Appliance-Level Flexible Scheduling for Socio-Technical Smart Grid Optimization

被引:9
|
作者
Fanitabasi, Farzam [1 ]
Pournaras, Evangelos [2 ]
机构
[1] Swiss Fed Inst Technol, Chair Computat Social Sci, CH-8092 Zurich, Switzerland
[2] Univ Leeds, Sch Comp, Leeds LS2 9JT, W Yorkshire, England
来源
IEEE ACCESS | 2020年 / 8卷 / 08期
关键词
Home appliances; Load management; Schedules; Smart grids; Power system stability; Cost function; Appliance scheduling; flexibility; demand response; smart grid; distributed optimization; DEMAND-SIDE MANAGEMENT; PEAK ELECTRICITY DEMAND; ENERGY-DEMAND; DISTRIBUTED ALGORITHM; HOUSEHOLD APPLIANCES; FLEXIBILITY; TIME; FRAMEWORK; RESOURCE; STRATEGY;
D O I
10.1109/ACCESS.2020.3001763
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Participation in residential energy demand response programs requires an active role by consumers. They contribute flexibility in how they use their appliances as the means to adjust energy consumption, and reduce demand peaks, possibly at the expense of their own comfort (e.g., thermal). Understanding the collective potential of appliance-level flexibility for reducing demand peaks is challenging and complex. For instance, physical characteristics of appliances, usage preferences, and comfort requirements all influence consumer flexibility, adoption, and effectiveness of demand response programs. To capture and study such socio-technical factors and trade-offs, this paper contributes a novel appliance-level flexible scheduling framework based on consumers' self-determined flexibility and comfort requirements. By utilizing this framework, this paper studies (i) consumers' usage preferences across various appliances, as well as their voluntary contribution of flexibility and willingness to sacrifice comfort for improving grid stability, (ii) impact of individual appliances on the collective goal of reducing demand peaks, and (iii) the effect of variable levels of flexibility, cooperation, and participation on the outcome of coordinated appliance scheduling. Experimental evaluation using a novel dataset collected via a smartphone app shows that higher consumer flexibility can significantly reduce demand peaks, with the oven having the highest system-wide potential for this. Overall, the cooperative approach allows for higher peak-shaving compared to non-cooperative schemes that focus entirely on the efficiency of individual appliances. The findings of this study can be used to design more cost-effective and granular (appliance-level) demand response programs in participatory and decentralized Smart Grids.
引用
收藏
页码:119880 / 119898
页数:19
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