CN116260197B - Power grid peak load regulation and control method, system and computer equipment - Google Patents
Power grid peak load regulation and control method, system and computer equipment Download PDFInfo
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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
- H02J3/466—Scheduling the operation of the generators, e.g. connecting or disconnecting generators to meet a given demand
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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
- H02J3/003—Load forecast, e.g. methods or systems for forecasting future load demand
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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
- H02J3/008—Circuit arrangements for ac mains or ac distribution networks involving trading of energy or energy transmission rights
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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
- H02J3/04—Circuit arrangements for ac mains or ac distribution networks for connecting networks of the same frequency but supplied from different sources
- H02J3/06—Controlling transfer of power between connected networks; Controlling sharing of load between connected networks
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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
- H02J3/24—Arrangements for preventing or reducing oscillations of power in networks
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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
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/10—Power transmission or distribution systems management focussing at grid-level, e.g. load flow analysis, node profile computation, meshed network optimisation, active network management or spinning reserve management
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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
- 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]
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Abstract
The application relates to the technical field of smart power grids, and solves the technical problem that peak load regulation and control effects are poor due to low user responsiveness at a demand side, in particular to a power grid peak load regulation and control method, a power grid peak load regulation and control system and computer equipment, which comprise the following steps: acquiring a daily load prediction curve of all the detected electric equipment in the power system in the predicted daily; extracting all peak inflection points in the daily load prediction curve by adopting a second derivative method; comparing the load predicted value corresponding to the peak inflection point with a preset load threshold; if the load predicted value corresponding to at least one peak inflection point exceeds a preset load threshold, judging the predicted day as a peak day and executing the next step; otherwise, the predicted day is judged not to be the peak day, and peak load regulation is not needed. According to the peak electricity price determining method, the peak electricity price is determined according to the correlation between the load and the electricity price, the user responsiveness at the peak time period demand side is improved, meanwhile, the output force of each unit at the power generation side is regulated to provide peak load, and the regulation and control effect is improved.
Description
Technical Field
The application relates to the technical field of smart power grids, in particular to a method, a system and computer equipment for regulating peak load of a power grid.
Background
The peak load is a load when the power load supply is in tension, which causes the shortage of the standby capacity of the power system and endangers the safe and reliable operation of the system, so that the peak load needs to be transferred or reduced by a regulation and control means to improve the operation reliability of the power system.
At present, the research on peak load regulation is mainly based on a fully-open electric power market environment, and the power supply output of a power generation side is regulated so as to meet the power balance and smooth load curve of a power grid to the greatest extent, but when peak load occurs, the power grid power difference cannot be effectively stabilized due to insufficient power generation regulation capability, and the power generation side regulation cost is high, so that a regulation strategy for transferring or reducing the peak load by combining a demand response means appears on the market, and although the regulation mode achieves a certain effect in the foreign electric power market, the demand side regulation mode is still in a semi-open stage due to the development of the domestic electric power market, the time-of-use electricity price is mainly used, and the responsiveness of a demand side user is low, so that the peak load regulation effect is poor.
Disclosure of Invention
Aiming at the defects of the prior art, the application provides a method, a system and computer equipment for regulating peak load of a power grid, which solve the technical problem of poor peak load regulating effect caused by lower user responsiveness at a demand side.
In order to solve the technical problems, the application provides the following technical scheme: a method for regulating and controlling peak load of a power grid comprises the following steps:
s1, acquiring a daily load prediction curve of all measured electric equipment in a power system in a prediction day;
s2, extracting all peak inflection points in the daily load prediction curve by adopting a second derivative method, recording the number of the peak inflection points as n, and numbering the n peak inflection points in sequence according to time sequence;
s3, comparing the load predicted value corresponding to the peak inflection point with a preset load threshold;
if the load predicted value corresponding to at least one peak inflection point exceeds a preset load threshold, judging the predicted day as a peak day and executing the next step; otherwise, judging that the predicted day is not the peak day, and not needing to carry out peak load regulation;
s4, determining a daily peak period by adopting an adaptive step iteration method according to the daily load prediction curve;
s5, determining a total regulation strategy of the peak load of the power grid from two aspects of a power generation side and a demand side according to the peak period;
and S6, regulating and controlling the peak load of the power grid on a prediction day according to the total regulation and control strategy.
Further, the specific process of the step S3 includes the following steps:
s31, judging whether a load predicted value corresponding to a peak inflection point exceeds a preset load threshold, if the load predicted value corresponding to the peak inflection point exceeds the preset load threshold, resetting a counter m to be m+1, and setting an initial value of the counter m to be 0, otherwise, keeping the counter m unchanged;
s32, resetting the cycle iteration number i to be i+1, wherein the initial value of the cycle iteration number i is 0;
s33, judging whether the number of loop iteration times i is smaller than the number of peak inflection points n, returning to the step S31 if the number of loop iteration times i is smaller than the number of peak inflection points n, otherwise executing the step S34;
s34, judging whether the counter m is larger than or equal to 1, if the counter m is larger than or equal to 1, judging that the predicted day is the peak day, and executing the step S4, otherwise, judging that the predicted day is not the peak day, namely, not carrying out peak load regulation.
Further, the specific process of the step S4 includes the following steps:
s41, dividing the daily load prediction curve into a plurality of curve segments by taking a peak inflection point of which the load prediction value exceeds a preset load threshold value as a target point and taking valley inflection points on the left side and the right side of the peak inflection point as critical points;
s42, searching each curve segment by adopting an adaptive step iteration method to obtain a corresponding peak region;
s43, merging peak areas with intersections to obtain at least one daily peak period.
Further, the specific process of step S42 includes the following steps:
s421, obtaining load predicted values L and R respectively corresponding to the left critical point and the right critical point of the curve segment and a minimum value B of unit step length min ；
S422, judging whether the load predicted value L exceeds a preset load threshold, if so, marking a left critical point as a left boundary point of a corresponding peak area, otherwise, setting an initial value of a unit step length as half of a time interval length B between a target point of the curve section and the left critical point, and setting the target point as a starting point;
s423, extracting a load predicted value corresponding to a predicted point of a unit step length of the interval starting point along the descending direction, judging whether the load predicted value is larger than a preset load threshold, and if so, resetting the unit step length to bej represents the number of step resetting times, and judges whether the unit step is larger than the minimum value of the unit step, if yes, the predicted point is set as a new starting point and then returns to step S423, if no, the predicted point is marked as the left boundary point of the corresponding peak area;
if not, resetting the unit step length toj represents the number of step resetting times, and judges whether the unit step is larger than the minimum value of the unit step, if yes, the step S423 is returned, if not, the original starting point of the iteration is marked as the left boundary point of the corresponding peak area;
s424, the right boundary point of the peak area in the curve segment is determined by adopting the same principle of the steps S422 and S423.
Further, the specific process of step S5 includes the following steps:
s51, determining a power generation side regulation strategy for regulating peak load according to the start-stop time of the daily peak period;
s52, determining a demand side regulation strategy for regulating peak load according to the power generation side regulation strategy and the duration of the daily peak period.
Further, the specific process of step S51 includes the following steps:
s511, acquiring related parameters of minimum startup and shutdown time, climbing efficiency, power generation cost and line state of each unit in the power generation side;
s512, establishing a power generation side dispatching model by taking the lowest cost of the power generation side as a target and taking the starting and stopping time and climbing efficiency of a daily peak period as constraint conditions;
and S513, solving a power generation side dispatching model by adopting an interior point method to obtain a power generation side regulation strategy for regulating the start and stop of each unit on the power generation side.
Further, the specific process of step S52 includes the following steps:
s521, determining the real-time electricity price of the peak time period according to the power generation side regulation strategy;
and S522, optimizing the real-time electricity price according to the duration of the daily peak time period and an electricity fee rewarding and punishing mechanism to obtain the peak electricity price for regulating and controlling the demand side.
The technical scheme also provides a system for realizing the regulation method of the peak load of the power grid, which comprises the following steps:
the data acquisition module is used for acquiring daily load prediction curves of all the detected electric equipment in the power system in the prediction day;
the peak inflection point extraction module is used for extracting all peak inflection points in the daily load prediction curve by adopting a second derivative method, recording the number of the peak inflection points as n and numbering the n peak inflection points in sequence according to time sequence;
the peak day judging module is used for comparing the load predicted value corresponding to the peak inflection point with a preset load threshold;
if the load predicted value corresponding to at least one peak inflection point exceeds a preset load threshold, judging the predicted day as a peak day and executing the next step; otherwise, judging that the predicted day is not the peak day, and not needing to carry out peak load regulation;
the daily peak period dividing module is used for determining a daily peak period by adopting an adaptive step iteration method according to the daily load prediction curve;
the total regulation strategy determining module is used for determining the total regulation strategy of the peak load of the power grid from two aspects of a power generation side and a demand side according to the peak period of the day;
and the peak load regulation and control module is used for regulating and controlling the peak load of the power grid on a prediction day according to the total regulation and control strategy.
The technical scheme also provides computer equipment, which comprises a processor and a memory, wherein the memory is used for storing a computer program, and the method for regulating and controlling the peak load of the power grid is realized when the processor executes the computer program in the memory.
The application also provides computer equipment, which comprises a processor and a memory, wherein the memory is used for storing a computer program, and the processor realizes the regulation and control method of the peak load of the power grid when executing the computer program in the memory.
By means of the technical scheme, the application provides a method, a system and computer equipment for regulating peak load of a power grid, which at least have the following beneficial effects:
1. according to the method, peak inflection points of a daily load prediction curve are judged according to a preset load threshold, so that peak days are automatically detected in time, the output of each unit on the power generation side is adjusted according to the start-stop time of the daily peak period, the power difference of a power grid is stabilized, meanwhile, according to the correlation between the load and the electricity price, a peak electricity price policy is implemented in the daily peak period, an electricity fee rewarding and punishment mechanism is combined, the user responsiveness on the demand side is improved by using a price lever, the purpose of transferring and reducing peak loads of users is achieved, the power supply pressure on the power generation side in the peak period is reduced, the peak load regulation effect is improved, and further stable operation of a power system can be effectively ensured.
2. According to the peak point-of-inflection method, the peak inflection point of the load predicted value exceeding the preset load threshold is taken as the target point, and the peak point-of-inflection method is combined with the critical point, so that the peak point-of-moment point is obtained by performing binary search on the corresponding curve segment by adopting the self-adaptive step-length iteration method, the searching time for determining the peak area in the curve segment is greatly shortened, the dividing precision of the daily peak period is improved, the peak load regulation and control efficiency is improved, and the peak point-of-inflection method has higher social value and application prospect and is easy to popularize and apply.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute a limitation on the application. In the drawings:
FIG. 1 is a flow chart of a control method provided by the application;
FIG. 2 is a schematic diagram of a daily load prediction curve provided by the application;
FIG. 3 is a flow chart of a certain day spike period provided by the present application;
FIG. 4 is a schematic diagram of peak load control effects provided by the present application;
FIG. 5 is a block diagram of a control system according to the present application;
fig. 6 is a block diagram showing an internal structure of a computer device according to an embodiment of the present application.
In the figure: 10. a data acquisition module; 20. a peak inflection point extraction module; 30. a peak day determination module; 40. a daily peak period dividing module; 50. a total regulation strategy determining module; 60. and a peak load regulation module.
Detailed Description
In order that the above-recited objects, features and advantages of the present application will become more readily apparent, a more particular description of the application will be rendered by reference to the appended drawings and appended detailed description. Therefore, the realization process of how to apply the technical means to solve the technical problems and achieve the technical effects can be fully understood and implemented.
The present embodiment is presented in the following context, and is a specific implementation of a solution proposed for solving the actual problem existing in long-term operation of the power system.
As known, the daily electricity load has the law of higher daytime electricity consumption and lower night electricity consumption, and for a new energy power station, especially for wind power generation, the phenomenon that a large amount of electric energy is wasted at night and energy storage is in shortage in the daytime causes instability in power grid operation, the power output of a power generation side needs to be regulated for load regulation, but the power difference of the power grid cannot be effectively stabilized due to insufficient regulation capacity of the power generation side, and the regulation cost of the power generation side is higher.
In order to ensure stable operation of a new energy power station, a strategy of regulating and controlling loads through a demand side appears on the market, but since domestic power market development is still in a semi-open stage, a demand side regulation mode is still mainly based on time-sharing electricity price, and the existing method for formulating the time-sharing electricity price has the problems of being too subjective and insufficient in implementation effect analysis, so that the load transfer rate is lower, and further the regulation and control effect of peak loads is poor.
Examples
Referring to fig. 1-4, a specific implementation manner of the present embodiment is shown, in the present embodiment, by adjusting the output of each unit on the power generation side according to the start-stop time of the peak load on the day, and determining the peak electricity price according to the correlation between the load and the electricity price, and combining the electricity fee rewarding and punishing mechanism to intervene on the electricity consumption behavior of the user on the demand side, the purpose of improving the peak load regulation effect and ensuring the stable operation of the power system is achieved.
As shown in fig. 1, a method for regulating peak load of a power grid includes the following steps:
s1, acquiring a daily load prediction curve of all measured electric equipment in the power system in a prediction day.
Extracting a plurality of similar daily load data with most similar predicted daily characteristics from historical data of a metering automation system, carrying out normalization processing, predicting the load power in the predicted daily according to the plurality of similar daily load data after the normalization processing, and drawing daily load pre-load of all the detected electric equipment in the power system in the predicted dailyCurve Y is measured as shown in fig. 2. The prediction day feature may be described by a vector, i.e.: x= (X 1 ,x 2 ,…,x k ) The predicted daily feature vector X determines the shape of the daily load prediction curve Y for the predicted day.
The daily load prediction belongs to short-term load prediction, and refers to determining load data at a specific moment in the future under the condition of meeting a certain precision requirement by considering a plurality of factors such as the operation characteristic, capacity-increasing decision, meteorological conditions, date type, electricity price and the like of a power system, and the like, and the similar day refers to a historical day with higher similarity in terms of date type, meteorological conditions, electricity price and the like with the predicted day.
S2, extracting all peak inflection points in the daily load prediction curve by adopting a second derivative method, recording the number of the peak inflection points as n, and numbering the n peak inflection points in sequence according to time sequence.
The peak inflection points refer to points on the curve where the upward concave arc and the downward concave arc are separated, in this embodiment, all peak inflection points are obtained from the daily load prediction curve by adopting a second derivative method, as shown in fig. 2, the number n of all peak inflection points in the daily load prediction curve of the power system in a certain area is 5, and the peak inflection points are numbered as a, b, c, d and e in sequence according to a time sequence.
S3, comparing the load predicted value corresponding to the peak inflection point with a preset load threshold, if the load predicted value corresponding to at least one peak inflection point exceeds the preset load threshold, judging the predicted day as the peak day and executing the next step, otherwise, judging that the predicted day is not the peak day, namely, not carrying out peak load regulation. The specific process comprises the following steps:
s31, judging whether a load predicted value corresponding to a peak inflection point exceeds a preset load threshold, resetting a counter m to be m+1 if the load predicted value corresponding to the peak inflection point exceeds the preset load threshold, and setting an initial value of the counter m to be 0, wherein the counter m is unchanged if the load predicted value corresponding to the peak inflection point does not exceed the preset load threshold;
s32, resetting the cycle iteration number i to be i+1, wherein the initial value of the cycle iteration number i is 0;
s33, judging whether the number of loop iteration times i is smaller than the number of peak inflection points n, returning to the step S31 if the number of loop iteration times i is smaller than the number of peak inflection points n, otherwise executing the step S34;
s34, judging whether the counter m is larger than or equal to 1, if the counter m is larger than or equal to 1, judging that the predicted day is the peak day, and executing the step S4, otherwise, judging that the predicted day is not the peak day, namely, the peak load regulation is not needed, and ending the regulation.
In this embodiment, the load threshold is set to a load of 90% of the installed capacity of the grid system, for example, if the installed capacity of the grid system in a certain region is 7800MW, the load threshold is set to 7020MW, and as can be seen from fig. 2, the load predicted values corresponding to 5 peak inflection points are 6820, 7120, 7330, 7240 and 7100, respectively, where the load predicted values corresponding to peak inflection points b, c, d and e are all greater than 7020MW, so the predicted day is marked as a peak day and the next step is executed.
And S4, determining a daily peak period by adopting an adaptive step iteration method according to the daily load prediction curve. As shown in fig. 3, the specific process of determining the daily peak period includes the steps of:
s41, dividing the daily load prediction curve into a plurality of curve segments by taking a peak inflection point of which the load predicted value exceeds a preset load threshold value as a target point and taking valley inflection points on the left side and the right side of the peak inflection point as critical points.
In this embodiment, it is known through step S3 that the peak inflection points of the load predicted value exceeding the preset load threshold include four of b, c, d and e, and the daily load predicted curve can be divided into four curve segments Y by taking the four peak inflection points as the target points and the valley inflection points on the left and right sides of each peak inflection point as the critical points b 、Y c 、Y d 、Y e Curves between (1) - (2), (2) - (3), (3) - (4) and (4) - (5) are respectively corresponding in order.
S42, searching each curve segment by adopting an adaptive step iteration method to obtain a corresponding peak region.
S421, obtaining load predicted values L and R respectively corresponding to the left critical point and the right critical point of the curve segment, and a minimum value B of unit step length min 。
S422, judging whether the load predicted value L exceeds a preset load threshold, if so, marking the left critical point as the left boundary point of the corresponding peak area, otherwise, setting the initial value of the unit step length as half of the time interval length B between the target point of the curve section and the left critical point, and setting the target point as a starting point.
S423, extracting a load predicted value corresponding to a predicted point of a unit step length of the interval starting point along the descending direction, judging whether the load predicted value is larger than a preset load threshold, and if so, resetting the unit step length to bej represents the number of step resetting times, and judges whether the unit step is larger than the minimum value of the unit step, if yes, the predicted point is set as a new starting point and then returns to step S423, if no, the predicted point is marked as the left boundary point of the corresponding peak area;
if not, resetting the unit step length toj represents the number of step resetting times, and judges whether the unit step is greater than the minimum value of the unit step, if yes, the step S423 is returned, and if not, the original starting point of the iteration is marked as the left boundary point of the corresponding peak area.
S424, the right boundary point of the peak area in the curve segment is determined by adopting the same principle of the steps S422 and S423.
In the present embodiment, reference is made to FIG. 2 and a curve segment Y b The specific procedure for determining the peak region is described for the sake of example:
curve segment Y b The load predicted values corresponding to the left critical point (1) and the right critical point (2) are 6750MW and 7050MW respectively, firstly, the load predicted value 6750MW corresponding to the left critical point (1) is compared with the load threshold 7020MW, and as the load predicted value 6750MW corresponding to the left critical point (1) is smaller than the load threshold 7020MW, the initial value of the unit step is set to be 1 hour, and the target point b is taken as the starting point to extract the predicted point 9 minutes in the morning of the unit step at intervalsSince the load predicted value 6900MW corresponding to the predicted point 30 minutes at 9 am is smaller than the load threshold 7020MW, the unit step length is reset to 0.5 hour, the reset unit step length is equal to the unit step length minimum value, the predicted point b is taken as the starting point to extract the load predicted value 7040MW corresponding to the predicted point 10 minutes at 10 am of the interval unit step length, since the load predicted value 7040MW corresponding to the predicted point 10 minutes at 10 am is larger than the load threshold 7020MW, the unit step length is reset to 0.25 hour, and since the reset unit step length is smaller than the unit step length minimum value, the 10 minutes at am is marked as the curve segment Y b A left boundary point of the inner spike region;
since the load predicted value 7050MW corresponding to the right critical point (2) is greater than the load threshold 7020MW, the right critical point (2) is marked as a curve segment Y b And finally obtaining a curve segment Y according to the left boundary point and the right boundary point b A spike region within.
According to the method, the peak inflection point of the load predicted value exceeding the preset load threshold is taken as the target point and combined with the critical point, and the corresponding curve segment is subjected to binary search by adopting the self-adaptive step iteration method to obtain the peak moment point, so that the search time for determining the peak region in the curve segment is greatly shortened, the dividing precision of the daily peak period is improved, and the regulating and controlling efficiency and precision of the peak load are improved.
S43, merging peak areas with intersections to obtain at least one daily peak period.
And comparing boundary points of any two adjacent peak areas, merging peak areas with the same boundary point to obtain at least one peak union area, and obtaining a daily peak period according to the time corresponding to the left boundary point and the right boundary point of the peak union area.
For example, the daily load prediction curve shown in FIG. 2 contains two daily peak periods of 10:00-16:00 and 21:00-22:00, respectively.
And S5, determining a total regulation strategy of the peak load of the power grid from two aspects of a power generation side and a demand side according to the peak period of the day.
And S51, determining a power generation side regulation strategy for regulating peak load according to the start-stop time of the peak period of the day. The specific process for determining the power generation side regulation strategy comprises the following steps:
s511, acquiring related parameters of minimum on-off time, climbing efficiency, power generation cost and line state of each unit in the power generation side.
S512, a power generation side dispatching model is established by taking the lowest cost of the power generation side as a target and taking the starting and stopping time and the climbing efficiency of a daily peak period as constraint conditions.
In the present embodiment, the expression of the objective function that minimizes the power generation side cost is as follows:
in the above-mentioned method, the step of,indicating the running and maintenance costs of the kth generator with respect to its power output at time tIs a function of (2); />A function representing the transmission cost of the gamma-th line with respect to the active power flow of the line;wherein (1)>The flow of power from bus i to j and from bus j to i on line γ at time t is shown.
The expression in which the start-stop time of the daily peak period is a constraint condition is as follows:
wherein, the liquid crystal display device comprises a liquid crystal display device,indicating the time that the assembly k has been operated when it was ready to be shut down at time t, < >>For its corresponding peak time start time, +.>Indicating the time that the assembly k has been shut down when it is ready to start at time t, < >>The time is terminated for its corresponding spike instant.
The expression of the unit climbing efficiency constraint is as follows:
wherein RU k And RD (RD) k The up-hill and down-hill limit values of the unit k are indicated, respectively.
And S513, solving a power generation side dispatching model by adopting an interior point method to obtain a power generation side regulation strategy for regulating the start and stop of each unit on the power generation side.
And solving a dispatching model at the power generation side by adopting an interior point method to obtain dispatching instructions for regulating the start and stop of each unit at the power generation side and sending the dispatching instructions to a unit control device at the power generation side, and controlling the switching action of each unit at the power generation side to realize the regulation and control of peak load.
According to the embodiment, the power supply output of each unit in the power generation side is regulated according to the start-stop time of the daily peak period, so that the power balance and the smooth load curve of the power grid are met to the maximum extent, and the stable operation of the power system is ensured.
S52, determining a demand side regulation strategy for regulating peak load according to the power generation side regulation strategy and the duration of the daily peak period.
S521, determining the real-time electricity price of the peak period of the day according to the power generation side regulation strategy.
The start-stop plan of each unit on the power generation side in the load regulation period can be known through the power generation side regulation strategy, the optimal dynamic power flow of system communication at each moment is solved by adopting an interior point method, so that a corresponding Lagrange multiplier is obtained, at the moment, the marginal price is the real-time electricity price of a daily peak period, and if a user k is connected to a bus i, the expression of the real-time electricity price of the daily peak period is as follows:
in the above-mentioned method, the step of,representing the total cost of power transmission and distribution of the bus l at the moment t, < >>The total cost of power generation of the bus bar l at time t is indicated,representing the apportionment ratio of class k users.
And S522, optimizing the real-time electricity price according to the duration of the daily peak period and an electricity fee punishment mechanism to obtain the peak electricity price for regulating and controlling the demand side.
The method is characterized in that the economic benefit is maximum and the daily maximum load is minimum, the duration of the daily peak period and the electric charge rewarding and punishing mechanism are used as constraint conditions, a multi-objective optimization algorithm is adopted to optimize the real-time electricity price, and an optimization model expression is as follows:
in the above, delta is more than or equal to 1 and less than or equal to N T And delta is an integer representing the time cell number in the peak day; p (dp) 1 ,dp 2 ) δ The load at the delta-th hour in peak day is expressed as dp 1 ,dp 2 If dp is the function of 1 ,dp 2 All are 0, the load condition of the peak electricity price under the condition of not implementing is indicated;the interrupt load amount at the peak time delta for the z-th interruptible load is shown.
In this embodiment, the electric charge rewarding mechanism refers to that if the actual electricity consumption of the user in the peak period is less than or equal to the average electricity consumption of the period corresponding to the non-peak day that occurs for a period of time (for example, several weeks) closest to the peak day, the electric charge is proportionally returned according to the average electricity consumption.
And S6, regulating and controlling the peak load of the power grid on a prediction day according to a total regulation and control strategy.
In the power market environment, the fluctuation of electricity price can influence the load, and the fluctuation of the load can influence the electricity price, so that the power generation side regulation strategy and the peak electricity price are used as peak load total regulation strategies, the lever principle is utilized to regulate the output of each unit in a peak period, the electricity price is improved at the same time, as shown in fig. 4, the load in the peak period after regulation is obviously reduced, and the load is transferred, so that the aim of transferring a user and reducing peak load is fulfilled, the power supply pressure of a power grid in the power supply peak period is reduced, and the stable operation of a power system is ensured.
Referring to fig. 5, the present embodiment further provides a system for implementing the method for controlling peak load of the power grid, including:
the data acquisition module 10 is used for acquiring a daily load prediction curve of all the tested electric equipment in the power system in the predicted daily;
the peak inflection point extracting module 20 is configured to extract all peak inflection points in the daily load prediction curve by using a second derivative method, record the number of the peak inflection points as n, and number the n peak inflection points in sequence according to time sequence;
the peak day judging module 30 is configured to compare a load predicted value corresponding to a peak inflection point with a preset load threshold; if the load predicted value corresponding to at least one peak inflection point exceeds a preset load threshold, judging the predicted day as a peak day and executing the next step; otherwise, judging that the predicted day is not the peak day, and not needing to carry out peak load regulation;
a daily peak period dividing module 40, configured to determine a daily peak period according to a daily load prediction curve by adopting an adaptive step iteration method;
the total regulation strategy determining module 50 is configured to determine a total regulation strategy of the peak load of the power grid from two aspects of a power generation side and a demand side according to a peak period of a day;
the peak load regulation module 60 is configured to regulate peak load of the power grid on a predicted day according to a total regulation strategy.
According to the method, peak inflection points of a daily load prediction curve are judged according to a preset load threshold, so that peak days when peak loads occur are automatically detected in time, peak inflection points of load prediction values exceeding the preset load threshold are used as target points, and a corresponding curve segment is subjected to binary search by adopting a self-adaptive step iteration method to obtain peak moment points, so that the searching time of peak areas in the curve segment is greatly shortened, the dividing precision of daily peak time periods is improved, then the power output of each unit on the power generation side is adjusted according to the starting and stopping time of the daily peak time periods, the power grid power difference is stabilized, meanwhile, a peak price policy is implemented in the daily peak time periods according to the correlation of loads and electricity prices, an electricity price rewarding and punishment mechanism is combined, the price lever is utilized, the user responsiveness on the demand side is improved, the aim of transferring and reducing the peak loads by users is achieved, the power supply pressure on the peak time period power generation side is reduced, the peak load regulation effect is improved, and stable running of a power system is effectively ensured.
The present embodiment also provides a computer device, and an internal structure of the computer device will be described with reference to fig. 6, where the computer device may include, but is not limited to: processor, memory, network interface, display screen and input device connected by system bus.
The processor may be the central processing unit (CentralProcessingUnit, CPU) of the computer device, as well as other general purpose processors and digital signal processors (DigitalSignalProcessor, DSP), etc., by connecting various parts of the overall device using various interfaces and lines, and by executing or executing computer readable instructions and/or modules stored in memory, and invoking data stored in memory, to perform various functions of the computer device; the processor referred to herein may be a central processing unit, CPU, or other general purpose processor, digital signal processor, DSP, application specific integrated circuit, ASIC, off-the-shelf programmable gate array, FPGA, or other programmable logic device, discrete gate or transistor logic device, discrete hardware components, or the like; wherein the general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory is used for storing computer readable instructions and/or modules, and mainly comprises a storage medium and an internal memory, wherein the storage medium can be a nonvolatile storage medium or a volatile storage medium, the storage medium stores an operating system, and can also store computer readable instructions, and when the computer readable instructions are executed by the processor, the processor can realize the regulation method of the peak load of the power grid, for example, the steps S1 to S7 shown in fig. 1 and 5 and other extensions of the method and the extension of related steps; alternatively, the processor executes the computer readable instructions to implement the functions of the modules/units of the grid spike load regulation system in the above embodiment, such as the functions of the modules 10 to 60 shown in fig. 5, and in order to avoid repetition, a detailed description will not be given here.
The network interface is used for communicating with an external server through network connection; the display screen can be a liquid crystal display screen or an electronic ink display screen; the input device can be a touch layer covered on the display screen, can also be a key, a track ball or a touch pad arranged on the shell of the computer equipment, and can also be an external keyboard, a touch pad or a mouse, etc.
It should be noted that the memory may be integrated into the processor or may be separate from the processor, and the structure shown in fig. 6 is merely a schematic block diagram of a portion of the structure related to the present application, and does not constitute a limitation of the computer device to which the present application is applied, and a specific computer device may include more or less components than those shown in the drawings, or may combine some components, or employ different component arrangements.
The foregoing embodiment numbers of the present application are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments. From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, or may be implemented by hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. ROM/RAM, magnetic disk, optical disk) as described above, comprising instructions for causing a terminal device (which may be a mobile phone, a computer, a server, or a network device, etc.) to perform the method according to the embodiments of the present application.
The foregoing embodiments have been presented in a detail description of the application, and are presented herein with a particular application to the understanding of the principles and embodiments of the application, the foregoing embodiments being merely intended to facilitate an understanding of the method of the application and its core concepts; meanwhile, as those skilled in the art will have variations in the specific embodiments and application scope in accordance with the ideas of the present application, the present description should not be construed as limiting the present application in view of the above.
Claims (7)
1. The method for regulating and controlling the peak load of the power grid is characterized by comprising the following steps of:
s1, acquiring a daily load prediction curve of all measured electric equipment in a power system in a prediction day;
s2, extracting all peak inflection points in the daily load prediction curve by adopting a second derivative method, recording the number of the peak inflection points as n, and numbering the n peak inflection points in sequence according to time sequence;
s3, comparing the load predicted value corresponding to the peak inflection point with a preset load threshold;
if the load predicted value corresponding to at least one peak inflection point exceeds a preset load threshold, judging the predicted day as a peak day and executing the next step; otherwise, judging that the predicted day is not the peak day, and not needing to carry out peak load regulation;
s4, determining a daily peak period by adopting an adaptive step iteration method according to the daily load prediction curve;
the specific process of step S4 includes the following steps:
s41, dividing the daily load prediction curve into a plurality of curve segments by taking a peak inflection point of which the load prediction value exceeds a preset load threshold value as a target point and taking valley inflection points on the left side and the right side of the peak inflection point as critical points;
s42, searching each curve segment by adopting an adaptive step iteration method to obtain a corresponding peak region;
s43, merging peak areas with intersections to obtain at least one daily peak period;
the specific process of step S42 includes the following steps:
s421, obtaining load predicted values L and R respectively corresponding to the left critical point and the right critical point of the curve segment and the minimum value of the unit step length；
S422, judging whether the load predicted value L exceeds a preset load threshold, if so, marking a left critical point as a left boundary point of a corresponding peak area, otherwise, setting an initial value of a unit step length as half of a time interval length B between a target point of the curve section and the left critical point, and setting the target point as a starting point;
s423, extracting a load predicted value corresponding to a predicted point of a unit step length of the interval starting point along the descending direction, judging whether the load predicted value is larger than a preset load threshold, and if so, resetting the unit step length to be，/>The number of step resetting is represented, whether the unit step is larger than the minimum value of the unit step is judged, if yes, the predicted point is set to be a new starting point and then returns to the step S423, and if not, the predicted point is marked as a left boundary point of a corresponding peak area;
if not, resetting the unit step length to，/>Representing the number of step resetting, judging whether the unit step is larger than the minimum value of the unit step, if so, returning to the step S423, and if not, marking the original starting point of the iteration as the left boundary point of the corresponding peak area;
s424, determining a right boundary point of a peak area in the curve segment by adopting the same principle of the steps S422 and S423;
s5, determining a total regulation strategy of the peak load of the power grid from two aspects of a power generation side and a demand side according to the peak period;
and S6, regulating and controlling the peak load of the power grid on a prediction day according to the total regulation and control strategy.
2. The method for regulating peak power grid load according to claim 1, wherein the specific process of step S3 includes the following steps:
s31, judging whether a load predicted value corresponding to a peak inflection point exceeds a preset load threshold, if the load predicted value corresponding to the peak inflection point exceeds the preset load threshold, resetting a counter m to be m+1, and setting an initial value of the counter m to be 0, otherwise, keeping the counter m unchanged;
s32, resetting the cycle iteration number i to be i+1, wherein the initial value of the cycle iteration number i is 0;
s33, judging whether the number of loop iteration times i is smaller than the number of peak inflection points n, returning to the step S31 if the number of loop iteration times i is smaller than the number of peak inflection points n, otherwise executing the step S34;
s34, judging whether the counter m is larger than or equal to 1, if the counter m is larger than or equal to 1, judging that the predicted day is the peak day, and executing the step S4, otherwise, judging that the predicted day is not the peak day, namely, not carrying out peak load regulation.
3. The method for regulating peak power grid load according to claim 1, wherein the specific process of step S5 includes the following steps:
s51, determining a power generation side regulation strategy for regulating peak load according to the start-stop time of the daily peak period;
s52, determining a demand side regulation strategy for regulating peak load according to the power generation side regulation strategy and the duration of the daily peak period.
4. A method for controlling peak load of power grid according to claim 3, wherein the specific process of step S51 includes the following steps:
s511, acquiring related parameters of minimum startup and shutdown time, climbing efficiency, power generation cost and line state of each unit in the power generation side;
s512, establishing a power generation side dispatching model by taking the lowest cost of the power generation side as a target and taking the starting and stopping time and climbing efficiency of a daily peak period as constraint conditions;
and S513, solving a power generation side dispatching model by adopting an interior point method to obtain a power generation side regulation strategy for regulating the start and stop of each unit on the power generation side.
5. A method for controlling peak load of power grid according to claim 3, wherein the specific process of step S52 includes the following steps:
s521, determining the real-time electricity price of the peak time period according to the power generation side regulation strategy;
and S522, optimizing the real-time electricity price according to the duration of the daily peak time period and an electricity fee rewarding and punishing mechanism to obtain the peak electricity price for regulating and controlling the demand side.
6. A system for implementing the grid spike load regulation method of any one of claims 1-5, comprising:
the data acquisition module (10) is used for acquiring daily load prediction curves of all the detected electric equipment in the power system in the predicted day;
the peak inflection point extraction module (20) is used for extracting all peak inflection points in the daily load prediction curve by adopting a second derivative method, recording the number of the peak inflection points as n and numbering the n peak inflection points in sequence according to time sequence;
the peak day judging module (30), the peak day judging module (30) is used for comparing the load predicted value corresponding to the peak inflection point with a preset load threshold;
if the load predicted value corresponding to at least one peak inflection point exceeds a preset load threshold, judging the predicted day as a peak day and executing the next step; otherwise, judging that the predicted day is not the peak day, and not needing to carry out peak load regulation;
the daily peak period dividing module (40) is used for determining a daily peak period by adopting an adaptive step iteration method according to the daily load prediction curve;
the total regulation strategy determining module (50) is used for determining a total regulation strategy of the peak load of the power grid from the power generation side and the demand side according to the peak period of the day;
and the peak load regulation module (60) is used for regulating and controlling the peak load of the power grid on a prediction day according to the total regulation strategy.
7. A computer device comprising a processor and a memory for storing a computer program, the processor implementing a method of regulating peak load of a power grid according to any one of claims 1 to 5 when executing the computer program in the memory.
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