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This research work aims to provide detailed feasibility, a techno-economic evaluation, and energy management of stand-alone hybrid photovoltaic-diesel-battery (PV/DG/B) system. The proposed system can be applied to supply a specific load that is far away from the utility grid (UG) connection, and it is located in Minya city, Egypt, as a real case study. The daily required desalinated water is 250 m 3. The total brackish water demands are 350-500 m 3 and 250-300 m 3 of water in summer and winter seasons, respectively. Two different sizes of reverse osmosis (RO) units; RO-250 and RO-500, two energy control dispatch strategies; load following (LF) and cycle charging (CC); two sizes of DG; 5 kW and 10 kW are considered in the case study. The cost of energy, renewable fraction, environmental impact, and breakeven grid extension distance are the main criteria that have been considered to determine the optimal size of PV/DG/B to supply the load demand. HOMER ® software is used to perform the simulation and optimization. For this case study, the minimum cost of energy and the minimum total present cost are 0.074 $/kWh and 207676 $, respectively. This is achieved by using a RO-500 unit and a LF dispatch control strategy. The related sizes to the best option of PV/DG/B are 120 kW PV array, 10 kW DG, 64 batteries, and 50 kW converter. A comparison with grid extension and installing stand-alone diesel generation is also carried out. The results of comparison have confirmed that the grid connection is better than all considered options using the RO-250 unit. However, for the RO-500 unit, all options of hybrid PV/DG/B are more economically feasible compared with grid connection, and the best cost-effective option is the one including LF strategy with 10 kW DG. Stand-alone diesel generator produces 119110 kg/year and 117677 kg/year of CO2 respectively for RO-250 and RO-500.

In this paper, a Modified Farmland Fertility Optimization algorithm (MFFA) has been presented for optimal sizing of a grid connected hybrid system including photovoltaic (PV), wind turbines and fuel cell (FC). The system is optimal designed for providing a clean, reliable and affordable energy by adopting hybrid power systems. This system is very important for countries looking to achieve their sustainable development goals. MFFA is proposed in order to reduce the processing implementation time. The optimization method depends on the high reliability of the hybrid power supply, small fluctuation in the injected energy to the grid and high utilization of the wind and solar complementary characteristics. Moreover, MFFA is applied to minimize the cost of energy while satisfying the operational constraints. A real case study of a hybrid power system for Ataka region in Egypt is introduced to evaluate the performance of the proposed optimization method. Moreover, a comprehensive comparison between the proposed MFFA optimization technique and the conventional Farmland Fertility Algorithm (FFA) has been presented to validate the proposed MFFA.

It is well known that compact arrays introduce spatial channel correlation, antenna coupling, superdirectivity and noise correlation. While these effects have been thoroughly investigated for point to point MIMO, only isolated results are available on the effect of such phenomena on performance of relaying systems. This paper tries to fill part of this void. Specifically we study the impact of lossless and lossy compact antenna arrays on multiuser amplify and forward (AF) relaying in the presence of different noise sources. We optimize the gain allocation for sum rate maximization under a dissipated power constraint. For compact arrays this constraint is more relevant than the commonly used radiated power constraint. We provide an extensive insight-oriented discussion of our results, some of which may appear counterintuitive at first glance. We show that for compact MIMO relaying the standard model, considering only channel correlation but ignoring antenna coupling and noise correlation, is insufficient and may lead to a wrong system characterization.

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