Utility Supply Research Articles

Recent progress in iron and steel industry decarbonization strategies: industrial advancements and challenges.

The iron and steel industry is widely acknowledged as a carbon-intensive sector, contributing significantly to greenhouse gas emissions. As the global demand and production of iron and steel continue to rise, the early implementation of low-carbon and zero-carbon strategies to expedite the decarbonization processes in the iron and steel industry is paramount for achieving the Intergovernmental Panel on Climate Change (IPCC)'s 2 ℃ climate goal. This article provides a comparative evaluation of recent low-carbon and zero-carbon strategies applied in the iron and steel industry, focusing on the fossil carbon reduction, end carbon utilization, auxiliary strategies, and international supply chain relocation. It delves into the practical manifestations, untapped possibilities, and prevailing challenges associated with these strategies' industrial implementation. Furthermore, it assesses and compares the current carbon-saving potential of the strategies within the global iron and steel industry. The results show that, despite a large industrial scale, low-carbon strategies in iron and steel have a limited emission reduction capacity of up to 55%. While zero-carbon strategies offer higher potential (95-100% reduction), they are still nascent and not widely used. Meeting the IPCC's 2 ℃ target by 2050 with current strategies alone is challenging. Hence, scaling up zero-carbon strategies quickly and expanding low-carbon ones in the long run are critical for iron and steel's carbon neutrality.

Time is money: An analysis of cost drivers in ambulatory sinus surgery.

Functional endoscopic sinus surgery (FESS) is one of the most commonly performed otolaryngologic procedures and is associated with significant cost variability. We performed a retrospective analysis of all inflammatory sinus surgeries at a single tertiary care medical center from July 2021 to July 2023. The electronic medical record was reviewed for patient factors and cost variables for each procedure, and multivariable analysis was performed. A total of 221 patients were included in analysis with a mean age of 48.2 years. There was a 44.8% incidence (n=99) of nasal polyps and 31.2% (n=69) of cases were revision surgeries. The average total cost for the surgical encounter was $8960.31 (standard deviation $1967.97). Operating room time represented $4912.46 (54.8% of all costs), while average operating room supply costs were $1296.06 (14.5%) and recovery room costs were $919.48 (10.3%). Total costs were significantly associated with length of surgery ($7.83/min, p=0.04), in addition to presence of nasal polyps ($531.96, p=0.04). There was no significant association between total costs and the remaining clinical and demographic factors. Costs associated with ambulatory FESS for inflammatory sinus disease vary across patients and this cost variability is predominantly driven by time efficiency within the operating room, as well as supply utilization and nasal polyposis to a lesser degree. As a result, operating room efficiency represents a primary target for cost-related interventions. Additionally, our data provide a framework for surgeons and hospitals to make evidence-based decisions on intraoperative equipment in a tradeoff between efficiency and supply costs. Our findings indicate that an approach focused on streamlining efficiency across the entire ambulatory surgery encounter will have the greatest impact on reducing healthcare expenses for both the patient and the health system.

A Real-Time Hierarchical Energy Management Strategy for FTPSS to Improve the PV/RBE Utilization and Power Supply Quality

A Real-Time Hierarchical Energy Management Strategy for FTPSS to Improve the PV/RBE Utilization and Power Supply Quality

Intelligent current-speed soft-starting controller for an induction motor drive system

In industry, three-phase induction motors (IMs) are the most used motors. IMs’ high starting supply current and large accelerating torque make their starting process a potential source of unnecessary energy waste, especially when it is repeated. To overcome the starting problems of an IM, an intelligent soft-starter controller based on an artificial neural network (ANN) is proposed. The controller contains two soft starting control schemes namely, current and speed controls. That allows one to select the soft starting control scheme based on the load requirements and/or supply utility capability. Current and speed controls are to keep the motor's starting current and accelerating torque constant at a specified level, respectively. That is achieved by selecting the appropriate firing angles for the thyristors in the soft starter. The online determination of the thyristor firing angles is resolved through the application of the ANN approach. First, the ANN models for two control techniques are developed using a MATLAB Neural Network Toolbox for training. Based on the current-speed and torque-speed characteristics, two ANN models are trained for a range of thyristor firing angles. Secondly, the ANN models of two control schemes are implemented using MatLab/Simulink for a 3kW three-phase IM. A variety of simulation tests prove that a validation on control technique's effectiveness under various load conditions (no-load, pump, constant, and linear loads) and reference values exists. The least inrush current and smooth acceleration are obtained with two control schemes.

Analyzing economic inflation's impact on food security and accessibility through econometric modeling

This study investigates the impact of economic inflation on food security and accessibility through the development of an econometric modeling approach. As inflation rates rise, the purchasing power of consumers diminishes, leading to increased food prices and potentially exacerbating food insecurity. This research aims to quantify the relationship between inflation and food security indicators, such as availability, access, utilization, and stability of food supplies. By employing time-series data and econometric techniques, the model captures the dynamic interactions between inflation rates, food prices, and socioeconomic factors affecting food security. The model incorporates key variables, including consumer price index (CPI), food inflation, income levels, and unemployment rates, to analyze their collective impact on food security across different demographics. The findings indicate that rising inflation significantly correlates with higher food prices, disproportionately affecting low-income households and vulnerable populations. This relationship highlights the necessity of understanding inflation's broader implications on food accessibility, especially in regions where food security is already a pressing issue. Future research directions are proposed, focusing on policy interventions aimed at stabilizing food prices and enhancing food security. Potential strategies include price controls, subsidies for staple foods, and targeted social safety nets for low-income households. Additionally, the study suggests further examination of supply chain factors contributing to food price volatility, such as transportation costs and global market dynamics, which can exacerbate inflation's effects on food security. This research contributes to the literature on food security by providing empirical evidence of inflation's impact on food accessibility and identifying critical areas for policy intervention. By addressing the complex interplay between inflation and food security, stakeholders, including policymakers and food industry leaders, can develop informed strategies to mitigate adverse effects and promote food security in inflationary environments.

IoT-Enabled Cross-Platform Applications for Real-Time Logistics Monitoring

Internet of Things (IoT)The integration of Internet of Things (IoT) technology and cross-platform mobile applications has revolutionized real-time logistics monitoring, enabling unprecedented visibility, efficiency, and proactive management of supply chain operations. This article explores the key components of IoT-enabled logistics monitoring, including IoT sensors, data integration, real-time tracking, automated notifications, predictive maintenance, and proactive supply chain management. The benefits of implementing these solutions are highlighted, such as reduced risks, optimized routes, improved operational efficiency, and enhanced customer satisfaction. The article also discusses the challenges associated with IoT implementation, including data integration, connectivity, security, and privacy, and provides strategies for overcoming these obstacles. Through real-world case studies, the tangible impact of IoT-enabled cross-platform applications in logistics is demonstrated, showcasing the potential for significant improvements in cost savings, asset utilization, and overall supply chain performance. As the IoT landscape continues to evolve, the adoption of these technologies will become increasingly critical for logistics providers looking to maintain a competitive edge in the market.

Clustering Analysis of Food Security, Waste and Loss: Malaysia Agricultural Insights

As the world population grows rapidly nowadays, the demand for food has come to rise. The escalating demand for food has caused substantial wastage and loss, which not only hampers food security efforts but also aggravates greenhouse gas (GHG) emissions, intensifying the environmental crisis. Among numerous countries, Malaysia, with its diverse agricultural profile, emerges as a good fit for our case study. This study chooses the clustering technique to examine food sector data in Malaysia and investigate the link between the clustering results on food data and the data on GHG emissions. This case study aims to find crops depending on their production efficiency, underline those that match major waste, and estimate their contribution to greenhouse gas emissions. Three clustering techniques, Gaussian Mixture Modelling (GMM), Birch, and Density Peak clustering, are applied in the Production and Supply Utilisation Accounts (SUA) datasets, help to identify and cluster crops based on their similar traits to acquire uncovered patterns between the food sector and environmental issues. Using cutting-edge clustering algorithms and visualization tools, this study investigated in-depth the complex interactions among food production, waste, and greenhouse gas emissions in Malaysia. By addressing food production efficiency and waste reduction, the outcome will be a cascade of benefits that not only improve food security but also help to lessen negative environmental effects. This study illuminates the multifaceted dynamics of food production, waste, and environmental impact, offering valuable insights and pathways toward a more sustainable future for Malaysia and potentially other nations.

Low carbon economic scheduling of integrated energy system with concentrating solar power and multi-stage hydrogen utilization based on ladder-type carbon trading

ABSTRACT As the energy crisis and the greenhouse effect intensify, developing a sustainable and clean energy system is particularly important. How to increase the utilization of clean energy and reduce carbon emissions is a pressing issue. To this end, an integrated energy system (IES) framework incorporating multi-stage hydrogen utilization and concentrated solar power (CSP) has been developed. This study optimizes the scheduling of the IES using a ladder-type carbon trading method to optimize the output of each unit, thereby achieving low-carbon economic operation. The research investigates the conversion and utilization among multiple heterogeneous energy flows, including electricity, heat, gas, and hydrogen, with a focus on the integration of multi-stage hydrogen utilization and CSP heat supply, and the interconnections among different units. Four comparative cases are established to evaluate the proposed IES framework in reducing the totalcost, mitigating renewable energy curtailment, and lowering carbon emissions. The results show that the proposed IES framework presents optimal results, with a total cost reduction of 19.74% and a carbon emission reduction of 36.79 tons, no new energy waste, and high carbon benefits. The proposed IES framework facilitates flexible and efficient distribution of multiple energy types, meeting energy demands while enabling multi-energy complementarity and feasibility.

Prediction and Evaluation of Industrial Land Intensive Use: Adding Policy Impact to System Dynamics Model

Nowadays, urban development prioritizes improving quality over mere quantitative expansion, which requires a shift in land use from previous extensive use patterns to a more refined and efficient intensive use pattern. The intensive use of industrial land (IUIL) is a resource-utilization strategy for industrial land that aims at maximizing the dual growth of ecological and economic benefits by minimizing resource consumption and factor costs. In this research, IUIL is deconstructed into four aspects: input intensity, utilization intensity, economic benefits, and environmental benefits. Grounded in a qualitative analysis of the interconnected casual feedback among the various factors influencing IUIL, a system dynamics model with 36 indicators for IUIL evaluation and prediction is constructed. Policy impacts on IUIL from the supply side, utilization side, and supervision side are analyzed and embedded for a scenario simulation based on the theory of the entire life cycle of land use. The simulation shows its efficiency in reporting the variation tendency of industrial land use with varied policy impact strength. The results reveal a dynamic understanding of the evolving patterns of land intensification and present different characteristics of IUIL. This study further proposes policy recommendations to provide experience and references for the authorities to promote high-quality urbanization development in practice.

Assessment of Bitumen Paver and HMP Efficiency for a Road Project

One of the important and dependable sectors of the national economy is the equipment used in highway construction. In the process of building constructions, efficient utilization of labour, supplies, and machinery must be fervently pursued through competent project management. The adoption of innovative procedures and new equipment has resulted in a dramatic advance in construction technology in recent decades. The selection of the right type and size of construction equipment typically affects how productive a project is on the job site. Thus, it is essential that site managers and construction planners understand the primary equipment categories that are most frequently used in construction. Technical aspects and working conditions are taken into consideration in the article's method of calculating the operational productivity and cost of asphalt pavers. This increases the accuracy of decisions made about how to organize and manage highway maintenance activities on Chikhali-Tarsod NH-6.

Variable Capital Utilization and Indeterminacy

Variable capital utilization has been widely used in business cycle research based on the observation that utilization rate is variable over time. The common assumption is that capital depreciates faster when it is utilized more extensively. This paper shows analytically that variable capital utilization makes it easier for indeterminacy to arise. In particular, when both capital utilization and labor supply become infinitely elastic, the required degree of external increasing returns can be arbitrarily small.

Safety-driven design of carbon capture utilization and storage (CCUS) supply chains: A multi-objective optimization approach

Safety-driven design of carbon capture utilization and storage (CCUS) supply chains: A multi-objective optimization approach

Study on controllability assessment of a new type of power system based on lagrangian function integrated assessment method

The complex structure and multiple controllability metrics of the new power system require a comprehensive assessment approach. We propose a controllability assessment method based on the Lagrangian function, analyzing key factors that influence controllability. Our index system includes distributed power supply utilization rate, energy storage station charge state, power factor, and voltage offset. Using Lagrange shadow price theory, we construct a guideline layer index system treating bottom indexes as constraints. We formulate an optimization function utilizing the Lagrangian shadow price theory and considering weights calculated from the bottom index’s shadow price. These weights inform primary evaluation. By combining primary evaluation results, weights, and variable coefficients using the percentage system method, we determine comprehensive evaluation results for the new power system’s controllability. Experimental results demonstrate the high reliability of this method’s evaluation indexes, indicating their effectiveness. This research provides valuable insight for the advancement of the new power system. Region 1 had the lowest overall evaluation score of 51.57 and was rated general. The overall score of Region 2 was 77.24, which was considered good. Region 3 received the highest overall score of 86.29 and was rated as excellent.Graphical

Research on Electricity Balance and Measurement Optimization of New Energy Power System Considering Renewable Energy Consumption Mechanism

With the rapid development of renewable energy, the new energy power system is facing the challenge of large-scale grid connection and consumption of renewable energy. In order to achieve efficient utilization and stable power supply of renewable energy, this study proposes a renewable energy consumption mechanism based on optimization methods. By establishing a power and electricity balance model, consider the relationship between different types of renewable energy generation and electricity demand. Various optimization strategies have been proposed for energy consumption issues in different scenarios, including power generation scheduling, energy storage optimization, and flexible load management. Validate the effectiveness of the proposed mechanism in terms of electricity balance and metering optimization through a model. The experimental results indicate that this mechanism can effectively enhance the renewable energy consumption capacity of the new energy power system, reduce energy waste, promote energy cleanliness and sustainable development, and has certain theoretical and practical significance for promoting the sustainable development of the new energy power system and responding to energy transformation.

Optimal supply chain performance: risk aversion to green innovation

PurposeAlthough many countries are focusing on the management of construction and demolition waste (CDW) resource utilization, the effect of risk aversion of the green innovation-led enterprise on the performance of the CDW resource utilization supply chain is unclear when considering different green innovation contexts (green innovation led by the building materials remanufacturer or by the construction waste recycler). This study aims to investigate how the level of risk aversion of the green innovation-led enterprise affects CDW resource utilization under different green innovation contexts based on contingency theory.Design/methodology/approachUsing Stackelberg game theory, this study establishes a decision model consisting of a building materials remanufacturer, construction waste recycler and CDW production unit and investigates how the level of risk aversion of the green innovation-led enterprise under different green innovation contexts influences the performance level of the supply chain.FindingsThe conclusions are as follows. (1) For the green innovation-led enterprise, the risk-averse behaviour is always detrimental to his own profits. (2) For the follower, the profits of the construction waste recycler are negatively correlated with the level of risk aversion of the green innovation-led enterprise in the case of a small green innovation investment coefficient. If the green innovation investment coefficient is high, the opposite result is obtained. (3) When the green innovation investment coefficient is low, the total supply chain profits decrease as the level of risk aversion of the green innovation-led enterprise increases. When the green innovation investment coefficient is high, total supply chain profit shows an inverted U-shaped trend with respect to the degree of risk aversion of the green innovation-led enterprise.Originality/value(1) This study is the first to construct a green innovation context led by different enterprises in the CDW resource utilization supply chain, which provides a new perspective on green management and operation. (2) This study is the first to explore the operation mechanism of the CDW resource utilization supply chain based on contingency theory, which provides new evidence from the CDW resource utilization supply chain to prove contingency theory. At the same time, this study examines the interactive effects of the green innovation cost coefficient and the degree of risk aversion of green innovation-led enterprises on the performance of supply chain members, expanding the contingency theory research on contingencies affecting enterprise performance. (3) This study will guide members of the CDW resource utilization supply chain to rationally face risks and achieve optimal supply chain performance.

Efficiency analysis of China's urban water supply utilities using a dynamic multiactivity network DEA model

Efficiency analysis of China's urban water supply utilities using a dynamic multiactivity network DEA model

The influence of regulation on preference for utility infrastructure investment to generate income for Australian water corporations

ABSTRACT Effects of price regulation and preference for utility supply infrastructure on Australian urban water utilities and urban water markets are examinated using historical data, models of the future and a case study of Greater Sydney. Australian regulators utilise the building block method based on operating and capital costs, and a Regulatory Asset Base to set nominal revenue requirements and ultimately prices for water utility services. Regulation of water utilities that is dependent on a Regulatory Asset Base drives preference for utility infrastructure and is remote from market mechanisms of consumer demands for water and sewage services. These regulatory processes are not linked to the operation of the urban water market of government owned utility and distributed solutions, and act to crowd out viable complementary solutions including water efficiency, distributed water sources and alternative pricing models. Government regulation, ownership and operation of utilities may produce strong performance from the perspective of urban water corporations but decrease economic efficiency, resilience and social welfare in urban water markets. The role of major water corporations needs to be redefined in a market recognising multiple complementary water sources and services. Regulation of utility services should have regard to the entire market, market demand, environmental health and consumer welfare.

A parameter design method of LC filter circuit for closed‐loop dynamic power supply system based on linear power amplifier

AbstractThe linear power amplifier (LPA) suffers from low power supply utilization in the DC power supply mode, leading to reduced output efficiency. This paper constructs an efficient power supply mode based on closed‐loop dynamic power supply system (CLDPSs). The CLDPSs can generate a pair of bipolar dynamic power supplies based on a predetermined signal to provide power to LPA, which can maintain a small voltage drop between the power supply and the output of LPA, thereby improving the power supply utilization of LPA. In addition, the study also focuses on the conflicting relationship between the output ripple and the dynamic performance of the CLDPSs, for which a new parametric design of the LC filter circuit is proposed, aiming to achieve a balance between these two aspects. Finally, a voice coil motor driving platform is constructed for experimental testing. The results demonstrate that the output ripple and dynamic performance of the CLDPSs can be balanced. In comparison to the DC power supply mode, the CLDPSs power supply mode can enhance the efficiency of LPA by 2 times while the driving accuracy of voice coil motor is basically unchanged.

The challenge of closing the climate adaptation gap for water supply utilities

Many drinking water utilities face immense challenges in supplying sustainable, drought-resilient services to households. Here we propose a quantified framework to perform drought risk analysis on ~5600 potable water supply utilities and evaluate the benefit of adaptation actions. We identify global hotspots of present-day and mid-century drought risk under future scenarios of climate change and demand growth (namely, SSP1-2.6, SSP3-7.0, SSP5-8.5). We estimate the mean rate of unsustainable or disrupted utility supply at 15% (interquartile range, 0–26%) and project a global increase in risk of between 30–45% under future scenarios. Implementing the most cost-effective adaptation action identified per utility would mitigate additional future risk by 75–80%. However, implementing the subset of cost-effective options that generate sufficient tariff revenue to provide a benefit-cost ratio that is greater than 1 would only achieve 5–20% of this benefit. The results underline the challenge of attracting the financing required to close the climate adaptation gap for water supply utilities.

Economic optimization scheduling of virtual power plants considering an incentive based tiered carbon price

Economic optimization scheduling of virtual power plants considering an incentive based tiered carbon price