Community-Based Optimal Scheduling of Smart Home Appliances Incorporating Occupancy Error

One challenge facing the utility is management of peak demands since electricity cannot be stored in bulk so the utility has to match demand at any point in time. Demand response management has proven to be a significant way of reducing these peaks. Scheduling of electrical appliances and proper design of the electricity tariffs are some of the mechanisms used in demand response management to reduce these peaks. With proper design demand response scheme, the consumer will be motivated to either shift their loads from peaking periods or reduce their consumption. It was the aim of this study to come out with scheduling scheme to reduce peaking in the grid taking into account occupancy error detection factor and combining wind energy and solar to reduce the intermittency nature of these renewables. In this study a mixed integer linear programming based smart appliance scheduling scheme with real-time pricing and algorithm to service as motion sensor were proposed. It can be said that the proposed scheduling scheme and pricing scheme (real-time pricing) provided enough incentives for the customers to encourage them to accept the proposed scheme. Significant savings on electricity bill of the community was realized using the proposed schemes. Savings made on occupancy error detection alone was not significant as compared to the total power consumed by the community, but it must be realized that this is just a conceptual study and it does not represent reality. It was therefore recommended that the proposed scheduling scheme incorporating occupancy error detection mechanism should be deployed in a real community of residential housing and simulate in realistic conditions.

Name thesis:degree_name

Master of Science in Electrical Engineering

Level thesis:degree_level

masters

Discipline thesis:degree_discipline

Electrical Engineering

Grantor dc:publisher

University of Toledo

Year dc:date

2013

Author dc:creator

• Ansu-Gyeabour, Ernest

Contributors dc:contributor

• Lingfeng , Wang

• Electrical Engineering
• Sustainability
• Smart Grid
• Demand Response
• Smart Home
• Optimal Smart Appliances
• Real-Time Pricing
• Appliances Scheduling
• Occupancy Error Detection

Statement dc:rights

• unrestricted
• This thesis or dissertation is protected by copyright: some rights reserved. It is licensed for use under a Creative Commons license. Specific terms and permissions are available from this document's record in the OhioLINK ETD Center.

Language dc:language

English

Repository record dc:identifier

http://rave.ohiolink.edu/etdc/view?acc_num=toledo1365171120

OAI identifier oai:identifier

oai:etd.ohiolink.edu:toledo1365171120