CN104809294A - Establishing method for responsivity model of user for time-of-use electricity price - Google Patents
Establishing method for responsivity model of user for time-of-use electricity price Download PDFInfo
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- CN104809294A CN104809294A CN201510215305.9A CN201510215305A CN104809294A CN 104809294 A CN104809294 A CN 104809294A CN 201510215305 A CN201510215305 A CN 201510215305A CN 104809294 A CN104809294 A CN 104809294A
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- 230000005611 electricity Effects 0.000 title claims abstract description 38
- 238000000034 method Methods 0.000 title claims abstract description 28
- 230000004044 response Effects 0.000 claims abstract description 27
- 229920006395 saturated elastomer Polymers 0.000 claims abstract description 7
- 230000000638 stimulation Effects 0.000 claims abstract description 6
- 230000004043 responsiveness Effects 0.000 claims description 11
- 238000011002 quantification Methods 0.000 claims description 3
- 230000000694 effects Effects 0.000 description 2
- 230000031016 anaphase Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 238000012886 linear function Methods 0.000 description 1
- 238000013178 mathematical model Methods 0.000 description 1
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
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Abstract
The invention discloses an establishing method for a responsivity model of a user for a time-of-use electricity price. According to the method, under the condition of meeting the basic safety electricity use, a peak-valley price difference is adopted for realizing peak clipping and valley filling, wherein the larger the peak-valley price difference is, the higher the positivity of the user for peak clipping and valley filling is; when the peak-valley price difference is increased to a certain threshold value, the stimulation to the user reaches a limiting value, namely, the response of the user also reaches a saturated state, and the user no longer responds along with the further increasing of the peak-valley price difference. According to the establishing method, a function relationship between peak-valley electric quantity ratio and peak-valley price ratio of the user is established, so that a scientific basis for setting the electricity price is supplied to a grid company. Through the function relationship, the economic efficiency of the grid company and the user can be effectively protected, the peak-valley price ratio can be adjusted according to the practical electricity use condition of the user, and the economic efficiency of the grid company and the user can be extremely ensured.
Description
Technical field
The present invention relates to the method for building up of a kind of user to the responsiveness model of tou power price, belong to electric power network technique field.
Background technology
When after the division completing the tou power price period, to peak valley price difference ratio, grid company is set as that it is crucial, if peak valley price difference is lower than too, user does not almost respond tou power price or responds very little, does not reach the object of tou power price setting, if peak valley price difference is than too low too high, understand the business efficiency of harm users greatly, prior art generally all adopts the mode of experience to set peak valley price difference ratio, and the method is scientific and anaphase effect is all poor, is difficult to meet current demand.
Summary of the invention
The object of the invention is: for the defect of prior art, there is provided a kind of user to the method for building up of the responsiveness model of tou power price, can science be objective shows the response of user to tou power price, for Scientific Establishment peak valley price difference ratio provides foundation, to overcome the deficiencies in the prior art.
Technical scheme of the present invention
A kind of user is to the method for building up of the responsiveness model of tou power price, the method adopts under the prerequisite meeting basic security electricity consumption, electricity price between peak and valley is adopted to realize being used for peak load shifting, wherein electricity price between peak and valley is larger, more can stimulate the enthusiasm of user's peak load shifting, when electricity price between peak and valley increases to certain threshold value, a ultimate value be reached to the stimulation of user, namely the response of user also reaches saturated, and user can not respond along with the further increase of electricity price between peak and valley; The concrete model of this responsiveness is as follows:
Wherein, k
1represent electrical price pattern; k
2represent peak-valley electric energy ratio;
Work as k
1min=1, when namely not implementing tou power price, k
2maxfor the initial peak valley electricity ratio of power consumer, that is to say the initial threshold that user responds; Along with k
1increase, enter the linear zone of load responding, user starts to respond tou power price, and load starts to shift, and corresponding load peak-valley electric energy compares k
2continuous minimizing; When arriving certain threshold value k
1maxtime, user's response is tending towards saturated, and user will no longer change along with the change of electricity price, and namely peak-valley electric energy no longer reduces along with the increase of k1 than k2, and k2 also reaches corresponding saturation value k
2min.
Aforesaid a kind of user in the method for building up of the responsiveness model of tou power price, the parameter k of customer response model
1max, k
2maxand k
2minacquiring method is;
One, k
2maxwhat represent is the peak-valley electric energy ratio of user when not implementing tou power price on initial user load curve, and that is to say the initial threshold of response model, this parameter directly can be asked for according on the load curve of user;
Two, k
2minwhat represent is the maximum peak valley electricity ratio that user can occur when peak load shifts after implementing tou power price, different user particularly industrial user often all can have a ultimate value when carrying out load transfer plan due to the mode of production of industry, technological process difference, when this limit value is reached, no matter electricity price stimulates large again, user also no longer will make response, k
2mincorresponding k1 is exactly k
1max, that is to say that user, to electricity price, electrical price pattern when responding no longer occurs, wherein k
2minand k
1maxbad direct quantification is determined, adopts least square method to carry out parameter estimation, and namely setting is implemented the quadratic sum of the estimated value of peak-valley electric energy ratio after tou power price and the difference of measured value minimum is objective function:
Wherein, k2i is the estimated value of the peak-valley electric energy ratio of user after i-th enforcement tou power price; K2i ' is the measured value of user's peak-valley electric energy ratio after i-th enforcement tou power price, in order to make objective function reach minimum, adopts least square method to ask extreme value to carry out parameter estimation to objective function.
Owing to have employed technique scheme; compared with prior art; the present invention is by setting up the peak-valley electric energy of user than the funtcional relationship with electrical price pattern; for grid company formulates the foundation of the science that electricity price provides; by this funtcional relationship; can the business efficiency of available protecting grid company and user, the adjustment of electrical price pattern can be carried out again according to the electricity consumption situation of user's reality, maximize the business efficiency that ensure that grid company and user.
Accompanying drawing explanation
Accompanying drawing 1 is effect degree model schematic of the present invention.
Embodiment
Below in conjunction with accompanying drawing to the present invention with being described in further detail, but not as any limitation of the invention.
Embodiments of the invention: degree should wait n user to the responsiveness model of tou power price
One. the mathematical model of user's response
The part throttle characteristics, industry characteristic, the mode of production etc. of user to the responsiveness of tou power price and user is all closely related, the load responding curve of power consumer to tou power price of areal is also different, but, the cardinal rule of different user response is consistent, namely under the prerequisite meeting basic security electricity consumption, be all that electricity price between peak and valley is larger, more can stimulate the enthusiasm of user's peak load shifting.
When the electricity price between peak and valley of tou power price is less, also less to the stimulation of user, user does not almost respond tou power price or responds very little, when electricity price between peak and valley increases, also increase the stimulation of user, the response of user to tou power price also strengthens gradually thereupon, when electricity price between peak and valley increases to certain threshold value, reach a ultimate value to the stimulation of user, namely the response of user also reaches saturated, and user can not respond along with the further increase of electricity price between peak and valley.In order to simplified model, this response process piecewise linear function can be represented, as shown in Figure 1.
Wherein, k1 represents electrical price pattern; K2 represents peak-valley electric energy ratio.
When k1min=1(does not implement tou power price) time, k2max is the initial peak valley electricity ratio of power consumer, that is to say the initial threshold that user responds; Along with the increase of k1, enter the linear zone of load responding, user starts to respond tou power price, and load starts to shift, corresponding load peak-valley electric energy minimizing more continuous than k2; When arriving certain threshold value k1max, user's response is tending towards saturated, and user will no longer change along with the change of electricity price, and namely peak-valley electric energy no longer reduces along with the increase of k1 than k2, and k2 also reaches corresponding saturation value k2min.
Two. the parameter of customer response model is asked for
Although for all power consumers, k1min=1 represents that electrical price pattern is the same terms of 1 when not implementing tou power price, but the response curve of different power consumer is differentiated, be reflected in the linearity range slope of response curve, the difference of saturation region threshold value, namely the value of k1max, k2max, k1min is different, and the reasonable value degree of these three parameters will directly embody the really degree of user's response curve.
What k2max represented is the peak-valley electric energy ratio of user when not implementing tou power price on initial user load curve, that is to say the initial threshold of response model, this parameter directly can be asked for according on the load curve being divided in user of the timesharing period set.
What k2min represented is the maximum peak valley electricity ratio that user can occur when peak load shifts after implementing tou power price, different user particularly industrial user often all can have a ultimate value when carrying out load transfer plan due to the mode of production of industry, technological process difference, when this limit value is reached, no matter electricity price stimulates large again, and user also no longer will make response.K1 corresponding to k2min is exactly k1max, that is to say that user, to electricity price, electrical price pattern when responding no longer occurs.
In above three parameters except k2max can directly quantize to ask for, the bad direct quantification of k2min and k1max is determined, needs constantly to carry out matching to response curve, just can ask for after Approach by inchmeal.Least square method can be adopted to carry out parameter estimation, and namely setting is implemented the quadratic sum of the estimated value of peak-valley electric energy ratio after tou power price and the difference of measured value minimum is objective function:
Wherein, k2i is the estimated value of the peak-valley electric energy ratio of user after i-th enforcement tou power price; K2i ' is the measured value of user's peak-valley electric energy ratio after i-th enforcement tou power price.In order to make objective function reach minimum, least square method is adopted to ask extreme value to carry out parameter estimation to objective function.
When implementing number of times and being more, the sample measured value observed is also more, and the estimated value of function parameter is also more close to actual value, and the really degree of the matching of user's response curve is also higher, also more can react the true response condition of user.
Claims (2)
1. a user is to the method for building up of the responsiveness model of tou power price, it is characterized in that: the method adopts under the prerequisite meeting basic security electricity consumption, electricity price between peak and valley is adopted to realize being used for peak load shifting, wherein electricity price between peak and valley is larger, more can stimulate the enthusiasm of user's peak load shifting, when electricity price between peak and valley increases to certain threshold value, a ultimate value be reached to the stimulation of user, namely the response of user also reaches saturated, and user can not respond along with the further increase of electricity price between peak and valley; The concrete model of this responsiveness is as follows:
Wherein, k
1represent electrical price pattern; k
2represent peak-valley electric energy ratio;
Work as k
1min=1, when namely not implementing tou power price, k
2maxfor the initial peak valley electricity ratio of power consumer, that is to say the initial threshold that user responds; Along with k
1increase, enter the linear zone of load responding, user starts to respond tou power price, and load starts to shift, and corresponding load peak-valley electric energy compares k
2continuous minimizing; When arriving certain threshold value k
1maxtime, user's response is tending towards saturated, and user will no longer change along with the change of electricity price, and namely peak-valley electric energy no longer reduces along with the increase of k1 than k2, and k2 also reaches corresponding saturation value k
2min.
2. a kind of user according to claim 1 is to the method for building up of the responsiveness model of tou power price, it is characterized in that: the parameter k of customer response model
1max, k
2maxand k
2minacquiring method is;
One, k
2maxwhat represent is the peak-valley electric energy ratio of user when not implementing tou power price on initial user load curve, and that is to say the initial threshold of response model, this parameter directly can be asked for according on the load curve of user;
Two, k
2minwhat represent is the maximum peak valley electricity ratio that user can occur when peak load shifts after implementing tou power price, different user particularly industrial user often all can have a ultimate value when carrying out load transfer plan due to the mode of production of industry, technological process difference, when this limit value is reached, no matter electricity price stimulates large again, user also no longer will make response, k
2mincorresponding k1 is exactly k
1max, that is to say that user, to electricity price, electrical price pattern when responding no longer occurs, wherein k
2minand k
1maxbad direct quantification is determined, adopts least square method to carry out parameter estimation, and namely setting is implemented the quadratic sum of the estimated value of peak-valley electric energy ratio after tou power price and the difference of measured value minimum is objective function:
Wherein, k2i is the estimated value of the peak-valley electric energy ratio of user after i-th enforcement tou power price; K2i ' is the measured value of user's peak-valley electric energy ratio after i-th enforcement tou power price, in order to make objective function reach minimum, adopts least square method to ask extreme value to carry out parameter estimation to objective function.
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Cited By (5)
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| CN107516151A (en) * | 2017-09-04 | 2017-12-26 | 云南电网有限责任公司电力科学研究院 | A kind of electric appliance optimization method and system |
| CN111242702A (en) * | 2020-02-29 | 2020-06-05 | 贵州电网有限责任公司 | Method for formulating power grid peak-valley time-of-use electricity price considering minimum system peak-valley difference |
| CN111784409A (en) * | 2020-07-13 | 2020-10-16 | 南方电网能源发展研究院有限责任公司 | Model construction method, device, equipment and medium for configuring peak clipping measures |
| CN112862535A (en) * | 2021-02-25 | 2021-05-28 | 国网河北省电力有限公司营销服务中心 | Method for determining power price responsiveness of power-dedicated transformer client and terminal equipment |
| CN113268932A (en) * | 2021-06-15 | 2021-08-17 | 贵州大学 | Landslide displacement prediction method based on Gaussian process regression and neural network |
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Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN111784409A (en) * | 2020-07-13 | 2020-10-16 | 南方电网能源发展研究院有限责任公司 | Model construction method, device, equipment and medium for configuring peak clipping measures |
| CN111784409B (en) * | 2020-07-13 | 2024-04-26 | 南方电网能源发展研究院有限责任公司 | Model construction method, device, equipment and medium for configuring peak clipping measures |
| CN112862535A (en) * | 2021-02-25 | 2021-05-28 | 国网河北省电力有限公司营销服务中心 | Method for determining power price responsiveness of power-dedicated transformer client and terminal equipment |
| CN113268932A (en) * | 2021-06-15 | 2021-08-17 | 贵州大学 | Landslide displacement prediction method based on Gaussian process regression and neural network |
| CN113268932B (en) * | 2021-06-15 | 2022-07-19 | 贵州大学 | Landslide displacement prediction method based on Gaussian process regression and neural network |
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Application publication date: 20150729 Assignee: Tianjin Xinxiang Technology Co.,Ltd. Assignor: Beijing Legend Yousheng Culture Media Co.,Ltd. Contract record no.: X2023980037700 Denomination of invention: Method for Establishing a Response Model of Users to Time of Use Electricity Prices Granted publication date: 20171222 License type: Common License Record date: 20230706 |
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