Time based device clustering for domestic power scheduling

Aziz, Muhammad Adnan; Qureshi, Ijaz Mansoor; Cheema, Tanweer Ahmad; Malik, Arshad Nawaz

doi:10.21833/ijaas.2017.01.001

Cited by 5 publications

(12 citation statements)

References 16 publications

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“…Out of these 1000 houses, each class of community consists of 250 houses. The clustering parameters are tuned for one day's load profile as proposed by Aziz et al [33]. This section presents the results and simulation outcomes for the proposed algorithm.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…The number of clusters is decided to be 5. The selected parameters are claimed to be the best clustering combination for randomly generated load profiles for a period of 90 days [33].…”

Section: Simulation Resultsmentioning

confidence: 99%

“…In this study, following four types of profiles are generated. Profile for unoptimized data, profile with IBR included with PSO for load scheduling [33], profile with CCHEMS based appliance clustering [33] and profile with the proposed dynamic appliance clustering. Note that the electricity pricing data is taken from Ameren Illinois Power Company (2015) for the duration of 11th April 2015 to 9th July 2015.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…9. The C3 is varied from 2 to 7 clusters per community with both uniform and unequal cluster sizes [33]. Based on PARR best clustering combination is employed in randomly generated population load profile for 90 days as presented in simulations Section-V.…”

Section: B Formulation Of Dcchemsmentioning

confidence: 99%

“…But model uses a population of only 25 houses. Aziz et al presents a power scheduling methodology for a large population [32], [33]. However, the technique is based on the assumption of homogeneous consumption.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

A Novel Dynamic Appliance Clustering Scheme in a Community Home Energy Management System for Improved Stability and Resiliency of Microgrids

Abbasi

Sultan²,

Aziz

et al. 2021

IEEE Access

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Power scheduling of domestic appliances is a vital preference for bridging the gap between demand and generation of electricity in a microgrid. For a stable microgrid, an acceptable mechanism must reduce the peak to average ratio (PAR) of power demand with supplementary benefits for consumers as reduced electricity charges. Recent studies have focused on PAR and cost reduction for a small consumer population. Furthermore, researchers have mainly considered homogeneous consumer loads. This study focuses on residential power scheduling for electricity cost reduction for consumers and load profile PAR curtailment for a relatively large consumer population with non-homogeneous loads. A sample population of 1000 consumers from various classes of society is considered. The proposed dynamic clustered community home energy management system (DCCHEMS) allows the clustering of appliances based on time overlap criteria. Comparatively flatter power demand is attained by utilizing the clustered appliances in conjunction with particle swarm optimization under the influence of user-defined constraints. Modified inclined block rates with real-time electricity pricing strategies are deployed to minimize the electricity costs. DCCHEMS achieved higher efficiency rates in contrast to the traditional non-clustering and static clustering optimization schemes. An improvement of 21% in peak to average ratio, 4% in cost reduction, and 19% in variance to mean ratio is obtained.

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Section: Simulation Resultsmentioning

confidence: 99%

“…The number of clusters is decided to be 5. The selected parameters are claimed to be the best clustering combination for randomly generated load profiles for a period of 90 days [33].…”

Section: Simulation Resultsmentioning

confidence: 99%

Section: Simulation Resultsmentioning

confidence: 99%

Section: B Formulation Of Dcchemsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A Novel Dynamic Appliance Clustering Scheme in a Community Home Energy Management System for Improved Stability and Resiliency of Microgrids

Abbasi

Sultan²,

Aziz

et al. 2021

IEEE Access

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Mechanical, morphological, and tribological behavior of Eulaliopsis binata fiber epoxy composites

Pradhan

Acharya

Prakash

2020

J of Applied Polymer Sci

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This study is aimed at the potential use of a new natural fiber in polymer based composites (Eulaliopsis binata fiber) as a reinforcing material whose potential for tribological applications is still an unexposed area of research. The characterization studies of the fiber has been carried out with XRD, EDS, and Scanning electron microscope (SEM). Different weight percentages (10, 20, 30, and 40%) of short fiber were taken as reinforcement with epoxy polymer resin and hardener to study the tensile, flexural, and impact strength as well as the abrasive wear behavior of the developed composites. The experimental results indicate significant improvement in the mechanical and wear properties of epoxy with the incorporation of Eulaliopsis binata (EB) fiber. The composites containing 30 and 20 weight fraction of Eulaliopsis binata fiber exhibit optimum mechanical properties and abrasion resistance, respectively. The fractured and worn surfaces of the composites were studied under SEM to find out the failure mechanisms.

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