NDLI: Distributed residential energy resource scheduling with renewable uncertainties

Content Provider	IET Digital Library
Author	Luo, Fengji Dong, Zhao Yang Xu, Zhao Kong, Weicong Wang, Fan
Abstract	Advances in metering and two-way communication technologies foster the studies of Home Energy Management System (HEMS). This study proposes a new HEMS, which optimally schedules the distributed residential energy resources (DRERs) in a smart home environment with varying electricity tariff and high solar penetrations. The uncertainties of solar power output are captured by using Monte Carlo sampling technique to generate multiple solar output scenarios based on the probabilistic solar radiation model. The homeowner's rigid and elastic restrictions on the operations of the automatically controlled household appliances are modelled. Based on this, an optimal DRER scheduling model is proposed to minimise the home operation cost while taking into account the homeowner's requirements. A new heuristic optimisation algorithm recently proposed by the authors, i.e. natural aggregation algorithm, is used to solve the proposed model. Simulations based on real Australian solar data are conducted to validate the proposed method.
Starting Page	2770
Ending Page	2777
Page Count	8
ISSN	17518687
Volume Number	12
e-ISSN	17518695
Issue Number	Issue 11, Jun (2018)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-gtd/12/11
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-gtd.2017.1136
Journal	IET Generation, Transmission & Distribution
Publisher Date	2018-03-22
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Australian Solar Data Automatically Controlled Household Appliance Cost Reduction Distributed Power Generation Distributed Residential Energy Resource Scheduling Domestic Appliances Electricity Tariff Energy Management System HEMS Heuristic Optimisation Algorithm Home Energy Management System Monte Carlo Method Monte Carlo Sampling Technique Natural Aggregation Algorithm Optimal DRER Scheduling Model Optimisation Optimisation Technique Photovoltaic Power System Power Generation Economics Power Generation Scheduling Power Market Power System Economics Power System Managemen Power System Operation Probabilistic Solar Radiation Model Probability Renewable Energy Source Renewable Uncertainty Sampling Method Smart Home Environment Solar Power Output Solar Power Stations Tariffs Two-way Communication Technology
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
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