A highly resolved modeling technique to simulate residential power demand

By Matteo Muratori, M. Roberts, Ramteen Sioshansi, Vincenzo Marano, Giorgio Rizzoni. 2013

219 citations recorded by the source corpus.

Subfields: Building and Construction, Electrical and Electronic Engineering, Renewable Energy, Sustainability and the Environment

View Paper: https://www.semanticscholar.org/paper/94f7cc6de23b4abf4a184c52566270383e986030

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. Ramteen Sioshansi
2. Antonio J. Conejo
3. Giorgio Rizzoni
4. Matteo Muratori

In Electrical and Electronic Engineering

1. Matteo Muratori
2. Iain Staffell
3. Antonio J. Conejo
4. Ramteen Sioshansi
5. Yixian Liu
6. T. Bossmann
7. Giorgio Rizzoni
8. Luis Baringo

In Renewable Energy, Sustainability and the Environment

1. Matteo Muratori
2. Iain Staffell
3. Antonio J. Conejo
4. Ramteen Sioshansi
5. T. Bossmann
6. Giorgio Rizzoni
7. M. Joos

Citations in the corpus

• Multistage Stochastic Investment Planning With Multiscale Representation of Uncertainties and Decisions (2018, methodology): “Electricity-demand patterns are modeled using Monte Carlo simulation [33] and time series techniques [34].”
• The Shape of Future Electricity Demand: Exploring Load Curves in 2050s Germany and Britain (2015, background): “Most of the studies focus on the load curve projection of single sectors or consumers [26]–[33].”
• Residential Demand Response: Dynamic Energy Management and Time-Varying Electricity Pricing (2016, background): “4Laundry is modeled as two separate parts: washing and drying [26].”