Proton exchange membrane fuel cell degradation prediction based on Adaptive Neuro-Fuzzy Inference Systems

This paper studies the prediction of the output voltage reduction caused by degradation during nominal operating condition of a PEM fuel cell stack. It proposes a methodology based on Adaptive Neuro-Fuzzy Inference Systems (ANFIS) which use as input the measures of the fuel cell output voltage during operation. The paper presents the architecture of the ANFIS and studies the selection of its parameters. As the output voltage cannot be represented as a periodical signal, the paper proposes to predict its temporal variation which is then used to construct the prediction of the output voltage. The paper also proposes to split this signal in two components: normal operation and external perturbations. The second component cannot be predicted and then it is not used to train the ANFIS. The performance of the prediction is evaluated on the output voltage of two fuel cells during a long term operation (1000 h). Validation results suggest that the proposed technique is well adapted to predict degradation in fuel cell systems.     

Combining solar irradiance measurements,satellite-derived data and a numerical weather prediction model to improve intra-day solar forecasting

Isolated power systems need to generate all the electricity demand with their own renewable resources. Among the latter, solar energy may account for a large share. However, solar energy is a fluctuating source and the island power grid could present an unstable behavior with a high solar penetration. Global Horizontal Solar Irradiance (GHI) forecasting is an important issue to increase solar energy production into electric power system. This study is focused in hourly GHI forecasting from 1 to 6 h ahead. Several statistical models have been successfully tested in GHI forecasting, such us autoregressive (AR), autoregressive moving average (ARMA) and Artificial Neural Networks (ANN). In this paper, ANN models are designed to produce intra-day solar forecasts using ground and exogenous data. Ground data were obtained from two measurement stations in Gran Canaria Island. In order to improve the results obtained with ground data, satellite GHI data (from Helioclim-3) as well as solar radiation and Total Cloud Cover forecasts provided by the European Centre for Medium-Range Weather Forecasts (ECMWF) are used as additional inputs of the ANN model. It is shown that combining exogenous data (satellite and ECMWF forecasts) with ground data further improves the accuracy of the intra-day forecasts.     

Modeling of heat transfer and fluid flow characteristics of helicoidal double-pipe heat exchangers using Adaptive Neuro-Fuzzy Inference System (ANFIS)

In this paper an Adaptive Neuro-Fuzzy Inference System (ANFIS) is used for modeling the effect of important parameters on heat transfer and fluid flow characteristics of helicoidal double-pipe heat exchangers using some numerically investigated and compared with those to experimental results for training and test data. In this way, overall heat transfer coefficient (U_o) and inner and annular pressure drop (ΔP_in, ΔP_an) are modeled with respect to the variation of inner and annular dean number (De_in, De_an), inner and annular Prandtl number (Pr_in, Pr_an) and pitch of coil (B) which are defined as input (design) variables. Then, we divided these data into train and test sections in order to accomplish modeling. We instructed ANFIS network by 75% of numerical-validated data. Twenty-five percent of primary data which had been considered for testing the appropriateness of the models was entered into ANFIS network models and results were compared by two statistical criterions (R², RMSE). Considering the results, it is obvious that our proposed modeling by ANFIS is efficient and valid and it can be expanded for more general states.     

Dynamic modelling and simulation of a new air conditioning prototype by solar energy

This work presents a new design of an air conditioning prototype by solar energy developed at the Laboratory of Electromechanical Systems of the National Engineering School of Sfax, Tunisia. The new conception permits to produce heat or cold by using solar energy without polluting the environment. The installation, composed of four compartments, consists of three functioning modes according to the season of the year and according to the climatic conditions.A numerical model is developed to study the behaviour of the unit. This model uses real meteorological data to predict the performance of a thermal solar driven system. The dynamic modelling and simulation of only two modes of functioning (winter mode and summer mode without pre-cooling of air) are presented in this paper. This theoretical model is expected to help in predicting the behaviour of the installation in various climatic conditions. Besides, it would enhance the performance of such installation.     

Development of a neural network-based fault diagnostic system for solar thermal applications

The objective of this work is to present the development of an automatic solar water heater (SWH) fault diagnosis system (FDS). The FDS system consists of a prediction module, a residual calculator and the diagnosis module. A data acquisition system measures the temperatures at four locations of the SWH system and the mean storage tank temperature. In the prediction module a number of artificial neural networks (ANN) are used, trained with values obtained from a TRNSYS model of a fault-free system operated with the typical meteorological year (TMY) for Nicosia, Cyprus and Paris, France. Thus, the neural networks are able to predict the fault-free temperatures under different environmental conditions. The input data to the ANNs are various weather parameters, the incidence angle, flow condition and one input temperature. The residual calculator receives both the current measurement data from the data acquisition system and the fault-free predictions from the prediction module. The system can predict three types of faults; collector faults and faults in insulation of the pipes connecting the collector with the storage tank and these are indicated with suitable labels. The system was validated by using input values representing various faults of the system.     

Off-design performance analysis of a closed-cycle ocean thermal energy conversion system with solar thermal preheating and superheating

This article reports the off-design performance analysis of a closed-cycle ocean thermal energy conversion (OTEC) system when a solar thermal collector is integrated as an add-on preheater or superheater. Design-point analysis of a simple OTEC system was numerically conducted to generate a gross power of 100 kW, representing a base OTEC system. In order to improve the power output of the OTEC system, two ways of utilizing solar energy are considered in this study: (1) preheating of surface seawater to increase its input temperature to the cycle and (2) direct superheating of the working fluid before it enters a turbine. Obtained results reveal that both preheating and superheating cases increase the net power generation by 20–25% from the design-point. However, the preheating case demands immense heat load on the solar collector due to the huge thermal mass of the seawater, being less efficient thermodynamically. The superheating case increases the thermal efficiency of the system from 1.9% to around 3%, about a 60% improvement, suggesting that this should be a better approach in improving the OTEC system. This research provides thermodynamic insight on the potential advantages and challenges of adding a solar thermal collection component to OTEC power plants.     

Modelling of solar energy potential in Nigeria using an artificial neural network model

In this study, an artificial neural network (ANN) based model for prediction of solar energy potential in Nigeria (lat. 4–14°N, log. 2–15°E) was developed. Standard multilayered, feed-forward, back-propagation neural networks with different architecture were designed using neural toolbox for MATLAB. Geographical and meteorological data of 195 cities in Nigeria for period of 10 years (1983–1993) from the NASA geo-satellite database were used for the training and testing the network. Meteorological and geographical data (latitude, longitude, altitude, month, mean sunshine duration, mean temperature, and relative humidity) were used as inputs to the network, while the solar radiation intensity was used as the output of the network. The results show that the correlation coefficients between the ANN predictions and actual mean monthly global solar radiation intensities for training and testing datasets were higher than 90%, thus suggesting a high reliability of the model for evaluation of solar radiation in locations where solar radiation data are not available. The predicted solar radiation values from the model were given in form of monthly maps. The monthly mean solar radiation potential in northern and southern regions ranged from 7.01–5.62 to 5.43–3.54 kW h/m² day, respectively. A graphical user interface (GUI) was developed for the application of the model. The model can be used easily for estimation of solar radiation for preliminary design of solar applications.     

Neural network modelling of thermal stratification in a solar DHW storage

In this study an artificial neural network (ANN) model is introduced for modelling the layer temperatures in a storage tank of a solar thermal system. The model is based on the measured data of a domestic hot water system. The temperatures distribution in the storage tank divided in 8 equal parts in vertical direction were calculated every 5 min using the average 5 min data of solar radiation, ambient temperature, mass flow rate of collector loop, load and the temperature of the layers in previous time steps. The introduced ANN model consists of two parts describing the load periods and the periods between the loads. The identified model gives acceptable results inside the training interval as the average deviation was 0.22 °C during the training and 0.24 °C during the validation.     

Performance prediction of a direct expansion solar assisted heat pump using artificial neural networks

This paper presents the suitability of artificial neural network (ANN) to predict the performance of a direct expansion solar assisted heat pump (DXSAHP). The experiments were performed under the meteorological conditions of Calicut city (latitude of 11.15 °N, longitude of 75.49 °E) in India. The performance parameters such as power consumption, heating capacity, energy performance ratio and compressor discharge temperature of a DXSAHP obtained from the experimentation at different solar intensities and ambient temperatures are used as training data for the network. The back propagation learning algorithm with three different variants (such as, Lavenberg–Marguardt (LM), scaled conjugate gradient (SCG) and Pola-Ribiere conjugate gradient (CGP)) and logistic sigmoid transfer function were used in the network. The results showed that LM with 10 neurons in the hidden layer is the most suitable algorithm with maximum correlation coefficients (R²) of 0.999, minimum root mean square (RMS) value and low coefficient of variance (COV). The reported results conformed that the use of ANN for performance prediction of DXSAHP is acceptable.     

Optical properties of liquids for direct absorption solar thermal energy systems

A method for experimentally determining the extinction index of four liquids (water, ethylene glycol, propylene glycol, and Therminol VP-1) commonly used in solar thermal energy applications was developed. In addition to the extinction index, we report the refractive indices available within the literature for these four fluids. The final value reported is the solar-weighted absorption coefficient for the fluids demonstrating each fluid’s baseline capacity for absorbing solar energy. Water is shown to be the best absorber of solar energy of the four fluids, but it is still a weak absorber, only absorbing 13% of the energy. These values represent the baseline potential for a fluid to be utilized in a direct absorption solar thermal collector.     

Dynamic simulation of thermal energy storage system of Badaling 1 MW solar power tower plant

In this paper, the thermal energy storage system of Badaling 1 MW solar power tower plant is modelled from mathematical models for whole of the working conditions using the modular modelling method. This model can accurately simulate the recharge and discharge processes of thermal energy storage system. The dynamic and static characteristics of the thermal energy storage system are analyzed based on the model response curves of the system state parameters that are obtained from different steam flow disturbances. Conclusions of this paper are good references for the design, operating, and control strategy of solar thermal power plant.     

Study of hybrid energy system coupling fuel cell,solar thermal system and photovoltaic cell

The present work examines the combination of solar energy systems with Fuel cell. Indeed, fuel cells are green storage systems without any pollution effects. They are supplied by oxygen and hydrogen to produce electricity. That is why it is inescapable to find a source of hydrogen in order to use fuel cell. Several techniques can be adopted to produce hydrogen depending on the availability and the cost of the sources. One of the most utilized techniques is electrolysers. They allow to obtain hydrogen from water by several technologies among them proton exchange membrane (PEM) which is considered in this work. On the other hand, electrolysers need electrical power to operate. A green-green energy system can be constructed by using a renewable energy source to supply fuel cell trough electrolysers. A comparison between two solar systems (Photovoltaic and Parabolic Trough) coupled to fuel cell is performed. A case study on the Lebanese city of Tripoli is carried out. The study shows the performance of each of both combined systems for different parameters and proposes recommendations depending on the considered configuration.     

Study on thermal performance of solar methanol reforming MCFC-GT-ST-CHP system

In recent years, fuel cells have begun to attract the attention of many countries in the world. Based on Aspen Plus, this paper constructs a distributed energy system about solar assisted Methanol reforming-Molten Carbonate Fuel Cell (MR-MCFC), which is combined with GT-ST power generation system and heating system. The results show that the MCFC efficiency, total electrical efficiency and total thermal efficiency of the system are 44.12%, 58.62% and 90.36%, respectively. The research results will provide a theoretical basis for exploring a new method of highly complementary utilization of solar energy and chemical energy. By analyzing the variable working conditions of the system, the complementary utilization affinity characteristics of the solar MR-MCFC and the integrated system are revealed. We will continue to innovate and optimize the system in order to provide reference for the further development of the CHP (Combined Heat and Power) system.     

Experimental performance evaluation of a novel heat exchanger for a solar hot water storage system

The performance of a novel heat exchanger unit (‘Solasyphon’) developed for a solar hot water storage system was experimentally investigated. The ‘Solasyphon’ is a simple ‘bolt-on’ heat exchange unit that can be integrated externally to a traditional single-coil hot water cylinder (HWC) avoiding the costly replacement of an existing HWC with a twin-coil HWC. The installation cost of a ‘Solasyphon’ is lower compared to a traditional HWC thus offers greater cost effectiveness. A data acquisition system was designed to compare the thermal performance of an integrated ‘Solasyphon’ HWC with a traditional twin-coil HWC under controlled simulated conditions. The analysis was based on experimental data collected under various operating conditions including different primary supply temperatures (solar simulated); primary supply patterns and draw off patterns. The results indicated that the ‘Solasyphon’ delivered solar heated water directly to the top of the HWC producing a stratified supply at a useable temperature. Under variable solar conditions the ‘Solasyphon’ would transfer the heat gained by a solar collector to a HWC more efficiently and quickly than a traditional HWC. The ‘Solasyphon’ system can reduce installation costs by 10–40% and has a lower embodied energy content due to less material replacement.     

Performance analysis and parametric study of thermal energy storage in an aquifer coupled with a heat pump and solar collectors,for a residential complex in Tehran,Iran

Aquifers are underground porous formations containing water. Confined aquifers are the formations surrounded by two impermeable layers, called cap rocks and bed rocks. These aquifers are suitable for seasonal thermal energy storage.In the present study, a confined aquifer was considered to meet the cooling and heating energy needs of a residential complex located in Tehran, Iran. Three different alternatives were analyzed in this aquifer thermal energy storage (ATES), including: using ATES for cooling alone, for cooling and heating, as a heat pump, and for heating alone, employing flat plate solar energy collectors. A numerical simulation, based on the finite difference method, was carried out for velocity and temperature distributions as well as the heat transfer in the aquifer. The thermal energy recovery factor and the annual coefficient of performance of the system were determined under various schemes of operation, revealing that the combination of the ATES with the heat pump, to meet both cooling and heating needs of the complex, is the best. The study was repeated for different aquifer properties.     

Potential application of a centralized solar water-heating system for a high-rise residential building in Hong Kong

There is a growing, government-led trend of applying renewable energy in Hong Kong. One area of interest lies in the wider use of solar-energy systems. The worldwide fast development of building-integrated solar technology has prompted the design alternative of fixing the solar panels on the external façades of buildings. In Hong Kong, high-rise buildings are found everywhere in the urban districts. How to make full use of the vertical facades of these buildings to capture the most solar radiation can be an important area in the technology promotion. In this numerical study, the potential application of a centralized solar water-heating system in high-rise residence was evaluated. Arrays of solar thermal collectors, that occupied the top two-third of the south and west façades of a hypothetical high-rise residence, were proposed for supporting the domestic hot-water system. Based on typical meteorological data, it was found that the annual efficiency of the vertical solar collectors could reach 38.4% on average, giving a solar fraction of 53.4% and a payback period of 9.2 years. Since the solar collectors were able to reduce the heat transmission through the building envelope, the payback was in fact even shorter if the energy saving in air-conditioner operation was considered.     

Effects of working fluids on the performance of a bi-directional thermodiode for solar energy utilization in buildings

A series of experiments were conducted to investigate the effects of different working fluids on the behavior and performance of a bi-directional thermodiode. The thermodiode was made up of two rectangular loops mounted between a collector plate and a radiator plate. The loops were filled with a working fluid for effective heat transfer when the thermodiode was forward biased. Five different working fluids were tested with thermal conductivity values ranging from 0.1 to 0.607 W/m-K, thermal expansion coefficient values ranging from 2.54 × 10⁻⁴ to 1.43 × 10⁻³ 1/K, and kinematic viscosity values ranging from 6.5 × 10⁻⁷ to 1 × 10⁻⁴ m²/s. The thermodiode was heated by a radiant heater consisting of 88 halogen lamps that generated a heat flux of about 10³ W/m² on the collector surface. Experimental results indicated that the onset time for natural convection to be induced throughout the diode system did not differ considerably when different working fluids were used. On the other hand the required fluid temperature differences in the loops for the onset of throughflow were quite different and depended strongly upon the viscosity and other properties such as thermal expansion coefficient and specific heat of the working fluid. Of the five fluids tested, water and low-viscosity silicon oil had the highest heat transfer rate. An analytical model was developed to predict and analyze the steady operation of the diode system when different working fluids are used.     

Public energy performance policy and the effect on diffusion of solar thermal systems in buildings: A Dutch experience

Energy performance policy is an important element in the European Energy Performance of Buildings Directive (Directive 2002/91/EC—in short: EPBD, published 4 January 2003), which the European Commission is now urging all European member states to introduce for the building sector by 2006. One of the expected benefits of energy performance policy is that it can help to introduce innovations such as solar thermal systems. However, few studies have analysed this so far. This paper describes the extent to which the penetration of solar thermal systems in the residential building sector is directly related to energy performance policy in the Netherlands. The concept of energy performance policy is explained and the effects of using energy performance policy for several years in the Netherlands are described, through the results of an empirical study. Statistical analysis appears to show no association between Dutch energy performance policy and the application of solar thermal systems in the domestic sector.     

Optimal analysis of a space solar dynamic power system

The major purpose of the present study is the theoretical modeling, numerical simulation and optimal analysis of a space solar dynamic power system. Using the method of system analysis, a mathematical and physical model is developed to describe the process of energy transfer and conversion in a space solar dynamic power system. As a new assessing criterion for total launch mass, it is proposed to combine the system mass and aerodynamic drag area into a unified criterion. The effects of the configurations and operating parameters on the system performance are analyzed and the optimal scheme of a space solar dynamic power system is obtained by numerical simulation.