A new optimal energy management strategy based on improved multi-objective antlion optimization algorithm: applications in smart home

Ramezani, Maryam; Bahmanyar, Danial; Razmjooy, Navid

doi:10.1007/s42452-020-03885-7

Cited by 55 publications

(18 citation statements)

References 25 publications

(30 reference statements)

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“…These algorithms have a lot of variety [ 21 ]. The great variety of these algorithms in solving different problems, as well as the introduction of new algorithms with different titles, has made choosing a suitable algorithm for the user who intends to use them a difficult and complex task [ 22 ]. On the other hand, each of these algorithms obtains the optimal solution with certain accuracy and speed.…”

Section: Methodsmentioning

confidence: 99%

An Optimized Method for Skin Cancer Diagnosis Using Modified Thermal Exchange Optimization Algorithm

Liu

Pan

Nanehkaran

et al. 2021

Computational and Mathematical Methods in Medicine

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Skin cancer is the most common cancer of the body. It is estimated that more than one million people worldwide develop skin cancer each year. Early detection of this cancer has a high effect on the disease treatment. In this paper, a new optimal and automatic pipeline approach has been proposed for the diagnosis of this disease from dermoscopy images. The proposed method includes a noise reduction process before processing for eliminating the noises. Then, the Otsu method as one of the widely used thresholding method is used to characterize the region of interest. Afterward, 20 different features are extracted from the image. To reduce the method complexity, a new modified version of the Thermal Exchange Optimization Algorithm is performed to the features. This improves the method precision and consistency. To validate the proposed method’s efficiency, it is implemented to the American Cancer Society database, its results are compared with some state-of-the-art methods, and the final results showed the superiority of the proposed method against the others.

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Section: Methodsmentioning

confidence: 99%

An Optimized Method for Skin Cancer Diagnosis Using Modified Thermal Exchange Optimization Algorithm

Liu

Pan

Nanehkaran

et al. 2021

Computational and Mathematical Methods in Medicine

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“…A HEMS is presented in [54]. To obtain a solution to the problem, four metaheuristics are considered: integrated multi-objective antlion optimization, multi-objective PSO, the second version of the non-dominated sorting GA, and the basic antlion optimizer algorithm.…”

Section: Heuristics and Metaheuristicsmentioning

confidence: 99%

Recent Techniques Used in Home Energy Management Systems: A Review

et al. 2022

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Power systems are going through a transition period. Consumers want more active participation in electric system management, namely assuming the role of producers–consumers, prosumers in short. The prosumers’ energy production is heavily based on renewable energy sources, which, besides recognized environmental benefits, entails energy management challenges. For instance, energy consumption of appliances in a home can lead to misleading patterns. Another challenge is related to energy costs since inefficient systems or unbalanced energy control may represent economic loss to the prosumer. The so-called home energy management systems (HEMS) emerge as a solution. When well-designed HEMS allow prosumers to reach higher levels of energy management, this ensures optimal management of assets and appliances. This paper aims to present a comprehensive systematic review of the literature on optimization techniques recently used in the development of HEMS, also taking into account the key factors that can influence the development of HEMS at a technical and computational level. The systematic review covers the period 2018–2021. As a result of the review, the major developments in the field of HEMS in recent years are presented in an integrated manner. In addition, the techniques are divided into four broad categories: traditional techniques, model predictive control, heuristics and metaheuristics, and other techniques.

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“…The total priority level induced by starting the operation of MC-controllable appliances a i ∈ L MC at times t a i s ∈ TS a i D in a day d ∈ D is defined as the square root of the sum of the squared priority level of each MC-controllable appliance as in Equation (9).…”

Section: User Comfortmentioning

confidence: 99%

“…In [ 8 ], a REM approach was presented by a mixed-integer nonlinear programming problem with time or energy-based task classification. In [ 9 ] authors presented an improved multi-objective optimization algorithm to minimize the electricity cost with considering the user comfort. A new binary particle swarm optimization with quadratic transfer function was proposed in [ 10 ] for scheduling shiftable appliances in smarthomes.…”

Section: Introductionmentioning

confidence: 99%

An Appliance Scheduling System for Residential Energy Management

Ozkan

2021

Sensors

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In this work, an Appliance Scheduling-based Residential Energy Management System (AS-REMS) for reducing electricity cost and avoiding peak demand while keeping user comfort is presented. In AS-REMS, based on the effects of starting times of appliances on user comfort and the user attendance during their operations, appliances are divided into two classes in terms of controllability: MC-controllable (allowed to be scheduled by the Main Controller) and user-controllable (allowed to be scheduled only by a user). Use of all appliances are monitored in the considered home for a while for recording users’ appliance usage preferences and habits on each day of the week. Then, for each MC-controllable appliance, preferred starting times are determined and prioritized according to the recorded user preferences on similar days. When scheduling, assigned priorities of starting times of these appliances are considered for maintaining user comfort, while the tariff rate is considered for reducing electricity cost. Moreover, expected power consumptions of user-controllable appliances corresponding to the recorded user habits and power consumptions of MC-controllable appliances corresponding to the assigned starting times are considered for avoiding peak demand. The corresponding scheduling problem is solved by Brute-Force Closest Pair method. AS-REMS reduces the peak demand levels by 45% and the electricity costs by 39.6%, while provides the highest level of user comfort by 88%. Thus, users’ appliance usage preferences are sustained at a lower cost while their comfort is kept impressively.

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A new optimal energy management strategy based on improved multi-objective antlion optimization algorithm: applications in smart home

Cited by 55 publications

References 25 publications

An Optimized Method for Skin Cancer Diagnosis Using Modified Thermal Exchange Optimization Algorithm

An Optimized Method for Skin Cancer Diagnosis Using Modified Thermal Exchange Optimization Algorithm

Recent Techniques Used in Home Energy Management Systems: A Review

An Appliance Scheduling System for Residential Energy Management

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