CN104574210A - Full-dimension electricity market analyzing and researching method - Google Patents
Full-dimension electricity market analyzing and researching method Download PDFInfo
- Publication number
- CN104574210A CN104574210A CN201510007930.4A CN201510007930A CN104574210A CN 104574210 A CN104574210 A CN 104574210A CN 201510007930 A CN201510007930 A CN 201510007930A CN 104574210 A CN104574210 A CN 104574210A
- Authority
- CN
- China
- Prior art keywords
- dimension
- model
- electricity market
- full
- analysis
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 230000005611 electricity Effects 0.000 title claims abstract description 39
- 238000000034 method Methods 0.000 title claims abstract description 16
- 238000004458 analytical method Methods 0.000 claims abstract description 32
- 230000007774 longterm Effects 0.000 claims abstract description 9
- 238000010586 diagram Methods 0.000 claims abstract description 8
- 238000011160 research Methods 0.000 claims description 14
- 238000012482 interaction analysis Methods 0.000 claims description 2
- 108010014173 Factor X Proteins 0.000 description 3
- 238000004141 dimensional analysis Methods 0.000 description 2
- 238000001556 precipitation Methods 0.000 description 2
- 238000012098 association analyses Methods 0.000 description 1
- 238000007796 conventional method Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000013213 extrapolation Methods 0.000 description 1
- YHXISWVBGDMDLQ-UHFFFAOYSA-N moclobemide Chemical compound C1=CC(Cl)=CC=C1C(=O)NCCN1CCOCC1 YHXISWVBGDMDLQ-UHFFFAOYSA-N 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0637—Strategic management or analysis, e.g. setting a goal or target of an organisation; Planning actions based on goals; Analysis or evaluation of effectiveness of goals
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/06—Energy or water supply
Landscapes
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Engineering & Computer Science (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- Tourism & Hospitality (AREA)
- General Business, Economics & Management (AREA)
- Health & Medical Sciences (AREA)
- Theoretical Computer Science (AREA)
- Marketing (AREA)
- Entrepreneurship & Innovation (AREA)
- General Physics & Mathematics (AREA)
- Educational Administration (AREA)
- Physics & Mathematics (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Development Economics (AREA)
- Game Theory and Decision Science (AREA)
- Public Health (AREA)
- Water Supply & Treatment (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
- Supply And Distribution Of Alternating Current (AREA)
Abstract
The invention discloses a full-dimension electricity market analyzing and researching method. In previous electricity market analysis, the electricity market demand environment is analyzed basically based on one type of information and a certain dimension. The full-dimension electricity market analyzing and researching method comprises the following steps that a full-dimension database influencing electricity market demands is established; all dimension electricity market analyzing frame diagrams are drawn; analyzing models for all dimensions and all service levels are established, and the models of all the service levels are associated; a full-dimension electricity market demand analyzing result is obtained. The electricity market is analyzed and studied in all the dimensions through full-dimension data and the associated models, and thus short-term, medium-term and long-term planning of the electricity market and the development direction and supply and demand analysis of the electricity market are facilitated.
Description
Technical field
The present invention relates to grid power market analysis and research application, specifically a kind of full dimension Electricity market analysis and research method.
Background technology
Electricity market analysis is in the past analyze electric power market demand environment based on a category information, certain dimension substantially.Such as certain electric power saving market demand analysis is generally analyze based on the electric power data self of its this province and study.Conventional method is trend extrapolation, ARIMA, gray prediction, traditional output value unit consumption method, elastic coefficient method etc., is all single model mostly.And the concept of full dimensional analysis and research, comprise each factor affecting electric power market demand exactly, as the research application model that internal and external factors, short-term factor and long term factor consider.By full dimension Electricity market analysis and research, the factor affecting electric power market demand can be dissected in further detail, electricity market is more intactly analyzed, to contribute to the short-term of electricity market, the rational of medium and long term planning.
Summary of the invention
Technical matters to be solved by this invention is the defect overcoming the existence of above-mentioned prior art, a kind of full dimension Electricity market analysis and research method are provided, it is by building full dimension data storehouse, set up the analytical model of each dimension and business level, and the model of each business level is associated, to obtain full dimension electric power market demand analyses and prediction result.
For this reason, the technical solution used in the present invention is: a kind of full dimension Electricity market analysis and research method, and it is characterized in that, the method comprises the following steps:
1) the full dimension data storehouse affecting electric power market demand is built, described full dimension data storehouse comprises the inside and outside influence factor, short-term factor and the long term factor data that affect electric power market demand, be specially and spatially comprise international macro environment data, the whole nation and each province and city data, time is contained year, season, monthly, day data, business comprises the full dimension integrated data such as electric power, economy, the energy, industry, trade, temperature, precipitation;
2) each dimension Electricity market analysis frame diagram is drawn;
3) set up the analytical model of each dimension and business level, and the model of each business level is associated;
4) by the model interaction analysis of each business level of previous step, obtain full dimension electric power market demand analysis result, consider each factor according to this analysis result electric power market demand is predicted.
Further, step 3) concrete steps as follows:
A) set up the analytical model of each dimension and business level: according to step 2) in each dimension Electricity market analysis frame diagram, build the analytical model of each dimension and business level respectively;
Produce added value and two for two and produce power consumption annual prediction model:
Y＝C+A*X
1+B*X
2，
Wherein, Y represents that two of t region produce added value, X
1represent that two of t region produce employment volume, X
2represent that two of t region produce investment in fixed assets, C is constant term, and A is factor X
1coefficient, B is factor X
2coefficient;
Y
□＝α+β*X
□，
Wherein, Y
□represent that two of t region produce power consumption, X
□represent that two of t region produce the CPI (2003=100) in added value/t regions, namely two of t region produce added values (can the rate of exchange), α is constant term, and β is factor X
□coefficient;
B) model of each business level is associated: obtain result by setting up last layer level model and running, then using the input variable of this result as next hierarchal model, obtain net result by running next hierarchal model.
The present invention utilizes full dimension data and relevance model to carry out the research of full dimensional analysis and prediction to electricity market, contributes to short-term, the medium and long term planning of carrying out electricity market, and the future thrust of electricity market and supply and demand analysis.
Accompanying drawing explanation
Fig. 1 is process flow diagram of the present invention;
Fig. 2 is Regional Macro economic System annual prediction model framework figure;
Fig. 3 is region quantity of electricity annual prediction model framework figure.
Embodiment
The present invention is further illustrated below in conjunction with Figure of description.
Analyses and prediction are carried out for the full dimension electric power market demand of the method for the invention to Zhejiang Province, first full dimension data storehouse is built, secondly according to analytical framework figure, set up the analytical model of each dimension and business level, and the model of each business level is associated, the Electricity market analysis finally obtaining full dimension predicts the outcome.
Full dimension Electricity market analysis as shown in Figure 1 and research method, comprise the following steps:
S1, build the full dimension data storehouse affecting electric power market demand;
In the present embodiment, for Zhejiang Province.The full dimension data storehouse of Zhejiang Province's full dimension Electricity market analysis and research comprises the inside and outside influence factor, short-term factor and the long term factor data that affect electric power market demand.Be specially and spatially comprise international macro environment data, the whole nation and each province and city data, the time is contained year, season, monthly, day data, business comprises the full dimension integrated data such as electric power, economy, the energy, industry, trade, temperature, precipitation.
S2, draw each dimension Electricity market analysis frame diagram: for Zhejiang Province's annual economical electric power conduction model, it researchs and analyses frame diagram as shown in Figures 2 and 3.As can be seen from the figure the level of economic development is the key factor affecting Zhejiang Province's electricity needs, is one of core in this full dimension application model by the analytical mathematics of economic conduct power.According to being divided into long-term model, medium-term and long-term model (annual model, season model) and short-run model the time when it builds, be divided into again economic model and power model two modules according to business dimension simultaneously.
S3, set up the analytical model of each dimension and business level, and the model of each business level is associated;
For Zhejiang Province's annual economical electric power conduction model:
(1) Zhejiang Province's annual economical and annual electric power analysis forecast model is set up respectively according to above-mentioned analytical framework figure;
Enumerate wherein Zhejiang Province two and produce added value and two product power consumption annual prediction models:
ln(Y)＝-7.9672+1.8172*ln(X
1)+0.4611*ln(X
2)
Wherein, Y represents that the Zhejiang Province two of t produces added value, X
1represent that the Zhejiang Province two of t produces employment volume, X
2represent that the Zhejiang Province two of t produces investment in fixed assets.
Y
□＝145.1395+17.3678*X
□+[MA(1)＝-08805]
Wherein, Y
□represent that the Zhejiang Province two of t produces power consumption, X
□represent that Zhejiang Province CPI (2003=100) i.e. Zhejiang Province two of t that Zhejiang Province two of t produces added value/t produces added value (can the rate of exchange).
(2) Zhejiang Province's annual economical is associated with annual power model: first to the Zhejiang Province's annual economical model established, high, normal, basic three kinds of different sight schemes are set (according to the urbanization ratio mentioned in Zhejiang Province's planning, level of economic development re-set target etc., height predicted value in three groups of the external input variable of given year economic model, in table 1), and operation is predicted the outcome, again using the predicted value of annual economical model prediction result as annual power model input variable, Zhejiang Electricity Market demand forecast result is obtained by running annual power model.
Table 1
S4, obtain full dimension electric power market demand analysis result: by annual economical and the power model association analysis of previous step, Zhejiang Province's Analyzing Total Electricity Consumption annual prediction value can be obtained, in table 2.
Table 2
Again in conjunction with the analysis of other dimensions, such as season model, temperature is on the impact etc. of electricity, predicted Zhejiang Electricity Market demand by the analysis of full dimension, final given Zhejiang Province Analyzing Total Electricity Consumption predicted value in 2014,2015 is respectively 3524,3,618 hundred million kilowatt hours.
The above embodiment is only be described the preferred embodiment of the present invention; not scope of the present invention is limited; under not departing from the present invention and designing the prerequisite of spirit; the various distortion that those of ordinary skill in the art make technical scheme of the present invention and improvement, all should fall in protection domain that claims of the present invention determine.
Claims (2)
1. full dimension Electricity market analysis and a research method, it is characterized in that, the method comprises the following steps:
1) build the full dimension data storehouse affecting electric power market demand, described full dimension data storehouse comprises the inside and outside influence factor, short-term factor and the long term factor data that affect electric power market demand;
2) each dimension Electricity market analysis frame diagram is drawn;
3) set up the analytical model of each dimension and business level, and the model of each business level is associated;
4) by the model interaction analysis of each business level of previous step, obtain full dimension electric power market demand analysis result, consider each factor according to this analysis result electric power market demand is predicted.
2. full dimension Electricity market analysis according to claim 1 and research method, is characterized in that, step 3) concrete steps as follows:
A) set up the analytical model of each dimension and business level: according to step 2) in each dimension Electricity market analysis frame diagram, build the analytical model of each dimension and business level respectively;
B) model of each business level is associated: obtain result by setting up last layer level model and running, then using the input variable of this result as next hierarchal model, obtain net result by running next hierarchal model.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510007930.4A CN104574210A (en) | 2015-01-08 | 2015-01-08 | Full-dimension electricity market analyzing and researching method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510007930.4A CN104574210A (en) | 2015-01-08 | 2015-01-08 | Full-dimension electricity market analyzing and researching method |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN104574210A true CN104574210A (en) | 2015-04-29 |
Family
ID=53090200
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201510007930.4A Pending CN104574210A (en) | 2015-01-08 | 2015-01-08 | Full-dimension electricity market analyzing and researching method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN104574210A (en) |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102903063A (en) * | 2012-09-19 | 2013-01-30 | 中国电力科学研究院 | Integral electricity market operation system |
| US20130113296A1 (en) * | 2011-11-08 | 2013-05-09 | Samsung Electronics Co., Ltd. | Wireless power transmission system, resonator in wireless power transmission system, and resonator design method for optimum power division |
| CN103413254A (en) * | 2013-09-04 | 2013-11-27 | 国家电网公司 | Medium-and-long-term load prediction research and management integration application system |
| CN104134102A (en) * | 2014-07-30 | 2014-11-05 | 国家电网公司 | LEAP-model-based method for predicating medium-and-long-term electricity demand distribution of power grid |
-
2015
- 2015-01-08 CN CN201510007930.4A patent/CN104574210A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20130113296A1 (en) * | 2011-11-08 | 2013-05-09 | Samsung Electronics Co., Ltd. | Wireless power transmission system, resonator in wireless power transmission system, and resonator design method for optimum power division |
| CN102903063A (en) * | 2012-09-19 | 2013-01-30 | 中国电力科学研究院 | Integral electricity market operation system |
| CN103413254A (en) * | 2013-09-04 | 2013-11-27 | 国家电网公司 | Medium-and-long-term load prediction research and management integration application system |
| CN104134102A (en) * | 2014-07-30 | 2014-11-05 | 国家电网公司 | LEAP-model-based method for predicating medium-and-long-term electricity demand distribution of power grid |
Non-Patent Citations (1)
| Title |
|---|
| 赖敏 等: "影响电力消费市场因素分析研究", 《电力技术经济》 * |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Jin et al. | Spatiotemporal patterns in urbanization efficiency within the Yangtze River Economic Belt between 2005 and 2014 | |
| Liao | The evolution of wind energy policies in China (1995–2014): An analysis based on policy instruments | |
| Zhao et al. | Digital‐Twin‐Based Evaluation of Nearly Zero‐Energy Building for Existing Buildings Based on Scan‐to‐BIM | |
| Tardioli et al. | Data driven approaches for prediction of building energy consumption at urban level | |
| Chen et al. | City size and urban labor productivity in China: New evidence from spatial city-level panel data analysis | |
| Liu et al. | Impact of digital economy on urban sustainable development: Evidence from Chinese cities | |
| CN104091293B (en) | The power network long-term load characteristic prediction method changed based on power structure | |
| Chen et al. | A multi-objective optimization strategy for building carbon emission from the whole life cycle perspective | |
| Wang et al. | A cost–benefit analysis of the environmental taxation policy in China: A frontier analysis‐based environmentally extended input–output optimization method | |
| Li et al. | Hybrid Emergy-LCA (HEML) based metabolic evaluation of urban residential areas: The case of Beijing, China | |
| Wu et al. | LCA-based economic benefit analysis for building integrated photovoltaic (BIPV) façades: a case study in Taiwan | |
| Ma et al. | Does digitalization support green transition in Chinese cities? Perspective from Metcalfe's Law | |
| Guo et al. | A forecasting analysis on China ‘S energy use and carbon emissions based on A dynamic computable general equilibrium model | |
| Crawford | Towards a comprehensive approach to zero-emissions housing | |
| CN104881718A (en) | Regional power business index constructing method based on multi-scale leading economic indicators | |
| CN113155498B (en) | High-resolution building operation energy consumption carbon emission measuring method, system and equipment | |
| Xu et al. | Community load leveling for energy configuration optimization: Methodology and a case study | |
| Cui et al. | Dynamic decomposition analysis and forecasting of energy consumption in shanxi Province based on VAR and GM (1, 1) models | |
| Salim et al. | Quantitative analysis of sustainable housing energy systems based on Estidama pearl rating system | |
| Yang et al. | Electricity consumption characteristics and prediction model of a large airport terminal in Beijing | |
| Duan et al. | A novel multivariate grey model of energy consumption under carbon trading background and its application | |
| Aghamolaei | Evaluation of supply and demand in building energy performance: application of retrofit scenarios in residential building | |
| Lin et al. | Does China’s energy development plan affect energy conservation? Empirical evidence from coal-fired power generation | |
| Pak et al. | Proposal of the energy consumption analysis process for the residential houses using big data analytics technique | |
| CN103325066A (en) | Network load forecasting management system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20150429 |
|
| RJ01 | Rejection of invention patent application after publication |