A preference-based demand response mechanism for energy management in a microgrid

被引:49
作者
da Silva, Igor R. S. [1 ]
Rabelo, Ricardo de A. L. [1 ]
Rodrigues, Joel J. P. C. [1 ,2 ]
Solic, Petar [3 ]
Carvalho, Arthur [4 ]
机构
[1] Univ Fed Piaui, Teresina, PI, Brazil
[2] Inst Telecomunicacoes, Porto, Portugal
[3] Univ Split, Split, Croatia
[4] Miami Univ, Oxford, OH 45056 USA
关键词
Demand Response; Microgrid; Optimization; NSGA-III; Smart grid; NONDOMINATED SORTING APPROACH; RENEWABLE ENERGY; SMART GRIDS; STOCHASTIC OPTIMIZATION; SIDE MANAGEMENT; ALGORITHM; OPERATION; PERFORMANCE; APPLIANCES; EFFICIENCY;
D O I
10.1016/j.jclepro.2020.120034
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
In this work, a preference-based, demand response (DR) multi-objective optimization model based on real-time electricity price is presented to solve the problem of optimal residential load management. The purpose of such a model is threefold: 1) to minimize the costs associated with consumption; 2) to minimize the inconvenience caused to consumers; and 3) to minimize environmental pollution. Potential solutions to the underlying multi-objective optimization problem are subject to a set of electrical and operational constraints related to home appliances categories and the utilization of distributed energy resources (DER) and energy storage systems (ESS). The use of the proposed model is illustrated in a realistic microgrid scenario where suitable solutions were found by the Non-Dominated Sorting Genetic Algorithm III (NSGA-III). These solutions determine new operational periods for home appliances as well as the utilization of DER and ESS for the planning horizon while considering consumer preferences. Besides helping consumers to take advantage of the benefits offered by DR, the experimental results show that the multi-objective DR model together with the NSGA-III algorithm can effectively minimize energy-consumption costs as well as reduce inconvenience costs and environmental pollution. (C) 2020 Elsevier Ltd. All rights reserved.
引用
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页数:14
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