Unused Capacity Research Articles

Optimal planning of SOP in distribution network considering 5G BS collaboration

AbstractThe flexibility of soft open point (SOP) in spatial power regulation enhances the distribution network's (DN) integration of large‐scale renewable energy sources. However, the high cost of SOP and its limited capability for temporal power regulation impede its widespread adoption. Given the rapid expansion of 5G base stations (BSs), utilizing their energy storage to participate in DN planning and operation optimization provides a promising solution. Therefore, this paper proposes an optimal planning method of SOP in DN, considering collaborations with 5G BSs. The objective is to enhance DN’s power regulation in both temporal and spatial dimensions, while minimizing the investment cost of SOP and fully utilizing the unused capacity in base station energy storage (BSES). Firstly, the flexible regulation models of SOP and 5G BS are established, with the real‐time dispatchability of BSES formulated. Then, a bi‐level optimization model is proposed, where the planning layer aims to minimize the total cost, while the operational layer aims to decrease the average voltage deviation. Additionally, an improved Shapley value method based on interactive power is developed for benefit allocation, which enhances the engagement of 5G BSs to participate in DN regulation. The effectiveness of proposed method is validated by simulation results.

Optimization dispatching strategy for an energy storage system considering its unused capacity sharing

In renewable energy systems, energy storage systems can reduce the power fluctuation of renewable energy sources and compensate for the prediction deviation. However, if the renewable energy prediction deviation is small, the energy storage system may work in an underutilized state. To efficiently utilize a renewable-energy-sided energy storage system (RES), this study proposed an optimization dispatching strategy for an energy storage system considering its unused capacity sharing. First, this study proposed an unused capacity-sharing strategy for the RES to fully utilize the storage’s unused capacity and elevate the storage’s service efficiency. Second, RES was divided into “deviation-compensating energy storage (DES)” and “sharing energy storage (SES)” to clarify the function of RES in the operation process. Third, this study established an optimized dispatching model to achieve the lowest system operating cost wherein the unused capacity- sharing strategy could be integrated. Finally, a case study was investigated, and the results indicated that the proposed model and algorithm effectively improved the utilization of renewable-energy-side energy storage systems, thereby reducing the total operation cost and pressure on peak shaving.

Integrated Optimal Energy Management of Multi-Microgrid Network Considering Energy Performance Index: Global Chance-Constrained Programming Framework

Distributed generation (DG) sources play a special role in the operation of active energy networks. The microgrid (MG) is known as a suitable substrate for the development and installation of DGs. However, the future of energy distribution networks will consist of more interconnected and complex MGs, called multi-microgrid (MMG) networks. Therefore, energy management in such an energy system is a major challenge for distribution network operators. This paper presents a new energy management method for the MMG network in the presence of battery storage, renewable sources, and demand response (DR) programs. To show the performance of each connected MG’s inefficient utilization of its available generation capacity, an index called unused power capacity (UPC) is defined, which indicates the availability and individual performance of each MG. The uncertainties associated with load and the power output of wind and solar sources are handled by employing the chance-constrained programming (CCP) optimization framework in the MMG energy management model. The proposed CCP ensures the safe operation of the system at the desired confidence level by involving various uncertainties in the problem while optimizing operating costs under Mixed-Integer Linear Programming (MILP). The proposed energy management model is assessed on a sample network concerning DC power flow limitations. The procured power of each MG and power exchanges at the distribution network level are investigated and discussed.

A Cooperative Game Approach for Optimal Design of Shared Energy Storage System

The energy sector’s long-term sustainability increasingly relies on widespread renewable energy generation. Shared energy storage embodies sharing economy principles within the storage industry. This approach allows storage facilities to monetize unused capacity by offering it to users, generating additional revenue for providers, and supporting renewable energy prosumers’ growth. However, high investment costs and long payback periods often hinder the development of battery storage. To address this challenge, we propose a shared storage investment framework. In this framework, a storage investor virtualizes physical storage equipment, enabling prosumers to access storage services as though they owned the batteries themselves. We adopt a cooperative game approach to incorporate storage sharing into the design phase of energy systems. To ensure a fair distribution of cooperative benefits, we introduce a benefit allocation mechanism based on contributions to energy storage sharing. Utilizing realistic data from three buildings, our simulations demonstrate that the shared storage mechanism creates a win–win situation for all participants. It also enhances the self-sufficiency and self-consumption of renewable energy. This paper provides valuable insights for shared storage investors regarding optimal design and benefit allocation among multiple stakeholders.

Primary Frequency Control with an Air Handling Unit

The green energy transition threatens stability of the power grid due to associated reduction in grid synchronous inertia. Primary frequency control (PFC) can compensate for the challenge; however, sufficient procurement of primary frequency capacity could depend on more extensive employment of demand-side loads for PFC. Ventilation fans in particular present a promising class of such loads because of ubiquity of variable-frequency drives and relatively slow thermal and ventilation dynamics of indoor spaces. This research proposes a novel method for PFC by an air handling unit: the open loop control is shown to have favorable dynamic characteristics, and its impact on indoor climate is shown to be tolerable. This study suggests that the largely unused primary frequency capacity of ventilation fans could be exploited to provide primary frequency response for low inertia power grids.

Application of Time-Driven Activity-Based Costing for Head and Neck Microvascular Free Flap Reconstruction.

Traditional hospital accounting fails to provide an accurate cost of complex surgical care. Here we describe the application of time-driven activity-based costing (TDABC) to characterize costs of head and neck oncologic procedures involving free tissue transfer. Retrospective cohort study. Single tertiary academic medical center. An analysis of head and neck oncologic procedures involving microvascular free flap reconstruction from 2018 to 2020 (n = 485) was performed using TDABC methodology to measure cost across operative case and postoperative admission, using quantity of time and cost per unit of each resource to characterize resource utilization. Univariate and generalized linear mixed models were used to examine associations between patient and hospital characteristics and cost of care delivery. The total cost of care delivery was $41,905.77 ± 21,870.27 with operating room (OR) supplies accounting for only 10% of the total cost. Multivariable analyses identified significant cost drivers including operative time, postoperative length of stay, number of return trips to the OR, postoperative complication, number of free flaps performed, and patient transfer from another hospital or via emergency department admission (P < .05). Operative time and postoperative length of stay, but not operative supplies, were primary drivers of cost of care for head and neck oncology cases involving free tissue transfer. TDABC offers granular cost characterization to inform cost optimization through unused capacity identification and postoperative admission efficiencies.

Misallocation in multiple airport regions

In many of the most densely populated and dynamic economic regions around the world, passengers have access to multiple airports in their neighborhood. Beijing, Hong Kong and the Greater Bay Area, London, New York and Tokyo can serve as prominent examples. Due to geographic accessibility and facility characteristics, some airports within the same multiple-airport region (MAR) may have unused capacity whereas others experience severe congestion. Policy makers in MARs, therefore, face a common challenge: managing the allocation of air traffic among airports. Perimeter rules set upper limits on the distances of nonstop flights operated from specific airports within MARs. Traffic distribution rules such as perimeter rules have been used in the United States and Japan. In this study, we distinguish between misallocation and quantity effects. We demonstrate that in the absence of regulation (laissez faire) a combination of a high demand combined with low capacity, as would be the case for LaGuardia as well as Reagan National in the US, can produce substantial welfare losses due to misallocation. This indicates that there can be benefits from centralized policies in the form of perimeter rules and that the introduction or repeal of such rules requires a careful assessment of the effects on the MAR as a whole.

A comprehensive framework for predicting electric vehicle's participation in ancillary service markets

AbstractElectric vehicles (EVs) have significant potential to offer unused capacity in ancillary service markets, providing unique opportunities for market operators to utilise these resources. EVs have a rapid response and high availability, making them a good fit for the frequency containment reserve (FCR) market. However, EV aggregators (EVAGs) must aggregate capacity blocks due to the limited capacity of individual EVs. An application of a supervised machine learning method named XGBoost is suggested to help EVAGs predict the amount of EV participation in the FCR market. The objective is to forecast yearly involvement using data from only a single week, using the game theory method SHapley Additive exPlanations (SHAP) to minimise extra data. The proposed strategy helps aggregators and uses feature engineering to select EVs with high potential to boost revenue. The proposed framework is effective in predicting EV performance in the DK‐2 market, as shown by multiple analyses.

Developing a tactical decision-making framework for a sustainable egg supply chain considering switchable parallel machines

ABSTRACT The increasing world population has increased food supply needs in recent years. Despite the numerous studies in the field of food supply chains, there are few articles on optimizing a sustainable egg supply chain. A fuzzy multi-objective mathematical model is presented to optimize a sustainable egg supply chain in a tactical decision structure. Switchable green packaging and labeling machines in parallel production lines, suppliers with different reliability rates and the provision of raw materials with different qualities have been studied in this article. Despite the significant reduction of the total costs while using switchable machines, the majority of the costs are still related to raw materials so that an increase of 2 to 4 times in the amount of input materials can change the values of objective functions by 23% to 60%. By using the unused capacity of the packaging and labeling machines, the total costs can be reduced significantly.

Cloud Cost Optimization: Achieving Cost Savings through AWS Spot Fleet Utilization and Optimizing Cloud Resource Usage

Purpose: Cloud computing has revolutionized the way organizations deploy and manage their IT infrastructure. However, as cloud adoption increases, so does the complexity of managing cloud costs.&#x0D; Methodology: AWS Spot Fleet offers a compelling way to optimize cloud expenses by leveraging unused computing capacity at a fraction of the standard price.&#x0D; Findings: This paper explores strategies for cloud cost optimization through AWS Spot Fleet utilization and effective cloud resource management.&#x0D; Unique contribution to theory, policy and practice: By incorporating real-time use cases and practical advice, we aim to guide organizations in maximizing their cloud investment without sacrificing performance or reliability.

Technical Efficiency of Mexico's Public Health System in the Delivery of Obstetric Care, during 2012-2018.

The objective of this study was to evaluate the technical efficiency of Mexico's public health system in the delivery of obstetric care from 2012 to 2018. A multi-stage quantitative study of the public health institutions responsible for 95% of the system's obstetric services was conducted using data envelopment analysis. The efficiency of state-level productive units (decision-making units, or DMUs) was calculated and juxtaposed with the DMUs' maximum (0.82) and minimum (0.22) scores. Using the outcomes of the initial stage, the average technical efficiency of each institution at the national level was estimated and compared. The results were also utilized to estimate and compare the average efficiency of each state-level health system based on economic characteristics (state GDP per capita). Outputs included prenatal visits and deliveries, while inputs comprised gynecologists, exam rooms, and delivery rooms. Institutional efficiency ranged from 0.16 to 0.82, with an average of 0.417. The Ministry of Health (0.82) and the Mexican Social Security Institute (0.747) exhibited the highest efficiency scores, while the remaining institutions (Institute for Social Security and Services for State Workers [ISSSTE]; Mexican Petroleum [PEMEX]; the Secretary of National Defense [SEDENA]; and the Navy [SEMAR]) scored below the health system average. Of the 153 DMUs, 20% surpassed the maximum (0.82) and 40.6% fell below the minimum (0.22). These findings indicate that 80% of DMUs have unused operational capacity that could be utilized to enhance technical efficiency. No relationship was found between efficiency and the GDP of Mexico's 32 politico-administrative divisions. The efficiency gap between institutions (0.66) shows that while some DMUs are saturated (exhibiting high efficiency scores), the majority have unused operational capacity. Leveraging this untapped capacity could address the needs of vulnerable populations facing restricted access due to health system fragmentation.

The impact of Airport business practices and governance forms on excess capacity

Excess capacity poses a persistent challenge for airports as they often encounter lumpy capacity problems. The excess capacity is primarily influenced by factors such as uncertain demand, airline competition, airport pricing strategies, and the market structure of the airport industry. However, airport business practices also account for this issue. Using data from 59 U.S. airports between 2009 and 2019, we found that residual airports have less unused capacity than compensatory airports. This can be explained by the control of signatory airlines over the residual airports’ investment decisions and the lack of retained earnings under the residual agreement. We did not detect a significant difference in excess capacity between single-purpose and multipurpose governance forms. However, it is noteworthy that large hub airports exhibit higher capacity utilization compared to medium hub airports. Airports dominated by LCCs have higher capacity utilization rates, while the unused capacity remains consistent between cargo and non-cargo airports.

Jam in the Tunnel: On Urban Freight Tunnels, Their Operational Scheduling, and Unused Transport Capacity

Underground passageways for the transport of goods and people have fascinated mankind throughout the centuries. Recent initiatives in different parts of the world aim at rekindling the freight tunnel concept for urban logistics. According to this concept, freight is lifted into a tunnel, moved via electrically powered vehicles, rail cars, or maglev shuttles toward inner-city microhubs, and finally delivered with environmentally friendly vehicles to urban recipients. The main justification for this concept to outweigh the huge tunnel boring cost is a substantial reduction of road-based urban freight traffic. To warn about unfulfilled expectations, however, we show that the combination of time-critical goods, small inner-city hubs with restricted storage capacity, and the wrong booking procedure can hinder a loading of tunnel vehicles to capacity. To do so, we consider a polynomially solvable scheduling problem where due date-restricted shipments are to be assigned to tunnel vehicles and delivered to a given set of microhubs with limited storage capacity. Scarce hub capacities, tight due dates, and the wrong booking policy may not only lead to unused tunnel capacity but also to shipments that cannot be feasibly transported through the tunnel. If they are handed over to trucks as a fallback option, we show that a Braess-like paradox can occur: The time-critical, small-lot transports of the leftover shipments can produce even more surface traffic than trucking all shipments right from the start without the tunnel. Supplemental Material: The online appendices are available at https://doi.org/10.1287/serv.2023.0005 .

The potential of combining passenger rail with freight: A New York City case study

Utilizing passenger rail, including subways, to transport goods can have advantages over trucking in terms of efficiency and emissions. While some experimentation is ongoing in this area, combined passenger and rail opportunities in specific cities merit further attention. To more concretely examine how to leverage passenger rail for freight, this paper explores the potential of utilizing unused capacity in New York City (NYC) subway trains for transporting goods. Using General Transit Feed Specification (GTFS), rail and passenger data for the NYC subway, we found ways to use excess capacity and existing rail lines for freight transportation. We visualized a freight train timetable and graph, analyzed meet-errors between freight and passenger trains, and formulated prevention policies. Using U.S. Environmental Protection Agency data, we estimated emission reductions from replacing trucks with unused subway capacity. Our findings suggest that with adequate policies, investments and redesign, combining passenger rai and freight in the subways could significantly reduce truck trips, traffic congestion, and greenhouse gas emissions compared to trucking alone. However, implementing this approach requires careful collaborative planning, investment, enhanced security screening, and streamlined operations to minimize impacts on passenger transport. Further efforts should explore in more depth the costs and benefits and practical design and policy issues around using excess passenger rail capacity for freight transport in NYC and other cities.

Development and application of energy-efficient medical beds based on IoT for patient monitoring

Later logical accomplishments and mechanical progresses have brought forward a gigantic show of modern or overhauled restorative gadgets, empowered with highly evolved embedded-control capacities and interactivity. From the ultimate decade of the 20th century, restorative beds have specifically been motivated through this surge, taking on unused shapes and capacities, whereas obliging to installation properties that have gotten to be famous for those gadgets. The beyond fifteen a long time have too delivered ahead modifications to conceptual systems, concerning the item plan and fabricating forms, As properly as the persistent viewpoints on patient-care situations and openness. This paper offers the components and the steps of design and implementation of electric medical bed supplied with monitoring devices and various sensors working together to give the Arduino a full report about the conditions of patient and according to this report the right decisions can be taken. The principles of internet of things (IOT) are applied to achieve this instrument. The paper primarily focuses on the objectives, components, and functionality of the system, such as monitoring physical parameters, detecting emergencies, reducing workload, and communicating with caretakers.

Calculation of the Cost of Training Medical Students in One of the AJA Universities of Medical Sciences Using Time-Driven Activity-Based Costing Method

Background: Estimating the total cost of services is crucial for utilizing available resources more efficiently and effectively. By employing the time-driven activity-based costing (TDABC) method, not only can costs be calculated, but also the efficiency and unused capacity of resources can be assessed. Objectives: This study aimed to calculate the cost of education for each medical student at one of the AJA Medical sciences Universities in 2022 using the TDABC method. Methods: This quantitative study was conducted cross-sectionally and retrospectively in a descriptive-analytical manner. The data were collected and analyzed through interviews and observations. To analyze and allocate costs, administrative and educational departments were categorized into three levels: Overhead, intermediate, and final activity centers. Then, using the TDABC approach in Microsoft Excel 2013 software costs from the overhead and intermediate activity centers to the final activity center and students. Results: The study estimated the average cost of educating each medical student to be approximately IRR 6 267 568 065. Additionally, the unused capacity of resources in overhead and intermediate centers was observed to be 30% (range: 4 - 44%) and 33% (range: 26 - 43%), respectively. Conclusions: The findings indicated that the cost per student is somewhat reasonable; however, there is a high level of unused capacity in the university and faculty activity centers. The effective management of human resources and equipment is necessary to enhance service delivery processes, increase productivity, and reduce unused capacity.

Reverse milk run – the logistics retrenchment strategy

Learning outcomes After completion of the case study, students will be able to understand the concept of clustering and identify clusters for improving capacity utilization, analyse transport routes to optimize logistics resources, analyse the impact of a full truckload on resource optimization, evaluate unused capacity and ascertain the impact of reverse milk run to reduce the same and apply clustering and reverse milk run to optimize the logistics resources. Case overview/synopsis The case study is about a freight forwarding company that offered end-to-end logistics solutions for the exporters based in India. Within a short time span, the company became one of the sought-after service providers for its clients. However, when the company planned to expand its business by expanding its client base, the efficiencies reduced and hurt the profitability of the company. It was all excellent with the limited number of clients, but as the number of distantly located clients surged, the operating costs increased. Trucks were running with partial loads, thus reducing efficiency. The rate of increase in cost surpassed the rate of revenue every time. The cost per mile of transportation was on the rise. The surging fuel prices were adding to the heat. In spite of being one of the first choices for clients, the company could not generate good profit margins. If they chose to increase prices, the company would have lost customers to the cheaper unorganized players in the market. It was time to choose between growth and survival. The company could not sustain itself without devising a mechanism to reduce costs. The company would not have sustained itself without devising a mechanism to reduce costs. To sustain in the business, the company had to device a mechanism to reduce costs. Whether to continue operating the conventional way or to transform? Was there a logistics strategy that would have improved transportation efficiency and reduced the costs for the company? Complexity academic level The case study is suitable for teaching post-graduate management courses in operations and logistics, supply chain management and supply chain analytics, as well as entrepreneurship-related courses. Supplementary material Teaching notes are available for educators only. Subject code CCS 9: Operations and logistics.

The relationships between Risk Factors and the changes of Histopathological of Tissue Colon Cancer in Iraq Patients

The transformation of an ordinary cell into a cancerous one could be a dynamic process which often involves the approval of oncogenes as well as deactivation of tumor suppressor properties (alterations). Most changes are emptied by cellular genome dauntlessness and repair components. In any case, many genetic changes give cells an advancement advantage and unused capacities, driving to their neoplastic alter. As other cancers, like melanoma, sarcoma, and lymphoma, could affect the colon, colon cancer, also known as colon carcinoma, affects the epithelium of colon. The uncontrolled proliferation regarding colorectal epithelial cells might be a hallmark of colorectal cancer (CRC). The multistep carcinogenesis hypothesis states that pigment cells go through a sequence of atomic alterations before they become totally dangerous cells. The inactivation related to the Adenomatous polyposis coli (APC) signaling pathway is the most frequent hereditary cause of activation. The pathology of damage includes oncogene changes, tumor suppressor qualities, and probably many signaling pathways, which put cancers at risk of metastasis. In advanced nations, CRC has a high disease-specific mortality rate and impacts over a million individuals annually. Worldwide, CRC ranks 3 rd in terms of the incidence in both women and men. Africa and Central and South Asia have experienced the biggest drops in CRC, whereas New Zealand, Australia, North America, and Europe have experienced highest change rates.

An analytical method for sizing energy storage in microgrid systems to maximize renewable consumption and minimize unused storage capacity

This paper presents a novel analytical method to optimally size energy storage in microgrid systems. The method has fast calculation speeds, calculates the exact optimal, and handles non-linear models. The method first constructs a temporal storage profile of stored energy, based on how storage charges and discharges in response to renewable generation and load demand. The storage is sized according to the largest cumulative charge or discharge in the profile. In essence, the storage profile represents how storage is utilized within a given system, and the method sizes optimal storage to maximize that profile, such that storage utilization is maximized, and unutilized or wasted storage is eliminated. Maximizing storage utilization also maximizes renewable consumption and minimizes load shedding, as storage utilization is the temporal transfer of energy from renewable generation to load demand. The proposed method is extended iteratively to account for storage’s energy limits, power limits, and energy leakage. Two solar–battery case studies demonstrate the method. The first study shows that optimally sized storage does not have wasted capacity due to over-sizing, nor cause energy deficits due to under-sizing. The second case study shows increasing the storage size reduces the marginal increase in energy provided by storage, indicating diminishing returns. The diminishing return thresholds are defined by the largest daily and annual storage designs. The result shows the largest daily design only requires 3% of the annual design’s storage size, but provides 80% of the energy provided by the annual design. The proposed method can be used as a decision support tool for energy analysts, to determine required storage capacity when coupled with known renewable generation and load demand.

Fuel Use Reduction and Economic Savings from Optimization of Road Transportation of Coniferous Roundwood

One of the 10 priorities of the Green New Deal is sustainable transportation. It should be considered in the perspective of long-term ecological and economic sustainability, according to the trend of opportunities for sustainable development. The economic and environmental aspects of transportation related to the harvesting and movement of timber play a special role in the energy cost and their environmental impact per distance of raw material supply. The principles of rational and energy-efficient use of transportation equipment play a key role in the movement of raw timber. These are influenced by the availability of timber resources, limitation of vehicle payloads, reduction of energy consumption expressed in terms of reduction of fuel combustion, or current legal and road regulations for timber transportation. The paper evaluates economic and environmental factors in relation to the demand for fuels necessary for the implementation of road transportation of softwood timber. The aim of this paper was to present the current situation of the use of transportation means in the movement of bulky timber, as well as opportunities to optimize fuel consumption and CO2 emissions, affecting the economic and environmental effects. Previous studies on fuel consumption in the transportation of roundwood indicate irrational use of vehicles. This indicates unused payload capacity increasing energy inputs expressed in fuel consumption. It has been empirically investigated that this is the result of improperly approved transport sets adapted to the material being transported. In addition, it was shown that there is a clear correlation between the vehicle payload utilization rate and economic and environmental factors. The results of this study point to the potential to increase the use of transportation vehicles for timber transportation and reduce fuel combustion and CO2 emissions by 7–20%.