in the statistical period z, wherein the calculation formula is as follows:
in the formula (I), the compound is shown in the specification,
is the total power generation amount T of the unit i in the statistical period z z Is the total number of time segments of the counting cycle z, t is the counting time,
generating active power output for the historical actual measurement of the new energy unit i at the moment t;
(12) The generating load rate of the computer set is as follows:
in the formula, A i，z Load rate, C, of unit i in statistical period z i The rated installed capacity of the unit;
(13) The average power generation load rate of the unit for years is counted, and the calculation formula is as follows:
in the formula (I), the compound is shown in the specification,
the average generating load rate of the unit i in a statistical period z for years, Y is the statistical number of years, A i，z，y Calculating the historical power generation load rate of the unit i in the statistical period z of the statistical year y through the step (12);
(14) And (3) calculating the predicted power generation amount of the statistical period z of the unit i, wherein the calculation formula is as follows:
in the formula, F z In order to calculate the predicted total power generation amount of the period z, N is the number of the units;
(15) Decomposing the predicted power generation amount of the unit i prediction cycle z into each time interval, wherein the calculation formula is as follows:
(16) Repeating the steps (11) to (15), sequentially calculating the predicted power generation amount of each statistical period, and calculating the original power transmission channel capacity requirement R t ：
In the formula, N represents the set of all units, NW, NP, NH and NF are dividedRespectively showing the collection of wind power, photovoltaic, hydroelectric and thermal power units, L t The electric load at time t.
(2) And (4) considering the maintenance requirements of the power transmission equipment, establishing a power transmission channel capacity demand optimization model, and solving the model to obtain the corrected power transmission channel capacity demand.
The power transmission channel capacity demand optimization model comprises the following steps:
u j，t -u j，t-1 ＝y j，t -z j，t
y j，t +z j，t ≤1
wherein T is the total number of the optimization time periods, and T is a time period subscript; m is the number of power transmission equipment forming a power transmission channel, and j is a subscript of the power transmission equipment;
the maximum transmission capacity is the transmission channel; r t The power transmission capacity required by power transmission channel to meet power transmission is calculated in the step 1; d j，t The influence value of the transmission equipment j on the transmission capacity of the transmission channel due to overhaul in the time period t is shown; k is a radical of t A decision variable of 0/1 is adopted, which indicates that at the moment t, the capacity of the power transmission channel cannot meet the requirement due to the fact that whether equipment maintenance can be carried out or not; u. of j，t Is a 0/1 decision variable and represents the state that the power transmission equipment j is operated or overhauled in the time period tState; y is j，t A decision variable of 0/1 represents the maintenance starting state of the equipment; z is a radical of formula j，t A decision variable of 0/1 represents the overhaul finish state of the equipment;
minimal time is required to service equipment j.
Based on the method, the invention provides a power delivery and transmission channel capacity prediction device, which comprises a processor and a memory, wherein the memory stores a computer executable program, and the processor executes the calculation steps in the power delivery and transmission channel capacity prediction method.
Has the advantages that: when the capacity requirements of the medium and long-term time scale power transmission channel are evaluated, the medium and long-term power transaction, the uncertainty of output of wind power, photovoltaic power and electricity and the like and the influence of regular maintenance of power transmission equipment on the power transmission capacity of the channel are comprehensively considered, the power transmission channel capacity can be predicted and optimized, the phenomena of wind abandoning, light abandoning and water abandoning can be reduced in the trans-regional new energy transaction, and the renewable energy consumption is promoted.
Drawings
Fig. 1 is a schematic diagram of an interconnected power grid.
Detailed Description
The technical solution of the present invention is further described below with reference to the accompanying drawings and examples.
The invention relates to a method for predicting the capacity of a power transmission channel for transmitting power outwards, which comprises the following steps: and (1) predicting the capacity of the transmission channel. The medium and long time scales are divided, seasonal factors, meteorological factors, raw material supply and the like are considered, and different statistical periods are formed for different energy type units. And then, counting the generated energy, the load rate and the like of the units of different energy types in different counting periods by utilizing the historical measured data of the units in the dispatching technical support system, predicting the generated energy, decomposing the generated energy to generate a generated power curve, and calculating by combining medium-and-long-term loads and medium-and-long-term trading contracts to obtain the original capacity requirement of the power transmission channel. (2) And establishing a power transmission channel capacity demand optimization model, considering the maintenance requirements of power transmission equipment, and calculating to obtain the final power transmission channel capacity demand.
(1) The capacity of the power transmission channel is predicted, and the specific process is as follows:
statistical period and calculation period partitioning
The main types of generating sets in China include thermal power, hydroelectric power, nuclear power, wind power, photovoltaic power and the like, in regions with relatively concentrated energy sources in the west and north, the main types include hydroelectric power, thermal power, wind power and photovoltaic power, the generating capacity of the generating sets of the types is influenced by primary energy supply, and obvious seasonal characteristics are presented if the hydroelectric power has a dry season and a rich season every year, the wind power is influenced by monsoon, and the photovoltaic generating capacity is influenced by illumination. The method is influenced by uncertain factors such as wind speed, sunlight, reservoir incoming water and the like, the accuracy of the power prediction of renewable energy sources such as wind, light and water is generally low, the predicted output and the actual power generation have great difference under certain conditions, and great challenges are brought to power generation scheduling. It is very difficult to accurately predict the short-term power generation output curves of wind power and photovoltaic power, but if the time scale is enlarged to the middle and long term (the middle and long term usually means more than 360 hours) to predict the power generation amount of the wind power, photovoltaic month and year, the average illumination days and the windy days of different months of different years are basically consistent, and the average effect of long-term accumulation effect is considered, the power generation amount of the wind power, photovoltaic power and hydropower in a certain time period can be accurately predicted. Therefore, when the statistical period is divided, the factors are considered, and different statistical periods are divided for thermal power, hydropower, wind power and photovoltaic units.
For example, assuming that a year is divided by natural months to form 12 statistical cycles, Z =12. Further, the whole year needs to be subdivided into a plurality of periods, and if the time interval of the periods is 1 hour, a total of 8760 periods per year. According to the division of the statistical cycles, each statistical cycle comprises a plurality of time intervals, and T is set z The time interval of the z-th statistical cycle is represented, and the 1 st statistical cycle time interval divided into 12 statistical cycles is divided into 1 ＝T 2 ＝…＝730。
Power transmission channel capacity prediction
(11) And (4) calculating the generated energy of each unit in the statistical period z according to the statistical period and the calculation time period divided in the step 1.
The generating capacity calculation formula of the unit is as follows:
in the formula (I), the compound is shown in the specification,
is the total power generation amount T of the unit i in the statistical period z z Is the total period number of the statistical period z, t is the statistical time,
and generating active power output for the historical actual measurement of the new energy unit i at the moment t.
(12) And calculating the generating load rate of the unit by using the rated capacity of the unit as follows:
in the formula, A i，z Load rate, C, of unit i in statistical period z i The rated installed capacity of the unit.
(13) The average generating load rate of the multi-year unit is calculated by utilizing the historical measured data of a plurality of years, and the calculation formula is as follows:
in the formula (I), the compound is shown in the specification,
the average generating load rate of the unit i in a statistical period z for years, Y is the statistical number of years, A i，z，y And calculating the historical power generation load rate of the unit i in the statistical period z of the statistical year y through a formula (2).
(14) Calculating the predicted generating capacity of the statistical period z of the unit i by using the historical average generating load rate and the rated capacity of the unit, wherein the calculation formula is as follows:
in the formula, F z And N is the number of the units for calculating the predicted total power generation amount of the period z.
(15) Decomposing the predicted power generation amount of the unit i prediction cycle z into each time interval, wherein the calculation formula is as follows:
(16) And (4) according to different statistical periods divided by different unit types, repeating the formulas (1) to (5), and predicting a power generation output curve, wherein the power generation output curve is the power generation amount of all the units corresponding to different moments t. The transmission channel capacity requirement is calculated using equation (6).
In the formula, N represents a set of all the units.
(2) Power transmission channel capacity optimization
In order to ensure the reliable and stable operation of the power transmission channel, the power transmission channel needs to be overhauled regularly, the general overhaul period is one year, annual overhaul is divided into major overhaul and minor overhaul according to the operation time of channel equipment, and the overhaul time of different overhaul types is different. In order to avoid the major influence of the overhaul time period on the power transmission capacity of the power transmission channel as much as possible, reduce the abandoned wind and abandoned light and promote the new energy consumption, the overhaul time window of the power transmission channel equipment needs to be optimized, and the power transmission channel is enabled to transmit power to the maximum extent while the overhaul time of all the equipment is met.
In order to achieve the purpose, a power transmission channel capacity optimization model based on power transmission channel capacity prediction, power transmission channel equipment maintenance time and the influence of the power transmission equipment on the power transmission capacity is established, and maintenance time of a maintenance plan is optimized. After the power transmission channel equipment is overhauled, the power transmission capacity of the model is reduced to minimize the estimated capacity reduction value of the channel as an optimization target, and the expression is
In the above formula, T is the total number of optimized time periods, T is the subscript of the time period, M is the number of power transmission equipment forming the power transmission channel, j is the subscript of the power transmission equipment,
for maximum transmission capacity of the transmission channel, R t The transmission capacity required for power transmission is satisfied for the transmission channel, and is obtained by calculation in step 1, D j，t The influence value k of the transmission equipment j on the transmission capacity of the transmission channel due to the overhaul of the transmission equipment j in the time period t t Is a 0/1 decision variable, which indicates that at the moment t, the capacity of the power transmission channel is smaller than the estimated capacity demand due to equipment overhaul or not, k t =1 denotes that the transmission channel capacity does not meet the requirement, k t And =0 represents that the power transmission channel capacity satisfies the requirement.
For any time t, the value of the capacity reduction of the power transmission channel caused by the overhaul of all the power transmission equipment meets the following constraint condition:
in the formula u j，t Is a 0/1 decision variable which represents the state that the power transmission equipment j is operated or overhauled in the time period t when u j，t =1, indicating that the power transmission equipment j overhauls during the time period t, when u j，t And =0, which indicates a time period t for maintenance of the power transmission equipment j.
Introducing 0/1 decision variable y j，t A decision variable z of 0/1 representing the maintenance starting state of the equipment j，t Indicates the maintenance completion state of the equipment, u j，t 、Y j，t 、z j，t These 3 variables satisfy the following relationship:
u j，t -u j，t-1 ＝y j，t -z j，t (10)
furthermore, at the same time, the equipment cannot start and end maintenance at the same time, variable y j，t 、z j，t The following constraints are satisfied.
y j，t +z j，t ≤1 (11)
When each transmission equipment is overhauled, the maximum influence value of each transmission equipment on the capacity of a transmission channel is determined by a power grid structure, power flow transfer and the like, and can be obtained in advance through operation mode analysis, power flow sensitivity analysis and the like. Therefore, the influence of the equipment on the power transmission capacity should satisfy the following constraint conditions.
In the formula (I), the compound is shown in the specification,
the maximum influence value on the power transmission capacity of the power transmission channel after the maintenance of the power transmission equipment j is obtained.
The maintenance of each device needs a period of continuous time to ensure the maintenance to be finished smoothly, so that the continuous maintenance time of each device is at least greater than the requirement of minimum maintenance time.
In the formula (I), the compound is shown in the specification,
minimal time is required to service equipment j.
And the optimization targets and the constraint conditions form a mixed integer programming model, and the maintenance states of all the power transmission equipment are calculated by using commercial solving software.
And re-correcting the estimated transmission channel capacity requirement by utilizing the equipment maintenance state calculated by the optimization model to obtain the requirement for meeting the final transmission channel capacity. The calculation formula is as follows:
in the formula, r t Is the corrected transmission channel capacity requirement.
Considering different power generation types including different units of wind power, photovoltaic, hydroelectric power and thermal power, dividing statistical periods according to different types of the units of the wind power, the photovoltaic, the hydroelectric power and the thermal power, and setting the statistical periods of the different types of the units to be Z respectively W 、Z P 、Z H 、Z F . Subdividing the year into a plurality of segments, if the time interval of the segments is 1 hour, then 8760 segments in total per year, then the range of the segment t is t e [1, 8760 ]]. Each statistical cycle of each unit type comprises a plurality of time intervals, and the number of the time intervals contained in the z-th statistical cycle is set as T z Then, there are:
wherein, period z For the z-th statistical cycle containing a set of time Periods, periods is a set of all time Periods.
The sum of the number of time segments contained in all statistical cycles is 8760.
In the formula, T z The number of periods included in the period z is counted.
According to the formulas (1) to (5), calculating the statistical periods 1 to Z in sequence W And the predicted output of each wind turbine generator unit obtains the active power of each wind turbine generator unit in all time periods:
P i，t i∈NW，t∈Periods (17)
according to the formulas (1) to (5), calculating the statistical periods 1 to Z in sequence P And the predicted output of each photovoltaic unit obtains the active power of each photovoltaic unit in all time periods:
P i，t i∈NP，t∈Periods (18)
according to the formulas (1) to (5), calculating the statistical periods 1 to Z in sequence H And the predicted output of each hydroelectric generating set obtains the active power of each photovoltaic generating set in all time periods:
P i，t i∈NH，t∈Periods (19)
according to the formulas (1) to (5), calculating the statistical periods 1 to Z in sequence F And the predicted output of each thermal power generating unit obtains the active power of each photovoltaic unit in all time periods:
P i，t i∈NF，t∈Periods (20)
estimating transmission channel capacity according to equation (18)
In the formulas (17) to (21), NW, NP, NH, NF represent the set of wind power, photovoltaic, hydroelectric, and thermal power generation units, respectively, and L t The electric load at time t.
The power transmission channel generally consists of a plurality of power transmission devices, which are usually power transmission lines, as shown in fig. 1, a power grid a, a power grid B, and a power grid C are interconnected by a plurality of power transmission lines, wherein the interconnected power transmission lines may be direct current power transmission lines or alternating current power transmission lines. Different power transmission channels which are formed by a plurality of power transmission lines are respectively a power transmission channel TAB of the power grid A and the power grid B, a power transmission channel TAC of the power grid A and the power grid C, and a power transmission channel TBC of the power grid B and the power grid C. For the outgoing power grid or the incoming power grid, physical equipment of the power transmission channel is equivalent during modeling, modeling calculation is only carried out on the power grid, and a detailed model of the power grid on the other side of the power transmission channel is not needed to be known.
The power transmission channel is composed of M devices, and when all the devices operate, the maximum power transmission capacity of the power transmission channel is R max Considering that the transmission capacity at different transmission moments is influenced by factors such as ambient temperature and the like, the transmission capacity at each time interval may be different, and the method is used
Representing the power transmission capacity for time period t. When the component equipment j of the power transmission channel exits the operation, the power transmission capacity of the power transmission channel is reduced, and the value D is reduced j，t And (4) showing. Maximum transmission capacity
And D j，t Determined from the nominal parameters of the transmission channel, are known parameters. The relation between the two can be simply considered, and the maximum power transmission capacity of the power transmission channel is considered
And D j，t The relationship of formula (22) is satisfied.
When the power transmission channel is overhauled, the capacity of the power transmission channel is necessarily reduced, and in order to meet the requirement of pre-estimating the capacity R of the power transmission channel as much as possible t The method reduces the energy waste phenomena of wind abandoning, light abandoning, water abandoning and the like caused by insufficient channel capacity, and constructs the following optimization model for solving:
u j，t -u j，t-1 ＝y j，t -z j，t
y j，t +z j，t ≤1
in the above formula, T is the total number of the optimization time periods, and T is the subscript of the time period; m is the number of power transmission equipment forming a power transmission channel, and j is a subscript of the power transmission equipment;
the maximum power transmission capacity of the power transmission channel; r t The power transmission capacity required by power transmission channel to meet power transmission is calculated in the step 1; d j，t The influence value of the transmission equipment j on the transmission capacity of the transmission channel due to overhaul in the time period t is shown; k is a radical of formula t A decision variable of 0/1 is adopted, which indicates that at the moment t, the capacity of the power transmission channel cannot meet the requirement due to the fact that whether equipment maintenance can be carried out or not; u. of j，t A decision variable of 0/1, which represents the state of the power transmission equipment j during the time period t; y is j，t A decision variable of 0/1 represents the maintenance starting state of the equipment; z is a radical of formula j，t A decision variable of 0/1 represents the overhaul finish state of the equipment;
minimal time is required for servicing equipment j.
Using commercial mathematical softwareSolving the mixed integer programming mathematical model described by the formula (23) to obtain the maintenance or running state u of the power transmission equipment j，t . And (5) correcting the estimated transmission channel capacity requirement by using a formula (14) to obtain the corrected transmission channel capacity requirement.
Based on the method, the device for predicting the capacity of the power transmission channel comprises a processor and a memory, wherein the memory stores a computer executable program, and the processor executes the following steps:
(1) Respectively aiming at the units with different energy types, dividing annual statistical time into a plurality of statistical periods with medium and long time scales, and predicting the original power transmission channel capacity demand according to the historical measured data of the units with different energy types; wherein, the units of different energy types include wind power, photovoltaic, water and electricity, thermal power unit. Predicting an original power transmission channel capacity demand, comprising the following processes:
(11) Calculating the generated energy of each unit i in the statistical period z, wherein the calculation formula is as follows:
in the formula (I), the compound is shown in the specification,
is the total power generation amount T of the unit i in the statistical period z z Is the total number of time segments of the counting cycle z, t is the counting time,
generating active power output for the historical actual measurement of the new energy unit i at the moment t;
(12) The generating load rate of the computer set is as follows:
in the formula, A i，z Load rate, C, of unit i in statistical period z i The rated installed capacity of the unit;
(13) The average generating load rate of the units for years is counted, and the calculation formula is as follows:
in the formula (I), the compound is shown in the specification,
the average generating load rate of the unit i in a statistical period z for years, Y is the statistical number of years, A i，z，y Calculating the historical power generation load rate of the unit i in the statistical period z of the statistical year y through the step (12);
(14) And (3) calculating the predicted power generation amount of the statistical period z of the unit i, wherein the calculation formula is as follows:
in the formula, F z In order to calculate the predicted total power generation amount of the period z, N is the number of the units;
(15) Decomposing the predicted power generation amount of the unit i prediction cycle z into each time interval, wherein the calculation formula is as follows:
(16) Repeating the steps (11) to (15), sequentially calculating the predicted power generation amount of each statistical period, and calculating the original power transmission channel capacity requirement R t ：
In the formula, N represents the set of all units, NW, NP, NH and NF represent the set of wind power, photovoltaic, hydroelectric and thermal power units respectively, and L represents t The electric load at time t.
(2) And (4) considering the maintenance requirements of the power transmission equipment, establishing a power transmission channel capacity demand optimization model, and solving the model to obtain the corrected power transmission channel capacity demand.
The power transmission channel capacity demand optimization model comprises the following steps:
u j，t -u j，t-1 ＝y j，t -z j，t
y j，t +z j，t ≤1
wherein T is the total number of the optimization time periods, and T is a time period subscript; m is the number of power transmission equipment forming a power transmission channel, and j is a subscript of the power transmission equipment;
the maximum transmission capacity is the transmission channel; r is t The power transmission capacity required by power transmission channel to meet power transmission is calculated in the step 1; d j，t The influence value of the transmission equipment j on the transmission capacity of the transmission channel due to overhaul in the time period t is shown; k is a radical of t A decision variable of 0/1 represents that at the moment t, the capacity of a power transmission channel can not meet the requirement due to equipment maintenance or not; u. of j，t A decision variable of 0/1, which represents that the power transmission equipment j is in an operation or maintenance state in a time period t; y is j，t A decision variable of 0/1 represents the maintenance starting state of the equipment; z is a radical of j，t A decision variable of 0/1 represents the overhaul finish state of the equipment;
minimal time is required to service equipment j.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting the same, and although the present invention is described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: modifications and equivalents may be made to the embodiments of the invention without departing from the spirit and scope of the invention, which is to be covered by the claims.
Claims (4)
1. A method for predicting capacity of a power transmission channel for power transmission is characterized by comprising the following steps:
(1) Respectively aiming at the units with different energy types, dividing annual statistical time into a plurality of statistical periods with medium and long time scales, and predicting the original power transmission channel capacity requirement in each statistical period according to the historical measured data of the units with different energy types; the method for predicting the original power transmission channel capacity requirement comprises the following steps:
(11) Calculating the generated energy of each unit i in the statistical period z, wherein the calculation formula is as follows:
in the formula (I), the compound is shown in the specification,
is the total power generation amount T of the unit i in the statistical period z z Is the total number of time segments of the counting cycle z, t is the counting time,
generating active power output for the historical actual measurement of the new energy unit i at the moment t;
(12) The generating load rate of the computer set is as follows:
in the formula, A i，z Load rate, C, of unit i in statistical period z i The rated installed capacity of the unit;
(13) The average generating load rate of the units for years is counted, and the calculation formula is as follows:
in the formula (I), the compound is shown in the specification,
the average generating load rate of the unit i in a statistical period z for years, Y is the statistical number of years, A i，z，y Calculating the historical power generation load rate of the unit i in the statistical period z of the statistical year y through the step (12);
(14) And (3) calculating the predicted power generation amount of the statistical period z of the unit i, wherein the calculation formula is as follows:
in the formula (I), the compound is shown in the specification,
counting the predicted generating capacity of the period z for the unit i;
(15) Decomposing the predicted power generation amount of the prediction period z of the unit i into each time interval to set as P i，t The calculation formula is as follows:
(16) Repeating the steps (11) to (15),sequentially calculating the predicted generating capacity of each statistical period, and calculating the original power transmission channel capacity requirement R t ：
In the formula, N represents the set of all the units, NW, NP, NH and NF represent the sets of wind power, photovoltaic, hydroelectric and thermal power units respectively; l is a radical of an alcohol t Is the electrical load at time t;
(2) The method comprises the steps of calculating the maintenance requirement of the power transmission equipment, establishing a power transmission channel capacity requirement optimization model, and solving the model to obtain a corrected power transmission channel capacity requirement; the power transmission channel capacity demand optimization model is as follows:
u j，t -u j，t-1 ＝y j，t -z j，t
y j，t +z j，t ≤1
wherein T is the total number of the optimization time periods, and T is a time period subscript; m is the number of power transmission equipment forming a power transmission channel, and j is a subscript of the power transmission equipment;
the maximum power transmission capacity of the power transmission channel; r t The power transmission capacity required by power transmission channel to meet power transmission is calculated in the step 1; d j，t The influence value of the transmission equipment j on the transmission capacity of the transmission channel due to overhaul in the time period t is shown; k is a radical of t A decision variable of 0/1 is adopted, which indicates that at the moment t, the capacity of the power transmission channel cannot meet the requirement due to the fact that whether equipment maintenance can be carried out or not; u. of j，t A decision variable of 0/1, which represents that the power transmission equipment j is in an operation or maintenance state in a time period t; y is j，t A decision variable of 0/1 represents the maintenance starting state of the equipment; z is a radical of formula j，t A decision variable of 0/1 represents the overhaul finish state of the equipment;
minimal time is required to service equipment j.
2. The method for predicting the capacity of a power delivery transmission path according to claim 1, characterized in that: the power units with different energy types in the step (1) comprise wind power, photovoltaic, hydroelectric and thermal power units.
3. An apparatus for predicting capacity of a power transmission path for power delivery, comprising a processor and a memory, the memory storing a computer-executable program, the processor executing the steps of:
(1) Respectively aiming at the units with different energy types, dividing annual statistical time into a plurality of statistical periods with medium and long time scales, and predicting the original power transmission channel capacity requirement in each statistical period according to the historical measured data of the units with different energy types; the method for predicting the original power transmission channel capacity requirement comprises the following steps:
(11) Calculating the generated energy of each unit i in the statistical period z, wherein the calculation formula is as follows:
in the formula (I), the compound is shown in the specification,
is the total power generation amount T of the unit i in the statistical period z z Is the total period number of the statistical period z, t is the statistical time,
generating active power output for the historical actual measurement of the new energy unit i at the moment t;
(12) The generating load rate of the computer set is as follows:
in the formula, A i，z Load rate, C, of unit i in statistical period z i The rated installed capacity of the unit;
(13) The average generating load rate of the units for years is counted, and the calculation formula is as follows:
in the formula (I), the compound is shown in the specification,
the average generating load rate of the unit i in a statistical period z for years, Y is the statistical number of years, A i，z，y Calculating the historical power generation load rate of the unit i in the statistical period z of the statistical year y through the step (12);
(14) Calculating the predicted generating capacity of a statistical period z of a unit i, wherein the calculation formula is as follows:
in the formula (I), the compound is shown in the specification,
counting the predicted generating capacity of the period z for the unit i;
(15) Decomposing the predicted power generation amount of the prediction period z of the unit i into each time interval to set as P i，t The calculation formula is as follows:
(16) Repeating the steps (11) to (15), sequentially calculating the predicted power generation amount of each statistical period, and calculating the original power transmission channel capacity requirement R t ：
In the formula, N represents the set of all units, NW, NP, NH and NF represent the sets of wind power, photovoltaic, hydroelectric and thermal power units respectively; l is t Is the electrical load at time t;
(2) The method comprises the steps of calculating the maintenance requirement of the power transmission equipment, establishing a power transmission channel capacity requirement optimization model, and solving the model to obtain a corrected power transmission channel capacity requirement; the power transmission channel capacity demand optimization model is as follows:
u j，t -u j，t-1 ＝y j，t -z j，t
y j，t +z j，t ≤1
wherein T is the total number of the optimization time periods, and T is a time period subscript; m is the number of power transmission equipment forming a power transmission channel, and j is a subscript of the power transmission equipment;
the maximum power transmission capacity of the power transmission channel; r t The power transmission capacity required by power transmission channel to meet power transmission is calculated in the step 1; d j，t The influence value of the transmission equipment j on the transmission capacity of the transmission channel due to overhaul in the time period t is shown; k is a radical of t A decision variable of 0/1 is adopted, which indicates that at the moment t, the capacity of the power transmission channel cannot meet the requirement due to the fact that whether equipment maintenance can be carried out or not; u. of j，t A decision variable of 0/1, which represents the state of the power transmission equipment j during the time period t; y is j，t A decision variable of 0/1 represents the maintenance starting state of the equipment; z is a radical of j，t A decision variable of 0/1 represents the overhaul finish state of the equipment;
minimal time is required to service equipment j.
4. The power delivery transmission channel capacity prediction device according to claim 3, characterized in that: the power units with different energy types in the step (1) comprise wind power, photovoltaic, hydroelectric and thermal power units.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911169497.9A CN111030088B (en) | 2019-11-25 | 2019-11-25 | Method and device for predicting capacity of power transmission channel for power transmission |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911169497.9A CN111030088B (en) | 2019-11-25 | 2019-11-25 | Method and device for predicting capacity of power transmission channel for power transmission |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111030088A CN111030088A (en) | 2020-04-17 |
| CN111030088B true CN111030088B (en) | 2022-11-11 |
Family
ID=70202017
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201911169497.9A Active CN111030088B (en) | 2019-11-25 | 2019-11-25 | Method and device for predicting capacity of power transmission channel for power transmission |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111030088B (en) |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109066805A (en) * | 2018-07-18 | 2018-12-21 | 合肥工业大学 | A kind of transregional interconnected network generating and transmitting system dynamic dispatching optimization method |
| CN109390973A (en) * | 2018-11-30 | 2019-02-26 | 国家电网公司西南分部 | A kind of sending end electric network source structural optimization method considering channel constraint |
| CN109428343A (en) * | 2017-08-22 | 2019-03-05 | 中国电力科学研究院 | A kind of Method for optimized planning and device of new energy base Transmission Corridor transmission line capability |
-
2019
- 2019-11-25 CN CN201911169497.9A patent/CN111030088B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109428343A (en) * | 2017-08-22 | 2019-03-05 | 中国电力科学研究院 | A kind of Method for optimized planning and device of new energy base Transmission Corridor transmission line capability |
| CN109066805A (en) * | 2018-07-18 | 2018-12-21 | 合肥工业大学 | A kind of transregional interconnected network generating and transmitting system dynamic dispatching optimization method |
| CN109390973A (en) * | 2018-11-30 | 2019-02-26 | 国家电网公司西南分部 | A kind of sending end electric network source structural optimization method considering channel constraint |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111030088A (en) | 2020-04-17 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11641177B2 (en) | Coordinated control of renewable electric generation resource and charge storage device | |
| CN107248751B (en) | A kind of energy storage station dispatch control method for realizing distribution network load power peak load shifting | |
| CN111555281B (en) | Method and device for simulating flexible resource allocation of power system | |
| CN102694391B (en) | Day-ahead optimal scheduling method for wind-solar storage integrated power generation system | |
| Salimi et al. | Simultaneous operation of wind and pumped storage hydropower plants in a linearized security-constrained unit commitment model for high wind energy penetration | |
| CN110490363B (en) | Multi-day unit combination optimization method and system | |
| US20160092622A1 (en) | Method for modeling medium and long term wind power output model of medium and long term optimal operationof power system | |
| US20190228481A1 (en) | Intelligent energy management system for distributed energy resources and energy storage systems using machine learning | |
| CN108039737B (en) | Source-grid-load coordinated operation simulation system | |
| CN103606967A (en) | Dispatching method for achieving robust operation of electrical power system | |
| CN104915737A (en) | Coordinating economic dispatching method for power system containing large-scale wind power based on risk control | |
| CN107910883A (en) | The random production analog method of sequential load curve is corrected based on hydroenergy storage station | |
| CN107800153B (en) | Electric heat energy rolling robust scheduling method for electric heat storage and wind power consumption | |
| CN103887813B (en) | Based on the control method that the wind power system of wind power prediction uncertainty runs | |
| CN104682447A (en) | Power system economic dispatching method containing multiple wind power plants | |
| CN109038556B (en) | Thermal power generating unit flexibility transformation capacity calculation method and system | |
| CN114792994A (en) | New energy and outgoing connecting line time sequence production simulation optimization method and system | |
| CN117239740B (en) | Optimal configuration and flexibility improvement method and system for virtual power plant system | |
| CN117040027B (en) | Coordination optimization method and device for rural virtual power plant | |
| CN105932668A (en) | New energy power generation right replacement assessment method used for minimizing electric quantity of abandoned wind and abandoned light | |
| CN111030088B (en) | Method and device for predicting capacity of power transmission channel for power transmission | |
| CN104659818A (en) | Optimal allocation method for positive and negative spinning reserve capacity in system comprising wind farm | |
| CN113394820B (en) | Optimized scheduling method for new energy grid-connected power system | |
| CN105896535A (en) | Wind farm generation right replacement capacity evaluation method for minimizing wind curtailment capacity | |
| CN114676979B (en) | Energy scheduling method and device, computer equipment and storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |