Interruption Cost Research Articles

Severe Increase in Nursing Labor Cost and Effect on Surgical Department Financial Margins at an Academic, Tertiary Medical Center.

A pre-existing nationwide nursing shortage drastically worsened during the pandemic, causing a significant increase in nursing labor costs. We examined the financial impact of these changes on department of surgery financial margins. Operating room, inpatient, and outpatient financial metrics were analyzed. Monthly averages from a 14-month control cohort, January 2019 to February 2020 (pre-COVID-19), were compared with a 21-month cohort, March 2020 to November 2021 (COVID-19). True revenue and cost data from hospital accounting records, not estimates or administrative projections, were analyzed. Statistics were performed with standard Student's t -test and the Anderson-Darling normality test. Monthly surgical nursing costs increased significantly, with concomitant significant decreases in departmental contribution to margin. No significant change was observed in case volume per month, length of stay per case, or surgical acuity, as standardized by the US Centers for Medicare & Medicaid Services Case Mix Index. To obviate insurance payor mix as a variable and standardize cost data, surgical nursing expense per relative value unit was analyzed, demonstrating a significant increase. Hospital-wide agency nursing costs increased from $5.1 to $13.5 million per month (+165%) in 2021. Our results demonstrate a significant increase in surgical nursing labor costs with a resultant erosion of department of surgery financial margins. Use of real-time accounting data instead of commonly touted administrative approximations or Medicare projections increases both the accuracy and generalizability of the data. The long-term impact of both direct costs from supply chain interruption and indirect costs, such as limited operating room and ICU access, will require further study. Clearly this ominous trend is not viable, and fiscal recovery will require sustained, strategic workforce allocation.

Providing an optimal demand response program through placement of automatic switches and energy storage systems to improve the reliability of power distribution networks

AbstractCreating highly reliable distribution networks is becoming increasingly vital in today's society. In a similar vein, utilities have issues in properly planning and developing distribution networks, both to reduce their imposed costs and to meet the demands of their consumers. In the presence of Demand Response Program (DRP), this research provides a coordinated architecture that considers automated switches and Energy Storage Units (ESUs) placement with the uncertainty of repair time to enhance the reliability of power distribution network. The suggested objective for optimal placement of automatic switches, ESUs and DRPs is to minimize a combination of reliability index (SAIDI) and Total Cost of system (TC). Customer interruption cost, energy not supplied cost, automated switch investment, ESU investment, ESU participation cost, and DRP cost are all considered as parts of the total cost. The proposed method is used in four different cases on a common reliability test system, followed by numerous sensitivity studies, in order to illustrate applicability and efficiency of suggested method.

An Optimal Scheduling Method of Shared Energy Storage System Considering Distribution Network Operation Risk

Shared energy storage systems (SESS) have been gradually developed and applied to distribution networks (DN). There are electrical connections between SESSs and multiple DN nodes; SESSs could significantly improve the power restoration potential and reduce the power interruption cost during fault periods. Currently, a major challenge exists in terms of how to consider both the efficiency of the operation and the reliability cost when formulating the SESS scheduling scheme. A SESS optimal scheduling method that considers the DN operation risk is proposed in this paper. First, a multi-objective day-ahead scheduling model for SESS is developed, where the user’s interruption cost is regarded as the reliability cost and it is the product of the occurrence probability of the expected accident and the loss of power outage. Then, an island partition model with SESS was established in order to accurately calculate the reliability cost. Via the maximum island partition and island optimal rectification, the SESS was carefully integrated into the power restoration system. Furthermore, in order to minimize the comprehensive operation cost, an improved genetic algorithm for the island partition was designed to solve the complex SESS optimal scheduling model. Finally, a case study on the improved PG&E 69 bus system was analyzed. Moreover, we found that the DN’s comprehensive operation cost decreased by 6.6% using the proposed method.

Optimal Phase Balancing in Electricity Distribution Feeders Using Mixed-Integer Linear Programming

A mixed-integer linear programming (MILP) model that includes reductions in neutral current, feeder energy-loss cost, customer interruption cost, and labor cost is developed to derive the optimal phase-swapping strategy to enhance the phase balancing of distribution feeders. The neutral current of the distribution feeder is reduced by the phase-swapping strategy so that the tripping of the low-energy overcurrent relay can be prevented and customer-service interruption costs and the labor cost to execute the phase-swapping works can be justified by the energy-loss reduction obtained. The novelty of the study is its derivation of the phase-swapping strategy using mixed-integer linear programming to solve the problem of the unbalance of the distribution feeders. A Taipower distribution feeder is used to derive the phase-swapping strategy to demonstrate the proposed MILP model for phase balancing. The comparison of the phase currents and neutral current before phase-swapping reveals that the three-phase balance was not only significantly improved, but that the voltage unbalance was also decreased dramatically using the proposed phase-swapping strategy.

Economic analysis of annual load loss due to voltage sags in industrial distribution networks with distributed PVs

In an industry, analysis of load disconnection indices is essential to determine the annual economic loss because of the high cost of load interruptions. With the interconnection of PVs in modern industrial networks, this analysis gets more complicated due to controls associated with PV inverters for reactive power support. Hence, the paper proposes a unique method for such analysis that relies on dynamic simulation to calculate load disconnections. The dynamic simulation allows the integration of the voltage tolerance curve of loads and controls associated with PVs making the scenarios more realistic. The indices are determined by employing statistical experiments which account for annual variability of daily solar and load profiles with the least possible runs of dynamic simulation. The proposed method is applied to calculate load disconnection indices for an IEEE 399-1997 industrial distribution system. A comparative analysis of the cost of disconnection under a variety of solar penetration and operation scenarios is presented. Network planners and reliability engineers can potentially utilize the proposed method to identify PV inverter controls, placement, and size effects on the annual load disconnection indices due to voltage sags.

The Gender Wage Gap in an Online Labor Market: The Cost of Interruptions

Abstract This paper analyses gender differences in working patterns and wages on Amazon Mechanical Turk, a popular online labour platform. Using information on 2 million tasks, we find no gender differences in task selection nor experience. Nonetheless, women earn 20% less per hour on average. Gender differences in working patterns are a significant driver of this wage gap. Women are more likely to interrupt their working time on the platform with consequences for their task completion speed. A follow-up survey shows that the gender differences in working patterns and hourly wages are concentrated amongst workers with children.

A Risk-Based Framework to Improve a Distribution System’s Resilience against Earthquakes

Earthquakes and other natural disasters have caused significant damages to power systems, indicating the necessity to enhance power system resilience. This paper proposes a risk-based resilience enhancement framework against earthquakes that considers their stochastic nature. The proposed framework supports the decision-making of distribution system operators (DSOs) for retrofitting substation components and underground cables to enhance distribution system resilience. The framework consists of four phases, namely earthquake modeling, vulnerability assessment, risk assessment, and resilience enhancement. An attenuation relationship is used to model the earthquake characteristics. Vulnerability assessment includes the failure probability calculation of substation components and a fault-tree method application to examine the seismic vulnerability of the substation. Conditional value at risk (CVaR) is used to assess the seismic risk, and includes the estimation of repair cost and customer interruption cost due to the damage caused by the earthquake, as well as the power generation cost of the distributed energy resources (DERs) used to meet the demand locally. A modified risk reduction worth (RRW) metric is adopted to determine the optimal retrofitting strategy to enhance resilience. The proposed framework was applied to a real distribution substation to examine the effectiveness of substation component retrofitting for resilience enhancement.

Multi Microgrid Framework for Resilience Enhancement Considering Mobile Energy Storage Systems and Parking Lots

This paper proposes a practical and effective planning approach that takes advantage of the mobility and flexibility of mobile energy storage systems (MESSs) to increase distribution system resilience against complete area blackouts. MESSs will be very useful for boosting the system’s resilience in places affected by disasters when the transmission lines are damaged. A joint post-disaster restoration strategy for MESSs and PEV-PLs is proposed, along with distributed generation and network reconfigurations, to reduce total system costs, which include customer interruption costs, generation costs, and MESS operation and transportation costs. The integrated strategy accounts for the uncertainty of the production of wind- and solar-powered microgrids (MGs) and different forms of load demand. Therefore, this paper assesses the effect of MESSs on distribution system (DS) resilience in respect of MG cost reduction and flexibility. Due to the multiple networks, PEV-PLs, DGs, and MESS limitations, the suggested restoration problem is stated as a mixed-integer linear programming problem. The suggested framework is complemented using a benchmark testing system (i.e., 33-bus DS). To assess the effectiveness of the proposed model, the model’s output is contrasted with results from typical planning and a traditional model. The comparison of the data shows that the suggested model, in addition to MESSs, effectively achieves a large decrease in cost and enhances the DS resilience level.

Optimal layout model of feeder automation equipment oriented to the type of fault detection and local action

In feeder automation transformation there are difficulties in equipment and location selection. To help with this, an optimal layout model of feeder automation equipment oriented to the type of fault detection and local action is proposed. It analyzes the coordination relationship of the three most common types of automation equipment, i.e., fault indicator, over-current trip switch and non-voltage trip switch in the fault handling process, and the explicit expressions of power outage time caused by a fault on different layouts of the above three types of equipment are given. Given constraints of power supply reliability and the goal of minimizing the sum of equipment-related capital investment and power interruption cost, a mixed-integer quadratic programming model for optimal layout is established, in which the functional failure probability of equipment is linearized using the 3delta principle in statistics. Finally, the basic characteristics of the proposed model are illustrated by different scenarios on the IEEE RBTS-BUS6 system. It can not only take into account fault location and fault isolation to enhance user power consumption perception, but also can guide precise investment to improve the operational quality and efficiency of a power company.

Markov-Based Reliability Assessment for Distribution Systems Considering Failure Rates

Switches (SWs) and renewable distributed generations (RDG) are subject to failure as well as other components of a system that are usually presumed fully reliable in the literature. It can lead to an overestimation of their contribution to reliability enhancement disregarding their dysfunction. This study considers the failure rate of SWs and RDGs to assess their impact on the reliability cost of the system and their effect on the optimal placement using a Markov-based approach. The optimal placement of SWs and RDGs in radial distribution systems is carried out simultaneously aim at minimizing the overall cost including investment, maintenance of SWs, and RDGs alongside the interruption cost. The performance of the model is verified through different scenarios and tested on RBTS bus 2. The results show that high values of the failure rates lead to fewer allocations to prevent plummeting the reliability of the system and increasing the capacity of the RDG results in fewer SWs allocation.

Distributed peer-to-peer transactive residential energy management with cloud energy storage

Transactive energy management stimulates residential prosumers to participate in a local market. This improves energy efficiency and reduces energy costs. An effective method to reduce consumers' electricity bills is the usage of energy storage devices. However, the high investment and maintenance costs of these devices still limit their applications in the individual distributed framework. Recently, cloud energy storage (CES) as a shared energy storage technology has been introduced to provide storage services for residential consumers at a lower cost. In order to overcome the limitations of the individual framework and create new economic prospects, the CES is used in this paper to support numerous residential consumers in the energy market. This paper proposes an optimal energy management model in a transactive energy framework based on a distributed optimization mechanism for peer-to-peer (P2P) energy trading with the usage of the alternating direction method of multipliers. In this cooperative structure, residential users and CES participate in a decentralized framework to reach a consensus that preserves their privacy. In this proposed model, different types of loads, distributed energy resources and users' costs consisting of the grid energy cost, the P2P energy cost, the battery degradation cost, the thermal discomfort cost, the interruption cost, and the daily investment cost for individual batteries and CES are considered. The effectiveness of the proposed model is verified through various simulations. Numerical results show that the presence of CES in the proposed model and its participation in P2P energy trading reduces the cost of residential users, decreases the energy demand from the network, and increases CES owner's profit. Therefore, the application of the proposed model is valuable for the residential users, CES, and the grid.

Risk assessment criteria for utilizing dynamic line rating in presence of electric vehicles uncertainty

Dynamic line rating (DLR) is a grid enhancing technology to enable a more effective use of transmission capacity of existing infrastructure. The growth in load consumption along with a high integration of electric vehicles (EV) highlights the potential of DLR utilization for reducing the congestion costs and overloading risks. Selecting the proper lines for DLR implementation is necessary to exploit optimally the benefits of DLR. In this paper, we propose risk assessment criteria to select proper lines for DLR implementation to minimize the system operation costs and the risk of overloading caused by high EV integration. A stochastic method is introduced to model the uncertain behavior of EV in charging stations. Furthermore, we analyze the impact of inherent uncertainties in DLR by comparing different DLR percentages. The benefits of using DLR in different percentages are then quantified in terms of supply and interruption costs. The results show improvements in system supply cost, system reliability, and operation risks.

Age differences in the recovery from interruptions.

We tested the hypothesis that there is an age-related deficit in the recovery from interruptions. This hypothesis is based on the idea that it is more difficult for old than for young adults to establish a focused state after working memory has been "opened up" through an interruption. Old (N = 95) and young adults (N = 94) performed competing nondominant and dominant primary tasks (selecting either exogenously or endogenously cued targets) in alternating, single-task blocks that were occasionally interrupted through trials with unrelated math tasks. As predicted, after interruptions, older adults showed increased and prolonged recovery costs, as well as generally larger endogenous/exogenous and conflict effects in blocks that contained interruptions. Individual differences in working memory (WM) capacity did not produce comparable results, suggesting that the interruption-based deficits were specific to aging. In addition, the theoretically important, paradoxical cost asymmetry (i.e., larger interruption costs for the dominant exogenous than for the nondominant endogenous task) was stronger in old than in young adults. These results provide novel insights about the interplay between WM and long-term memory during task control, as well as the origin of age differences in task-set selection. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Optimal resilient allocation of mobile energy storages considering coordinated microgrids biddings

This paper presents an algorithm for optimal resilient allocation of Mobile Energy Storage Systems (MESSs) for an active distribution system considering the microgrids coordinated bidding process. The main contribution of this paper is that the impacts of coordinated biddings of microgrids on the allocation of MESSs in the day-ahead and real-time markets are investigated. The proposed optimization framework is another contribution of this paper that decomposes the optimization process into multiple procedures for the day-ahead and real-time optimization horizons. The active distribution system can transact active power, reactive power, spinning reserve, and regulating reserve with the microgrids in the day-ahead horizon. Further, the distribution system can transact active power, reactive power, and ramp services with microgrids on the real-time horizon. The self-healing index and coordinated gain index are introduced to assess the resiliency level and coordination gain of microgrids, respectively. The proposed algorithm was simulated for the 123-bus test system. The method reduced the average value of aggregated operating and interruption costs of the system by about 60.16% considering the coordinated bidding of microgrids for the worst-case external shock. The proposed algorithm successfully increased the self-healing index by about 49.88% for the test system.

Dynamic Economic Dispatching Considering Time-Coupling Spinning Reserve Response Risk with High Penetration of Wind Power

Aiming at the problem that the current dynamic economic dispatch (DED) fails to consider the response risk of spinning reserve caused by the fluctuation and uncertainty of wind power, we work out a DED problem considering time-coupling spinning reserve response risk while the stochasticity and variability arising from RESs are taken into consideration. The developed framwork unified the response risk of reserve caused by forced shutdown of the unit into the response risk caused by time coupling. The expected customer interruption cost (ECOST) and the expected abandoned wind cost considering this reserve response risk are added to the objective function. While seeking the minimum objective function, the system is automatically configured with suitable reserve to ensure the consistency of the system’s response risk in each period. An improved multi-universe parallel quantum genetic algorithm was used to solve the model. Numerical examples and analysis prove the effectiveness and feasibility of the proposed method.

Supply continuity in Turkish electricity distribution grid: electricity interruption cost forecasting with time series analysis and machine learning

Supply continuity in Turkish electricity distribution grid: electricity interruption cost forecasting with time series analysis and machine learning

A global and local perspective of interruption frequency in a visual search task.

We investigated the impact of frequency of interruptions in a simulated medical visual search task. Participants (N = 150) performed the visual search task during which they were interrupted by a number-classification task in 25, 50, or 75% of all trials, respectively, reflecting the frequency conditions (i.e., low, mid, high). Target presence (i.e., present vs. absent) and interruption (i.e., uninterrupted vs. interrupted) were varied within-subjects, and interruption frequency was varied between-subjects. Globally, on a frequency condition level, participants in the low frequency condition had longer mean response times (RT) for the primary visual search task than in the high condition, but there were no other performance differences between the three frequency conditions. Locally, on the level of specific interruption effects, accuracy decreased directly after interruptions for target present but not for target absent trials. Furthermore, interruptions caused significant interruption costs, reflected in slower overall RTs in interrupted than in uninterrupted trials. The combined findings show that especially for critical visual search tasks as in the medical field, interruptions—regardless of frequency—should be avoided.

Reliability based maintenance programming by a new index for electrical distribution system components ranking

Reliability and accessibility of distribution systems are important goals that have significant impacts on the costs. The proper strategy of maintenance based on components arrangement and assets is the best way to reach these goals. This strategy is a kind of uses reliability-centered maintenance (RCM). Due to the limited maintenance budget, performing maintenance activities for all components of the system is neither possible nor logical. So most of the resources should be allocated to the most critical and important components. This paper presents a novel analytical method of prioritization of distribution systems’ components by introducing a new weighted cumulative Reliability-based diagnostic importance factor. This new factor includes different reliability indexes in form of diagnostic factors and will show that the order of components obtained by this method is better than another method in saving the budget and providing reliability of the system. The process of decision-making for prioritization of distribution systems’ components based on their criticality degree will both improve the reliability level of the total system and decrease the cost of load interruption and finally maintenance costs. The proposed model is implemented on a radial distribution network. Numerical results show the effectiveness of the proposed RCM model for micro-grids.

Optimal Modification of Peak-Valley Period Under Multiple Time-of-Use Schemes Based on Dynamic Load Point Method Considering Reliability

Time-of-use (TOU) is an effective price-based demand response strategy. A reasonable design of TOU strategy can effectively reduce the peak-valley difference, and then produce a lot of benefits (such as delaying power grid investment, reducing interruption cost, and improving reliability). However, changing peak-valley period has a great influence on the peak-valley difference and power supply reliability of power system. Therefore, this paper aims to investigate the optimal modification of peak-valley period considering reliability loss under multiple TOU schemes. Firstly, this paper presents a clustering model and algorithm of optimal load curve based on a minimum error iteration method. Secondly, an optimal modification of peak-valley period based on a dynamic load point method is proposed, and the traditional peak-valley difference is replaced by the global peak-valley difference to calculate the objective function. Thirdly, this paper establishes a load–reliability relation fitting model based on the back propagation neural network. Finally, the effectiveness and correctness of the proposed method are investigated by the Roy Billinton test system and reliability test system.

The mechanics of plastic volumetric deformation of rock and the rockburst mechanism

Relevance and problematics. The problem of rock pressure dynamic manifestations, primarily rockbursts and tectonic shocks, is particularly acute for both coal fields and ore deposits. Dynamic manifestations of rock pressure lead to injury and death, to kilometers of destroyed mine workings, loss of minerals, business interruption and additional costs for forecast and prevention. However, these geomechanical phenomena seem to be the most unexplored. They have been studied purely at the empirical level. This is due to poor understanding of the elastic energy accumulation and release mechanism in dynamic phenomena. Methods of research. The proposed model of plastic deformation of rock and the resulting mechanism of rockbursts and tectonic shocks, impacts and earthquakes are based on analytical criteria for rock plasticity and strength, confirmed by a large amount of experimental data. Results, their analysis and recommendations for use. Based on the previous studies performed by the author, a new model of plastic deformation of rocks at the stage of deformation strengthening is proposed. Based on this model, the mechanism of rock plastic deformation, the mechanism of fractured block media destruction and accumulation of deformation energy by rocks are substantiated. It is shown that blocks of various ranks turning leads to deformation energy accumulation in the rock mass. The energy is accumulated both in the blocks and in the surrounding. Conclusions. The proposed model of rockburst and other dynamic phenomena, as well as block mass strength criterion, made it possible to obtain a burst hazard criterion in an analytical form for the first time. The fracturing (blocking) role and contribution to the rockburst mechanism has been shown for the first time. Comparison of the proposed burst hazard criterion with an empirical analogue shows good convergence.