A Model Predictive Control Approach to Microgrid Operation Optimization
By Alessandra Parisio, Evangelos Rikos, Luigi Glielmo. IEEE Transactions on Control Systems Technology, 2014
816 citations recorded by the source corpus.
Subfields: Control and Systems Engineering, Electrical and Electronic Engineering
View Paper: https://www.semanticscholar.org/paper/8cd138cef93f96208ff9e48b3078e96fed004315
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Control and Systems Engineering
- Oliver Sawodny
- Julia Sachs
- Dipti Srinivasan
- Martin Braun
- Stefan Tenbohlen
- Thomas Reindl
- Mohsen Nemati
- Ce Shang
In Electrical and Electronic Engineering
- Oliver Sawodny
- Julia Sachs
- Dipti Srinivasan
- Martin Braun
- Stefan Tenbohlen
- Thomas Reindl
- Mohsen Nemati
- Ce Shang
Citations in the corpus
- A Two-Stage Model Predictive Control Strategy for Economic Diesel-PV-Battery Island Microgrid Operation in Rural Areas (2016, methodology): “The formulation of a linear mixed integer optimization problem within the MPC for the optimal operation of energy systems comprising renewables, battery and diesel generators in [13] is extended in [14], [15] with a forecast algorithm and evaluated using experiments.”
- Optimization of unit commitment and economic dispatch in microgrids based on genetic algorithm and mixed integer linear programming (2018, methodology): “[17] have introduced an optimizer for the EMS based on the MILP, which considers UC, ED of the system.”
- Economic and Environmental Generation and Voyage Scheduling of All-Electric Ships (2016, methodology): “Different modelling methods, which expand the control variables to include the charge and discharge power flow [26], [27], or which introduce the mixed logical dynamical system to transform the “if – else” logic [38], will increase the control effort.”
- A Two-Layer Energy Management System for Microgrids With Hybrid Energy Storage Considering Degradation Costs (2018, methodology): “However, the degradation cost of ESS was either neglected or modeled on a very rough and general basis in [16]–[18].”
- Stochastic model predictive control for economic/environmental operation management of microgrids: An experimental case study (2016, background): “See [60,61] for an outline of the forecasting algorithm and parameters estimation, such as investment and operating costs, minimum up and down times of the DG units, efficiencies, storage limits.”
- Control Techniques in AC, DC, and Hybrid AC–DC Microgrid: A Review (2018, neutral): “straints as well [62]–[64].”