- Title
- Stochastic residential energy resource scheduling by multi-objective natural aggregation algorithm
- Creator
- Luo, Fengji; Ranzi, Gianluca; Liang, Gaoqi; Dong, Zhao Yang
- Relation
- 2017 IEEE Power & Energy Society General Meeting. Proceedings of the 2017 IEEE Power & Energy Society General Meeting (Chicago, IL 16-20 July, 2017)
- Relation
- Funding BodyARCGrant NumberFT140100130 http://purl.org/au-research/grants/arc/FT140100130
- Publisher Link
- http://dx.doi.org/10.1109/PESGM.2017.8274308
- Publisher
- Institute of Electrical and Electronics Engineers (IEEE)
- Resource Type
- conference paper
- Date
- 2017
- Description
- This paper studies the coordinated scheduling of residential energy resources in a smart home environment. The particularity of this paper is to consider the uncertainties of the must-run appliance load demand forecast errors and to addresses the residential energy resource scheduling through a multi-objective optimization approach. Multiple 1-day must-run appliance power demand scenarios are firstly generated from the house's historical energy consumption data. Based on this, a stochastic day-ahead appliance scheduling model is formulated, aiming to minimize the 1-day energy costs while maximizing the preference of the homeowner simultaneously. A new multi-objective optimization tool, i.e. Multi-Objective Natural Aggregation Algorithm (MONAA), is proposed to solve the stochastic day-ahead appliance scheduling model. Simulations are designed for the validation of the proposed method.
- Subject
- smart home; demand response; natural aggregation algorithm; smart grid; multi-objective optimization
- Identifier
- http://hdl.handle.net/1959.13/1385649
- Identifier
- uon:32267
- Identifier
- ISBN:9781538622124
- Language
- eng
- Reviewed
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