CN109494810B - Intermittent energy power station scheduling evaluation method and power-limiting distribution method for evaluation - Google Patents

Intermittent energy power station scheduling evaluation method and power-limiting distribution method for evaluation Download PDF

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CN109494810B
CN109494810B CN201710816901.1A CN201710816901A CN109494810B CN 109494810 B CN109494810 B CN 109494810B CN 201710816901 A CN201710816901 A CN 201710816901A CN 109494810 B CN109494810 B CN 109494810B
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power
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王建勋
徐斌
金龙云
熊健
张继权
申鸿伟
岳菁鹏
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Beijing Tsingsoft Technology Co ltd
State Grid Jilin Electric Power Corp
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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
    • H02J3/38—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
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    • 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
    • Y02E40/00—Technologies for an efficient electrical power generation, transmission or distribution
    • Y02E40/70—Smart grids as climate change mitigation technology in the energy generation sector
    • 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
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    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
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Abstract

The invention discloses a scheduling evaluation method of an intermittent energy power station, which comprises the following steps: step 1, selecting an evaluation index of an intermittent energy power station; the selected grid-connected performance evaluation indexes are divided into 3 dimensions: the method comprises the following steps of (1) predicting an electric energy index, a power station operation technical level index and a power station grid-connected level index; step 2, calculating and distributing the weight of the three latitude evaluation indexes by using a moment estimation optimization algorithm; step 3, establishing an intermittent energy power station scheduling index evaluation model according to the weight distribution in the step 2, and performing evaluation and scoring; the method comprises the steps of establishing a new energy grid-connected scheduling sequence evaluation model, distributing weights by a moment estimation optimization algorithm, sequencing grid-connected performance of each power station, and reasonably distributing the limited capacity share of each new energy power station on the basis of the sequencing. The method has a positive guiding effect on improving the operating technical level of the intermittent energy power station.

Description

Intermittent energy power station scheduling evaluation method and power-limiting distribution method for evaluation
Technical Field
The invention relates to the technical field of short-term power grid dispatching of a power system, in particular to an intermittent energy power station dispatching evaluation method and a power-limiting distribution method for the evaluation.
Background
As the proportion of intermittent energy sources in the power grid becomes greater, intermittent energy sources have become one of the main power sources of the power grid. However, the technical level of the intermittent energy source as a novel power source is not mature, and the management mode is not completely determined, so that the technical level and the operation level of the existing intermittent energy source power station are different, and a lot of difficulties are brought to the operation of a power grid dispatching mechanism. In order to better ensure the power balance of the power grid, intermittent energy sources must be brought into the scheduling plan management of the power grid, and the intermittent energy source power prediction of a scheduling end mainly focuses on the total output of the full-grid intermittent energy sources so as to participate in the system balance; in order to ensure the accuracy of the intermittent energy power prediction of the whole network of the dispatching terminal and strengthen the operation management of the intermittent energy power station, the intermittent energy power station is required to also carry out the intermittent energy power prediction and report the prediction result. In order to promote the improvement of the technical level of the intermittent energy power station, the requirements for evaluating the prediction result and the grid-connected performance are provided.
Disclosure of Invention
Aiming at the problems, the invention provides an intermittent energy power station scheduling evaluation method and a power limiting distribution method for the evaluation, aiming at the process that the intermittent energy power station participates in short-term scheduling, the sequencing of the grid-connected performance of each power station is realized by establishing an intermittent energy grid-connected scheduling sequence evaluation model and distributing the weight by a moment estimation optimization algorithm, and the power limiting capacity share of each intermittent energy power station is reasonably distributed on the basis of the sequencing. The method has positive guiding effect on solving the problem of intermittent energy consumption and improving the technical level of intermittent energy power station operation, has positive guiding effect on improving the technical level of intermittent energy power station operation, and can effectively solve the problem in the background technology.
In order to achieve the purpose, the invention provides the following technical scheme: the scheduling evaluation method of the intermittent energy power station comprises the following steps:
step 1, selecting an evaluation index of an intermittent energy power station; the selected grid-connected performance evaluation indexes are divided into 3 dimensions: the method comprises the following steps of (1) predicting an electric energy index, a power station operation technical level index and a power station grid-connected level index;
step 2, calculating and distributing the weight of the three latitude evaluation indexes by using a moment estimation optimization algorithm;
and 3, establishing an intermittent energy power station scheduling index evaluation model according to the weight distribution in the step 2, and performing evaluation and scoring.
As a preferred technical solution of the present invention, the electric energy prediction index in step 1 includes:
the accuracy of the prediction is improved by the method,
Figure BDA0001405293720000021
wherein: r is1To predict curve accuracy; pMkIs the actual average power over a period k; pPkPredicted average power for a period k; n is the total number of daily assessment time periods (96 points are taken to subtract assessment-free points); cap is the starting capacity of the station;
the monthly (yearly) average intermittent energy source prediction curve accuracy (%) is an arithmetic mean of the daily average prediction curve accuracy;
the yield of the product is predicted to be high,
Figure BDA0001405293720000022
wherein:
Figure BDA0001405293720000031
Figure BDA0001405293720000032
the monthly average intermittent prediction curve accuracy (%) is the arithmetic mean of the daily average prediction accuracy;
the reporting rate is predicted, and the reporting rate is predicted,
Figure BDA0001405293720000033
wherein:
dsdays for successful data transmission; dcCalendar days;
the power station operation level indexes in the step 1 comprise:
active control capability r4，
Figure BDA0001405293720000034
Reactive power control capability r5，
Figure BDA0001405293720000035
Low voltage ride through capability r6，
Figure BDA0001405293720000036
And the power station grid-connected level index in the step 1 is as follows: including yesterday power limit, month accumulated power limit, and power station execution plan condition in grid-connected period,
yesterday power limit r7,
Figure BDA0001405293720000037
Wherein, Plim(k) A power limit for a kth period;
monthly accumulated power limit r8,
Figure BDA0001405293720000038
Wherein r is7(T) is the daily electricity limit, T is the number of days elapsed in the month;
planned execution rate r9
r9＝QMK/QK*100％
Wherein Q isMKActual grid-connected electric quantity; qKTo plan grid-connected electricity quantity.
As a preferred technical scheme of the present invention, the specific operation of performing weight calculation and distribution on the evaluation index by the moment estimation optimization algorithm in step 2 is to select an integrated assignment method for improving subjective and objective weights based on a moment estimation theory, so as to achieve the objective weighting and subjective guidance of decision making and objective index evaluation.
First, the objective and subjective weighting plan,
setting m evaluation indexes, each evaluation index di(1. ltoreq. i.ltoreq.m) with q weights, wiThe weight of each index is represented by:
setting n subjective weighting evaluation rules, and setting the subjective weight set of each index determined according to each subjective weighting rule as follows:
Ws＝{wsil 1 is not less than s is not less than n,1 is not less than i is not less than m, and
Figure BDA0001405293720000041
satisfy the requirement of
Figure BDA0001405293720000042
wsi≥0。
After the decision matrix is normalized, weighting is carried out on the evaluation indexes by q-n objective weighting methods to obtain an objective weight set which is as follows:
Wb＝{wbii n +1 is not less than b and not more than q,1 is not less than i and not more than m, and
Figure BDA0001405293720000043
satisfy the requirement of
Figure BDA0001405293720000044
wbi≥0。
Second, the parameter estimation of the combining weights,
according to the basic idea of moment estimation, each evaluation index di(1 ≦ i ≦ m), the expectation of subjective weight and objective weight is:
Figure BDA0001405293720000051
wherein the subjective and objective weighting coefficients alpha of each indexi、βiComprises the following steps:
Figure BDA0001405293720000052
for the evaluation indexes in the multi-index decision matrix, it can be considered that one sample is taken from 2 populations respectively, and the basic idea of the moment estimation theory is also adopted, so that the following can be obtained:
Figure BDA0001405293720000053
and third, the optimization objectives of the combining weights,
the q weights of each evaluation index are formed by sampling subjective weights and objective weights, so that w is satisfiediThe deviation from its q subjective-objective weights is minimal:
Figure BDA0001405293720000054
in the formula, w is more than or equal to 0siLess than or equal to 1; i is more than or equal to 1 and less than or equal to m, alpha is a subjective weight coefficient, and beta is an objective weight coefficient.
For all indexes, the weight optimization goal can be:
Figure BDA0001405293720000055
and converting multi-target optimization into single-target optimization by an equal-weight linear weighting method, so that an optimal combined weight vector based on a plurality of subjective and objective evaluation indexes is realized:
Figure BDA0001405293720000061
as a preferable technical scheme of the invention, the intermittent energy power station dispatching index model in the step 3 is a half-ladder model or an integer model, the half-ladder model comprises a half-ladder model,
Figure BDA0001405293720000062
Figure BDA0001405293720000063
wherein a and b are thresholds of the model, and x is a magnitude of the scoring parameter;
ladder model
Figure BDA0001405293720000064
Figure BDA0001405293720000071
Wherein a and b are thresholds of the model, and x is a magnitude of the scoring parameter;
the integer model can be expressed as
f(x)＝C1x，C1Represents a constant other than 0;
all of the above-mentioned f (x) represent dependent variables, and all of the above-mentioned x represent independent variables.
The invention also provides a power limiting distribution method of the intermittent energy power station, which comprises the following steps,
the method comprises the following steps that 1, priority scheduling sequencing of the intermittent power stations is obtained through evaluation indexes of the intermittent power stations;
step 2, obtaining the electricity-limiting power distribution coefficient of each power station according to the priority scheduling sequence in the step 1;
and 3, distributing the required electricity limiting power according to the principle that the electricity limiting reference capacity of the intermittent power station is in equal proportion.
As a preferred technical solution of the present invention, the method for calculating the power-limiting reference capacity of the power station in step 3 is as follows:
Figure BDA0001405293720000072
wherein the content of the first and second substances,
Figure BDA0001405293720000073
is the power-limited reference capacity of the wind farm i,Cifor the rated installed capacity, S, of the wind farm iiScoring results of grid-related performance assessment of wind power plant i, SavgAnd the average value of the grid-related performance assessment results of the whole grid wind power plant is obtained.
Compared with the prior art, the invention has the beneficial effects that:
aiming at the process that the intermittent energy power stations participate in short-term scheduling, the grid-connected performance of each power station is sequenced by establishing an intermittent energy grid-connected scheduling sequence evaluation model and distributing weights with a moment estimation optimization algorithm, and the limited capacity share of each intermittent energy power station is reasonably distributed on the basis of the sequencing. The method has a positive guiding effect on solving the problem of intermittent energy consumption and improving the operation technical level of the intermittent energy power station, and has a positive guiding effect on improving the operation technical level of the intermittent energy power station.
Drawings
Fig. 1 is a schematic diagram of a process of priority scheduling evaluation and power-limiting distribution of a new energy power station.
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 (b):
referring to fig. 1, the present invention provides a technical solution:
the scheduling evaluation method of the intermittent energy power station is characterized by comprising the following steps of:
step 1, selecting an evaluation index of an intermittent energy power station; the selected grid-connected performance evaluation indexes are divided into 3 dimensions: the method comprises the following steps of (1) predicting an electric energy index, a power station operation technical level index and a power station grid-connected level index;
step 2, calculating and distributing the weight of the three latitude evaluation indexes by using a moment estimation optimization algorithm;
step 3, establishing an intermittent energy power station scheduling index evaluation model according to the weight distribution in the step 2, and performing evaluation and scoring;
assuming that the information of grid-connected performance indexes of intermittent energy power stations in a certain area is shown in table 1, it can be known that the horizontal parameters of the power stations are different, although the prediction accuracy of the power station A is high, the reactive power control capability is poor, and the difficulty of reasonably distributing the limited electric quantity of each power station is objectively increased.
TABLE 1 basic data table of intermittent energy power station
Intermittent energy power station A B C D F
Prediction accuracy 96％ 93％ 91％ 89％ 92％
Predicted yield 83％ 91％ 94％ 96％ 95％
Prediction reporting rate 99％ 98％ 99％ 99％ 97％
Yesterday power limit 36 28 19 56 34
Monthly accumulated electricity limit 259 121 142 80 241
Rate of completion of plan 89％ 92％ 94％ 88％ 86％
Active control capability 1 0 1 1 1
Reactive power control capability 0 1 0 1 0
Low voltage ride through capability 1 0 1 0 1
Index weight calculation
Calculating according to an subjective and objective weight assignment method based on moment estimation in the text to obtain an index weight table of each power station:
TABLE 2 index weight assignment
Evaluation index Weight of
Prediction accuracy 27.03％
Predicted yield 9.38％
Prediction reporting rate 8.52％
Yesterday power limit 9.33％
Monthly accumulated electricity limit 8.78％
Rate of completion of plan 8.54％
Active control capability 8.46％
Reactive power control capability 11.43％
Low voltage ride through capability 8.48％
Power station priority scheduling evaluation
In view of the initial construction stage of the power station, in the debugging and optimizing stage, the model selects a half-lift model and an integer model.
TABLE 3 priority scheduling evaluation of intermittent energy power station
Intermittent energy power station A B C D F
Grid connection performance scoring 92.81 74.55 81.06 81.16 90.66
Intermittent energy power station power-limiting distribution
The method comprises the following steps that 1, priority scheduling sequencing of the intermittent power stations is obtained through evaluation indexes of the intermittent power stations;
step 2, obtaining the electricity-limiting power distribution coefficient of each power station according to the priority scheduling sequence in the step 1;
step 3, distributing the required electricity limiting power according to the principle that the electricity limiting reference capacity of the intermittent power station is in equal proportion;
in order to ensure the requirement of safe operation of the power grid, the output of new energy is reduced by 110 MW. According to the principle that the electricity-limiting reference capacity of each station is in equal proportion according to the electricity-limiting reference capacity of the new energy station, the proportion of the electricity-limiting distribution result of each station to the electricity-limiting reference capacity is
Figure BDA0001405293720000111
The power-limiting reference capacity of each station reflects the result of the power-related performance assessment, so that the final power-limiting distribution of the wind power plant with higher power-related performance assessment score is less, the fair and fair dispatching is reflected, the new energy station is stimulated to actively improve the power-related performance of the new energy station, and the running safety of the system is ensured.
Table 4 intermittent energy power station grid-connected electricity-limiting distribution meter
Figure BDA0001405293720000112
The working principle of the invention is as follows: the priority scheduling sequence of the new energy power stations is obtained through evaluation indexes of the new energy power stations, and the power limiting power distribution coefficient of each power station can be calculated while the grid-connected performance of each power station is visually known through scheduling. Under the condition that a batch of power stations face limitation, the limited total power is distributed to obtain the power required to be limited by each power station through a distribution coefficient, the power limit quantity of the power station with lower grid-connection performance score is more, and the power limit quantity of the power station with higher grid-connection performance score is lower or not. The method has the advantages that fairness and fairness of dispatching are reflected, new energy power stations are stimulated to strengthen self construction, grid connection performance is improved, and safety of system operation is effectively improved.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.

Claims (2)

1. The scheduling evaluation method of the intermittent energy power station is characterized by comprising the following steps of:
step 1, selecting an evaluation index of an intermittent energy power station; the selected grid-connected performance evaluation indexes are divided into 3 dimensions: the method comprises the following steps of (1) predicting an electric energy index, a power station operation technical level index and a power station grid-connected level index;
step 2, calculating and distributing the weight of the three dimensional evaluation indexes by using a moment estimation optimization algorithm;
step 3, establishing an intermittent energy power station scheduling index evaluation model according to the weight distribution in the step 2, and performing evaluation and scoring; the electric energy prediction index comprises:
the accuracy of the prediction is improved by the method,
Figure FDA0003537892110000011
wherein: r is1To predict curve accuracy; pMkIs the actual average power over a period k; pPkPredicted average power for a period k; n is the total number of daily assessment time periods, and 96 points are taken to subtract the assessment-free points; cap is the startup capacity of the station;
the average intermittent energy source prediction curve accuracy of the month or the year is the arithmetic mean of the daily average prediction curve accuracy;
the yield of the product is predicted to be high,
Figure FDA0003537892110000012
wherein:
Figure FDA0003537892110000013
Figure FDA0003537892110000014
the monthly average intermittent prediction curve accuracy is the arithmetic mean of the daily average prediction accuracy;
the reporting rate is predicted, and the reporting rate is predicted,
Figure FDA0003537892110000015
wherein:
dsdays for successful data transmission; dcCalendar days;
the power station operation level indexes in the step 1 comprise:
the active control capability r4 is,
Figure FDA0003537892110000021
reactive power control capability r5，
Figure FDA0003537892110000022
Low voltage ride through capability r6，
Figure FDA0003537892110000023
And the power station grid-connected level index in the step 1 is as follows: including yesterday power limit, month accumulated power limit, and power station execution plan condition in grid-connected period,
yesterday power limit r7,
Figure FDA0003537892110000024
Wherein, Plim(k) A power limit for a kth period;
monthly accumulated power limit r8,
Figure FDA0003537892110000025
Wherein r is7(T) is the daily electricity limit, T is the number of days elapsed in the month;
planned execution rate r9
r9＝QMK/QK*100％
Wherein Q isMKActual grid-connected electric quantity; qKGrid-connected electric quantity for planning;
in the step 3, the intermittent energy power station dispatching index model adopts a half-ladder model or an integer model, the half-ladder model comprises a half-ladder model,
Figure FDA0003537892110000031
wherein a and b are thresholds of the model, and x is a magnitude of the scoring parameter;
ladder model
Figure FDA0003537892110000032
Wherein a and b are thresholds of the model, and x is a magnitude of the scoring parameter;
the integer model is expressed as f (x) ═ C1x，C1Represents a constant other than 0;
all of the above-mentioned f (x) represent dependent variables, and all of the above-mentioned x represent independent variables.
2. The scheduling evaluation method for the intermittent energy power plant as claimed in claim 1, wherein: in the step 2, the moment estimation optimization algorithm performs weight calculation and distribution on the evaluation indexes, and an integrated assignment method for improving subjective and objective weights based on a moment estimation theory is selected, so that subjective guidance and objective index evaluation of decisions are taken into consideration, and subjective and objective weighting is integrated.
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