A novel minimum cost maximum power algorithm for future smart home energy management

Singaravelan, A.; Kowsalya, M.

doi:10.1016/j.jare.2017.10.001

Cited by 15 publications

(7 citation statements)

References 16 publications

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“…125 Also in previous investigations, the conflict of aims between potentially worse solution results in the form of local optima and lower computation times is considered. 14 To allow a classification for the length of the computing times, a HEMS optimization problem with a horizon of 24 hours and 15-minute intervals can be taken as an example. This problem is represented by 192 binary decision variables, 96 continuous decision variables, and 625 constraints.…”

Section: Methodsmentioning

confidence: 99%

“…Therefore, the use of heuristics can be an efficient way to determine results 125 . Also in previous investigations, the conflict of aims between potentially worse solution results in the form of local optima and lower computation times is considered 14 …”

Section: Quantitative Evaluation Of the Literature Reviewmentioning

confidence: 99%

“…The literature search on EMS for buildings identified 117 relevant scientific papers 3‐119 . As shown in Figure 1, research interest in EMS for buildings has increased significantly over the last decade.…”

Section: Properties Of the Analyzed Papersmentioning

confidence: 99%

“…Of the researched scientific publications, 98 papers are accessible and can be evaluated to determine the current state of research 3‐100 . Only these 98 papers can be used to examine the current state of research.…”

Section: Properties Of the Analyzed Papersmentioning

confidence: 99%

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Overview of the current state of research on characteristics and algorithms of energy management systems in households and buildings

Schminke

2021

Intl J of Energy Research

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The decentralization of energy supply and the fluctuating feed-in from renewable energies lead to an increasing need to generate electricity and heat locally and efficiently. Therefore, different energy systems are used together at building level. Consequently, energy management systems (EMSs) in the building sector and households are becoming increasingly complex and are facing new challenges. To face these challenges, EMSs are required to enable efficient and combined operation of multiple energy systems and components. The increasing research into EMS is leading to a growing field of research with different characteristics, objectives, and algorithms. However, the resulting diversification of the research topic is accompanied by a lack of transparency. Therefore, this article is the first to provide a comprehensive quantitative evaluation of the state of research. For this purpose, 98 relevant publications are quantitatively evaluated. This article focuses on methods, model characteristics, optimization objectives, price structures, observation horizon, and components and devices used of EMS. The detailed evaluation of these topics creates a high level of transparency in EMS research to provide precise insights into current research priorities and potential weaknesses, to allow researchers to classify their own work and to identify potential research topics. Highlights• For the first time, a quantitative study on EMS research is presented • The evaluation of 98 relevant publications provides detailed insights • Insights about methods, characteristics, objectives, prices, horizons, and components • Detailed graphical evaluations for each sub-area of the study K E Y W O R D S energy price structures, energy management systems in buildings, optimization goals, overview

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Section: Methodsmentioning

confidence: 99%

Section: Quantitative Evaluation Of the Literature Reviewmentioning

confidence: 99%

Section: Properties Of the Analyzed Papersmentioning

confidence: 99%

Section: Properties Of the Analyzed Papersmentioning

confidence: 99%

See 2 more Smart Citations

Overview of the current state of research on characteristics and algorithms of energy management systems in households and buildings

Schminke

2021

Intl J of Energy Research

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“…By the same token, a solution is proposed in Ref. [12] to reduce the energy consumption cost and the peak demand of a residential unit through integration of an EMS. The proposed design benefits from wireless communication and smart metering infrastructure in order to make an efficient scheduling for the electric appliances.…”

Section: Related Workmentioning

confidence: 99%

Integrated Management of Energy, Wellbeing and Health in the Next Generation of Smart Homes

Jaouhari

García

Anvari‐Moghaddam

et al. 2019

Sensors

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This contribution proposes an implementation for next generation smart homes, where heterogeneous data, coming from multiple sensors (medical, wellbeing, energy, contextual, etc.) and house equipment (smart fridge, smart TV, etc.), need to be managed, secured and visualized. As a first step, it focuses only on energy and health data. However, it aims to lay the foundations to manage any type of information towards the development of smart interactions with the house, which might include artificial intelligence and machine learning. These data are securely collected using a central Web of Things gateway, located inside the smart home. For the e-health part, a set of possible use-cases is provided, along with the current progress of the implantation. In this regard, the main idea is to link the next generation smart homes with external medical entities in order to provide, first, quick intervention in the event of an abnormality being detected, and to be able to provide basic medical services such as remote consultations with a doctor for a particular health issue. This vision can be very promising, particularly in rural areas, where access to medical services is difficult. As for the energy part, the aim is to collect users’ energy consumption inside the smart home, which can be supplied from different sources (heat, water, gas, or electricity), and to enable the use of advanced algorithms to predict and manage local energy consumption and production (if any). This approach combines data collected from smart meters, operational information of the smart energy devices (the status of smart plugs), user’s requests and external network signals such as energy prices. By using a home energy management system that accepts such input parameters, the operation of in-home devices and appliances can be optimally controlled according to different objectives (e.g., minimizing energy costs and maximizing user’s comfort level).

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Renewable Energy Management and Implementation in Indian Engineering Institutions—A Case Study

Nair

Ramalingam

Shanmugam

et al. 2019

Advances in Intelligent Systems and Computing

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A novel minimum cost maximum power algorithm for future smart home energy management

Abstract: Graphical abstract

Cited by 15 publications

References 16 publications

Overview of the current state of research on characteristics and algorithms of energy management systems in households and buildings

Overview of the current state of research on characteristics and algorithms of energy management systems in households and buildings

Integrated Management of Energy, Wellbeing and Health in the Next Generation of Smart Homes

Renewable Energy Management and Implementation in Indian Engineering Institutions—A Case Study

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