Influence of thermal energy storage and heat pump parametrization for demand-side-management in a nearly-zero-energy-building using model predictive control

•Demand-Side-Management with air-to-water heat pump in a Nearly-Zero-Energy-Building.•Model Predictive Control with Artificial Neural Network for heat demand prediction.•Variation of storage capacity and heat pump power shows cost savings up to 24.3%•Market based concepts need further incentives to...

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Bibliographic Details
Published in:Energy and buildings 2020-11, Vol.226, p.110364, Article 110364
Main Authors: Bechtel, Steffen, Rafii-Tabrizi, Sasan, Scholzen, Frank, Hadji-Minaglou, Jean-Régis, Maas, Stefan
Format: Article
Language:English
Subjects:
Cost analysis
Cost control
Cost reduction
Demand
Demand-side-management
Electricity
Electricity pricing
Energy conservation
Energy efficiency
Energy management
Energy storage
Green buildings
Heat exchangers
Heat pumps
Heat storage
Heat-pump
Impact analysis
Incentives
Model predictive control
Neural networks
NZEB
Optimization
Parameterization
Photovoltaic cells
Photovoltaics
Predictive control
Thermal energy
Turbines
Wind power
Wind turbines
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Summary:•Demand-Side-Management with air-to-water heat pump in a Nearly-Zero-Energy-Building.•Model Predictive Control with Artificial Neural Network for heat demand prediction.•Variation of storage capacity and heat pump power shows cost savings up to 24.3%•Market based concepts need further incentives to exploit the flexibility potential of heat pumps. 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.
ISSN:0378-7788
1872-6178
DOI:10.1016/j.enbuild.2020.110364