Elephant Herding Optimization Metaheuristic to Minimize Electricity Cost in a Smart House

2021 ◽  
pp. 12-20
Author(s):  
Samia Chibani Sadouki ◽  
Souhila Ait Hacene Ouhadda
Keyword(s):  
Electricity Cost ◽  
Smart House

scholarly journals Heuristic Algorithm for Minimizing the Electricity Cost of Smart House

2017 ◽  
Vol 11 (4) ◽  
Author(s):  
Mohamed Arikiez ◽  
Faisal Alotaibi ◽  
Farouq Gdhaidh ◽  
Radwan Khershif ◽  
Salahedin Rehan
Keyword(s):  
Heuristic Algorithm ◽  
Electricity Cost ◽  
Smart House

Comparison and Validation of Operational Cost in Smart Houses with the Introduction of a Heat Pump or a Gas Engine

2015 ◽  
Vol 16 (1) ◽  
pp. 59-74 ◽  
Author(s):  
Tsubasa Shimoji ◽  
Hayato Tahara ◽  
Hidehito Matayoshi ◽  
Atsushi Yona ◽  
Tomonobu Senjyu
Keyword(s):  
Distribution Systems ◽  
Heat Pumps ◽  
Wind Generation ◽  
Operational Cost ◽  
Gas Engine ◽  
Electricity Cost ◽  
Exhaust Heat ◽  
Electric Equipment ◽  
Smart House ◽  
The Cost

Abstract Due to the concerns of global warming and the depletion of energy resources, renewable energies such as wind generation (WG) and photovoltaic generation (PV) are gaining attention in distribution systems. Efficient electric equipment such as heat pumps (HP) not only contribute low levels of carbon to society, but are also beneficial for consumers. In addition, gas instruments such as the gas engine (GE) and fuel cells (FC) are expected to reduce electricity cost by exhaust heat. Thus, it is important to clarify which systems (HP or GE) are more beneficial for consumers throughout the year. This paper compares the operational cost for the smart house between using the HP and the GE. Current electricity and gas prices are used to calculate the cost of the smart house. The system considered in this research comprises a PV, battery, solar collector (SC), uncontrolled load and either an HP or a GE. In order to verify the effectiveness of the proposed system, MATLAB is used for simulations.

Adjusting Electricity Cost Depending on Power Supply Outages

2020 ◽  
Vol 67 (2) ◽  
pp. 44-50
Author(s):  
Vadim E. Bolshev ◽  
Aleksandr V. Vinogradov ◽  
Alina V. Vinogradova ◽  
Aleksey V. Bukreev ◽  
Aleksandr A. Lansberg
Keyword(s):  
Power Quality ◽  
Power Supply ◽  
Power Supply System ◽  
Economic Incentive ◽  
Supply System ◽  
Research Purpose ◽  
Electricity Cost ◽  
Economic Method ◽  
Urgent Task ◽  
Supply Reliability

During the functioning of power supply system, there can be situations where the culprit in interruptions of power supply to consumers and a power quality violation is a power supply company or a consumer himself. Therefore, the economic incentive for power supply companies and consumers to increase power supply reliability and power quality is an urgent task. To implement such incentives, it is necessary to control the facts and time of power supply outages and their values as well as cases and time of non-compliance of power quality with the requirements of standards. It is possible with the use of a monitoring system for power supply reliability and power quality. (Research purpose) The research purpose is in developing a technical and economic method for stimulating power supply companies and consumers to increase efficiency of power supply system. (Materials and methods) The article provides a review of the structural diagram of a system for monitoring power supply reliability and power quality including devices for monitoring the number and duration of power outages and voltage deviations. (Results and discussion). An economic method has been developed to stimulate power supply companies and consumers to increase power supply system efficiency. The essence of the method is to control the parameters of power supply reliability and power quality, identify the violation of these parameters, determine the culprit of the violation, determine the time characteristics of the violation, summarize the duration of violations for the reporting period, compare the actual amount of duration with the allowable one, determine the amount of compensation for the violation and impose sanctions on payment compensation by the perpetrators of violations of these parameters. The article presents an algorithm for adjusting the cost of electricity supplied to consumers depending on the number and duration of voltage deviations and the number and duration of outages. The algorithm serves to ensure the operation of the specified technical and economic method. (Conclusions) The algorithm works in conjunction with a system for monitoring power supply reliability and power quality based on signals from devices that control the number and duration of outages and voltage deviations.

scholarly journals Smart House Control using LabVIEW

2020 ◽  
Vol 1716 ◽  
pp. 012004
Author(s):  
S Angalaeswari ◽  
T Deepa ◽  
D Subbulekshmi ◽  
S. Krithiga ◽  
Machupalli Narsimha Reddy ◽  
...  
Keyword(s):  
Smart House

scholarly journals Optimal Artificial Neural Network Type Selection Method for Usage in Smart House Systems

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 47
Author(s):  
Vasyl Teslyuk ◽  
Artem Kazarian ◽  
Natalia Kryvinska ◽  
Ivan Tsmots
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Artificial Neural Network ◽  
Artificial Neural Networks ◽  
Input Data ◽  
Optimization Criterion ◽  
Fuzzy Input ◽  
Different Types ◽  
Smart House ◽  
Artificial Neural

In the process of the “smart” house systems work, there is a need to process fuzzy input data. The models based on the artificial neural networks are used to process fuzzy input data from the sensors. However, each artificial neural network has a certain advantage and, with a different accuracy, allows one to process different types of data and generate control signals. To solve this problem, a method of choosing the optimal type of artificial neural network has been proposed. It is based on solving an optimization problem, where the optimization criterion is an error of a certain type of artificial neural network determined to control the corresponding subsystem of a “smart” house. In the process of learning different types of artificial neural networks, the same historical input data are used. The research presents the dependencies between the types of neural networks, the number of inner layers of the artificial neural network, the number of neurons on each inner layer, the error of the settings parameters calculation of the relative expected results.

scholarly journals A Rapid Review on Community Connected Microgrids

2021 ◽  
Vol 13 (12) ◽  
pp. 6753
Author(s):  
Moiz Masood Syed ◽  
Gregory M. Morrison
Keyword(s):  
Literature Review ◽  
Urban Areas ◽  
Energy Use ◽  
Residential Buildings ◽  
Optimal Solution ◽  
Building Energy ◽  
Rapid Review ◽  
Solar Pv ◽  
Electricity Cost ◽  
Building Energy Use

As the population of urban areas continues to grow, and construction of multi-unit developments surges in response, building energy use demand has increased accordingly and solutions are needed to offset electricity used from the grid. Renewable energy systems in the form of microgrids, and grid-connected solar PV-storage are considered primary solutions for powering residential developments. The primary objectives for commissioning such systems include significant electricity cost reductions and carbon emissions abatement. Despite the proliferation of renewables, the uptake of solar and battery storage systems in communities and multi-residential buildings are less researched in the literature, and many uncertainties remain in terms of providing an optimal solution. This literature review uses the rapid review technique, an industry and societal issue-based version of the systematic literature review, to identify the case for microgrids for multi-residential buildings and communities. The study describes the rapid review methodology in detail and discusses and examines the configurations and methodologies for microgrids.

A Tool for Thermoeconomic Analysis and Optimization of Gas, Steam, and Combined Plants

1997 ◽  
Vol 119 (4) ◽  
pp. 885-892 ◽  
Author(s):  
A. Agazzani ◽  
A. F. Massardo
Keyword(s):  
Cost Model ◽  
Optimization Technique ◽  
Energy System ◽  
Physical Structure ◽  
Capital Cost ◽  
Marginal Costs ◽  
Electricity Cost ◽  
Combined Cycles ◽  
Thermodynamic Variables ◽  
Definition Of

The aim of this work is to demonstrate the capability of an original “modular” simulator tool for the thermoeconomic analysis of thermal-energy systems. The approach employed is based on the Thermoeconomic Functional Analysis (T.F.A.), which, through definition of the “functional productive diagram” and the establishment of the capital cost function of each component, allows the marginal costs and the unit product costs, i.e., the “internal economy,” of the functional exergy flows to be obtained in correspondence to the optimum point. The optimum design of the system is obtained utilizing a traditional optimization technique, which includes both physical structure of the energy system described in terms of thermodynamic variables and cost model (capital cost of the components, maintenance and amortization factors, unit fuel cost, unit electricity cost, etc.). As an application example to show the practicability of the tool, the thermoeconomic analysis of various complex multipressure combined cycles (with or without steam reheating) is carried out. The results are analyzed and discussed in depth.

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