CN116205345A - Optimal scheduling method and system considering wind-solar prediction and maintenance plan - Google Patents
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Abstract
The invention belongs to the field of power system dispatching, and particularly relates to an optimal dispatching method and system considering wind-solar prediction and maintenance planning, wherein the method comprises the following steps: s1, acquiring historical operation data of an electric power system, unit parameters of the electric power system and an initial overhaul plan; s2, predicting a wind power output curve; s3, predicting a photovoltaic output curve; s4, establishing a model; s5, obtaining a unit overhaul plan and a scheduling strategy in the system. According to the invention, the randomness of new energy output, the economy of maintenance plan and the operation characteristics are fully considered, on the basis of accurately predicting wind-solar output, the cooperative optimization scheduling model considering the maintenance plan is established, so that the cooperative operation of different energy sources of wind, solar and fire is realized while the electric power and electric quantity balance requirement of the system is met, the energy utilization efficiency is improved, and the purpose of economic and stable operation of the system is achieved by the optimal scheduling scheme with the minimum cost while the constraint of the maintenance plan of the system is met.
Description
Technical Field
The invention belongs to the field of power system dispatching, and particularly relates to an optimal dispatching method and system considering wind-solar prediction and maintenance planning.
Background
With the reduction of non-renewable resources worldwide, clean energy sources such as wind, light and the like are connected in a large scale, however, the output has the characteristics of randomness and fluctuation, so that a great challenge is brought to the stable operation of a power system, wind and light prediction becomes an important way for solving the problem currently, the use efficiency of wind and light power generation is related, and the wind and light power generation system is an important foundation for realizing stable and reliable grid connection of wind and light.
In a novel power system of large-scale and high-proportion new energy sources, the operation of multiple types of power sources such as wind, light, fire and the like has the difference and complementarity, and a reasonable scheduling scheme is formulated according to the coordination and complementation effects of the multiple energy sources, so that the risk brought by the uncertainty of the output of the new energy sources to the power and electricity balance of the system can be effectively reduced; in addition, the establishment of the maintenance plan directly influences the maximum available power generation power of the unit, and indirectly determines the power supply capacity of the system.
At present, a series of researches are developed for the operation optimization of a novel power system of a large-scale and high-proportion new energy source by a plurality of scholars, but most of the researches are based on a given overhaul plan to carry out the optimized scheduling of a wind-light-fire system, so that the optimization space of the problem is limited to a certain extent, meanwhile, the randomness and the fluctuation of the output of the new energy source such as wind-light are ignored, the energy utilization rate is low, and the formulated optimized scheduling plan is unreasonable.
In this regard, the invention provides the optimal scheduling method and the optimal scheduling system which can fully consider the randomness of wind-light output and the rationality of maintenance plan, consider the randomness and the fluctuation of the output of new energy sources such as wind-light and the like, and improve the energy utilization rate.
Disclosure of Invention
In order to solve or improve the problem that the optimized scheduling of the system in the background art ignores randomness and fluctuation of new energy output such as wind and light, so that the energy utilization rate is low, and the formulated optimized scheduling plan is unreasonable, the invention provides an optimized scheduling method considering wind and light prediction and maintenance plan, which comprises the following specific technical scheme:
the invention provides an optimized scheduling method considering wind-solar prediction and maintenance planning, which comprises the following steps:
s1, acquiring historical operation data of an electric power system, unit parameters of the electric power system and an initial overhaul plan;
s2, predicting a wind power output curve according to the data of the S1;
s3, predicting a photovoltaic output curve according to the data of the S1;
s4, establishing a collaborative optimization scheduling model considering the maintenance plan;
and S5, inputting the wind power output curve, the photovoltaic output curve, the power system operation data and the initial overhaul plan into a collaborative optimization scheduling model considering the overhaul plan, and obtaining the overhaul plan and the scheduling strategy of the unit in the system.
Preferably, the parameters of the power system are mainly parameters of a thermal power generating unit; the power system operation data comprise a system annual load curve and wind and light historical operation data.
Preferably, the predicted wind power output curve mainly comprises historical data processing and wind power prediction model establishment.
Preferably, the wind power historical data processing mainly comprises the steps of selecting wind power generation historical data, performing simple data processing, and correcting and filling abnormal and lost data.
Preferably, the wind power prediction model is as follows:
wherein, K (·) is a kernel function; h is the window width, also known as the smoothing factor; n is the sample size; qw1, qw2, …, qwn are n sample values of qw;
the selection method of the optimal wide window h comprises the steps of selecting 2 different kernel functions, and establishing a model by taking integral variance as an objective function to obtain the optimal window width:
substituting the optimal wide window into the kernel density estimation function to obtain the probability density of the wind power electric quantity, and combining a random sampling method to obtain a predicted wind power output curve.
Preferably, the predicted photovoltaic output curve mainly considers that the output level of a photovoltaic power generation system is directly affected by solar radiation, selects average output of photovoltaic days as a weather index, takes typical weather fine days, cloudy days and rainy days as a clustering center, adopts an FCM clustering algorithm for clustering, and represents the occurrence probability of various weather in corresponding time intervals by average membership:
wherein p is j Probability of occurrence for the j-th type of weather; n (N) j The number of samples for the j-th type of weather; u (u) ij The membership of sample i with respect to cluster center j.
And combining the occurrence probabilities of various weather to obtain a photovoltaic output curve.
Preferably, the collaborative optimization scheduling model considering the maintenance plan mainly comprises an objective function and constraint conditions aiming at minimizing the total cost of system operation and maintenance plan adjustment cost.
Preferably, the system operation cost comprises operation cost of the thermal power unit, start-stop cost of the thermal power unit, overhaul cost of the thermal power unit and wind-solar energy discarding punishment cost.
Preferably, the constraint conditions of the collaborative optimization scheduling model considering the overhaul plan comprise overhaul constraints, unit operation constraints and system operation constraints.
The invention also provides an optimized dispatching system considering wind-light prediction and maintenance planning, which comprises an optimized dispatching method adopting the optimized dispatching method considering wind-light prediction and maintenance planning, a data acquisition module, a wind-light output prediction module and a calculation dispatching module;
the data acquisition module is used for acquiring historical operation data of the power system, unit parameters of the power system and an initial overhaul plan;
the wind-light output prediction module stores a wind-light output prediction model; the wind-light output prediction model is used for predicting a wind-light output curve based on wind-light historical data;
the calculation scheduling module stores a collaborative optimization scheduling model considering the overhaul plan; the collaborative optimization scheduling model considering the overhaul plan calculates the start-stop state, the output level and the overhaul plan of the unit in each hour of the unit in the system, thereby completing the optimization scheduling considering the overhaul plan of the unit.
The beneficial effects of the invention are as follows: compared with the prior art, the optimal scheduling method and system for considering wind-light prediction and maintenance plans realize accurate prediction of wind-light output based on the wind-light output prediction model, and the maintenance constraint of the system is fully established by establishing the collaborative optimization model considering the maintenance plans, so that the wind-light-fire unit output plan is determined, the electric power and electric quantity balance of the system is realized by utilizing the coordination of multiple energy sources, the energy supply potential of multiple energy sources in the system is fully exerted, the energy source rate of the system and the safe and economic operation level of the system are improved, and the development of a novel electric power system is promoted.
According to the invention, the randomness of new energy output, the economy of maintenance plan and the operation characteristics are fully considered, on the basis of accurately predicting wind-solar output, the cooperative optimization scheduling model considering the maintenance plan is established, so that the cooperative operation of different energy sources of wind, solar and fire is realized while the electric power and electric quantity balance requirement of the system is met, the energy utilization efficiency is improved, and the purpose of economic and stable operation of the system is achieved by the optimal scheduling scheme with the minimum cost while the constraint of the maintenance plan of the system is met.
Drawings
FIG. 1 is a collaborative optimization scheduling model framework of the present invention that considers a service plan;
FIG. 2 is a flow chart of an optimized scheduling method that takes into account wind-solar prediction and maintenance planning in accordance with the present invention;
FIG. 3 is a schematic diagram of an optimized dispatch system of the invention that takes into account wind and light predictions and maintenance plans.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are some, but not all embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
It should be understood that the terms "comprises" and "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It is also to be understood that the terminology used in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in this specification and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
It should be further understood that the term "and/or" as used in the present specification and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes such combinations.
In order to solve the problem that in the background art, the randomness and fluctuation of new energy output such as wind and light are ignored in the optimal scheduling of the system, so that the energy utilization rate is not high, and the formulated optimal scheduling plan is not reasonable enough, an optimal scheduling method and system considering wind and light prediction and maintenance plan are provided as shown in fig. 1 to 3, and the method and system comprise the following steps:
s1, acquiring historical operation data of an electric power system, unit parameters of the electric power system and an initial overhaul plan;
s2, predicting a wind power output curve according to the data of the S1;
s3, predicting a photovoltaic output curve according to the data of the S1;
s4, establishing a collaborative optimization scheduling model considering the maintenance plan;
and S5, inputting the wind power output curve, the photovoltaic output curve, the power system operation data and the initial overhaul plan into a collaborative optimization scheduling model considering the overhaul plan, and obtaining the overhaul plan and the scheduling strategy of the unit in the system.
As a specific implementation mode of the invention, the parameters of the electric power system are mainly parameters of the thermal power generating unit; the power system operation data comprise a system annual load curve and wind and light historical operation data.
As a specific implementation mode of the invention, the predicted wind power output curve mainly comprises the steps of processing historical data and establishing a wind power prediction model, correcting and filling abnormal and lost data based on wind power historical data, and establishing the wind power prediction model, wherein the specific steps are as follows:
wherein, K (·) is a kernel function; h is the window width, also known as the smoothing factor; n is the sample size; q w1 、q w2 、…、q wn Is q w Is a sample of n sample values;
the selection method of the optimal wide window h comprises the steps of selecting 2 different kernel functions, and establishing a model by taking integral variance as an objective function to obtain the optimal window width:
substituting the optimal wide window into the kernel density estimation function to obtain the probability density of the wind power electric quantity, and combining a random sampling method to obtain a predicted wind power output curve.
As a specific implementation mode of the invention, the predicted photovoltaic output curve mainly considers that the output level of a photovoltaic power generation system is directly influenced by solar radiation, the average output of a photovoltaic day is selected as a weather index, typical weather is a sunny day, cloudy and rainy day as a clustering center, FCM clustering algorithm is adopted for clustering, and the probability of occurrence of various weather in a corresponding period is represented by average membership, and the method is specifically as follows:
wherein p is j Probability of occurrence for the j-th type of weather; n (N) j The number of samples for the j-th type of weather; u (u) ij The membership of sample i with respect to cluster center j.
And combining the occurrence probabilities of various weather to obtain a photovoltaic output curve.
As a specific embodiment of the invention, a collaborative optimization scheduling model considering the maintenance plan is established according to the initial maintenance plan and the wind-light output curve, and the model aims at an objective function with the minimum total system running cost and maintenance plan adjustment cost and considers related constraint conditions.
The objective function of the collaborative optimization scheduling model considering the overhaul plan is specifically as follows:
wherein T is the total time period number in the scheduling period; t is scheduleA time period; g is the number of the thermal power generating unit; nth, g are the number of thermal power generating units; c (C) th,p,g,t The operation cost of the thermal power unit g in the period t is set; c (C) th,up,g,t 、C th,dn,g,t The starting and stopping costs of the thermal power generating unit g in the period t are respectively; c (C) th,M,g,t The overhaul cost of the thermal power unit g in the period t is set; c (C) r,t Punishment cost for wind and light energy discarding in t period; c (C) th,ad,g Punishment cost for the maintenance plan reported by the thermal power generating unit g is adjusted.
The running cost of the thermal power generating unit is as follows:
wherein a is g 、b g 、c g The secondary term, the primary term and the constant term coefficients of the running cost of the thermal power unit g are respectively; p is p th,g,t Active output of the thermal power unit g in the t period; i th,g,t The starting and stopping state of the thermal power generating unit g in the period t is a 0/1 variable, 1 represents starting and 0 represents stopping.
The starting and stopping costs of the thermal power are as follows:
C th,up,g,t ＝λ th,up,g α th,g,t (7)
C th,dn,g,t ＝λ th,dn,g β th,g,t (8)
wherein lambda is th,up,g 、λ th,dn,g The single start-up and shutdown costs of the thermal power generating unit g are respectively; alpha th,g,t 、β th,g,t The starting and stopping actions of the thermal power generating unit g in the period t are 0/1 variable, 1 represents the action, and 0 represents the non-action.
The overhaul cost of the thermal power generating unit is as follows:
C th,M,g,t ＝λ th,M,g,t X th,g,t (9)
wherein lambda is th,M,g,t The overhaul cost of the thermal power unit g in the period t is set; x is X th,g,t The overhaul state of the thermal power generating unit g in the t period is 0/1 variable, 1 represents overhaul, and 0 represents non-overhaul.
The thermal power overhaul adjustment cost is as follows:
C th,ad,g ＝wy th,g (10)
wherein w is penalty cost of the thermal power unit maintenance plan adjusted; y is th,g Whether the maintenance plan of the thermal power generating unit g is the same as the reported time period is a 0/1 variable, 1 represents that the thermal power generating unit g is adjusted, and 0 represents that the thermal power generating unit g is not adjusted.
The wind and solar energy discarding penalty cost is as follows:
C r,t ＝λ r,t (p R,t -p r,t ) (11)
wherein lambda is r,t Punishment cost coefficients for the wind and light energy discarding at the t period; p is p R,t The total wind and light output is t time period; p is p r,t And the total power of the wind-solar network is t time period.
The constraint conditions comprise maintenance constraint, unit operation constraint and system operation constraint.
The total time period number of the actual overhaul of the unit is equal to the reported overhaul time period.
Wherein T is th,M,g The maintenance time reported by the thermal power generating unit g is obtained.
Once the maintenance is started, the maintenance cannot be interrupted and should be continued until the whole maintenance process is finished.
The service adjustment constraints are as follows:
X th,g,t -X th,g,t-1 ≥1-2y th,g t＝T th,st,g (14)
wherein T is th,st,g And the time period for starting overhaul of the thermal power generating unit is shown. When t=t th,st,g If X th,g,t 、X th,g,t-1 The values of (2) are "0-0", "0-1", "1-1", y th,g Only a value of 1 can be taken, namely, the reported maintenance plan is adjusted; if X th,g,t 、X th,g,t-1 Is "1-0", y since the optimization objective is to minimize the cost th,g And the value is 0, namely the reported maintenance plan is not adjusted.
When the unit is overhauled, the unit must be stopped; when the unit is not overhauled, 2 states of startup and shutdown exist:
I th,g,t ≤1-X th,g,t (15)
the unit operation constraint mainly relates to the start-stop state and the output range limitation.
Thermal power generating unit output upper and lower limit constraint:
P th,g,min I th,g,t ≤P th,g,t ≤P th,g,max I th,g,t (16)
wherein P is th,g,max 、P th,g,min The upper and lower limits of the output of the thermal power generating unit are respectively set.
Minimum start-up and shutdown constraint of thermal power generating unit:
in the method, in the process of the invention,
the continuous operation time of the g-th thermal power generating unit at the time t-1; />
The shortest continuous operation time of the thermal power generating unit is set; />
The method is characterized in that the shortest continuous shutdown time of the thermal power generating unit is provided; />
The continuous shutdown time of the g-th thermal power generating unit at the time t-1 is obtained.
Thermal power generating unit start-stop state and start-stop action constraint:
α th,g,t -β th,g,t ＝I th,g,t -I th,g,t-1 (19)
wind-light output constraint:
0≤P r,t ≤P R,t (20)
the system operation constraints need to satisfy the system power balance constraints.
Wherein P is L,t Is the total load of the system for period t.
As a specific embodiment of the present invention, referring to fig. 3, consider an optimized scheduling system for wind-solar prediction and maintenance planning, comprising: the wind-solar power generation system comprises a data acquisition module, a wind-solar power generation prediction module and a calculation scheduling module, wherein the data acquisition module, the wind-solar power generation prediction module and the calculation scheduling module are as follows:
the data acquisition module is used for acquiring historical operation data of the power system, unit parameters of the power system and an initial overhaul plan;
the wind-light output prediction module is used for realizing accurate prediction of a wind-light output curve according to the wind-light historical operation data and the established wind-light prediction model;
the calculation scheduling module is used for calculating the on-off state, the output level and the unit maintenance plan of a unit in the system according to the wind-light output curve and the system operation parameters and the established collaborative optimization scheduling model considering the maintenance plan, so that the optimization scheduling is completed and the electric power and electric quantity balance of the electric power system is realized;
in the calculation scheduling module, the collaborative optimization scheduling model considering the overhaul plan is shown in formulas (5) - (21).
And finally obtaining the economic dispatch plan of the wind, light and fire power system meeting the maintenance and operation constraint of the system after calculation.
Those of ordinary skill in the art will appreciate that the elements of the examples described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the elements of the examples have been described generally in terms of functionality in the foregoing description to clearly illustrate this interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
In the embodiments provided in this application, it should be understood that the division of units is merely a logic function division, and there may be other manners of division in practical implementation, for example, multiple units may be combined into one unit, one unit may be split into multiple units, or some features may be omitted.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the invention, and are intended to be included within the scope of the appended claims and description.
Claims (10)
1. An optimized scheduling method considering wind-solar prediction and maintenance planning is characterized by comprising the following steps:
s1, acquiring historical operation data of an electric power system, unit parameters of the electric power system and an initial overhaul plan;
s2, predicting a wind power output curve according to the data of the S1;
s3, predicting a photovoltaic output curve according to the data of the S1;
s4, establishing a collaborative optimization scheduling model considering the maintenance plan;
and S5, inputting the wind power output curve, the photovoltaic output curve, the power system operation data and the initial overhaul plan into a collaborative optimization scheduling model considering the overhaul plan, and obtaining the overhaul plan and the scheduling strategy of the unit in the system.
2. The optimal scheduling method considering wind-solar prediction and maintenance planning according to claim 1, wherein the method comprises the following steps: the parameters of the power system are mainly parameters of a thermal power generating unit; the power system operation data comprise a system annual load curve and wind and light historical operation data.
3. The optimal scheduling method considering wind-solar prediction and maintenance planning according to claim 1, wherein the method comprises the following steps: the predicted wind power output curve mainly comprises historical data processing and wind power prediction model establishment.
4. An optimized scheduling method considering wind-solar prediction and maintenance planning according to claim 3, characterized in that: the wind power historical data processing is mainly to select wind power generation historical data, perform simple data processing and correct and fill abnormal and lost data.
5. The optimal scheduling method considering wind-light prediction and maintenance planning according to claim 1, wherein the wind-light prediction model is as follows:
wherein, K (·) is a kernel function; h is the window width, also known as the smoothing factor; n is the sample size; q w1 、q w2 、…、q wn Is q w Is a sample of n sample values;
the selection method of the optimal wide window h comprises the steps of selecting 2 different kernel functions, and establishing a model by taking integral variance as an objective function to obtain the optimal window width:
substituting the optimal wide window into the kernel density estimation function to obtain the probability density of the wind power electric quantity, and combining a random sampling method to obtain a predicted wind power output curve.
6. The optimal scheduling method considering wind-solar prediction and maintenance planning according to claim 1, wherein the predicted photovoltaic output curve mainly considers that the output level of a photovoltaic power generation system is directly affected by solar radiation, average output of photovoltaic days is selected as a weather index, typical weather fine days, cloudy weather and rainy weather are used as a clustering center, FCM clustering algorithm is adopted for clustering, and the probability of occurrence of various weather in corresponding time periods is represented by average membership:
wherein p is j Probability of occurrence for the j-th type of weather; n (N) j The number of samples for the j-th type of weather; u (u) ij The membership of sample i with respect to cluster center j.
And combining the occurrence probabilities of various weather to obtain a photovoltaic output curve.
7. The optimal scheduling method considering wind-solar prediction and maintenance planning according to claim 1, wherein the method comprises the following steps: the collaborative optimization scheduling model considering the maintenance plan mainly comprises an objective function and constraint conditions aiming at minimizing the total system operation cost and maintenance plan adjustment cost.
8. The optimal scheduling method considering wind-solar prediction and maintenance planning according to claim 1, wherein the method comprises the following steps: the system operation cost comprises the operation cost of the thermal power unit, the start-stop cost of the thermal power unit, the overhaul cost of the thermal power unit and the wind-solar energy discarding punishment cost.
9. The optimal scheduling method considering wind-solar prediction and maintenance planning according to claim 1, wherein the method comprises the following steps: constraint conditions of the collaborative optimization scheduling model considering the overhaul plan comprise overhaul constraints, unit operation constraints and system operation constraints.
10. An optimized dispatching system considering wind-light prediction and maintenance plan is characterized in that: an optimized dispatching method which comprises an optimized dispatching method taking wind-light prediction and maintenance planning into consideration according to any one of claims 1-9, and further comprises a data acquisition module, a wind-light output prediction module and a calculation dispatching module;
the data acquisition module is used for acquiring historical operation data of the power system, unit parameters of the power system and an initial overhaul plan;
the wind-light output prediction module stores a wind-light output prediction model; the wind-light output prediction model is used for predicting a wind-light output curve based on wind-light historical data;
the calculation scheduling module stores a collaborative optimization scheduling model considering the overhaul plan; the collaborative optimization scheduling model considering the overhaul plan calculates the start-stop state, the output level and the overhaul plan of the unit in each hour of the unit in the system, thereby completing the optimization scheduling considering the overhaul plan of the unit.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117273413A (en) * | 2023-11-23 | 2023-12-22 | 中国电建集团贵阳勘测设计研究院有限公司 | Overhauling and arranging method for water-wind-solar-storage-base-regulated power supply unit |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117273413A (en) * | 2023-11-23 | 2023-12-22 | 中国电建集团贵阳勘测设计研究院有限公司 | Overhauling and arranging method for water-wind-solar-storage-base-regulated power supply unit |
| CN117273413B (en) * | 2023-11-23 | 2024-02-06 | 中国电建集团贵阳勘测设计研究院有限公司 | Overhauling and arranging method for water-wind-solar-storage-base-regulated power supply unit |
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