Imene Yahyaoui

Study of combined cycle of Solid Oxide Fuel Cell with Micro Gas Turbines

Solid Oxide Fuel Cells (SOFC) present many advantages to generate electricity from natural gas, such as high efficiency, and little noise. However, the most important advantage of SOFC is its ability to operate at high temperatures. Their high operating temperature makes possible to use natural gas as fuel, so external hydrogen is not necessary for operation. In addition, in hybrid systems with cogeneration, the SOFC can be combined with micro gas turbine (MGT) to generate more power for the same amount of fuel. This cogeneration is interesting for power generation, from few kilowatts, for residences and commercial buildings, until megawatts as in plants for electric power generation, or industries. The study presented hear shows the increased efficiency when a MGT is integrated into the system to take advantage of exhaust gases of the SOFC.

Evaluation of a Long Term System coupled with a Short Term System of a hydrogen-based microgrid

Coupling of a Long Term System (LTS) with a Short Term System (STS) of a hydrogen-based microgrid is considered here in this work to control the operation of a set of electrolyzers that produce hydrogen from renewable energies. Both systems are based on Model Predictive Control (MPC) ideas. The LTS manages the on/off conditions of the electrolyzers taking into account control and prediction horizons in terms of hours (high level control), regulating the operation point of the devices using meteorological predictions. The STS adapts in a low-level control the behavior of the electrolyzers with the rest of the components of the microgrid (battery and ultracapacitor). The plant is modeled in the Mixed Logic Dynamic (MLD) framework due to the presence of logical states such as the start-up/shut down of the electrolyzers and charge/discharge states in the battery and ultracapacitor. These systems are validated in a simulation showing the adequate operation of the components of the microgrid.

Viability of DG, DG/PV and PV/Batteries Plants for Water Pumping: Sensitivity Analysis According to Geographical and Economic Parameters Variations

This chapter presents a study for the cost sensitivity of autonomous water pumping systems based on climatic, geographic, and economic parameters studies. Thus, some architectures for water pumping systems, which include the diesel generator (DG)/pump, the PV/DG/pump, and the PV-batteries/DG/pump, respectively, and a model for the DG are first described in depth. Then, the cost of these three systems are evaluated, and compared with each other, using climatic, geographic, and economic data of three countries, which are Tunisia, Spain, and Qatar.

Sizing Optimization of the Photovoltaic Irrigation Plant Components

Sizing PV water pumping plants is an essential step for the system design and use, since it affects the installation autonomy, the safe operation, and cost of the system. Thus, in this chapter, a review on sizing algorithms in the literature is first detailed. Then, an algorithm to decide on the optimum components sizes of a PV water pumping installation, which are the PV panels surface, the battery bank capacity, and the reservoir volume, is proposed. The algorithm aims to ensure the system autonomy, the protection of the batteries against deep discharge and to pump the water volume needed for crops irrigation, by ensuring the pump supply during the required pumping duration. The sizing result reliability is first tested for a 10xa0ha land surface, using measured climatic and crops data of the target area, and then it is compared with HOMER and PVsyst results.

Renewable Energies and Irrigation

Renewable energies are positioned as a good solution to fossil fuel depletion. For remote sites, where the grid is not available, renewable energies provide an excellent solution, since the energy sources are abundant (namely, solar radiation and wind). Thus, in this chapter, a state of the art of renewable energies use for water pumping is detailed. Hence, the situation of using renewable energies worldwide, namely, photovoltaic, thermal, wind, wave, hydraulic, and biomass energies, and the different photovoltaic installation architectures is first studied. Then, the renewable energies use for irrigation, tomatoes irrigation specifications and factors, namely, the soil, the climate, and the crops data are explained and detailed in depth.

Optimum Energy Management of the Photovoltaic Irrigation Installation

PVPs generate energy intermittently, due to the frequent changes in the solar radiation. Thus, managing the energy is important, especially for autonomous installations, for which a precise balance between the PV power generated and the power demanded by the load is required. In this chapter, a Fuzzy Management Algorithm for the optimum operation of a PV irrigation system composed of PVPs, a lead–acid battery bank, and a submerged pump, is presented and validated experimentally. The algorithm makes decisions on the interconnection time of the PVP, the battery bank, and the pump, depending on the PV power generated, the battery dod , and the stored water in the reservoir. The control algorithm aims to ensure a continuous pump supply and the battery bank protection against deep discharge and excessive charge. The algorithm effectiveness is then tested on a specific case study, during the vegetative cycle of tomatoes (from March to July ), and using data from the target location.

Modeling of the Photovoltaic Irrigation Plant Components

Autonomous photovoltaic (PV) installation is a promising solution to supply water pumping systems, used for crop irrigation in remote agriculture areas, which are characterized by a good solar insolation throughout the year. Thus, in this chapter, models for the PV installation components, namely, the PV generator, the battery bank, the converters, and the water pump are detailed in depth, and some of them are experimentally validated, using meteorological data for the target area.

Implementation of an Advanced Automated Management System for the Optimization of Energy and Power Terms in a Water Purification Plant (WPP) with a Photovoltaic Plant (PP)

Currently, the use of software systems for optimizing the sustainable use of water and energy resources has been implemented in a wide range of productive sectors. In the sector of Water Purification Plants (WPP) the sustainable control of water and energy consumption is carried out by means of advanced Supervisory Control And Data Acquisition (SCADA) systems. The main objective of these SCADA systems is controlling the consumption of these resources in real time. In the majority of the occasions, optimization systems for the sustainability consumption of these resources are not integrated in the SCADA system. With the integration of systems for optimization, the determination in real time of the most viable option for the sustainable management of resources is expected. In this paper, a case study in the Southeast Spain of an advanced automated management system for the optimization of energy and power terms in a WPP with renewable energy based in a Photovoltaic Power Plant (PVPP) is presented. Firstly, the introduction and some additional details for the entire problem are presented. Moreover, the main parts of the software integrated in the SCADA system of the WPP will be detailed.