Economic Model Predictive Control for building climate control in a Smart Grid

By R. Halvgaard, Niels Kjølstad Poulsen, Henrik Madsen, J. B. Jørgensen. IEEE PES Innovative Smart Grid Technologies Conference, 2012

315 citations recorded by the source corpus.

Subfields: Building and Construction, Control and Systems Engineering, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/d6e273ee8b84db3c3224655bfdad7a820e2419b2

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Building and Construction

1. Pierre Pinson
2. Henrik Madsen
3. Juan M. Morales

In Control and Systems Engineering

1. Pierre Pinson
2. Mark J. O'Malley
3. Henrik Madsen

In Electrical and Electronic Engineering

1. Pierre Pinson
2. Henrik Madsen
3. Juan M. Morales
4. Marco Zugno
5. Mark J. O'Malley
6. Rafal Weron
7. Antonio J. Conejo
8. Janina Ketterer

Citations in the corpus

• Benefits and challenges of electrical demand response: A critical review (2014, methodology): “Model predictive control is also commonly used in studies considering building climate control for demand response [60, 61, 62], and again in these studies the thermal parameters and constraints of the system are taken as known.”
• Optimal Bidding Strategy for Microgrids Considering Renewable Energy and Building Thermal Dynamics (2014, unknown): “Commitment status of unit at time .”
• A bilevel model for electricity retailers' participation in a demand response market environment (2013, methodology): “LP formulation of the consumer problem Based on the work in Halvgaard et al. (2012) we consider a threestate, discrete-time state space model for the heating dynamics of a building.”