Capacity Adjustment Research Articles

Chloroplast ATP synthase restricts photosynthesis under fluctuating light in tomato but not in maize

Photosynthesis in fluctuating light requires coordinated adjustments of diffusion conductance and biochemical capacity, but the role of chloroplast ATP synthase activity (gH+) in dynamic photosynthesis is not well understood. In this study, we measured gas exchange, chlorophyll fluorescence and electrochromic shift signals in fluctuating light for leaves of tomato (Solanum lycopersicum) and maize (Zea mays). During the transition from sun to shade, simultaneous increases in gH+, effective quantum yield of PSII, and net CO2 assimilation rate (AN) occurred in tomato but uncoupled in maize, indicating that gH+ limited AN during the sun-to-shade transition in tomato but not in maize. During the shade-to-sun transition, gH+ increased simultaneously with stomatal conductance, mesophyll conductance and Rubisco carboxylation capacity in tomato, suggesting that gH+ is an overlooked factor affecting light induction of AN in tomato. By comparison, gH+ maintained at high levels in maize and its AN was mainly restricted by stomatal conductance. Our results reveal that the kinetics of gH+ in fluctuating light differs between species, and chloroplast ATP synthase may be a potential target for improving dynamic photosynthesis in crops such as tomato.

The Propagation of Congestion on Transportation Networks Analyzed by the Percolation Process

Percolation theory has been widely employed in network systems as an effective tool to analyze phase transitions from functional to nonfunctional states. In this paper, we analyze the propagation of congestion on transportation networks and its influence on origin–destination (OD) pairs using the percolation process. This approach allows us to identify the most critical links within the network that, when disrupted due to congestion, significantly impact overall network performance. Understanding the role of these critical links is essential for developing strategies to mitigate congestion effects and enhance network resilience. Building on this analysis, we propose two methods to adjust the capacities of these critical links. First, we introduce a greedy method that incrementally adjusts the capacities based on their individual impact on network connectivity and traffic flow. Second, we employ a Particle Swarm Optimization (PSO) method to strategically increase the capacities of certain critical links, considering the network as a whole. These capacity adjustments are designed to enhance the network’s resilience by ensuring it remains functional even under conditions of high demand and congestion. By preventing the propagation of congestion through strategic capacity enhancements, the transportation network can maintain connectivity between OD pairs, reduce travel times, and improve overall efficiency. Our approach provides a systematic method for improving the robustness of transportation networks against congestion propagation. The results demonstrate that both the greedy method and the PSO method effectively enhance network performance, with the PSO method showing superior results in optimizing capacity allocations. This research is crucial for maintaining efficient and reliable mobility in urban areas, where congestion is a persistent challenge, and offers valuable insights for transportation planners and policymakers aiming to design more resilient transportation infrastructures.

Execution of revised BMIM similarity coefficient for part family formation in reconfigurable manufacturing system

The reconfigurable manufacturing system (RMS) is an advanced manufacturing strategy that enables precise adjustment of functionality and capacity to meet fluctuating demands economically. RMS focuses on part families, allowing configurations to be adapted for new part requirements. Optimizing flow line design to produce various parts involves minimizing reconfigurations and associated costs by enhancing operation sequence similarity. This article proposes a novel sequence optimization using the Longest Common Subsequence (LCS) method to reduce bypassing moves and machine idle times. The study introduces a similarity coefficient derived from LCS and employs average linkage hierarchical clustering to categorize parts in a case study. Unlike traditional methods, this approach considers material movements both before the initial machine and after the final processing station, addressing gaps in bypassing move calculations. The impact of different weighting scenarios for Type-II moves (ω) and machine idleness (β) on clustering was examined. For example, with Type-II move weights (ω) of {1.0, 0.6, 0.3, 0.0} and equal weightings for bypassing moves (α) and machine idleness (β) set at 0.5, a threshold value of 0.3 results in eight clusters, such as Cluster 1 {1, 11, 10, 12} and Cluster 3 {3, 5, 6, 4, 15, 9, 13, 14, 7, 8}. Lower threshold values lead to fewer clusters with larger sizes, indicating a more consolidated part family grouping. Various Type-II move weights and material handling scenarios demonstrate how different weighting configurations affect clustering and part family sizes. This approach enhances RMS efficiency by integrating comprehensive material handling considerations and optimizing clustering based on operational similarities.

Protective effects of the exogenous application of salicylic acid and chitosan on chromium-induced photosynthetic capacity and osmotic adjustment in Aconitum napellus.

Chitosan (CTS) is recognized for enhancing a plant's resilience to various environmental stresses, such as salinity and drought. Moreover, salicylic acid (SA) is acknowledged as a growth regulator involved in addressing metal toxicity. However, the effectiveness of both compounds in mitigating Cr-induced stress has remained relatively unexplored, especially in the case of Aconitum napellus, a medicinally and floricultural important plant. Therefore, the primary objective of this study was to investigate the potential of CTS and SA in alleviating chromium (Cr)-induced stress in A. napellus. To address these research questions, we conducted a controlled experiment using potted plants to evaluate the individual and combined impacts of CTS and SA on plants exposed to Cr stress. Foliar application of CTS (0.4g/L) or SA (0.25 mmol/L) led to significant improvements in the growth, chlorophyll content, fluorescence, and photosynthetic traits of A. napellus plants under Cr stress. The most notable effects were observed with the combined application of CTS and SA, resulting in increases in various morphological parameters, such as shoot length (2.89% and 7.02%) and root length (27.75% and 3.36%) under the Cr 1 and Cr 2 treatments, respectively. Additionally, several physiological parameters, such as chlorophyll a (762.5% and 145.56%), chlorophyll b (762.5% and 145.56%), carotenoid (17.03% and 28.57%), and anthocyanin (112.01% and 47.96%) contents, were notably improved under the Cr 1 and Cr 2 treatments, respectively. Moreover, the combined treatment of CTS and SA improved the fluorescence parameters while decreasing the levels of enzymatic antioxidants such as catalase (27.59% and 43.79%, respectively). The application also notably increased osmoprotectant parameters, such as the total protein content (54.11% and 20.07%) and the total soluble sugar content (78.17% and 49.82%) in the leaves of A. napellus in the Cr 1 and 2 treatments, respectively. In summary, these results strongly suggest that the simultaneous use of exogenous CTS and SA is an effective strategy for alleviating the detrimental effects of Cr stress on A. napellus. This integrated approach opens promising avenues for further exploration and potential implementation within agricultural production systems.

Closed-loop workload input–output control of production systems: A hybrid simulation study

Workload Control (WLC) is a method of adjusting the overall workload in the production system by controlling the input of production orders and the output of produced items. It contributes to the predictability of lead times and more accurate delivery date commitments in make-to-order manufacturing. Input control relates to order release and output control to capacity adjustment. In a recent previous work, a novel approach to integrated input–output control has been proposed: a dynamic closed-loop model where automatic feedback control is added and where order release and capacity decisions are based on the observed shop floor state. In this paper, this approach is further investigated in a more realistic hybrid simulation setting, combining discrete-time controllers and a discrete-event model of a manufacturing shop. The hybrid model was applied to two different systems: an elementary 4-machine shop floor (as a proof of concept) and a more complex real system, a manufacturing cell of cylinder liners. The results show that simultaneous input–output control is effective and enables the systems to maintain WIP balance, absorb demand fluctuations, and effectively reject disturbances. The simulations of the complex system showed that it might be advantageous to provide more local or more global information to the controllers, depending on the variability of the processing times and on the managerial focus. Closed-loop discrete-event models for WLC production control are unprecedented. Also, a simultaneous input and output control setting is much less reported in WLC literature than settings with input control only (i.e., order release only). This paper contributes in both ways.

Genome-wide analysis of the AP2/ERF gene family in Pennisetum glaucum and the negative role of PgRAV_01 in drought tolerance

APETALA2/ethylene-responsive (AP2/ERF) plays crucial roles in resisting diverse stresses and in regulating plant growth and development. However, little is known regarding the structure and function of the AP2/ERF genes in pearl millet (Pennisetum glaucum). The AP2/ERF gene family may be involved in the development and maintenance of P. glaucum resilience to abiotic stresses, central to its role as a vital forage and cereal crop. In this study, PgAP2/ERF family members were identified and comprehensive bioinformatics analyses were performed, including determination of phylogenetic relationships, gene structures, conserved motifs, chromosomal localization, gene duplication, expression pattern, protein interaction network, and functional characterization of PgRAV_01 (Related to ABI3/VP1). In total, 78 PgAP2/ERF members were identified in the P. glaucum genome and classified into five subfamilies: AP2, ERF, DREB, RAV, and soloist. Members within the same clade of the PgAP2/ERF family showed similar gene structures and motif compositions. Six duplication events were identified in the PgAP2/ERF family; calculation of Ka/Ks values showed that purification selection dominated the evolution of PgAP2/ERFs. Subsequently, a potential interaction network of PgAP2/ERFs was generated to predict the interaction relationships. Additionally, abiotic stress expression analysis showed that most PgAP2/ERFs were induced in response to drought and heat stresses. Furthermore, overexpression of PgRAV_01 negatively regulated drought tolerance in Nicotiana benthamiana by reducing its antioxidant capacity and osmotic adjustment. Taken together, these results provide valuable insights into the characteristics and functions of PgAP2/ERF genes, with implications for abiotic stress tolerance, and will ultimately contribute to the genetic improvement of cereal crop breeding.

Adjustment of storage capacity for non-structural carbohydrates in response to limited water availability in two temperate woody species.

Reserves of non-structural carbohydrates (NSC) stored in living cells are essential for drought tolerance of trees. However, little is known about the phenotypic plasticity of living storage compartments (SC) and their interactions with NSC reserves under changing water availability. Here, we examined adjustments of SC and NSC reserves in stems and roots of seedlings of two temperate tree species, Acer negundo L. and Betula pendula Roth., cultivated under different substrate water availability. We found that relative contents of soluble NSC, starch and total NSC increased with decreasing water availability in stems of both species, and similar tendencies were also observed in roots of A. negundo. In the roots of B. pendula, soluble NSC contents decreased along with the decreasing water availability, possibly due to phloem decoupling or NSC translocation to shoots. Despite the contrast in organ responses, NSC contents (namely starch) positively correlated with proportions of total organ SC. Individual types of SC showed markedly distinct plasticity upon decreasing water availability, suggesting that water availability changes the partitioning of organ storage capacity. We found an increasing contribution of parenchyma-rich bark to the total organ NSC storage capacity under decreasing water availability. However, xylem SC showed substantially greater plasticity than those in bark. Axial storage cells, namely living fibers in A. negundo, responded more sensitively to decreasing water availability than radial parenchyma. Our results demonstrate that drought-induced changes in carbon balance affect the organ storage capacity provided by living cells, whose proportions are sensitively coordinated along with changing NSC reserves.

Improved Cell Allocation Strategies Using K-Means Clustering in Congested 6TiSCH Environments.

The 6TiSCH protocol (IEEE 802.15.4e) is crucial for the Industrial Internet of Things (IIoT), utilizing a time-slotted channel hopping (TSCH) mode based on node distribution. In this study, we propose an innovative cell allocation strategy based on node position clustering using the K-means algorithm, specifically designed to address congestion and optimize resource distribution in the 6TiSCH network. Our mechanism effectively groups nodes into clusters, allowing for dynamic adjustment of cell capacities in congested areas by analyzing traffic patterns and the spatial distribution of nodes. This clustering approach enhances the efficiency of slot frame utilization and minimizes communication delays by reducing interference and improving routing stability. The proposed strategy leverages the clustering results to improve cell usage efficiency and reduce communication latency between nodes. By tailoring cell allocation to the specific traffic needs of each cluster, we significantly reduce packet loss, manage congestion more effectively, and enhance data transmission reliability. We evaluated the clustering method using the K-means algorithm through experiments with the 6TiSCH simulator. Additionally, we considered using objective functions in Routing Protocol for Low-Power and Lossy Networks (RPL), such as OF0 and MRHOF, to assess clustering results and their impact on throughput and packet delivery. Our method resulted in significantly improved average performance metrics. Under the OF0 routing protocol, we achieved a 30.01% latency reduction, a 15.95% faster joining time, an 8% higher packet delivery ratio, and a 13.82% throughput increase. Similarly, we observed a 12.34% improvement in packet delivery ratio, 21.06% latency reduction, 12.68% faster joining time, and 25.97% higher throughput speed with the MRHOF routing protocol. These findings highlight the effectiveness of the improved cell allocation strategy in congested 6TiSCH environments, offering a better solution for enhancing network performance in IIoT applications.

Multi-regional economic recovery simulation using an Adaptive Regional Input–Output (ARIO) framework

The economic repercussions of natural hazards extend beyond immediate damages, impacting more than the directly affected regions through trading ties and interrupted service provisions. The Adaptive Regional Input–Output (ARIO) model has been developed to assess these indirect impacts by considering changes in productive capacity and demand-driven output adjustments. We extend a recently refined ARIO model (R-ARIO) to conduct a multi-regional multi-sector analysis. This extension accounts for the geographical disparities in direct damages and inter-regional economic interactions. To illustrate the effectiveness of this approach, we present a case study of the 2011 Tohoku earthquake and assess its economic impacts across 13 prefectures in the East-Japan region. The paper further compares the outcomes of single- and multi-regional analyses to showcase the effect of inter-regional trading ties on economic resilience. Additionally, trade-offs involved in selecting the study area boundary for the multi-regional analysis are discussed.

A genetic algorithm to solve the production lot-sizing problem with capacity adjustment

When dynamic production capacity is considered in production lot-sizing plans, it becomes very challenging to efficiently determine the optimal production plan. Many papers apply “at most one fractional production period” to develop efficient algorithms, but those algorithms are still time consuming. In this paper, in a special situation where costs are non-speculative, we provide a novel proposal based on “at least one balance period”, in which the products made in this period not only satisfy the demands in this period but also backlogged demands and some demands after this period, to obtain an efficient algorithm. This algorithm complexity is one level lower than the algorithm without non-speculative cost assumptions in the literature regarding the number of periods in their time complexity function. Then, in a general situation, we propose a combination of two complementary algorithms as an efficient heuristic method. Moreover, in the literature, the estimation of computation time complexity in searching for the optimal production plan considers only the number of capacity levels and production periods on theoretical view. However, with numerical experiments, we observe that demand variation could also have significant effects on the computation time in practice.

Work Faster, Work in Parallel, or Work Overtime? An Assessment of Short-Term Capacity Adjustments by Simulation

Many firms use short-term capacity adjustments to deal with demand changes over time, and a broad literature assesses when and where to adjust capacity. This study highlights that this may be dependent on the type of capacity flexibility used to actually realize the adjustment. By comparing for the first-time capacity adjustments by speeding up processing rates, working in parallel, or using overtime, significant differences in the operational performance are identified, with the latter resulting in the best percentage tardy performance. This provides important insights for the interpretation of the existing literature, guides the future literature, and helps managers to make better decisions.

Geographic industry concentration and asymmetric cost behavior

AbstractThis research diverges from the existing literature on cost stickiness by examining the relationship between a firm's geographic proximity to industry peers, termed industry co‐location, and its asymmetrical cost behavior. We propose that managerial decisions regarding resource adjustment are influenced by the state of resource markets in the firm's vicinity, hypothesizing that a high concentration of industry peers triggers downward asset price spirals during simultaneous resource liquidation. Additionally, we anticipate that industry‐wide demand exceeding fixed capacity exacerbates congestion costs, thereby diminishing bargaining power in local resource markets. We predict that heightened resource adjustment costs linked to industry co‐location discourage managers from reducing capacity commitments, thereby increasing cost stickiness. Our findings support this prediction, demonstrating a positive association between industry co‐location and cost stickiness. Moreover, we observe that cost stickiness intensifies when closely located industry peers experience declines in sales. This paper provides initial evidence illuminating the impact of industry co‐location on cost stickiness and suggests managerial implications to prevent costlier capacity adjustment through local resource markets.

A resource prediction method for air traffic cyber-physical-social system

Air traffic is exhibiting the characteristics of large flow, strong coupling, and high time variation. Therefore, the complex network of air traffic is more vulnerable to disturbances. When it is disturbed, the failure of some nodes spreads through dependency relationships in the network, resulting in cascade failure. In the event of a cascade failure, the network may quickly collapse until it is paralyzed, with widespread delays and flight cancellations. The current flow management and deployment methods still remain in the control-oriented stage, which is mainly completed by air traffic controls (ATCs), and lack of accurate flow adjustment and effective utilization of capacity. The whole air traffic system and its peripheral factors are intricate, so human and social factors must be integrated into the control and decision-making of the system. Considering engineering and social factors such as operation environment, social environment, personnel, rules, equipment, and information processing, we analyse the air traffic in a cyber-physical-social system (CPSS). To reflect the actual system behaviour rules, dynamic response, limit state, and so on, the corresponding computational experiment and comprehensive evaluation system are established. Based on neural networks and other technologies, a resource prediction scheme based on task demand is proposed for multi-dimensional resources such as airports, air routes, and ATC, to reduce the cost of system resource scheduling and improve resource utilization through resource prediction and adjustment. Finally, the accuracy of the proposed resource prediction algorithm is verified by theoretical analysis and simulation.

Bat thermoregulation in the heat: seasonal variation in evaporative cooling capacities in four species of European bats

Phenotypic flexibility is an important source of physiological variation in endotherms and plays an integral role in species’ response to rapid environmental changes. Studies of phenotypic flexibility have focused on winter acclimatization and cold endurance, and there are fewer data on summer acclimatization and adjustments in heat dissipation capacity, especially in Temperate-Zone species. We used indirect calorimetry and thermometry to test if thermoregulation at high air temperatures (Ta) varies between spring and summer in four species of European vespertilionid bats: Nyctalus noctula, Pipistrellus nathusii, P. pygmaeus, and P. pipistrellus. We measured subcutaneous body temperature (Tsub), evaporative water loss, and resting metabolic rate while exposing bats to a stepped profile of increasing Ta, from 28 °C–48 °C. We predicted that during summer, bats increase heat tolerance and evaporative cooling capacity, to better tolerate hotter Tas. In contrast, we found lower maximum ratios of evaporative heat loss (EHL) to metabolic heat production (MHP) during summer, but no seasonal differences in maximum Ta tolerated or Tsub. The main cause of this seasonal difference in maximum EHL/MHP seems to be from bats increasing EWL more gradually with increasing Ta in summer than spring, particularly in the smaller Pipistrellus species. Therefore, this seasonal variation in heat-dissipation strategies may reflect enhanced water conservation during summer to avoid dehydration, as bats are confined to roosts for longer and hotter days compared to spring.

A hybrid model for shop floor simulation and work-in-process feedback control

In this paper, a smart hybrid model for shop floor simulation and control is proposed based on dynamic modelling and control theory’s analytical tools. The model is smart because the production levels are automatically adjusted based on feedback loops, considering shop floor current states (i.e., it is a closed-loop model). It is hybrid because it deals with discrete and continuous transitions, and integrates two approaches: switched arrival systems (SAS) and bond graphs (BG). This novel integrated SAS + BG model is applied to a production system in the food industry and four production control rules (well-known from the operations management literature) are tested: pure push and pull rules and extended push and pull rules. The results showed that the SAS is effective to dynamically represent intermittent production systems, and its use, coupled with bond graphs, allows the definition of capacity adjustment and production control rules that are effective to control the work in process (WIP). The extended pull rule outperformed the remaining ones, corroborating prior literature. This paper contributes with a novel approach that is modular and can be extended to represent the closed-loop dynamics of different configurations of multi-product multi-station production systems, with a disaggregated level of detail.

Extending ConWIP by flexible capacity and WIP-Cap adjustment for a make-to-order multi-item multi-stage production system

Extending ConWIP by flexible capacity and WIP-Cap adjustment for a make-to-order multi-item multi-stage production system

Seasonal variation in the relationship between leaf chlorophyll content and photosynthetic capacity

AbstractAccurate estimation of photosynthesis is crucial for ecosystem carbon cycle modelling. Previous studies have established an empirical relationship between photosynthetic capacity (maximum carboxylation rate, Vcmax; maximum electron transport rate, Jmax) and leaf chlorophyll (Chl) content to infer global photosynthetic capacity. However, the basis for the Chl‐Vcmax relationship remains unclear, which is further evidenced by the temporal variations in the Chl‐Vcmax relationship. Using multiple years of observations of four deciduous tree species, we found that Vcmax and Jmax acclimate to photosynthetically active radiation faster (4–8 weeks) than Chl (10–12 weeks). This mismatch in temporal scales causes seasonality in the Vcmax‐Chl relationship. To account for the mismatch, we used a Chl fluorescence parameter (quantum yield of Photosystem II, Φ(II)) to tighten the relationship and found Φ(II) × Chl correlated with Vcmax and Jmax (r2 = 0.74 and 0.72 respectively) better than only Chl (r2 = 0.7 and 0.6 respectively). It indicates that Φ(II) accounts for the short‐term adjustment of leaf photosynthetic capacity to light, which was not captured by Chl. Our study advances our understanding of the ecophysiological basis for the empirical Vcmax‐Chl relationship and how to better infer Vcmax from Chl and fluorescence, which guides large‐scale photosynthesis simulations using remote sensing.

The light-responsive transcription factor SlBBX20 improves saline-alkali resistance of Solanum lycopersicum by affecting photosynthetic capacity, antioxidant capacity, and osmotic adjustment

The transcription factor BBX family is associated with plant responses to abiotic stress. Among the 31 SlBBXs genes in tomato, SlBBX20 is the most strongly induced by saline-alkali stress. However, the response mechanism of the SlBBX20 transcription factor under saline-alkali stress remains unclear. In this study, we investigated the effect of the SlBBX20 transcription factor on saline-alkali tolerance in tomato using wild-type (WT), SlBBX20 overexpression lines, SlBBX20-silenced materials (TRV2-SlBBX20) and their controls (TRV2-empty). Under normal conditions, overexpression of SlBBX20 increased tomato photosynthetic capacity (contents of chlorophyll a, chlorophyll b and carotenoids, net photosynthetic rate), leaf palisade and spongy tissue thickness, and total antioxidant capacity. In contrast, the photosynthetic capacity and total antioxidant capacity of SlBBX20 silenced material did not change significantly relative to the control. Under saline-alkali stress, overexpression of SlBBX20 significantly reduced the relative conductivity, malondialdehyde content, reactive oxygen species levels (O2•−, H2O2), and increased the relative water content, photosynthetic capacity, total antioxidant capacity, antioxidant enzyme activities (peroxidase, superoxide dismutase, and catalase) and proline content in tomato leaves. And silencing SlBBX20 showed the opposite trend. Furthermore, through transcriptome sequencing of WT and SlBBX20-OE lines grown in saline-alkali stress condition at 0 h and 12 h, three differentially expressed genes related to saline-alkali stress (SlP5CR, SlHsp21.6A, SlHsp26.2) were identified. Yeast one-hybrid and dual-luciferase assays confirmed that SlBBX20 might bind to the G-box cis-acting elements in the promoter regions of SlP5CR, SlHsp21.6A, and SlHsp26.2 genes, exerting transcriptional regulatory functions. In conclusion, overexpression of SlBBX20 enhances saline-alkali tolerance in tomatoes by sustaining leaf photosynthetic capacity, reducing ROS accumulation, and elevating antioxidant enzyme activity and proline content.

Enhancing Make-to-Order Manufacturing Agility: When Flexible Capacity Meets Dynamic Pricing

The rise of online marketplaces has raised customer expectations regarding customization and lead time. It poses significant challenges to manufacturing firms and prompts a move from make-to-stock to a more flexible make-to-order system. Compared to make-to-stock settings, make-to-order systems cannot smooth fluctuations in demand using available stock. While viewing dynamic pricing as a useful strategy to balance supply with demand, many manufacturing firms can also create capacity flexibility. In that scenario, system costs could be cut by managing capacity and demand simultaneously. In this paper, we consider a make-to-order production environment with base and surge capacity as well as the ability to adjust product pricing. Our main focus is on operational decision-making, assuming that the base capacity and surge capacity are fixed, but activating the surge capacity incurs a setup cost. Initially, we propose a stochastic control model to reflect this complex decision problem. However, our initial model leads to an intractable dynamic programming problem. To overcome this, we convert the problem to a more tractable diffusion control problem. This approach helps to reveal the conditions under which utilizing flexible capacity is more advantageous than relying solely on fixed capacity. When flexible capacity is advantageous, we provide a solution to the diffusion control problem that can guide optimal capacity and price adjustments. We discover an interesting interplay between capacity adjustment and dynamic pricing. In particular, we find that the price, which aims at reducing congestion, may not monotonically increase with the congestion level when capacity adjustments incur a fixed cost.

Research on Thermal Adaptability of Flexible Operation in Different Types of Coal-Fired Power Units

The flexible mode of operation of coal-fired units can accommodate large-scale renewable power integration into the grid, providing more grid capacity. The flexibility transformation of coal-fired units in thermal power plants can be achieved through main steam extraction and reheated steam extraction. A 300 MW subcritical unit, 600 MW subcritical unit and 660 MW ultra-supercritical unit with six flexible operation modes were chosen as the research model to investigate the thermal adaptability for flexible operation. The results show that from the perspective of the source of steam extraction, the main steam extraction scheme is suitable for the flexible adjustment of peak load capacity, and the reheated extraction scheme is suitable for the flexible operation of low load and high thermal efficiency. Moreover, from the perspective of thermal performance adaptability, the 600 MW unit has a wider load regulation capacity than the 300 MW and 660 MW units, and is suitable as the peak shaving unit. This work can provide theoretical guidance for different types of coal-fired units in choosing flexible operation schemes.