Kodjo Agbossou

Performance of a stand-alone renewable energy system based on energy storage as hydrogen

Electrolytic hydrogen offers a promising alternative for long-term energy storage of renewable energy (RE). A stand-alone RE system based on energy storage as hydrogen has been developed and installed at the Hydrogen Research Institute, and successfully tested for autonomous operation with developed control system and power conditioning devices. The excess energy produced, with respect to the load requirement, has been sent to the electrolyzer for hydrogen production. When energy produced from the RE sources became insufficient, with respect to the load requirement, the stored hydrogen was fed to a fuel cell to produce electricity. The RE system components have substantially different voltage-current characteristics and they are integrated through power conditioning devices on a dc bus for autonomous operation by using a developed control system. The developed control system has been successfully tested for autonomous operation and energy management of the system. The experimental results clearly indicate that a stand-alone RE system based on hydrogen production is safe and reliable.

Dynamic behavior of a PEM fuel cell stack for stationary applications

We discuss the behavior and performance of a proton exchange membrane fuel cell stack under fast load commutations. We present experimental results for the polarization curves, energy balance sheet, and time response of the fuel cells. Although load transients are present both in the voltage and current generated, it is found that the fuel cell system response is faster than 0.15 s to load commutations. The experimental results were also compared to the Amphlett et al. and Kim et al. models, which were found to describe the data well.

Renewable energy systems based on hydrogen for remote applications

An integrated renewable energy (RE) system for powering remote communication stations and based on hydrogen is described. The system is based on the production of hydrogen by electrolysis whereby the electricity is generated by a 10 kW wind turbine (WT) and 1 kW photovoltaic (PV) array. When available, the excess power from the RE sources is used to produce and store hydrogen. When not enough energy is produced from the RE sources, the electricity is then regenerated from the stored hydrogen via a 5 kW proton exchange membrane fuel cell system. Overview results on the performances of the WT, PV, and fuel cells system are presented.

Characterization of a Ballard MK5-E Proton Exchange Membrane Fuel Cell Stack

We present the results of an experimental investigation of the energy balance of a Ballard MK5-E proton exchange membrane fuel cell (PEMFC) stack. We have investigated the transient phenomena that occur during PEMFC stack warm-up, under load switching, and when the PEMFC stack is connected to a DC/AC inverter. A simple and convenient model describing the polarization curve as a function of the temperature is presented and validated by our experimental data. We also present experimental results on the increase PEMFC stack performance as a function of the current density for different oxygen concentrations of the oxidant gas.

Analytical model for predicting the performance of photovoltaic array coupled with a wind turbine in a stand-alone renewable energy system based on hydrogen

We present the results of an analysis of the performance of a photovoltaic array that complement the power output of a wind turbine generator in a stand-alone renewable energy system based on hydrogen production for long-term energy storage. The procedure for estimating hourly solar radiation, for a clear sunny day, from the daily average solar insolation is also given. The photovoltaic array power output and its effective contribution to the load as well as to the energy storage have been determined by using the solar radiation usability concept. The excess and deficit of electrical energy produced from the renewable energy sources, with respect to the load, govern the effective energy management of the system and dictate the operation of an electrolyser and a fuel cell generator. This performance analysis is necessary to determine the effective contribution from the photovoltaic array and the wind turbine generator and their contribution to the load as well as for energy storage.

Nonlinear model identification of wind turbine with a neural network

A nonlinear model of wind turbine based on a neural network (NN) is described for the estimation of wind turbine output power. The proposed nonlinear model uses the wind speed average, the standard deviation and the past output power as input data. An anemometer with a sampling rate of one second provides the wind speed data. The NN identification process uses a 10-min average speed with its standard deviation. The typical local data collected in September 2000 is used for the training, while those of October 2000 are used to validate the model. The optimal NN configuration is found to be 8-5-1 (8 inputs, 5 neurons on the hidden layer, one neuron on the output layer). The estimated mean square errors for the wind turbine output power are less than 1%. A comparison between the NN model and the stochastic model mostly used in the wind power prediction is done. This work is a basic tool to estimate wind turbine energy production from the average wind speed.

Output Power Maximization of a Permanent Magnet Synchronous Generator Based Stand-alone Wind Turbine

This paper proposes output power maximization control of wind energy system. A permanent magnet synchronous generator (PMSG) is used as a variable speed generator in the proposed wind energy system. In order to achieve the maximum power control of wind turbine across a wide range of wind speeds, a dynamic modeling and simulation of wind system with battery energy storage including wind disturbances is presented in this paper. This model should be able to support the analysis of the interaction between the mechanical structure of the wind turbine and the electrical load during different operational modes. These wind turbine concept models can be used and even extended for the study of different aspects, e.g. the assessment of power quality, control strategies, connection of the wind turbine at different types of grid and storage systems

Development of a MPPT method for photovoltaic systems

In the algorithms found in the literature for finding the optimum point of operation MPPT ( maximum power point tracking), of photovoltaic (PV) modules, the initial reference value is fixed arbitrarily and without constraints. This reduces the performance of research into the optimal operation point of PV systems. In order to improve this performance, a MPPT method based on a nonlinear approach is proposed for estimation of the initial value of the reference. The combination of this approach with the perturbation and observation (P and O) method has enabled progress to be made in the search for the optimal operation point of the PV system.

DC bus control of variable speed wind turbine using a buck-boost converter

For most of the peak power extraction methods in wind turbine generation system described in the current literature, it is necessary to know the wind turbines maximum power curve and the wind speed measurement. These methods used the maximum power curve obtained via simulations or tests for individual wind turbines. This makes these methods difficult and expensive to implement in practice. In addition, the use of wind speed sensor to measure the wind speed adds to a system a cost and presents some difficulties in practical implementation. This paper describes the design of a buck-boost converter circuit used to achieve the maximum power control of wind turbine driven permanent magnet synchronous generator (PMSG). The PMSG is suitably controlled according to the generator speed and thus the power from a wind turbine settles down on the maximum power point by the proposed MPPT control method, where the wind turbines maximum power curve and the information on wind velocity are not required

Two-Layer Energy-Management Architecture for a Fuel Cell HEV Using Road Trip Information

This paper investigates the design of a two-layer energy-management system for a fuel cell hybrid electric vehicle (HEV). The first layer (upper layer) deals with the vehicle energy consumption, whereas the second layer (lower layer) deals with the power splitting between the fuel cell and the battery. The upper layer aims at providing the globally optimal energy consumption profile by considering the road-trip information and the vehicle dynamics. This energy profile is independent of the number and type of power sources on the vehicle. Therefore, it can be used to assist the real-time power splitting algorithm implemented into the lower layer. This layer design goal is mainly to share the vehicle power demand between the fuel cell and the battery while minimizing the hydrogen consumption. In addition, the splitting method takes into account the fuel cell efficiency map and the hydrogen/electricity relative pricing while imposing a smooth behavior on the fuel cell. This smooth behavior is desirable to preserve the fuel cell life and reduce the oxygen starvation phenomenon. The proposed energy-management system has been successfully implemented and validated on an HEV test bench. The experiments and simulations using several standard driving cycles suggest that the approach can reduce the hydrogen consumption up to 10% compared to a rule-based method and a depleting-sustaining method while preserving at the same time the battery pack from overdischarging.