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2 Journal of Power Technologies

2 2017

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Stochastic risk and reliability assessments of energy management system in grid of microgrids under uncertainty

Nikmehr N., Najafi-Ravadanegh S.

Journal of Power Technologies

2017

Vol. 97, nr 3

179--189

As various renewable energy resources (RERs) are exploited within microgrids (MGs), some important challenges have arisen as regards coping with generation fluctuations. This paper proposes a probabilistic method aimed at achieving optimal coordinated operation in a grid of microgrids under uncertainties of RERs and variable load demand. In the supposed structure based on networked microgrids (NMGs), a two-level strategy is required for guaranteeing efficient coordination between the MGs and distribution network operator (DNO). Another contribution of the paper deals with the flexibility of NMGs in improving the reliability of the whole system. Additionally, the value at risk (VaR) calculations for output results are carried out for different confidence levels with two important methods. In sum, the aim of the paper is to minimize total energy costs considering the environmental effects. To achieve this purpose, the Imperialist Competitive Algorithm (ICA) as a heuristic algorithm is applied to solve the optimal power dispatch problem and the obtained results are compared using the Monte Carlo Simulation (MCS) method. As the input data are modeled under uncertainties, the output results are described with probability distribution function (PDF).

Incorporating DC-DC boost converters in power flow studies

Feyzi H., Gholizadeh-Roshanagh R., Sabahi M., Najafi-Ravadanegh S.

Journal of Power Technologies

2017

Vol. 97, nr 1

28--34

Power electronic interfaces (PEI) play an important role in future power systems. From planning and operation perspectives, there is a need to model PEIs for power flow applications. In this paper, precise modeling of a DC-DC boost converter for load flow analysis is presented, which can be generalized for other kinds of PEIs. As an application, the presented model is employed for uncertainty analysis of systems, considering uncertainty in wind power generation. The simulations are performed on a wind farm DC distribution network. The results demonstrate the robustness of the presented load flow algorithm.