Overview of voltage control strategies in medium voltage networks with implementation of distributed generation

2011 ◽  
Author(s):  
M. Jacxsens ◽  
B. Meersman ◽  
T.L. Vandoorn ◽  
J.D.M. De Kooning ◽  
L. Vandevelde
Keyword(s):  
Distributed Generation ◽  
Control Strategies ◽  
Voltage Control ◽  
Medium Voltage

scholarly journals Optimal Voltage Control in MV Network with Distributed Generation

Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 469
Author(s):  
Piotr Kacejko ◽  
Paweł Pijarski
Keyword(s):  
Distributed Generation ◽  
High Efficiency ◽  
Traditional Approach ◽  
Control Process ◽  
Voltage Control ◽  
Active Participation ◽  
Voltage Transformer ◽  
Medium Voltage ◽  
Voltage Quality ◽  
Classical Control

The article presents the concept of voltage control in a medium-voltage network, using the classical control of a HV/MV (High Voltage/Medium Voltage) transformer and active participation of distributed generation sources. The proposed solution is based on the results of the optimization process. The objective function is considered as a single-criterion—the voltage quality indicator or value of power losses in the network, and optionally as two-criteria (voltage quality and losses combined, with appropriately selected weight factors). The analysis carried out for random selection of independent variables, using the original heuristic algorithm, indicated a very high efficiency of the proposed control process, compared to the traditional approach. A significant improvement in the voltage quality index and reduction of losses was found, which justifies the advisability of looking for new solutions in the field of voltage control in MV networks, taking into account active participation of distributed generation.

scholarly journals Improving PV Resilience by Dynamic Reconfiguration in Distribution Grids: Problem Complexity and Computation Requirements

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 830
Author(s):  
Filipe F. C. Silva ◽  
Pedro M. S. Carvalho ◽  
Luís A. F. M. Ferreira
Keyword(s):  
Distributed Generation ◽  
Optimal Solution ◽  
Dynamic Reconfiguration ◽  
Scheduling Problem ◽  
Low Carbon ◽  
Distribution Grid ◽  
Medium Voltage ◽  
Classical Computing ◽  
The Impact ◽  
Distribution Grids

The dissemination of low-carbon technologies, such as urban photovoltaic distributed generation, imposes new challenges to the operation of distribution grids. Distributed generation may introduce significant net-load asymmetries between feeders in the course of the day, resulting in higher losses. The dynamic reconfiguration of the grid could mitigate daily losses and be used to minimize or defer the need for network reinforcement. Yet, dynamic reconfiguration has to be carried out in near real-time in order to make use of the most updated load and generation forecast, this way maximizing operational benefits. Given the need to quickly find and update reconfiguration decisions, the computational complexity of the underlying optimal scheduling problem is studied in this paper. The problem is formulated and the impact of sub-optimal solutions is illustrated using a real medium-voltage distribution grid operated under a heavy generation scenario. The complexity of the scheduling problem is discussed to conclude that its optimal solution is infeasible in practical terms if relying upon classical computing. Quantum computing is finally proposed as a way to handle this kind of problem in the future.

scholarly journals Proposal of an Adaptive Neurofuzzy System to Control Flow Power in Distributed Generation Systems

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-16 ◽  
Author(s):  
Helbert Eduardo Espitia ◽  
Iván Machón-González ◽  
Hilario López-García ◽  
Guzmán Díaz
Keyword(s):  
Statistical Analysis ◽  
Distributed Generation ◽  
Distribution System ◽  
Voltage Control ◽  
Control Flow ◽  
The Other ◽  
Charge Variation ◽  
Flow Power ◽  
Dynamics Identification ◽  
Neurofuzzy Systems

Systems of distributed generation have shown to be a remarkable alternative to a rational use of energy. Nevertheless, the proper functioning of them still manifests a range of challenges, including both the adequate energy dispatch depending on the variability of consumption and the interaction between generators. This paper describes the implementation of an adaptive neurofuzzy system for voltage control, regarding the changes observed in the consumption within the distribution system. The proposed design employs two neurofuzzy systems, one for the plant dynamics identification and the other for control purposes. This focus optimizes the controller using the model achieved through the identification of the plant, whose changes are produced by charge variation; consequently, this process is adaptively performed. The results show the performance of the adaptive neurofuzzy system via statistical analysis.

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