Developing a Model Predictive Control-Based Algorithm for Energy Management System of the Catenary-Based Electric Truck

2016 ◽  
Author(s):  
Khashayar Olia ◽  
Masood Shahverdi ◽  
Michael Mazzola ◽  
Abdelwahed Sherif
Keyword(s):  
Model Predictive Control ◽  
Energy Management ◽  
Predictive Control ◽  
Management System ◽  
Energy Management System

scholarly journals Phase Balancing Home Energy Management System Using Model Predictive Control

Energies ◽  
2018 ◽  
Vol 11 (12) ◽  
pp. 3323 ◽  
Author(s):  
Bharath Rao ◽  
Friederich Kupzog ◽  
Martin Kozek
Keyword(s):  
Model Predictive Control ◽  
Energy Management ◽  
Predictive Control ◽  
Management System ◽  
Mixed Integer ◽  
Energy Management System ◽  
Integer Quadratic Programming ◽  
Three Phase ◽  
Home Energy Management ◽  
Home Energy Management System

Most typical distribution networks are unbalanced due to unequal loading on each of the three phases and untransposed lines. In this paper, models and methods which can handle three-phase unbalanced scenarios are developed. The authors present a novel three-phase home energy management system to control both active and reactive power to provide per-phase optimization. Simplified single-phase algorithms are not sufficient to capture all the complexities a three-phase unbalance system poses. Distributed generators such as photo-voltaic systems, wind generators, and loads such as household electric and thermal demand connected to these networks directly depend on external factors such as weather, ambient temperature, and irradiation. They are also time dependent, containing daily, weekly, and seasonal cycles. Economic and phase-balanced operation of such generators and loads is very important to improve energy efficiency and maximize benefit while respecting consumer needs. Since homes and buildings are expected to consume a large share of electrical energy of a country, they are the ideal candidate to help solve these issues. The method developed will include typical distributed generation, loads, and various smart home models which were constructed using realistic models representing typical homes in Austria. A control scheme is provided which uses model predictive control with multi-objective mixed-integer quadratic programming to maximize self-consumption, user comfort and grid support.

Energy management system for PV-battery microgrid based on model predictive control

2019 ◽  
Vol 15 (1) ◽  
pp. 20 ◽  
Author(s):  
M. Reyasudin Basir Khan ◽  
Jagadeesh Pasupuleti ◽  
Jabbar Al-Fattah ◽  
Mehrdad Tahmasebi
Keyword(s):  
Model Predictive Control ◽  
Energy Management ◽  
Predictive Control ◽  
Management System ◽  
Renewable Energy Sources ◽  
Storage System ◽  
Renewable Resource ◽  
Energy Management System ◽  
Solar Photovoltaic ◽  
Multiple Sources

<p>There had been increase of the usage of renewable energy sources to supply electricity in remote areas. However, microgrid consists of renewable sources such as solar Photovoltaic (PV) poses challenges for a reliable energy supply due to its intermittent nature. This paper presents a microgrid model with Energy Management System based on Model Predictive Control (MPC). The microgrid comprises of PV, and battery storage system. The goal of the EMS is to deliver a reliable and optimal generation from multiple sources in the microgrid. Moreover, the MPC will also provide controls for the battery charging for a smooth PV output. The model simulated based on actual load profile and renewable resource such as solar radiation. Several disturbances such as variation of load, generation and PV shading has been simulated to measure the performance of the EMS. The results illustrate the system ability to exhibits robust performance in variety of conditions.</p>

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