Double layer home energy supervision strategies based on demand response and plug-in electric vehicle control for flattening power load curves in a smart grid

Khemakhem, Siwar; Rekik, Mouna; Krichen, Lotfi

doi:10.1016/j.energy.2018.10.187

Cited by 61 publications

(22 citation statements)

References 33 publications

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“…In [191] a nano-grid system was composed of hybrid solar-battery elements in a type of plug-in electric model to optimize the use of energy. A model of doublelayer plug-in electric control to efficiently filter and flatten load amplitudes was discussed in [192]. The proposed model was developed for smart grid systems of home infrastructures.…”

Section: Optimal Energy Management and Sustainabilitymentioning

confidence: 99%

Smart Homes: How Much Will They Support Us? A Research on Recent Trends and Advances

et al. 2021

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The advances in the Internet of Things (IoT) provide several chances to develop a variety of innovations supporting smart home users in several industries including healthcare, energy management, etc. Ubiquitous support by intelligent appliances at modern homes, which constantly work to gather information can help us to solve everyday issues. In this paper, we present a comparative study of recent advances in smart home development. The study aims to present the main trends in this field. During the analysis of the research reports and patents, we identify the propositions that constitute the main research streams. Through extensive analysis, we provide an outlook on the wide spectrum of the proposed solutions. We also analyze the main market to present which publishers are leading with the innovative science in this field. We also show the leaders of science and technology in the World. Finally, we define the ratio of the developments and outline the next stage of the development in the smart home industry. INDEX TERMS Internet of Things (IoT), smart home, healthcare, energy management, security. I. INTRODUCTION O VER time, the type of home was evolving. The shape of the house was evolving during ages, cultural revolutions, and climate changes. We have divided our homes into rooms devoted to sleeping, cooking, work, children, sanitary needs, warehousing, etc. People started to settle in various locations and continents.

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Section: Optimal Energy Management and Sustainabilitymentioning

confidence: 99%

Smart Homes: How Much Will They Support Us? A Research on Recent Trends and Advances

et al. 2021

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“…Słowa kluczowe: SmartX, akwizycja danych pomiarowych, analiza zużycia energii elektrycznej, smart home, inteligentny dom, internet of things, IoT, indeks zielonej energii domową. Może być realizowana przez planowanie działania urządzeń [3] lub też wykorzystywanie dostępnych urządzeń jako magazynów energii. Klasycznym przykładem może być dostosowanie czasu ładowania samochodu elektrycznego w celu maksymalnego wykorzystania energii produkowanej ze źródeł odnawialnych.…”

Section: Wprowadzenieunclassified

The SmartX Platform Application for the Measured Data Acquisition and Energy Management

Kowalczyk

Szeląg

2020

PAR

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“…Few methods are anticipated to maximize the power system self-healing ability together with system reliability, improve economic including cost minimization, decrease energy consumption and maximized customer participation in the direction of decreasing gas emissions, renewable energy system persistent employ on conventional grid also demand side management. 20,21 The rationale behind the research of these problem solutions in terms of data driven strategies at energy management system modeling is owing to the fact that rare cases only the EMS can evaluate local micro-grid energy optimal schedule flows in real time. For this purpose, the linear programming (LP), mixed-integer linear programming (MILP), greedy algorithms, or dynamic programming (DP) based deterministic algorithm are commonly reported in the literature.…”

Section: Introductionmentioning

confidence: 99%

“…Normally, goal of smart grid is to use communication also calculation approach. Few methods are anticipated to maximize the power system self‐healing ability together with system reliability, improve economic including cost minimization, decrease energy consumption and maximized customer participation in the direction of decreasing gas emissions, renewable energy system persistent employ on conventional grid also demand side management 20,21 …”

Section: Introductionmentioning

confidence: 99%

A GBDT‐SOA approach for the system modelling of optimal energy management in grid‐connected micro‐grid system

Arumugam¹,

Kuppan²

2020

Int J Energy Res

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In this manuscript, a hybrid approach for energy management in grid connected MG system is proposed. The grid connected MG system has photovoltaic (PV), wind turbine (WT), micro turbine (MT), battery. The proposed hybrid approach is the consolidation of both the Gradient Boosting Decision Trees (GBDT) and Sandpiper Optimization Algorithm (SOA) and this way the proposed technique is named as GBDT-SOA. Here, at grid connected microgrid configuration the required load demand is ever monitored by the GBDT approach. The perfect combination of the MG is optimized by SOA considering the predicted load requirement. The fuel cost including grid power hourly power variation, operation and maintenance cost of the grid connected microgrid system is defined as the objective of the proposed technique. The constraints are power demand, renewable energy sources, state of charge of storage elements. Batteries have been used as an energy source, to stabilize and allow the renewable power system units to maintain running in a steady, stable output power. At that point, the proposed model is executed in MATLAB/ Simulink work site and the performance is analyzed with existing techniques, such as BFO, SOA and SSA. The efficiency of the sources like photovoltaic, wind turbine, micro turbine, and battery using proposed technique is 95.9375%, 92.113%, 94.387% and 93.7560%.

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Double layer home energy supervision strategies based on demand response and plug-in electric vehicle control for flattening power load curves in a smart grid

Cited by 61 publications

References 33 publications

Smart Homes: How Much Will They Support Us? A Research on Recent Trends and Advances

Smart Homes: How Much Will They Support Us? A Research on Recent Trends and Advances

The SmartX Platform Application for the Measured Data Acquisition and Energy Management

A GBDT‐SOA approach for the system modelling of optimal energy management in grid‐connected micro‐grid system

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