Flexible Resource Research Articles

Novel R package to quantify and monetize burden of disease attributable to air pollution and noise

Abstract Background Ambient air pollution and noise substantially impact public health and the economy. Different methods to quantify these impacts are described in the literature. Objectives Within the European project BEST-COST (Burden of disease-based methods for estimating the socio-economic cost of environmental stressors), we aim to develop an open-source R package to quantify and monetise the disease burden attributable to air pollution and noise, including the impact of social inequalities. Methods The developed code will allow for different calculation pathways including: single baseline health data vs. age-specific estimates from life tables; relative and absolute risk; scenario comparison based on the population attributable fraction vs. population impact fraction; single-pollutant vs. correlated exposures; and outdoor vs. indoor air pollution. Moreover, the package can digest a variety of input data formats for the exposure-response function (e.g. relative risk with fixed shape vs. user-defined function) and exposure data (e.g. population-weighted mean vs. categorical distribution, spatial data). Eligible impact metrics will include morbidity incidence and prevalence, number of deaths, years of life lost, and years lived with disability. Finally, the R package will enable quantifying social inequities (using a novel multiple deprivation index) and monetising the attributable disease burden (using a state-of-the-art approach). Results During development, the R package will be tested in BEST-COST case studies in 5 European countries (BE, EE, FR, NO, PT), compared with existing tools, and discussed with key users in a workshop. The final R package will be available on GitHub in 2026. Conclusions This tool will allow the quantification and monetisation of the health impact of air pollution and noise. The R package will be a flexible programming resource that can be used as a standalone or combined with existing tools to build a more solid basis for evidence-based policy making. Key messages • This open-source tool will allow the quantification and monetisation of the health impact of air pollution and noise, including the impact of social inequalities. • The R package will be a flexible programming resource that can be used as a standalone or combined with existing tools to build a more solid basis for evidence-based policy making.

The Moderating Role of Supply Chain Agility on the Relationship Between Strategic Flexibility and Organizational Market Performance in Nigerian Pharmaceutical Industry

The pharmaceutical industry is key to the survival of the human race, but equally becoming increasingly susceptible to global disruptions. In Nigeria, records have shown that the industry is plagued with several problems, inclusive of low employee productivity, poor market share, low innovation performance, poor and marginal sales growth and low profitability, which are likely a result of a lack of strategic flexibility in the face of increasing environment turbulence and intense competition. Despite efforts from researchers, the moderating role of supply chain agility has been largely overlooked in the literature. Therefore, this study examines the moderating role of supply chain agility on the relationship between strategic flexibility (resource flexibility, coordination flexibility, proactive flexibility, reactive flexibility and futurity) and organisational performance. A survey research design was used to collect data from 642 management and senior staff employees of six pharmaceutical companies listed on the Nigerian Exchange Group. A total enumeration method was adopted for the study, with a well-structured adapted questionnaire, having Cronbach’s alpha reliability coefficients ranging from 0.725 to 0.945. Partial Least Squares Structural Equation Modeling (PLS-SEM) was chosen to achieve the research goal. The PLS-SEM analysis revealed that strategic flexibility positively affects organizational performance (β = -0.093, p> 0.050, Q2 = 0.644). However, supply chain agility negatively moderates this effect, indicating that while agility is beneficial independently, it can counteract the positive impact of strategic flexibility when combined. The study recommended that the management of pharmaceutical companies in Nigeria should pay serious attention to strategic flexibility as an organizational capability that can enhance performance in the face of increasing uncertainties in and unpredictability nature of the business environment.

Bi-Directional Charging with V2L Integration for Optimal Energy Management in Electric Vehicles

Electric vehicles (EVs) are becoming increasingly popular as an efficient transportation solution but they also present unique challenges for energy management. Bi-directional charging (BDC) is a solution that allows EVs to not only consume energy from the grid but also supply energy back to the grid. This facilitates vehicle-to-load (V2L) integration, where EVs can act as mobile power sources for homes, buildings, and the grid. V2L enables better energy management by utilizing EVs as a flexible resource to balance grid demand and supply in the proposed system. This is achieved through intelligent coordination between the EVs, charging stations, and the grid, using smart meters and communication networks. Integration of BDC and V2L also enables EVs to provide backup power during grid outages, reduce the need for costly grid infrastructure, and support renewable energy integration. BDC with V2L integration is a promising approach for optimal energy management in EVs and can play a significant role in the future of sustainable transportation and energy systems. The proposed model reached 95.13% charging efficiency, 95.03% energy management, 95.69% power rating, 96.28% voltage support and 87.99% temperature management.

Container migration for edge computing in industrial Internet with joint latency reduction and reliability enhancement

Edge computing has emerged as a prominent trend in the field of information technology, offering flexible and robust resources for the industrial Internet. How to migrate container accurately is crucial for edge computing in the industrial Internet, as it plays a vital role in enhancing service response speed and safeguarding uninterrupted continuity of production operations. In this paper, we explore the problem of container migration in edge computing within the industrial Internet, aiming to reduce latency and enhance reliability. We establish a two-objective optimization model to comprehensively capture the container migration problem and formulate it as a constrained optimization model. The formulated model provides a systematic framework that effectively balances the trade-off between reducing latency and enhancing reliability. To tackle the migration strategy derived from the optimization model, we propose a migration algorithm based on the improved binary whale optimization algorithm. Our migration algorithm incorporates the adaptive probability and adaptive position weight within the hunting and searching operations, effectively enhancing the search efficiency during the solving process. The experimental results demonstrate the effectiveness of the established model in reducing the objective value, while the proposed migration algorithm surpasses existing algorithms by achieving an average reduction of at least 15.59% in the objective value.

Integrated market scheduling with flexibility options

This work presents a generic optimization framework using advanced mixed-integer programming techniques to integrate day-ahead and balancing markets with distributed energy resources such as storage, electric vehicles, demand response, and Transmission and Distribution System Operators' coordination schemes. The day-ahead model determines optimal initial energy scheduling, while the balancing model optimizes energy and reserve products for three market designs with varying Transmission and Distribution System Operators’ coordination. The framework is applied to the interconnected Greek-Bulgarian-Romanian power system, considering 2030 installed capacities.The model outputs illustrate market coupling scenarios among Romania, Bulgaria, and Greece, highlighting clear price signals and distributed energy resources flexibility. Results reveal the significance of a diverse energy mix for energy security and show that Transmission and Distribution System Operators’ coordination significantly influences ancillary service prices, with reductions of up to 80 % in certain scenarios. Net demand values determine electricity flow direction. Flexibility providers like storage can cover up to 100 % of the upward congestion management requirements and 11 % of upward balancing energy, helping smooth energy allocation from intermittent renewables. The impact of electric vehicle penetration on generation scheduling is minimal. The proposed model offers valuable insights for system operators, market participants, and policymakers, enabling them to provide accurate price signals and optimize resource allocation.The integrated day-ahead and balancing market models support efficient renewable energy integration, emissions reduction, enhanced grid stability, and investment in low-carbon technologies. This aligns with the United Nations Framework Convention on Climate Change goals, contributing to the development of sustainable and resilient energy systems.

The Use of the CDC Preventive Health and Health Services Block Grant to Address Social Determinants of Health to Advance Health Equity.

State public health departments use federal funding to examine and address social determinants of health (SDOH) within their communities to improve health and advance health equity. Yet, most federal funding is categorical (ie, funding used for a specific program or narrow purpose), which can create barriers to addressing social and structural drivers of inequity. The Preventive Health and Health Services Block Grant (PHHS Block Grant) is a flexible funding mechanism that provides health departments the latitude to identify and fund initiatives that address local public health needs. It is unclear, however, to what extent health departments use this flexible resource to incorporate SDOH into their programs. Cross-sectional, descriptive analysis of state health department PHHS Block Grant program administrative data. This study examined PHHS Block Grant budgets and workplans for the federal Fiscal Year 2021 to assess whether state health departments aligned their grant-funded program with the national objectives associated with the Healthy People 2030 SDOH Framework. Forty-seven states and the District of Columbia were included in this study. Percent of states that used PHHS Block Grant funds to address SDOH; proportion of funding allocated to address SDOH; percentage of programs that addressed SDOH. Three-fourths (75%) of states allocated funds to 97 programs aligning with at least 1 Healthy People 2030 SDOH-related objective. Fifty of the programs were fully or primarily funded by the PHHS Block Grant. Results also show that as the states' PHHS Block Grant funding level increased so did the percent of states that allocated funding toward SDOH programs. This study shows that state health departments are using the PHHS Block Grant to address SDOH, and that the grant plays an important funding role for these programs. States are incorporating the grant into their funding strategies to address SDOH.

Power allocation optimization strategy for multiple virtual power plants with diversified distributed flexibility resources

AbstractThe virtual power plant integrating the flexible resources in the distribution network can provide additional adjustment capacity for the auxiliary services of distribution network. However, the actual internal situation of distribution network including insufficient adjustable capacity of energy storage, unreasonable power allocation, and voltage overrun leads to the difficulties in optimization scheduling. Therefore, this paper proposes a power allocation optimization strategy of distributed electricity‐H2 virtual power plants (EHVPPs) with aggregated flexible resources. Specifically, a distributed EHVPP division method based on the granular K‐medoids clustering algorithm is proposed to realize the independent autonomy and coordinated interaction between EHVPPs, and in order to quantify the operation and regulation capacity of distributed EHVPPs, an aggregation approach of regulating feasible domains of flexibility resources based on the improved zonotope approximations is developed. Moreover, a power allocation strategy based on the flexibility weight factor is proposed to handle the calculated minimum deviation between the total active output of PV and the dispatching power command, realizing the self‐consistency of distributed EHVPPs. Comparative studies have demonstrated the superior performance of the proposed methodology in economic merits and self‐consistency efficiency.

Medium- and Long-Term Power System Planning Method Based on Source-Load Uncertainty Modeling

In order to consider the impact of source-load uncertainty on traditional power system planning methods, a medium- and long-term optimization planning method based on source-load uncertainty modeling and time-series production simulation is proposed. First, a new energy output probability model is developed using non-parametric kernel density estimation, and the spatial correlation of the new energy output is described using pair-copula theory to model the uncertainty analysis of the new energy output. Secondly, a large number of source-load scenarios are generated using the Markov chain Monte Carlo simulation method, and the optimal selection method for discrete state numbers is provided, and then the scenario reduction is carried out using the fast forward elimination technology. Finally, the typical time-series curves of the source-load uncertainty characteristics obtained are incorporated into the optimization planning method together with various flexible resources, such as the demand-side response and energy storage, and the rationality of the planning scheme is judged and optimized based on key indicators such as the cost, wind–light abandonment rate, and loss-of-load rate. Based on the above methods, this paper offers an example of the power supply planning scheme for a certain region in the next 30 years, providing effective guidance for the development of new energy in the region.

Complementary Analysis and Performance Improvement of a Hydro-Wind Hybrid Power System

Hydropower as a flexible regulation resource is a rare choice to suppress the ever-increasing penetration of wind power in electrical power systems. The complementary characteristics and performance improvement of a hydro–wind hybrid power system based on a mathematical model of the hybrid power system is studied in this paper. This established model takes into account the stochastic variation in wind speeds in the wind power subsystem and the hydraulic–mechanical–electrical coupling characteristics of the hydropower subsystem. The complementary analysis is conducted based on the evaluation variables outputted by the established model, such as the wind power, hydro-regulation power, hydraulic power, and frequency. To make full use of the regulation capability of the hydropower system, the optimization of parameter settings is also carried out to improve complementary performances of the hybrid power system. The results from the complementary analysis show the detailed characteristics of hydro–wind coordinated operation under different types of real wind speeds. Here, 95% of installed hydro-capacity is used to complement the power shortage of the intermittent wind energy under the low wind speed. Alternatively, only around 66% of the installed hydro-capacity can be utilized to cope with the fluctuation in wind power under the medium and high wind speeds before the optimization of parameter settings. The recommended values and change rules of the control, hydraulic, and electrical parameters for the hydropower system are subsequently revealed from the analysis of parameter settings to contribute to a stable and safe hybrid power system. The results show that the optimized parameter can increase the maximal regulating capacity of the hydropower system by nearly 9 MW, approximately a sixth of the total installed hydropower capacity. The method and results obtained in this paper provide theoretical and technical guidance for the safe and economical operation of power stations.

Optimal Scheduling of Integrated Energy System Considering Virtual Heat Storage and Electric Vehicles

Integrated energy systems (IESs) are complex multisource supply systems with integrated source, grid, load, and storage systems, which can provide various flexible resources. Nowadays, there exists the phenomenon of a current power system lacking flexibility. Thus, more research focuses on enhancing the flexibility of power systems by considering the participation of IESs in distribution network optimization scheduling. Therefore, the optimal scheduling of IESs considering virtual heat storage and electric vehicles (EVs) is proposed in this paper. Firstly, the basic structure of IESs and mathematical models for the operation of the relevant equipment are presented. Then, an optimal scheduling strategy of an IES considering virtual heat storage and electric vehicles is proposed. Finally, an IES with an IEEE 33-node distribution network, 20-node Belgian natural gas network, and 44-node heating network topologies is selected to validate the proposed strategy. The proposed models of integrated demand response (IDR), EV orderly charging participation, virtual heat storage, and actual multitype energy storage devices play the role of peak shaving and valley filling, which also helps to reduce the scheduling cost from CNY 11,253.0 to CNY 11,184.4. The simulation results also demonstrate that the proposed model can effectively improve the operational economy of IESs, and the scheduling strategy can promote the consumption of renewable energy, with the wind curtailment rate decreasing from 63.62% to 12.50% and the solar curtailment rate decreasing from 56.92% to 21.34%.

Coordinating and valuing the flexibility resources in a rural integrated energy system by considering correlated source-load uncertainty

This paper proposes a two-stage model for flexible resource coordination and value analysis in rural areas, which considers the specific biomass energy conversion supply and the correlated uncertainties on both sides of the integrated energy system. Firstly, it describes the impacts of correlated uncertainty on the actual output of the source and load based on factor analysis and affine variables, and constructs an affine optimization model for cooperative scheduling of system-wide flexible resources. Secondly, according to the energy supply envelope area of flexible resources within the scheduling cycle, it proposes the value measurement indices of system flexibility adjustment ability and economic benefit to evaluate the sensitivity of flexible resources. Finally, the simulation results show that the proposed method can effectively reduce the conservatism of the scheduling scheme, and analyzing the influence of capacities and time-of-use tariff on flexibility value provides a reference for the construction of integrated energy systems in rural areas.

Whose Egg, Whose Sperm, Whose Household Registration? Reproductive Decisionmaking Among LGBT Parents in China

This article examines how LGBT individuals and couples in China make reproductive decisions in a sociopolitical context characterized by homophobia and an absence of LGBT familial rights and legal recognition. The existing literature on LGBTQ+ childbearing and family formation, based primarily in Euro-American countries, tends to focus on the central role of same-sex marriage legalization and features marriage as the core intimate bond that bestows parental and other familial rights. This article argues that China’s household registration (hukou) system is an equally, if not more, salient regulatory system that determines daily life opportunities, access to state-subsidized schooling and health care, life-long social welfare, and placement in a hierarchy of urban versus rural citizenship. LGBT intending parents in China make reproductive decisions with a child’s hukou in mind, treating genetic contributions, gestational labor, and legal parental status as flexible resources to achieve desired hukou outcomes. The hukou system encourages reproductive strategies that make and unmake LGBT kinship, securing family bonds that otherwise lack legal and social recognition while potentially risking parental precarity. The article suggests new directions for LGBT rights advocacy by focusing on the governing systems and statuses that determine access to key citizenship resources and family rights.

Potential assessment of coordinated regulation of power load of emerging industrial users based on extreme scenarios of electric vehicle aggregators

AbstractWith the advancement of industrial low carbonization and electrification, emerging industrial production technologies have the characteristics of high‐power consumption and significant impact load. In the context of increasing global climate change, frequent extreme weather events have brought serious challenges to the balance of power and electricity in the power system, and have a significant impact on the production scheduling of industrial users, especially industrial users using electrified production technology. First, based on the representative high‐power industrial users of hydrogen reduction steel plants and internet datacentres (IDC), this paper establishes a flexible resource scheduling optimization model for single industrial users, and considers the collaborative relationship between multi‐user flexible resources to establish a collaborative scheduling optimization model for industrial users. Then, considering the charging and discharging characteristics of electric vehicles (EV) in extreme scenarios, the redundant capacity of EVs is aggregated by EV aggregators and sold to industrial users, and a collaborative scheduling optimization model of EV aggregators and industrial users is established. Finally, the effectiveness of the proposed model and algorithm is verified by simulation analysis. Compared with the traditional industrial user production optimization, the proposed model can tap the potential of multi‐agent scheduling operation in extreme scenarios.

Maintaining reliability in a 100% decarbonized power sector: The interrelated role of flexible resources

Reliability will remain a key requirement for decarbonized power sectors, but also a concern with the high penetration of variable renewable energy (VRE). The traditional approach for reliability is by producing enough energy and adapting rapidly to changes in load with the dispatch of fossil fuel power plants, especially natural gas power plants. However, this will have to evolve as decarbonization progresses. Can various flexibility resources such as transmission, storage and demand response provide the same reliability benefits? This paper uses a detailed, capacity expansion and hourly operation model to investigate the possibility and the cost of reaching different levels of planning reserve margins (PRM), in the multi-regional context of the North American Northeast. We find that while it is possible to entirely avoid natural gas power plants or nuclear ones to obtain high PRM, it would come at a very high cost and would require high levels of transmission, storage and demand response. We also detail why these three flexibility resources are needed in combination. The implications for energy policies are significant: in order for power system's cost to remain reasonable, reliability must count on some carbon-neutral natural gas or nuclear generation, along with interties with neighboring systems, storage and high levels of demand response.

Integrated resource strategic planning considering inter-regional flexibility supply–demand balance: A case study for the Northwest and Central Grid in China

China’s rapid advancement in renewable energy and regional power grid interconnection has highlighted the need for enhanced system flexibility to ensure the security and stability of regional power systems. To address this issue, this study presents a new framework for integrated resource strategic planning for inter-regional flexibility (IRSP-IF). This framework evaluates inter-regional flexibility demand and optimizes power resource allocation across regions. The northwest and central grids in China are used as case studies to evaluate inter-regional power resource allocation from 2022 to 2035. This analysis considers key factors including flexibility supply–demand balance constraints, regional power grid interconnections, and time scales for assessing flexibility demand. The results show that incorporating these constraints and interconnections into the strategic power plan enables greater integration of renewable energy while reducing both installed capacity and the overall cost of regional power resources. In the S3 scenario, which includes inter-regional flexibility supply–demand balance, the total integration of wind and solar power increases by 1.54%. Additionally, the combined average annual fixed and operating costs decrease by 1.44 billion yuan compared to the S2 scenario, which only considers single-region flexibility supply–demand balance. Furthermore, evaluating flexibility demand at a shorter time scale results in a higher proportion of flexible resources, with an average annual growth of 24.43%.

Scheduling and assessment of multi-area virtual power plant including flexible resources using swarm intelligence technique

A virtual power plant (VPP) makes the distributed energy resources (DERs) visible to support grid services, promoting clean energy use by offering an alternative to reduce reliance on conventional sources. This paper proposes optimized operation and scheduling of VPP by forming a group of flexible resources that includes renewables i.e., solar, wind power, fuel cell, and co-generation units along with storage facilities to form a holistic network in a multi-area interconnected system framework. Initially, the scheduling is performed for a single area system in which a comparison is made with the available work relevant to the proposed formulation. In addition, the scheduling is further extended to the proposed multi-area based virtual power plant (MAVPP) performed on a day-ahead (DA) basis and the target objective(s) i.e., net profit and emission are optimized. Furthermore, a recently developed marine predator optimization algorithm (MPOA) is employed to solve the proposed problem formulation and the results are compared and discussed extensively with conventional techniques. Also, the analysis pertaining to MAVPP is carried out which is beneficial in terms of economic and environmental perspective. The result reveals that the maximum value of net profit for MAVPP is converging to an optimum value of 59,351.88 $ followed by the attained value of minimum emission of 51,700.73 Kg by consuming an elapsed time of 92.96 and 104.76 s., respectively in 200 iterations. The outcomes are promising and upon comparison with the available literature work, the superiority of the selected technique is evident in terms of computational time, improvement of net profit and reduction in emission followed by the ease of convergence behaviour in fewer iterations.

Stochastic optimal allocation of grid-side independent energy storage considering energy storage participating in multi-market trading operation

The integration of large-scale intermittent renewable energy generation into the power grid imposes challenges to the secure and economic operation of the system, and energy storage (ES) can effectively mitigate this problem as a flexible resource. However, the conventional ES allocation is mostly planned to meet the regulation demands of individual entities, which is likely to result in low utilization of ES and difficult to recover the investment cost. Therefore, a two-stage stochastic optimal allocation model for grid-side independent ES (IES) considering ES participating in the operation of multi-market trading, such as peak-valley arbitrage, frequency regulation, and leasing, is proposed in this paper to improve the comprehensive benefits and utilization rate of ES. The first stage aims to allocate IES and develop a systematic scheduling plan based on the forecast of wind power output and load demand, while the second stage responds to the uncertainty of wind power output by re-dispatching generating units and invoking ES power leased by wind farms. Then, a two-layer loop iterative solution algorithm based on the Benders decomposition is formed to effectively solve the proposed model. Finally, the approach developed in this paper is applied to a modified IEEE RTS-79 test system, and the results verify that it is both feasible and effective.

Research on the collaborative operation strategy of shared energy storage and virtual power plant based on double layer optimization

Large-scale access to distributed energy resources leads to new energy consumption problems and safe operation risks in the power system. Virtual power plants and shared energy storage are effective ways to promote the flexible consumption of distributed energy resources and improve the reliability and economy of power system operation. Based on the concept of sharing economy and considering the complementary characteristics of source and load resources between different virtual power plants, this paper focuses on the optimisation of shared energy storage and multi-virtual power plant operation. Firstly, distributed wind power, distributed photovoltaic and flexible load resources are aggregated into virtual power plants to analyze the cooperative operation mode of shared energy storage and multi-virtual power plant systems. Secondly, a two-layer decision model for shared energy storage configuration and multi-VPP system operation optimisation is constructed, with the upper model solving the optimal energy storage configuration scheme by maximising the revenue of the shared energy storage operator, and the lower model optimising the multi-VPP system operation strategy by minimising the total operation cost, the maximum amount of new energy consumed, and the minimum amount of carbon emission as the multi-objective optimisation strategy. Finally, a simulation analysis is carried out, and the results show that compared with the independent operation mode of each virtual power plant, the model proposed in this paper increases the annual profit of the shared energy storage operator by 7180¥, reduces the operating cost of the VPP system by 7.08 %, improves the rate of renewable energy consumption by 0.82 %, and reduces the annual carbon emission by 54.91 t, which realizes the mutual benefits of the virtual power plant and the shared energy storage.

Designing for Resilience: Principles for Building Organizational Adaptability

Organizational disruptions from events like the COVID-19 pandemic have demonstrated the importance of resilience - an organization's ability to anticipate risks, maintain core functions during crises, and adapt successfully. This article outlines eight design principles that research indicates can help build resilience into an organization's structures, systems, culture and operations. Drawing from literature in fields like organizational development, crisis leadership and strategic management, the principles focus on distributing leadership and information sharing; promoting flexible, modular designs; ensuring redundancy of critical resources; cultivating a learning culture; maintaining flexible funding and resources; conducting scenario planning and training; fostering strategic partnerships; and taking an adaptive approach to goals. The principles are grounded in academic research but presented through the lens of a practitioner's consulting experience. The article also discusses practical strategies for applying the resilience design framework to assess risks, strengthen crisis response capabilities, and nurture continuous organizational learning and adaptation.

Integrated real-time dispatch of power and gas systems

The integrated operation of the electricity and gas systems has attracted the attention of many researchers due to the ever-increasing interdependency between the two systems. In this paper, a novel framework for the real-time rolling dispatch of the integrated system is presented, targeting to attain the economically optimal and technically secure gas system real-time operation through the control of the available flexibility procured by various resources. A decoupled day-ahead scheduling is initially executed to determine unit commitment and gas linepack target decisions, which are then utilized as inputs to the proposed integrated real-time dispatch model. Intra-day gas system control is executed in a hierarchical procedure through the deployment of four control actions from various inter-system flexibility providers. The presented analysis illustrates that, based on the selection of control parameters, the activation of flexibility resources from both systems can be steered in such a way as to alleviate linepack deviations, even in cases of severely limited scheduled gas supply. The proposed control framework is tested on the Greek power and gas systems, providing significant insights regarding the activation of the control actions for the real-time gas system balancing in different look-ahead horizons.