Power Balance Research Articles

NATO’s Artificial Intelligence Strategy and Interoperability Challenges: The Case of Turkey

ABSTRACT The rapid advancement of artificial intelligence (AI) has significantly changed military applications, creating new competitive advantages and shifting the global balance of power. This article examines NATO’s AI strategy and the associated interoperability challenges, with a particular focus on Turkey. NATO’s AI strategy seeks to enhance interoperability among its member states by fostering the integration of AI technologies into military capabilities. However, achieving this goal is complicated by the varying levels of AI technological advancement, divergent national AI-military strategies and differing geopolitical considerations among member countries. Using Turkey as a case study, this paper explores how the rapid development of AI-based military drones contributes to Turkey’s strategic autonomy and enhances regime resilience while also highlighting certain interoperability considerations within NATO. The analysis underlines the need for a cohesive approach to AI integration that addresses these disparities to maintain NATO’s collective defence capabilities.

The Balance of Power

The Balance of Power

Operational reliability and non-deterministic resilience estimation of active distribution network incorporating effect of real-time dynamic hosting capacity

Active distribution networks are increasingly recognized essential for achieving sustainable development goals. Traditionally, hosting capacity was considered as a static measure for planning distributed energy resources integration. This work introduces the concept of dynamic hosting capacity, which recurrently re-evaluates hosting capacity in response to erratic modern grid conditions. The introduction of dynamic hosting capacity facilitated testing variations of power injection from minimum to 100 %, sustaining power system governing parameter limits. This embarked the need of operational reliability assessment and enhancing situational awareness for optimum power injection and balance. To achieve operational reliability analysis based on dynamic hosting capacity, hybrid probability distribution function-based Monte Carlo simulation is proposed. This resulted in 85–90 %. improvisation of solar photovoltaic generation and load alignment, as this methodology provides comprehensive and accurate assessment of system performance under diverse uncertainties. The framework's validation includes projection of time-varying operational reliability indices, over time independent reliability indices i.e., dynamic loss of load probability, dynamic loss of load expectation, dynamic loss of load duration, dynamic loss of load frequency, dynamic grid margin, and dynamic grid dependency. This resulted in 30 % improvement in assessment of grid margin, facilitating reliable uncertainty handling competence. Additionally, expectation maximization algorithm is proposed to evaluate non-deterministic resilience due to ambiguities associated with solar photovoltaic distributed energy resources. The non-deterministic resilience assessment testified 80 % bounce-back rate, demonstrating better adaptability and robustness. The entire analysis is conducted in MATLAB, validated using Typhoon Hardware-in-Loop real-time platform, and compared with existing literatures to demonstrate its effectiveness.

Computing the Network’s Equilibrium Point at the Fault Clearing Instant in Transient Stability Studies

This paper proposes an approach for computing the network’s equilibrium point related to the fault clearing time in transient stability studies. The computation of this point is not a trivial task, particularly when the algebraic network’s equations are expressed in the power balance form. A natural attempt to solve this problem is using Newton’s method. However, convergence issues are found because of the lack of a general strategy for initializing nodal voltages at the clearing time. This problem has not been widely discussed in the existing literature and, therefore, is comprehensively analyzed in this paper. Furthermore, the paper proposes the use of a network’s model based on current injections and an extended admittance matrix to overcome the problem. This model is efficiently solved via the fixed-point iteration method, which involves factorization of the extended admittance matrix into the product of a lower triangular matrix [L] and an upper triangular matrix [U]. This solution executes a just once and only forward–backward substitution during the iterative solution process. Case studies clearly demonstrate the proposal’s effectiveness in computing the equilibrium point in operating conditions where Newton’s method fails to converge.

Ultra-Short-Term Wind Farm Power Prediction Considering Correlation of Wind Power Fluctuation

Accurate ultra-short-term power prediction for wind farms is challenging under rapid wind speed fluctuations, complicating production planning and power balancing. This paper proposes a new method considering spatial and temporal correlations of wind fluctuations among adjacent wind farms. The method first calculates the time difference between power fluctuations based on wind speed, direction, and relative positions, determining the prior information period. The variational Bayesian model is then used to extract implicit relationships between power fluctuations of adjacent wind farms, enabling power prediction during the prior information period. Finally, the non-prior information period is predicted to complete the ultra-short-term power prediction. Using measured data from three wind farms in Fujian Province, compared to other models, the method demonstrates improved accuracy by effectively leveraging the power fluctuation characteristics of adjacent wind farms, and it has a certain amount of generalizability.

ENERGY MANAGEMENT IN HYBRID PV-WIND-BATTERY STORAGE-BASED MICROGRID USING DROOP CONTROL TECHNIQUE

The paper presents an efficient energy management system designed for a small-scale hybrid microgrid incorporating wind, solar, and battery-based energy generation systems using the droop control technique. The heart of the proposed system is the energy management system, which is responsible for maintaining power balance within the microgrid. The EMS continuously monitors variations in renewable energy generation and load demand and adjusts the operation of the energy conversion systems and battery storage to ensure optimal performance and reliability. The primary objective of the energy management system is to maintain power balance within the microgrid, even in the face of fluctuations in renewable energy generation and load demand. This involves dynamically adjusting the operation of the renewable energy sources and battery storage system to match the instantaneous power requirements of the microgrid. Overall, the paper presents a comprehensive approach to designing and implementing an efficient energy management system for a small-scale hybrid wind-solar-battery-based microgrid to extract maximum profit from electricity generation. By integrating renewable energy sources with energy storage and advanced control algorithms, the proposed system aims to enhance the reliability, stability, and sustainability of the microgrid's power supply.

Distributed Secondary Control of DC Microgrid with Power Management Based on Time-of-Use Pricing and Internal Price Rate

This paper presents a novel approach to manage distributed DC microgrids (DCMG) by integrating a time-of-use (ToU) electricity pricing scheme and an internal price rate calculation mechanism. The proposed power-management system is designed to effectively handle uncertainties such as utility grid (UG) availability, fluctuating electricity prices, battery state of charge (SOC) levels, and frequent plug-ins and plug-outs of electric vehicles (EVs). Uncertainties in DCMG systems often lead to inefficiencies, power imbalances, and inexact voltage regulation issues within DCMGs. In addition, to maintain the power balance and constant voltage regulation under various operational states, the proposed scheme also incorporates secondary control into the DCMG power-management system. Unlike the existing approaches that often fail to adapt dynamically to changing conditions, the proposed method is the first approach to consider the concept of internal price rate in designing the DCMG power management. To address this challenge, this approach proposes a more resilient power-management strategy to enhance the efficiency and adaptability of DCMG systems. Extensive simulations and experimental validations demonstrate the practicality and adaptability of the proposed control strategy under diverse test conditions, including operation transitions between grid-connected mode (GCM) and islanded mode (IM), low battery SOC condition, operation transition from the current control mode (CCM) to distributed secondary control mode (DSCM), and EV plug-in scenarios. The test results confirm that the proposed method enhances the reliability, efficiency, and economic viability of DCMG systems, making it a promising solution for future smart grid and renewable energy integrations.

Quality Improvement Decisions in Service Supply Chains with Collaborative and Free-Riding Behaviors

The dominant position of a member within a service supply chain plays a crucial role in fostering a willingness to improve service quality. Consequently, this study examines a service supply chain comprising a supplier and an integrator, aiming to investigate the influence of four different power structures, namely, supplier-led, integrator-led, supplier–integrator power balance, and supplier–integrator centralized decision, on the decision-making process for service quality improvement by members. The findings highlight that the optimal willingness to improve service quality in a service supply chain is not necessarily infinitely close to 100%, and is influenced by factors such as revenue share, cost, effect, and dominant position. In cases where the collaborative improvement effect is weak, even the dominant member may display a limited willingness, rendering centralized decision-making meaningless. If the collaborative improvement effect surpasses the combined independent improvement effects, the dominant position can help strengthen willingness, although it may not always result in higher profits. Conversely, a power-balanced scenario can be advantageous in achieving the highest profit for the entire supply chain.

Active power balance control of wind-photovoltaic-storage power system based on transfer learning double deep Q-network approach

IntroductionThis study addresses the challenge of active power (AP) balance control in wind-photovoltaic-storage (WPS) power systems, particularly in regions with a high proportion of renewable energy (RE) units. The goal is to effectively manage the AP balance to reduce the output of thermal power generators, thereby improving the overall efficiency and sustainability of WPS systems.MethodsTo achieve this objective, we propose the transfer learning double deep Q-network (TLDDQN) method for controlling the energy storage device within WPS power systems. The TLDDQN method leverages the benefits of transfer learning to quickly adapt to new environments, thereby enhancing the training speed of the double deep Q-network (DDQN) algorithm. Additionally, we introduce an adaptive entropy mechanism integrated with the DDQN algorithm, which is further improved to enhance the training capability of agents.ResultsThe proposed TLDDQN algorithm was applied to a regional WPS power system for experimental simulation of AP balance control. The results indicate that the TLDDQN algorithm trains agents more rapidly compared to the standard DDQN algorithm. Furthermore, the AP balance control method based on TLDDQN can more accurately manage the storage device, thereby reducing the output of thermal power generators more effectively than the particle swarm optimization-based method.DiscussionOverall, the TLDDQN algorithm proposed in this study can provide some insights and theoretical references for research in related fields, especially those requiring decision making.

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.

Characteristics of disruptions observed in the initial operation phase of JT-60SA

Abstract Disruption database in the JT-60SA first plasma operation period has been constructed. The disruptions have been divided into three categories based on their characteristics, and the characteristics of each category have been discussed. The most commonly observed disruptions were vertical displacement events (VDEs). As expected by simulations using the MHD equilibrium control simulator (MECS), a highly elongated plasma was likely to disrupt by VDE when the gap between the plasma surface and the wall is large. Despite the quite high edge safety factor q 95 of above 10 in the initial operation, some discharge disrupted because of control failure caused by the n = 1 tearing mode. One possible cause of the n = 1 tearing mode is the edge cooling in high density. The last category is the radiative disruptions, which is characterized by slow current decay with multiple spikes in soft x-ray signals. These spikes are thought to be related to the MHD activity that occurred when the cooling front crossed the rational surface. The radiative disruptions are attributed to a sudden change in edge power balance.

A Novel Family of Single‐Phase Direct Buck AC‐AC Converters With Continuous Input Current, Reduced Components, and Balanced Power Losses

ABSTRACTThis paper introduces a single‐phase step‐down AC‐AC converter designed for voltage sag/swell compensation applications. The converter features a minimal component count, continuous input current, and high efficiency, although only one power switch operates at a high frequency per input voltage half‐cycle. It offers a linear and broad voltage conversion ratio (D) without right‐half‐plane zeros in its small‐signal transfer function, simplifying the controller design. The proposed converter does not need dead time. It ensures balanced voltage and current stresses and power losses among power switches, easing the selection of semiconductors. Compared with existing topologies, it excels in total capacitor voltage, switching device power, and volume metrics of capacitors and inductors, thereby reducing cost and size. Experimental results from a 250‐W prototype demonstrate a peak efficiency of 94.8% and effective voltage sag/swell mitigation as a DVR.

A distributionally robust optimization approach of multi-park integrated energy systems considering shared energy storage and Uncertainty of Demand Response

To enhance the economic efficiency and renewable energy integration capacity of multi-park integrated energy systems (MPIES) and address the issue of insufficient consideration of demand response uncertainty in existing studies, this paper proposes a distributionally robust optimization approach for multi-park integrated energy systems, considering shared energy storage and the uncertainty of demand response. First, models of the shared energy system and demand response are established. Based on these models, a deterministic optimization scheduling model for MPIES is developed, aiming to minimize system costs while considering constraints such as grid power balance. To address uncertainty in demand response, this paper employs Interval Type-2 Fuzzy Theory to construct uncertainty sets and considers system reliability constraints. The original optimization problem is then transformed into an equivalent robust counterpart model, and the optimal distributionally robust solution is obtained through parameter domain decomposition methods. Finally, the proposed method is validated using the IEEE 33-bus system. The results show that considering shared energy storage and demand response individually can reduce total system costs by 4.86 % and 26.46 %, respectively. After accounting for the uncertainty in demand response, the total system cost increases only slightly by 4.36 %, but this improves the system's robustness.

A figurational analysis of Health and/or Physical Education teacher educators’ conceptualisations of policy, and their sociogenesis

ABSTRACT Policy engagement is key to promoting quality physical education yet it has been identified as a ‘grand challenge’ for Health and/or Physical Education (H/PE) internationally. All H/PE professionals, including teacher educators, have a collective responsibility to engage with policy but existing research tells us little about how H/PE teacher educators (H/PETEs) understand and engage with policy. It is important to examine H/PETEs conceptualisations of policy for a few reasons, not least because teacher educators play a crucial role in supporting future generations of teachers who themselves will need to engage with policy as a core feature of their professional lives. Drawing on figurational sociology, and the concept of assemblage, this paper offers insights into the nature and development – or sociogenesis – of teacher educators’ conceptualisations of policy. The data shared in this paper was generated through semi-structured interviews with 12 H/PETE from 7 countries. Inductive-deductive analysis – drawing largely on figurational concepts such as interdependence, power, habitus and sociogenesis – revealed that H/PETEs conceptualised policy as: (i) informing intended action and change; (ii) a way to govern practice; (iii) imposition and possibility. In terms of how these conceptualisations came to be, key features of the H/PETE figuration that were identified as influential include: (i) interdependence with human and non-human elements; (ii) balances of power and (iii) social and individual habitus. It is concluded that capitalising on these elements through professional learning, for example, could support H/PETEs in engaging with policy in productive and meaningful ways. Given that engaging with policy is viewed as a collective responsibility of H/PETEs, and many – if not all – of the H/PETEs felt they needed support in this regard, this should be a key focus for the field.

An Examination of The Alliance System and Its Effective Attraction in Conducting Modern Diplomacy

The quest to maintain a balance in interstate relations, achieve collective security, and mutual support in case of war led to the formation or the emergence of the alliance system. As such, the alliance system was an unsteady and delicate system of interstate relation which started in Europe during the period of the evolution of state formation roughly between 1500 and early 1900. Although the alliance system sometimes prevent war, it was used most times to tilt the balance of power in favour of the allies. Consequently, the alliance system began to define several activities in the world ranging from economic, social, political, to cultural life. Attempts have been made to examine the alliance system and its effective attraction in conducting modern diplomacy. The study was carried out with the aid of secondary sources and internet materials. The result of the findings in this study shows that the main idea underpinning the alliance system was collective security for it was believed that since all the major European powers had strong allies, a major war could not break out since an attack on one power would lead to a counterattack not only by that country, but their allies. The paper concludes that the alliance system has had an effective attraction in conducting modern diplomacy.

Student radiographers’ confidence of adapting practice for autistic patients: A qualitative survey on the role of placement experiences

IntroductionHealthcare services can be inaccessible to autistic people without adaptions to clinical practice and the care provided. Therefore, understanding how radiographer education develops students' confidence in adapting care for autistic patients is crucial. This study aimed to explore how placement experience impacts student radiographer confidence in adapting care for autistic patients. MethodsUK final-year student diagnostic and therapeutic radiographers were invited to complete a qualitative online survey. The survey asked for a description of placement experiences; of observing and/or performing the care of autistic patients and how this impacted confidence in caring for autistic patients. The data was thematically analysed. Results43 responses (of 44 received) were included, from which 5 themes emerged. Those who felt placement experiences developed confidence described opportunities to apply theory learnt at university (theme 1) or drew attention to the benefit of prior (external) experience with autistic people (theme 3). However, the balance of power with the supervising radiographer (theme 2), witnessing autistic patients in distress (theme 4), and the heterogeneous nature of autism (theme 5) disrupted students’ development of confidence. ConclusionSeveral participants in this study found clinical placement developed confidence with autistic patients through applying knowledge and providing an opportunity for reflexive learning. However, various obstacles hindered this development, such as witnessing distressed patients, limited experiences with autistic patients and difficulty navigating relationships with radiographers. Implications for practiceTo improve student radiographers’ confidence of providing care for autistic patients, educators should consider methods, e.g., co-produced simulation, to fill potential gaps in their experience. There is also a pressing need for all radiographers to understand their responsibility in educating students and their impact on student wellbeing.

Gait speed in older adults: exploring the impact of functional, physical and social factors

Purpose: With age there is a neuromuscular and cognitive decline that impacts on functional ability. One of the most characteristic and easily recognisable signs of this decline is a decrease in usual gait speed. For older adults, gait speed is a non-invasive indicator of health and functional status and is regarded as a vital sign. As it predicts various conditions later in life, measuring usual walking speed is crucial in the clinical setting. Therefore, analysing and determining the association between walking speed and the impact of functional and socio-economic variables may facilitate the prevention of associated health problems and the maintenance of physical function in older adults. This study aims to identify the key factors that influence walking speed in older adults, as well as to examine the influence of socio-economic status on walking speed. Methods: A total of 1253 older adults (89.5% women) with a mean age of 78.1 ± 5.8 voluntarily participated in this descriptive cross-sectional study, which examines the results of functional capacity tests and socioeconomic data in older adults. To assess physical function, SPPB tests (chair stand test, balance tests, gait speed test), manual grip strength, muscle quality index, and power were conducted, in addition to measuring body composition and socioeconomic status. Results: The final regression model showed that gait speed was significantly partially explained (R2=0.35; p<0.01) by the socioeconomic environment, age, balance, and relative power. At the same time, belonging to a higher socio-economic environment is linked to lower relative power (p<0.01; η2=0.07). Conclusions: Exploring the factors that affect walking speed in older adults, this study highlights that age, relative power and balance are significant determinants. These clinical markers provide crucial information for designing personalized and effective interventions to promote healthy aging. Keywords: Frailty, gait speed, elderly, relative power, socioeconomic status.

Experimental investigation of steady state power balance in double null and single null H mode plasmas in MAST Upgrade

Global power balance calculations in steady state H mode plasmas varying the distance between separatrices (drsep) and the divertor configuration have been performed in MAST Upgrade. As drsep becomes more negative, more of the power crossing the separatrix goes to the lower divertor. The inner divertor receives a higher fraction of the power exhaust in a Super-X divertor plasma compared to a conventional divertor plasma at similar negative drsep, which is a concern for high power devices employing alternative divertor configurations for power exhaust handling. Global power accounting suggests >30% of the input power is unaccounted for with the power loss channels quantified in this work. Charge exchange and orbit losses from the NBI could account for a large fraction of unaccounted power but it is not possible to precisely determine this without further diagnostic calibration.

Co-optimization of distributed generation, flexible load, and energy storage for promoting renewable energy consumption and power balancing in distribution networks

As more and more DGs are built and connected to the DN, the DN exhibits a notable degree of stochasticity and volatility. This stochasticity and volatility can result in an imbalance of active power in real-time, which may ultimately lead to a collapse of the DN. Therefore, in order to achieve a balance between carbon emissions and economic efficiency, this study introduces a strategy aimed at enhancing the PBC of the DN by employing a collaborative optimization approach involving DG, FL, and ES. The main contribution of this paper is to find a methodology for the co-optimization of DG, FL, and ES, which optimizes the PBC of the DN and the absorption rate of DG to the best conditions. Firstly, a model of DG-FL uncertainty in multiple scenarios is developed, and typical operational scenarios are extracted by effectively quantifying the DG-FL uncertainty of the distribution network. Secondly, a quantitative evaluation method for the balance degree of DG-FL based on IET is proposed. Finally, a two-stage optimization model for DG-FL-ES collaboration is established. The scientific rigor and practical applicability of the proposed method for improving the PBC and facilitating the integration of renewable energy sources are demonstrated through a case study of the power grid in a specific region of Zhejiang Province. The results demonstrate that the method proposed in this paper can enhance the BDODF by 43.44 % and achieve a 100 % absorption rate of renewable energy.

Analytical Solution of Seismic Power-Based Equation of Motion

This research proposes an innovative power-based equation of motion (PBEM) for the single degree of freedom (SDOF) system considering seismic excitation. The external or input frequency function, solution of time, relation between external and kinetic powers, and equation of strain-power (SP) are obtained by solving the power balance equation (PBE). The external frequency function is related to both the particular and total solutions of the PBEM. The particular solution of PBEM is applied on the shake table test of the tunnel-soil-pile interaction (TSPI) model, real-scale test of 2-storied reinforced concrete frame structure, and case study of Bolu tunnel for the verification purpose. The differences in verification (PBEM and previous works) results are found to be 21.6 % for the real-scale test and 19.5 % for the case study. These differences may represent a reasonable agreement with verification. Also, the relationship between the kinetic and external powers is verified with the previous shake table test of steel cantilever column, whereas the difference in results is found to be 5 %. Finally, a design chart is proposed for predicting the input frequency function for various frequency ratios and damping.