An optimal day-ahead load scheduling approach based on the flexibility of aggregate demands

被引:101
作者
Ayon, X. [1 ]
Gruber, J. K. [2 ]
Hayes, B. P. [3 ]
Usaola, J. [1 ]
Prodanovic, M. [2 ]
机构
[1] Univ Carlos III Madrid, Dept Elect Engn, Ave Univ 30, Madrid 28911, Spain
[2] IMDEA Energy Inst, Elect Syst Unit, Avda Ramon de la Sagra 3, Madrid 28935, Spain
[3] Natl Univ Ireland Galway, Dept Elect & Elect Engn, Univ Rd, Galway, Ireland
关键词
Demand flexibility; Demand response; Load scheduling; Electricity market; OF-USE TARIFFS; SIDE MANAGEMENT; BUILDINGS;
D O I
10.1016/j.apenergy.2017.04.038
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
080707 [能源环境工程]; 082001 [油气井工程];
摘要
The increasing trends of energy demand and renewable integration call for new and advanced approaches to energy management and energy balancing in power networks. Utilities and network system operators require more assistance and flexibility shown from consumers in order to manage their power plants and network resources. Demand response techniques allow customers to participate and contribute to the system balancing and improve power quality. Traditionally, only energy-intensive industrial users and large customers actively participated in demand response programs by intentionally modifying their consumption patterns. In contrast, small consumers were not considered in these programs due to their low individual impact on power networks, grid infrastructure and energy balancing. This paper studies the flexibility of aggregated demands of buildings with different characteristics such as shopping malls, offices, hotels and dwellings. By using the aggregated demand profile and the market price predictions, an aggregator participates directly in the day-ahead market to determine the load scheduling that maximizes its economic benefits. The optimization problem takes into account constraints on the demand imposed by the individual customers related to the building occupant comfort. A case study representing a small geographic area was used to assess the performance of the proposed method. The obtained results emphasize the potential of demand aggregation of different customers in order to increase flexibility and, consequently, aggregator profits in the day-ahead market. (C) 2017 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1 / 11
页数:11
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