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Alessandra Parisio
Researcher at University of Manchester
Publications - 61
Citations - 4367
Alessandra Parisio is an academic researcher from University of Manchester. The author has contributed to research in topics: Model predictive control & Microgrid. The author has an hindex of 23, co-authored 52 publications receiving 3706 citations. Previous affiliations of Alessandra Parisio include Royal Institute of Technology & University of Sannio.
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Proceedings ArticleDOI
An MPC-based Energy Management System for multiple residential microgrids
TL;DR: A Model Predictive Control (MPC) approach to Energy Management Systems (EMSs) for multiple residential microgrids aiming at minimizing the overall costs of each residential microgrid is presented.
Proceedings ArticleDOI
Randomized Model Predictive Control for HVAC Systems
Alessandra Parisio,Damiano Varagnolo,Daniel Risberg,Giorgio Pattarello,Marco Molinari,Karl Henrik Johansson +5 more
TL;DR: This work proposes a randomization technique that finds suboptimal solutions to the generally non-convex stochastic MPC problem and investigates the proposed approach by means of numerical simulations and real tests, and shows its practical effectiveness and computational tractability.
Journal ArticleDOI
Estimating the impacts of demand response by simulating household behaviours under price and CO2 signals
TL;DR: In this paper, the authors developed a simulation model to investigate the joint influence of price and CO2 signals in a demand response (DR) program in the ex ante evaluation, which consists of a Markov chain load model for forecasting the power demands of residential consumers and a scheduling program for providing optimal schedules for smart appliances.
Journal ArticleDOI
Generalised Control-Oriented Modelling Framework for Multi-Energy Systems
TL;DR: A novel generalised modelling framework for multi-energy systems that is particularly well suited to, though not limited to, predictive control applications is presented.
Proceedings ArticleDOI
Robust Optimization of operations in energy hub
TL;DR: Simulation results underline the benefits resulting from the application of the proposed approach using Robust Optimization techniques to an energy hub structure located in Waterloo, Canada.