Supply-demand Imbalance Research Articles

Wind intermittency and supply-demand imbalance: Evidence from U.S. regional power markets

Wind intermittency and supply-demand imbalance: Evidence from U.S. regional power markets

Re-evaluation of CO<sub>2</sub> storage capacity of depleted fractured-vuggy carbonate reservoir

<p>Confronting the dual crises of energy supply-demand imbalances and climate change, carbon neutrality emerges as a vital strategy for China in mitigating resource and environmental constraints, while fostering technological advancement and sustainable growth. In the context of extensive hydrocarbon exploitation, the CO<sub>2</sub> storage capacity within depleted oil fields could be significantly underestimated in comparison to the prevalent practice of saline aquifer sequestration. In this study, we employ both theoretical and computational models to investigate the temporal (from microseconds to millennia) and spatial (spanning pore, Darcy, and hybrid scales) dynamics of CO<sub>2</sub> trapping mechanisms in post-depletion carbonate reservoir with fractured-vuggy systems. The multiscale storage efficiency factor is obtained from simulation results and substituted into the existing analytical models for calculating CO<sub>2</sub> storage volume in field cases, reappraising the carbon sequestration potential of fracture-vuggy carbonate. Drawing from comparative results, we discern that depleted carbonate can dissolve and mineralize more CO<sub>2</sub> than saline layer, despite the storage volume can be considerably less. The annual storage capacity per well of two geological systems are comparable. Under unfavorable geological conditions, the minimum unit storage capacity of carbonate reservoir exceeds that of saline aquifer. The study's discoveries offer fresh perspectives on reliable and efficient CO<sub>2</sub> geological storage, contributing to the reduction of atmospheric carbon emissions and advancing the utilization of underground resources and global energy transformation.</p>

Nonlinear Influence and Interaction Effect on the Imbalance of Metro-Oriented Dockless Bike-Sharing System

Dockless Bike-Sharing (DBS) is an eco-friendly, convenient, and popular form of ride-sharing. Metro-oriented DBS systems have the potential to promote sustainable transportation. However, the availability of DBS near metro stations often suffers from either scarcity or overabundance. To investigate the factors contributing to this imbalance, this paper examines the nonlinear influences and interactions that impact the DBS system near metro stations, with Shenzhen, China serving as a case study. An ensemble learning approach is employed to predict the imbalance state. Then, the machine learning interpretation method (i.e., SHapley Additive exPlanations) is used to quantify the contribution of effects, discover the strength of interactions between factors and uncover their underlying interactive connections. The results indicate the influence of external factors and the relations between pairwise variables (e.g., road density and the day of the week) for each imbalanced state. Provide two quantized sets of factors that can result in the supply-demand imbalance and support future transport planning decisions to enhance the accessibility and sustainability of Metro-oriented DBS systems.

Ion injection bipolar membrane electrodialysis realizes over 8 mol/L NaOH conversion from a brine stream

AbstractThe chlor‐alkali process is currently the predominant technology for caustic soda production but has several major challenges, such as enormous energy demand and supply–demand imbalance between NaOH and Cl2 in downstream industries. Herein, we propose a novel ion‐injection bipolar membrane electrodialysis (IJBMED) system that is capable of boosting water splitting in a bipolar membrane with an ultrahigh current density while omittance concentration polarization in anion‐ and cation‐exchange membranes. The results indicate that the IJBMED approach enables one‐step conversion of the NaCl‐containing brine stream into 8.12 mol/L NaOH with specific energy consumption of 0.79 kWh/kg NaOH (23 wt.% → 25 wt.%), compared to 2.15 kWh/kg NaOH (28 wt.% → 30 wt.%) for the chlor‐alkali process. The advantages of low energy consumption and omittance of chlorine emissions suggest that IJBMED might be a promising alternative to the chlor‐alkali process, revealing a new route to reshape the chemical industry for caustic soda production.

Using Conversational AI to Facilitate Mental Health Assessments and Improve Clinical Efficiency Within Psychotherapy Services: Real-World Observational Study.

Most mental health care providers face the challenge of increased demand for psychotherapy in the absence of increased funding or staffing. To overcome this supply-demand imbalance, care providers must increase the efficiency of service delivery. In this study, we examined whether artificial intelligence (AI)-enabled digital solutions can help mental health care practitioners to use their time more efficiently, and thus reduce strain on services and improve patient outcomes. In this study, we focused on the use of an AI solution (Limbic Access) to support initial patient referral and clinical assessment within the UK's National Health Service. Data were collected from 9 Talking Therapies services across England, comprising 64,862 patients. We showed that the use of this AI solution improves clinical efficiency by reducing the time clinicians spend on mental health assessments. Furthermore, we found improved outcomes for patients using the AI solution in several key metrics, such as reduced wait times, reduced dropout rates, improved allocation to appropriate treatment pathways, and, most importantly, improved recovery rates. When investigating the mechanism by which the AI solution achieved these improvements, we found that the provision of clinically relevant information ahead of clinical assessment was critical for these observed effects. Our results emphasize the utility of using AI solutions to support the mental health workforce, further highlighting the potential of AI solutions to increase the efficiency of care delivery and improve clinical outcomes for patients.

Energy price bubbles and extreme price movements: Evidence from China's coal market

This study investigates the factors behind the extreme price movements in China's coal market, with a particular focus on the impact of climate risk and energy transition in recent years. The Generalized Sup Augmented Dickey-Fuller (GSADF) method is employed to detect coal price bubbles, and a dynamic model averaging (DMA) approach is then used to analyze the causes of these price bubbles. The findings reveal that price bubbles in the Chinese coal market are mainly triggered by fluctuations in international energy prices. The extreme prices are rooted in supply-demand imbalances resulting from energy transition, economic development, and geopolitical conflicts. Policies aimed at adjusting coal supplies can effectively mitigate abnormal coal price fluctuations in China, while normal coal price fluctuations are significantly influenced by changes in energy demand driven by macroeconomic development. During the green transition towards renewable energy, the current high prices of fossil energy present challenges to China's energy supply security but also offer opportunities for the development of the renewable energy market. However, energy transition has facilitated the spread of price bubbles across coal, natural gas, and renewable energy markets, potentially leading to contagion effects.

Assessing the Impact of Futures Trading Availability on Spot Market Dynamics of Indian Pepper

Modern agricultural tools boost productivity across crops. Pepper, a lucrative cash crop, attracts global cultivation, bolstering yields. However, heightened productivity brings risks like price fluctuations and supply-demand imbalances, impacting the market's stability and success. Utilizing futures contracts is a common strategy to mitigate risks, yet the challenge lies in ensuring the availability of futures aligned with the specific commodity and contract size. In the Indian context, where pepper futures have been introduced and withdrawn multiple times, this study seeks to examine the impact of the presence or absence of pepper futures trading on pepper spot prices. Econometric techniques such as the Johansen cointegration test, VECM, Granger causality test, and ARIMA modeling were employed to analyze market integration and price autocorrelation. Findings indicate short-term cointegration between pepper spot and futures markets, striving for long-term equilibrium. Futures were found to influence the pepper spot market. ARIMA modeling recommended ARIMA(11,1,7) during futures presence and ARIMA(1,2,2) during absence for representing distinct periods.

Spatial drivers of ecosystem services supply-demand balances in the Nanjing metropolitan area, China

Ecosystem services (ESs) are the foundation of human well-being. Previous studies have paid limited attention to the interactions among several factors that influence the balance of ESs supply and demand at the grid scale. This study focused on four ESs–water yield (WY), grain yield (GY), carbon storage (CS), and recreational services (RS)–and examined their supply and demand in the Nanjing Metropolitan Area (NMA) in 2000, 2010, and 2020 at the pixel level. Our primary objective was to pinpoint regions characterised by imbalances in ESs supply and demand. In addition, we aimed to explore the interactions among the key elements that contribute to these imbalances. The Geodetector model (GD) was employed to elucidate the 14 distinct primary driving factors influencing the ESs supply-demand balance and their interactions. Our results showed that imbalances in WY and CS supply-demand were predominantly identified in the northern and southern regions of the Yangtze River Basin and certain urban centres. Imbalances in GY were occasionally found in the peripheral areas of cities. The spatial patterns of RS supply-demand imbalances resembled population patterns. The interaction between annual runoff depth and the proportion of built-up land (PB) had the highest explanatory power for changes in the WY supply-demand balance at 54%. The interaction between population density (POP) and the proportion of cultivated land (PC) had the highest explanatory power for the GY supply-demand balance at 29%. The interaction between the proportion of forest land (PF) and average annual ground temperature had the highest explanatory power for the CS supply-demand balance at 67%. The combined effect of PB and Net primary productivity had the highest explanatory power for the RS supply-demand balance at 41%. Overall, this study demonstrated the spatial heterogeneity of ESs at a finer scale than at the county level. This is important for the effective conservation and sound management of ESs. These findings provide decision-makers with insights into regulating regional ecosystem factors and improving local ecological environments based on local conditions.

Study on Market-Based Trading Strategies for Biomass Power Generation Participation in Microgrid Systems

The Chinese government places significant importance on biomass energy due to its renewable and environmentally friendly attributes. However, the high cost of power generation poses a considerable hurdle to its development. This study aims to address the challenges facing the profitability and sustainable development of biomass power generation after the gradual withdrawal of the Chinese government by proposing a day-ahead real-time market-based trading strategy. It is prompted by the incentives offered by the Chinese government for the ongoing power market reform. This strategy is developed for a microgrid system that integrates biomass power generation with other renewable energy sources. The principles followed by the microgrid system include self-generation and consumption, electricity surplus sales, and electricity shortfall procurement. During the day-ahead stage, peak and valley tariffs are decided by the microgrid operator to exert influence on the incentives of capacity providers in accordance with the load trends, while in the intraday stage, the supply-demand imbalance is resolved by the stored electricity. In the trading process, marginal production and marginal pricing are specified to ensure the minimum trading volume and price for capacity traders, ensuring their profitability. It is demonstrated in this study that the trading strategy presented is more effective than conventional fixed-price trading in making biomass power generation profitable and sustainable, even after the Chinese government subsidy is phased out. Moreover, the other participant in the microgrid system can boost their earnings when compared to generating power individually for trading.

Analysis of the Water Resource Carrying Capacity in Guyuan City

To assess the water resource carrying capacity of Guyuan City, an analysis was conducted using the load index method, principal component analysis, and ecological water footprint method. A comprehensive analysis was carried out using these three methods to evaluate the current state of water resource carrying capacity in Guyuan City. The results indicate that the water resource carrying capacity in Guyuan City is mainly influenced by economic development factors, water supply–demand balance factors, and natural factors. During the period from 2002 to 2016, the water resource carrying capacity fluctuated in response to changes in the total water resources. However, from 2016 to 2021, it exhibited an increasing trend due to improvements in water resource utilization efficiency and effective water conservation measures. However, the water resource carrying capacity remains at a relatively low level, and it has consistently been in an overloaded state, with the development and utilization of water resources approaching their limits. Water scarcity in Guyuan City is a pressing concern, characterized by severe limitations on its potential for development and utilization. The persistent supply–demand imbalance is anticipated to impede the region’s pursuit of high-quality economic development in the foreseeable future.

Assessing Distributional and Perceived Equity of Urban Green Spaces in Qingdao’s Historic Urban Area

Urban green spaces (UGSs) satisfy citizens’ physical and psychological demands and are considered an integral part of sustainable urban development. However, the distribution of UGS is often uneven, especially in historic urban areas with high building density and limited facilities, thus leading to issues of green inequity. This study examines two dimensions of green equity in Qingdao’s historic urban area, distributional equity and perceived equity, based on a fine-grained division of units and districts. Distributional equity is analyzed using the Gaussian two-step floating catchment area (G2SFCA) method and Gini coefficient to accurately calculate the equity in distribution and accessibility of UGSs. The perceived equity is assessed through the green view index (GVI) and location quotient of the streets, which represents citizens’ visual perception of green quality. Based on these analyses, a dual-perspective evaluation model of green equity is conducted, and the results show a significant imbalance of greenery supply and population demand in the historical urban area of Qingdao. This disequilibrium in green spaces leads to 62.20% of people living with low green equity, while only 8.12% experience high green equity. To maximize social justice, priority should be given to improving the 15 districts with low green equity; doing so could effectively reduce green inequity within historic urban areas where facilities and resources are relatively scarce, thereby improving the efficiency of urban renewal efforts.

Fault Recovery Methods for a Converged System Comprised of Power Grids, Transportation Networks and Information Networks

Recently, triple-network convergence systems (TNCS) have emerged from the deep integration of the power grid, transportation networks, and information networks. Fault recovery research in the TNCS is important since this system’s complexity and interactivity can expand the fault’s scale and increase the fault’s impact. Currently, fault recovery focuses primarily on single power grids and cyber–physical systems, but there are certain shortcomings, such as ignoring uncertainties, including generator start-up failures and the occurrence of new faults during recovery, energy supply–demand imbalances leading to system security issues, and communication delays caused by network attacks. In this study, we propose a recovery method based on the improved twin-delayed deep deterministic algorithm (TD3), factoring in the shortcomings of the existing research. Specifically, we establish a TNCS model to analyze interaction mechanisms and design a state matrix to represent the uncertainty changes in the TNCS, a negative reward to reflect the impact of unit start-up failures, a special reward to reflect the impact of communication delay, and an improved actor network update mechanism. Experimental results show that our method obtains the optimal recovery decisions, maximizes restoration benefits in power grid failure scenarios, and demonstrates a strong resilience against communication delays caused by DoS attacks.

Organ donation decision-making in ICU patients: from the perspectives of organ coordinators and physicians in China – a qualitative study

ObjectivesIntensive care unit (ICU) dying patients are the most important source of organ donation. This study explores the reasons affecting organ donation in the Chinese sociocultural context from the perspectives...

Landscape management and planning as a spatial organization method connecting CES supply-demand assessment and sustainable tourism development

Evaluating the balance between the supply and demand of Cultural Ecosystem Service (CES) in space is the key to linking ecosystem services to human well-being. However, due to its invisibility, it is difficult to quantify and is often ignored in ecosystem service evaluation. Based on social media photos, by integrating multisource data and using a clustering algorithm and the MaxEnt model, this paper maps and evaluates the supply-demand balance of three CES of aesthetic, historical and cultural, and leisure services in Suzhou, China. The result shows a widespread imbalance between supply and demand in Suzhou, among which the cultural heritage CES imbalance area as high as 48.1% accounts for the largest proportion, and the aesthetic imbalance area accounts for 38.4%, while the recreation imbalance area accounts for 37%. Building upon the assessment of supply and demand balance at the urban scale, we further identified the supply-demand imbalance at the scenic area scale by integrating local tourism development policies in Suzhou and selecting a typical scenic area, Xishan Island. Based on the urban and scenic area supply-demand assessment results, this paper proposes a multiscale CES supply-demand allocation strategy. This comprehensive approach not only furnishes valuable guidance for local decision-making and management within the realm of sustainable tourism but also holds potential for wider applicability to diverse urban areas worldwide that share analogous contextual backgrounds. Management implicationsCES supply and demand assessment can help identify the CES supply-demand imbalance areas of tourist destinations. Landscape management and planning is a spatial organization method to balance CES supply-demand mismatches in tourist destinations. Optimizing landscape structure at multiple scales will be of instructional significance for the protection and development of tourist destinations. A ‘CES assessment and mapping – landscape management and planning – tourism protection and development’ system is beneficial to achieve the sustainable development of tourism.

Demand response strategy study of a radiant roof cooling system based on the thermal inertia of the building envelope

There is an imbalance between supply and demand in the power system. Implementing demand response control strategies for air-conditioning systems is beneficial to optimize the allocation of power resources. Here, we use two single strategies and a combination strategy for the radiant roof cooling system: passive energy storage, global temperature reset, and the passive energy storage-global temperature reset combination strategy to implement demand response control, all of which achieve peak load reduction or shifting by changing the indoor controlled parameters. Based on the thermal inertia of the building envelope, we utilize a TRNSYS model to analyze the performance of three demand response strategies of radiant roof cooling systems in terms of thermal comfort, energy consumption, operating costs, and peak load shifting rates. The findings reveal that implementing demand response strategies can reduce the operating energy consumption of radiant roof cooling systems and facilitate peak load shifting. Among them, the combined response strategy shows the best peak load transfer effect, with a transfer rate of 19.84% and a better operating economy. Meanwhile, we find that the outdoor temperature affects the implementation of demand response strategies for the radiant roof cooling system based on the thermal inertia of the building envelope. Practical application The study has significant application value in the following aspects: Implementing a demand response strategy for the radiant roof cooling system, based on the thermal inertia of the building envelope, can reduce operational energy consumption and achieve peak load shifting. This approach effectively addresses the issue of supply-demand imbalance in the power system. The application of the work could facilitate improved operational energy efficiency, contributing to emissions reduction goals and optimizing the use of intermittent renewable energy systems in power grids.

Optimal network-wide adjustments of initial airport slot allocations with connectivity and fairness objectives

Due to serious demand-supply imbalances, many airports around the world are highly congested. Access to these highly congested (Level 3, coordinated) airports is controlled through the use of the IATA World Airport Slot allocation Guidelines (WASG). At an individual airport, slots requested by each airline are allocated at the airport under consideration independently without taking into account the interactions between slots allocated at different airports. However, in order for the air-transport network to operate seamlessly, ensuring network-wide connectivity of flights, and the interdependencies existing between the slots allocated at individual airports need to be considered. Several models have been proposed in the literature to deal with the optimum allocation of slots at a single airport. However, the literature currently does not adequately address the network-wide slot allocation problem. In this paper, we are introducing a novel approach to address the network-wide slot allocation problem. Our approach considers as an input the individual airport schedules generated during the slot allocation process at individual airports and optimally adjusts them to ensure network-wide flight connectivity by taking into account the interdependencies existing between flights connecting pairs of airports.To this end, we propose bi-objective mathematical models, which consider schedule efficiency and inter-airline fairness objectives, and incorporate the importance that different airports have for the functioning of the air transport network, using the IATA connectivity indices and the betweenness centrality measures. We solve the proposed models using the ε − constraint method to investigate trade-offs between network-wide schedule efficiency and fairness, and we investigate the effect of these trade-offs on the airlines and the airports. Results from the application of the proposed models to a test network suggest that the consideration of the contribution of the airports to network connectivity affect the way that the total network-wide schedule displacement is distributed among the airports. Specifically, we found that the use of the IATA connectivity index tends to allocate less schedule displacement to airports with frequent flights to many destinations, while the use of the betweenness centrality measure allocates less schedule displacement to airports that are more critical in ensuring the connectivity of other airports in the network.

Síndrome coronario agudo. Código infarto en urgencias

Acute coronary syndrome (ACS) is a set of clinical entities caused by the partial or total obstruction of a coronary artery related, in most cases, to the rupture or erosion of a vulnerable atherosclerotic plaque that produces acute ischemia and, in the most severe cases, myocardial necrosis. ACS is a potentially fatal pathology that requires early diagnosis and treatment. For this reason, patients with compatible symptoms, fundamentally chest pain, must have an electrocardiogram within the first ten minutes of their arrival to the emergency department or healthcare service. The pillars of treatment include monitoring, antithrombotic treatment and treatment for reducing cardiovascular events, optimization of the supply-demand imbalance in the myocardium, and improvement in perfusion. The latter must be very early in patients with ACS with ST segment elevation, preferentially by means of a primary angioplasty or, if this cannot be performed in the first 120minutes after medical contact, with fibrinolytic agents. Prevention of ACS through a healthy lifestyle, the early identification and treatment of risk factors, and education on the symptoms of a possible ACS are important for reducing the disease burden and improving the results of treatment.

Development and performance evaluation of a self-sustaining electric generator with automatic control

Energy plays an important role globally. Industrial growth, coupled with high system losses, has resulted in a major demand-supply imbalance resulting in an energy shortage with a devastating effect on the economies of countries. The pollution brought by the combusting energy source and the price-increasing-motion of fuel tends people to explore and use greener and cheaper alternatives. Combining solar sources with Thermoelectric Generators (TEGs), and Piezo-Electric Generators (PEGs), and the concept of using a prime mover and secondary mover of the electric generator, in which, the idea of a self-sustaining electric generator with an automatic control system has come to exist. The self-sustaining electric generator with an automatic control system is compact based on the positioning of the components. The system is acceptable for households used. The noise level of the project passed the Class 1 noise level standard of the Philippines stated in NPCC Memorandum Circular No. 002, Series of 1980, vibration level is concluded to be better with enclosure, and the temperature rise is of normal temperature. The generated power yielded an above-average efficiency. The produced mathematical model validated the Seebeck effect theory, showing the proportional relationship between electrical power and temperature difference.

Assessing the Accessibility and Equity of Urban Green Spaces from Supply and Demand Perspectives: A Case Study of a Mountainous City in China

Urban green space accessibility is an essential consideration in determining environmental liveability and the well-being of individuals, and the spatial inequity of urban green space supply and demand has become a research focus. However, few studies have conducted a multidimensional and comprehensive assessment of the influences on accessibility from the different perspectives of supply and demand. To address this, our study centred on the mountainous Chongqing region and established a comprehensive research framework examining the spatial pattern of accessibility of urban green spaces and its correlation with physical geographical elements and socioeconomic factors. We reveal the spatial distribution characteristics of urban green space accessibility by using Gaussian-based two-step floating catchment area and network analysis methods and further observe the spatial clustering features utilising hotspot analysis. The ordinary least squares (OLS) model and the spatial lag model were used to evaluate the physical geographical and socioeconomic disparities. Our findings reveal explicit blind spots in urban green space accessibility, primarily within the 30 min travel threshold in the city’s marginal area. A discernible supply–demand imbalance existed in the urban core, constituted by implicit blind spots. Furthermore, we identified that the relationship between urban green space accessibility and elevation under different methods is not always consistently significant over space because spatial heterogeneity may exist. Most concerningly, the study found inequities in urban green space accessibility, particularly impacting vulnerable demographics such as the elderly and lower-income groups. These results can inform urban planners and policymakers about the blind spots of urban green space accessibility and sufficiently consider the physical and socioeconomic heterogeneity of the space to determine where and how to implement inclusive urban greening policies or planning schemes. It is also of great significance in increasing awareness of vulnerable groups and preventing environmental inequality.

Ride-sourcing market equilibrium analysis and optimization under immediate matching strategies

Supply/demand characteristics and price strategies in the ride-sourcing market are affected by matching strategies. In particular, immediate matching strategies are widely adopted to tackle supply–demand imbalance issues. This paper studies a two-sided ride-sourcing market under two immediate matching strategies: driver-first-come-first-serve and passenger-first-come-first-serve. In the former, the system is considered over-saturated with passengers, such that any driver is matched immediately upon posting their availability. Therefore, the market would be devoid of waiting drivers. In comparison, the latter strategy is oversaturated with drivers, such that any newly arriving passenger is immediately matched, and there are no waiting passengers in the system. We first derive generalized supply and demand functions and prove that the immediate matching strategies are optimal to maximize the number of completed trips under certain conditions based on equilibrium analysis. Then, we characterize the market equilibrium and discuss the properties of the wild-goose-chase phenomenon under two immediate matching strategies. We optimize the ride-sourcing platform's strategies to achieve a joint profit of platform and driver maximization (monopoly optimum), social welfare maximization (social optimum), and second-best optimum (entailing a reservation profit for the platform). Numerical experiments are conducted to demonstrate the effects of user heterogeneity, and the properties of pricing strategies under both matching strategies on the monopolistic and social optimal solution. The gained managerial insights provide suggestions for decision-makers to coordinate supply and demand in the ride-sourcing market.