Cyclic Voltammetry Study and Solar Light Assisted Photocatalytic Activity of the CeFeO/CeO/FeO Composite.

The semiconducting nature of CeFeO/CeO/FeO nanocomposite has permitted the degradation of the organic toxic dye methylene blue under the irradiation of ultraviolet and visible light portions of solar radiation. Fullprof-assisted Rietveld refinement analysis, performed using the Match software, has revealed the orthorhombic nature of CeFeO. In addition, in the synthesized material, the cubic phase byproduct CeO was found due to the highly oxidizing nature of the cerium element.

Household electricity consumption prediction using database combinations, ensemble and hybrid modeling techniques.

Household electricity consumption (HEC) is changing over time, depends on multiple factors, and leads to effects on the prediction accuracy of the model. The objective of this work is to propose a novel methodology for improving HEC prediction accuracy. This study uses two original datasets, namely questionnaire survey (QS) and monthly consumption (MC), which contain data from 225 consumers from Maharashtra, India.

The improved integrated Exponential Smoothing based CNN-LSTM algorithm to forecast the day ahead electricity price.

The deregulation of electricity market has led to the development of the short-term electricity market. The power generators and consumers can sell and purchase the electricity in the day ahead terms. The market clearing electricity price varies throughout the day due to the increase in the consumers bidding for electricity.

A peer-and self-group competitive behavior-based socio-inspired approach for household electricity conservation.

This paper proposes a knowledge-based decision-making system for energy bill assessment and competitive energy consumption analysis for energy savings. As humans have a tendency toward comparison between peers and self-groups, the same concept of competitive behavior is utilized to design knowledge-based decision-making systems. A total of 225 house monthly energy consumption datasets are collected for Maharashtra state, along with a questionnaire-based survey that includes socio-demographic information, household appliances, family size, and some other parameters.