Time and Device Based Priority Induced Demand Side Load Management in Smart Home with Consumer Budget Limit

Khan, Asif; Javaid, Nadeem; Iqbal, Muhammad; Anwar, Naveed; Haq, Inzimam-ul; Ahmad, Feroz

doi:10.1109/aina.2018.00129

Cited by 10 publications

(12 citation statements)

References 14 publications

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“…On the other hand, in [185] , [186] , an accretive comfort algorithm based on time-dependent and device-based priorities, implemented with the GA technique, was proposed. Another research was presented in [187] , which considered cost and peak load reduction with optimal user comfort as their main objectives.…”

Section: Energy Scheduling Controller and Optimization Techniques In ...mentioning

confidence: 99%

Analysis of energy management schemes for renewable-energy-based smart homes against the backdrop of COVID-19

Ayub

Ayob

Tan

et al. 2022

Sustainable Energy Technologies and Assessments

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Section: Energy Scheduling Controller and Optimization Techniques In ...mentioning

confidence: 99%

Analysis of energy management schemes for renewable-energy-based smart homes against the backdrop of COVID-19

Ayub

Ayob

Tan

et al. 2022

Sustainable Energy Technologies and Assessments

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“…In [18], the authors have suggested a genetic algorithm-based DSM technique for industrial and commercial micro-grid with one solarbased RES, two diesel generators, and BSS, with the dynamic pricing DR program of the utility grid. A multi-comfortbased optimization scheme for home energy management is proposed in [19] based on time and appliance-based priorities under DSM to schedule load and keep cost under user budget limits. Multiple agents have been suggested to manage different appliances, energy storage systems, and renewable energy from a smart home DSM system within the home area network.…”

Section: Introductionmentioning

confidence: 99%

Demand Response Program for Efficient Demand-Side Management in Smart Grid Considering Renewable Energy Sources

et al. 2022

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A smart energy management controller can improve energy efficiency, save energy costs, and reduce carbon emissions and energy consumption while accurately catering to consumer consumption habits. Having integrated various renewable energy systems (RESs) and a battery storage system (BSS), we proposed an optimization-based demand-side management (DSM) scheduler and energy management controller (SEMC) for a smart home. The suggested SEMC creates a DSM-based operational plan regarding user-centered and comfort-aware preferences. Using the generated appliances operation plan, consumers can reduce energy costs, carbon emissions, peak-to-average ratio (PAR), improve their comfort in terms of thermal, illumination, and appliances usage preferences. A schedule for residential consumers is suggested using ant colony optimization (ACO), teaching learning-based optimization (TLBO), Jaya algorithm, rainfall algorithm, firefly algorithm, and our hybrid ACO and TLBO optimization (ACTLBO) algorithm. Five existing algorithms-based frameworks validate the DSM framework that relies on ACTLBO. The results validate that the integration of RESs and BSS, and adapting our proposed algorithm and SEMC under demand response program real-time price reduced the energy bill costs, PAR and CO 2 in Case I: only external grid (EG) usage by 42.14%, 22.05%, and 28.33%, in Case II: EG with RESs by 21.79%, 11.27%, 17.02%, and in Case III: EG with RESs and BSS by 28.76%, 41.53%, 21.86%, respectively as compared to without employing SEMC. Moreover, the user comfort improvement index-ratio with scheduling using ACTLBO is 7.77%, 24.73%, 5.00%, and 3.43% in terms of average delay, indoor air quality, thermal, and visual, respectively. Simulation results show that the proposed DSM-based framework outperforms existing frameworks to reduce energy bill costs, reduce carbon emissions, mitigate peak loads, and improve user comfort.INDEX TERMS energy management controller, user-comfort, demand shifting, load scheduling, battery storage systems, demand response, solar energy, smart grid. NOMENCLATURE

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“…Several DR pricing schemes are defined in the literature. The survey presented in [3] contains a comprehensive review of DR pricing programs and how these programs are integrated with different optimization-based approaches ( [4], [5]). Some of those price-based programs are currently available in different jurisdictions around the world [6].…”

Section: Introductionmentioning

confidence: 99%

Optimal setting of time-and-level-of-use prices for an electricity supplier

Anjos

Brotcorne

Gomez-Herrera

2021

Energy

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Time and Device Based Priority Induced Demand Side Load Management in Smart Home with Consumer Budget Limit

Cited by 10 publications

References 14 publications

Analysis of energy management schemes for renewable-energy-based smart homes against the backdrop of COVID-19

Analysis of energy management schemes for renewable-energy-based smart homes against the backdrop of COVID-19

Demand Response Program for Efficient Demand-Side Management in Smart Grid Considering Renewable Energy Sources

Optimal setting of time-and-level-of-use prices for an electricity supplier

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