CN105719198A - Method for calculating housing vacancy rate based on resident power consumption behaviors - Google Patents
Method for calculating housing vacancy rate based on resident power consumption behaviors Download PDFInfo
- Publication number
- CN105719198A CN105719198A CN201610042842.2A CN201610042842A CN105719198A CN 105719198 A CN105719198 A CN 105719198A CN 201610042842 A CN201610042842 A CN 201610042842A CN 105719198 A CN105719198 A CN 105719198A
- Authority
- CN
- China
- Prior art keywords
- power consumption
- community
- resident
- radix
- region
- 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
- 238000000034 method Methods 0.000 title claims abstract description 13
- 230000006399 behavior Effects 0.000 title abstract 3
- 230000005611 electricity Effects 0.000 claims description 106
- 238000000205 computational method Methods 0.000 claims description 10
- 238000012935 Averaging Methods 0.000 claims description 4
- 238000010276 construction Methods 0.000 abstract description 3
- 238000004519 manufacturing process Methods 0.000 abstract description 3
- 230000008859 change Effects 0.000 description 4
- 238000004458 analytical method Methods 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 230000009467 reduction Effects 0.000 description 2
- 229920006395 saturated elastomer Polymers 0.000 description 2
- 230000006978 adaptation Effects 0.000 description 1
- 230000008901 benefit Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 230000036541 health Effects 0.000 description 1
- 230000035800 maturation Effects 0.000 description 1
- 238000004445 quantitative analysis Methods 0.000 description 1
- 238000011084 recovery Methods 0.000 description 1
- 230000004083 survival effect Effects 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
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/06—Electricity, gas or water supply
-
- 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—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/16—Real estate
Abstract
The invention discloses a method for calculating a housing vacancy rate based on resident power consumption behaviors.According to the method, through statistics of a resident power consumption total and the number of permanent residents in an area, a resident daily power consumption cardinality and a floating range are calculated, the full electric quantity of a cell is calculated, the resident power consumption behaviors are tracked, the actual power consumption quantity is obtained, and the actual power consumption quantity and the full electric quantity are utilized to calculate the housing vacancy rate.By calculation of the housing vacancy rate, future resident power consumption states can be calculated, and the theoretical basis is provided for production and construction of electric power supporting devices, so as to conveniently and reasonably deploy electric power facilities of each cell.
Description
Technical field
The invention belongs to power domain, be specifically related to a kind of housing vacancy rate computational methods based on residential electricity consumption behavior.
Background technology
Housing vacancy rate refers to that vacant floor space of a certain moment accounts for the ratio of the house gross area.The calculating of housing vacancy rate is to understand the market demand trend to house, if house is vacant too much, illustrates that demand is not enough or purchasing power is inadequate, and corresponding adjustment can be made in country or market.As being usually utilized to evaluate an important indicator of real estate market " health degree ", housing vacancy rate receives much concern always.The too high topic of China's real estate market vacancy rate is mentioned repeatly, and wherein differ in the source of data, and from " number lamp method ", to big data estimation, person who quote respectively has reason, but is difficult to obtain society and generally approves, key issue is that data deficiency is authoritative.
Power industry is the important foundation industry of national economy, and the development of other branchs of industry is played requisite supporting role.Owing to power industry is absent from inventory problem, it is possible to the truth of reflection economic development, it is generally regarded as " wind vane " of economy.Grid company, as the important force of Electricity market analysis and prediction, bears the important task instructing company's correct decisions.Go deep into thorough Electricity market analysis and have become as Utilities Electric Co.'s adaptation requirement of the market economy, the element task of guarantee company's investment repayment and raising effectiveness of operation, only according to electricity needs characteristic, demand structure, the corresponding development plan adjusting company and business plan, Cai Nengshi power grid enterprises establish oneself in an unassailable position in the market, try to achieve survival and development for a long time.
In electricity quantitative analysis and categorizing process; this analysis strategy is proposed challenge by the Rapid Variable Design of World Economics; American's subprime mortgage crisis impact in 2008 is just disappeared gradually; European debt crisis in 2011 attacks again; the impact that twice economic crisis brings sweeps over the country rapidly; China's economic development brings impact, user experienced by a series of changes such as economic descending, economic recovery, and the development and change of electricity needs are brought significant impact by this.
Along with the raising of living standards of the people, the proportion of residential electricity consumption row increases year by year.In the process that role becomes more and more important, residential electricity consumption behavior is also gradually in change.How by the vacant degree in residential electricity consumption behavior prediction house, it is that Utilities Electric Co. at different levels assists the relevant departments such as government to carry out the important foundation of urban construction and Power System Planning and operation.
Summary of the invention
The invention aims to the defect solving exist in prior art, it is provided that the method for the calculating housing vacancy rate that a kind of energy is accurate and effective, real-time.
In order to achieve the above object, the invention provides a kind of housing vacancy rate computational methods based on residential electricity consumption behavior, comprise the following steps:
(1) according to historical data, the residential electricity consumption total amount in each region and permanent resident population's sum are added up；
(2) calculate, according to residential electricity consumption total amount and permanent resident population's sum, average resident's day electricity consumption radix that each region is corresponding；
(3) distinguish the day type of different times, calculate the fluctuation range of resident's day electricity consumption radix in each region；
(4) to each community, according to average resident's day electricity consumption radix that population specified in community is corresponding with its region of step (2) gained, calculating expiring of each community puts power consumption radix；The domain of walker of the resident's day electricity consumption radix in its region according to step (3) gained, calculating expiring of each community puts power consumption fluctuation area；
(5) according to the actual power consumption in each community, calculate the housing vacancy rate of each community: when the actual power consumption of community is put in power consumption fluctuation area in expiring of this community of step (4) gained, or when being higher than the peak completely putting power consumption fluctuation area, the housing vacancy rate of Ze Gai community is 0%；When the actual power consumption of community is lower than when expiring the minimum putting power consumption fluctuation area of this community of step (4) gained, the community, average resident day electricity consumption radix/3/ that housing vacancy rate is (completely putting power consumption radix-actual power consumption)/region of Ze Gai community is specified moves in amount.
Wherein, the day type distinguishing different times in step (3) divided according to working day and festivals or holidays, calculated not resident's day electricity consumption radix under type on the same day respectively, it is determined that the fluctuation range of resident's day electricity consumption radix.
The actual electricity consumption of step (5) Zhong Ge community measures the daily power consumption average in a period of time of this community.
Present invention also offers one more accurate, refinement ground, based on the housing vacancy rate computational methods of residential electricity consumption behavior, comprise the following steps:
(1) according to historical data, add up the residential electricity consumption total amount in each region and permanent resident population's sum, calculate average resident's day electricity consumption radix that each region is corresponding；
(2) classify according to city planning earth in Nei Ge community, each region, is divided into three class power consumption stratum of correspondence, calculates resident's day electricity consumption radix of each power consumption stratum in each region；
(3) distinguish the day type of different times, calculate the fluctuation range of resident's day electricity consumption radix of each power consumption stratum in each region；
(4) to each community, according to resident's day electricity consumption radix that population specified in community is corresponding with the power consumption stratum belonging to its region of step (2) gained, calculating expiring of each community puts power consumption radix；The domain of walker of resident's day electricity consumption radix that the power consumption stratum belonging to its region according to step (3) gained is corresponding, calculating expiring of each community puts power consumption fluctuation area；
(5) the actual power consumption according to each community, calculate the housing vacancy rate of each community: when the actual power consumption of community is put in power consumption fluctuation area in expiring of this community of step (4) gained, or when being higher than the peak completely putting power consumption fluctuation area, the housing vacancy rate of Ze Gai community is 0%；When the actual power consumption of community is lower than when expiring the minimum putting power consumption fluctuation area of this community of step (4) gained, belonging to (completely putting power consumption radix-actual power consumption)/region, the community, resident day electricity consumption radix/3/ of power consumption stratum is specified moves in amount for the housing vacancy rate of Ze Gai community.
Circular is as follows:
(1) macroscopic statistics region residential electricity consumption total amount and region permanent resident population sum.
(1.1) according to data statistics, residential electricity consumption total amount and permanent resident population's sum of several months in region is extracted；
(1.2) different resident clusters is distinguished, classify according to city planning earth, Nei Ge community, region is divided into three class power consumption stratum of correspondence: belong to a class residential estate R1(facility complete, environment is good, land used based on bottom residence) community be set to a class power consumption stratum, belong to two class residential estate R2(facilities more complete, environment is better, with many, in, high residential building is primaryly) community be set to two class power consumption stratum, belong to three class residential estate R3(facilities to be relatively short of, environment is poor, to need the simple and crude settlement land used transformed, including dilapidated house, shanty town, the lands used such as emergency dwelling) community be set to three class power consumption stratum；
(1.3) according to historical data, compile power consumption and permanent resident population's data of several months of ripe community of a class power consumption stratum and three class power consumption stratum, prepare for calculating resident's day electricity consumption radix.
(2) day electricity consumption cardinal sum day electricity consumption radix domain of walker is calculated.
(2.1) according to the residential electricity consumption total amount of several moons (at least 6 months) in 1.1 regions extracted and permanent resident population's sum, average resident's day electricity consumption radix that each region is corresponding is calculated, as resident's day electricity consumption radix of two class power consumption stratum in region；
(2.2) compile electricity consumption total amount and permanent resident population's data of several moons of ripe community (at least 6 months) of a class power consumption stratum and three class power consumption stratum according to step 1.2, calculate the resident's day electricity consumption radix obtaining a class power consumption stratum and three class power consumption stratum；
(2.3) according to dividing on working day and festivals or holidays, resident's daily power consumption meansigma methods of the different power consumption stratum of the different date types adding up at least 6 months, calculate the difference between resident's daily power consumption of the different power consumption stratum obtaining working day and festivals or holidays respectively, then calculating the ratio (being set to a) of this difference same step (2.1) averaging of income resident's day electricity consumption radix, (namely about resident's day electricity consumption radix, the ratio of fluctuation is a/2 namely to may be set to the fluctuation range of resident's day electricity consumption radix.), the day electricity consumption radix change in this fluctuation range all regards as normal electricity consumption and floats.
(3) determine specified amount correspondence population in selected cell type and community, calculate and completely put power consumption.
In conjunction with the finding of mass data, selection type community is idealized and completely puts power consumption calculating, in order to planning vacant electricity amount, specific algorithm is:
The specified amount correspondence population of resident's day electricity consumption radix × cell type of power consumption stratum belonging to power consumption=community is completely put in community
Afterwards, belonging to community, power consumption fluctuation area is completely put in the domain of walker specification community of resident's day electricity consumption radix of power consumption stratum.
(4) the actual electricity in statistics community is followed the tracks of, it is determined that actual electricity is with the relation completely put between power consumption.
(4.1) follow the tracks of the electricity of several moons of community (at least 6 months), calculate resident's day electricity consumption radix of community according to month natural law, obtain actual power consumption；
(4.1) judge that actual power consumption is whether completely putting in power consumption fluctuation area: if higher than fluctuation area or in fluctuation area, then can determine that community is saturated occupancy, namely give tacit consent to vacancy rate 0%；If lower than fluctuation area, then calculate vacant population by equation below,
Vacant population=(completely putting power consumption-actual power consumption)/day electricity consumption radix
(5) calculate the vacant amount in community, and calculate the housing vacancy rate of community.
Vacant population can define cell type reduction to amount according to government planning land used, and the meansigma methods generally according to each household 3 people is calculated, and can obtain the housing vacancy rate of community:
Housing vacancy rate=vacant amount/community is specified moves in amount
The present invention has the advantage that the present invention is from by resident's electricity root, calculates resident's day electricity consumption radix by distinguishing residential electricity consumption behavior, obtains the housing vacancy rate of community compared to existing technology.Traceable residential electricity consumption behavior simultaneously, efficiently and effectively update cell capacity data and electricity consumption radix level status, under the overall situation of macroscopic view comprehensive regulation, true feedback residential electricity consumption condition and population resource distribution variation tendency, root, embody national economy and living standards of the people, make power department accurately follow the tracks of residential electricity consumption behavior.The present invention is by distinguishing different types of power consumption stratum and different date type, understand the consumption habit of dissimilar resident, judge the peak of power consumption of dissimilar resident, the person works thus effective dispensing line fault is got rid of the danger, more efficiently ensure residential electricity consumption reliability.Adopt the inventive method, can effectively instruct power department to the production of electric power facility, construction.
Detailed description of the invention
Below in conjunction with specific embodiment, the present invention is described in detail.
(1) district of macroscopic statistics whole city residential electricity consumption total amount and region permanent resident population sum.
(1.1) according to data statistics, extract this Urban Residents electricity consumption total amount and permanent resident population's sum, calculate resident's day electricity consumption radix according to power consumption month by month, the region-wide interior average resident's day electricity consumption radix of calculating of averaging；
(1.2) different resident clusters is distinguished, region land-use style described in multiple community is divided three classes power consumption stratum: belong to a class residential estate R1(facility complete, environment is good, land used based on bottom residence) community be set to a class power consumption stratum, belong to two class residential estate R2(facilities more complete, environment is better, with many, in, high residential building is primaryly) community be set to two class power consumption stratum, belong to three class residential estate R3(facilities to be relatively short of, environment is poor, to need the simple and crude settlement land used transformed, including dilapidated house, shanty town, the lands used such as emergency dwelling) community be set to three class power consumption stratum；
(1.3) a class power consumption stratum and the ripe cell data of three class power consumption stratum are compiled.
(2) day electricity consumption cardinal sum day electricity consumption radix domain of walker is calculated.
The electricity consumption total amount of (2.1) one class power consumption stratum and three class power consumption stratum's maturation communities is averaged after carrying out preliminary treatment, with corresponding resident clusters permanent resident population's quantity and month natural law do ratio, a class and resident's day electricity consumption radix of three class electricity stratum can be obtained；Resident's day electricity consumption radix using region-wide interior average resident's day electricity consumption radix as two class power consumption stratum；
(2.2) according to dividing on working day and festivals or holidays, resident's daily power consumption meansigma methods of the different power consumption stratum of the different date types adding up at least 6 months, calculate the difference between resident's daily power consumption of the different power consumption stratum obtaining working day and festivals or holidays respectively, then the ratio of this difference same step (2.1) averaging of income resident's day electricity consumption radix is calculated, namely may be set to the fluctuation range of resident's day electricity consumption radix, the day electricity consumption radix change in this fluctuation range all regards as normal electricity consumption and floats.
(3) determine specified amount correspondence population in selected cell type and community, calculate and completely put power consumption.
In conjunction with the finding of mass data, selection type community is idealized and completely puts power consumption calculating, in order to planning vacant electricity amount, specific algorithm is:
The specified amount correspondence population of resident's day electricity consumption radix × cell type of power consumption stratum belonging to power consumption=community is completely put in community
Afterwards, belonging to community, power consumption fluctuation area is completely put in the domain of walker specification community of resident's day electricity consumption radix of power consumption stratum.
(4) the actual electricity in statistics community is followed the tracks of, it is determined that actual electricity is with the relation completely put between power consumption.
(4.1) follow the tracks of the electricity of several months of community, calculate resident's day electricity consumption radix of community according to month natural law, obtain actual power consumption；
(4.1) judge that actual power consumption is whether completely putting in power consumption fluctuation area: if higher than fluctuation area or in fluctuation area, then can determine that community is saturated occupancy, namely give tacit consent to vacancy rate 0%；If lower than fluctuation area, then calculate vacant population by equation below,
Vacant population=(completely putting power consumption-actual power consumption)/day electricity consumption radix
(5) calculate the vacant amount in community, and calculate the housing vacancy rate of community.
Vacant population can define cell type reduction to amount according to government planning land used, and the meansigma methods generally according to each household 3 people is calculated, and can obtain the housing vacancy rate of community:
Housing vacancy rate=vacant amount/community is specified moves in amount
Extract each 2 of the community adhering to different power consumption stratum in region separately, follow the tracks of the electricity consumption behavior in each community in January, 2010 in June, 2012, calculate the housing vacancy rate in community according to above-mentioned steps respectively, obtain result as follows:
The housing vacancy rate (unit: %) of each community of table 1
Expire, according to each community, the average housing vacancy rate putting electricity and affiliated different power consumption stratum, following residential electricity consumption need state can be calculated, for electric power corollary equipment production, build theoretical foundation be provided, with the electric power facility of each community of convenient and reasonable deployment.Simultaneously when meeting with extensive power failure, it is possible to estimate resident in advance and move in situation.
Claims (6)
1. the housing vacancy rate computational methods based on residential electricity consumption behavior, it is characterised in that: comprise the following steps:
(1) according to historical data, the residential electricity consumption total amount in each region and permanent resident population's sum are added up；
(2) calculate, according to residential electricity consumption total amount and permanent resident population's sum, average resident's day electricity consumption radix that each region is corresponding；
(3) distinguish the day type of different times, calculate the fluctuation range of resident's day electricity consumption radix in each region；
(4) to each community, according to average resident's day electricity consumption radix that population specified in community is corresponding with its region of step (2) gained, calculating expiring of each community puts power consumption radix；The domain of walker of the resident's day electricity consumption radix in its region according to step (3) gained, calculating expiring of each community puts power consumption fluctuation area；
(5) according to the actual power consumption in each community, calculate the housing vacancy rate of each community: when the actual power consumption of community is put in power consumption fluctuation area in expiring of this community of step (4) gained, or when being higher than the peak completely putting power consumption fluctuation area, the housing vacancy rate of Ze Gai community is 0%；When the actual power consumption of community is lower than when expiring the minimum putting power consumption fluctuation area of this community of step (4) gained, the community, average resident day electricity consumption radix/3/ that housing vacancy rate is (completely putting power consumption radix-actual power consumption)/region of Ze Gai community is specified moves in amount.
2. the housing vacancy rate computational methods based on residential electricity consumption behavior, it is characterised in that: comprise the following steps:
(1) according to historical data, add up the residential electricity consumption total amount in each region and permanent resident population's sum, calculate average resident's day electricity consumption radix that each region is corresponding；
(2) classify according to city planning earth in Nei Ge community, each region, is divided into three class power consumption stratum of correspondence, calculates resident's day electricity consumption radix of different power consumption stratum in each region；
(3) distinguish the day type of different times, calculate the fluctuation range of resident's day electricity consumption radix of different power consumption stratum in each region；
(4) to each community, according to resident's day electricity consumption radix that population specified in community and its region of step (2) gained, affiliated power consumption stratum are corresponding, calculating expiring of each community puts power consumption radix；The domain of walker of resident's day electricity consumption radix that the power consumption stratum belonging to its region according to step (3) gained is corresponding, calculating expiring of each community puts power consumption fluctuation area；
(5) the actual power consumption according to each community, calculate the housing vacancy rate of each community: when the actual power consumption of community is put in power consumption fluctuation area in expiring of this community of step (4) gained, or when being higher than the peak completely putting power consumption fluctuation area, the housing vacancy rate of Ze Gai community is 0%；When the actual power consumption of community is lower than when expiring the minimum putting power consumption fluctuation area of this community of step (4) gained, belonging to (completely putting power consumption radix-actual power consumption)/region, the community, resident day electricity consumption radix/3/ of power consumption stratum is specified moves in amount for the housing vacancy rate of Ze Gai community.
3. housing vacancy rate computational methods according to claim 1 and 2, it is characterised in that: the day type distinguishing different times in described step (3) divided according to working day and festivals or holidays.
4. housing vacancy rate computational methods according to claim 1 and 2, it is characterised in that: the actual electricity consumption of described step (5) Zhong Ge community measures the daily power consumption average in a period of time of this community.
5. housing vacancy rate computational methods according to claim 2, it is characterised in that: in described step (2), resident's day electricity consumption radix of each power consumption stratum in each region is chosen 10 years and above ripe community is calculated.
6. housing vacancy rate computational methods according to claim 2, it is characterized in that: in described step (3), the fluctuation range of resident's daily power consumption of the different power consumption stratum in each region is calculated as follows: resident's daily power consumption meansigma methods of the different power consumption stratum of the different date types adding up at least 6 months, calculate the difference between resident's daily power consumption of the different power consumption stratum obtaining working day and festivals or holidays respectively, then calculate the ratio of this difference same step (1) averaging of income resident's day electricity consumption radix, namely may be set to the fluctuation range of resident's day electricity consumption radix.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610042842.2A CN105719198A (en) | 2016-01-22 | 2016-01-22 | Method for calculating housing vacancy rate based on resident power consumption behaviors |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610042842.2A CN105719198A (en) | 2016-01-22 | 2016-01-22 | Method for calculating housing vacancy rate based on resident power consumption behaviors |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN105719198A true CN105719198A (en) | 2016-06-29 |
Family
ID=56153718
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610042842.2A Pending CN105719198A (en) | 2016-01-22 | 2016-01-22 | Method for calculating housing vacancy rate based on resident power consumption behaviors |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN105719198A (en) |
Cited By (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108595587A (en) * | 2018-04-19 | 2018-09-28 | 宁波三星医疗电气股份有限公司 | City dweller's distribution situation acquisition methods based on intelligent grid |
| CN108776868A (en) * | 2018-06-05 | 2018-11-09 | 广东电网有限责任公司电力科学研究院 | A kind of rural area village hollowing appraisal procedure and device based on electricity consumption big data |
| CN109598638A (en) * | 2018-11-06 | 2019-04-09 | 深圳供电局有限公司 | A kind of Research on Housing Vacancy Rate projectional technique and system based on electricity consumption data analysis |
| CN110059114A (en) * | 2019-03-16 | 2019-07-26 | 平安城市建设科技(深圳)有限公司 | Housing vacancy rate acquisition methods, device, terminal and computer readable storage medium |
| CN111190890A (en) * | 2019-12-26 | 2020-05-22 | 深圳供电局有限公司 | User daily electricity quantity data cleaning method, device, equipment and medium |
| CN112258063A (en) * | 2020-10-28 | 2021-01-22 | 国家电网有限公司客户服务中心 | Method and system for calculating idle classification of housing |
| CN112465378A (en) * | 2020-12-09 | 2021-03-09 | 国网四川省电力公司电力科学研究院 | Method and device for self-adaptive study and judgment of vacant house based on electric power big data mining |
| CN112488738A (en) * | 2020-12-16 | 2021-03-12 | 甘肃同兴智能科技发展有限责任公司 | Method and equipment for identifying resident vacant residents based on electric power big data |
| CN112732772A (en) * | 2020-12-15 | 2021-04-30 | 国网湖南省电力有限公司 | Method for measuring and calculating housing vacancy rate based on monthly resident power consumption |
| CN112907063A (en) * | 2021-02-10 | 2021-06-04 | 国网河北省电力有限公司信息通信分公司 | Population mobility rate and house vacancy rate determining method and terminal equipment |
| CN115936922A (en) * | 2022-11-24 | 2023-04-07 | 国网山东省电力公司临沂供电公司 | Village hollow rate accounting method based on electricity consumption data |
-
2016
- 2016-01-22 CN CN201610042842.2A patent/CN105719198A/en active Pending
Cited By (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108595587A (en) * | 2018-04-19 | 2018-09-28 | 宁波三星医疗电气股份有限公司 | City dweller's distribution situation acquisition methods based on intelligent grid |
| CN108776868A (en) * | 2018-06-05 | 2018-11-09 | 广东电网有限责任公司电力科学研究院 | A kind of rural area village hollowing appraisal procedure and device based on electricity consumption big data |
| CN109598638A (en) * | 2018-11-06 | 2019-04-09 | 深圳供电局有限公司 | A kind of Research on Housing Vacancy Rate projectional technique and system based on electricity consumption data analysis |
| CN110059114A (en) * | 2019-03-16 | 2019-07-26 | 平安城市建设科技(深圳)有限公司 | Housing vacancy rate acquisition methods, device, terminal and computer readable storage medium |
| CN111190890B (en) * | 2019-12-26 | 2024-03-29 | 深圳供电局有限公司 | Method, device, equipment and medium for cleaning daily electricity quantity data of user |
| CN111190890A (en) * | 2019-12-26 | 2020-05-22 | 深圳供电局有限公司 | User daily electricity quantity data cleaning method, device, equipment and medium |
| CN112258063A (en) * | 2020-10-28 | 2021-01-22 | 国家电网有限公司客户服务中心 | Method and system for calculating idle classification of housing |
| CN112465378A (en) * | 2020-12-09 | 2021-03-09 | 国网四川省电力公司电力科学研究院 | Method and device for self-adaptive study and judgment of vacant house based on electric power big data mining |
| CN112732772A (en) * | 2020-12-15 | 2021-04-30 | 国网湖南省电力有限公司 | Method for measuring and calculating housing vacancy rate based on monthly resident power consumption |
| CN112488738B (en) * | 2020-12-16 | 2024-02-27 | 甘肃同兴智能科技发展有限责任公司 | Resident vacant resident identification method and equipment based on electric power big data |
| CN112488738A (en) * | 2020-12-16 | 2021-03-12 | 甘肃同兴智能科技发展有限责任公司 | Method and equipment for identifying resident vacant residents based on electric power big data |
| CN112907063A (en) * | 2021-02-10 | 2021-06-04 | 国网河北省电力有限公司信息通信分公司 | Population mobility rate and house vacancy rate determining method and terminal equipment |
| CN112907063B (en) * | 2021-02-10 | 2023-02-28 | 国网河北省电力有限公司信息通信分公司 | Population mobility rate and house vacancy rate determining method and terminal equipment |
| CN115936922A (en) * | 2022-11-24 | 2023-04-07 | 国网山东省电力公司临沂供电公司 | Village hollow rate accounting method based on electricity consumption data |
| CN115936922B (en) * | 2022-11-24 | 2023-10-13 | 国网山东省电力公司临沂供电公司 | Village hollow rate accounting method based on electricity consumption data |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN105719198A (en) | Method for calculating housing vacancy rate based on resident power consumption behaviors | |
| Schiefelbein et al. | Automated urban energy system modeling and thermal building simulation based on OpenStreetMap data sets | |
| Poruschi et al. | Energy justice, the built environment, and solar photovoltaic (PV) energy transitions in urban Australia: A dynamic panel data analysis | |
| Garcia et al. | Socio-demographic profiles in suburban developments: Implications for water-related attitudes and behaviors along the Mediterranean coast | |
| Grouillet et al. | Historical reconstruction and 2050 projections of water demand under anthropogenic and climate changes in two contrasted Mediterranean catchments | |
| Scott et al. | Effects of climate change and population growth on the transboundary Santa Cruz aquifer | |
| Ribó-Pérez et al. | Effects of self-generation in imperfectly competitive electricity markets: The case of Spain | |
| Obeta et al. | Factors responsible for rural residential water supply shortage in southeastern Nigeria | |
| Kanakoudis et al. | Forecasting the residential water demand, balancing full water cost pricing and non-revenue water reduction policies | |
| Chowdhury et al. | Enabling a low-carbon electricity system for Southern Africa | |
| Wang et al. | Managing the Colorado River for an uncertain future | |
| Colmenar-Santos et al. | An assessment of photovoltaic potential in shopping centres | |
| Morales et al. | Predominant commercial sectors in Florida and their water use patterns | |
| Rahman et al. | A Review of the Energy-employment Nexus in. Bangladesh: Rural-urban Electrification and Sectoral Occupation Patterns | |
| Geng et al. | Optimizing urban block morphologies for net-zero energy cities: Exploring photovoltaic potential and urban design prototype | |
| Sumer et al. | Evaluation of conservation measures in the Upper San Pedro Basin | |
| Sushil Jha et al. | A Comparative Study of Economic Development of Gujarat and Kerala (A Study With Special Reference to the Role of Infrastructure in Economic Development) | |
| Carvallo | Strategic Planning for Universal Electricity Access | |
| Muccione et al. | The climate-cryosphere-water nexus in central Asia | |
| Neale | Assessing Tradeoffs of Urban Water Demand Reduction Strategies | |
| Pérez Odeh | Trends in portfolio optimization in a new risk-driven market era: a review and application of models for planners, investors and managers. | |
| Odeh | Trends in Portfolio Optimization in a New Risk-driven Market Era: A Review and Application of Models for Planners, Investors and Managers | |
| Zeyringer | Temporal and Spatial Explicit Modelling of Renewable Energy Systems: Modelling variable renewable energy systems to address climate change mitigation and universal electricity access | |
| Itika | Assessment Of Small-Scale Run-Of-River Hydropower Potential Of Birbir River, Baro-Akobo Basin, Ethiopia | |
| Luong Van Anh | Solutions to climate change to rural water supply in Red River Delta. |
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 | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20160629 |