Optimizing Energy Consumption in Smart Homes: A Comprehensive Review of Demand Side Management Strategies

Gado, Dina M.; Hamdan, I.; Kamel, Salah; Abdelaziz, Almoataz Y.; Jurado, Francisco

doi:10.1109/chilecon60335.2023.10418744

2023 IEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies (CHILECON) 2023

DOI: 10.1109/chilecon60335.2023.10418744

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Optimizing Energy Consumption in Smart Homes: A Comprehensive Review of Demand Side Management Strategies

Dina M. Gado,

I. Hamdan,

Salah Kamel

et al.

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2024

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Cited by 2 publications

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Uncertainty Cost Functions for Wave Energy

Rehman,

Idarraga-Ospina,

Rivera

2024

Wseas Transactions on Power Systems

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Wave energy is considered as an important energy source for people living near coastal areas to meet their basic energy needs. Innovative and new technologies can be used for this energy utilization to run the loads from sea waves. Due to its uncertain power availability, we can use uncertainty cost functions based on probability distributions for the availability of the operation of the wave energy microgrid. These probability distributions are based on several mapping models designed for the wave energy, wave height, and wave speed mapping to make the energy more stable and reliable. In contrast to other renewable energy sources, wave energy is inherently unpredictable, making it impossible to model with a single, globally applicable probability distribution function (PDF). The prediction of the behavior of primary wave energy for this purpose is completely based on several probability distribution functions (PDFs) which can be considered as the best for all conditions. In this paper, we have used the Weibull-Rayleigh probability distribution model to develop the uncertainty cost function for wave energy. The Monte-Carlo process is carried out to get the results supported by the Rayleigh probability distribution model consisting of wave height, and uncertain cost histograms. Cost is minimized by using the Weibull Rayleigh model for both overestimation and underestimation costs of wave energy. Monte-Carlo simulation results are further compared with analytical calculation and error between them.

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Uncertainty Cost Functions for Wave Energy

Rehman,

Idarraga-Ospina,

Rivera

2024

Wseas Transactions on Power Systems

View full text Add to dashboard Cite

show abstract

Simplified Approach for Wind Uncertainty Cost Functions using a Mixture of Uniform Probability Distribution

García,

Rehman,

Rodriguez

2024

Wseas Transactions on Power Systems

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Wind energy generation is an individual source of energy considered in renewable energy resources. It is completely dependent on the natural process of air blown in the area or past forecasting of air blown data. It is considered an uncertain source of energy and less reliable in the context of real-time energy provisions. To make this wind energy more reliable and consistent, we are introducing a simplified approach for wind uncertainty cost functions based on uniform probability distributions and its evaluation for usage. We have developed analytical mathematics cost functions based on several assumptions and they are constructed using Weibull and Rayleigh probability distributions. The proposed method produces the required results to make this energy reliable and consistent with the distribution networks. Computing time and complexity are less as compared to the other methods to minimize the uncertainty of wind energy.

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Optimizing Energy Consumption in Smart Homes: A Comprehensive Review of Demand Side Management Strategies

Cited by 2 publications

References 51 publications

Uncertainty Cost Functions for Wave Energy

Uncertainty Cost Functions for Wave Energy

Simplified Approach for Wind Uncertainty Cost Functions using a Mixture of Uniform Probability Distribution

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