CN113644649A - Method for solving scheduling plan deviation of wind-light-water complementary power generation system - Google Patents

Method for solving scheduling plan deviation of wind-light-water complementary power generation system Download PDF

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CN113644649A
CN113644649A CN202110767449.0A CN202110767449A CN113644649A CN 113644649 A CN113644649 A CN 113644649A CN 202110767449 A CN202110767449 A CN 202110767449A CN 113644649 A CN113644649 A CN 113644649A
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CN113644649B (en
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赖春羊
马光文
谢航
黄炜斌
陈仕军
夏利名
赵丽伟
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Sichuan University
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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
    • H02J3/004—Generation forecast, e.g. methods or systems for forecasting future energy generation
    • 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
    • H02J3/466—Scheduling the operation of the generators, e.g. connecting or disconnecting generators to meet a given demand
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/20—The dispersed energy generation being of renewable origin
    • H02J2300/22—The renewable source being solar energy
    • H02J2300/24—The renewable source being solar energy of photovoltaic origin
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/20—The dispersed energy generation being of renewable origin
    • H02J2300/28—The renewable source being wind energy
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E10/00—Energy generation through renewable energy sources
    • Y02E10/50—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

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Abstract

The invention relates to the field of resource scheduling of a wind-light-water complementary system, in particular to a method for solving scheduling plan deviation of a wind-light-water complementary power generation system, which comprises the following steps: firstly, acquiring wind power and photoelectric prediction error levels in a current complementary system; predicting wind and light power output conditions in day-ahead scheduling and reserving power and electricity scheduling capability; and thirdly, making a day-ahead scheduling plan. The invention makes up the deficiency of the current relevant research on the problem of the deviation between the day-ahead scheduling and the actual scheduling caused by the wind-light prediction error, and can reduce the deviation between the day-ahead scheduling and the actual scheduling and guide the scheduling planning of a complementary system by reserving the water and electricity scheduling capability in the day-ahead scheduling planning.

Description

Method for solving scheduling plan deviation of wind-light-water complementary power generation system
Technical Field
The invention relates to the technical field of resource scheduling of a wind-light-water complementary system, in particular to a method for solving scheduling plan deviation of a wind-light-water complementary power generation system.
Background
In order to solve the volatility and intermittency of wind power and photovoltaic power generation and improve the utilization rate of wind and light resources, wind and light and other energy sources with adjustable performance are combined into a complementary power generation system so as to complete various operation targets. Limited by the current wind and light prediction technology, the actual situation has certain error with the planning situation.
At present, when a power generation side carries out complementary system optimization scheduling, there are two main ways for processing wind-solar output input:
(1) and (4) ignoring wind and light prediction error influence, and performing optimized scheduling by taking a typical wind and light output process as a determination process. This type of research focuses on the discussion of the role of regulating energy sources and complementary modes of operation under certain objectives. Due to the fact that a typical wind-solar output process is adopted for scheduling, the research has small guiding significance on actual scheduling of a specific day.
(2) And (4) predicting the wind and light output by adopting a certain mode in consideration of the uncertainty of the wind and light. Such methods are often employed for day-ahead dispatch planning. In addition to the research content comprising the first category of approaches, this category of research focuses on the characterization of wind and light uncertainty. Generally, the wind and light uncertainty is represented by adopting the error between a predicted value and an actual value, or a specific model is adopted to extract and fit uncertainty factors, and then wind and light random output is obtained through random sampling and multi-scene generation technologies. Although the research considers wind-light uncertainty so as to predict the wind-light output more accurately, the wind-light output is still taken as deterministic information to be input into an optimization model when the actual operation is carried out. It can be seen that in the complementary optimization scheduling of the current power generation side, a scheduling plan has a deviation from the actual optimization operation.
For the power grid side, power grid balance is a precondition which must be met by the safe operation of the power grid, and the uncertainty of power output is increased due to large-scale wind-solar grid connection. In order to solve the deviation between actual and planned output caused by wind and light uncertainty, a mode of rotating reserve capacity is generally adopted, and the influence of wind and light fluctuation on power balance of a power grid is counteracted by reserving a part of reserve capacity. Relevant research is mainly developed aiming at the power balance requirement of a power grid side, and the problem that the scheduling plan and the actual operation of the wind-light-water complementary system have deviation cannot be solved.
With the development of the electric power spot market, the participation of the wind, light and water complementary system in the market competition is a necessary trend, and due to the influence of wind and light prediction errors, the day-ahead scheduling plan of the complementary system is deviated from the actual operation condition, and the complementary system is punished in the market environment.
Disclosure of Invention
In order to solve the problems in the prior art, the invention provides a method for solving the scheduling plan deviation of a wind-light-water complementary power generation system, and solves the problem that the day-ahead plan is deviated from the actual operation due to the wind-light output prediction deviation. The strategy for dynamically reserving the hydropower dispatching capacity is provided for the formulation of the day-ahead dispatching plan of the complementary system, the dispatching model is established according to the maximum average output and the minimum output fluctuation of the complementary system, the deviation of the day-ahead dispatching plan and the actual situation can be effectively avoided through the strategy model, the dispatching operation of the complementary system is guided, and the problems in the background art are solved.
In order to achieve the purpose, the invention provides the following technical scheme: a method for solving the scheduling plan deviation of a wind-solar-water complementary power generation system comprises the following steps:
firstly, acquiring wind power and photoelectric prediction error levels in a current complementary system;
predicting wind and light power output conditions in day-ahead scheduling and reserving power and electricity scheduling capability;
and thirdly, making a day-ahead scheduling plan.
Preferably, in the first step, the wind power error level calculation method in the current complementary system is as follows:
Figure BDA0003152387690000021
in the formula: x is the number oftObtained based on historical datathe maximum wind power prediction error in the t time period;
Figure BDA0003152387690000022
predicting wind power output MW for a historical t period;
Figure BDA0003152387690000031
actual wind power output, MW, for a corresponding time period t;
the photoelectric error level calculation method in the current complementary system comprises the following steps:
Figure BDA0003152387690000032
in the formula: y istThe maximum photoelectric prediction error in the t time period is obtained according to historical data;
Figure BDA0003152387690000033
predicting the photoelectric output power MW for the historical t period;
Figure BDA0003152387690000034
corresponding to the actual photoelectric output, MW, during the period t.
Preferably, in the second step, the method for predicting the wind-solar power output situation and reserving the hydropower scheduling capability in the day-ahead scheduling comprises the following steps:
Figure BDA0003152387690000035
Figure BDA0003152387690000036
in the formula:
Figure BDA0003152387690000037
reserving scheduling capacity, MW, for the hydropower station maximum in the time period t;
Figure BDA0003152387690000038
respectively a time interval t wind power day and a photoelectric dayPre-prediction output, MW;
Figure BDA0003152387690000039
water installed capacity, MW;
Figure BDA00031523876900000310
the maximum power generation capacity of hydropower, MW, is time period t.
Preferably, in step three, the making of the day-ahead scheduling plan comprises model building and model solving; the model establishment comprises the establishment and normalization of a complementary system average output maximum and output fluctuation minimum objective function and constraint conditions.
Preferably, the maximum objective function of the average output of the complementary system is as follows:
Figure BDA00031523876900000311
Figure BDA00031523876900000312
in the formula: i is1For maximum system average output, MW;
Figure BDA00031523876900000313
mean contribution, MW, to the system; n is a radical ofh,t、Np,t、Nw,tThe water power, the photoelectric power and the wind power output and MW are respectively in the time period t;
the minimum objective function of the output fluctuation of the complementary system is as follows:
I2＝minF
Figure BDA0003152387690000041
in the formula: i is2To minimize output fluctuation, MW; f is system output fluctuation, MW; n is a radical oftThe output of the complementary system in the time period t, MW;
the normalization method of the maximum target function of the average output of the complementary system comprises the following steps:
Figure BDA0003152387690000042
in the formula: l is the utilization rate of the generating capacity;
Figure BDA0003152387690000043
respectively available wind and light output and MW in a time period t;
the normalization method of the objective function with the minimum output fluctuation of the complementary system comprises the following steps:
Figure BDA0003152387690000044
in the formula: and S is the output stability of the complementary system.
Preferably, the constraint conditions are: system constraints, wind and light resource constraints and hydropower constraints;
the system constraints include power balance and power balance;
the wind-solar resource constraint comprises: output constraint and energy abandon constraint;
the hydro-electrical constraints include: scheduling capability constraint, output constraint, water balance constraint, water abandoning constraint, water level constraint, reservoir capacity constraint and vibration area constraint.
Preferably, the model solving step is as follows:
s1: forecasting the wind-solar output condition and acquiring the flow condition, determining scheduling time intervals, reserving the hydropower scheduling capacity for each time interval, and calculating the maximum hydropower generation capacity of each time interval after the scheduling capacity is reserved;
s2: determining all operation schemes, calculating the average output force and output force fluctuation of the schemes, and calculating a target function value;
s3: judging whether all the operation schemes are traversed, if not, returning to S2, and if so, selecting the scheme meeting the requirement;
s4: and outputting all the selectable scheduling schemes.
The invention has the beneficial effects that:
1) the method of the invention considers the influence of wind and light prediction errors on the formulation of a scheduling plan, provides a strategy for dynamically reserving the hydropower scheduling capability, establishes a scheduling model, can effectively reduce the deviation of the current scheduling plan and the actual operation, and guides a complementary system to optimally operate;
2) the method makes up the deficiency of the research related to the deviation of the day-ahead scheduling plan and the actual scheduling in the current wind-light-water complementary system, can better fit the development prospect of the power market, and better meets the actual production requirement.
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FIG. 1 is a schematic flow diagram of the process of the present invention;
fig. 2 is a schematic diagram of steps for reserving hydropower scheduling capacity according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example 1
Referring to fig. 1-2, the present invention provides a technical solution: a method for solving the scheduling plan deviation of a wind-solar-water complementary power generation system is disclosed, and the flow is shown in figure 1, and the method comprises the following steps:
firstly, acquiring wind power and photoelectric prediction error levels in a current complementary system;
predicting wind and light power output conditions in day-ahead scheduling and reserving power and electricity scheduling capability;
and thirdly, making a day-ahead scheduling plan.
Each step of the method for solving the scheduling plan deviation of the wind, light and water complementary power generation system of the embodiment is described in detail in turn as follows:
the method comprises the following steps: acquiring wind power and photoelectric prediction error levels in a current complementary system:
the prediction errors of wind power generation and photovoltaic power generation in the current system in the time period t are respectively set as xtAnd yt。
Figure BDA0003152387690000061
In the formula: x is the number oftThe maximum prediction error of the wind power in the t time period is obtained according to historical data;
Figure BDA0003152387690000062
predicting wind power output MW for a historical t period;
Figure BDA0003152387690000063
corresponding to the actual wind power output in the period t, MW.
Figure BDA0003152387690000064
In the formula: y istThe maximum photoelectric prediction error in the t time period is obtained according to historical data;
Figure BDA0003152387690000065
predicting the photoelectric output power MW for the historical t period;
Figure BDA0003152387690000066
corresponding to the actual photoelectric output, MW, during the period t.
Step two: forecasting the wind and light power output condition in the day-ahead scheduling and reserving the water and electricity scheduling capability;
the reserved hydropower dispatching capacity is realized by setting different hydropower maximum power generation capacities for each dispatching time interval when a day-ahead dispatching plan is made. According to the wind and light prediction error, the maximum output deviation which is possible to appear in the wind and light in a time period is calculated to be used as the maximum reserved scheduling capability of the hydropower in the time period, the reserved scheduling capability is subtracted from the hydropower device to be used as the maximum hydropower generation capability in the time period, and the hydropower participates in the system optimization scheduling according to the maximum hydropower generation capability after the reserved scheduling capability when the scheduling plan is scheduled in the day ahead.
The reserved scheduling capability method comprises the following steps:
Figure BDA0003152387690000067
Figure BDA0003152387690000068
in the formula:
Figure BDA0003152387690000069
reserving scheduling capacity, MW, for the hydropower station maximum in the time period t;
Figure BDA00031523876900000610
respectively predicting output and MW for the time period t wind power and the photoelectric day ahead;
Figure BDA00031523876900000611
water installed capacity, MW;
Figure BDA00031523876900000612
the maximum power generation capacity of hydropower, MW, is time period t.
The steps of reserving hydropower scheduling capacity are shown in figure 2.
Step three: making a day-ahead scheduling plan, wherein the making of the day-ahead scheduling plan comprises model building and model solving;
the model establishment comprises the establishment and normalization of a complementary system average output maximum and output fluctuation minimum objective function and constraint conditions;
the most important purpose of forming a complementary system by using hydropower as an adjusting energy source and wind power and photoelectricity is to stabilize fluctuation and intermittence of wind and light and improve the consumption of the wind and light, so that a scheduling model is established by taking the maximum average output and the minimum output fluctuation of the complementary system as targets.
(1) Maximum average output
Figure BDA0003152387690000071
Figure BDA0003152387690000072
In the formula: i is1For maximum system average output, MW;
Figure BDA0003152387690000073
mean contribution, MW, to the system; n is a radical ofh,t、Np,t、Nw,tThe power output and MW of hydropower, photoelectricity and wind power are respectively time period t.
(2) Minimum output fluctuation
The standard deviation is chosen here to measure the output fluctuation:
I2＝minF
Figure BDA0003152387690000074
in the formula: i is2To minimize output fluctuation, MW; f is system output fluctuation, MW; n is a radical oftThe complementary system output, MW, for time period t.
The normalization comprises average output normalization and output fluctuation normalization;
(1) mean output normalization
Defining the ratio of the output to the maximum generating capacity in a time period as a generating capacity utilization rate L, and taking the index as the average output after normalization:
Figure BDA0003152387690000075
in the formula: l is the utilization rate of the generating capacity;
Figure BDA0003152387690000076
respectively, the available wind and light output and MW in the time period t.
(2) Output ripple normalization
In order to facilitate solving, the two objective functions are unified into a forward index, the output fluctuation index F is subjected to forward conversion and normalization processing, and the normalized index is named as output stability S. The larger the output fluctuation index is, the smaller the output stability S is, and S belongs to [0,1 ]. The transformation was as follows:
Figure BDA0003152387690000081
in the formula: and S is the output stability of the complementary system.
(3) Objective function
The converted single objective function is:
I＝max(L+S)
in the formula: i is the maximized objective function value.
The constraint conditions comprise system constraint, wind and light resource constraint and hydropower constraint;
(1) system constraints
1) Balance of output forces
Nt＝Nw,t+Np,t+Nh,t
2) Electric quantity balance
Figure BDA0003152387690000082
(2) Wind and light resource constraints
1) Restraint of output
Figure BDA0003152387690000083
2) Energy rejection constraint
Figure BDA0003152387690000084
(3) Hydropower restraint
1) Scheduling capability constraints
Figure BDA0003152387690000085
2) Restraint of output
Figure BDA0003152387690000091
3) Water balance constraint
ΔVt＝(Qin,t-Qt-Qa,t-Qo,t)×Δt
In the formula: Δ VtFor the variation of the storage capacity of the reservoir in time t, m3；Qin,t、Qt、Qa,t、Qo,tWater and electricity warehousing, power generation, water abandonment and other water use flow m3S; Δ t is the length of the time period t, s.
4) Waste water restraint
0≤Qa,t≤Qin,t
5) Water level restraint
Zs≤Zt≤Zz
In the formula: ztThe reservoir water level is time t, m; zs、ZzThe dead water level and the normal water storage level m of the reservoir are respectively.
6) Capacity constraint
Vs≤Vt≤Vz
In the formula: vtThe time period t is the storage capacity of the reservoir, m3；Vs、VzRespectively corresponding to the dead reservoir and the normal water storage level, m3。
7) Confinement of vibration region
Figure BDA0003152387690000092
In the formula:
Figure BDA0003152387690000093
and respectively corresponding upper and lower output limits MW of the hydropower station vibration area j in the time period t.
S1: forecasting the wind-solar output condition and acquiring the flow condition, determining scheduling time intervals, reserving the hydropower scheduling capacity for each time interval, and calculating the maximum hydropower generation capacity of each time interval after the scheduling capacity is reserved;
s2: determining all operation schemes, calculating the average output force and output force fluctuation of the schemes, and calculating a target function value;
s3: judging whether all the operation schemes are traversed, if not, returning to S2, and if so, selecting the scheme meeting the requirement;
s4: and outputting all the selectable scheduling schemes.
The invention aims to solve the problem that the condition of deviation exists between the formulation of a dispatching plan and the actual condition, the influence of the current prediction technology exists, and the wind power and photovoltaic power generation predictions have errors, so that the deviation exists between the dispatching plan and the actual condition.
The invention provides a method for reserving the scheduling capability of the electric power, which aims to reduce the deviation between a plan and actual operation and enhance the reliability of the scheduling plan, and takes the problem that the scheduling operation plan has deviation with the actual operation under the prediction error into consideration.
Although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that various changes in the embodiments and/or modifications of the invention can be made, and equivalents and modifications of some features of the invention can be made without departing from the spirit and scope of the invention.

Claims (7)

1. A method for solving the scheduling plan deviation of a wind-solar-water complementary power generation system is characterized by comprising the following steps: the method comprises the following steps:
firstly, acquiring wind power and photoelectric prediction error levels in a current complementary system;
predicting wind and light power output conditions in day-ahead scheduling and reserving power and electricity scheduling capability;
and thirdly, making a day-ahead scheduling plan.
2. The method for solving the scheduling plan deviation of the wind, light and water complementary power generation system according to claim 1, wherein: in the first step, the wind power error level calculation method in the current complementary system comprises the following steps:
Figure FDA0003152387680000011
in the formula: x is the number oftThe maximum prediction error of the wind power in the t time period is obtained according to historical data;
Figure FDA0003152387680000012
predicting wind power output MW for a historical t period;
Figure FDA0003152387680000013
actual wind power output, MW, for a corresponding time period t;
the photoelectric error level calculation method in the current complementary system comprises the following steps:
Figure FDA0003152387680000014
in the formula: y istThe maximum photoelectric prediction error in the t time period is obtained according to historical data;
Figure FDA0003152387680000015
predicting the photoelectric output power MW for the historical t period;
Figure FDA0003152387680000016
corresponding to the actual photoelectric output, MW, during the period t.
3. The method for solving the scheduling plan deviation of the wind, light and water complementary power generation system according to claim 1, wherein: in the second step, the method for predicting the wind and light power output situation and reserving the hydropower dispatching capacity in the day-ahead dispatching comprises the following steps:
Figure FDA0003152387680000017
Figure FDA0003152387680000018
in the formula:
Figure FDA0003152387680000019
reserving scheduling capacity, MW, for the hydropower station maximum in the time period t;
Figure FDA00031523876800000110
respectively predicting output and MW for the time period t wind power and the photoelectric day ahead;
Figure FDA00031523876800000111
water installed capacity, MW;
Figure FDA00031523876800000112
the maximum power generation capacity of hydropower, MW, is time period t.
4. The method for solving the scheduling plan deviation of the wind, light and water complementary power generation system according to claim 1, wherein: in the third step, the day-ahead scheduling plan formulation comprises model establishment and model solution; the model establishment comprises the establishment and normalization of a complementary system average output maximum and output fluctuation minimum objective function and constraint conditions.
5. The method for solving the scheduling plan deviation of the wind, light and water complementary power generation system according to claim 4, wherein: the maximum target function of the average output of the complementary system is as follows:
Figure FDA0003152387680000021
Figure FDA0003152387680000022
in the formula: i is1For maximum system average output, MW;
Figure FDA0003152387680000023
mean contribution, MW, to the system; n is a radical ofh,t、Np,t、Nw,tThe water power, the photoelectric power and the wind power output and MW are respectively in the time period t;
the minimum objective function of the output fluctuation of the complementary system is as follows:
I2＝min F
Figure FDA0003152387680000024
in the formula: i is2To minimize output fluctuation, MW; f is system output fluctuation, MW; n is a radical oftThe output of the complementary system in the time period t, MW;
the normalization method of the maximum target function of the average output of the complementary system comprises the following steps:
Figure FDA0003152387680000025
in the formula: l is the utilization rate of the generating capacity;
Figure FDA0003152387680000026
respectively available wind and light output and MW in a time period t;
the normalization method of the objective function with the minimum output fluctuation of the complementary system comprises the following steps:
Figure FDA0003152387680000031
in the formula: and S is the output stability of the complementary system.
6. The method for solving the scheduling plan deviation of the wind, light and water complementary power generation system according to claim 4, wherein: the constraint conditions are as follows: system constraints, wind and light resource constraints and hydropower constraints;
the system constraints include power balance and power balance;
the wind-solar resource constraint comprises: output constraint and energy abandon constraint;
the hydro-electrical constraints include: scheduling capability constraint, output constraint, water balance constraint, water abandoning constraint, water level constraint, reservoir capacity constraint and vibration area constraint.
7. The method for solving the scheduling plan deviation of the wind, light and water complementary power generation system according to claim 4, wherein: the model solving steps are as follows:
s1: forecasting the wind-solar output condition and acquiring the flow condition, determining scheduling time intervals, reserving the hydropower scheduling capacity for each time interval, and calculating the maximum hydropower generation capacity of each time interval after the scheduling capacity is reserved;
s2: determining all operation schemes, calculating the average output force and output force fluctuation of the schemes, and calculating a target function value;
s3: judging whether all the operation schemes are traversed, if not, returning to S2, and if so, selecting the scheme meeting the requirement;
s4: and outputting all the selectable scheduling schemes.
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Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20110282601A1 (en) * 2011-07-25 2011-11-17 Hoff Thomas E Computer-Implemented System And Method For Estimating Power Data For A Photovoltaic Power Generation Fleet
CN108596525A (en) * 2018-06-29 2018-09-28 国家电网有限公司 The cold and hot micro- energy net robust Optimization Scheduling electrically provided multiple forms of energy to complement each other
CN109449971A (en) * 2018-10-29 2019-03-08 国网甘肃省电力公司 A kind of multiple target electric power system source lotus interaction Optimization Scheduling of new energy consumption
CN109858173A (en) * 2019-02-18 2019-06-07 华中科技大学 A kind of multiple target tangent method of wind-light-water complementary electricity-generating system combined dispatching
CN110782363A (en) * 2019-08-15 2020-02-11 东南大学 AC/DC power distribution network scheduling method considering wind power uncertainty
CN112671040A (en) * 2021-01-11 2021-04-16 华北电力大学 Day-ahead optimal scheduling method of multi-energy complementary system considering maximum new energy consumption

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20110282601A1 (en) * 2011-07-25 2011-11-17 Hoff Thomas E Computer-Implemented System And Method For Estimating Power Data For A Photovoltaic Power Generation Fleet
CN108596525A (en) * 2018-06-29 2018-09-28 国家电网有限公司 The cold and hot micro- energy net robust Optimization Scheduling electrically provided multiple forms of energy to complement each other
CN109449971A (en) * 2018-10-29 2019-03-08 国网甘肃省电力公司 A kind of multiple target electric power system source lotus interaction Optimization Scheduling of new energy consumption
CN109858173A (en) * 2019-02-18 2019-06-07 华中科技大学 A kind of multiple target tangent method of wind-light-water complementary electricity-generating system combined dispatching
CN110782363A (en) * 2019-08-15 2020-02-11 东南大学 AC/DC power distribution network scheduling method considering wind power uncertainty
CN112671040A (en) * 2021-01-11 2021-04-16 华北电力大学 Day-ahead optimal scheduling method of multi-energy complementary system considering maximum new energy consumption

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
张歆蒴等: "大型风光水混合能源互补发电系统的优化调度研究" *
闻昕等: "考虑预测不确定性的风–光–水多能互补系统调度风险和效益分析" *

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