Mobile application for household energy consumption feedback using smart meters: Increasing energy awareness, encouraging energy savings and avoiding energy peaks

Short-Term Load Forecasting for buildings has gained a lot of importance in recent times due to the ongoing penetration of renewable energy and the upgradation of power system networks to Smart Grids embedded with smart meters. Power System expansion is not able to keep pace with the energy consumption demands. In this scenario, accurate household energy forecasting is one of the key solutions to managing the demand side energy. Even a small percentage of improvement in forecasting error, translates to a lot of saving for both producers and consumers. In this paper, it was found out that Aggregated 1-Dimensional Convolutional Neural Networks can be effectively modeled to predict the household consumption with greater accuracy than a basic 1-Dimensional Convolutional Neural Network model or a classical Auto Regressive Integrated Moving Average model. The proposed Aggregated Convolutional Neural Network model was tested on a 4 year household energy consumption dataset and gave very promising Root Mean Square Error reduction

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Why Low-Carbon Publicity Effect Limits? The Role of Heterogeneous Intention in Reducing Household Energy Consumption

Energies ◽

10.3390/en14227634 ◽

2021 ◽

Vol 14 (22) ◽

pp. 7634

Author(s):

Jin Zhang ◽

Lianrui Ma ◽

Jinkai Li

Keyword(s):

Energy Consumption ◽

Energy Saving ◽

Energy Awareness ◽

Low Carbon ◽

Rapid Urbanization ◽

Household Energy ◽

Consumption Behavior ◽

Household Energy Consumption ◽

Energy Behavior ◽

Saving Behavior

Low-carbon knowledge is seen as having a key role in interfering with household energy consumption behaviors by wide consensus from political and academic areas. Whether low-carbon publicity will help to reduce household energy consumption is still in dispute. By constructing an integrated knowledge-intention-behavior model and using 1335 detailed survey questionnaires of household energy behavior in Henan Province, the central area in China, this paper finds that in the developing area low-carbon knowledge or publicity cannot positively impact household energy-saving behavior even if mediated by energy awareness and energy-saving attitudes. Low-carbon knowledge does improve energy-saving attitude and attitude does not decrease household energy consumption directly. Familiarity with particular energy-saving knowledge would decrease the household energy consumption but not significantly in the statistics. Path analysis unfolds the reason that the heterogeneous effects of purchase-based intention and habitual intention explain energy consumption behavior. Subgroup analysis supports those economic factors of income and energy prices play key roles in explaining such household energy consumption behavior in the rapid urbanization area. This paper gives new evidence on the residential energy-saving behavior intervention among developing areas.

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