NDLI: Forecasting and optimisation for microgrid in home energy management systems

Content Provider	IET Digital Library
Author	Shakir, Majed Biletskiy, Yevgen
Abstract	The wide proliferation of renewable energy and deregulation of power grid systems require small power utilization systems to deploy intelligent methods of adjustment to the user power demand. To accomplish this goal, the smart power demand forecasting and power consumption optimization methods and algorithms need to be developed. For this purpose, small power utilization systems can benefit from the techniques developed for the smart grid in general. The present paper is devoted to the development of a forecasting model based on the Long Short-Term Memory (LSTM) method and an optimization model based on Genetic Algorithm (GA) adopted for the use in home energy management systems (HEMS). The present work describes a smart microgrid architecture with a focus on LSTM and GA. The experiments demonstrate that the developed algorithms generate a stable pattern of daily power demand. The use of the developed algorithms allows automated shifting of power to achieve the lowest price without sacrificing their comfort. The main contributions of the present work are the inclusion of all parts of the smart microgrid architecture (non-invasive load identification, forecasting, optimization, renewable energy sources and storage elements) in the research proposing a fully automated control in HEMS rather than recommendation based only.
Starting Page	3458
Ending Page	3468
Page Count	11
ISSN	17518687
Volume Number	14
e-ISSN	17518695
Issue Number	Issue 17, Sep (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-gtd/14/17
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-gtd.2019.1285
Journal	IET Generation, Transmission & Distribution
Publisher Date	2020-06-02
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Demand Side Management Distributed Power Generation Energy Management System Genetic Algorithm Home Energy Management System Load Identification Subsystem Long Short-term Memory Method Neural Computing Technique Newton-phaselet Algorithm Noninvasive Load Identification Optimisation Technique Power Consumption Power Consumption Optimisation Power Engineering Computing Power Grid System Power System Economics Power System Managemen Power System Operation Power Utilisation System Recurrent Neural Nets Renewable Energy Source Small-scale Smart Grid Architecture Smart Microgrid Architecture Smart Power Demand Forecasting
Content Type	Text
Resource Type	Article
Subject	Control and Systems Engineering Energy Engineering and Power Technology Electrical and Electronic Engineering

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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