Data-driven probabilistic power flow analysis for a distribution system with Renewable Energy sources using Monte Carlo Simulation

Author(s):  
Gonzalo E. Constante-Flores ◽  
Mahesh Illindala
2021 ◽  
Vol 8 ◽  
Author(s):  
E. K. Hussain ◽  
Philipp R. Thies ◽  
Jon Hardwick ◽  
Peter M. Connor ◽  
Mohammad Abusara

This paper presents a methodology for the reliability and power flow analysis of islands or off-grid power networks for situations of scarce data and information. It offers a new and pragmatic approach to derive the required power network information, including the power cable parameters and the load at each power node. The paper aims to present the developed methodology, and to illustrate its application, using Ushant Island as a case study. The assessment of the current power network status and the reliability analysis are presented. Grid performance parameters are further compared for conventional diesel generator operation and renewable energy generation scenarios, demonstrating the advantages of replacing the existing diesel units with renewable energy sources in terms of system reliability. The analysis shows that by introducing renewable energy systems to the island’s grid, the reliability of the grid increases by up to 50% and cable capacity usage reduces by up to 30%. Furthermore, this work suggests that it would not be necessary to modify the grid cables when substituting the diesel generator. The paper will be of interest to network planners, community stakeholders, project developers and decision-makers concerned with renewable energy investment on islands and in remote rural areas.


2013 ◽  
Vol 768 ◽  
pp. 298-300
Author(s):  
P. Sivakumar ◽  
D. Poornima

For growing of electrical demand in the modern world energy requirement is tremendously increased day to day power market. Nowadays the non-conventional energy sources are utilized to meet out the current power demand through PV, wind and other non-conventional resources etc. In this concern the energy drawn from the other non-conventional energy sources is highly variable due to the nature of uncertainties. Hence the optimal load dispatch of the power is highly difficult, one of the attempts is to eradicate this difficulty by adding developed uncertainty model of PV and wind sourced power generation in power system network. Uncertainties of PV irradiation and wind speed models are developed by using generic probabilistic approach. By using this hybrid system, instantaneous power flow of a DG system is obtained through Monte carlo simulation (MCS) in the MATLAB/SIMULINK packages. Enhancement of optimal power flow (opf) and system reliability due to addition of uncertainty variables in DG sourced power systems.Index TermsLoad flow analysis, Monte Carlo simulation (MCS), integration of Photovoltaic generator and wind (PVG and WEG).


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