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International audience; Coupling water desalination processes with Renewable Energy Sources (RESs) can be a sustainable and ecological approach to the global water/energy supply crisis. In this regard, small-scale standalone battery-less Brackish Water Reverse Osmosis (BWRO) desalination system powered by a hybrid PV/Wind RES is expected to meet freshwater demand of a small isolated community. One particularity of the proposed architecture deals with the absence of electrochemical storage; only taking benefit of hydraulic storage in water tanks when RE is available. This study puts forward the prime importance of Water/Power flows management optimization. For this purpose, an online Fuzzy Logic-based Energy Management Strategy (FLEMS) is proposed. Firstly, a Hand-Made Fuzzy Inference System (HMFIS) was designed to identify the instantaneous power sharing between the system hydro-mechanical processes (well pumping, water storage and desalination processes). Secondly, an offline genetic algorithm optimization was applied on the HMFIS design in order to optimize the power sharing factor and maximize freshwater production. Then, when applying unknown power profile, the optimized FLEMS demonstrated its performance to improve the system energy efficiency and enhance the brackish water (from 16.7% in autumn to 63% in summer) and freshwater production (to 3.3% during autumn for instance) compared with the HMFIS-based EMS.

International audience; In remote areas, the vital need is production of drinking water and the provision of electrical energy for housing.Often the only sources of energy are based on renewable energies with storage to create a local micro-network.This paper investigates the optimal design of embodied energy for water treatment by reverse osmosis, comingfrom brackish water (6 g/l) and with a double storage that is done in a drinking water tank and in batteries forelectricity. Taking account wind and photovoltaic potentials in such system for assessing its performance impliesits simulation over long periods of time. This can drastically increase the CPU time cost related to the design step,especially if the system energy management and sizing are sequentially optimized into a two-level optimizationprocess. In order to solve this problem and accelerate the system simulation, meta-models are used for representingthe system constraints and objectives. These meta-models are built by the design of experiments method. From realistic data, the results of this paper show that the contribution of the meta-models divides by two or three the design time by obtaining values of the sizing parameters close to the dynamic simulator depicting the real operation of the whole system.

International audience; In this paper, an ultra-local model control approach based on adaptive Smith predictor is proposed. The design of adaptive PID controller takes into account the estimation of variable time delay which is compensated by the addition of an adaptive Smith predictor. The purpose of this paper is to solve the online estimation problem of time delay thanks to the proposed identification method of ultra-local model parameters. A performance comparison between the proposed control approach and the Smith predictor control with classical PID is carried out. The numerical simulation results of the thermal process study with severe constraints and operating conditions show the superiority of the adaptive PID controller. The robustness with respect to noises, disturbances and system parameter uncertainties of control approaches are highlighted.

International audience; In this paper, the authors investigate four original methodologies for sizing a battery bank inside a passive wind turbine system. This device interacts with wind and load cycles, especially for a stand-alone application. Generally, actual wind speed measurements are of long duration which leads to extensive processing time in a global optimization context requiring a wide number of system simulations. The first part of this article outlines two sizing methodologies based on a statistical approach for the sizing of the electrochemical storage device of a stand-alone passive wind turbine system. Two other efficient methodologies based on the synthesis of compact wind speed profiles by means of evolutionary algorithms are described in the second part of this paper. The results are finally discussed with regard to the relevance of the battery bank sizing and in terms of computation cost, this later issue being crucial to an Integrated Optimal Design (IOD) process.

International audience; This paper aims at defining energy management strategy for a water pumping and desalination process which would be powered by a hybrid (solar PV & wind) renewable generation system. Several pumping subsystems for well pumping, water storage and desalination are coupled. The particularity of the proposed architecture with its management deals with the absence of electrochemical storage, only taking benefit of hydraulic storage in water tanks: in such an autonomous device, given a certain level of intermittent power following wind and sun irradiation conditions, and given hydraulic characteristics of water pumping subsystems, this study puts forward the prime importance of a water and power flow management optimization. For this purpose, both dynamic and quasi static models are proposed before stetting the management strategy based on optimal power dispatching. Subsequent results are analyzed in terms of robustness and performance.

This paper deals with the design of an ultra­ local model control. The proposed approach is based on the estimation of the ultra-local model parameters using least squares resolution technique instead of numerical derivation technique. The closed-loop control is implemented through an adaptive PI in order to reject the influences of the dis­ turbance and noise output signais. Its main advantages are: its simplicity and its robustness with respect to the parame­ ter uncertainties of system. In this paper, it is processed to test the efficiency of the parameter estimation method com­ pared with the performance of numerical derivation tech­ nique. The method is applied to the water level control of a two-tank-system. Numerical simulations show that the gen­ erated desired trajectory is followed in an efficient way even with severe operating conditions.

An off-grid energy system based on renewable photovoltaics (PV) and wind turbines (WT) generators is coupled via converters to electric and hydraulic networks. The electric network is composed of consumers and of a battery bank for electrical storage, while the hydraulic part is made of motor-pumps and hydraulic tanks for water production and desalination. Both battery and water tanks are used to optimize the power management of both electric and hydraulic subsystems by ensuring electric load demand and by reducing at the same time water deficit following the operation of the renewable intermittent source. Thus, both electric and hydraulic subsystems are strongly coupled in terms of energy making necessary to manage the power flows provided by renewable sources to optimize the overall system performance. In this paper, two kinds of management strategies are then compared in the way they share the hybrid power sources between the storage devices (battery and tanks) and the electrical/hydraulic loads. The first approach deals with an “uncoupled power management” in which the operation of electrical and hydraulic loads does not depend on the state of the intermittent renewable sources: in particular, hydraulic pumps are operated only taking account of water demand and tank filling but without considering power sources. On the contrary, given the available power produced by the sources, the second class of strategy (i.e. the “coupled management strategy”) consists of a “smart” power sharing between the electrical and hydraulic networks with regard to the battery SOC and the tank L 1 and L 2 . A dynamic simulator of the hybrid energy system has been developed and tested using a MATLAB environment. The system performance is shown under the two investigated approaches (uncoupled vs coupled). Several tests are carried out using real meteorological data of a remote area and a practical load demand profile. The simulation results show that the “coupled strategy” clearly outperforms the classical “uncoupled” management strategies.

International audience; This paper is devoted to an experimental comparison between two different methods of ultra-local model control. The concept of the first proposed technique is based on the linear system resolution technique to estimate the ultra-local model parameters. The second proposed method is based on the linear adaptive observer which allows the joint estimation of state and unknown system parameters. The closed-loop control is implemented via an adaptive PID controller. In order to show the efficiency of these two control strategies, experimental validations are carried out on a two-tank system. The experimental results show the effectiveness and robustness of the proposed controllers.

This paper proposes a metamodel design for a Photovoltaic/Wind/Battery Energy System. The modeling of a hybrid PV/wind generator coupled with two kinds of storage i.e. electric (battery) and hydraulic (tanks) devices is investigated. A metamodel is carried out by hybrid spline interpolation to solve the relationships between several design variables i.e. the design parameters of different subsystems and their associate response variables i.e. system indicators performance. The developed model has been successfully validated under real test conditions.

International audience; In this paper, the authors face the problem of wind speed processing as environmental variable of a wind turbine system. Generally, the information on wind speed measurements is processed over long periods of time to be relevant with respect to the site characteristics (average and maximum speeds, statistics). Subsequent large scale profiles of wind speed lead to long processing time for simulation analysis and especially for optimization design that penalizes the search of optimal solutions. An original synthesis approach of a compact and representative wind speed profile using an Evolutionary Algorithm (EA) is proposed. This approach is compared to a purely statistical approach based on random number generators. It allows reducing the actual wind profile duration with compression ratios greater (two months of wind speed measurements are compressed in only 1 hour). Then, the synthesis approach by EA is applied to the sizing of an autonomous hybrid system based on wind turbine with battery storage for stand-alone energy systems. It has proven its effectiveness in reducing 200 days of wind speed measurements in only 10 days, allowing sizing the storage system with a significant gain in terms of computing time in the framework of the optimization process.

In this paper, the authors investigate two methodologies for synthesizing compact wind speed profiles by means of evolutionary algorithms. Such profile can be considered as input parameter in a prospective design process by optimization of a passive wind system with storage. Compact profiles are obtained by aggregating elementary patterns in order to fulfil some target indicators. The main difference between both methods presented in the paper is related to the choice of these indicators. In the first method, they are related to the storage system features while they only depend on wind features in the second.

International audience; In this paper, we present the design of ultra wideband (UWB) planar Five-Port Reflectometer using the elliptic coupler which has the advantage to offer a wide bandwidth compared to the hybrid one. The elliptic coupler and the five-port circuit were designed and simulated in the 1.5 to 3.5 GHz band using ADS software of Agilent. An analytical calculus and simulation results of a five-port circuit using elliptic coupler demonstrate limitations of this structure.

In this paper, an original optimization method to jointly determine a reduced study term and an optimum battery sizing is investigated. This storage device is used to connect a passive wind turbine system with a stand alone network. A Weibull probability density function is used to generate different wind speed data. The passive wind system is composed of a wind turbine, a permanent magnet synchronous generator feeding a diode rectifier associated with a very low voltage DC battery bus. This study is essentially based on a similitude model applied on an 8 kW wind turbine system. Our reference model is taken from a 1.7 kW optimized system. The wind system generated power and the load demand are coupled through a battery sized using a statistical approach.

International audience; The linear stability of a plane layer with horizontal temperature and concentration stratification corresponding to gradient zone of a solar pond is investigated. The problem is described by Navier-Stokes equations with Boussinesq-Oberbeck approximation. Two source terms are introduced in the energy equations: the absorption of solar energy characterized by the extinction radiative coefficient μe and by the parameter f defined as the ratio of extracted heat flux to absorbed heat flux in the lower convective zone. The influence of the parameters μe and f on the onset of thermosolutal convection in the case of confined and infinite layers is analyzed. It is found that convection starts in an oscillatory state, independently of the RaS value. Different convection solutions were found for marginal stability and steady state.

International audience; In this paper, the authors report the development of a Systemic Optimization Process (SOP) devoted to a passive wind turbine system with electrochemical storage bank. Aim of the SOP is to find the optimal combination and sizing among sets of system components, that meets the desired system requirements with the lowest system owning cost. The passive wind system associated to the storage bank interacts with wind and load cycles (deterministic data). Sets of passive wind turbines are obtained through an Integrated Optimal Design (IOD) process. The system cost model is inspired from constructor data for the wind turbines and related to the battery cycles for the storage bank. An optimization problem is developed and performed using an exhaustive search. The optimization results are finally exposed and discussed

International audience; In this paper, the authors investigate a robust Integrated Optimal Design (IOD) devoted to a passive wind turbine system with electrochemical storage bank: this stand alone system is dedicated to rural electrification. The aim of the IOD is to find the optimal combination and sizing among a set of system components that fulfils system requirements with the lowest system Total Cost of Ownership (TCO). The passive wind system associated with the storage bank interacts with wind speed and load cycles. A set of passive wind turbines spread on a convenient power range (2 - 16 kW) are obtained through an IOD process at the device level detailed in previous papers. The system cost model is based on data sheets for the wind turbines and related to battery cycles for the storage bank. From the range of wind turbines, a "system level" optimization problem is stated and solved using an exhaustive search. The optimization results are finally exposed and discussed through a sensitivity analysis in order to extract the most robust solution versus environmental data variations among a set of good solutions.