scholarly journals Statistical analysis of air conditioning peak loads of multiple dwellings

2019 ◽  
Vol 111 ◽  
pp. 04057
Author(s):  
Tetsushi Ono ◽  
Aya Hagishima ◽  
Jun Tanimoto ◽  
Sheikh Ahmad Zaki ◽  
Naja Aqilah Hisham
Keyword(s):  
Statistical Analysis ◽  
Air Conditioning ◽  
Time Series Data ◽  
Electricity Consumption ◽  
Series Data ◽  
Kuala Lumpur ◽  
Air Conditioners ◽  
Time Patterns ◽  
Load Peak ◽  
Smart Community

Evaluation of the aggregated air-conditioning load of multiple dwellings is important for demand response through the optimum control of numerous air-conditioners (A/Cs), for development of smart-city or smart-community technologies. However, past studies have mainly focused on the characteristics of A/C load in a single household. With this background, the authors conducted statistical analysis of time-series data for A/C electricity consumption in 489 dwellings in Osaka, Japan, and 20 dwellings in Kuala Lumpur, Malaysia to grasp the feature of aggregated A/C load of multiple dwellings. The findings of this analysis are followings: 1) the aggregated A/C load peak per dwelling decreased by almost 50% as the number of dwellings increased from 1 to 10, due to the offset of the diverse time-patterns of A/C load. 2) The occurrence of the top 2.5% A/C load shows strong time and date dependency for an A/C load aggregated by many dwellings:

scholarly journals Time series data measurement on electricity consumption for selected domestic appliances in typical terrace house of Malaysia

2019 ◽  
Vol 8 (3) ◽  
pp. 1144-1153
Author(s):  
Naja Aqilah ◽  
Sheikh Ahmad Zaki Shaikh Salim ◽  
Aya Hagishima ◽  
Nelidya Md Yusoff ◽  
Fitri Yakub
Keyword(s):  
Time Series Data ◽  
Electricity Consumption ◽  
Hot Water ◽  
Series Data ◽  
Small Contribution ◽  
Washing Machine ◽  
Air Conditioners ◽  
Power Characteristics ◽  
Data Measurement ◽  
Domestic Appliances

This paper describes the pattern of electricity consumption from total and selected domestic appliances at a typical terrace house in Malaysia. The measured appliances can be classified into four groups on the basis of pattern of use which are ‘standby’ (TV), ‘active’ (massage chair, charger of hand phone, laptop and power bank, washing machine, air-conditioners, iron, standing fan, shower heaters, rice cooker, toaster, microwave), ‘cold’ (refrigerator) and ‘cold and hot’ (water dispenser). The major contribution of monthly electricity consumption comes from ‘cold’ appliances that consume 118.8 kWh/month followed by ‘active’ appliances that consume 87.8 kWh/month and ‘cold and hot’ appliance with 52.5 kWh/month. ‘Standby’ appliances shown a small contribution to the total electricity with 0.9 kWh/month. The amount of energy consumed depends on time-of-use, power characteristics of particular appliances as well as occupancy period.

Short-Term Measurements of Household Electricity Demand During Hot Weather in Kuala Lumpur

2017 ◽  
Vol 7 (3) ◽  
pp. 1436
Author(s):  
Nassir Ranjbar ◽  
Sheikh Ahmad Zaki ◽  
Nelidya Md Yusoff ◽  
Fitri Yakub ◽  
Aya Hagishima
Keyword(s):  
Time Series Data ◽  
Electricity Consumption ◽  
Weather Conditions ◽  
Electricity Demand ◽  
Series Data ◽  
Air Conditioner ◽  
Kuala Lumpur ◽  
Short Term ◽  
Minute Interval ◽  
Hot Weather

The aim of this study was to conduct short-term measurements on household electricity demand under hot weather conditions in a residential area in Kuala Lumpur. The measurements included total and air conditioner (AC) electricity consumption of 10 households in an apartment building as well as outdoor air temperatures, which were collected from March to May 2016. Results indicated that the average AC electricity consumption contributed to a major portion of total household electricity consumption, which ranged from 19.4 to 52.3% during the measurement period. Additionally, 1-minute interval time series data indicated household energy consumption more accurately than 30- or 60-minute interval.

scholarly journals Load and Household Profiles Analysis for Air-Conditioning and Total Electricity in Malaysia

2019 ◽  
Author(s):  
Naja Aqilah Hisham ◽  
Sheikh Ahmad Zaki ◽  
Aya Hagishima ◽  
Nelidya Md Yusoff
Keyword(s):  
Air Temperature ◽  
Indoor Air ◽  
Questionnaire Survey ◽  
Energy Demand ◽  
Air Conditioning ◽  
Time Series Data ◽  
Electricity Consumption ◽  
Field Measurements ◽  
Series Data ◽  
Living Room

Load profile of household air-conditioning (AC) and total electricity consumption is essential to increase the stability of the energy demand on the grid. Therefore, field measurements on time series data of total and AC electricity consumption from 20 households were conducted from March 2016 to August 2017. The questionnaire survey was carried out simultaneously to grasp the profile of each family. The average total daily and AC consumption were 14.5 kWh/day and 3.9 kWh/day, respectively. The average hourly electricity consumption for total was 0.6 kWh/hour, meanwhile for AC was 0.2 kWh/hour. About 20% of the total peak demand was contributed by the consumption of AC. The indoor air temperature was measured in the bedroom (BR) when AC was switched ON and OFF with an average of 27 ∘C and 29 ∘C, respectively. However, the indoor air temperature in the living room (LR) was 2∘C and 1∘C higher if compared to BR for both conditions. Based on the questionnaire survey, 92% of the occupants preferred a temperature setting below than the level recommended by the Malaysian standard i.e., 24 ∘C. These results might be beneficial to understand the occupant behavior of electricity demand in Malaysia for designing smart grid energy systems in the future.

Implementing Business Intelligence in Electricity Markets

2010 ◽  
pp. 283-295
Author(s):  
José Ramón Cancelo ◽  
Antoni Espasa
Keyword(s):  
Electricity Markets ◽  
Business Intelligence ◽  
Explicit Knowledge ◽  
Time Series Data ◽  
Contextual Information ◽  
Electricity Consumption ◽  
Point Of View ◽  
Series Data ◽  
Basic Ideas ◽  
Set Up

The authors elaborate on three basic ideas that should guide the implementation of business intelligence tools. First, the authors advocate for closing the gap between structured information and contextual information. Second, they emphasize the need for adopting the point of view of the organization to assess the relevance of any proposal. In the third place, they remark that any new tool is expected to become a relevant instrument to enhance the learning of the organization and to generate explicit knowledge. To illustrate their point, they discuss how to set up a forecasting support system to predict electricity consumption that converts raw time series data into market intelligence, to meet the needs of a major organization operating at the Spanish electricity markets.

scholarly journals Market model analysis and forecasting behavior of watermelon production in Bangladesh

2014 ◽  
Vol 26 (1-2) ◽  
pp. 47-56
Author(s):  
Murshida Khanam ◽  
Umme Hafsa
Keyword(s):  
Time Series ◽  
Statistical Analysis ◽  
Linear Models ◽  
Time Series Data ◽  
Arima Model ◽  
Model Analysis ◽  
Market Model ◽  
Series Data ◽  
Log Linear

An attempt has been made to study various models regarding watermelon production in Bangladesh and to identify the best model that may be used for forecasting purposes. Here, supply, log linear, ARIMA, MARMA models have been used to do a statistical analysis and forecasting behavior of production of watermelon in Bangladesh by using time series data covering whole Bangladesh. It has been found that, between the supply and log linear models; log linear is the best model. Comparing ARIMA and MARMA models it has been concluded that ARIMA model is the best for forecasting purposes. DOI: http://dx.doi.org/10.3329/bjsr.v26i1-2.20230 Bangladesh J. Sci. Res. 26(1-2): 47-56, December-2013

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