Prediction of Latvian Electrical Power System for Reliability Evaluation Including Wind Energy
            
            2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe)
            2017
            
        
                Aleksejs Soboļevskis,
        
                Inga Zicmane
        
    
            
            
            Within the last two decades, increase in electricity demand and environmental concern resulted in fast growth of power production from renewable sources. Wind power is one of the most efficient alternatives. Therefore, the issue on integration of a new renewable power plant into the existing electrical power system(EPS) is the topical terms of stability.
The goal of this paper is to ensure approach for finding of EPS options, which are most weak to outer impacts, identify their relations with the EPS parameters, use this data for enhancement of power system behavioural properties. Thus, accessibility of data on the location of weak spot allows identify and control nodes, in which the biggest oscillations of operational parameters are observed due to perturbations in the network.
            
            
            
                Keywords
                Power system control; power system simulation; power system stability; power system protection.
            
            
                DOI
                10.1109/EEEIC.2017.7977400
            
            
                Hyperlink
                http://ieeexplore.ieee.org/document/7977400/
            
            
            Soboļevskis, A., Zicmane, I. Prediction of Latvian Electrical Power System for Reliability Evaluation Including Wind Energy. In: 2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe), Italy, Milan, 6-9 June, 2017. Piscataway, NJ: IEEE, 2017, pp.1-5. ISBN 978-1-5386-3918-4. e-ISBN 978-1-5386-3917-7. Available from: doi:10.1109/EEEIC.2017.7977400
            
                Publication language
                English (en)