Home Energy Management System for Interconnecting and Sensing of Electric Appliances

Cho, Wei Ting; Lai, Chin Feng; Huang, Yueh Min; Lee, Wei Tsong; Huang, Sing Wei

doi:10.3837/tiis.2011.07.004

Cited by 7 publications

(4 citation statements)

References 25 publications

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“…There is a paradigm shift experienced in recent years in which people started preferring electric cars instead of ICE-based fuel engine cars to be productive, sustainable, and ahead of the competition [24]. Cho et al [25] proposed an Interconnecting and detecting electric appliances as part of a home energy management system. This technique can be used in our proposed model for electric generation in India.…”

Section: Future Generation Of Electricitymentioning

confidence: 99%

Optimal Energy Forecasting Using Hybrid Recurrent Neural Networks

Poongavanam¹,

Kasinathan²,

Kanagasabai³

2023

Intelligent Automation &Amp; Soft Computing

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The nation deserves to learn what India's future energy demand will be in order to plan and implement an energy policy. This energy demand will have to be fulfilled by an adequate mix of existing energy sources, considering the constraints imposed by future economic and social changes in the direction of a more sustainable world. Forecasting energy demand, on the other hand, is a tricky task because it is influenced by numerous micro-variables. As a result, an macro model with only a few factors that may be predicted globally, rather than a detailed analysis for each of these variables, is required. In this work, a hybrid approach is proposed for identifying the optimal generation-based mix of electricity systems in India. This approach is developed by combing Recalling-Enhanced Recurrent Neural Network (RERNN) and Giza Pyramids Construction (GPC). RERNN possesses selective memory features whereas GPC is a meta-heuristic algorithm that deals with different sets of problems. The goal of this approach is to assess the present load requirements and production profile to understand the current requirement and its production methods. Data on regards to electricity load profile involving the generation of all power plants, capacity factors and transmission limits were gathered from different sources including the Indian National Load Dispatch Centre, Central Electricity Authority database, annual reports of India and regional load dispatching centers. The proposal has introduced the RERNN technique to analyze the optimal time series whereas the GPC technique is involved in the optimization of RERNN parameters. The present work is simulated in MATLAB and the performance assessed with different parameters. The present technique gives an effective results in terms of accuracy, computational efficiency and feasibility.

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Section: Future Generation Of Electricitymentioning

confidence: 99%

Optimal Energy Forecasting Using Hybrid Recurrent Neural Networks

Poongavanam¹,

Kasinathan²,

Kanagasabai³

2023

Intelligent Automation &Amp; Soft Computing

View full text Add to dashboard Cite

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“…Creating a potential rule to bolster national security standards allows for a further evaluation of the best way to deploy local hydro and renewable energy sources [29]. The system's clustering approach locates the cluster data that corresponds to the identified features and groups of linked electric appliances, removes noise from the credit for functionality, and finds flawed electric usage mechanisms [30]. In order to manage the variations brought about by the mainstreaming of renewable energy, we proposed and examined the effectiveness of demand-side measures.…”

Section: Related Research Workmentioning

confidence: 99%

Energy Forecasting Information System of Optimal Electricity Generation using Fuzzy-based RERNN with GPC

2023

KSII TIIS

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In this paper, a hybrid fuzzy-based method is suggested for determining India's best system for power generation. This suggested approach was created using a fuzzy-based combination of the Giza Pyramids Construction (GPC) and Recalling-Enhanced Recurrent Neural Network (RERNN). GPC is a meta-heuristic algorithm that deals with solutions for many groups of problems, whereas RERNN has selective memory properties. The evaluation of the current load requirements and production profile information system is the main objective of the suggested method. The Central Electricity Authority database, the Indian National Load Dispatch Centre, regional load dispatching centers, and annual reports of India were some of the sources used to compile the data regarding profiles of electricity loads, capacity factors, power plant generation, and transmission limits. The RERNN approach makes advantage of the ability to analyze the ideal power generation from energy data, however the optimization of RERNN factor necessitates the employment of a GPC technique. The proposed method was tested using MATLAB, and the findings indicate that it is effective in terms of accuracy, feasibility, and computing efficiency. The suggested hybrid system outperformed conventional models, achieving the top result of 93% accuracy with a shorter computation time of 6814 seconds.

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“…the same interface. This standard solution has been utilized as a basic model in related work [4][13] [14], where provider bundles are developed specifically for the platform. This solution is often combined with the inversion of control pattern, through which the Bundle Manager finds and starts the Provider Bundles, which consumes the common service.…”

Section: Common Servicementioning

confidence: 99%

Flexible Service Composition Based on Bundle Communication in OSGi

Alcarria¹,

Robles²,

Morales³

et al. 2012

KSII TIIS

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Service provision and consumption platforms are more and more used to enable communication between sensors, actuators and intelligent devices, since they provide mechanisms that make possible the combination of components to create composed services. However, these kinds of platforms have limitations to adapt themselves to new and unknown devices. In this work we analyze the challenge of component or bundle communication by using the Open Services Gateway Initiative (OSGi) technology and we propose three mechanisms with the aim of contributing to flexible component communication: Common Service, Specific Service and WSIF Web Service Invocation. We provide these solutions with some architectural models and validate them through different example services. Finally we compare them regarding performance, flexibility and application complexity.

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Home Energy Management System for Interconnecting and Sensing of Electric Appliances

Cited by 7 publications

References 25 publications

Optimal Energy Forecasting Using Hybrid Recurrent Neural Networks

Optimal Energy Forecasting Using Hybrid Recurrent Neural Networks

Energy Forecasting Information System of Optimal Electricity Generation using Fuzzy-based RERNN with GPC

Flexible Service Composition Based on Bundle Communication in OSGi

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