MANFIS based SMART home energy management system to support SMART grid

G.K, Jabash Samuel; Jasper, J.

doi:10.1007/s12083-020-00884-8

Cited by 18 publications

(6 citation statements)

References 11 publications

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“…This work differs from other related surveys in the literature, such as, [22][23][24][25][26][27][28][29][30][31][32][33][34] in being the first meta-analytic review on efficient SG energy management. From the existing literature, it is also conclude that mostly meta-heuristic techniques are used for optimization because of their ability to deal with large and complex scenarios with less execution time.…”

Section: Motivation For the Research Workmentioning

confidence: 90%

“…For efficient supply demand balance, the EMS makes use of various control strategies namely proportional-integral (PI) and adaptive neuro fuzzy inference system (ANFIS). Jabash Samuel and Jasper, 30 have explained the Smart Home Energy Management System using Multi-output Adaptive neuro-fuzzy inference system for efficient management of Energy Storage System, scheduled appliances and to integrate Renewable energy. The controller can interrupt or postpone scheduled appliances and trading surplus energy between consumers thereby reducing reverse power flow and electricity cost.…”

Section: Recent Research Work: a Brief Reviewmentioning

confidence: 99%

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A hybrid RFCRO approach for the energy management of the grid connected microgrid system

Roy

Mandal

2020

Int Trans Electr Energ Syst

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Energy management of the grid connected microgrid (MG) systems with low cost using a novel hybrid algorithm is implemented in this paper. The novel proposed hybrid technique is the combined performance of both the Random Forest (RF) and Coral Reefs Optimization (CRO) algorithm and in this way it is named as RFCRO. Optimum operation of micro-sources for decreasing the electricity production cost by hourly day-ahead and real-time scheduling is the main objective of the paper. The proposed hybrid technique is to manage the power flows between the energy sources and the grid. To achieve this point, demand response and minimum cost of energy are determined. This technique is involved with the mathematical optimization problems that necessitate more than one fitness function to be optimized simultaneously. By using the inputs of MG-like wind turbine, photovoltaic array, battery, and fuel cell with corresponding cost functions, the RF is employed to predict the load demand. CRO clarifies the squirrel in optimizing the configuration of MG based on the load demand. The proposed hybrid technique is implemented in MATLAB/ Simulink working platform and compared with other solution techniques like

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Section: Motivation For the Research Workmentioning

confidence: 90%

Section: Recent Research Work: a Brief Reviewmentioning

confidence: 99%

A hybrid RFCRO approach for the energy management of the grid connected microgrid system

Roy

Mandal

2020

Int Trans Electr Energ Syst

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“…This solution was implemented in the form of a platform for data collection and sharing on the way to integrated energy management. The system presented in [200] is called MANFIS. The idea is based on smart management by using a neuro-fuzzy inference model to adjust the usage to current needs of storage, connected appliances, and renewable energy source.…”

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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“…Samuel et al [17] suggested a multi-output adaptive neuro-fuzzy inference system (MANFIS)based home energy management system. The fuzzy controller can interrupt various appliance operations and exchange consumers' excess energy via the grid, thereby decreasing power flow and the cost of electricity.…”

Section: Literature Survey and Features Of This Research Papermentioning

confidence: 99%

“…This simplifies the integration of RES effective energy for the removal of waste energy and enlargement of revenue. The charging of energy storage systems is implemented as follows, W e a,R (r + 1) = W e a,R (r) − A e c,R (r) + W e R (r) (17) as inferred from Equation 17where W e a,R (r) indicates the original ESS energy stored at each slot of time r and A e c,R (r) is the component of energy storage system strained energy. The attributes of energy determined in energy storage system restraints are provided as,…”

Section: Controllablementioning

confidence: 99%

Fuzzy Efficient Energy Smart Home Management System for Renewable Energy Resources

2020

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This article provides a fuzzy expert system for efficient energy smart home management systems (FES-EESHM), demand management, renewable energy management, energy storage, and microgrids. The suggested fuzzy expert framework is utilized to simplify designing smart microgrids with storage systems, renewable sources, and controllable loads on resources. Further, the fuzzy expert framework enhances energy and storage to utilize renewable energy and maximize the microgrid’s financial gain. Moreover, the fuzzy expert system utilizes insolation, electricity price, wind speed, and load energy controllably and unregulated as input variables to enable energy management. It uses input variables including insolation, electrical quality, wind, and the power of uncontrollable and controllable loads to allow energy management. Furthermore, these input data can be calculated, imported, or predicted directly via grid measurement using any prediction process. In this paper, the input variables are fuzzified, a series of rules are specified by the expert system, and the output is de-fuzzified. The findings of the expert program are discussed to explain how to handle microgrid power consumption and production. However, the decisions on energy generated, controllable loads, and own consumption are based on three outputs. The first production is for processing, selling, or consuming the energy produced. The second output is used for controlling the load. The third result shows how to produce for prosumer’s use. The expert method can be checked via the hourly input of variable values. Finally, to confirm the findings, the method suggested is compared to other available approaches.

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MANFIS based SMART home energy management system to support SMART grid

Cited by 18 publications

References 11 publications

A hybrid RFCRO approach for the energy management of the grid connected microgrid system

A hybrid RFCRO approach for the energy management of the grid connected microgrid system

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

Fuzzy Efficient Energy Smart Home Management System for Renewable Energy Resources

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