A method for distinguishing appliance, lighting and plug load profiles from electricity ‘smart meter’ datasets

George, Dane; Swan, Lukas G.

doi:10.1016/j.enbuild.2016.10.048

Cited by 16 publications

(7 citation statements)

References 13 publications

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“…Meanwhile most of the authors just presented the need for dataset for e cient and reliable energy supply, discussion about appliances, lighting, and plug loads (ALP) that take-up the energy is also emphasized by [13]. In their argument some houses use heating and cooling appliances that need to be captured in the dataset.…”

Section: Literature Reviewmentioning

confidence: 99%

A Novel Load Forecast, and Sizing Model of a Hybrid PV-Hydroelectric Microgrid System Using Python

Zarma,

Galadima,

Karataev

et al. 2024

Preprint

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Conventional sources of energy have played major in burning diesel, petrol into carbon dioxide. Carbon and greenhouse emissions have immensely contributed toward global warming and thus face global criticism from environmental activists and the UN agencies. Therefore, it became imperative to reduce or cut these emissions. Renewable energy systems have over the years gained attention from researchers and environmentalists due to their clean nature. Thus, they are emission free and reduce the reduction of carbon emissions. Furthermore, the size of the energy system depends on the energy demand required by the load. In the foregoing, the demand of Nile university for one year was obtained weekly. Furthermore, a load forecasting model was developed using python for the prediction of the energy demand. An average model accuracy of 98% was obtained. However, the campus uses four synchronized generators as energy sources coupled with a grid-tied PV/solar system and a public utility energy grid. The greenhouse emissions because of using these generators was determined. Using an energy content factor (EC) of 38.6 GJ/kL and an emission factor (EF) of 69.5Kg CO2 -e per GJ the greenhouse gas emission is obtained as 21,008.22 tones. Similarly, the carbon saved from using the grid-tied solar system is obtained at 202.96 tones. Therefore, the need for replacing the generators with a renewable energy system is obvious. Hence, to reduce the carbon emissions by the diesel generators used by the campus, a hydroelectric energy system was sized based on existing models. A best- and worst-case scenarios were modelled and obtained. Results have shown that the River/Stream of water passing through Nile has potentials that can be harnessed to curb the issues of emission.

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Section: Literature Reviewmentioning

confidence: 99%

A Novel Load Forecast, and Sizing Model of a Hybrid PV-Hydroelectric Microgrid System Using Python

Zarma,

Galadima,

Karataev

et al. 2024

Preprint

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“…[21] finds (based on 25 homes monitored in the Greater Toronto Area (GTA)) an average electricity usage of between 600 and 1200 kWh/month for an average home size of 225 m 2 . [22] reports (based on 23 households in Ottawa) the maximum annual peak to be less than 1.1 kW which is equivalent to a typical consumption of less than 486 kWh/month.…”

Section: Household Consumption and Loadmentioning

confidence: 99%

Prosumers and energy pricing policies: When, where, and under which conditions will prosumers emerge? A case study for Ontario (Canada)

Kuznetsova

Anjos

2021

Energy Policy

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“…Many studies have been conducted to increase the energy efficiency and reduce the GHG emissions of existing buildings. Many are related to the upgrade of space conditioning [10][11][12][13][14], hotwater systems [15][16][17], lighting systems [18][19][20][21], electronic appliances [22][23][24] or plug load [25][26][27]. These studies have analyzed the overall energy consumption reduction effect by upgrading major building systems using representative residential buildings by region.…”

Section: Introductionmentioning

confidence: 99%

Carbon Footprint Reduction through Residential Building Stock Retrofit: A Metro Melbourne Suburb Case Study

Seo

Foliente

2021

Energies

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Since existing residential buildings are a significant global contributor to energy consumption and greenhouse gas (GHG) emissions, any serious effort to reduce the actual energy and carbon emissions of the building sector should explicitly address the carbon mitigation challenges and opportunities in the building stock. This research investigates environmentally and economically sustainable retrofit methods to reduce the carbon footprint of existing residential buildings in the City of Greater Dandenong as a case study in Metropolitan Melbourne, Australia. By categorizing energy use into various building age brackets and dwelling types that align with changes in energy regulations, we identified various retrofit prototypes to achieve a targeted 6.5-star and 8-star energy efficiency rating (out of a maximum 10-star rating system). The corresponding operational energy savings through different retrofit options are examined while also considering the quantity of materials required for each option, along with their embodied energy and GHG emissions, thus allowing a more comprehensive lifecycle carbon analysis and exploration of their financial and environmental payback times. Results show that when buildings are upgraded with a combination of insulation and double-glazed windows, the environmental benefits rise faster than the financial benefits over a dwelling’s lifecycle. The size or percentage of a particular dwelling type within the building stock and the remaining lifecycle period are found to be the most important factors influencing the payback periods. Retrofitting the older single detached dwellings shows the greatest potential for lifecycle energy and carbon savings in the case suburb. These findings provide households, industry and governments some guidance on how to contribute most effectively to reduce the carbon footprint of the residential building sector.

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A method for distinguishing appliance, lighting and plug load profiles from electricity ‘smart meter’ datasets

Cited by 16 publications

References 13 publications

A Novel Load Forecast, and Sizing Model of a Hybrid PV-Hydroelectric Microgrid System Using Python

A Novel Load Forecast, and Sizing Model of a Hybrid PV-Hydroelectric Microgrid System Using Python

Prosumers and energy pricing policies: When, where, and under which conditions will prosumers emerge? A case study for Ontario (Canada)

Carbon Footprint Reduction through Residential Building Stock Retrofit: A Metro Melbourne Suburb Case Study

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