CN115760194A - Method, device and equipment for optimizing peak-valley electricity price and time interval and storage medium - Google Patents
Method, device and equipment for optimizing peak-valley electricity price and time interval and storage medium Download PDFInfo
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Abstract
The invention discloses a peak-valley electricity price and time interval optimization method, which comprises the following steps: establishing a double-layer joint optimization model taking peak-valley electricity price and peak-valley time period as independent variables; generating the hours corresponding to the peak-valley period, initializing the generated peak-valley period, and starting the iterative calculation of the peak-valley period: optimizing the peak-valley electricity price in the double-layer combined optimization model to obtain a first objective function value of the peak-valley optimization electricity price, optimizing the peak-valley time period in the double-layer combined optimization model to obtain a second objective function value of the peak-valley optimization time period, recording the peak-valley optimization electricity price, the peak-valley optimization time period and the second objective function when the first objective function value is the same as the second objective function value, and outputting the recorded optimization scheme after each iteration until the number of iterations reaches a preset number; thereby outputting the optimal second objective function value and the corresponding peak-valley electricity price and peak-valley time period. The invention solves the technical problems of unreasonable peak-valley electricity price design and peak-valley time interval division in the prior art.
Description
Technical Field
The invention relates to the technical field of energy management, in particular to a peak-valley electricity price and time period optimization method, a device, equipment and a storage medium.
Background
The existing peak-valley time-of-use electricity price design method generally divides a peak-valley time period firstly, then decides the peak-valley time-of-use electricity price, and the peak-valley time period is obtained by independent division according to the numerical value of a load curve. For example, by using a fuzzy membership function and other methods, a peak-valley time period and corresponding hours are obtained through optimization according to the numerical value of a load curve, then the peak-valley electricity price is formulated according to the divided peak-valley time period, or the hours corresponding to the peak time period, the flat time period and the valley time period are set firstly, then the numerical values of the load curve are sequenced, and the load is divided into the peak time period, the flat time period and the valley time period from large to small in sequence; and then, the peak-valley electricity price is made according to the divided peak-valley time periods.
However, the existing peak-valley period is divided only by considering the magnitude of the load curve, and the influence on the design of peak-valley electricity price, the interaction mechanism among user response behaviors and the implementation effect of time-sharing electricity price is neglected, so that the time-sharing electricity price mechanism effect cannot reach the optimum, and the value of the hours corresponding to the peak-valley period completely depends on the expert experience or the magnitude of the load value in each period, and is lack of scientificity.
Therefore, an optimization method which can enable the time-of-use electricity price to be more effective and enable the peak-valley electricity price design and the peak-valley time interval division to be more scientific and reasonable is needed at present.
Disclosure of Invention
The invention provides a peak-valley electricity price and time interval optimization method, a device, equipment and a storage medium, which aim to solve the technical problems of low time-of-use electricity price utility, unreasonable peak-valley electricity price design and unreasonable peak-valley time interval division in the prior art.
In order to solve the above technical problem, an embodiment of the present invention provides a method for optimizing peak-to-valley electricity prices and time periods, including:
establishing a double-layer joint optimization model taking peak-valley electricity price and peak-valley time period as independent variables;
generating hours corresponding to a peak-valley period, starting iterative calculation of peak-valley electricity price and the peak-valley period according to the peak-valley period generated by power load initialization of a power grid, optimizing the peak-valley electricity price in the double-layer combined optimization model in each iterative calculation of the peak-valley electricity price and the peak-valley period to obtain a first target function value of the peak-valley optimized electricity price, and optimizing the peak-valley period in the double-layer combined optimization model to obtain a second target function value of the peak-valley optimized period, so that when the first target function value and the second target function value are the same, the peak-valley optimized electricity price, the peak-valley optimized period and the second target function are recorded and used as an optimization scheme of current iteration, and the recorded optimization scheme after each iteration is output until the iteration times reach preset times;
and comparing the second objective function values in all the optimization schemes, thereby outputting the optimal second objective function value and the corresponding peak-valley electricity price and peak-valley time period thereof.
As a preferred scheme, the establishing of the double-layer joint optimization model taking the peak-valley electricity price and the peak-valley time period as independent variables specifically comprises the following steps:
according to the peak-valley electricity price and the peak-valley time period under the time-of-use electricity price mechanism, the peak-valley electricity price and the peak-valley time period are used as independent variables, a double-layer joint optimization model using the peak-valley electricity price and the peak-valley time period as the independent variables is constructed, and the peak-valley electricity price are combinedAnd (4) restraining the valley period:
F x x≥f x ，F y y≥f y ，G x x＝g x ，G y y＝g y ，U x x+U y y≥u，V x x+V y y = v; wherein M (x, y, M, i) ≧ M i i＝1,2,3,...，N(x,y,n,j)＝Π j j＝1,2,3,...；
Wherein w is an objective function value; x is a variable vector of peak-to-valley electricity prices; y is a variable vector at peak-to-valley time; c. C x 、c y Coefficient vectors corresponding to x and y respectively;
is a coefficient constant; f x 、F y 、G x 、G y 、U x 、U y 、V x 、V y Are coefficient matrices; f. of x 、f y 、g x 、g y 、u、v、Μ i 、Π j Are all constant vectors;
are all coefficient constants.
As a preferred scheme, the generating the number of hours corresponding to the peak-valley period and initializing the generated peak-valley period according to the power load of the power grid specifically include:
according to the power load curve of the power grid, the load is taken from large to small in the peak time period until all the hours meeting the peak time period are obtained, the load is taken from small to large in the valley time period until all the hours meeting the valley time period are obtained, and the rest time period is taken as the flat time period, so that the initialization of the peak-valley time period is completed.
As a preferred scheme, the optimizing the peak-to-valley electricity price in the double-layer joint optimization model to obtain a first objective function value of the peak-to-valley optimized electricity price specifically includes:
according to the initialized peak-valley time period, optimizing and calculating the peak-valley electricity price in the double-layer combined optimization model:
F x x≥f x ，G x x＝g x ，U x x+U y y≥u，V x x+V y y = v; wherein M (x, y, M, i) ≧ M i i＝1,2,3,...，N(x,y,n,j)＝Π j j =1,2,3.; thereby obtaining a first objective function value of the peak-valley optimized electricity prices.
As a preferred scheme, the optimizing the peak-valley period in the double-layer joint optimization model to obtain a second objective function value of the peak-valley optimization period specifically includes:
and optimizing and calculating the peak-valley time period in the double-layer combined optimization model according to the peak-valley optimization electricity price:
F y y≥f y ，G y y＝g y ，U x x+U y y≥u，V x x+V y y = v; wherein M (x, y, M, i) ≧ M i i＝1,2,3,...，N(x,y,n,j)＝Π j j =1,2,3.; thereby obtaining a second objective function value for the peak-to-valley optimization interval.
As a preferred scheme, after the optimizing the peak-valley period in the dual-layer joint optimization model to obtain the second objective function value of the peak-valley optimization period, the method further includes:
and when the first objective function value is different from the second objective function value, performing optimization calculation on the peak-valley electricity price again, and performing optimization calculation on the peak-valley time period until the first objective function value obtained through optimization calculation is equal to the corresponding second objective function value.
As a preferred scheme, the comparing the second objective function values in all the optimization schemes to output an optimal second objective function value and corresponding peak-to-valley electricity prices and peak-to-valley periods thereof specifically includes:
and comparing the second objective function values in all the optimization schemes to obtain the minimum second objective function value, and outputting the peak-valley electricity price and the peak-valley time period corresponding to the minimum second objective function value.
Correspondingly, the invention also provides a device for optimizing peak-valley electricity price and time interval, which comprises: the device comprises a modeling module, an optimizing module and an output module;
the modeling module is used for establishing a double-layer joint optimization model taking peak-valley electricity price and peak-valley time period as independent variables;
the optimization module is used for generating hours corresponding to a peak-valley period, starting iterative calculation of peak-valley electricity prices and the peak-valley period according to the peak-valley period generated by power load initialization of a power grid, optimizing the peak-valley electricity prices in the double-layer combined optimization model in each iterative calculation of the peak-valley electricity prices and the peak-valley period to obtain a first target function value of the peak-valley optimized electricity prices, and optimizing the peak-valley period in the double-layer combined optimization model to obtain a second target function value of the peak-valley optimized period, so that when the first target function value is the same as the second target function value, the peak-valley optimized electricity prices, the peak-valley optimized period and the second target function are recorded and used as an optimization scheme of current iteration, and the recorded optimization scheme after each iteration is output until the iteration times reach preset times;
and the output module is used for comparing the second objective function values in all the optimization schemes, so as to output the optimal second objective function value and the corresponding peak-valley electricity price and peak-valley time period.
As a preferred scheme, the establishing of the double-layer joint optimization model taking the peak-valley electricity price and the peak-valley time period as independent variables specifically comprises the following steps:
according to the peak-valley electricity price and the peak-valley time period under the time-of-use electricity price mechanism, constructing a double-layer joint optimization model taking the peak-valley electricity price and the peak-valley time period as independent variables, and constraining the peak-valley electricity price and the peak-valley time period:
F x x≥f x ，F y y≥f y ，G x x＝g x ，G y y＝g y ，U x x+U y y≥u，V x x+V y y = v; wherein M (x, y, M, i) ≥ M i i＝1,2,3,...，N(x,y,n,j)＝Π j j＝1,2,3,...；
Wherein w is an objective function value; x is a variable vector of peak-to-valley electricity prices; y is a variable vector at peak-to-valley time; c. C x 、c y Coefficient vectors corresponding to x and y respectively;
is a coefficient constant; f x 、F y 、G x 、G y 、U x 、U y 、V x 、V y Are coefficient matrices; f. of x 、f y 、g x 、g y 、u、v、Μ i 、Π j Are all constant vectors;
are all coefficient constants.
As a preferred scheme, the generating the number of hours corresponding to the peak-valley period and initializing the generated peak-valley period according to the power load of the power grid specifically include:
according to the power load curve of the power grid, the load is taken from large to small in the peak time period until all the hours meeting the peak time period are obtained, the load is taken from small to large in the valley time period until all the hours meeting the valley time period are obtained, and the rest time period is taken as the flat time period, so that the initialization of the peak-valley time period is completed.
As a preferred scheme, the optimizing the peak-to-valley electricity price in the double-layer joint optimization model to obtain a first objective function value of the peak-to-valley optimized electricity price specifically includes:
based on the initialized peak-to-valley period,performing optimization calculation on the peak-valley electricity prices in the double-layer joint optimization model:
F x x≥f x ，G x x＝g x ，U x x+U y y≥u，V x x+V y y = v; wherein M (x, y, M, i) ≧ M i i＝1,2,3,...，N(x,y,n,j)＝Π j j =1,2,3.; thereby obtaining a first objective function value of the peak-valley optimized electricity prices.
As a preferred scheme, the optimizing the peak-valley period in the double-layer joint optimization model to obtain a second objective function value of the peak-valley optimization period specifically includes:
and optimizing and calculating the peak-valley time period in the double-layer combined optimization model according to the peak-valley optimization electricity price:
F y y≥f y ，G y y＝g y ，U x x+U y y≥u，V x x+V y y = v; wherein M (x, y, M, i) ≧ M i i＝1,2,3,...，N(x,y,n,j)＝Π j j =1,2,3.; thereby obtaining a second objective function value for the peak-to-valley optimization interval.
As a preferred scheme, after the optimizing the peak-valley period in the dual-layer joint optimization model to obtain the second objective function value of the peak-valley optimization period, the method further includes:
and when the first objective function value is different from the second objective function value, performing optimization calculation on the peak-valley electricity price again, and performing optimization calculation on the peak-valley time period until the first objective function value obtained through optimization calculation is equal to the corresponding second objective function value.
As a preferred scheme, the comparing the second objective function values in all the optimization schemes to output an optimal second objective function value and corresponding peak-to-valley electricity prices and peak-to-valley periods thereof specifically includes:
and comparing the second objective function values in all the optimization schemes to obtain the minimum second objective function value, and outputting the peak-valley electricity price and the peak-valley time period corresponding to the minimum second objective function value.
Accordingly, the present invention also provides a terminal device comprising a processor, a memory and a computer program stored in the memory and configured to be executed by the processor, wherein the processor, when executing the computer program, implements the peak-to-valley electricity rate and time period optimization method as described in any one of the above.
Accordingly, the present invention also provides a computer readable storage medium comprising a stored computer program; wherein the computer program when executed controls an apparatus in which the computer readable storage medium is located to perform the peak-to-valley electricity rate and time period optimization method as described in any one of the above.
Compared with the prior art, the embodiment of the invention has the following beneficial effects:
according to the technical scheme, a double-layer combined optimization model taking the peak-valley electricity price and the peak-valley time period as independent variables is established, interaction mechanisms of the peak-valley time period, the peak-valley electricity price and user response behaviors can be fully considered, the peak-valley time period is generated in an initialized mode, so that the peak-valley time period completely corresponds to the load size, the iteration times are reduced, the optimal result is obtained quickly, iteration of hours in the peak-valley time period is performed, the first objective function value and the second objective function value are obtained in iterative calculation, common optimization of the hours in the peak-valley time period, the peak-valley electricity price and peak-valley time period is achieved, the second objective function value in the optimization scheme after each iteration is compared after the iteration times reach the preset value, the optimal second objective function value and the corresponding peak-valley electricity price and peak-valley time period are output, and time-sharing electricity price design and peak-valley time period division are more scientific and reasonable.
Drawings
FIG. 1: the step flow chart of the peak-valley electricity price and time interval optimization method provided by the embodiment of the invention;
FIG. 2 is a schematic diagram: the method comprises the steps of designing a flow chart of a peak-valley time period and peak-valley electricity price double-layer optimization model optimization method considering hours in the peak-valley time period;
FIG. 3: the embodiment of the invention provides a structural schematic diagram of a peak-valley electricity price and time interval optimizing device.
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 obtained by a person skilled in the art without inventive step based on the embodiments of the present invention, are within the scope of protection of the present invention.
Example one
Referring to fig. 1, a method for optimizing peak-to-valley electricity prices and time periods provided in an embodiment of the present invention includes the following steps S101 to S103:
step S101: and establishing a double-layer joint optimization model taking the peak-valley electricity price and the peak-valley time period as independent variables.
As a preferred scheme of this embodiment, the establishing of the double-layer joint optimization model using the peak-valley electricity price and the peak-valley period as arguments specifically includes:
according to the peak-valley electricity price and the peak-valley time period under the time-of-use electricity price mechanism, constructing a double-layer joint optimization model taking the peak-valley electricity price and the peak-valley time period as independent variables, and constraining the peak-valley electricity price and the peak-valley time period:
G x x＝g x ，G y y＝g y ，U x x+U y y≥u，V x x+V y y = v; wherein M (x, y, M, i) ≧ M i i＝1,2,3,...，N(x,y,n,j)＝Π j j =1,2,3.; wherein w is an objective function value; x is a variable vector of peak-to-valley electricity prices; y is a variable vector at peak-to-valley time; c. C x 、c y The coefficient vectors are respectively corresponding to x and y;
c xa,yb is a coefficient constant; f x 、F y 、G x 、G y 、U x 、U y 、V x 、V y Are all coefficient matrices; f. of x 、f y 、g x 、g y 、u、v、Μ i 、Π j Are all constant vectors;
are all coefficient constants.
It should be noted that, in the process of constructing the model of the dual-layer joint optimization model, the optimization calculation feasibility of the model is not considered first, so as to avoid multiple and complex parameters from influencing the construction process of the dual-layer joint optimization model, and thus, the optimization model including the peak-valley electricity price and the peak-valley time period as independent variables can be quickly established in the construction process, the model objective function value is determined by the peak-valley electricity price and the peak-valley time period, and the peak-valley electricity price and the peak-valley time period are constrained within a certain range.
It can be understood that by constructing a double-layer combined optimization model of the peak-valley electricity price and the peak-valley time period, the interaction mechanism of the peak-valley time period, the peak-valley electricity price and the user response behavior can be fully considered, so that the user response behavior and the influence of the user response behavior on the objective function can be fully considered in the peak-valley time period and the peak-valley electricity price, and the design of the peak-valley electricity price and the division of the peak-valley time period are more scientific and reasonable.
Step S102: generating hours corresponding to a peak-valley period according to the power load of a power grid, initializing the generated peak-valley period, starting iterative calculation of the peak-valley period, so that in each iterative calculation of the peak-valley period, optimizing the peak-valley power price in the double-layer combined optimization model to obtain a first objective function value of the peak-valley optimized power price, and optimizing the peak-valley period in the double-layer combined optimization model to obtain a second objective function value of the peak-valley optimized period, so that when the first objective function value is the same as the second objective function value, the peak-valley optimized power price, the peak-valley optimized period and the second objective function are recorded as an optimization scheme of current iteration, and the recorded optimization scheme after each iteration is output until the iteration number reaches a preset number.
As a preferred scheme of this embodiment, the generating the hours corresponding to the peak-valley period according to the electrical load of the power grid, and initializing the generated peak-valley period specifically include:
according to the power load curve of the power grid, the peak time interval of the load from large to small is obtained until all the hours of the peak time interval are obtained, the valley time interval of the load from small to large is obtained until all the hours of the valley time interval are obtained, and the rest time interval is used as the flat time interval, so that the initialization of the peak-valley time interval is completed.
It should be noted that the peak-valley period of the initial iteration of the double-layer joint optimization model is generated by initializing with a numerical ordering method according to the input peak, average and valley hours. The peak period may be exemplified by starting with a large to small electrical load per hour, taking the peak period until all peak period-satisfying hours are taken, for example: for 24 hours a day, the average power load of each hour can be visually obtained according to the power load of the power grid, and the power loads of each hour are sorted from large to small, so that 10:00-14:00 and 18: -21:00 two periods are peak periods, namely, the number of hours corresponding to the peak period is 7 hours; the valley period is determined by starting with the power load for each hour from small to large, taking the valley period until all the hours satisfying the valley period are taken, for example: the electric loads in each hour are sorted from small to large, and the ratio of 0:00-7: the one period 00 is a valley period, i.e., the valley period corresponds to 7 hours. The remaining period is thus obtained as a flat period. Therefore, the peak-valley time period generated by initialization completely corresponds to the load size, the iteration times can be reduced, and the optimal result can be quickly obtained.
It can be understood that, because the numerical sorting method is initialized and generated or only the magnitude of the load is considered in the peak-valley period generated according to the membership function, and the system condition, the load response behavior and the like cannot be considered, the peak-valley period is continuously optimized in the lower layer, so that the peak-valley electricity price and the peak-valley period can be considered mutually, the system condition, the load response behavior and the like can be considered fully, and the time-of-use electricity price effect is better.
As a preferred scheme of this embodiment, the optimizing the peak-to-valley electricity price in the double-layer joint optimization model to obtain a first objective function value of the peak-to-valley optimized electricity price specifically includes:
according to the initialized peak-valley time period, the power transmission cost and the power generation cost, carrying out optimization calculation on the peak-valley electricity price in the double-layer combined optimization model:
G x x＝g x ，U x x+U y y≥u，V x x+V y y = v; wherein M (x, y, M, i) ≧ M i i＝1,2,3,...，N(x,y,n,j)＝Π j j =1,2,3.; thereby obtaining a first objective function value of the peak-valley optimized electricity prices.
In this embodiment, the peak-valley period is obtained by dividing, and the peak-valley period y is a known quantity, so that the peak-valley electricity price in the double-layer joint optimization model can be directly optimized and calculated, and the first objective function value w of the peak-valley optimized electricity price x is obtained after optimization x 。
As a preferred scheme of this embodiment, the optimizing the peak-valley period in the double-layer joint optimization model to obtain a second objective function value of the peak-valley optimization period specifically includes:
and optimizing and calculating the peak-valley time period in the double-layer combined optimization model according to the peak-valley optimization electricity price:
F y y≥f y ，G y y＝g y ，U x x+U y y≥u，V x x+V y y = v; wherein M (x, y, M, i) ≧ M i i＝1,2,3,...，N(x,y,n,j)＝Π j j =1,2,3.; thereby obtaining peak-to-valley optimizationA second objective function value for the time interval.
In this embodiment, the peak-valley optimized electricity price x is obtained through optimization, and the peak-valley optimized electricity price x is a known quantity, so that the peak-valley period in the double-layer combined optimization model can be directly optimized and calculated, and the second objective function value w of the peak-valley optimized period y is obtained through optimization y 。
Before the iterative computation of the peak-valley period, the original parameters of the iterative computation, including but not limited to load, transmission cost, generation cost and other data, need to be input, and the input is performed according to the targets and constraints considered when the time-of-use electricity price is established by the power grid enterprise and the electricity selling enterprise.
As a preferable solution of this embodiment, after the optimizing the peak-valley period in the two-layer joint optimization model to obtain the second objective function value of the peak-valley optimization period, the method further includes:
and when the first objective function value is different from the second objective function value, performing optimization calculation on the peak-valley electricity price again, and performing optimization calculation on the peak-valley time period until the first objective function value obtained by optimization calculation is equal to the corresponding second objective function value.
In the present embodiment, the first objective function value w x And a second objective function value w y Same, i.e. when w x ＝w y Then, the current peak-valley time period and the peak-valley electricity price double-layer optimization inner circulation are ended, and the second objective function value w of the current circulation is directly recorded k ＝w y Peak-to-valley optimized electricity price x k = x, peak-to-valley optimization period y k And (= y). At a first objective function value w x And a second objective function value w y When not identical, i.e. when w x ≠w y And then, returning to the peak-valley electricity price optimization again, namely re-optimizing and calculating to obtain the peak-valley optimized electricity price and a corresponding first objective function value, and re-optimizing the peak-valley time period, namely re-optimizing and calculating to obtain the peak-valley optimized time period and a corresponding second objective function value until the first objective function value obtained by optimization and calculation is equal to the corresponding second objective function value, so that the continuous interactive optimization and optimization of the peak-valley time period and the peak-valley electricity price are ensured。
It should be noted that, when the iteration number does not reach the preset number, the peak-valley period y is returned to be initialized again, that is, the peak-valley period under the curves of different power grid power loads, and then the iterative optimization calculation of the first objective function value and the second objective function value is performed by using different peak-valley periods, so that the peak-valley power price and the peak-valley period can be mutually considered, and the system condition and the load response behavior can be fully considered. It is understood that, alternatively, the preset times is the combined number of the peak, average and valley hours (the sum of the peak, average and valley hours is 24 h) accepted when the power grid enterprise and the power selling enterprise set the time-of-use electricity price.
Step S103: and comparing the second objective function values in all the optimization schemes, thereby outputting the optimal second objective function value and the corresponding peak-valley electricity price and peak-valley time period.
As a preferred embodiment of this embodiment, the comparing the second objective function values in all the optimization schemes, so as to output an optimal second objective function value and corresponding peak-to-valley electricity prices and peak-to-valley periods thereof, specifically:
and comparing the second objective function values in all the optimization schemes to obtain the minimum second objective function value, and outputting the peak-valley electricity price and the peak-valley time period corresponding to the minimum second objective function value.
In this embodiment, by comparing the second objective function values in different optimization schemes, the peak-valley electricity price and the peak-valley time period corresponding to the minimum second objective function value are output, so that it can be ensured that the time of the peak-valley electricity price and the time of the peak-valley time period are both within the constraint condition, and the relationship between the peak-valley electricity price and the peak-valley time period is optimal under the condition of the minimum second objective function value, so as to find the optimal number of hours corresponding to the peak-valley time period, and the optimal peak-valley time period can be obtained by dividing no matter what the number of hours is in the peak-valley time period, which better meets the supply and demand conditions of each time of the power system, so that the time-of-use electricity price is more optimal, and the peak-valley electricity price formulation and the peak-valley time period division are more scientific and reasonable.
In this embodiment, please refer to fig. 2, which is a flowchart of a peak-valley time period and peak-valley electricity price dual-layer optimization model optimization method designed in consideration of hours in the peak-valley time period according to the present invention, first, a peak-valley electricity price and peak-valley time period dual-layer combined optimization model is established, the cycle number is set to 0, i.e., k =0, and an original parameter is input, so as to generate hours corresponding to the peak-valley time period, k = k +1 and initially divide the peak-valley time period, and the peak-valley electricity price is optimized, so as to obtain the peak-valley optimized electricity price x and the objective function value w thereof x And optimizing the peak-valley period to obtain the peak-valley optimization period y and the objective function value w thereof y (ii) a Judgment of w x And w y If not, re-optimizing the peak-valley electricity price and the peak-valley time period; if the peak value and the valley value are equal, recording an objective function value w corresponding to the peak-valley optimization time period of the current cycle k ＝w y Peak-valley optimized electricity price x k = x, peak-to-valley optimization period y k = y; judging whether the iteration times K is less than or equal to K, if so, returning to regenerate the hours corresponding to the peak-valley period, and ensuring that the hours corresponding to the peak-valley period of the rest power grid power load curves execute the iterative optimization calculation in the invention; if K is larger than K, the iterative optimization calculation is completed for all the hours in the peak-valley period, the objective function value obtained by each circulation is output, namely the optimization result, and the objective function values are compared to obtain the optimal result, wherein the optimal result comprises the following steps: and the optimal target function value and the corresponding peak-valley electricity price and peak-valley time period thereof.
It can be understood that the peak-valley time period and the peak-valley electricity price are continuously optimized in an interactive mode, the optimal peak-valley electricity price and the optimal peak-valley time period under the set peak-valley time hours are obtained, and the peak-valley electricity price design and the peak-valley time period division are more scientific and reasonable.
The above embodiment is implemented, and has the following effects:
according to the technical scheme, a double-layer combined optimization model with the peak-valley electricity price and the peak-valley time as independent variables is established, interaction mechanisms of the peak-valley time, the peak-valley electricity price and user response behaviors can be fully considered, the peak-valley time is initialized to be generated, so that the peak-valley time completely corresponds to the load size, the iteration times are reduced, the optimal result is quickly obtained, iteration of the peak-valley time hours is further performed, the first objective function value and the second objective function value are obtained in iterative calculation, common optimization of the peak-valley time hours, the peak-valley electricity price and the peak-valley time is achieved, and after the iteration times reach a preset value, the second objective function value in the optimization scheme after each iteration is compared, the optimal second objective function value and the corresponding peak-valley electricity price and peak-valley time are output, so that the electricity time-share utility is better, the peak-valley electricity price design and the peak-valley time division are more scientific and reasonable.
Example two
Please refer to fig. 3, which is a device for optimizing peak-to-valley electricity rates and time periods according to the present invention, comprising: a modeling module 201, an optimization module 202, and an output module 203.
The modeling module 201 is configured to establish a double-layer joint optimization model using peak-valley electricity prices and peak-valley time periods as independent variables.
The optimization module 202 is configured to generate hours corresponding to a peak-valley period, initialize the peak-valley period, start iterative calculation of the peak-valley electricity price and the peak-valley period, optimize the peak-valley electricity price in the dual-layer joint optimization model to obtain a first objective function value of the peak-valley optimized electricity price in each iterative calculation of the peak-valley electricity price and the peak-valley period, and optimize the peak-valley period in the dual-layer joint optimization model to obtain a second objective function value of the peak-valley optimized period, so that when the first objective function value is the same as the second objective function value, the peak-valley optimized electricity price, the peak-valley optimized period, and the second objective function are recorded as an optimization scheme of current iteration, and the recorded optimization scheme after each iteration is output until the iteration number reaches a preset number.
And the output module 203 is configured to compare the second objective function values in all the optimization schemes, so as to output an optimal second objective function value and corresponding peak-to-valley electricity prices and peak-to-valley time periods thereof.
As a preferred scheme of this embodiment, the establishing of the double-layer joint optimization model using the peak-valley electricity price and the peak-valley period as arguments specifically includes:
according to the peak-valley electricity price and the peak-valley time period under the time-of-use electricity price mechanism, constructing a double-layer joint optimization model taking the peak-valley electricity price and the peak-valley time period as independent variables, and constraining the peak-valley electricity price and the peak-valley time period:
F x x≥f x ，F y y≥f y ，G x x＝g x ，G y y＝g y ，U x x+U y y≥u，V x x+V y y = v; wherein M (x, y, M, i) ≧ M i i＝1,2,3,...，N(x,y,n,j)＝Π j j =1,2,3.; wherein w is an objective function value; x is a variable vector of peak-to-valley electricity prices; y is a variable vector of the peak-valley period; c. C x 、c y Coefficient vectors corresponding to x and y respectively;
is a coefficient constant; f x 、F y 、G x 、G y 、U x 、U y 、V x 、V y Are all coefficient matrices; f. of x 、f y 、g x 、g y 、u、v、Μ i 、Π j Are all constant vectors;
are all coefficient constants.
As a preferred scheme of this embodiment, the generating the hours corresponding to the peak-valley period according to the electrical load of the power grid, and initializing the generated peak-valley period specifically include:
according to the power load curve of the power grid, the peak time interval of the load from large to small is obtained until all the hours of the peak time interval are obtained, the valley time interval of the load from small to large is obtained until all the hours of the valley time interval are obtained, and the rest time interval is used as the flat time interval, so that the initialization of the peak-valley time interval is completed.
As a preferred scheme of this embodiment, the optimizing the peak-to-valley electricity price in the double-layer joint optimization model to obtain a first objective function value of the peak-to-valley optimized electricity price specifically includes:
according to the initialized peak-valley time period, the power transmission cost and the power generation cost, carrying out optimization calculation on the peak-valley electricity price in the double-layer combined optimization model:
F x x≥f x ，G x x＝g x ，U x x+U y y≥u，V x x+V y y = v; wherein M (x, y, M, i) ≧ M i i＝1,2,3,...，N(x,y,n,j)＝Π j j =1,2,3.; thereby obtaining a first objective function value of the peak-to-valley optimized electricity prices.
As a preferred scheme of this embodiment, the optimizing the peak-valley period in the double-layer joint optimization model to obtain a second objective function value of the peak-valley optimization period specifically includes:
and optimizing and calculating the peak-valley time period in the double-layer combined optimization model according to the peak-valley optimization electricity price:
F y y≥f y ，G y y＝g y ，U x x+U y y≥u，V x x+V y y = v; wherein M (x, y, M, i) ≧ M i i＝1,2,3,...，N(x,y,n,j)＝Π j j =1,2,3.; thereby obtaining a second objective function value for the peak-to-valley optimization interval.
As a preferable solution of this embodiment, after optimizing the peak-valley period in the dual-layer joint optimization model to obtain a second objective function value of the peak-valley optimization period, the method further includes:
and when the first objective function value is different from the second objective function value, performing optimization calculation on the peak-valley electricity price again, and performing optimization calculation on the peak-valley time period until the first objective function value obtained by optimization calculation is equal to the corresponding second objective function value.
As a preferred embodiment of this embodiment, the comparing the second objective function values in all the optimization schemes, so as to output an optimal second objective function value and its corresponding peak-to-valley electricity price and peak-to-valley period specifically includes:
and comparing the second objective function values in all the optimization schemes to obtain the minimum second objective function value, and outputting the peak-valley electricity price and the peak-valley time period corresponding to the minimum second objective function value.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working process of the apparatus described above may refer to the corresponding process in the foregoing method embodiment, and is not described herein again.
The embodiment has the following effects:
according to the technical scheme, a double-layer combined optimization model taking the peak-valley electricity price and the peak-valley time period as independent variables is established, interaction mechanisms of the peak-valley time period, the peak-valley electricity price and user response behaviors can be fully considered, the peak-valley time period is generated in an initialized mode, so that the peak-valley time period completely corresponds to the load size, the iteration times are reduced, the optimal result is obtained quickly, iteration of hours in the peak-valley time period is performed, the first objective function value and the second objective function value are obtained in iterative calculation, common optimization of the hours in the peak-valley time period, the peak-valley electricity price and peak-valley time period is achieved, the second objective function value in the optimization scheme after each iteration is compared after the iteration times reach the preset value, the optimal second objective function value and the corresponding peak-valley electricity price and peak-valley time period are output, and time-sharing electricity price design and peak-valley time period division are more scientific and reasonable.
EXAMPLE III
Correspondingly, the invention also provides a terminal device, comprising: a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, the processor implementing the peak-to-valley electricity rate and time period optimization method as described in any one of the above embodiments when executing the computer program.
The terminal device of this embodiment includes: a processor, a memory, and a computer program, computer instructions stored in the memory and executable on the processor. The processor implements the steps in the first embodiment, such as steps S101 to S103 shown in fig. 1, when executing the computer program. Alternatively, the processor, when executing the computer program, implements the functions of each module/unit in the above-described apparatus embodiments, such as the modeling module 201.
Illustratively, the computer program may be partitioned into one or more modules/units that are stored in the memory and executed by the processor to implement the invention. The one or more modules/units may be a series of computer program instruction segments capable of performing specific functions, which are used for describing the execution process of the computer program in the terminal device. For example, the modeling module 201 is configured to build a two-layer joint optimization model with the peak-valley electricity price and the peak-valley period as arguments.
The terminal device can be a desktop computer, a notebook, a palm computer, a cloud server and other computing devices. The terminal device may include, but is not limited to, a processor, a memory. It will be appreciated by those skilled in the art that the schematic diagram is merely an example of a terminal device and does not constitute a limitation of a terminal device, and may include more or less components than those shown, or combine certain components, or different components, for example, the terminal device may also include input output devices, network access devices, buses, etc.
The Processor may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may be any conventional processor or the like, said processor being the control center of said terminal device, and various interfaces and lines are used to connect the various parts of the whole terminal device.
The memory may be used to store the computer programs and/or modules, and the processor may implement various functions of the terminal device by running or executing the computer programs and/or modules stored in the memory and calling data stored in the memory. The memory may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function, and the like; the storage data area may store data created according to the use of the mobile terminal, and the like. In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), at least one magnetic disk storage device, a Flash memory device, or other volatile solid state storage device.
Wherein, the terminal device integrated module/unit can be stored in a computer readable storage medium if it is implemented in the form of software functional unit and sold or used as a stand-alone product. Based on such understanding, all or part of the flow of the method according to the embodiments of the present invention may also be implemented by a computer program, which may be stored in a computer-readable storage medium, and when the computer program is executed by a processor, the steps of the method embodiments may be implemented. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, read-Only Memory (ROM), random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like. It should be noted that the computer readable medium may contain content that is subject to appropriate increase or decrease as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer readable media does not include electrical carrier signals and telecommunications signals as is required by legislation and patent practice.
Example four
Accordingly, the present invention also provides a computer-readable storage medium, which includes a stored computer program, wherein when the computer program runs, a device in which the computer-readable storage medium is located is controlled to execute the peak-valley electricity rate and time interval optimization method according to any one of the above embodiments.
The above-mentioned embodiments are provided to further explain the objects, technical solutions and advantages of the present invention in detail, and it should be understood that the above-mentioned embodiments are only examples of the present invention and are not intended to limit the scope of the present invention. It should be understood that any modifications, equivalents, improvements and the like, which come within the spirit and principle of the invention, may occur to those skilled in the art and are intended to be included within the scope of the invention.
Claims (10)
1. A method for optimizing peak-to-valley electricity rates and time periods, comprising:
establishing a double-layer joint optimization model taking peak-valley electricity price and peak-valley time period as independent variables;
generating hours corresponding to a peak-valley period, starting iterative calculation of peak-valley electricity price and the peak-valley period according to the peak-valley period generated by power load initialization of a power grid, optimizing the peak-valley electricity price in the double-layer combined optimization model in each iterative calculation of the peak-valley electricity price and the peak-valley period to obtain a first target function value of the peak-valley optimized electricity price, and optimizing the peak-valley period in the double-layer combined optimization model to obtain a second target function value of the peak-valley optimized period, so that when the first target function value and the second target function value are the same, the peak-valley optimized electricity price, the peak-valley optimized period and the second target function are recorded and used as an optimization scheme of current iteration, and the recorded optimization scheme after each iteration is output until the iteration times reach preset times;
and comparing the second objective function values in all the optimization schemes, thereby outputting the optimal second objective function value and the corresponding peak-valley electricity price and peak-valley time period thereof.
2. The method according to claim 1, wherein the establishing of the two-layer joint optimization model using the peak-to-valley electricity price and the peak-to-valley period as arguments specifically comprises:
according to the peak-valley electricity price and the peak-valley time period under the time-of-use electricity price mechanism, taking the peak-valley electricity price and the peak-valley time period as independent variables, constructing a double-layer joint optimization model taking the peak-valley electricity price and the peak-valley time period as the independent variables, and constraining the peak-valley electricity price and the peak-valley time period:
F x x≥f x ，F y y≥f y ，G x x＝g x ，G y y＝g y ，U x x+U y y≥u，V x x+V y y = v; wherein M (x, y, M, i) ≧ M i i＝1,2,3,...，N(x,y,n,j)＝Π j j＝1,2,3,...；
Wherein w is an objective function value; x is a variable vector of peak-to-valley electricity prices; y is a variable vector of the peak-valley period; c. C x 、c y Coefficient vectors corresponding to x and y respectively;
is a coefficient constant; f x 、F y 、G x 、G y 、U x 、U y 、V x 、V y Are coefficient matrices; f. of x 、f y 、g x 、g y 、u、v、Μ i 、Π j Are all constant vectors;
are all coefficient constants.
3. The method for optimizing peak-valley electricity prices and time periods according to claim 2, wherein the number of hours corresponding to the peak-valley time period is generated, and the generated peak-valley time period is initialized according to the power load of the power grid, specifically:
according to the power load curve of the power grid, the load is taken from large to small in the peak time period until all the hours meeting the peak time period are obtained, the load is taken from small to large in the valley time period until all the hours meeting the valley time period are obtained, and the rest time period is taken as the flat time period, so that the initialization of the peak-valley time period is completed.
4. The method according to claim 3, wherein the optimization of the peak-to-valley electricity prices in the two-layer joint optimization model obtains a first objective function value of the peak-to-valley optimized electricity prices, specifically:
according to the initialized peak-valley time period, optimizing and calculating the peak-valley electricity price in the double-layer combined optimization model:
F x x≥f x ，G x x＝g x ，U x x+U y y≥u，V x x+V y y = v; wherein M (x, y, M, i) ≧ M i i＝1,2,3,...，N(x,y,n,j)＝Π j j =1,2,3.; thereby obtaining a first objective function value of the peak-valley optimized electricity prices.
5. The method according to claim 3, wherein the optimization of the peak-to-valley period in the two-layer joint optimization model obtains a second objective function value of the peak-to-valley optimization period, specifically:
and optimizing and calculating the peak-valley time period in the double-layer combined optimization model according to the peak-valley optimization electricity price:
F y y≥f y ，G y y＝g y ，U x x+U y y≥u，V x x+V y y = v; wherein M (x, y, M, i) ≥ M i i＝1,2,3,...，N(x,y,n,j)＝Π j j =1,2,3.; thereby obtaining a second objective function value for the peak-to-valley optimization interval.
6. The method of claim 4, wherein after optimizing the peak-to-valley period in the dual-layer joint optimization model to obtain the second objective function value of the peak-to-valley optimization period, the method further comprises:
and when the first objective function value is different from the second objective function value, performing optimization calculation on the peak-valley electricity price again, and performing optimization calculation on the peak-valley time period until the first objective function value obtained by optimization calculation is equal to the corresponding second objective function value.
7. The method as claimed in claim 4, wherein the comparing the second objective function value in all the optimization schemes to output the optimal second objective function value and the corresponding peak-to-valley electricity price and peak-to-valley period comprises:
and comparing the second objective function values in all the optimization schemes to obtain the minimum second objective function value, and outputting the peak-valley electricity price and the peak-valley time period corresponding to the minimum second objective function value.
8. An apparatus for peak-to-valley electricity rate and time period optimization, comprising: the device comprises a modeling module, an optimizing module and an output module;
the modeling module is used for establishing a double-layer joint optimization model taking peak-valley electricity price and peak-valley time period as independent variables;
the optimization module is used for generating hours corresponding to a peak-valley period, starting iterative calculation of peak-valley electricity prices and the peak-valley period according to the peak-valley period generated by power load initialization of a power grid, optimizing the peak-valley electricity prices in the double-layer combined optimization model to obtain a first target function value of the peak-valley optimized electricity prices in each iterative calculation of the peak-valley electricity prices and the peak-valley period, optimizing the peak-valley period in the double-layer combined optimization model to obtain a second target function value of the peak-valley optimized period, recording the peak-valley optimized electricity prices, the peak-valley optimized period and the second target function as an optimization scheme of current iteration when the first target function value is the same as the second target function value, and outputting the recorded optimization scheme after each iteration until the iteration number reaches a preset number;
and the output module is used for comparing the second objective function values in all the optimization schemes, so as to output the optimal second objective function value and the corresponding peak-valley electricity price and peak-valley time period.
9. A terminal device comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, the processor when executing the computer program implementing the peak-to-valley electricity rate and time period optimization method of any one of claims 1-7.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium comprises a stored computer program; wherein the computer program when executed controls an apparatus in which the computer readable storage medium is located to perform the peak-to-valley electricity rate and time period optimization method of any one of claims 1-7.
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| CN117060425B (en) * | 2023-10-12 | 2024-04-09 | 国网浙江省电力有限公司宁波供电公司 | Distribution network peak-valley difference self-adaptive control method and system based on reinforcement learning |
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