Method for predicting daily water consumption of urban dweller

A technology of urban residents and forecasting methods, applied in forecasting, data processing applications, instruments, etc., can solve problems such as inability to meet micro-scheduling and provide basis for water supply scheduling, and achieve the goal of reducing the leakage rate of pipe networks and reducing water supply energy consumption Effect

Inactive Publication Date: 2016-08-17
GUANGZHOU INST OF GEOGRAPHY GUANGDONG ACAD OF SCI
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Problems solved by technology

[0007] The forecast of water consumption based on yearly and monthly time scales cannot provide a basis for water supply scheduling at various times ...

Method used

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  • Method for predicting daily water consumption of urban dweller
  • Method for predicting daily water consumption of urban dweller
  • Method for predicting daily water consumption of urban dweller

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Embodiment Construction

[0025] Traditional water use forecasts based on yearly and monthly time scales cannot provide a basis for water supply scheduling at various times of the day; while water use forecasts based on large spatial scales such as the country, province, and city cannot meet the needs of micro-scheduling. The invention takes urban residents' domestic water as the analysis object, based on the detailed water consumption data collected by the smart water meter, takes the day as the time scale, and takes the household as the spatial scale to predict the residents' domestic water use. The traditional monthly water consumption data cannot support us to complete the water consumption forecast on a daily time scale, and the detailed data of water consumption collected by smart water meters is higher in accuracy and frequency than existing remote water meters. According to the detailed water consumption data of users in a community, every fifteen minutes or daily time period can be used as a ti...

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Abstract

The invention discloses a method for predicting the daily water consumption of urban residents. Based on the detailed data of residents' domestic water consumption, the data is merged according to the time period type of residents' domestic water consumption, and according to the merged water use data, the time scale is calculated according to the hour and day. Two time scales are used to predict the domestic water consumption of urban residents and achieve better results. The present invention can simulate and analyze residents' domestic water consumption, and can provide residents with services such as water consumption forecasting and step-by-step water price prompts; on the other hand, by predicting the daily water consumption of all users in a certain area, it can provide microscopic water supply for water supply enterprises. Scheduling provides an auxiliary decision-making basis, thereby reducing water supply energy consumption, and at the same time reducing the leakage rate of the pipe network which is proportional to the water supply pressure.

Description

technical field [0001] The invention relates to the technical field of urban water supply, in particular to a method for predicting daily water consumption of urban residents. Background technique [0002] Some scholars have achieved good results in water consumption prediction and evolution simulation research based on real data. These studies are based on the monthly water consumption of water supply companies' manual meter reading and the annual total water consumption in local yearbooks. The spatial scale covers regions, provinces, cities, and countries, and the time scale is mostly monthly and annual. Such studies provide data support for the formulation of macroeconomic planning, water resource planning, rational allocation of water resources, formulation of water-saving measures, and formulation of scheduling plans for water supply companies. However, there are differences in these studies in terms of water use properties, time scales, spatial scales, and data precis...

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Application Information

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IPC IPC(8): G06Q10/04G06Q50/06
CPCG06Q10/04G06Q50/06
Inventor 杨骥李勇张南峰杨敬锋
Owner GUANGZHOU INST OF GEOGRAPHY GUANGDONG ACAD OF SCI
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