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  • 1.
    Duvnjak Zarkovic, Sanja
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Electromagnetic Engineering.
    Hilber, Patrik
    KTH, School of Electrical Engineering and Computer Science (EECS), Electromagnetic Engineering.
    Shayesteh, Ebrahim
    KTH, School of Electrical Engineering and Computer Science (EECS), Electromagnetic Engineering.
    On the Security of Electricity Supply in Power Distribution Systems2018In: 2018 IEEE International Conference on Probabilistic Methods Applied to Power Systems (PMAPS), IEEE conference proceedings, 2018, article id 8440489Conference paper (Refereed)
    Abstract [en]

    Security of electricity supply has become a fundamental requirement for modern societies. However, attempts to define and evaluate security of supply have differed from one another. This paper reviews relevant studies in order to give a comprehensive explanation of the security of supply concept. The paper includes theory, assessment, methodology, regulations, data and practical issues associated with the security of supply and power system reliability. Special focus is given to the methodologies used for improving the reliability and security of supply in power distribution systems.

  • 2.
    Duvnjak Zarkovic, Sanja
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Electromagnetic Engineering.
    Stankovic, Stefan
    KTH, School of Electrical Engineering and Computer Science (EECS), Electric Power and Energy Systems.
    Shayesteh, Ebrahim
    KTH, School of Electrical Engineering and Computer Science (EECS), Electromagnetic Engineering.
    Hilber, Patrik
    KTH, School of Electrical Engineering and Computer Science (EECS), Electromagnetic Engineering.
    Reliability improvement of distribution system through distribution system planning: MILP vs. GA2019In: 2019 IEEE Milan PowerTech, 2019Conference paper (Refereed)
    Abstract [en]

    Distribution system planning (DSP) is very important because it can result in reliability enhancement and large cost savings for both utilities and consumers. DSP is a complex nonlinear problem, which can be solved with different optimization methods. This paper compares two such optimization methods, conventional (mixed-integer linear programming - MILP) and meta-heuristic (genetic algorithm - GA), applied to the DSP problem: construction of feeders in distribution power system from scratch. The main objective of DSP is to minimize the total cost, where both the investment and operational outage costs are considered, while the reliability of the whole system is maximized. DSP problem is applied to an actual distribution system. Solution methods are outlined, and computational results show that even though GA gives reasonably good results in faster computation time, MILP provides a better optimal solution with simpler implementation.

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