Micropower system optimization for the telecommunication towers based on various renewable energy sources

This study investigates the technical and cost-effective performance of options renewable energy sources to develop a green off-grid telecommunication tower to replace diesel generators in Malaysia. For this purpose, the solar, wind, pico-hydro energy, along with diesel generators, were examined to compare. In addition, the modeling of hybrid powering systems was conducted using hybrid optimization model for energy (HOMER) simulation based on techno-economic analysis to determine the optimal economically feasible system. The optimization findings showed that the hybrid high-efficiency fixed photovoltaic (PV) system with battery followed by 2 kW pico-hydropower and battery are the optimal configurations for powering off-grid telecommunication towers in Malaysia with the lowest net present cost (NPC) and cost of energy (COE). These costs of NPC and COE are more down than diesel generator costs with battery by 17.45%, 16.45%, 15.9%, and 15.5%, respectively. Furthermore, the economic evaluation of the high-efficiency solar fixed PV panels system annual cash flow compared to the diesel generator with the battery system indicated a ten-year payback period.

Evaluation of the Cost-Optimal Method Applied to Existing Schools Considering PV System Optimization

In Italy in 2020, only 15.5% of school building heritage was retrofitted from an energy and environmental point of view. In this paper, the cost-optimal method was applied to two different school buildings belonging to the same Italian cold climate zone but characterized by different structural and technological solutions. The research aims at defining the cost-effective redevelopment solution among several ones proposed to apply to this building type. At the same time, this paper provides a critical analysis of the methodology applied, highlighting deficiencies related to a not proper evaluation of environmentally friendly retrofitting measures. In a cost-effective context, the main results show that the intervention on the heating system is more convenient than the retrofitting of the envelope. The energy saving is equal to about 35% for both considered schools. Among the different proposed requalification configurations, the adoption of PV (photovoltaic) electric generation is included. In this regard, an optimization procedure was implemented in a generative design environment to maximize energy production with reference to different design parameters. As a result, a solution with south oriented PV modules with a tilt angle of 42° and arranged in 0.7 m spaced rows proved to be the most effective.

System Optimization of Shared Mobility in Suburban Contexts

Shared mobility is a viable choice to improve the connectivity of lower-density neighbourhoods or suburbs that lack high-frequency public transportation services. In addition, its integration with new forms of powertrain and autonomous technologies can achieve more sustainable and efficient transportation. This study compares four shared-mobility technologies in suburban areas: the Internal Combustion Engine, Battery Electric, and two Autonomous Electric Vehicle scenarios, for various passenger capacities ranging from three to fifteen. The study aims to provide policymakers, transportation planners, and transit providers with insights into the potential costs and benefits as well as system configurations of shared mobility in a suburban context. A vehicle routing problem with time windows was applied using the J-Horizon software to optimize the costs of serving existing intra-community demand. The results indicate a similar fleet composition for Battery Electric and Autonomous Electric fleets. Furthermore, the resulting fleet for all four technologies is dominated by larger vehicle capacities. Due to the large share of driver cost in the total cost, the savings using a fleet of Autonomous Electric Vehicles are predicted to be 68% and 70%, respectively, compared to Internal Combustion and Battery Electric fleets.

Anaerobic Digestion, Codigestion of Food Waste, and Chicken Dung: Correlation of Kinetic Parameters with Digester Performance and On-Farm Electrical Energy Generation Potential

Valorization of agro-food waste through anaerobic digestion (AD) is gaining prominence as alternative method of waste minimization and renewable energy production. The aim of this study was to identify the key parameters for digester performance subjected to kinetic study and semicontinuous operation. Biochemical methane potential (BMP) tests were conducted in two different operating conditions: without mixing (WM) and continuous mixing (CM). Three different substrates, including food waste (FW), chicken dung (CD), and codigestion of FW and CD (FWCD) were used. Further kinetic evaluation was performed to identify mixing’s effect on kinetic parameters and correlation of the kinetic parameters with digester performance (volatile solid removal (VS%) and specific methane production (SMP)). The four models applied were: modified Gompertz, logistic, first-order, and Monod. It was found that the CM mode revealed higher values of Rm and k as compared to the WM mode, and the trend was consistently observed in the modified Gompertz model. Nonetheless, the logistic model demonstrated good correlation of kinetic parameters with VS% and SMP. In the continuous systems, the optimum OLR was recorded at 4, 5, and 7 g VS/L/d for FW, CD, and FWCD respectively. Therefore, it was deduced that codigestion significantly improved digester performance. Electrical energy generation at the laboratory scale was 0.002, 0.003, and 0.006 kWh for the FW, CD, and FWCD substrates, respectively. Thus, projected electrical energy generation at the on-farm scale was 372 kWh, 382 kWh, and 518 kWh per day, respectively. Hence, the output could be used as a precursor for large-scale digester-system optimization.

Monitoring and Analysis of Physical Exercise Effects Based on Multisensor Information Fusion

In this paper, multiple sensors are used to track human physiological parameters during physical exercise, and data information fusion technology is used to extract useful information for monitoring and analyzing the effects of physical exercise. This paper explores the interaction and developmental dynamics of multisensor information fusion technology and physical exercise data monitoring based on the interrelationship and interpenetration between the two. The design ideas and principles that should be followed for the software designed in this study are discussed from the perspective of the portable design of measurement instruments and the perspective of multisensor information fusion, and then, the overall architecture and each functional module are studied to propose a scientific and reasonable design model. The general methodological model to be followed for the development of this resource is designed, and the basic development process of the model is explained and discussed, especially the requirement analysis and structural design, and how to build the development environment are explained in detail; secondly, based on the course unit development process in this model, we clarify the limitations of the system through meticulous analysis of the measurement results, which provides a solid foundation for the next step of system optimization. Finally, with a focus on future development, we elaborate on the potential possible role and development trend of multisensor information fusion in the future period. In this paper, we propose to apply the multisensor data fusion algorithm to the monitoring, analysis, and evaluation of the effect of physical exercise, by collecting multiple human physiological parameters during physical exercise through multiple sensors and performing data fusion processing on the collected physiological parameters to finally evaluate the effect of physical exercise.

Numerical Investigation for Performance Enhancement of Photovoltaic Cell by Nanofluid Cooling

The cooling fluid is a key factor in cooling photovoltaic (PV) panels especially in the case of concentrated irradiance. Maintaining the panel at low temperature increases its efficiency. This paper investigates the usage of water-Al2O3 as a nanofluid for achieving the required cooling process. The particle concentrations and sizes are investigated to record their effect on heat transfer and pressure drop in the developing and developed regions. The research was performed using ANSYS CFD software with two different approaches: the single phase with average properties, and the discrete phase with the Eulerian-Lagrangian frame-work. Both approaches are compared to experimental results found in the literature. Both approaches show good agreement with the experimental results, with some advantage for the single-phase model both in processing time and in predicting heat transfer in the concentration range of 1-6% by volume. It was shown that, the heat transfer coefficient is greatly enhanced by increasing the particle concentration or decreasing the particle size. On the other hand, the usage of nanofluid causes a severe increase in the pumping power, especially with the increase in concentration and the reduction in particle size. Thus, a system optimization was suggested in order to raise the overall system efficiency for photovoltaic applications.

Construction of an Intelligent Analysis Model for Website Information Based on Big Data and Cloud Computing Technology

Based on big data and cloud computing technology, the development process of this system includes hardware cluster deployment of the delivery system, optimization of website delivery strategy, and development of the delivery management background system. The main functions in the following aspects are realized: first, we built the website back-end delivery subsystem and data collection and analysis subsystem to realize the control of website delivery and data collection; second, we designed and developed a process management subsystem for booking, management, and delivery of website resources and developed the contract management and order management subsystems to realize the accurate placement of user portraits on the website; then, the placement data monitoring and effect feedback subsystems, and the data inventory subsystem of the website system were designed and developed. Finally, based on the research of Android and based on the Eclipse platform, this article has completed the construction of the Android 4.0.3 version environment, successfully used the Java development language to develop a website information intelligent analysis and navigation system, and analyzed the various functional modules of the entire system. Experimental results show that the system not only realizes ordinary route and site query functions but also combines map API, integrates big data and cloud computing technology, and realizes congestion avoidance query, time optimal query, population heat map, and real-time viewing. The nearby use of this software’s personnel density distribution and other functions provides great convenience for personal travel, which can facilitate the real-time planning of travel plans, and has great practical and practical significance. Through the different levels of testing of various subsystems, the website delivery system meets the functional and nonfunctional requirements proposed by the network and on this basis realizes the use of group wisdom based on Pearson correlation coefficient, Cosine similarity, and Tanimoto coefficient for collaborative filtering website recommendation algorithm.