Optimization of Demand-Response-Based Intelligent Home Energy Management System with Binary Backtracking Search Algorithm

Latif, Suhaib N. Abdul; Shi, Jinjing; Salman, Hasnain Ali; Tang, Yongze

doi:10.3390/info11080395

Cited by 7 publications

(3 citation statements)

References 43 publications

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“…Incentive-Based Demand Response Programs [31] An optimization of demand-response-based intelligent home energy management system with binary backtracking search algorithm was presented by the authors.…”

Section: References Groups Reference Contributions Shortcomingsmentioning

confidence: 99%

A Multi-Objective Improved Cockroach Swarm Algorithm Approach for Apartment Energy Management Systems

Alhasnawi,

Jasim,

Jasim

et al. 2023

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The electrical demand and generation in power systems is currently the biggest source of uncertainty for an electricity provider. For a dependable and financially advantageous electricity system, demand response (DR) success as a result of household appliance energy management has attracted significant attention. Due to fluctuating electricity rates and usage trends, determining the best schedule for apartment appliances can be difficult. As a result of this context, the Improved Cockroach Swarm Optimization Algorithm (ICSOA) is combined with the Innovative Apartments Appliance Scheduling (IAAS) framework. Using the proposed technique, the cost of electricity reduction, user comfort maximization, and peak-to-average ratio reduction are analyzed for apartment appliances. The proposed framework is evaluated by comparing it with BFOA and W/O scheduling cases. In comparison to the W/O scheduling case, the BFOA method lowered energy costs by 17.75%, but the ICSA approach reduced energy cost by 46.085%. According to the results, the created ICSA algorithm performed better than the BFOA and W/O scheduling situations in terms of the stated objectives and was advantageous to both utilities and consumers.

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Section: References Groups Reference Contributions Shortcomingsmentioning

confidence: 99%

A Multi-Objective Improved Cockroach Swarm Algorithm Approach for Apartment Energy Management Systems

Alhasnawi,

Jasim,

Jasim

et al. 2023

Information

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“…Many difficult real-time engineering problems have been solved by using heuristic algorithms inspired by the behavior of many events or creatures in nature [18][19][20][21][22][23][24][25][26][27][28][29][30]. With the help of heuristic algorithms such as genetic algorithm (GA), particle swarm optimization (PSO), and differential evolution algorithm (DE), ML estimation is computed recursively for optimizing subspace search.…”

Section: Introductionmentioning

confidence: 99%

“…BSA algorithm is a new evolutionary algorithm that provides more efficient solutions with fewer parameters and has recently been used in wide application areas [22]. some studies are using BSA in many areas such as antenna design, medicine, meteorology, Complementary metal oxide semiconductor (CMOS) circuit design, and chemistry [22][23][24][25][26][27][28][29]. When we consider the literature, there is no heuristic-based proposal to eliminate the disadvantages of ML algorithms in MIMO-NOMA systems.…”

Section: Introductionmentioning

confidence: 99%

Symbol Detection Based on Back Tracking Search Algorithm in MIMO-NOMA Systems

Seyman¹

2022

Computer Systems Science and Engineering

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One of the most important methods used to cope with multipath fading effects, which cause the symbol to be received incorrectly in wireless communication systems, is the use of multiple transceiver antenna structures. By combining the multi-input multi-output (MIMO) antenna structure with non-orthogonal multiple access (NOMA), which is a new multiplexing method, the fading effects of the channels are not only reduced but also high data rate transmission is ensured. However, when the maximum likelihood (ML) algorithm that has high performance on coherent detection, is used as a symbol detector in MIMO NOMA systems, the computational complexity of the system increases due to higher-order constellations and antenna sizes. As a result, the implementation of this algorithm will be impractical. In this study, the backtracking search algorithm (BSA) is proposed to reduce the computational complexity of the symbol detection and have a good bit error performance for MIMO-NOMA systems. To emphasize the efficiency of the proposed algorithm, simulations have been made for the system with various antenna sizes. As can be seen from the obtained results, a considerable reduction in complexity has occurred using BSA compared to the ML algorithm, also the bit error performance of the system is increased compared to other algorithms.

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Review on optimization techniques and role of Artificial Intelligence in home energy management systems

Nutakki

Mandava

2023

Engineering Applications of Artificial Intelligence

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Optimization of Demand-Response-Based Intelligent Home Energy Management System with Binary Backtracking Search Algorithm

Cited by 7 publications

References 43 publications

A Multi-Objective Improved Cockroach Swarm Algorithm Approach for Apartment Energy Management Systems

A Multi-Objective Improved Cockroach Swarm Algorithm Approach for Apartment Energy Management Systems

Symbol Detection Based on Back Tracking Search Algorithm in MIMO-NOMA Systems

Review on optimization techniques and role of Artificial Intelligence in home energy management systems

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