期刊
ENERGY AND BUILDINGS
卷 226, 期 -, 页码 -出版社
ELSEVIER SCIENCE SA
DOI: 10.1016/j.enbuild.2020.110364
关键词
Heat-pump; Demand-side-management; Model predictive control; Neural networks; Energy storage; NZEB
资金
- European Union through the Interreg VA Grande Region initiative
- Enovos Luxembourg S.A.
The rollout of the supply dependent generators wind turbines and photovoltaics leads to a flexibility demand that can be adressed from the consumer side, via Demand-Side-Management, as well. In single family houses, the heat pump, in combination with thermal energy storage, can shift their energy comsumption according to price signals in order to reduce consumer costs. This paper analyses the impact of different heat storage sizes and heat pump powers on cost savings and shifting potential, focussing on the Luxembourgish context, when variable electricity prices based on the electricity market are applied. A model predictive controller determines the cost-optimal operating cycles of the heat pump. The building's heat demand is predicted with the help of a neural network. The results of the parametric study show significant differences in energy efficiency and cost savings. Furthermore limitations of taking advantage of variable electicity prices due to the price structure are disclosed. The cost savings however do not give a sufficient incentive for the consumer to invest in optimizing the heating system for Demand-Side-Management purposes. By consequence, the potential and the efficiency of Demand-Side-Management are limited and further incentives are necessary. (C) 2020 Elsevier B.V. All rights reserved.
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