Plant Unit Research Articles

Discrete control model Q-learning for an energy storage system with a hydrogen unit of an autonomous hybrid power plant of a railway substation

The paper considers the prospects for creating autonomous hybrid power plants using renewable energy sources and hydrogen as energy storage systems, as well as storage batteries, for the railway power supply system. A comparative analysis of various energy storage systems is carried out. A simulation model has been created that takes into account the characteristics of electric rolling stock trains, a model of the contact network of the inter-station zone of the railway stage, and a model of the energy storage system. Managing the flow of electricity in an autonomous hybrid power plant requires considering forecasts of electricity consumption and generation and the level of charge of the energy storage device. To solve the problem of synthesizing a control algorithm, the use of matrix Q-learning is proposed. The novelty of the study lies in the proposed approach of applying Q-learning to the problem under consideration based on discretization of input and output parameters of the model and verification of the approach on a simulation model built for a real railway section between the Yaya and Izhmorskaya stations (Kemerovo region of the Russian Federation). It is shown that the use of the proposed system makes it possible to equalize the voltage in the network between traction substations and provide a significant increase in the capacity of the railway section, and the proposed method of matrix Q-learning makes it possible to synthesize an effective algorithm for controlling the energy storage system as part of an autonomous hybrid power plant.

A pilot-scale evaluation of residual sludge quality in a worm-sludge treatment reed bed in the Mediterranean region

A pilot-scale study on sludge treatment reed beds investigated the combined effects of earthworms and Arundo donax on sewage sludge dewatering and residual sludge quality. Four units were tested: one planted with earthworms, one planted without earthworms, one unplanted with earthworms, and one control, each unit replicated. Over a year, 24 cycles of sludge (dry and volatile solid contents of 24.71 g.L−1, and 19.14 g.L−1) were fed onto the units at a sludge loading rate: 43.59 kg.DS.m−2.year−1. Afterward, the units experienced 132 days of resting period, increasing dry solids from 21 to 70 % and decreasing volatile solids from 81 to 69 % on average (40 % sludge volume reduction). The bottom layers of the planted unit with earthworms showed a 30 % reduction in volatile solids, indicating improved sludge stabilization. Macronutrient abundance in the residual sludge followed the sequence N > Ca > P > K > S > Mg. The planted unit with earthworms reduced micronutrient concentrations by 22 % compared to the control unit (Fe > Na > Mn > B > Mo). Earthworms also played a key role in reducing heavy metal concentrations by 11 % compared to the planted unit without earthworms (Zn > Cr > Pb > Ni > Cd). Heavy metal levels in the residual sludge met EU and Portugal standards, with a 99.9 % reduction in Escherichia coli and fecal coliforms. Cost estimation showed centrifugation and W-STRB scenarios cost 167 and 183 €.PE−1 for a ten-year operation, with O&M costs of 7 and 3 €.PE−1.year−1, respectively.

Ensuring Stable Operation of Wind Farms Connected to Distribution Networks

Wind farms with type IV wind turbines from various manufacturers are being massively put into operation. These wind turbines comply with the requirements of the grid codes of the countries where they are designed and/or manufactured, but do not factor in the specific features of the distribution networks of other countries to which they are connected. The study at issue involves a comparative analysis of the requirements of grid codes of different countries for the stable operation of wind turbines under standard disturbances. The low voltage ride through (LVRT) characteristic makes it possible to prevent wind turbine shutdowns in case of short-term voltage dips of a given depth and duration. The calculations of transient processes indicate that wind turbines may not meet the requirements of the grid code of a particular country for their stable operation. As a result, standard disturbances will block the reactive current injection and the wind turbine will be switched off. This is often caused by the relay protection devices with a time delay of 1–2 s, which are used in distribution networks and implement the functions of long-range redundancy. Excessive shutdowns of wind turbines lead to emergency rises in the loads for the generating units of conventional power plants, aggravating the post-accident conditions and disconnecting consumers of electricity. This article presents a method for checking the LVRT characteristic settings for compliance with the technical requirements for wind turbines. To prevent wind turbine outages, one should either change the configuration of the LVRT characteristic, upgrade the relay protection devices in the distribution network adjacent to the wind farm, or implement group or individual technical solutions at the wind farm. The performance of the proposed technical solutions is confirmed by the calculations of transient processes.

Manifesting the hidden pollutants: Quantifying emissions and environmental impact of petroleum refinery on PM2.5

This research thoroughly examined the emissions of primary fine particle and precursors of secondary particles (VOCs, SO2 and NOx) originating from the petroleum refinery operation. The central aim was to quantify the emission factors of fine particulate matter and analyze their spatial dispersion and source contributions, in order to evaluate their environmental impacts.The VOCs emission measurement appeared that the wastewater treatment plant unit was the most significant source of VOCs emissions, with pentane, cyclopentane, and propane being the dominant VOCs species released. The study employed the secondary organic aerosol potential (SOAP), sulfur oxidation ratio (SOR), and nitrogen oxidation ratio (NOR) methodologies to calculate the emissions of secondary PM2.5. The combustion stacks were the principal contributor to secondary PM2.5 emissions, with SO2 being the predominant secondary PM2.5 precursor species contributing to fine particulate matter, accounting for 82.5% of the total secondary PM2.5 emissions. The overall emission factor for the refinery was determined to be 0.31 g secondary PM2.5 per kg of refined crude oil. Furthermore, the analysis indicated that the combustion stacks were the primary contributors to PM2.5 concentrations at all receptor sites, accounting for 64.4%–80.8% of the total contribution, followed by the wastewater treatment unit and storage tanks. The study underscored the importance of focusing on secondary PM2.5 precursor emissions to effectively reduce emissions and environmental concentrations of PM2.5, highlighting the potential for more effective management and mitigation strategies targeting these precursors.

Artificial intelligence-enabled predictive planning for sewage treatment based on improved DNN and LSTM

Predictive planning is essential for sewage treatment, which ensures water security. In the context of Industry 4.0, new sensor technologies are generating large amounts of heterogeneous data from multiple sources in increasingly complex sewage treatment processes. This complexity renders traditional methods inadequate for the accurate and timely prognostication of data essential for predictive planning. To solve the challenge, this study proposes an architecture of artificial intelligence-enabled predictive planning to reduce cost and increase efficiency for sewage treatment. Within this architecture, a combination of a sparsely connected deep neural network model based on combined correlation analysis and an improved long short-term memory model based on periodicity is used to predict critical data for sewage treatment. Then, the proposed architecture is applied by using production data from the high-density pool unit of a sewage treatment plant. Results reveal that the accuracy of the data in predictive planning is 92.7 % compared with the actual data. Establishing this architecture for predictive planning provides a practical basis for the digital transformation of sewage treatment plants to automate processes, improve decision-making, reduce costs and increase operational efficiency.

Efficient recovery of organic phase from crud in solvent extraction unit of Sarcheshmeh copper complex in Iran by powerful water-absorbent reagents

The formation of stable multi-phase emulsions (crud) is a serious problem in almost all commercial solvent extraction (SX) plants. Crud is a mixture of organic and aqueous phases, air, and organic or inorganic solid particles, often found to distribute itself randomly throughout the separating phases of SX plants. Crud formation is encountered in almost all SX units in metal extraction plants. It causes the loss of solvent and thus increases the process costs. Therefore, the removal of crud and recovery of the expensive organic phase including diluent and extracting reagents from it is of great importance. In this research, the applicability of a range of powerful water absorbent reagents was studied for the recovery of organic phase from the crud formed in copper extraction/electrowining unit of Sarchashmeh copper complex (IRAN). The reagents included gypsum, carbomer, sodium polyacrylate, sodium sulfate, magnesium sulfate and calcium chloride. The results showed that gypsum, carbomer and sodium polyacrylate are effective additives which let the organic phase to be recovered with up to 95 % yield. To ensure that gypsum does not cause a negative effect on the copper loading and stripping of the recovered solvent, the extraction/stripping properties of the organic phase separated with gypsum was compared with the organic phase separated by centrifugation without additives. Surface tension analysis of the gypsum-recovered organic phase also confirmed its suitability for recovery of organic phase from crud. Finally, the calcium content of gypsum-recovered organic phase was measured and compared with that of the organic phase separated by centrifugation without any additive.

Probabilistic safety analysis of the large primary circuit leakages accident scenarios in the VVER-reactor

Probabilistic safety analysis of the loss of coolant accidents in the VVER-type reactor plant has been performed taking into account the internal initiating events of the reactor primary circuit large leakages. Swedish program code RiskSpectrum PSA was used for probabilistic safety analysis. Logical probabilistic models of the accident scenarios of the large primary circuit leakages in the VVER-type reactor were developed taking into account different operation modes of the power plant unit. Critical paths and probabilities of the accident scenarios occurrence of the large leakages were identified. The critical path of development of the reactor primary circuit large leakages accident with large leakages of 140–346 mm diameters is the accident sequence with a leak in the pipeline to the reactor pressurizer vessel. It has been established that the greatest contribution to the failure of safety functions during this initiating event is made by the failures due to common causes of the supporting systems (cooling and ventilation systems), critical consumers cooling circuit, emergency injection system. The critical path of the accident with large leakages of 346–850 mm diameters is the accident sequence with the rupture of any of the four primary circuit loops. The greatest contribution to the failure of safety functions during this initiating event is made by the failures due to common causes of the emergency injection system elements. Based on the accident analysis, recommendations for increase of performance reliability of safety functions during the large leakages accidents under all operation states of the nuclear power plant unit were given. In order to increase reliability of safety systems, it is necessary to eliminate failures due to common causes of equipment, increase the reliability of operation of supporting systems, change the maintenance and checking equipment procedures.

A research and application of a digital failure knowledge model for nuclear power plant

Abstract The accumulation and application of knowledge about equipment component failures in nuclear power plant unit systems is an important way for domestic and foreign nuclear power plants to improve unit availability and economic benefits. Based on the existing equipment component knowledge models in China and the experience of digital transformation, this paper proposes a digital fault knowledge model construction process and method for nuclear power plant components, which is of great significance for standardizing and guiding domestic nuclear power plant knowledge models.

Development and evaluation of a self-adaptable planting unit for an autonomous planting process of field vegetables

Today, the number of solutions for automated processes in agriculture is growing rapidly. This is primarily driven by the lack of available and affordable labour, pricing pressures, and regulatory requirements. Vegetable production in particular has a lot of potential for automation, as many process steps, such as planting, are performed partly manually. Fully automated systems for the planting process are characterized by their big size, which is only suitable for large farms. At the same time, these planters typically have a low level of intelligence, which is essential for a fully autonomous planting process performed by autonomous vehicles or robots. The following work therefore deals with the development and construction of a prototype for vegetable planting via a robotic platform. This prototype is designed to meet the requirements of a conventional planter and carry out the planting process automatically using a robotic platform. To ensure a robust robotic planting process, an AI-based control system has been integrated that can detect and adjust the planting quality. For this reason, the planting unit was designed to allow dynamic changes in working depth and furrow width. By dynamically controlling these planting parameters, there is potential for a more sustainable planting process with lower energy requirements. A number of evaluations have been carried out to validate the described characteristics of the prototype planting unit.

Ultra-microstructure analysis and model development of bamboo fiber cell walls

Bamboo fiber cell walls are crucial mechanical load-bearing units in plants, significantly influencing their physical and mechanical properties. This study explored the multi-layered structure and microfibril orientation of typical moso bamboo fiber with two broad layers. The microfibrils in the primary cell wall exhibited a disordered mesh-like structure with a microfibril angle (MFA) of 90°. The alternating narrow and broad layers in the secondary walls constituted the growth cycle layer together. Within this structure, the microfibrils were oriented in both Z-helices and S-helices. In the narrow layers, the MFA transitioned gradually from outer to inner layers, ranging from approximately 70° to 30°. Conversely, the broad layers had smaller MFA, ranging from about 5° to 20°. Finally, a typical model of multi-layered microfibril orientation of 4-year-old moso bamboo fiber cells was proposed.

Renewable energy-water nexus: Optimal design of an integrated system including a single flash geothermal plant, Kalina cycle, and seawater desalination units

This paper concerns the optimization of a dual-purpose desalination system based on a geothermal flash cycle, a Kalina cycle, and a desalination process. A non-linear mathematical programming (NLP) optimization is developed and implemented in GAMS –General Algebraic Modelling System– a high-level modeling environment widely used in process systems engineering (PSE). CONOPT, a NLP derivative-based optimization algorithm, is employed. Furthermore, dynamic link libraries (DLLs) are developed and implemented in C programming code to calculate the thermodynamic properties of all process streams. The DLLs are systematically called from the GAMS environment. Additionally, a solution strategy has been devised to facilitate model convergence. In this strategy, several models are solved sequentially, commencing with the simplest model and progressing to solve the most complex model. This approach enables the optimal sizing and operating conditions of all process units to be obtained simultaneously. Two process configurations, differing in the type of seawater desalination system (reverse osmosis and multi-stage flash desalination systems), are optimized. The proposed mathematical models are effective decision-making tools for the design and synthesis of integrated geothermal power and seawater desalination processes. They can be used as either simulators or optimizers, depending on the number of degrees of freedom specified by the user.

RAMD and transient analysis of a juice clarification unit in sugar plants

RAMD and transient analysis of a juice clarification unit in sugar plants

Repositioning of an Engineering Works Complex as an Industrial Hub for Spare Parts and Components Production

Ajaokuta Steel Company Limited (ASCL) comprises several units, including the Engineering Works Complex, which is one of the key auxiliary units of the steel plant. This complex is equipped with the necessary tools and machinery for producing fixtures and spare parts that meet a wide range of requirements. These machines are operated by welltrained engineers, skilled technicians, and artisans. The complex is designed to carry out repairs on equipment across the entire steel plant, as well as to manufacture spare parts for external agencies. Additionally, facilities are available for training technicians and artisans. The Engineering Works Complex consists of five major workshops: the Machine and Tools Shop, Forge and Fabrication Shops, Foundry and Pattern Making Shops, Power Equipment and Repair Shops, and the Rubberizing Shop. It is fully equipped to meet the industrial demand for spares and consumables, and it has the capacity to serve as a research institution where modern research can be conducted. This research aims to explore the potential of repositioning the Engineering Works Complex at Ajaokuta Steel Company as a leading industrial hub for the production of spare parts and components in Nigeria. The study will analyze the potential economic benefits of this repositioning, such as increased employment opportunities, higher productivity, and greater contributions to the national economy. By drawing on case studies from other countries that have successfully developed their engineering sectors, the research will provide insights and lessons that can be applied to the Nigerian context. The Engineering Works Complex is actively utilizing the government's local content policy to achieve these goals. With the necessary attention, including adequate funding for the various shops within the complex, it could generate significant revenue and create employment opportunities in downstream industries, ultimately contributing to the industrialization of local communities and the country at large.

Distribution of Rare Earth Elements in Ash from Lignite Combustion in Polish Power Plants.

Rare earth elements are an essential critical raw material in the development of modern technologies and are highly sensitive to both supply chain disruptions and market turbulence. The presented study examines the characteristics of fuel, fly ash, and bottom ash from lignite combustion in power plant units. Also, we attempted to determine the amount of amorphous glass in the ashes and whether and to what extent the glass from the ash samples is bound to REY. The suitability of the ash was assessed as an alternative source of REY. The fuel and ash samples were acquired from power plants in Poland. The tests determined the fuel quality parameters, including the chemical and phase composition, of amorphous glass using ICP-MS and XRD methods, respectively. The study showed that all ash samples dissolved in 4% HF were enriched in REY. The efficiency of REY enrichment varied, and its presence in the residue samples was found to be in similar proportions compared to the raw sample. All ash residue samples were enriched in critical elements. The obtained values of the Coutl prospective coefficient allowed for the classification of some of the analyzed ashes and their residues after dissolution in 4% HF as prospective REY raw materials.

Experimental Study of the Stress State of a Polymer Composite in a State of Compression

Long-term operation of the supporting surfaces of large-sized parts, in particular tubular units of thermal power plants, leads to the destruction of the contact surfaces. Moisture penetrates into the formed discontinuities, and the vibrations present in the equipment in use rapidly increase the gap, reaching values of 10–15 mm. The authors of this article proposed the application of a composite layer of multimetal 1018 material without performing additional preparatory operations, ensuring the mandatory penetration of the material into the body of the supporting surface. This depth provides additional stability by maintaining boundary conditions. To determine the rational thickness of the composite layer, mathematical modeling of static loading of samples with different thicknesses in a wide range of values (from 2 mm to 12 mm) was performed. It was determined that the effective implementation of the developed technology was possible due to an increase in the load-bearing capacity of the composite material by creating additional grooves, or artificially creating grooves by welding, in the body of the part with a depth of 2.5–3 mm. The optimal excess of the composite was 1.0–1.5 mm. The proposed technology increases the stability of the composite layer up to three times and allows restoration without the use of mechanical treatment. The increase in the maximum stress values was 770 MPa, compared to the standard technology of 205 MPa.

Solutions for the Implementation of Algorithms for Closed-Loop Control of the Frequency and Power of Large Power Plant Units Comprising Once-Through Boilers

Solutions for the Implementation of Algorithms for Closed-Loop Control of the Frequency and Power of Large Power Plant Units Comprising Once-Through Boilers

Participation of wind-storage combined system in the secondary frequency regulation control strategy of power grid

Abstract The secondary frequency modulation of the unit, that is, the automatic generation control (AGC), is the process of increasing or decreasing the power of the power generation unit by the power plant unit according to the dispatching command issued by the power grid dispatching center, and then using the frequency modulator to restore the frequency. Based on the principle of AGC, this paper establishes a frequency dynamic response model of the secondary frequency modulation of the traditional unit and the wind storage participation system including load frequency control (LFC) and traditional proportional-integral-derivative (PID) controllers, determines the frequency modulation control strategy of wind storage, and uses the distribution mode based on Area Control Error (ACE) signal to assist in the secondary frequency modulation. In order to solve the parameter optimization problem of the classical PID controller when the wind-storage combined system participates in the secondary frequency modulation under the large load disturbance, a parameter optimization model of the controller with PID was established, and the ITAE evaluation index was finally selected as the fitness function by comparing different fitness evaluation indexes. To overcome the problem that the conventional Particle Swarm Optimization (PSO) is prone to local extremum, the inertia weights and learning factors are adjusted nonlinearly to balance and optimize the global and local optimization capabilities and improve the search efficiency, and the parameters of the PID controller are optimized by the improved PSO algorithm. The simulation results show that the proposed algorithm improves the secondary frequency modulation effect under the background of a high proportion of renewable energy connected to the power grid.

Bimodal pattern of allometric scaling along grapevine shoots.

Each branch internode, and the organs growing on it, can be seen as a single morphological phytomer subunit, made of structurally and functionally interrelated components. However, allometric relationships between anatomy and morphology of these subunits remain unclear, particularly in the axial context. This study aims to address this knowledge gap, by measuring morpho-anatomical parameters and their allometric relationships along grapevine shoots. To facilitate comparison, shoot length was normalized and a relative position index was calculated for each internode, ranging from 0 at the base to 1 at the apex. Scaling relationships between morpho-anatomical parameters along the axis were developed and validated by statistical modeling. Most morpho-anatomical parameters displayed an axial behaviour of increasing then decreasing in size from base to apex, with the exception of shoot diameter and shoot vessel density. Relative position index of 0.2 acted as the data turning point for most variables analysed. During the first phase (relative position index below 0.2), the phytomer organs traits are uncoupled and show weak allometric correlation, and during the second phase the traits are strongly allometrically related. Our findings suggest that allometric relationships along grapevine shoots are not constant- they exhibit a bimodal pattern, possibly influenced by seasonal temperatures. This work could aid managing productivity shifts in agricultural and natural systems under global climate change and add to basic knowledge of differentiation and development of growth units in plants.

Multi-objective modeling of price and pollution in large-scale energy hubs with load management

This study introduces a novel multi-objective model that addresses emission costs, large-scale user operational expenses, and the efficiency of the electric storage system within an integrated energy hub encompassing heating, water, power, and gas sources. A key objective of this model is to maximize the performance of the electrical storage system. The study employs the epsilon-constraint method to construct the Pareto front, aiming to balance profitability and emission reduction from virtual power plant units. The final decision-making process utilizes a fuzzy decision-making technique. Additionally, demand response program (DRP) is incorporated to optimize peak-hour demand and align the load profile with defined objectives. The proposed approach is evaluated across various operational scenarios within a sample system, demonstrating its effectiveness and potential benefits in terms of cost reduction and environmental impact mitigation. Focusing on environmental impact, the carbon dioxide (CO2) emissions are also lower under the DRP scenario, amounting to 10253.92 kg without DRP versus 10127.74 kg with DRP. This reduction in emissions aligns with sustainable energy management goals, showcasing DRP's capability to mitigate environmental impacts associated with energy generation and consumption. The percentage improvements in total costs and emissions further highlight the advantages of employing DRP. The reductions in total costs range from approximately 1.2%–1.4%, demonstrating cost savings across different cost categories. Similarly, the decrease in CO2 emissions by approximately 1.2% underscores DRP's role in promoting environmentally friendly energy practices.

Evaluation of productivity and efficiency of a large-scale coupled or decoupled aquaponic system

Aquaponics, a sustainable agricultural method, is gaining attention for its closed-loop system's potential to address diverse environmental and economic challenges in traditional agriculture. The aim of this study was to fill knowledge gaps in scaling up lab-scale systems to larger-scale decoupled aquaponics, offering a comprehensive understanding of the system's productivity and water and fertiliser use efficiency. In coupled aquaponics (CAP), the aquaculture, and the hydroponic units are arranged in a single loop, and water flows continuously from the fish tanks to the plant unit and vice-versa. In decoupled aquaponics (DCAP), the aquaculture and hydroponics units are arranged in a multi-loop setup as separate functional units that can be controlled independently. This work compared coupled aquaponics, decoupled aquaponics and hydroponics (HP, in perlite slabs) under the same climatic conditions with a substrate grown crop in a pilot scale greenhouse. The evaluation of growth parameters, yield, water, and fertiliser use for basil, cucumber, parsley, and tomato cultivations co-cultivated with the tilapia recirculating aquaculture system (RAS) are presented. The highest yields were achieved by DCAP plants in all experiments (15% higher than HP and 19% than CAP for basil, 38% than CAP in cucumber, 17% and 72% than HP and CAP in parsley, and 8% and 55% for HP and CAP in tomato experiments). The CAP treatment that did not receive any fertilisers presented the highest water use efficiency compared to both HP and DCAP treatments. Also, compared to HP, the DCAP treatment presented higher water and fertilisers use efficiency. Consequently, the adoption of decoupled aquaponic systems is the key to aquaponic evolution in the future.