A Robust Mixed-Integer Programing Model for Reconfiguration of Distribution Feeders Under Uncertain and Variable Loads Considering Capacitor Banks, Voltage Regulators, and Protective Relays

Author(s):  
Meisam Mahdavi ◽  
H. Haes Alhelou ◽  
Pierluigi Siano ◽  
Vincenzo Loia
2020 ◽  
Author(s):  
Andrés Valdepeña Delgado

Power distribution systems are experiencing a fast transformation from simple one-way radial feeders to complex systems with multiple sources and bidirectional power flows. The rapid increase of Distributed Generation (DG) connected to the distribution system over the last decade, especially solar photovoltaic (PV), has been the key element to this transformation. The variable nature of PV-based DG has increased the complexity of voltage regulation in distribution systems. Electric Utilities are facing an increasing number of voltage issues in distribution systems with high penetration of DGs, leading customers to experience voltage levels outside of range A of the ANSI C84.1 standard. Electric Utilities have to expend resources, both human and economic, to mitigate the voltage issues caused by the interconnection of DG. The economic impact of voltage issues can be considerable in some cases. Conventional methods to mitigate voltage issues in distribution systems, such as the addition of voltage regulators and capacitor banks, could be ineffective in mitigating localized voltage issues caused by high levels of DG penetration. Other mitigation options, such as increasing the conductor size and the operating voltage of the feeder, are expensive. There is a clear need in the industry to locally solve voltage issues economically. In this dissertation, a new device, a Residential Static Volt-Ampere Reactive Compensator (RSVC), is proposed. The RSVC is used to mitigate low and high voltage issues by deploying them in a feeder with a high DG penetration level. This dissertation will investigate the interaction between solar inverters, voltage regulators and capacitor banks with the proposed RSVC. In order to reduce the number of buses to be analysed, the use of loss sensitivity factors will determine the candidate buses to host a RSVC. The results of this dissertation show that the use of RSVCs is able to mitigate low and high voltage conditions. Simulation results show that the RSVCs are able to control the voltage by absorbing and injecting reactive power according to the voltage seen at their terminals. Similar commercially available devices are not able to handle the injection and absorption of reactive power and are limited to handle either injection of reactive power or absorption of reactive power. The most common devices provide the capability of injecting reactive power.


Ingeniería ◽  
2020 ◽  
Vol 25 (3) ◽  
pp. 334-354
Author(s):  
Luis Alfonso Gallego Pareja ◽  
Jesus Maria Lopez Lezama ◽  
Oscar Gomez Carmona

Context: With the advent of the smart grid paradigm, electrical distribution network (EDN) operators are making efforts to modernize their power grids through the optimal implementation of distributed generators (DGs) and other devices such as capacitors (CAs) and voltage regulators (VRs). The optimal allocation of such devices is a challenging task involving discrete and integer decision variables. Method: This paper presents an approach for the optimal placement of CAs, VRs and DGs in EDNs. The distinctive feature of the proposed model is the fact that it can be used to optimize the allocation of all of these elements together, in pairs, or separately. The optimal implementation of these elements is formulated as a mixed integer nonlinear programming (MINLP) problem, and it is solved by means of a specialized genetic algorithm (SGA). Results: The proposed methodology was tested on the IEEE 69-bus test system. The results were compared with previous works from the specialized literature, showing the effectiveness and robustness of the model. Conclusions: It was found that the appropriate allocation of CAs, VRs, and DGs results in a significant power loss reduction. It was also found that the proposed model is faster than other techniques proposed in the specialized literature. Acknowledgements: The authors gratefully acknowledge the support from the Colombia Científica program, within the framework of the Ecosistéma Científico (Contract No. FP44842- 218-2018). The authors also acknowledge the support of the State University of Londrina and Universidad Tecnológica de Pereira (UTP).


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