Intelligent AC Distribution Panel for real-time load analysis and control in small-scale power grids with distributed generation

Author(s):  
David K.W. Li ◽  
Shahab Poshtkouhi ◽  
Olivier Trescases ◽  
Ray Orr ◽  
Ben Bacque
Sensors ◽  
2018 ◽  
Vol 19 (1) ◽  
pp. 60 ◽  
Author(s):  
Cesar Guzmán ◽  
José Carrera ◽  
Héctor Durán ◽  
Javier Berumen ◽  
Arturo Ortiz ◽  
...  

Virtual sensing is crucial in order to provide feasible and economical alternatives when physical measuring instruments are not available. Developing model-based virtual sensors to calculate real-time information at each targeted location is a complex endeavor in terms of sensing technology. This paper proposes a new approach for model-based virtual sensor development using computational fluid dynamics (CFD) and control. Its main objective is to develop a three-dimensional (3D) real-time simulator using virtual sensors to monitor the temperature in a greenhouse. To conduct this study, a small-scale greenhouse was designed, modeled, and fabricated. The controller was based on the convection heat transfer equation under specific assumptions and conditions. To determine the temperature distribution in the greenhouse, a CFD analysis was conducted. Only one well-calibrated and controlled physical sensor (temperature reference) was enough for the CFD analysis. After processing the result that was obtained from the real sensor output, each virtual sensor had learned the associative transfer function that estimated the output from given input data, resulting in a 3D real-time simulator. This study has demonstrated, for the first time, that CFD analysis and a control strategy can be combined to obtain system models for monitoring the temperature in greenhouses. These findings suggest that, generally, virtual sensing can be applied in large greenhouses for monitoring the temperature using a 3D real-time simulator.


2021 ◽  
Vol 317 ◽  
pp. 04032
Author(s):  
Denis ◽  
Enda Wista Sinuraya ◽  
Jaka Windarta ◽  
Yosua Alvin Adi Soetrisno ◽  
Kurnianto Fernanda

The increase in demand for electrical energy is increasing rapidly, in line with economic growth. In developing the electricity system, electrical energy service providers must provide electrical energy according to demand with good quality. The generation of conventional electric energy systems that use fossil fuels faces depleting fossil fuel sources, poor efficiency, and environmental pollution. This technology is known as Distributed Generation (DG). Distributed Generation (DG) or Micro Grid (MG) is a small-scale power plant located close to the load. The use of distributed generators can improve the entire system's efficiency, reduce transmission losses, reduce pollution, and ensure the continuity of the distribution of electrical energy. However, the drastic increase in the use of DG causes problems in the form of voltage and frequency stability which will be disturbed due to rapid changes in the generation and loading rates. If this is left unchecked, it can harm system security and reliability. A proper control strategy will restore system stability in the event of an imbalance.


Energies ◽  
2020 ◽  
Vol 13 (20) ◽  
pp. 5315
Author(s):  
Rade Čađenović ◽  
Damir Jakus

High penetration of small-scale distributed energy sources into the distribution network increase negative impacts related to power quality causing adverse conditions. This paper presents a mathematical model that maximizes distribution network hosting capacity through optimal distributed generation capacity allocation and control and grid reconfiguration. In addition to this, the model includes on-load tap changer control for stabilization of grid voltage conditions primarily in grid operating conditions related to voltage rise problems, which can limit grid hosting capacity. Moreover, the objective function allows the possibility of energy transfer between distribution and transmission grids. The proposed model considers alternative grid connection points for distributed generation and determines optimal connection points as well as install capacity while considering network operating limits. The model is cast as a multiperiod second-order cone linear program and involves aspects of active power management. The model is tested on a modified IEEE 33 bus test network.


Author(s):  
R. Rajesh ◽  
R. Droopad ◽  
C. H. Kuo ◽  
R. W. Carpenter ◽  
G. N. Maracas

Knowledge of material pseudodielectric functions at MBE growth temperatures is essential for achieving in-situ, real time growth control. This allows us to accurately monitor and control thicknesses of the layers during growth. Undesired effusion cell temperature fluctuations during growth can thus be compensated for in real-time by spectroscopic ellipsometry. The accuracy in determining pseudodielectric functions is increased if one does not require applying a structure model to correct for the presence of an unknown surface layer such as a native oxide. Performing these measurements in an MBE reactor on as-grown material gives us this advantage. Thus, a simple three phase model (vacuum/thin film/substrate) can be used to obtain thin film data without uncertainties arising from a surface oxide layer of unknown composition and temperature dependence.In this study, we obtain the pseudodielectric functions of MBE-grown AlAs from growth temperature (650°C) to room temperature (30°C). The profile of the wavelength-dependent function from the ellipsometry data indicated a rough surface after growth of 0.5 μm of AlAs at a substrate temperature of 600°C, which is typical for MBE-growth of GaAs.


1994 ◽  
Vol 33 (01) ◽  
pp. 60-63 ◽  
Author(s):  
E. J. Manders ◽  
D. P. Lindstrom ◽  
B. M. Dawant

Abstract:On-line intelligent monitoring, diagnosis, and control of dynamic systems such as patients in intensive care units necessitates the context-dependent acquisition, processing, analysis, and interpretation of large amounts of possibly noisy and incomplete data. The dynamic nature of the process also requires a continuous evaluation and adaptation of the monitoring strategy to respond to changes both in the monitored patient and in the monitoring equipment. Moreover, real-time constraints may imply data losses, the importance of which has to be minimized. This paper presents a computer architecture designed to accomplish these tasks. Its main components are a model and a data abstraction module. The model provides the system with a monitoring context related to the patient status. The data abstraction module relies on that information to adapt the monitoring strategy and provide the model with the necessary information. This paper focuses on the data abstraction module and its interaction with the model.


2007 ◽  
Vol 158 (8) ◽  
pp. 235-242 ◽  
Author(s):  
Hans Rudolf Heinimann

The term «precision forestry» was first introduced and discussed at a conference in 2001. The aims of this paper are to explore the scientific roots of the precision concept, define «precision forestry», and sketch the challenges that the implementation of this new concept may present to practitioners, educators, and researchers. The term «precision» does not mean accuracy on a small scale, but instead refers to the concurrent coordination and control of processes at spatial scales between 1 m and 100 km. Precision strives for an automatic control of processes. Precision land use differs from precision engineering by the requirements of gathering,storing and managing spatio-temporal variability of site and vegetation parameters. Practitioners will be facing the challenge of designing holistic, standardized business processes that are valid for whole networks of firms,and that follow available standards (e.g., SCOR, WoodX). There is a need to educate and train forestry professionals in the areas of business process re-engineering, computer supported management of business transactions,methods of remote sensing, sensor technology and control theory. Researchers will face the challenge of integrating plant physiology, soil physics and production sciences and solving the supply chain coordination problem (SCCP).


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