Next Article in Journal
Influence of Various Irradiance Models and Their Combination on Simulation Results of Photovoltaic Systems
Next Article in Special Issue
Engineering Support for Handling Controller Conflicts in Energy Storage Systems Applications
Previous Article in Journal
Field-Weakening Performance Improvement of the Yokeless and Segmented Armature Axial Flux Motor for Electric Vehicles
Previous Article in Special Issue
Automated Energy Scheduling Algorithms for Residential Demand Response Systems
Article Menu
Issue 10 (October) cover image

Export Article

Open AccessArticle
Energies 2017, 10(10), 1488; doi:10.3390/en10101488

PV Hosting Capacity Analysis and Enhancement Using High Resolution Stochastic Modeling

Departamento de Arquitectura de Computadores, Electrónica y Tecnología Electrónica, Escuela Politécnica Superior, Universidad de Córdoba, Campus de Rabanales, Edificio Leonardo da Vinci, E-14071 Córdoba, Spain
Power Electrical and Electronic Systems Research Group, Escuela de Ingenierías Industriales, Universidad de Extremadura, Avda. de Elvas, s/n, E-06006 Badajoz, Spain
Author to whom correspondence should be addressed.
Academic Editor: Pierluigi Siano
Received: 30 August 2017 / Revised: 19 September 2017 / Accepted: 20 September 2017 / Published: 26 September 2017
(This article belongs to the Special Issue Innovative Methods for Smart Grids Planning and Management)
View Full-Text   |   Download PDF [16059 KB, uploaded 26 September 2017]   |  


Reduction of CO2 emissions is a main target in the future smart grid. This goal is boosting the installation of renewable energy resources (RES), as well as a major consumer engagement that seeks for a more efficient utilization of these resources toward the figure of ‘prosumers’. Nevertheless, these resources present an intermittent nature, which requires the presence of an energy storage system and an energy management system (EMS) to ensure an uninterrupted power supply. Moreover, network-related issues might arise due to the increasing power of renewable resources installed in the grid, the storage systems also being capable of contributing to the network stability. However, to assess these future scenarios and test the control strategies, a simulation system is needed. The aim of this paper is to analyze the interaction between residential consumers with high penetration of PV generation and distributed storage and the grid by means of a high temporal resolution simulation scenario based on a stochastic residential load model and PV production records. Results of the model are presented for different PV power rates and storage capacities, as well as a two-level charging strategy as a mechanism for increasing the hosting capacity (HC) of the network. View Full-Text
Keywords: stochastic load modeling; solar power generation; energy storage; hosting capacity; energy management system stochastic load modeling; solar power generation; energy storage; hosting capacity; energy management system

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Palacios-Garcia, E.J.; Moreno-Muñoz, A.; Santiago, I.; Moreno-Garcia, I.M.; Milanés-Montero, M.I. PV Hosting Capacity Analysis and Enhancement Using High Resolution Stochastic Modeling. Energies 2017, 10, 1488.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Energies EISSN 1996-1073 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top