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(searched for: doi:10.1155/2015/493560)
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Oladepo Olatunde, , Pauzi Abdullah, Hasimah Abdul Rahman
Published: 1 October 2020
Journal of Energy Storage, Volume 31; doi:10.1016/j.est.2020.101673

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Published: 1 August 2019
Energies, Volume 12; doi:10.3390/en12152964

Abstract:
Photovoltaic distributed generation (PVDG) has seen tremendous growth in recent years, especially in the residential sector. Among other concerns, the voltage rise in AC networks is considered the most limiting factor in achieving increased PV penetration levels. A steady-state impact study is performed on a CIGRE low-voltage (LV) residential network. This paper compares six techniques to increase the PV penetration limit in the LV residential network, namely single-phase penetration (SPP), Distribution Scheme 1 (DS1), Distribution Scheme 2 (DS2), alternate phase penetration (APP), offline tap adjustment (OTA) and switched on-load tap adjustment (SOLTA). PSCAD software is used for this study. The best results are obtained for the DS2-SOLTA case that gives the minimum voltage magnitude and voltage unbalance in the system. The steady-state results are validated by a dynamic data study using measured solar irradiance and residential load data. A novel approach is also proposed for calculating the worst day from the data set. The obtained results verify the effectiveness of the proposed approach.
2016 19th International Conference on Network-Based Information Systems (NBiS) pp 196-203; doi:10.1109/nbis.2016.79

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Giorgio Graditi, Roberto Ciavarella, Maria Valenti, Gabriella Ferruzzi, Gaetano Zizzo
2016 International Symposium on Power Electronics, Electrical Drives, Automation and Motion (SPEEDAM) pp 295-299; doi:10.1109/speedam.2016.7526033

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, Yanjun Fang
Mathematical Problems in Engineering, Volume 2016, pp 1-14; doi:10.1155/2016/2167153

Abstract:
The environmental/economic dynamic scheduling for microgrids (MGs) is a complex multiobjective optimization problem, which usually has dynamic system parameters and constraints. In this paper, a biobjective optimization model of MG scheduling is established. And various types of microsources (like the conventional sources, various types of renewable sources, etc.), electricity markets, and dynamic constraints are considered. A recently proposed MOEA/D-M2M framework is improved (I-MOEA/D-M2M) to solve the real-world MG scheduling problems. In order to deal with the constraints, the processes of solutions sorting and selecting in the original MOEA/D-M2M are revised. In addition, a self-adaptive decomposition strategy and a modified allocation method of individuals are introduced to enhance the capability of dealing with uncertainties, as well as reduce unnecessary computational work in practice and meet the time requirements for the dynamic optimization tasks. Thereafter, the proposed I-MOEA/D-M2M is applied to the independent MG scheduling problems, taking into account the load demand variation and the electricity price changes. The simulation results by MATLAB show that the proposed method can achieve better distributed fronts in much less running time than the typical multiobjective evolutionary algorithms (MOEAs) like the improved strength Pareto evolutionary algorithm (SPEA2) and the nondominated sorting genetic algorithm II (NSGAII). Finally, I-MOEA/D-M2M is used to solve a 24-hour MG dynamic operation scheduling problem and obtains satisfactory results.
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