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Sizing of hybrid energy systems is primarily determined based on either cost criterion or produced pollution criterion. Optimization of a hybrid energy system for a typical house in Tunisia is investigated using particle swarm optimization (PSO). To the best of our knowledge, PSO algorithm has not been used for PV/batteries bank/diesel generator energy system optimization. Different parameters—namely, cost, required maintenance of the parts, lifetime of each components, and pollution produced by the diesel generator—are investigated simultaneously as objectives for optimal design of the hybrid system. Different designs are considered for the hybrid system where CO2 emission is measured and system total cost is calculated. It is crucial to choose proper ranges of the parameters used in the PSO algorithm to achieve stable and global optimal solution. It is found that the cost of the system optimized using minimum pollution criterion has about 0.3% extra overall cost compared to the system optimized using minimum overall system cost criterion. New and simple method is proposed in this work to select the range of the PV panels' number to achieve optimal solution of PSO algorithm. This method is based on calculating the number of PV panels under different conditions of solar radiation and load values. The considered conditions are maximum solar radiation, 50% of maximum radiation, and the radiation at 9:00 AM for maximum and minimum load values. The choice of these conditions was arbitrary and contemplated to cover a wide range of different possible solar radiation in the year. © 2018 American Institute of Chemical Engineers Environ Prog, 38:e13055, 2019

Photovoltaic based reverse osmosis desalination systems (PV/RO) present an effective method of water desalination especially in remote areas. The increase of the feed water temperature leads to an amelioration of the plant performances. Photovoltaic Thermal Collector (PV/T) represents an ideal power source as it provides both electric and thermal energies for the reverse osmosis process. Nevertheless, PV/T based RO plants should be controlled in order to solve operation problems related to electrical efficiency, reverse osmosis membrane, produced water and the rejected salts. This paper suggests a fuzzy logic controller for the flow rate of the circulating fluid into the PV/T collectors so as to ameliorate the system performances. The designed controller has improved the PV/T field electrical efficiency and preserved the reverse osmosis membrane which upgrades the system productivity. LABVIEW software is used to simulate the controlled system and validate the effectiveness of the controller.

A study of some MPPT algorithms and type (central or distributed) for an off-grid photovoltaic installation is presented. First, the efficiency of using MPPT algorithms in a specific application (water pumping) has been proved. Then, some widely used MPPT algorithms (Table Look-up Neurofuzzy, Incremental Conductance and Perturb and Observe) are compared, independently on the application. Their performances are evaluated using measured data from the target area, and compared in similar conditions, thanks to simulations. Since the P&O algorithm is easy to implement, and it shows a fast dynamic performance, although the non-linearity of the photovoltaic panel' model, it is selected to track the MPP and is successfully tested on a detailed model of a Buck converter, using PowerSim. Then, the power efficiency comparison between the central and distributed MPPT is discussed.

A novel algorithm is proposed to control the overall energy produced by a photovoltaic/battery bank/diesel generator renewable energy system. A renewable energy system is used to supply an off-grid connected house in Sfax, Tunisia. The algorithm computes recurrently the battery depth of discharge and diesel consumption of the diesel generator and then forecasts the photovoltaic subsystem output power every two minutes ahead. The estimated power is computed using an auto-regressive moving average model associated with a Kalman filter. During each calculation loop, hybrid system energy scheduling is accomplished considering criteria that guarantee the maximum use of generated renewable energy, minimum diesel generator operational time, and full-load need satisfaction during the whole day. Numerical simulations for two typical sunny and cloudy days in Sfax, Tunisia, are conducted in order to validate the algorithm and to compare the performance of managed system behavior with that of a standard unmanaged system. It is shown that the proposed energy management system could save fuel consumption by as much as 11.27% in the sunny day and 9.17% in the cloudy day.

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The energy demand in remote area cannot be satisfied unless renewable energy based plants are locally installed. In order to be efficient, such projects should be sized on the basis of maximizing the renewable energies exploitation and meeting the consumer needs. The aim of this work is to provide an algorithm-based calculation of the optimum sizing of a standalone hybrid plant composed of a wind generator, a photovoltaic panel, a lead acid-battery bank, and a water tank. The strategy consists of evaluating the renewable potentials (solar and wind). Obtained results are entered as inputs to established generators models in order to estimate the renewable generations. The developed optimal sizing algorithm which is based on iterative approach, computes plant components sizes for which load profile meet estimated renewable generations. The approach validation is conducted for A PV/Wind/Battery based farm located in Sfax, Tunisia. Obtained results proved that the energetic need is covered and only about 4% of the generated energy is not used. Also a cost investigation confirmed that the plant becomes profitable ten years after installation.Article History: Received June 24th 2017; Received in revised form September 26th 2017; Accepted Sept 30th 2017; Available onlineCitation: Brahmi, N., Charfi, S., and Chaabene, M. (2017) Optimum Sizing Algorithm for an off grid plant considering renewable potentials and load profile. Int. Journal of Renewable Energy Development, 6(3), 213-224.https://doi.org/10.14710/ijred.6.3.213-224