CN111612269B

CN111612269B - Method for optimizing annual power transmission scheme of clean energy

Info

Publication number: CN111612269B
Application number: CN202010467939.4A
Authority: CN
Inventors: 路亮; 周全; 魏明奎; 周泓; 黄媛
Original assignee: Southwest Branch of State Grid Corp
Current assignee: Southwest Branch of State Grid Corp
Priority date: 2020-05-28
Filing date: 2020-05-28
Publication date: 2021-11-30
Anticipated expiration: 2040-05-28
Also published as: CN111612269A

Abstract

The invention discloses a clean energy annual power transmission scheme optimization method, which belongs to the field of hydropower cluster scheduling, and comprehensively considers and analyzes the data of electric quantity such as the electricity generated in a province, the reserve capacity, the adjustable output and the like, combines the data of the target annual monthly general power consumption, the generated energy of each unit in the province and the like, analyzes and calculates the power transmission quantity outside each month by integrating the various data, and provides a complete annual power transmission optimization scheme which can be directly substituted into the scheme according to the actual condition to obtain data calculation; when the power transmission quantity of each month is analyzed and calculated, various data can be directly brought in according to actual conditions, and the method has universality, convenience, simplicity and strong real operability.

Description

Method for optimizing annual power transmission scheme of clean energy

Technical Field

The invention belongs to the field of hydropower cluster scheduling, and relates to a clean energy annual power transmission scheme optimization method.

Background

At present, relevant researches on the step hydropower have been initially carried out in China, but researches mainly centered on various coordinated optimization scheduling methods in the operation process of the step hydropower are carried out.

The patent [1] provides a scheduling method of a cascade hydroelectric virtual pumped storage power station, which takes the minimum deviation of actual peak regulation power and the minimum water consumption of cascade hydroelectric as scheduling targets, constructs a scheduling objective function of the cascade hydroelectric virtual pumped storage power station to solve and optimize scheduling so as to realize a short-term scheduling plan of a power system;

patent [2] discloses a self-adaptive optimization method and system for power generation dispatching of a cascade hydroelectric system, which are used for improving the overall power generation benefit of the cascade hydroelectric system;

patent [3] provides a cascade hydropower station short-term peak regulation model based on electric quantity control and a solving method, which can make cascade hydropower station fully play the peak regulation function of a cascade hydropower station group while meeting the daily optimized electric quantity, output climbing and output fluctuation control requirements;

the patent [4] discloses a multi-target scheduling parallel dimension reduction method of a giant cascade hydroelectric system;

the patent [5] provides a multi-energy coordination optimization scheduling method considering peak-shaving frequency modulation requirements;

the patent [6] provides a cascade hydropower robust optimization scheduling method based on a random security domain, the method judges the robust feasibility of a pre-scheduling scheme, and the scheduling scheme with robustness is finally obtained through feedback correction coordination optimization;

the patent [7] discloses a multi-period power flow optimization method for the cascade hydropower station water level control based on real-time feedback, which constructs a multi-period optimal power flow control method for coordinating the reservoir water level and the power grid operation, realizes the effect of linear treatment of complex nonlinear conditions based on real-time feedback, and greatly improves the running efficiency of the cascade hydropower station;

the patent [8] provides a combined trading strategy optimization method relating to the stepped hydropower participation provincial and western-to-east power transmission market, which provides beneficial support for the dispatching operation management of large-scale stepped hydropower station groups in the southwest region of China in a new power environment;

patent [9] proposes a double-layer optimization method for medium-and-long-term scheduling and maintenance of a cascade hydropower station in a market environment, wherein a medium-and-long-term scheduling intermediate result is taken as a boundary condition, the minimum maintenance loss is taken as an optimization target, and a maintenance loss optimization result and medium-and-long-term power generation income are merged into total income, so that joint optimization is realized;

the patent [10] provides a method and a system for collaborative combination division of a water, wind and light power station group based on regulation performance, improves the precision of collaborative operation optimization of multiple power sources, is beneficial to scheduling optimization of a complex power system containing multiple power sources, has important significance for improving development and utilization of clean energy, and has important popularization and use values;

patent [11] provides a hydropower group scheduling method considering non-constant coupling constraints; the patent [12] provides a daily optimized scheduling method of a cascade hydropower station considering continuous change of water flow delay;

patent [13] proposes a long-term operation method of a cross-basin cascade hydropower station group under the dynamic production of a giant hydropower station;

patent [14] proposes a daily optimization scheduling method for a cascade hydropower station considering continuous change of water flow delay, and compared with the previous scheduling method, the method has the advantages of detailed description of water flow delay, accurate model, good convergence effect, strong practicability and the like;

patent [15] proposes a real-time optimization scheduling method for a cascade hydropower station group under complex constraint, which incorporates a day-ahead power generation plan into a real-time scheduling algorithm, takes the maximum total energy storage of a cascade hydropower system as an optimization target, and meets the requirements of safety, timeliness, practicability and economy of real-time scheduling.

Patent [16] provides a method for making a stepped hydropower station medium-term power generation plan under the condition of a multi-scale power market, comprehensively considers the upstream and downstream complex constraint problem of a stepped hydropower station under the traditional non-market condition and new problems of multi-market power price, performance coupling, market risk and the like brought by the multi-scale market, can better guide the stepped hydropower station power generation process to respond to market price change, improves the overall income through market optimization and avoids the market risk;

the patent [17] provides a method for optimizing a combined trading strategy of a cascade hydropower participation provincial and western-to-east power transmission market, which provides beneficial support for the dispatching operation management of a large-scale cascade hydropower station group in the southwest region of China in a new power environment;

patent [18] proposes a double-layer optimization method for medium and long-term scheduling and overhaul of a cascade hydropower station in a market environment;

patent [19] proposes a day-ahead market clearing mechanism based on the coupling relation of cascade hydropower stations, which realizes the combined clearing of upstream and downstream power stations and solves the problem of unbalance matching between the bid amount and the generating capacity amount in the downstream power stations.

The invention discloses a medium-voltage distribution network accurate planning method based on three-layer macroscopic networking constraint, and the operability, the scientificity and the accuracy of a planning scheme are improved through the target guidance and the old-fashioned principle of global overall planning in space and near-far coordination and reinforcement planning in time.

Patent [21] discloses a power corridor planning method based on GIS information data, which reduces the problems of large water abandonment of hydropower and serious economic benefit loss caused by the delay of planning and construction of an outgoing channel, ensures that the green and environment-friendly hydropower is smoothly sent out, and creates continuous and reliable economic benefit, ecological benefit and social benefit.

The above patent [1-15] basically focuses on the operation side of the cascade hydropower stations and focuses on the problem of coordination and scheduling among the cascade hydropower stations; patents [16-19] focus on the electricity market side, and focus on the problems of how hydropower stations in upstream and downstream participate in competition in the electricity market and determination of clearing price; although the patent [20-21] relates to the problem of grid planning, the patent [20-21] mainly aims at a planning method of a precise power distribution network, and the planning method does not relate to the large-area coordination planning problem of the partition electric quantity balance class, and does not aim at the long-time dynamic process development analysis of leading reservoir construction, and the establishment of a suitable evaluation scheme and an evaluation system.

Therefore, an optimization method of the annual power transmission scheme of the clean energy needs to be researched urgently.

Disclosure of Invention

The invention aims to: the annual power transmission optimization scheme is a complete annual power transmission optimization scheme which can be directly substituted into the scheme according to actual conditions to obtain data calculation.

The technical scheme adopted by the invention is as follows:

the method for optimizing the annual power transmission scheme of the clean energy mainly comprises the following steps of:

analyzing and determining the provincial electric quantity data:

s1: finding out the maximum power load and power consumption of the province of the target year by month:

according to the statistics data of monthly electricity load and electricity consumption in the province of the current year, the study target year is predicted by combining electricity load acceleration, electricity consumption acceleration, economic acceleration and temperature condition prediction, and the maximum electricity load and electricity consumption are uniformly adjusted in the province of the month;

make the first month, province and interior coordinateThe maximum electricity load and the electricity consumption are respectively expressed as: MaxLoad_iAnd DisConCap_i(ii) a Wherein i is 1,2,3, …, 12;

s2: and (3) counting the adjustable output of the target annual month-by-month province general regulation:

let month i, the intra-provincial collective-control adjustable output be expressed as: FeaPow_iWherein i is 1,2,3, …, 12;

to ensure the safe and stable operation of the system, for each month i:

FeaPow_i>MaxLoad_i (1-1)

wherein i is 1,2,3, …, 12;

for the ith month, the adjustable output of the provincial general regulation meets the following requirements:

FeaPow_i＝HydPow_i+ThePow_i+WinPow_i+PhoPow_i (1-2)

wherein HydPow_i、ThePow_i、WinPow_i、PhoPow_iRespectively representing hydropower output, thermal power output, wind power output and photovoltaic output in the ith month;

and for the ith month, the hydroelectric power output meets the following requirements:

HydPow_i＝HydCap_i-MainHydCap_i (1-3)

among them, HydCap_i、MainHydCap_iRespectively representing the installed capacity and the planned overhaul capacity of water in the ith month;

and for the ith month, the thermal power output meets the following requirements:

ThePow_i＝CoalPow_i+GasPow_i+BioPow_i (1-4)

wherein, CoalPow_i、GasPow_i、BioPow_iRespectively representing coal electricity output, gas electricity output and biomass energy power generation output in the ith month;

for the ith month, the coal electricity output force meets the following requirements:

CoalPow_i＝CoalCap_i-MainCoalCap_i (1-5)

wherein, Coalcap_i、MainCoalCap_iRespectively for month iCoal-electricity installed capacity and planned overhaul capacity;

for the ith month, the gas-electricity output force meets the following requirements:

GasPow_i＝GasCap_i-MainGasCap_i (1-6)

wherein, GasCap_i、MainGasCap_iRespectively representing the gas-electricity installed capacity and the planned maintenance capacity of the ith month;

and for the ith month, the biomass energy generated output meets the following requirements:

BioPow_i＝BioCap_i-MainBioCap_i (1-7)

wherein, BioCap_i、MainBioCap_iRespectively representing the installed capacity and the scheduled maintenance capacity of biomass energy power generation in the ith month;

and for the ith month, the wind power generation output meets the following requirements:

WinPow_i＝CoeWinPow_i×WinCap_i (1-8)

among them, WinCap_i、CoeWinPow_iRespectively representing the installed capacity of the wind power generation and the corresponding guaranteed capacity coefficient of the ith month;

for the ith month, the output of the photovoltaic power generation meets the following requirements:

PhoPow_i＝CoePhoPow_i×PhoCap_i (1-9)

wherein PhoCap_i、CoePhoPow_iRespectively representing the installed photovoltaic power generation capacity and the corresponding guaranteed capacity coefficient of the ith month;

s3: determining the generated power and the reserve capacity in the province:

in month i, the generated power in province is expressed as StayPow_iSpare capacity is denoted ResPow_i；

S4: analyzing the surplus power at the peak time in the province;

month i, the intra-provincial peak power reserve is expressed as:

SurPeakPow_i＝FeaPow_i+StayPow_i-MaxLoad_i-ResPow_i (1-10)；

s5: determining the power transmission capacity of a direct current channel and an alternating current section:

the power transmission capacity of the kth outgoing channel is expressed as SendChilim_kWherein k is 1,2,3, …, s; the province totals s outward sending channels;

for the kth outward-sending channel, there are

ProPow_k＝SendChaLim_k-NatPow_k-RegPow_k (1-11)

Wherein k is 1,2,3, …, s;

the maximum outgoing space in the ith month province peak period is as follows:

wherein, Var_iIndicating that the delivery capacity of the ith month changes under the influence of external factors such as a power grid starting mode, channel maintenance and the like, wherein i is 1,2,3, … and 12; coe_kThe power-limited operation coefficient of the AC/DC power transmission line is shown to be influenced by factors such as safety and stability; in order to improve the operation efficiency of the algorithm, the direct current channel is controlled by taking a line as a unit, and the alternating current channel is controlled by taking a section as a unit.

S6: analyzing and calculating the power transmission quantity of one line all day:

in the ith month, according to one line all day, the electric power which can be sent out is as follows:

OneLineSendPow_i＝min(SurPeakPow_i,PeakMaxSendPow_i) (1-13)

then, in the ith month, according to one line all day, the electric quantity which can be sent out is as follows:

OneLineSendCap_i＝OneLineSendPow_i×Mon_i×24/10000 (1-14)；

s7: analyzing and calculating the maximum outgoing power of the valley period:

the maximum outgoing power space of the provincial valley period of the ith month is as follows:

TrouMaxSendPow_i＝PeakMaxSendPow_i+NatRegPow_i (1-15)

wherein i is 1,2,3, …, 12; NatRegPow_iThe peak regulation power of the country in the valley period of the ith month is represented;

s8: calculating the difference between the peak and the valley of the outgoing space:

at month i, the peak-to-valley difference in the delivery space, i.e., the remaining delivery space, was:

PeakTrouDifPow_i＝TrouMaxSendPow_i-OneLineSendPow_i (1-16)

s9: analyzing and predicting the difference between the average power consumption peak and valley in the province:

the average peak-to-valley power consumption difference in the ith month province is AvgConPeakTrouDifPow_iThen, the power delivered during the valley period is:

TrouSendPow_i＝min(AvgConPeakTrouDifPow_i,PeakTrouDifPow_i) (1-17)

the intra-provincial average power peak valley difference of the research target year is determined according to the intra-provincial average power peak valley difference of the previous year, the load acceleration, the air temperature prediction and other factors.

S10: calculating the electric quantity which can be increased in the valley period:

the electric quantity can be delivered in the valley period as follows:

TrouSendCap_i＝TrouSendPow_i×Mon_i×24/10000 (1-18)

s11: calculating all the electric quantity which can be sent out in the peak time and the valley time;

all the power that can be delivered out include: the power that can be delivered by one line all day plus the power that has been delivered by one line all day, namely:

SendCap_i＝OneLineSendCap_i+TrouSendCap_i (1-19)

wherein i is 1,2,3, …, 12;

and simultaneously analyzing and predicting the target year and month data:

s12: analyzing and predicting the annual monthly general electricity consumption of the target:

according to the condition of power consumption in the past year, the acceleration of the power consumption and the prediction of economy and temperature, the overall power consumption in the ith month of the research target year is determined and recorded as DisConCap_i；

S13: analyzing and predicting the generated energy of various units in province:

determining the generated energy of various units in the province according to the installed growth condition and the historical generated energy:

GenCap_i＝HydCap_i+TheCap_i+WinCap_i+PhoCap_i (1-20)

among them, HydCap_i、TheCap_i、WinCap_i、PhoCap_iRespectively representing the predicted generated energy of provincial hydropower, thermal power, wind power and photovoltaic power in the ith month;

for the thermal power generation amount of the ith month, the following steps are included:

TheCap_i＝CoalCap_i+GasCap_i+BioCap_i (1-21)

wherein, Coalcap_i、GasCap_i、BioCap_iThe power generation amount of coal electricity, gas electricity and biomass in the ith month is represented, and i is 1,2,3, … and 12;

s14: analyzing and determining provincial dispatching input electric quantity of each month:

in month i, the province power input includes national province power input and network power input, and can be expressed as

ProIncCap_i＝NatStayCap_i+RegStayCap_i (1-22)

Wherein, NatStayCap_i、RegStayCap_iRespectively representing the electricity saving quantity of the national state and the network reserve regulation in the ith month;

s15: analyzing and calculating the surplus of electric quantity in each month province:

in month i, the surplus of the provincial electric quantity is as follows:

ProSurCap_i＝GenCap_i+ProIncCap_i-DisConCap_i (1-23)

among them, GenCap_i、ProIncCap_i、DisConCap_iRespectively representing the generated energy, the provincial dispatching input electric quantity and the general dispatching electric quantity of various units in the province of the ith month;

performing the following analysis according to the analyzed provincial electric quantity data and the predicted target annual monthly data:

s16: the output electricity quantity of each month can be analyzed and calculated as follows:

and calculating according to the electric power and the electric quantity, wherein the electric quantity which can be delivered in the ith month is as follows:

CanBeSendCap_i＝min(ProSurCap_i,SendCap_i) (1-24)

wherein i is 1,2,3, …, 12;

s17: analyzing and calculating the delivery electric quantity of the peak and the valley:

in the ith month, the delivered electricity quantity in the peak time period is as follows:

OptOneLineSendCap_i＝OptCoe_i×OneLineSendCap_i (1-25)

wherein, OptCoe_iThe output power optimization coefficient of the ith month is represented;

in the ith month, the electric quantity delivered in the valley period is as follows:

OptTrouSendCap_i＝(TrouOptCoe_i×TrouSendCap_i,CanBeSendCap_i-OptOneLineSendCap_i) (1-26)

wherein TrouoPtCoe_iThe output power optimization coefficient of the i-th month is represented;

s18: analyzing and calculating the water and electricity discarding quantity of the peak and the valley:

in the ith month, the water and electricity abandoned quantity in the peak period is as follows:

PeakAbaCap_i＝(1-OptCoe_i)×OneLineSendCap_i (1-27)

the water and electricity discarded in the valley period is as follows:

TrouAbaCap_i＝TrouSendCap_i-OptTrouSendCap_i (1-28)。

further, the wind power guarantee capacity coefficient in the step S2 is selected according to the wind resource characteristics of the specific region, and 20% is taken in the scheme.

Further, in the step S2, the photovoltaic power generation guaranteed capacity coefficient is selected according to the solar energy resource characteristics of the specific region.

Further, the guaranteed capacity coefficient of photovoltaic power generation is 10% in 5-8 months, and is 7% in other months.

Further, in step S3, 400 ten million of generated power and 60 ten million of spare capacity are taken as the amount of generated power remaining in the province.

Further, in step S5, in order to improve the operation efficiency of the algorithm, the dc channels are controlled by the line unit, and the ac channels are controlled by the cross section unit.

In summary, due to the adoption of the technical scheme, the invention has the beneficial effects that:

1. the invention provides a clean energy annual power transmission scheme optimization method, which comprehensively considers and analyzes the electricity data such as the electricity generated in the province, the reserve capacity, the adjustable output and the like, combines the data such as the target annual monthly general electricity consumption, the electricity generation amount of each unit in the province and the like, analyzes and calculates the electricity transmission amount outside each month by integrating the various data, and provides a complete annual power transmission optimization scheme which can be directly substituted into the scheme according to the actual condition to obtain the data calculation;

2. the invention provides a clean energy annual power transmission scheme optimization method, which comprehensively considers and analyzes the electricity data such as the electricity generated in the province, the reserve capacity, the adjustable output and the like, combines the data such as the target annual monthly general electricity consumption, the electricity generation amount of each unit in the province and the like, analyzes and calculates the electricity transmitted outside each month by integrating the various data, can be directly brought in according to the actual condition, has universality, is convenient and simple, and has strong practical operability.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and that for those skilled in the art, other relevant drawings can be obtained according to the drawings without inventive effort, wherein:

fig. 1 is a schematic block diagram of the present invention.

Detailed Description

In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the detailed description and specific examples, while indicating the preferred embodiment of the invention, are intended for purposes of illustration only and are not intended to limit the scope of the invention. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations.

Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present invention without making any creative effort, shall fall within the protection scope of the present invention.

It is noted that relational terms such as "first" and "second," and the like, may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.

The features and properties of the present invention are described in further detail below with reference to examples.

Example one

In an embodiment of the present invention, as shown in fig. 1, a method for optimizing an annual power transmission scheme of clean energy mainly includes the following steps:

analyzing and determining the provincial electric quantity data:

in the ith month, the maximum power load and the maximum power consumption of the provincial city general regulation are respectively expressed as: MaxLoad_iAnd DisConCap_i(ii) a Wherein i is 1,2,3, …, 12;

to ensure the safe and stable operation of the system, for each month i:

FeaPow_i>MaxLoad_i (1-1)

wherein i is 1,2,3, …, 12;

FeaPow_i＝HydPow_i+ThePow_i+WinPow_i+PhoPow_i (1-2)

HydPow_i＝HydCap_i-MainHydCap_i (1-3)

ThePow_i＝CoalPow_i+GasPow_i+BioPow_i (1-4)

wherein, CoalPow_i、GasPow_i、BioPow_iRespectively show the coal electric output at the i-th month,Gas-electricity output and biomass energy power generation output;

CoalPow_i＝CoalCap_i-MainCoalCap_i (1-5)

wherein, Coalcap_i、MainCoalCap_iRespectively representing the coal electric installation capacity and the planned maintenance capacity of the ith month;

GasPow_i＝GasCap_i-MainGasCap_i (1-6)

BioPow_i＝BioCap_i-MainBioCap_i (1-7)

WinPow_i＝CoeWinPow_i×WinCap_i (1-8)

PhoPow_i＝CoePhoPow_i×PhoCap_i (1-9)

s3: determining the generated power and the reserve capacity in the province:

S4: analyzing the surplus power at the peak time in the province;

month i, the intra-provincial peak power reserve is expressed as:

SurPeakPow_i＝FeaPow_i+StayPow_i-MaxLoad_i-ResPow_i (1-10)；

for the kth outward-sending channel, there are

ProPow_k＝SendChaLim_k-NatPow_k-RegPow_k (1-11)

Wherein k is 1,2,3, …, s;

the maximum outgoing space in the ith month province peak period is as follows:

OneLineSendPow_i＝min(SurPeakPow_i,PeakMaxSendPow_i) (1-13)

OneLineSendCap_i＝OneLineSendPow_i×Mon_i×24/10000 (1-14)；

s7: analyzing and calculating the maximum outgoing power of the valley period:

TrouMaxSendPow_i＝PeakMaxSendPow_i+NatRegPow_i (1-15)

PeakTrouDifPow_i＝TrouMaxSendPow_i-OneLineSendPow_i (1-16)

TrouSendPow_i＝min(AvgConPeakTrouDifPow_i,PeakTrouDifPow_i) (1-17)

the electric quantity can be delivered in the valley period as follows:

TrouSendCap_i＝TrouSendPow_i×Mon_i×24/10000 (1-18)

SendCap_i＝OneLineSendCap_i+TrouSendCap_i (1-19)

wherein i is 1,2,3, …, 12;

and simultaneously analyzing and predicting the target year and month data:

GenCap_i＝HydCap_i+TheCap_i+WinCap_i+PhoCap_i (1-20)

TheCap_i＝CoalCap_i+GasCap_i+BioCap_i (1-21)

ProIncCap_i＝NatStayCap_i+RegStayCap_i (1-22)

in month i, the surplus of the provincial electric quantity is as follows:

ProSurCap_i＝GenCap_i+ProIncCap_i-DisConCap_i (1-23)

CanBeSendCap_i＝min(ProSurCap_i,SendCap_i) (1-24)

wherein i is 1,2,3, …, 12;

OptOneLineSendCap_i＝OptCoe_i×OneLineSendCap_i (1-25)

PeakAbaCap_i＝(1-OptCoe_i)×OneLineSendCap_i (1-27)

the water and electricity discarded in the valley period is as follows:

TrouAbaCap_i＝TrouSendCap_i-OptTrouSendCap_i (1-28)。

the annual power transmission optimization scheme is provided, which is complete and can be directly substituted into the scheme according to actual conditions to obtain data calculation.

Example two

In this embodiment, on the basis of the first embodiment, the wind power guaranteed capacity coefficient in step S2 is selected according to the wind resource characteristics of a specific area, and in this scheme, 20% is taken.

In the step S2, the photovoltaic power generation guaranteed capacity coefficient is 10% in 5-8 months, and is 7% in other months; 400 ten thousand million of generated power and 60 ten thousand of standby capacity are taken as the generated power in the province reserved in the step S3; in step S5, to improve the operation efficiency of the algorithm, the dc channels are controlled in units of lines, and the ac channels are controlled in units of cross sections.

The above description is only for the purpose of illustrating the preferred embodiments of the present invention and should not be taken as limiting the scope of the present invention, and any modifications, equivalents and improvements made by those skilled in the art within the spirit and principle of the present invention should be included in the scope of the present invention.

Claims

1. The method for optimizing the annual power transmission scheme of the clean energy is characterized by comprising the following steps: mainly comprises the following steps which are carried out in sequence:

analyzing and determining the provincial electric quantity data:

adjustable output meter for making the province and provinces in the ith monthShown as follows: FeaPow_iWherein i is 1,2,3, …, 12;

to ensure the safe and stable operation of the system, for each month i:

FeaPow_i＞MaxLoad_i (1-1)

wherein i is 1,2,3, …, 12;

FeaPow_i＝HydPow_i+ThePow_i+WinPow_i+PhoPow_i (1-2)

HydPow_i＝HydCap_i-MainHydCap_i (1-3)

ThePow_i＝CoalPow_i+GasPow_i+BioPow_i (1-4)

CoalPow_i＝CoalCap_i-MainCoalCap_i (1-5)

GasPow_i＝GasCap_i-MainGasCap_i (1-6)

BioPow_i＝BioCap_i-MainBioCap_i (1-7)

WinPow_i＝CoeWinPow_i×WinCap_i (1-8)

PhoPow_i＝CoePhoPow_i×PhoCap_i (1-9)

s3: determining the generated power and the reserve capacity in the province:

S4: analyzing the surplus power at the peak time in the province;

month i, the intra-provincial peak power reserve is expressed as:

SurPeakPow_i＝FeaPow_i+StayPow_i-MaxLoad_i-ResPow_i (1-10)；

for the kth outward-sending channel, there are

ProPow_k＝SendChaLim_k-NatPow_k-RegPow_k (1-11)

Wherein k is 1,2,3, …, s;

the maximum outgoing space in the ith month province peak period is as follows:

wherein, Var_iIndicates that the delivery capacity of the ith month is changed under the influence of external factors, i is 1,2,3, …, 12; coe_kRepresenting the limited power operation coefficient of the AC/DC power transmission line influenced by the safety and stability factors;

OneLineSendPow_i＝min(SurPeakPow_i，PeakMaxSendPow_i) (1-13)

OneLineSendCap_i＝OneLineSendPow_i×Mon_i×24/10000 (1-14)；

s7: analyzing and calculating the maximum outgoing power of the valley period:

TrouMaxSendPow_i＝PeakMaxSendPow_i+NatRegPow_i (1-15)

at month i, the peak-to-valley difference in the delivery space was:

PeakTrouDifPow_i＝TrouMaxSendPow_i-OneLineSendPow_i (1-16)

TrouSendPow_i＝min(AvgConPeakTrouDifPow_i，PeakTrouDifPow_i) (1-17)

the electric quantity can be delivered in the valley period as follows:

TrouSendCap_i＝TrouSendPow_i×Mon_i×24/10000 (1-18)

all the power that can be delivered out include: the electric quantity can be delivered outside in the electric quantity valley period that one line can be delivered outside all day, namely:

SendCap_i＝OneLineSendCap_i+TrouSendCap_i (1-19)

wherein i is 1,2,3, …, 12;

and simultaneously analyzing and predicting the target year and month data:

GenCap_i＝HydCap_i+TheCap_i+WinCap_i+PhoCap_i (1-20)

TheCap_i＝CoalCap_i+GasCap_i+BioCap_i (1-21)

ProIncCap_i＝NatStayCap_i+RegStayCap_i (1-22)

in month i, the surplus of the provincial electric quantity is as follows:

ProSurCap_i＝GenCap_i+ProIncCap_i-DisConCap_i (1-23)

CanBeSendCap_i＝min(ProSurCap_i，SendCap_i) (1-24)

wherein i is 1,2,3, …, 12;

OptOneLineSendCap_i＝OptCoe_i×OneLineSendCap_i (1-25)

OptTrouSendCap_i＝(TrouOptCoe_i×TrouSendCap_i，CanBeSendCap_i-OptOneLineSendCap_i) (1-26)

PeakAbaCap_i＝(1-OptCoe_i)×OneLineSendCapi (1-27)

the water and electricity discarded in the valley period is as follows:

TrouAbaCap_i＝TrouSendCap_i-OptTrouSendCap_i (1-28)。

2. the method according to claim 1, wherein the method comprises the steps of: in the step S2, the wind power guarantee capacity coefficient is 20%.

3. The method according to claim 1, wherein the method comprises the steps of: in step S2, the guaranteed photovoltaic power generation capacity coefficient is selected according to the characteristics of the solar energy resources in the specific area.

4. The method according to claim 3, wherein the method comprises: the guaranteed capacity coefficient of photovoltaic power generation is 10% in 5-8 months, and is 7% in other months.

5. The method according to claim 1, wherein the method comprises the steps of: in step S3, 400 ten million of generated power is taken as the power to be generated, and 60 ten million of standby capacity is taken as the standby capacity.

6. The method according to claim 1, wherein the method comprises the steps of: in step S5, to improve the operation efficiency of the algorithm, the dc channels are controlled in units of lines, and the ac channels are controlled in units of cross sections.