Amount Of Power Research Articles

A novel smart irrigation framework with timing allocation using solenoid valves and Arduino microcontroller

Irrigation in agriculture is the most common way of providing water to agricultural land or fields at normal stretches through channels and embedded platforms with the internet of things (IoT), to upgrade rural development. In this paper, the arrangement of the various types of irrigation systems and embedded platforms for agriculture was studied. The embedded platform can be designed in a suitable framework that can assist the irrigation system in growing more water-required crops. In this work, three relay switches, two solenoid valves, and one water pump source were connected to Arduino ESP32. The free version of Sinric Google Cloud was utilized significantly to control three devices namely, two solenoid valves using two relay switches and a water pump source using one relay switch. The experiment was executed in a prototype manner with timing allocation by considering two agricultural fields where water was supplied either in one field at a time and showed more prominent results to save time, replacement of manual valves, man intervention, power, and suitable quantity of water for more water-required crops namely, arecanut and coconut.

Ramp Rate Metric Suitable for Solar Forecasting

Solar irradiance forecasting plays a crucial role in integrating large quantities of intermittent solar power. Forecasting systems are commonly evaluated using metrics like root‐mean‐ square error (RMSE) and skill scores. However, these metrics aggregated over larger data sets do not adequately assess the prediction of ramp events, which are critical for many applications. This article introduces a novel, simple, and adaptable ramp rate metric that analyzes ramp events between successive lead times within forecasts. A case study on ramp rate mitigation in PV systems benchmarks suitable ramp thresholds for various solar irradiance components. The capabilities and limitations of deterministic and probabilistic forecasts from two all‐sky imager‐based models are evaluated for ramp prediction. A state‐of‐the‐art data‐driven vision transformer End2End model excels in RMSE and skill scores but performs poorly in ramp prediction. Conversely, a novel generative forecasting model combined with a convolutional neural network‐based irradiance model shows superior ramp prediction, achieving an F1 score of ≥0.7 for critical ramp events. This study underscores the importance of suitable ramp rate metrics and highlights the potential of generative models for enhancing ramp forecasting.

Two Energy-Efficient Backhauling Solutions for Small Cell Networks of 5G Using Green Communications

To meet the problem of ever-increasing wireless data congestion, the fifth-generation (5G) wireless communication system is projected to employ tiny cellphone networks for the needs of consumers heavily. One of the most significant elements of 5G networks will be sustainable interactions, as the quantity of power utilized by the information and communication technology (ICT) sector is expected to rise significantly by the end of the century. Therefore, scientists have focused much attention in recent years on developing strategies for designing small cell networks that use electricity optimistically. In addition, service providers need energy-efficient backing-up technologies to aid in using packed tiny cells. This research presents an interaction model that is well-suited to 5G HetNets and has a low power footprint. The model here accounts for an internet connection’s contact and backup portions. We create and present a mathematical framework to calculate the optimum number of tiny mitochondria that need to be maintained active at numerous hours of the day to minimize power consumption while still satisfying quality of service requirements set by customers. Our investigation into the backhaul’s electrical consumption led us to discover and put forward two energy-saving backing-up methods for 5G HetNets. Computer simulations show that the provided sustainable communication framework can reduce energy consumption by as much as 49% compared to the status quo.

Power Wheeling Pricing Considering Congestion in Power Network: A Review

Limited capacity of the power system infrastructure has a limiting effect on the quantity of electrical power that can be transmitted thereby resulting in the system been congested which also affects the quality of electrical energy supplied. Congestion is an undesired effect in power system with serious economic, reliability and security effect on power system infrastructure, which are yet to be adequately quantify in term of cost. Congestion occurrence and management on the power system network has been studied extensively, causes of congestion and various management techniques have been proposed which are at great financial consequences. While setting transmission wheeling prices, congestions are not adequately considered, nor are the management methods accurately financially compensated. Some wheeling pricing techniques however recognises the short coming and takes into consideration the financial cost of congestion and it’s management methods when setting their transmission wheeling costs. This paper is a review of wheeling methods that takes into consideration the cost of congestion and the management techniques when setting wheeling prices and makes a recommendation using financial and economic implication of the occurrence of congestion and the management techniques adopted in reducing the impact when setting wheeling prices, in order to encourage investment into the transmissions system infrastructures.

Vibration Analysis using Finite Element Analysis (FEA): An Evaluation of Pico-Tubular Bulb Type Turbine Blades Fabricated in Composite Materials

Tubular turbines have been widely employed and evolved fast when its introduction in the 1930s due to their strong technical and economic qualities and application. Because its performance and structure differ from those of ordinary vertical shaft units, local and international academics worked extensively on research techniques and technological means using numerical simulation and model testing. The transmissions of a high quantity of power, which may cause unwanted vibrations that reduce efficiency, increase wear, and, in the worst-case scenario, cause serious damage. In this paper, the material propose in order to substantiate that the random excitations and excess vibration of the pico-turbine can be prevented is the use of CFRP (carbon fiber reinforced polymer) and PLA (polylactic acid). In this paper, ANSYS® Mechanical modal simulation is used to evaluate the structures’ robustness behavior of the composite materials that were used as the main material in the fabrication of turbine blades for bulb-type turbine application. The use CFD simulation in SOLIDWORKS® is needed to examine the pressure fluctuation caused by unsteady flow that can contribute in the unwanted pulsation and to conform the modal simulation results. To validate the results, pressure pulsation experimentation is conducted to evaluate the fluctuation of the pressure affecting the blades or in the rotating region and it is analyzed through frequency response domain. Hence, in this paper, it is proven that the vibration behavior of the material is acceptable since the resulting natural frequency provides resulting stress, strain, and deformation that is allowable and below its ultimate tensile strength.

Efficacy of barium and calcium additives in lithium silicate glasses for nuclear shielding applications

This study presents a detailed investigation into the nuclear radiation shielding capabilities of lithium silicate (Li2O-SiO2) glass systems, specifically examining the impact of doping with barium oxide (BaO) and calcium oxide (CaO). Utilizing advanced simulation tools, including PAGEX and SRIM for charged particle interactions, and Phy-X/PSD for gamma-ray attenuation analysis, the radiation shielding effectiveness of BaO-based and CaO-based lithium silicate glasses were systematically compared. The gamma attenuation parameters (LAC, MAC, TVL, HVL, EBF, EABF, MFP, Zeff, Neff, FNRCS, and Zeq) of investigated glass samples were computed via the Phy-X/PSD program (15 keV-15 MeV energy). The HVL values vary between 0.007–14.203 cm, and the TVL values vary between 0.054–47.182 cm for all samples in the selected energy range. The highest and lowest values of FNRCS were observed for samples BaO20 and CaO5, with the values 0.093 and 0.1 cm−1, respectively. KERMAs were calculated using PAGEX software between the 1.5 keV and 20 MeV energy range, with the highest KERMA obtained for the BaO20 sample at 0.05 MeV and the lowest KERMA obtained for the CaO5 sample at the lowest density. The mass stopping power quantities were computed between 1 keV-10 GeV energy with PAGEX. The projected range values were calculated with SRIM codes. The lowest projected range values for both alpha particles and protons were obtained for the BaO20 sample with maximum density (3.391 g cm−3). The sample with BaO20 code showed better shielding potential for alpha and proton particles with lower values of projected range and mass stopping power. Findings reveal that the Li2O-BaO-SiO2 glass composition exhibits superior gamma-ray attenuation properties compared to its CaO-doped counterpart, with the BaO20 sample demonstrating particularly enhanced performance.

Oscillating water column wave energy converter arrays coupled with a parabolic-wall energy concentrator in regular and irregular wave conditions

Based upon previous research on a single, high-efficiency Oscillating Water Column (OWC) wave energy capture system (Mayon et al., 2021), this work further extends the numerical investigation to the layout design and performance of the wave energy convertor (WEC) array coupled with a parabolic, energy concentrating wall in both regular and irregular incident wave conditions. A heuristic method to identify the optimal siting of the component, cylindrical OWC WECs in the array, installed in the concave opening of the wall is presented. The most advantageous location of the chambers is found to lie on a parabolic curvature line which is inset from the wall. Two separate arrays composed of three and five component OWCs are investigated in a range of regular wave conditions. The hydrodynamic power and efficiency of each chamber in each of the arrays is determined, and subsequently the aggregated array performance is established. It is found that the primary OWC chamber in the array configuration can attain approximately the same hydrodynamic power output as a single, isolated OWC chamber located the parabolic wall focus, albeit with a narrower energy capture bandwidth. The secondary and tertiary component chambers in the arrays contribute a lesser, yet still considerable quantity of hydrodynamic power to the consolidated system. The cumulative hydrodynamic efficiency of the collective arrays is less than the hydrodynamic efficiency of a single OWC chamber at the wall focus, but more efficient than an isolated OWC chamber positioned in open-sea conditions. Moreover, the hydrodynamic efficiency of the arrays exhibits better stability across the range of incident wave periods investigated, denoting that the individual component chambers in the array are efficacious at different incident wave conditions. The five chamber array is comprehensively analysed in irregular incident wave conditions. The array system is demonstrated to maintain a high power output and efficient behaviour in irregular incident wave conditions-an effect attributable to the reflecting wall influence. In summary, the five-chamber array configuration yields a higher power output and improved stability in terms of efficiency performance when compared with the three-chamber array configuration in regular waves. The array maintains this exceptional performance in irregular incident wave conditions.

Synthesis of modeling and optimal management of smart grids

Smart grids may be characterized as the amalgamation of electrical grids, communication networks, specialized hardware, and computational intelligence (algorithms). This integration aims to oversee, regulate, and coordinate the generation, distribution, storage, and utilization of energy. Indeed, smart grid technologies have the potential to facilitate the distribution of substantial quantities of power generated from renewable sources. For this purpose, a comprehensive modeling approach is employed to simplify and enhance the feasibility of the task. It introduces a highly intricate system where modeling the components and relationships between entities proves challenging. Optimal energy management is necessary in this case. This paper provides a summary of an investigation into the modeling and optimal management of smart grids. In fact, this work allows a discussion of a hybrid system. Then we briefly introduce the domain of conceptual modeling within the enterprise.

Dorsal and median raphe neuronal firing dynamics characterized by nonlinear measures.

The dorsal (DRN) and median (MRN) raphe are important nuclei involved in similar functions, including mood and sleep, but playing distinct roles. These nuclei have a different composition of neuronal types and set of neuronal connections, which among other factors, determine their neuronal dynamics. Most works characterize the neuronal dynamics using classic measures, such as using the average spiking frequency (FR), the coefficient of variation (CV), and action potential duration (APD). In the current study, to refine the characterization of neuronal firing profiles, we examined the neurons within the raphe nuclei. Through the utilization of nonlinear measures, our objective was to discern the redundancy and complementarity of these measures, particularly in comparison with classic methods. To do this, we analyzed the neuronal basal firing profile in both nuclei of urethane-anesthetized rats using the Shannon entropy (Bins Entropy) of the inter-spike intervals, permutation entropy of ordinal patterns (OP Entropy), and Permutation Lempel-Ziv Complexity (PLZC). Firstly, we found that classic (i.e., FR, CV, and APD) and nonlinear measures fail to distinguish between the dynamics of DRN and MRN neurons, except for the OP Entropy. We also found strong relationships between measures, including the CV with FR, CV with Bins entropy, and FR with PLZC, which imply redundant information. However, APD and OP Entropy have either a weak or no relationship with the rest of the measures tested, suggesting that they provide complementary information to the characterization of the neuronal firing profiles. Secondly, we studied how these measures are affected by the oscillatory properties of the firing patterns, including rhythmicity, bursting patterns, and clock-like behavior. We found that all measures are sensitive to rhythmicity, except for the OP Entropy. Overall, our work highlights OP Entropy as a powerful and useful quantity for the characterization of neuronal discharge patterns.

Quick responding humidity sensor based on polyaniline/reduced graphene oxide composite

The relative humidity sensing response of the Polyaniline/ reduced Graphene Oxide (PRGO) composites has been explored in this present research work. For these observations, polyaniline (PANI), synthesised by the chemical oxidative polymerisation process, was physically blended using the different mass ratios of reduced graphene oxide (rGO). By the improved hummers method, graphene oxide (GO) is prepared, adding the minimal quantity of selenium power, and the GO was effectively and facilely reduced to rGO. By adding different weight per cent (wt%) of reduced Graphene oxide (rGO) to the polymer matrix, PRGO composites were prepared. Structural and morphological properties of rGO were confirmed by XRD, RAMAN, FTIR, SEM, EDX, and HR-TEM (elementary mapping) characterisations. XRD, FTIR SEM and EDX proficiencies were employed to characterise the PRGO composites. For the humidity sensing determination, the sensing film of the PANI, rGO, and PRGO composites is groomed by loading the sample on an IDT substrate through a drop casting technique. The PRGO-3 composite has shown an epitome response and recovery of 3 and 4 s, respectively. The PRGO-3 composite has the most minored and less real sensitivity with a lower limit of detection (LOD). Also, the prepared PRGO composites have recorded less hysteresis and good linearity and depicted exact stability over PANI and other PRGO composites. The physical parameters for PRGO composites were also calculated to determine the potentiality of a perfect sensor. The sensing mechanism also hashed out based on establishing chemisorption and physisorption layers.

Design of a Stand-Alone Photovoltaic (PV) System for a Three-Bedroom Apartment in Mubi, Adamawa State, Nigeria.

In the world today, electricity is also among the essential basic amenities of every human being because it drives the socio-economic activities of any country. More than 1.3 billion of the populations across the globe are living with low or no source of electricity. The lack of accessibility to electric power to this population brought an existence of a wide gap in current energy sources and this affected the growth of such population mostly residing in remote settlements of developing nations. Electrical energy is a significant feature for the economic and developmental advancement in every nation. Even with the abundance of many sources of energy (conventional and non-conventional sources) around the world and in Nigeria, there are still problems in accessing electricity which could be attributed to its generation, transmission, or distribution. These challenges hinder the socio-economic advancement of a country. About 95 million (55 % of Nigeria's population) Nigerians are living with no supply of electricity and the total power/electricity produced, there is about 30-35 % loss in the generated energy from transmission and distribution. This research studied the possibility of electrifying a three-bedroom apartment in Mubi's high residential layout using a solar photovoltaic system through the adoption of HOMER Software. The parameters/data used in this research work were obtained from the basic appliances usually found in an average household and from works of literature on studies performed on energy utilization in some residential areas in Nigeria, taking into consideration their power ratings, quantity, and solar component prices. These and some design considerations like system fixed capital operation and maintenance cost of ₦ 4,000 per year, project lifetime of 20 years, system fixed capital cost, discount rate of 9 %, average solar radiation data, coordinate of Mubi, among other parameters were applied in the HOMER software for the design, simulation and optimized results obtained. The optimized results indicate that a solar PV array of 5 kW comprising 25 solar panels of 200 W each, 10 sets of 12 V / 220 Ah batteries, and a 5000 VA inverter with charger are sufficient to accommodate the load of 16.086 kWh/day. The cost of energy (COE) with a 100 % renewable fraction is ₦ 410.94 / kWh.

Development of a smart powering system with ammonia fuel cells and internal combustion engine for submarines

The current limitations of hydrogen storage technology in submarines have prompted the need for alternative solutions. One promising option is the use of ammonia, a readily stored fuel. This paper presents an innovative, integrated system that runs on ammonia and does not rely on atmospheric air. The system combines Direct Ammonia Fuel Cell (DAFC) stack and an Internal Combustion Engine (ICE) technology to generate power, freshwater, and cooling. The system also recovers waste heat and utilizes it efficiently to produce these useful outputs. The study further aims to assess the system's performance using energy and exergy analysis methods and to conduct a parametric analysis to examine the impact of parameters and operating conditions on system efficiency. In the developed integrated system, the quantities of net power produced, cooling provided, and freshwater flow rate produced under specified conditions are 4069 kW, 589.5 kW, and 1.269 kg/s, respectively. Its energy and exergy efficiency were found to be 38.58% and 44.77%, respectively. The analysis study also obtains that increasing the ammonia flow rate supplied to the ICE and the steam flow rate provided to the turbine, as well as the reference temperature, could potentially improve both energetic and exergetic efficiencies.

Order parameter dynamics in complex systems: From models to data

Collective ordering behaviors are typical macroscopic manifestations embedded in complex systems and can be ubiquitously observed across various physical backgrounds. Elements in complex systems may self-organize via mutual or external couplings to achieve diverse spatiotemporal coordinations. The order parameter, as a powerful quantity in describing the transition to collective states, may emerge spontaneously from large numbers of degrees of freedom through competitions. In this minireview, we extensively discussed the collective dynamics of complex systems from the viewpoint of order-parameter dynamics. A synergetic theory is adopted as the foundation of order-parameter dynamics, and it focuses on the self-organization and collective behaviors of complex systems. At the onset of macroscopic transitions, slow modes are distinguished from fast modes and act as order parameters, whose evolution can be established in terms of the slaving principle. We explore order-parameter dynamics in both model-based and data-based scenarios. For situations where microscopic dynamics modeling is available, as prototype examples, synchronization of coupled phase oscillators, chimera states, and neuron network dynamics are analytically studied, and the order-parameter dynamics is constructed in terms of reduction procedures such as the Ott–Antonsen ansatz, the Lorentz ansatz, and so on. For complicated systems highly challenging to be well modeled, we proposed the eigen-microstate approach (EMP) to reconstruct the macroscopic order-parameter dynamics, where the spatiotemporal evolution brought by big data can be well decomposed into eigenmodes, and the macroscopic collective behavior can be traced by Bose–Einstein condensation-like transitions and the emergence of dominant eigenmodes. The EMP is successfully applied to some typical examples, such as phase transitions in the Ising model, climate dynamics in earth systems, fluctuation patterns in stock markets, and collective motion in living systems.

Virtual Instrumentation Applied to Calculation of Electrical Power Quantities in Single-Phase Systems

This paper presents a low cost virtual instrumentation platform. It is used in single-phase systems in order to calculate electric power quantities and indicators defined in IEEE Std. 1459-2010. The algorithm used to calculate the power quantities and indicators are based on synchronous reference frame, which is used to implement the definitions presented in IEEE Std. 1459-2010 under sinusoidal and nonsinusoidal utility conditions. To confirm the theoretical development, experimental results are presented by means of a versatile power monitoring system using a graphic platform, in which the apparent, active and nonactive powers can be viewed and analyzed, as well as the indicators.

Sustainable utilisation of rice husk for cleaner energy: A circular economy between agricultural, energy and construction sectors

Global research focuses on cleaner and sustainable energy alternatives like biomass due to the limited availability of coal and high CO2 emissions associated with coal combustion. Rice husk-based electricity generation is hindered by the absence of cogeneration facilities in rice mills. Rice (Oryza sativa) cultivation is wide-spread and constructing several biomass plants at various locations is uneconomical. Hence, instead of using as biomass, rice husk is field burnt as a method of disposal. Construction of only few rice cogenerations facilitates and using already existing sugar mills and coal based thermal plants cogeneration facilities in a combined way is cost-effective and sustainable solution. Therefore, the present study examines the synergistic utilisation of sugar mills, coal-based power plants and only few newly proposed biomass power plants for effective combustion of rice husk. Maharashtra, one of the largest states in India is considered as the study area. Already existing 181 sugar mills, 18 thermal power plants are considered in 36 districts of Maharashtra state. Site suitability analysis was performed using a multi-criteria decision-making technique and ArcGIS. Furthermore, sensitivity analysis was conducted to assess the robustness of the suitability index values. From the analysis, it is found that nine districts require new biomass power plants. In remaining 27 districts use of already existing cogeneration facilities at sugar mills and coal-based power plants are found to be economical than new plants. In addition, 98.7 % of carbon emission was reduced when rice husk is used instead of coal for generating the equivalent quantity of power.

Generic approach to assess the measuring performance of total-radiated power quantities by multi-channel resistive bolometer diagnostics on fusion experiments.

On present-day magnetic-confinement fusion experiments, the performance of multi-channel bolometer diagnostics has typically evolved over time through experience with earlier versions of the diagnostic and experimental results obtained. For future large-scale fusion experiments and reactors, it is necessary to be able to predict the performance as a function of design decisions and constraints. A methodology has been developed to predict the accuracy with which the volume-integrated total radiated power can be estimated from the measurements by a resistive bolometer diagnostic, considering, in particular, its line-of-sight geometry, étendues of individual lines of sight, bolometer-sensor characteristics, and the expected noise level that can be obtained with its electronics and signal chain. The methodology depends on a number of assumptions in order to arrive at analytical expressions but does not restrict the final implementation of data-processing of the diagnostic measurements. The methodology allows us to predict the performance in terms of accuracy, total-radiated power level, and frequency or time resolution and to optimize bolometer-sensor characteristics for a set of performance requirements. This is illustrated for the bolometer diagnostic that is being designed for the ITER experiment. The reasonableness, consequences, and limitations of the assumptions are discussed in detail.

Fundamental limits on radiative χ(2) second harmonic generation.

Recent advances in fundamental performance limits for power quantities based on Lagrange duality are proving to be a powerful theoretical tool for understanding electromagnetic wave phenomena. To date, however, in any approach seeking to enforce a high degree of physical reality, the linearity of the wave equation plays a critical role. In this manuscript, we generalize the current quadratically constrained quadratic program framework for evaluating linear photonics limits to incorporate nonlinear processes under the undepleted pump approximation. Via the exemplary objective of enhancing second harmonic generation in a (free-form) wavelength-scale structure, we illustrate a model constraint scheme that can be used in conjunction with standard convex relaxations to bound performance in the presence of nonlinear dynamics. Representative bounds are found to anticipate features observed in optimized structures discovered via computational inverse design. The formulation can be straightforwardly modified to treat other frequency-conversion processes, including Raman scattering and four-wave mixing.

Smart Demand Side Management for Techno-Economic Analysis of Microgrid System

The world uses about 20 trillion kilowatt hours of electricity annually. Because of this great level of necessity, the use of green energy is growing and is becoming more and more significant in today's society. Demand-side management (DSM) programs are described as the procedures for planning, carrying out, and overseeing the tasks assigned by electric utilities to encourage customers to adjust their loads and energy usage in order to reduce power consumption and lower their electricity costs. It is utilized in smart grid systems to balance energy generation and consumption in a way that benefits both customers and utilities, to achieve the goals of utility energy policies, and to modify the quantity and quality of power and electricity used. Customers should have the capacity to control their energy consumption, especially during peak usage, to enable them to make better informed decisions. Demand response (DR) and energy efficiency techniques were employed by DSM to assist energy users in lowering their consumption. to increase resilience, economy, sustainability, and efficiency. The main objective of this study is to apply two demand side management strategies, examine power flow analysis on distribution networks utilizing IEEE rules both before and after PV cells are integrated, and assess the impact of doing so. The approaches' practicality is confirmed by comparing the simulation results from one technique with the other. For the end user, lowering their electricity cost is their primary goal.

Investigation on the balance of Electricity and Quantity of Shanxi as an Electric Power Transmission base

With the proposal of a dual-carbon target, the issue of electricity balance may become a key limit to the efficient development of renewable energy in the Shanxi power grid. Therefore, the analysis of the Power and Peak Balance of the Shanxi Power Grid has become increasingly important. This paper constructed a mathematical mold for power and electricity balance. Then, with the traditional method with the platform method by comparing, the results of Shanxi’s electricity balance were analyzed. In the end, the feasibility of the platform method is applied in this paper. The results show the result of electricity and quantity of Shanxi electric power.

Energy, exergy and environmental impacts analyses of Pumped Hydro Storage (PHS) and Hydrogen (H2) energy storage processes

The objective of the present research is to compare the energy and exergy efficiency, together with the environmental effects of energy storage methods, taking into account the options with the highest potential for widespread implementation in the Brazilian power grid, which are PHS (Pumped Hydro Storage) and H2 (Hydrogen). For both storage technologies, energy pathways were envisioned, starting with electricity production from renewable sources (mostly intermittent ones), delivering more power than required during low-demand periods, and using the excess power, respectively, to pump water from the bottom to the top of hydroeletric powerplant lakes or to create gaseous H2 through water electrolysis. One and the other processes proceed with the energy recovery (re-electrification) stage, either utilizing traditional hydroelectricity technology or by combustion of H2 using latest gas turbines, when necessary, for ultimate consumption. The resources and emissions associated with both energetic pathways were investigated using the LCA (Life Cycle Assessment) approach, together with the latest established exergy-environmental methodologies and available data. It was considered that the identical quantity of stored power is re-electrified in the Pumped Hydro Storage situation. For an accurate comparison, it was also hypothesized that the same amount of energy a PHS could pump is electrically available for the Hydrogen storage case. With regard to energy and exergy efficiency, exergy costs of non-renewable, renewable, and total resources, in addition to the emissions cost of CO2 of both researched energy storage alternatives, numerical and comparative data were produced and presented. A sizable advantage for PHS is seen in the energy and exergy efficiency findings (more than 23 percentual points). The environmental exergy calculations for this scenario's findings show that PHS has benefits over H2 in that it uses only 84 % of the Hydrogen alternative's total resource exergy costs and emits 23 % less CO2.