Variable Supply Research Articles

Taking stock of caps on water use: fostering sustainability or falling short?

ABSTRACT Balancing water demands with available supplies on a scale that enables sustainable water use constitutes a complex governance challenge. Water managers face the daunting task of balancing water demands amidst variable supplies impacted by climate change and unsustainable extraction leading to drying lakes, depleted rivers, and shrinking aquifers. Traditionally, water managers have focused on bolstering water supplies to meet rising demands. However, this strategy is failing in many regions because of exorbitant costs, alongside environmental, legal, and political obstacles. Despite growing focus, no single solution ensures sustainable water use. Among governance options, capping water extractions holds theoretical promise, but evidence of their efficacy is limited and inconsistent due to shortcomings in their implementation, as detailed in this study. Our paper contributes to the literature on water governance by organizing empirical evidence of different types of caps. We developed a database to analyze 47 cases spanning 14 countries utilizing various types of caps (e.g., volumetric, water level limit, and moratorium) applied to different sources of water (e.g., aquifers, lakes, and rivers). We assess their efficacy in terms of enforceability, adaptability, and performance. We illustrate the strengths and weaknesses of capping as a water management strategy and offer recommendations to enhance its effectiveness.

Estimating time series semiparametric regression model using local polynomial estimator for predicting inflation rate in Indonesia

A model built from a parametric regression model and a nonparametric regression model is called a semiparametric regression (SR) model. The main problem in the SR model is the estimation of the regression function. In this study, we develop the SR model for time series data that is called Time Series Semiparametric Regression (TSSR) model, and discuss estimation of the TSSR model by using local polynomial. Also, we apply it to data of inflation rate (IR) in Indonesia where IR is as response variable, and both IR and money supply in the previous periods are as predictor variables. Next, we compare the results of estimating the IR using the TSSR with the classical method, namely the ARIMA. Also, the TSSR has high accurate criterion for predicting the IR in Indonesia. The results of this study are useful for analyzing Indonesia’s economic growth rate, which is one of the Sustainable Development Goals (SDGs)

Experimental investigation on the electrical and hydrogen-production performance of a novel PEM electrolyzer driven by CdTe PV with a tracking system

Addressing the challenges of intermittent and variable energy supply, solar hydrogen production via electrolysis has garnered significant attention due to its unique advantages, emerging as a hot topic in the scientific research domain. However, the application of this technology is currently mainly related to the non-tracking system, which undergoes a rapid change in solar irradiation during the day. To expand the matching relationship of solar irradiation, PV characteristics, and electrolyzer, this paper proposes the development of a Proton Exchange Membrane (PEM) electrolyzer driven by Cadmium Telluride (CdTe) photovoltaic (PV) modules with a tracking system for hydrogen production. An experimental platform was set up in Chengdu and the performance tests were carried out for different operating modes during summer. The experimental results demonstrate that the average electrical and hydrogen production efficiencies of the system are 13.11% and 7.88%, respectively, on a sunny day, with a total of 566.7 L of hydrogen produced within 7 h of operation. Furthermore, the solar irradiation received by the tracking surface of the system is significantly enhanced by 10.29% in comparison to the horizontal surface. On a cloudy day with an electrolyzer inlet water temperature of 45 °C, the system has the potential to achieve a hydrogen production efficiency of 11.15 %. At a constant current density of 1.0 A/cm2, the efficiency of the electrolysis process increased by 2.07% and 1.25% for each 10 °C increase in the temperature of the electrolyzer, having an inlet temperature of 35 °C. This study offers a novel approach for a PV-PEM system with a higher hydrogen production efficiency while also establishing a robust foundation for technology optimization and broader implementation.

Optimizing Microgrid Load Fluctuations through Dynamic Pricing and Electric Vehicle Flexibility: A Comparative Analysis

In the context of modern power systems, the reliance on a single-time-of-use electricity pricing model presents challenges in managing electric vehicle (EV) charging in a way that can effectively accommodate the variable supply and demand patterns, particularly in the presence of wind power generation. This often results in undesirable peak–valley differences in microgrid load profiles. To address this challenge, this paper introduces an innovative approach that combines time-of-use electricity pricing with the flexible energy storage capabilities of electric vehicles. By dynamically adjusting the time-of-use electricity prices and implementing a tiered carbon pricing system, this paper presents a comprehensive strategy for formulating optimized charging and discharging plans that leverage the inherent flexibility of electric vehicles. This approach aims to mitigate the fluctuations in the microgrid load and enhance the overall grid stability. The proposed strategy was simulated and compared with the no-incentive and single-incentive strategies. The results indicate that the load peak-to-trough difference was reduced by 30.1% and 18.6%, respectively, verifying its effectiveness and superiority. Additionally, the increase in user income and the reduction in carbon emissions verify the need for the development of EVs in tandem with clean energy for environmental benefits.

Distributed robust [formula omitted]asso-[formula omitted] based on [formula omitted]ash optimization for smart grid: Guaranteed robustness and stability

The integration of variable renewable energy supplies into smart grid energy management poses several obstacles to system operation. An efficient solution for resource management is essential to ensuring reliable operation. This research presents distributed robust Lasso-model predictive control (D − RLMPC) as a way to handle energy problems in a multi-layer and multi-time frame optimization method. The D − RLMPC is a hierarchical system that integrates a centralized supervisory management (SM) layer for long-term optimization with a distributed coordination management (CM) layer for short-term adaptation to high power fluctuations. The higher layer, known as the SM, is responsible for providing the grid operator with specific operating plans and offering guidance to the bottom layer, known as the CM. The CM is responsible for coordinating the interaction between the centralized optimization goals and the physical power system layer. Furthermore, a distributed extended Kalman filter (DEKF) is used to ascertain the inter-dependencies among subsystems. Next, an iterative approach based on Nash optimization is proposed to get the globally optimum solution of the whole system in a partly distributed manner. The simulation results demonstrate the effectiveness of the proposed control approach, which combines the advantages of centralized and distributed control to provide a comprehensive solution for the grid operating issue. To verify and assess the effectiveness of the suggested approach, the acquired outcomes are compared to those of the centralized robust, distributed robust, and distributedMPC approaches. The simulation findings confirm the practicality of using the suggested system to manage future smart grid assets.

Peculiarities of Arctic Ichthyofauna

An audit of the marine and freshwater ichthyofauna of the Arctic has been carried out. According to new data, the ichthyofauna of the Arctic is represented by 4 classes, 33 orders, 103 families, 251 genera and 479 species of cyclostomes and fish (or about 1% of the world fauna), of which 214 species or 45% of the number of species in the Arctic are true Arctic species. Arctic fish are characterized by polymorphism and euryphagy, which are associated with the variable and low food supply of northern water bodies. The ichthyofauna of the Arctic is well represented by taxa with a wide adaptive radiation (genera Coregonus, Salvelinus, Lycodes, etc.) and species with a complex intraspecific structure such as superspecies or species-complex. Another characteristic feature of the Arctic is low endemism of ichthyofauna at the level of families (5%), genera (2%) and species (10%). Possible routes of distribution of whitefish and pike in the water bodies of the North have been discussed.

Variable frequency constant pressure water supply system based on Siemens S-1200

Abstract This paper presents the design of an efficient, cost-effective, and intelligent variable frequency water supply control system. The system consists of a PLC, frequency converters, water pumps, pressure sensors, and other components to form a closed-loop control system. It enables closed-loop control of water pressure, ensuring a dynamic balance between water consumption and water supply. A user-friendly HMI is designed based on a software platform for easy operation by management personnel. It allows for seamless switching of the system’s operating modes and the running status of water pumps. Real-time display of pump operation and monitoring of system performance are also provided. Compared to traditional water supply methods, this system exhibits superior reliability, speed, and performance. It is capable of meeting the daily water consumption needs of residents in high-rise buildings.

Pengaruh Kebijakan Moneter dan Fiskal terhadap Pengangguran di Indonesia

The purpose of this study is to analyze the impact of monetary policy as seen from the BI Rate and the money supply (M2, and fiscal policy as seen from government spending and tax revenue in influencing the unemployment rate in Indonesia. The approach used in this research is quantitative. The data used are the BI Rate, the money supply (M2), government spending, tax revenue and unemployment in the form of time series data in an annual form from 1995 to 2019. The method used in this study is the Vector Auto analysis model. Regression (VAR). The stages used in this research test are a stationarity test, optimum lag test, VAR stability test, impulse response test, and variance decomposition test. The results of the impulse response indicate that the unemployment variable responds most to the shock of the interest rate variable (monetary policy) compared to other variables. The results of variance decomposition indicate that the contribution given by the BI Rate to the unemployment rate is the most significant relative to the contribution given by the variable money supply (M2), government spending, and tax revenue.

Food Banks as a "Treasure Trove": Users' Experiences of a Western Australian Food Relief Organization.

Food banks are providing crucial relief as food insecurity increases worldwide. While these services are essential for vulnerable populations, there is variability in foods available and users may experience poor nutritional quality, and an overabundance of discretionary foods, contributing to public health risks including overnutrition and obesity. Understanding how customers perceive food availability, variety, and quality is important to inform relief services and health interventions. This study reports the findings of a convergent parallel mixed-methods investigation of user experiences and perceptions of food availability, variety, and quality at a major food bank in Western Australia. Food bank customers (N = 207) at a food bank branch and mobile van locations completed a survey, with an option to complete a subsequent semi-structured interview (n = 15). Approximately 80% of the survey sample had low (48%) or very low (30%) food security, half of the sample had been using the food bank for longer than 6 months, and 77% reported the food bank as their first choice for food. Three-quarters (77%) reported financial barriers to a balanced diet in the past twelve months and described how limited availability and variety complicated shopping. Interviewees explained complex perceptions of these issues, including favouring healthy food while considering discretionary food as a "luxury" that enhanced their quality of life. Our findings suggest that food bank users experience barriers to maintaining a balanced diet, encounter variable supplies of healthy and nutritious foods, and have concerns about the impacts of frequent discretionary food consumption. These findings have implications for public health promotion.

Research on variable pressure oil supply servo system based on accumulator

Research on variable pressure oil supply servo system based on accumulator

Soil moisture-based irrigation interval and irrigation performance evaluation: In the case of lower kulfo catchment, Ethiopia

The lack of soil moisture-based irrigation intervals, poor distribution of irrigation water among users, and the time-based and spatial variability of water supply have been challenges for the productivity of irrigation schemes in the Lower Kulfo catchment, Southern Ethiopia. This study was conducted to develop soil moisture-based irrigation intervals and to evaluate irrigation water delivery and field level irrigation efficiencies. Soil water content, and flow along the canal and in the field were measured directly, and irrigation duty was estimated by using CropWat 8 model. To minimize water stress or excess problems, irrigation needs to be applied when soil water content drops to 35.7 % for onion and pepper, 34.4 %% for watermelon, and 32.5 % for wheat and maize from field capacity. However, irrigation was applied at 36.2 % for onion, 35.4 % for watermelon, 36.4 % for pepper, 36.2 % for maize, and 35 % for wheat in the existing irrigation scheme that increased irrigation amount in the field. The average percentage of soil moisture depletion (p) at time of irrigation was 27.4 %, which was below the recommended value. The average adopted irrigation and design irrigation interval were 4 & 6 days for onion and pepper, 5 & 7 days for watermelon and wheat, and 6 & 7 days for maize, respectively. The mean irrigation adequacy and dependability of the irrigation scheme in the lower Kulfo catchment were 1 & 0 for Arba Minch irrigation scheme, 0.5 & 0.2 for Arba Minch University farmland, 0.4 & 0.25 for private farmland and 0.1 & 0.43 for Kollashara farmland, respectively. The value of irrigation equity was 0.7 in January, 0.6 in February, and 0.8 in March which indicates the highly temporary variation of irrigation adequacy. The mean value of canal conveyance was 82.7 % and the average on-farm irrigation efficiency also was 56.6 %. The average value crop yield in the present study were 0.5ton/ha for wheat, 4.9ton/ha for onion, 6.2ton/ha for pepper, 0.6ton/ha for watermelon, 4.2ton/ha for maize that was very low compared with other control irrigation in the study area. Inadequate soil moisture-based intervals, inequitable water distribution, and variable supply hinder irrigation in the Lower Kulfo catchment; adopting optimized practices and robust management can enhance efficiency, equity, and crop productivity.

Drainage reorganization and alluvial architecture of endorheic basins: The Lower Cretaceous record of the Chubut Group in the Golfo San Jorge Basin (Patagonia, Argentina)

The size, shape, and organization of depositional systems in endorheic basins are controlled by the tectonic and climatic history of the sedimentary basin and its boundaries. We evaluate the changes in the alluvial architecture of the Matasiete (Aptian) and Castillo (Albian) formations of the Chubut Group (Cretaceous) in the endorheic Golfo San Jorge Basin (Patagonia, Argentina) analyzing a ∼150 km transect along the San Bernardo Fold Belt, subsurface data, and coeval fluvial successions of the Los Adobes Formation in the nearby Cañadón Asfalto Basin. The Aptian Matasiete Formation represents an externally-sourced, high-accommodation fluvial system with its headwaters in the current Cañadón Asfalto Basin, flowing toward the alkaline lake of the Pozo D-129 Formation through N–S oriented sedimentary corridors of tectonic origin. Low sinuosity, fixed channels with ribbon geometries (mean thickness 7.3 m, W/T ratio 14) are encased in red-colored floodplain fines, whereas stratigraphic intervals rich in resedimented tuffs contain braided rivers with W/T ratio up to 90. Deposition of the overlying Albian Castillo Formation occurred in a W-E elongated basin disconnected from the Cañadón Asfalto Basin, comprising aggradational, volcaniclastic floodplain deposits and smaller-scale fluvial channels of narrow-sheet geometries (mean thickness ∼ 3m, mean W/T ratio 45). The Castillo Formation shows spatial variation in fluvial styles and channel sizes, with intermittent to ephemeral rivers of small scale near the headwaters and seasonal, perennial rivers in downstream positions. Alluvial architecture changes between the Matasiete and Castillo formations reflect changes in the configuration of the basin boundaries, subsequent re-organization of the channel networks, and variable supply of volcaniclastic particles to drainage catchments of different hierarchy that evolved in areas with large variation of the preserved thickness. Comparable geomorphic scenarios in the Okavango Macrobasin show multiple base levels (lacustrine, ephemeral pans), several drainage catchments of variable orientation, scale, and behavior (perennial, intermittent to ephemeral), and exotic rivers adjacent to minor-scale courses.

Hardware-in-the-Loop Emulation of a SEPIC Multiplier Converter in a Photovoltaic System

This article presents the development and execution of a Single-Ended Primary-Inductor Converter (SEPIC) multiplier within a Hardware-in-the-Loop (HIL) emulation environment tailored for photovoltaic (PV) applications. Utilizing the advanced capabilities of the dSPACE 1104 platform, this work establishes a dynamic data exchange mechanism between a variable voltage power supply and the SEPIC multiplier converter, enhancing the efficiency of solar energy harnessing. The proposed emulation model was crafted to simulate real-world solar energy capture, facilitating the evaluation of control strategies under laboratory conditions. By emulating realistic operational scenarios, this approach significantly accelerates the innovation cycle for PV system technologies, enabling faster validation and refinement of emerging solutions. The SEPIC multiplier converter is a new topology based on the traditional SEPIC with the capability of producing a larger output voltage in a scalable manner. This initiative sets a new benchmark for conducting PV system research, offering a blend of precision and flexibility in testing supervisory strategies, thereby streamlining the path toward technological advancements in solar energy utilization.

State-of-the-art review on hydrogen's production, storage, and potential as a future transportation fuel.

Global energy consumption is expected to reach 911 BTU by the end of 2050 as a result of rapid urbanization and industrialization. Hydrogen is increasingly recognized as a clean and reliable energy vector for decarbonization and defossilization across various sectors. Projections indicate a significant rise in global demand for hydrogen, underscoring the need for sustainable production, efficient storage, and utilization. In this state-of-the-art review, we explore hydrogen production methods, compare their environmental impacts through life cycle analysis, delve into geological storage options, and discuss hydrogen's potential as a future transportation fuel. Combining electrolysis to make hydrogen and storing it in porous underground materials like salt caverns and geological reservoirs looks like a good way to balance out the variable supply of renewable energy and meet the demand at peak times. Hydrogen is a key component of our sustainable economy, and this article gives a broad overview of the process from production to consumption, touching on technical, economic, and environmental concerns along the way. We have made an attempt in this paper to compile different methods for the production of hydrogen and its storage, the challenges faced by current methods in the manufacturing of hydrogen gas, and the role of hydrogen in the future. This review paper will serve as a very good reference for hydrogen system engineering applications. The paper concludes with some suggestions for future research to help improve the technological efficiency of certain production methods, all with the goal of scaling up the hydrogen economy.

Artificial intelligence applications for enhancing organizational excellence: Modifying role of supply chain agility

The study’s goal was to demonstrate the modifying role of supply chain agility in the impact of artificial intelligence applications on organizational excellence in Jordanian e-commerce companies. The analytical and descriptive approach was adopted. The study population consisted of 160 companies operating in the e-commerce sector in Jordan. The sample comprised 400 respondents working in senior and middle management positions. The questionnaire was utilized to collect the data. The results showed an impact of artificial intelligence applications in all dimensions (expert systems and neural networks) on the organizational excellence of e-commerce companies in Jordan. The value of the adjusted coefficient of determination (Adj. R2) was .265%. Based on the model’s F value (4.1190) and its level of significance (P; 0.00), the impact of these techniques on organizational excellence is statistically significant. Additionally, the results displayed an impact of supply chain agility on improving the impact of artificial intelligence applications on organizational excellence. The value of the degree of influence ß after introducing the modified variable supply chain agility and the value of R Square increased by .11 at the significance level (Sig). = 0.000. This study recommended training workers to stay up to date with developments in artificial intelligence, expert systems, and neural networks in their operations, control of searching for this evidence within databases, and knowledge representation.

Megawatts to methane – a deep drop in emissions reduction transition for existing regional gas-based ammonia plants

Synthetic ammonia production sustains food production for more than half of the world’s population. Many regional ammonia plants convert all ammonia to ammonium nitrate fertiliser. With these, all carbon in the feed ends up as carbon dioxide (CO2), with around 2 tonnes of CO2 released per tonne of ammonia produced using natural gas. Conveniently, ammonia plants produce a substantial pre-concentrated CO2 stream. Ammonia plants are high-capex, long-life assets that operate for 40+ years. With the energy transition, replacing such assets is very high cost and will dramatically impact the cost of food production. Further, green energy is highly variable, leading to the need for additional supply side assets to stabilise energy supply. This paper outlines a transition approach for a 30% CO2 reduction (also a 43% case) to extend the useful life of these assets while re-using much of the plant, with the ability to turn on/off the green energy with minimal disruption for stable operation. The example plant is based on a typical 750 tpd ammonia gas Steam Methane Reforming (SMR) plant. The approach considers adding and integrating green power and biogas into this plant to reduce net reportable CO2 emissions. Methanation of CO2 has been demonstrated in several projects and is considered key in developing a transition pathway for an existing gas-based plant, extending its operational life and flexibility to operate with varying degrees of variable green energy supply. Further, whilst Synthetic Natural Gas (SNG) is used in this case, the approach can be beneficially applied with methanol and other Power-to-X opportunities.

Impacts of magnitude and texture of variable sediment supply on bedload transport

Impacts of magnitude and texture of variable sediment supply on bedload transport

Role of smart charging of electric vehicles and vehicle-to-grid in integrated renewables-based energy systems on country level

The energy transition based on variable renewable energy sources raises concerns on satisfying the electricity demand at all hours of a year, which is amplified by the ongoing energy system electrification. Balancing variable electricity supply and inelastic demand requires additional sources of flexibility in the system: flexible electricity generation, energy storage, grids, flexible demand, and overall sector coupling. Electrification of transport increases the electricity demand; however, it offers the opportunity to use additional low-cost flexibility from electric vehicles batteries. The LUT Energy System Transition Model was modified to model the smart charging and vehicle-to-grid functionality of electric vehicles in integrated energy systems. The results show that, in countries with a large fleet of electric vehicles, smart charging and vehicle-to-grid allow for a substantial reduction of energy storage requirements, reducing the electricity and heat storage capacity by 35% and 25%, respectively and leading to 4% lower system cost. Flexible operation of electrolysers required for e-fuels synthesis have a similar effect and, in combination with smart charging and vehicle-to-grid, can lead to 8% lower system cost. The impact of vehicle-to-grid naturally depends on assigned operational cost; however, it contributes to system cost reduction even at high costs of 50 or 100 €/MWh.

Hybrid Intelligent Control System for Adaptive Microgrid Optimization: Integration of Rule-Based Control and Deep Learning Techniques

Microgrids (MGs) have evolved as critical components of modern energy distribution networks, providing increased dependability, efficiency, and sustainability. Effective control strategies are essential for optimizing MG operation and maintaining stability in the face of changing environmental and load conditions. Traditional rule-based control systems are extensively used due to their interpretability and simplicity. However, these strategies frequently lack the flexibility for complex and changing system dynamics. This paper provides a novel method called hybrid intelligent control for adaptive MG that integrates basic rule-based control and deep learning techniques, including gated recurrent units (GRUs), basic recurrent neural networks (RNNs), and long short-term memory (LSTM). The main target of this hybrid approach is to improve MG management performance by combining the strengths of basic rule-based systems and deep learning techniques. These deep learning techniques readily enhance and adapt control decisions based on historical data and domain-specific rules, leading to increasing system efficiency, stability, and resilience in adaptive MG. Our results show that the proposed method optimizes MG operation, especially under demanding conditions such as variable renewable energy supply and unanticipated load fluctuations. This study investigates special RNN architectures and hyperparameter optimization techniques with the aim of predicting power consumption and generation within the adaptive MG system. Our promising results show the highest-performing models indicating high accuracy and efficiency in power prediction. The finest-performing model accomplishes an R2 value close to 1, representing a strong correlation between predicted and actual power values. Specifically, the best model achieved an R2 value of 0.999809, an MSE of 0.000002, and an MAE of 0.000831.

Effects of thermoelasticity induced aperture variation on performances of Enhanced geothermal system

Geothermal energy, as one of the renewable energy types, has great potential to balance the variable energy supply from photovoltaic and wind energy types. This, however, requires the development of an Enhanced Geothermal System (EGS). Injecting cold water into deep geo-reservoirs induces thermoelastic deformation and changes the fracture apertures, which may significantly affect the EGS lifetime and energy performance. In this case, this study develops a fully coupled thermal–hydraulic-mechanical model to investigate the impacts of temperature, pressure, and aperture heterogeneity on the alterations of fracture aperture. Then, considering the reservoir lifespan, the research takes a further step into the influence of heterogeneous aperture variation on EGS production temperature and long-term energy performance. Results show that aperture significantly varies once a temperature breakthrough occurs in the production well for both homogeneous and heterogeneous aperture fields. The thermoelasticity-induced aperture variations enhance water flow rate, leading to a considerable increase in reservoir heat production rate, but a shorter EGS lifespan. Furthermore, temperature variation shows a more substantial influence on aperture alteration compared to pressure change. Additionally, a sensitivity analysis indicates that the 30-year total energy output is proportional to the injection/production pressures and injection temperatures. However, the fracture with either excessively large or small initial apertures leads to worse EGS energy performance.