Search Results (48)

Under the construction background of carbon peak and carbon neutrality, high-energy-consuming enterprises, represented by the electrolytic aluminum industry, have become important carriers for energy conservation and emission reduction. These enterprises are characterized by significant energy consumption and high carbon emissions, greatly impacting the economic and environmental benefits of regional power grids. Existing research often focuses on grid revenue, leaving high-energy-consuming enterprises in a passive regulatory position. To address this, this paper constructs an economic dispatch strategy for power grids that considers waste heat utilization in high-energy-consuming enterprises. A typical representative, electrolytic aluminum load and its waste heat utilization model, for the entire production process of high-energy-consuming loads, is established. Using a tiered carbon trading calculation formula, a low-carbon production scheme for high-energy-consuming enterprises is developed. On the grid side, considering local load levels, the uncertainty of wind power output, and the energy demands of aluminum production, a robust day-ahead economic dispatch model is established. Case analysis based on the modified IEEE-30 node system demonstrates that the proposed method balances economic efficiency and low-carbon performance while reducing the conservatism of traditional optimization approaches. Full article

Microalgae proteins are increasingly recognized in the food and nutraceutical industries for their functional versatility and high nutritional value. Mild alkaline treatment is commonly used for cell wall degradation and intracellular protein solubilization, consequently enhancing the protein extraction yield. The findings of this study reveal that alkaline treatment alone, even at higher NaOH concentration (up to 0.3 M) and treatment time (up to 90 min), was ineffective (max. 2.4% yield) for the extraction of protein from Auxenochlorella protothecoides biomass. This challenge was significantly reduced through synergistic application of mechanical cell disruption using high-pressure homogenization (HPH) and alkaline solubilization. Single-pass HPH (35 k psi) alone without alkaline treatment led to 52.3% protein solubilization from wet biomass directly harvested from culture broth, while it was only 18.5% for spray-dried biomass. The combined effect of HPH and alkaline (0.1 M NaOH) treatment significantly increased protein extraction yield to 68.0% for a spray-dried biomass loading of 50 g L⁻¹. Through replacing spray-dried biomass with wet biomass, the requirement of NaOH was reduced by 5-fold to 0.02 M to achieve a similar yield of 68.1%. The process integration of HPH with the mild alkaline solubilization and utilization of wet biomass from culture broth showed high potential for industrialization of microalgae protein extraction. This method achieves high extraction yield while reducing alkaline waste and eliminating the need for energy-consuming drying of biomass, thereby minimizing the environmental impact. Full article

Heating, ventilation, and air-conditioning systems account for 40–60% of the energy consumed in commercial buildings, and much of this load originates from sub-optimal piping layouts in chiller-plant rooms. This study presents an automated routing framework that couples Building Information Modeling (BIM) with an enhanced A* search to produce collision-free, low-resistance pipelines while simultaneously guiding component selection. The algorithm embeds protective buffer zones around equipment, reserves maintenance corridors through an attention-based cost term, and prioritizes 135° elbows to cut local losses. Generated paths are exported as Industry Foundation Classes (IFC) objects for validation in a BIM digital twin, where hydraulic feedback drives iterative reselection of high-efficiency devices—including magnetic-bearing chillers, cartridge filters and tilted-disc valves—until global pressure drop and life-cycle cost are minimized. In a full-scale shopping-mall retrofit, the method significantly reduces pipeline resistance and operating costs, confirming its effectiveness and replicability for sustainable chiller-plant design. Full article

Rotor systems are basic in power generation, mechanical, and many other energy equipment and industrial fields. The smooth operation of equipment is linked to the successful operation of technological processes and the safe operation of working equipment. Working conditions nowadays are characterized by intensive rotation speeds, complex structures, and dynamic loads, contributing to different mechanical faults. Detecting such defects in the preliminary stages is inadequate, which could lead to emergencies, high economic loss, and reduced equipment life. Several modern diagnosis methods are widely utilized to monitor the condition in real-time mode, such as vibration parameter analysis, temperature deviation analysis, acoustic emission analysis, and other operational parameter analyses, to avoid the possibility of rotor failure. Some techniques like the vibration signal analysis method, spectral analysis, thermography, ultrasound diagnosis, and machine learning algorithms for predicting failure are of particular interest among them. These techniques allow the defects to be identified immediately and constitute effective preventive maintenance plans, thus significantly enhancing the reliability and economic efficiency of the rotor system operations. This current work is devoted to studying modern diagnostic methods of rotor systems, considering the areas of their realization that are used. This review discusses the theory of the applied methods, advantages, limitations, and the perspective of their further development in innovation integration. It aims to critically analyze and comprehensively systematize methods for energy-consuming rotor equipment condition monitoring that will enhance the efficiency of managing technical conditions for the main components of modern energy systems. Full article

The increasing power consumption reflects technological and industrial growth, but meeting this demand with conventional fossil-fuel-based plants is challenging. Microgrids address this issue by integrating renewable energy-based Distributed Energy Resources (DERs) and Energy Storage Systems (ESS). Efficient Microgrid operation requires a power management system to balance supply and demand, reduce costs, and ensure load prioritization. This paper presents a wide area measurement (WAMS)-based Centralized Power Management System (CPMS) for AC microgrids in both Islanded and Grid-Connected modes. The modified IEEE 13-bus system is utilized as a microgrid test system by integrating DERs and ESS. WAMS significantly enhances intra-microgrid communication by offering real-time, high-resolution monitoring of electrical parameters, surpassing the limitations of traditional SCADA-based monitoring systems. In grid-connected mode, the proposed CPMS effectively manages dynamic grid tariffs, generation variability in DERs, and state-of-charge (SoC) variations in the ESS while ensuring uninterrupted load supply. In islanded mode, a load prioritization scheme is employed to dynamically disconnect and restore loads to enhance the extent of load coverage across consumer categories. The inclusion of diverse load categories, such as domestic, industrial, commercial, etc., enhances the practical applicability of the CPMS in real-world power systems. The effectiveness of the proposed CPMS is validated through multiple case studies conducted in Simulink/MATLAB. Full article

Tapes are widely utilized across various industries, offering versatile solutions for bonding, sealing, and packaging applications. Their ease of use, strength, and adaptability make them essential in manufacturing, construction, and consumer markets. However, the effectiveness of tapes depends heavily on their adhesive performance, which is influenced by factors such as the adhesive layer composition, material compatibility, environmental conditions, and contact parameters. Quantifying adhesive performance through standardized testing is critical to ensuring reliability, optimizing functionality, and meeting industry-specific requirements. Traditional methods, such as peel and shear tests, are commonly used to evaluate the adhesive and shear strength of tapes. However, these methods typically operate at macro-load scales and often use complex sample geometries and significant material quantities. Recently, precision indentation–retraction testing has emerged as a promising technique for accurately quantifying the adhesion and cohesion forces of viscoelastic fluids. This study adapts this method to evaluate and compare the adhesive strength of various commercially available adhesive tapes. The adhesion force and separation energy of five commercial tapes, namely paper masking tape, high-temperature tape, insulation tape, duct tape, box wrapping tape, and double-sided tape, were measured using a Falex Tackiness Adhesion Analyser (TAA) tester, under controlled conditions (approach speed: 0.01 mm/s, retraction speed: 0.1 mm/s, and load: 50 mN). The results indicated that the adhesion force and separation energy varied significantly among the tapes, whereas a different pattern in the indentation–retraction curves was obtained for these tapes. In addition, the significance of difference among the adhesive properties of the tapes was assessed with the use of analysis of variance (ANOVA). This innovative approach not only enhances the precision of adhesive strength measurements but also provides valuable insights into adhesive layer properties, offering a novel tool for research, development, and quality control in tape production. Full article

The results of numerous studies show that the control of power grid modes is carried out mainly using a technical criterion. The economic criterion is taken into account through the use of complex and inaccurate models that do not accurately predict the result. The emergence of market relations in the energy sector makes power systems economic entities in terms of production and satisfaction of demand for electricity by various economic entities (industry, households, businesses, etc.). Under these conditions, electricity is a commodity with a corresponding price and quality indicators. This requires the application of the risk assessment methodology as an economic category in the activities of power systems as a business entity. The methodology of risk assessment in market conditions requires business entities to search for methods to minimize risk as a possibility of adverse events. Under these conditions, it becomes possible to make the best management decisions regarding the most important criterion that reflects the interests of business entities at a given time. However, the imperfection of the relevant methodology for risk assessment in the energy sector delays their application in the industry. At the same time, when making management decisions, three possible levels can be distinguished: decision-making in conditions of certainty, when the result is presented in a deterministic form and can be determined in advance; decision-making under conditions of risk, when the outcome cannot be determined in advance, but there is information on the probability of distribution of possible consequences; decision-making in conditions where the outcome is random and there is no information about the consequences of the decision. An analysis of scientific publications shows that some authors’ works are devoted to solving the issues of applying the theory and principles of risks in the energy sector, in which the problem is solved only at the first two levels. At the same time, the operation of energy facilities is characterized by a high level of uncertainty and incomplete information about the consequences of such decisions. Therefore, the development of a methodology for making management decisions in the energy sector based on the theory and practice of risks, taking into account the high level of uncertainty and incomplete information, is an urgent scientific task. Implementation of algorithms and programs for controlling the modes of power grids based on them can meet the requirements for reliable and high-quality energy supply to the most demanding consumers and create favorable conditions for their business. This work is devoted to the development of scientific and methodological foundations for determining the voltage risk in power system networks, taking into account the uncertain nature of the loads and its impact on consumers. Based on the results of the study, a mathematical model of the risk of voltage collapses in networks, an algorithm and a methodology for its calculation were proposed. Full article

In a modern and dynamic electricity market, ensuring reliable, sustainable and efficient electricity distribution is a pillar of primary importance for grid operation. The high penetration of renewable energy sources and the formation of competitive prices for utilities play a critical role in the wider economic development. Electricity load and price forecasting have been a key focus of researchers in the last decade due to the substantial economic implications for both producers, aggregators and end consumers. Many forecasting techniques and methods have emerged during this period. This paper conducts a extensive and analytical review of the prevailing load and electricity price forecasting methods in the context of the modern wholesale electricity market. The study is separated into seven main sections. The first section provides the key challenges and the main contributions of this study. The second section delves into the workings of the electricity market, providing a detailed analysis of the three markets that have evolved, their functions and the key factors influencing overall market dynamics. In the third section, the main methodologies of electricity load and price forecasting approaches are analyzed in detail. The fourth section offers a comprehensive review of the existing literature focusing on load forecasting, highlighting various methodologies, models and their applications in this field. This section emphasizes the advances that have been made in all categories of forecasting models and their practical application in different market scenarios. The fifth section focuses on electricity price forecasting studies, summarizing important research papers investigating various modeling approaches. The sixth section constitutes a fundamental discussion and comparison between the load- and price-focused studies that are analyzed. Finally, by examining both traditional and cutting-edge forecasting methods, this review identifies key trends, challenges and future directions in the field. Overall, this paper aims to provide an in-depth analysis leading to the understanding of the state-of-the-art models in load and price forecasting and to be an important resource for researchers and professionals in the energy industry. Based on the research conducted, there is an increasing trend in the use of artificial intelligence models in recent years, due to the flexibility and adaptability they offer for big datasets, compared to traditional models. The combination of models, such as ensemble methods, gives us very promising results. Full article

While South Africa is deemed one of the countries with the highest irradiation levels, it still utilises coal as its primary energy source due to its abundance. Due to the world-wide drive towards carbon neutrality, residential, commercial, agricultural, and industrial consumers are considering small-scale embedded generation systems. The National Rationalised Specifications 097-2-3 document specifies the scale of the embedded generation capacity a consumer is allowed to install. However, specifications do not yet make the required provisions for the addition of energy storage. The effective collective management of the grouped small-scale embedded generation systems could provide a high level of energy security and increase the percentage of renewable energy generation in the total energy mix. Potential challenges come into play when considering the stochastic nature of photovoltaic generation and its effect on the storage capacity and the dispersion in load profiles of the residential units typically present on a low-voltage network. This paper contributes by investigating the utilisation of photovoltaic generation in conjunction with storage as the basis for virtual power plant control, with the aim to safely increase renewable energy penetration and improve energy security, all while remaining within the South African low-voltage regulatory limits. A two-level virtual power plant controller is proposed with the dispersed energy storage units as the primary controllable resources and the dispersed photovoltaic generation as the secondary controllable resources. The objective of the controller is to achieve nodal energy management, energy sharing, and ancillary service provision and finally to increase renewable energy penetration. A representative single-feeder low-voltage network is simulated, and test cases of 50% and 75% renewable energy penetration are investigated as the basis for evaluation. The proposed controller architecture proved to maintain network integrity for both test cases. The adaptability of the controller architecture was also confirmed for a changed feeder topology; in this case, it was a multi-feeder topology. Future work is warranted to inform policy on the allowed levels of renewable energy penetration to be based not only on demand but also on the level of energy storage present in a network. Full article

Constructing isolated industrial microgrids with wind power is beneficial for improving the economic benefits of high-energy-consuming production, such as the electrolytic aluminum industry. Due to the specialized structure of industrial microgrids and the unique characteristics of the electrolytic aluminum load (EAL), the common emergency frequency control methods do not apply to the specific operational requirements of isolated industrial microgrids. Since EALs have huge regulating capacities and fast responses, this paper proposes a coordinated emergency frequency control scheme to deal with power disturbances in isolated industrial microgrids. The coordinated frequency control model of an industrial microgrid considering demand-side participation is derived. With the help of output regulation theory, a practical, feasible coordinated frequency controller is designed by introducing frequency deviation and power disturbance as feedback control signals. The proposed control scheme achieves reserve power distribution between the generation and demand sides. The microgrid frequency can be maintained within a permitted range in the presence of large power imbalances. The simulation results conducted in an actual isolated industrial microgrid validate the effectiveness and dynamic performance of the proposed control scheme. Full article

The electricity consumption of the textile industry accounts for 2.12% of the total electricity consumption in society, making it one of the high-energy-consuming industries in China. The textile industry requires the use of a large amount of industrial steam at various temperatures during production processes, making its dispatch and operation more complex compared to conventional electricity–heat integrated energy systems. As an important demand-side management platform connecting the grid with distributed resources, a virtual power plant can aggregate textile industry users through an operator, regulating their energy consumption behavior and enhancing demand-side management efficiency. To effectively address the challenges in load regulation for textile industry users, this paper proposes a coordinated optimization dispatching method for electricity–steam virtual-based power plants focused on textile industrial parks. On one hand, targeting the impact of different energy prices on the energy usage behavior of textile industry users, an optimization dispatching model is established where the upper level consists of virtual power plant operators setting energy prices, and the lower level involves multiple textile industry users adjusting their purchase and sale strategies and changing their own energy usage behaviors accordingly. On the other hand, taking into account the energy consumption characteristics of steam, it is possible to optimize the production and storage behaviors of textile industry users during off-peak electricity periods in the power market. Through this electricity–steam optimization dispatching model, the virtual power plant operator’s revenue is maximized while the operating costs for textile industry users are minimized. Case study analyses demonstrate that this strategy can effectively enhance the overall economic benefits of the virtual power plant. Full article

Liquefied natural gas carrier (LNGC) orders are increasing owing to marine environment regulations. The complexity of the integrated system applied to shipbuilding and software errors have increased with the high degree of automation. Direct on-site inspection methods are associated with high costs and safety risks, whereas software-based simulations rely heavily on the accuracy of the models of power system components. Hardware-in-the-loop simulation (HILS) can be utilized for designing and testing intricate real-time embedded systems. Specifically, HILS offers a reliable means of evaluating power management system (PMS) performance for LNGCs, which are high-value vessels commonly used in offshore plants. This study proposes a PMS–HIL test bed comprising a power supply unit, consumer, simulation control console, and main switchboard. The proposed HILS test bed utilizes the real equipment data of the shipbuilding industry to replicate the conditions associated with actual LNGCs. The proposed system is verified and validated through a software acceptance test procedure. Additionally, load-sharing, load-dependent start, blackout prevention, and preferential tests are performed for the PMS function evaluation. Test results indicate that the proposed system has great potential for conventional PMS commissioning. Therefore, it exhibits the potential to replace traditional factory acceptance tests. Additional development of the system will be conducted for ship automation, utilizing PMS control and an energy management system. Full article

The deployment of a green power alternative within an isolated network, powered by renewable energy sources, in the “Three North” region of China can facilitate the substitution of high-energy-consuming industrial loads with green power. However, an inadequate power supply configuration may lead to economic and reliability issues. To address this problem, effective capacity allocation within the green power alternative isolated network is proposed. The capacity allocation process starts with the design of a network structure that aligns with local conditions. Subsequently, a capacity allocation model is developed, considering economic factors, renewable energy utilization efficiency, and system reliability. The gray wolf optimizer is enhanced to establish a capacity allocation method for the green power alternative isolated network. This method is then employed to simulate and assess the performance of the network. The results indicate that the green alternative isolated grid can successfully facilitate green power substitution, satisfying the energy requirements of the loads. Full article

Mercury (Hg) is a toxic metal that is easily released into the atmosphere as a gas or a particulate. Since Hg has serious health impacts based on human exposure, it is a major concern where it accumulates. Southern Florida is a region of high Hg deposition in the United States. It has entered the southern Florida environment for over 56 MY. For the past 3000 to 8000 years, Hg has accumulated in the Everglades peatlands, where approximately 42.3 metric tons of Hg was deposited. The pre-industrial source of mercury that was deposited into the Everglades was from the atmosphere, consisting of combined Saharan dust and marine evasion. Drainage and the development of the Everglades for agriculture, and other mixed land uses have caused a 65.7% reduction in the quantity of peat, therefore releasing approximately 28 metric tons of Hg into the southern Florida environment over a period of approximately 133 years. Both natural and man-made fires have facilitated the Hg release. The current range in mercury release into the southern Florida environment lies between 994.9 and 1249 kg/yr. The largest source of Hg currently entering the Florida environment is from combined atmospheric sources, including Saharan dust, aerosols, sea spray, and ocean flux/evasion at 257.1–514.2 kg/yr. The remobilization of Hg from the Everglades peatlands and fires is approximately 215 kg/yr. Other large contributors include waste to energy incinerators (204.1 kg/yr), medical waste and crematory incinerators (159.7+ kg/yr), and cement plant stack discharge (150.6 kg/yr). Minor emissions include fuel emissions from motorized vehicles, gas emissions from landfills, asphalt plants, and possible others. No data are available on controlled fires in the Everglades in sugar farming, which is lumped with the overall peatland loss of Hg to the environment. Hg has impacted wildlife in southern Florida with recorded excess concentrations in fish, birds, and apex predators. This bioaccumulation of Hg in animals led to the adoption of regulations (total maximum loads) to reduce the impacts on wildlife and warnings were given to consumers to avoid the consumption of fish that are considered to be contaminated. The deposition of atmospheric Hg in southern Florida has not been studied sufficiently to ascertain where it has had the greatest impacts. Hg has been found to accumulate on willow tree leaves in a natural environment in one recent study. No significant studies of the potential impacts on human health have been conducted in southern Florida, which should be started based on the high rates of Hg fallout in rainfall and known recycling for organic sediments containing high concentrations of Hg. Full article

Fuel consumption optimization is a critical field of research within the automotive industry to meet consumer expectations and regulatory requirements. A reduction in fuel consumption can be achieved by reducing the energy consumed by the vehicle. Several subsystems contribute to the overall energy consumption of the vehicle, including the air conditioning (A/C) system. The loads within the A/C system are mainly contributed by the compressor, condenser fan, and underhood aerodynamic drag, which are the components targeted for overall vehicle energy use reduction in this paper. This paper explores a new avenue for A/C system control by considering the power consumption due to vehicle drag (regulated by the condenser fan and active grille shutters (AGS)) to reduce the energy consumption of the A/C system and improve the overall vehicle fuel economy. The control approach used in this paper is model predictive control (MPC). The controller is designed in Simulink, where the compressor clutch signal, condenser fan speed, and AGS open-fraction are inputs. The controller is connected to a high-fidelity vehicle model in Gamma Technologies (GT)-Suite (which is treated as the real physical vehicle) to form a software-in-the-loop simulation environment, where the controller sends actuator inputs to GT-Suite and the vehicle response is sent back to the controller in Simulink. Quadratic programming is used to solve the MPC optimization problem and determine the optimal input trajectory at each time step. The results indicate that using MPC to control the compressor clutch, condenser fan, and AGS can provide a 37.6% reduction in the overall A/C system energy consumption and a 32.7% reduction in the error for the air temperature reference tracking compared to the conventional baseline proportional integral derivative control present in the GT-Suite model. Full article