An improved particle swarm optimisation for unit commitment in microgrids with battery energy storage systems considering battery degradation and uncertainties

Using electric storage systems (ESSs) is known as a viable strategy to mitigate the volatility and intermittency of renewable distributed generators (DGs) in microgrids (MGs). Among different electric storage technologies, battery energy storage (BES) is considered as the best option. In unit commitment (UC) module, the set of committed dispatchable DGs along with their power, power exported to/imported from macrogrid and status and power of ESS units are determined. In this paper, BES degradation is considered in UC formulation and an efficient particle swarm optimisation with quadratic transfer function is proposed for solving UC in BES‐integrated MGs, while the uncertainties of demand, renewable generation and market price are considered and dealt with robust optimisation. UC is formulated as a multi‐objective optimisation problem whose objectives are MG operation cost and BES degradation. The resultant multi‐objective optimisation problem is converted into a single‐objective optimisation problem and the effect of weight factors on MG operation cost and BES lifecycle are investigated. The results show that by consideration of BES degradation in objective function, BES lifecycle increases from 350 to 500 and the minimum depth of charge increases from 5.5% to 34%; however, MG operation cost increases from $8717 to $8910.2. The results also show that by consideration of uncertainties, MG's operation cost increases by 8.22%.     

KSUTraffic: A Microscopic Traffic Simulator for Traffic Planning in Smart Cities

Simulation is a powerful tool for improving, evaluating and analyzing the performance of new and existing systems. Traffic simulators provide tools for studying transportation systems in smart cities as they describe the evolution of traffic to the highest level of detail. There are many types of traffic simulators that allow simulating traffic in modern cities. The most popular traffic simulation approach is the microscopic traffic simulation because of its ability to model traffic in a realistic manner. In many cities of Saudi Arabia, traffic management represents a major challenge as a result of expansion in traffic demands and increasing number of incidents. Unfortunately, employing simulation to provide effective traffic management for local scenarios in Saudi Arabia is limited to a number of commercial products in both public and private sectors. Commercial simulators are usually expensive, closed source and inflexible as they allow limited functionalities. In this project, we developed a local traffic simulator “KSUtraffic” for traffic modeling, planning and analysis with respect to different traffic control strategies and considerations. We modeled information specified by GIS and real traffic data. Furthermore, we designed experiments that manipulate simulation parameters and the underlying area. KSUTraffic visualizes traffic and provides statistical results on the simulated traffic which would help to improve traffic management and efficiency.     

Ultracompact methane steam reforming reactor based on microwaves susceptible structured catalysts for distributed hydrogen production

Hydrogen is a potential green energy vector. Since the heating of the reforming processes commonly used for its production is obtained by burning hydrocarbons, it has a substantial CO₂ footprint. One of the most critical aspects in the methane steam reforming (MSR) reaction is the heat transfer to the catalytic volume, due to the high heat fluxes required to obtain high methane conversions. Consequently, the reactor has complex geometries, along with the heating medium being characterized by temperatures higher than 1000 °C; expensive construction materials and high reaction volumes are therefore needed, resulting in slow thermal transients. These aspects increase the costs (both operative and fixed) as well as cause a decrease in the whole process efficiency. The heat transfer limitations due to the endothermicity of methane steam reforming reaction could be effectively overcome by microwave (MW) heating. This heating technique, that depends only on the dielectric properties of the materials, can result in an efficient and faster method for transferring heat directly to the catalyst, thus generating the heat directly inside the catalytic volume. In this work, Ni-based catalysts, differing from each other by the Ni loading (7 and 15 wt% with respect to the washcoat) were prepared. The catalysts were characterized by means of several techniques and tested in the MW-assisted methane steam reforming reaction. Furthermore, the energy balance of the entire process was performed to calculate the energy efficiency, making a preliminary evaluation of its feasibility in distributed hydrogen production also possible. The results of the preliminary tests showed that the prepared structured catalysts are very susceptible to the MW radiation, and that in the presence of the MSR reaction, it is possible to make the system reach a temperature of 900 °C. In the same tests, the CH₄ conversion showed a good approach to the thermodynamic equilibrium values starting at temperatures of about 800 °C at a value of gas hourly space velocity (GHSV) of about 5000 h^?1. The energy efficiency of the lab-scale system, calculated as the ratio among the energy absorbed by the system and the energy supplied by the microwaves, was about 50%. Future studies will deal with the microwave reactor optimization, aiming at the increase of the energy efficiency of the system, as well as to obtain a higher CH₄ conversion at lower temperatures and increase the H₂ yield and selectivity.     

An unsupervised approach for fault diagnosis of power transformers

Electrical utilities apply condition monitoring on power transformers (PTs) to prevent unplanned outages and detect incipient faults. This monitoring is often done using dissolved gas analysis (DGA) coupled with engineering methods to interpret the data, however the obtained results lack accuracy and reproducibility. In order to improve accuracy, various advanced analytical methods have been proposed in the literature. Nonetheless, these methods are often hard to interpret by the decision-maker and require a substantial amount of failure records to be trained. In the context of the PTs, failure data quality is recurrently questionable, and failure records are scarce when compared to nonfailure records. This work tackles these challenges by proposing a novel unsupervised methodology for diagnosing PT condition. Differently from the supervised approaches in the literature, our method does not require the labeling of DGA records and incorporates a visual representation of the results in a 2D scatter plot to assist in interpretation. A modified clustering technique is used to classify the condition of different PTs using historical DGA data. Finally, well-known engineering methods are applied to interpret each of the obtained clusters. The approach was validated using data from two different real-world data sets provided by a generation company and a distribution system operator. The results highlight the advantages of the proposed approach and outperformed engineering methods (from IEC and IEEE standards) and companies legacy method. The approach was also validated on the public IEC TC10 database, showing the capability to achieve comparable accuracy with supervised learning methods from the literature. As a result of the methodology performance, both companies are currently using it in their daily DGA diagnosis.     

Life-cycle assessment of hydrogen technologies with the focus on EU critical raw materials and end-of-life strategies

We present the results of a life-cycle assessment (LCA) for the manufacturing and end-of-life (EoL) phases of the following fuel-cell and hydrogen (FCH) technologies: alkaline water electrolyser (AWE), polymer-electrolyte-membrane water electrolyser (PEMWE), high-temperature (HT) and low-temperature (LT) polymer-electrolyte-membrane fuel cells (PEMFCs), together with the balance-of-plant components. New life-cycle inventories (LCIs), i.e., material inputs for the AWE, PEMWE and HT PEMFC are developed, whereas the existing LCI for the LT PEMFC is adopted from a previous EU-funded project. The LCA models for all four FCH technologies are created by modelling the manufacturing phase, followed by defining the EoL strategies and processes used and finally by assessing the effects of the EoL approach using environmental indicators. The effects are analysed with a stepwise approach, where the CML2001 assessment method is used to evaluate the environmental impacts. The results show that the environmental impacts of the manufacturing phase can be substantially reduced by using the proposed EoL strategies (i.e., recycled materials being used in the manufacturing phase and replacing some of the virgin materials). To point out the importance of critical materials (in this case, the platinum-group metals or PGMs) and their recycling strategies, further analyses were made. By comparing the EoL phase with and without the recycling of PGMs, an increase in the environmental impacts is observed, which is much greater in the case of both fuel-cell systems, because they contain a larger quantity of PGMs.     

Effect of water distribution in gas diffusion layer on proton exchange membrane fuel cell performance

Water management of proton exchange membrane fuel cells remains a prominent issue in research concerning fuel cells. In this study, the gas diffusion layer (GDL) of a fuel cell is partially treated with a hydrophobic agent, and the effect of GDL hydrophobicity on the water distribution in the fuel cell is examined. First, the effect of the position of the cathode GDL hydrophobic area relative to the channel on the fuel cell performance is investigated. Then, the water distribution in the fuel cell cathode GDL is observed using X-ray imaging. The experimental results indicate that when the hybrid GDL's hydrophobic area lies on the channel, water tends to accumulate under the rib, and the water content in the channel is low; this improves the fuel cell performance. When the hydrophobic area is under the rib, the water distribution is more uniform, but the performance deteriorates.     

Efficient fault diagnosis method of PEMFC thermal management system for various current densities

The temperature of a fuel cell has a considerable impact on the saturation of a membrane, electrochemical reaction speed, and durability. So thermal management is considered one of the critical issues in polymer electrolyte membrane fuel cells. Therefore, the reliability of the thermal management system is also crucial for the performance and durability of a fuel cell system. In this work, a methodology for component-level fault diagnosis of polymer electrolyte membrane fuel cell thermal management system for various current densities is proposed. Specifically, this study suggests fault diagnosis using limited data, based on an experimental approach. Normal and five component-level fault states are diagnosed with a support vector machine model using temperature, pressure, and fan control signal data. The effects of training data at different operating current densities on fault diagnosis are analyzed. The effects of data preprocessing method are investigated, and the cause of misdiagnosis is analyzed. On this basis, diagnosis results show that the proposed methodology can realize efficient component-level fault diagnosis using limited data. The diagnosis accuracy is over 92% when the residual basis scaling method is used, and data at the highest operating current density is used to train the support vector machine.     

Graduate Student Literature Review: Current recommendations and scientific knowledge on dairy goat kid rearing practices in intensive production systems in Canada,the United States,and France

Dairy goat kid rearing is the foundation of future milk production, yet little is known on this topic. References available to producers are limited, making it more difficult for dairy goat farms to reach their full production potential. This review paper aimed to identify the current recommendations on dairy goat kid rearing practices for intensive production systems and to assess whether the different recommendations were based on scientific literature. Recommendations on dairy goat kid rearing practices, from birth to weaning inclusively, were presented and compared between countries under similar intensive production systems, including Canada, the United States, and France. The different areas of rearing investigated included kidding management, colostrum management, liquid and solid feeding, health management, disbudding, housing, weaning, and growth monitoring. Gaps in the literature were identified in all areas except for disbudding. More research on the topic of goat kid raising practices would be beneficial to refine and validate current recommendations.