CN105320999A - Combination method for demand response based time-of-use power price strategy suitable for smart grid development - Google Patents
Combination method for demand response based time-of-use power price strategy suitable for smart grid development Download PDFInfo
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Abstract
The present invention discloses a combination method for a demand response based time-of-use power price strategy suitable for smart grid development. The combination method comprises the following steps: estimating electricity price affordability of enterprises with changes in multiple factors; according to a system load situation in conjunction with user demand-side analysis with seasonal attributes, carrying out period optimization that takes the seasonal attributes into account; and based on analysis of demand price elasticity in industries, differentiating application of the time-of-use power price in different situations, thereby forming a demand response based time-of-use power price strategy. According to the combination method for the time-of-use power price strategy, for different seasons, valley and peak power prices suitable for the seasons are set according to differences in demand price elasticity, so as to finally form a time-of-use power price strategy that combines peak and valley power prices, time-of-use power prices, and season-differentiated power prices.
Description
Technical field
The invention belongs to demand Side Management field, be specifically related to the combined method of the demand response tou power price strategy of a kind of intelligent grid development.
Background technology
China is in order to the challenge tackling day by day serious environmental problem, energy security problem is brought, State Grid Corporation of China strives for electrical network from traditional electrical network to the upgrading of efficient, economic, clean, interactive modern power network and leap, positive promotion clean energy resource development, proposes developing goal and the planning of building " strong intelligent grid ".
In China's power supply architecture, progressively strengthen regenerative resource accounting at present, therefore the utilization of effectively dissolving of new forms of energy is the problems needing to pay close attention to.In addition in recent years national economy to be in middle low speed momentum of development comparatively large to commercial power loading effects, and in the whole society in power consumption industrial user's power consumption occupy main status, the many provinces of China reach more than 80%.
For adapting to the integrated planning of intelligent grid development, actively promoting dissolving of regenerative resource, and encouraging the efficient electricity consumption of user, in the urgent need to implementing demand response strategy in user side.Demand response strategy effectively can shift the peakload of electrical network, alleviates shortage of electric power situation, ensures power grid security reliability service; And the ratio of dissolving of regenerative resource can be promoted, pull the load that area is overall, simultaneously environmental protect quality.
USDOE has just carried out demand Side Management research as far back as the seventies in last century, by adopting the management of power use technology of science and setting up the methods such as rational electricity price regulation, peak load is cut down, power consumption efficiency is improved, and electric power resource is saved thus achieved distinct economic.At present, 7 regional power systems such as California, USA, New England and New Jersey one, Pennsylvania one Maryland (PJM), and Pacific Ocean rock gas is with electrically numerous Utilities Electric Co. such as (PG & E) and Southern California Edison (SCE) is all own through establishing the Demand Side Response project based on the market promotion successively.
The developed country such as American-European has higher level in power network development construction and operational management, to have accumulated compare rich experience in demand Side Management with responder face.2003,15 member states such as Britain, Sweden, Spain participated in the Demand Side Response resource item of being taken the lead by USDOE (TheDepartmentofEnergy, DOE).
China launched the research to demand response aspect from 2004, achieve certain achievement in research at present, mainly concentrate on the ultimate principle of demand response and classification, Effect and impact to China's electricity market, the cost effectiveness analysis of demand response, the formulation of all kinds of Spot Price Model, according to foreign demand response implementation experience to aspects such as the opinions and suggestions of China's dsm aspect.But the market-oriented reform of China is for a long time confined to the link that generates electricity, and separates the factory and network, surfs the Net at a competitive price, and very limited in the reform of the user side marketization.Until the electricity about in-depth power market reform that the Central Committee of the Communist Party of China in 2015, State Council issue changes No. 9 literary compositions, the electricity market reform of China just starts to enter the reform stage that realizes.
Therefore, in energy development and the electricity market reform of China under the new situation, need the management of power use technology that studies science and set up rational electricity price regulation, this patent is dissolved in promotion regenerative resource and is guided in the efficient electricity consumption of user and has important theory directive significance and practice effect.
Summary of the invention
For the deficiencies in the prior art, the object of this invention is to provide a kind of combined method adapting to the demand response tou power price strategy of intelligent grid development, for solving the efficiency utilization of electric energy.
Adapt to a combined method for the demand response tou power price strategy of intelligent grid development, said method comprising the steps of:
S1, calculates the electricity price ability to bear of enterprise under multifactor variation;
S2, according to system loading situation, and in conjunction with the Demand-side analysis of user of attribute in season, the period carrying out taking into account attribute in season is optimized;
S3, on the basis that the every profession and trade price elasticity of demand is analyzed, to tou power price in varied situations should be used as differentiation process, thus to be formed based on the tou power price strategy of demand response.
Preferably, under described S1 measuring and calculating electricity price ability to bear of enterprise under multifactor variation comprises enterprise's electricity price ability to bear measuring and calculating and multifactor variation, enterprise's electricity price ability to bear is calculated;
The electricity price ability to bear measuring and calculating of described enterprise comprises following process, with reference to the production and operation raw data of enterprise, arrange out the relation of the cost of electric energy and total cost, when enterprise product price and other cost items remain unchanged, according to the rate of gross profit level of enterprise, calculate the susceptibility factor of enterprise's rate of gross profit to electricity price, in conjunction with between the rate of gross profit horizontal zone that enterprise can bear, thus obtain enterprise and can bear electricity price interval, namely enterprise is to the ability to bear of Electricity price fluctuation;
Under described multifactor variation, the measuring and calculating of enterprise's electricity price ability to bear comprises following process, based on Part I results of measuring, add the susceptibility factor of rate of gross profit to price, raw material and all the other costs, extract the inner link of electricity price susceptibility and rate of gross profit, price, raw material and all the other costs, analyze the impact of all the other factors vary on enterprise's electricity price ability to bear, thus obtaining under multifactor variation, enterprise is to the ability to bear of Electricity price fluctuation.
Preferably, the period optimization carrying out taking into account attribute in season in described S2 is specially: according to the historical load data of electric system, the prediction of following maximum monthly load, and 24 hourly load forecastings, the fuzzy membership function of application fuzzy mathematics, division is made to Pinggu, peak period of tou power price and flexible spike period, simultaneously, in conjunction with the analysis to the corresponding cost of electric power demand side every profession and trade, responding ability and point seasonal response characteristic, change the Time segments division mode in units of year, respectively optimization is made to the Time segments division in spring, summer, autumn and winter in each season.
Preferably, the described tou power price strategy based on demand response comprises basic time-of-use tariffs, flexibly Critical Peak Pricing and calendar variation electricity price three part, the described tou power price strategy based on demand response is specially point load data change in season according to every profession and trade under different electricity price background, ask for demand price own elasticity and coefficient of cross elasticity, build the demand tracing of reflection every profession and trade demand response characteristic, and the same industry Various Seasonal demand tracing of reflection Seasonal Characteristics; After obtain the tou power price optimized according to price elasticity of demand analysis, to tou power price in varied situations should be used as differentiation process, thus form a kind of tou power price strategy having merged time-of-use tariffs, tou power price and calendar variation electricity price.
Technical scheme of the present invention has following beneficial effect:
The present invention first proposed the combined method of demand response tou power price strategy adapting to intelligent grid development, analyzes the ability to bear of different enterprise to Electricity price fluctuation, thus provides foundation for the tou power price policy development of demand response; Secondly, the period having carried out taking into account attribute in season is optimized, and according to system loading situation, and in conjunction with the Demand-side analysis of user of attribute in season, is optimized the division of peak valley section and spike period at ordinary times; Tou power price strategy based on demand response is finally proposed.The combined method of this tou power price strategy can for different seasons, the difference of price elasticity according to demand, arrange the peak valley and Critical Peak Pricing that adapt to this season, the tou power price strategy of time-of-use tariffs, tou power price and calendar variation electricity price has been merged in final formation one.
Accompanying drawing explanation
Below by drawings and Examples, technical scheme of the present invention is described in further detail.
Fig. 1 is the measuring and calculating Organization Chart that the present invention adapts to measuring and calculating electricity price ability to bear of enterprise under multifactor variation of the combined method of the tou power price strategy of the Demand Side Response of intelligent grid development;
Fig. 2 be the present invention adapt to intelligent grid development Demand Side Response tou power price strategy combined method season attribute period optimization figure;
Fig. 3 is the Organization Chart that the present invention adapts to the tou power price strategy based on demand response of the combined method of the tou power price strategy of the Demand Side Response of intelligent grid development.
Embodiment
In order to have a clear understanding of technical scheme of the present invention, its detailed structure will be proposed in the following description.Obviously, the concrete execution of the embodiment of the present invention also not enough specific details being limited to those skilled in the art and haveing the knack of.The preferred embodiments of the present invention are described in detail as follows, and except these embodiments described in detail, can also have other embodiments.
Below in conjunction with drawings and Examples, the present invention is described in further details.
Embodiment of the present invention emphasis emphatically research adapts to the combined method of the tou power price strategy of the Demand Side Response of intelligent grid development.Comprise the following steps:
S1, calculates the electricity price ability to bear of enterprise under multifactor variation;
S2, according to system loading situation, and in conjunction with the Demand-side analysis of user of attribute in season, the period carrying out taking into account attribute in season is optimized;
S3, on the basis that the every profession and trade price elasticity of demand is analyzed, to tou power price in varied situations should be used as differentiation process, thus to be formed based on the tou power price strategy of demand response.
S1, calculates the electricity price ability to bear of enterprise under multifactor variation;
Analyze the ability to bear of different enterprise to Electricity price fluctuation, thus provide foundation for the tou power price policy development of demand response.Concrete measuring and calculating process is divided into " enterprise's electricity price ability to bear measuring and calculating " and " under multifactor variation the measuring and calculating of enterprise's electricity price ability to bear " two parts.
Enterprise's electricity price ability to bear measuring and calculating.The cost of electric energy is the part in enterprise's production cost, and the rise of electricity price or lower general who has surrendered cause the variation of production cost, impact the profit of enterprise.For different enterprise, the proportion that the cost of electric energy accounts for total cost is different, and therefore electricity price is floated and to be also not quite similar on the impact that it causes.
With reference to the production and operation raw data of enterprise, arrange out the relation of the cost of electric energy and total cost, when enterprise product price and other cost items remain unchanged, according to the rate of gross profit level of enterprise, calculate the susceptibility factor of enterprise's rate of gross profit to electricity price, in conjunction with between the rate of gross profit horizontal zone that enterprise can bear, thus obtain enterprise and can bear electricity price interval, namely enterprise is to the ability to bear of Electricity price fluctuation.
Enterprise's electricity price ability to bear measuring and calculating under multifactor variation.At Part I in the measuring and calculating of enterprise's electricity price ability to bear, calculate for simplifying, only analyze product price and other cost item when remaining unchanged, Electricity price fluctuation is on the impact of enterprise's rate of gross profit, but in the production management process of reality, due to the impact by changes in market supply and demand, enterprise's raw materials cost and product price are often floated, affect enterprise getting profit level, cause the electricity price ability to bear of enterprise also to change thereupon.
Therefore under being necessary to analyze multifactor variation situation, the electricity price ability to bear of enterprise.Based on Part I, add the susceptibility factor of rate of gross profit to price, raw material and all the other costs, extract the inner link of electricity price susceptibility and rate of gross profit, price, raw material and all the other costs, analyze the impact of all the other factors vary on enterprise's electricity price ability to bear, thus obtain under multifactor variation, enterprise is to the ability to bear of Electricity price fluctuation, and measuring and calculating framework as shown in Figure 1.
S2, according to system loading situation, and in conjunction with the Demand-side analysis of user of attribute in season, the period carrying out taking into account attribute in season is optimized;
First make preliminary Time segments division according to system loading data, on this basis, in conjunction with the Demand-side analysis of user of attribute in season, to peak valley, section and spike Time segments division are optimized at ordinary times.
The basic model that the Time segments division of tou power price relies on remains the fuzzy membership function of fuzzy mathematics, according to the historical load data of system, the prediction of following maximum monthly load, and 24 hourly load forecastings, division is made to Pinggu, peak period of tou power price and flexible spike period.Meanwhile, in conjunction with the analysis to the corresponding cost of electric power demand side every profession and trade, responding ability and point seasonal response characteristic, change the Time segments division mode in units of year, respectively optimization is made to the Time segments division in spring, summer, autumn and winter in each season.As shown in Figure 2.
S3, on the basis that the every profession and trade price elasticity of demand is analyzed, to tou power price in varied situations should be used as differentiation process, thus to be formed based on the tou power price strategy of demand response.
Power price grouped comprises basic time-of-use tariffs, flexible Critical Peak Pricing, and calendar variation electricity price three part, is optimized for basis with the period taking into account attribute in season, the tou power price strategy of research Demand-Oriented side.
The basis of formulation tou power price strategy is the analysis to the every profession and trade price elasticity of demand.First, according to point load data change in season of every profession and trade under different electricity price background, ask for demand price own elasticity and coefficient of cross elasticity, build the demand tracing of reflection every profession and trade demand response characteristic, and the same industry Various Seasonal demand tracing of reflection Seasonal Characteristics; After obtain the tou power price optimized according to price elasticity of demand analysis, to tou power price in varied situations should be used as differentiation process, thus form a kind of tou power price strategy having merged time-of-use tariffs, tou power price and calendar variation electricity price.As shown in Figure 3.
Such as, in certain normal non-spike day, electrical network performs Peak-valley TOU power price; In the spike day meeting spike criterion, increase and Critical Peak Pricing is set; For different seasons, the difference of price elasticity according to demand, arranges and adapts to the peak valley in this season and Critical Peak Pricing, final difference in a details and the tou power price strategy unified on the whole of being formed.
The present invention first proposed enterprise's electricity price ability to bear measuring method under multifactor variation, analyzes the ability to bear of different enterprise to Electricity price fluctuation, thus provides foundation for the tou power price policy development of demand response; Secondly, the period having carried out taking into account attribute in season is optimized, and according to system loading situation, and in conjunction with the Demand-side analysis of user of attribute in season, is optimized the division of peak valley section and spike period at ordinary times; Tou power price strategy based on demand response is finally proposed.The combined method of this tou power price strategy can for different seasons, the difference of price elasticity according to demand, arrange the peak valley and Critical Peak Pricing that adapt to this season, the tou power price strategy of time-of-use tariffs, tou power price and calendar variation electricity price has been merged in final formation one.
Finally should be noted that: above embodiment is only in order to illustrate that technical scheme of the present invention is not intended to limit; although with reference to above-described embodiment to invention has been detailed description; those of ordinary skill in the field still can modify to the specific embodiment of the present invention or equivalent replacement; these do not depart from any amendment of spirit and scope of the invention or equivalent replacement, are all applying within the claims awaited the reply.
Claims (4)
1. adapt to a combined method for the demand response tou power price strategy of intelligent grid development, it is characterized in that, said method comprising the steps of:
S1, calculates the electricity price ability to bear of enterprise under multifactor variation;
S2, according to system loading situation, and in conjunction with the Demand-side analysis of user of attribute in season, the period carrying out taking into account attribute in season is optimized;
S3, on the basis that the every profession and trade price elasticity of demand is analyzed, to tou power price in varied situations should be used as differentiation process, thus to be formed based on the tou power price strategy of demand response.
2. the combined method of the demand response tou power price strategy of adaptation intelligent grid development according to claim 1, it is characterized in that, under described S1 measuring and calculating electricity price ability to bear of enterprise under multifactor variation comprises enterprise's electricity price ability to bear measuring and calculating and multifactor variation, enterprise's electricity price ability to bear is calculated;
The electricity price ability to bear measuring and calculating of described enterprise comprises following process, with reference to the production and operation raw data of enterprise, arrange out the relation of the cost of electric energy and total cost, when enterprise product price and other cost items remain unchanged, according to the rate of gross profit level of enterprise, calculate the susceptibility factor of enterprise's rate of gross profit to electricity price, in conjunction with between the rate of gross profit horizontal zone that enterprise can bear, thus obtain enterprise and can bear electricity price interval, namely enterprise is to the ability to bear of Electricity price fluctuation;
Under described multifactor variation, the measuring and calculating of enterprise's electricity price ability to bear comprises following process, based on Part I results of measuring, add the susceptibility factor of rate of gross profit to price, raw material and all the other costs, extract the inner link of electricity price susceptibility and rate of gross profit, price, raw material and all the other costs, analyze the impact of all the other factors vary on enterprise's electricity price ability to bear, thus obtaining under multifactor variation, enterprise is to the ability to bear of Electricity price fluctuation.
3. the combined method of the demand response tou power price strategy of adaptation intelligent grid development according to claim 1, it is characterized in that, the period optimization carrying out taking into account attribute in season in described S2 is specially: according to the historical load data of electric system, following maximum monthly load prediction, and 24 hourly load forecastings, the fuzzy membership function of application fuzzy mathematics, division is made to Pinggu, peak period of tou power price and flexible spike period, simultaneously, in conjunction with to the corresponding cost of electric power demand side every profession and trade, the analysis of responding ability and point seasonal response characteristic, change the Time segments division mode in units of year, respectively optimization is made to the Time segments division in spring, summer, autumn and winter in each season.
4. the combined method of the demand response tou power price strategy of adaptation intelligent grid development according to claim 1, it is characterized in that, the described tou power price strategy based on demand response comprises basic time-of-use tariffs, flexible Critical Peak Pricing and calendar variation electricity price three part, the described tou power price strategy based on demand response is specially point load data change in season according to every profession and trade under different electricity price background, ask for demand price own elasticity and coefficient of cross elasticity, build the demand tracing of reflection every profession and trade demand response characteristic, and the same industry Various Seasonal demand tracing of reflection Seasonal Characteristics, after obtain the tou power price optimized according to price elasticity of demand analysis, to tou power price in varied situations should be used as differentiation process, thus form a kind of tou power price strategy having merged time-of-use tariffs, tou power price and calendar variation electricity price.
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106529704A (en) * | 2016-10-31 | 2017-03-22 | 国家电网公司 | Monthly maximum power load forecasting method and apparatus |
| CN107045657A (en) * | 2017-04-01 | 2017-08-15 | 国网宁夏电力公司经济技术研究院 | Analyzing Total Electricity Consumption calculating system and method |
| CN110245972A (en) * | 2019-04-26 | 2019-09-17 | 国网浙江省电力有限公司衢州供电公司 | A kind of more electricity prices meterings of power grid and scheduling system |
| CN110245777A (en) * | 2019-04-26 | 2019-09-17 | 国网浙江省电力有限公司衢州供电公司 | A kind of dispatching method of electric network based on more Price Mechanisms |
| CN111681133A (en) * | 2020-06-19 | 2020-09-18 | 国网北京市电力公司 | Method and device for processing electric load information |
| CN111798057A (en) * | 2020-07-06 | 2020-10-20 | 四川中电启明星信息技术有限公司 | Charging station site selection method based on fuzzy level profit analysis |
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2015
- 2015-11-03 CN CN201510735245.3A patent/CN105320999A/en active Pending
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106529704A (en) * | 2016-10-31 | 2017-03-22 | 国家电网公司 | Monthly maximum power load forecasting method and apparatus |
| CN107045657A (en) * | 2017-04-01 | 2017-08-15 | 国网宁夏电力公司经济技术研究院 | Analyzing Total Electricity Consumption calculating system and method |
| CN110245972A (en) * | 2019-04-26 | 2019-09-17 | 国网浙江省电力有限公司衢州供电公司 | A kind of more electricity prices meterings of power grid and scheduling system |
| CN110245777A (en) * | 2019-04-26 | 2019-09-17 | 国网浙江省电力有限公司衢州供电公司 | A kind of dispatching method of electric network based on more Price Mechanisms |
| CN111681133A (en) * | 2020-06-19 | 2020-09-18 | 国网北京市电力公司 | Method and device for processing electric load information |
| CN111681133B (en) * | 2020-06-19 | 2023-10-27 | 国网北京市电力公司 | Method and device for processing electric load information |
| CN111798057A (en) * | 2020-07-06 | 2020-10-20 | 四川中电启明星信息技术有限公司 | Charging station site selection method based on fuzzy level profit analysis |
| CN111798057B (en) * | 2020-07-06 | 2023-11-10 | 四川中电启明星信息技术有限公司 | Charging station site selection method based on fuzzy-hierarchy profit analysis |
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