Optimal Benefit Research Articles

Power data analysis and mining technology in smart grid

This study proposes a smart grid model named “GridOptiPredict”, which aims to achieve efficient analysis and processing of power system data through deep fusion of deep learning and graph neural network, so as to improve the intelligent level and overall efficiency of power grid operation. The model integrates three core functions of load forecasting, power grid state sensing and resource optimization into one, forming a closely connected and complementary framework. Through carefully designed experimental scheme, the practical value and effectiveness of “Grid OptiPredict” model are fully verified from three aspects: accuracy of load forecasting, sensitivity of power grid state sensing and efficiency of resource allocation strategy. Experimental results show that the model has significant advantages in prediction accuracy, model stability and robustness, resource optimization, security, information security, social and economic benefits and user experience.

Learning-based Pareto-optimum routing of ships incorporating uncertain meteorological and oceanographic forecasts

In modern shipping logistics, multi-objective ship route planning has attracted considerable attention in both academia and industry, with a primary focus on energy conservation and emission reduction. The core challenges in this field involve determining the optimal route and sailing speed for a given voyage under complex and variable meteorological and oceanographic conditions. Typically, the objectives revolve around optimizing fuel consumption, carbon emissions, duration time, energy efficiency, and other relevant factors. However, in the multi-objective route planning problem involving variable routes and speeds, the extensive solution space contains a substantial number of unevenly distributed feasible samples. Traditional heuristic optimization techniques, such as multi-objective evolutionary algorithms, which serve as the core component of optimization programs, suffer from inefficiencies in exploring the solution space. Consequently, these algorithms may tend to converge toward local optima during population iteration, resulting in a solution set characterized by sub-optimal convergence and limited diversity. This ultimately undermines the potential benefits of routing optimization. To address such challenging problem in route planning tasks, we propose a self-adaptive intelligent learning network aiming at capturing the potential evolutionary characteristics during population iteration, in order to achieve high-efficiency directed optimization of individuals. Additionally, an uncertainty-driven module is developed by incorporating ensemble forecasts of meteorological and oceanographic variables to form the Pareto frontier with more reliable solutions. Finally, the overall framework of the proposed learning-based multi-objective evolutionary algorithm is meticulously designed and validated through comprehensive analyses. Optimization results demonstrate its superiority in generating routing plans that effectively minimize costs, reduce emissions, and mitigate risks.

Enabling Precision Agriculture through a Web-Based Fertilization Management System for Nawungan Selopamioro Fruit Orchards

Precision Agriculture (PA) is an integrated farming system based on information and technology for managing agriculture to identify, analyze, and manage spatial and temporal diversity information in specific locations to obtain optimum and sustainable benefits while minimizing unwanted environmental impacts. Fertilization is one of the crucial phases in agricultural production process considering technical cultivation aspects, costs, and environmental impacts. The current fertilization process at Kebun Buah Nawungan Selopamioro (KBNS) is still conventional, so there is no standard rule in determining the fertilization dose. Therefore, a PA approach is needed to provide suitable fertilizer doses for agricultural production needs. This objective of this study was to develop of a web-based fertilizer management system, integrating with orchard management to enhance accessibility and decision-making. The system calculates fertilizer requirements by analyzing soil nutrient availability (N, P, K), cultivation area, crop type and age, and available fertilizer types. The development followed the waterfall methodology, encompassing stages from requirement analysis to system maintenance. The outcome is a web application that manages land assets, administrative activities, and fertilizer needs tailored to specific land blocks, crop characteristics, and nutrient inventories. Subsequent validation against field conditions ensures the accuracy of its recommendations. Although comprehensive testing confirmed a 100% success rate in functionality, the system currently operates within a limited scope of variables. Future enhancements are planned to incorporate broader agronomic factors, such as soil pH and texture, to augment the system's precision. Despite its limitations, this system represents a significant technological advance in precision agriculture, promising to improve fertilizer application efficiency and support sustainable farming practices.

Crystallographic anisotropy-dependent mechanochemical removal of GaAs: Nanoasperity experiments and atomistic simulations

In this paper, the nanoasperity wear tests on GaAs surfaces with different crystallographic orientations against SiO2 microsphere were performed using AFM. The removal behavior characterized by in-situ AFM imaging significantly relies on crystallographic anisotropy (111 > 110 > 100). The atomic structure of worn area characterized by HRTEM shows perfect crystal lattice, demonstrating the dominate role of the interfacial mechanochemical reactions during the material removal of GaAs. DFT calculations were conducted and the results reveal that the charge re-distribution behavior at the SiO2/GaAs interface governs the mechanochemical reactions, essentially leading to the crystallographic anisotropy dependence. This study not only enriches the mechanochemical reaction mechanism, but also benefits for the CMP optimization for GaAs.

Bioactive Compound Diversity in a Wide Panel of Sweet Potato (Ipomoea batatas L.) Cultivars: A Resource for Nutritional Food Development.

This study provides an overview of the composition of the raw root flesh of a panel of 22 sweet potato (Ipomoea batatas L.) cultivars, with a focus on bioactive compounds. The large diversity of the proximate and phytochemical compositions observed between cultivars and within and between different flesh colors pointed out the importance of composition analysis and not only color choice for the design of foods with nutritional benefits. The nutritional composition (starch, protein, total dietary fibers) and bioactive compound composition of 22 cultivars from Reunion Island, maintained in the Vatel Biological Resource Center, were investigated. Orange and purple cultivars stood out from white and yellow cultivars for their higher nutritional composition. Purple sweet potatoes were notable for their high contents of anthocyanins (55.7 to 143.4 mg/g dry weight (DW)) and phenolic compounds, in particular chlorogenic acid and ferulic acid, contributing to antioxidant activities, as well as their fiber content (14.1 ± 2.1% DW). Orange cultivars were rich in β-carotene (47.2 ± 0.7 mg/100 g DW) and to a lesser extent α-carotene (4.8 ± 1.2 mg/100 g DW). In contrast, certain white cultivars demonstrated suboptimal nutritional properties, rendering them less relevant even for applications where the lack of coloration in food is desired. Those characteristics enable the selection of sweet potato varieties to design food products ensuring optimal nutritional benefits and culinary versatility.

Two-stage multi-objective distributionally robust operation optimization and benefits equalization of an off-grid type electric-hydrogen-ammonia-methanol coupling system

As the proportion of renewable energy has increased significantly, electric-hydrogen coupling technology has emerged as a pivotal strategy for optimizing the utilization of renewable energy resources. In particular, within the power and chemical sectors, the preparation of ammonia and methanol using electric-hydrogen coupling technology has emerged as the two principal avenues for the utilization of hydrogen energy. However, as a nascent technology, the preparation of ammonia and methanol by electric-hydrogen coupling is confronted with a multitude of challenges, including the considerable uncertainty surrounding the generation of renewable energy, the dearth of economic benefits, and the need to ensure a fair allocation of benefits among the various stakeholders. To enhance the risk resistance of the electric-hydrogen-ammonia-methanol coupling system (EHAMCS), improve the economic benefits, ensure the environmentality and stability of the system, and realize the fair distribution of benefits among the energy participants, this paper constructs a multi-objective distributionally robust optimization (DRO) and multi-dimensional benefits equilibrium model for the EHAMCS and performs a numerical analysis with an off-grid type EHAMCS as an example. The results demonstrate that: 1) The cooperative operation of the EHAMCS offers notable economic advantages. When compared with only pursuing economic benefits, under multi-objective optimization, the economic benefits of the coupling system can be reduced by 1.49 %, but the carbon emission can be reduced by 10.06 %, and the instability is reduced by 0.02, which can create derivative benefits. 2) The two-stage DRO model is an effective means of addressing the impact of system operation uncertainty and the affine strategy enables the rapid adjustment of the day-ahead dispatching plan, thereby balancing the power deviation. 3) The multi-dimensional factor benefit balancing scheme is more conducive to the participation of clean energy and downstream ammonia and methanol energy subsystems in cooperative operation and promotes the consumption of clean energy while improving the energy conversion value of the EHAMCS to increase economic benefits. 4) EHAMCS operators should adjust their operational strategies in time with market and policy signals, and select historical samples reasonably, so as to realize the balance of the DRO model in terms of economy, robustness, and practicality. The effectiveness of the model and the superiority of the EHAMCS are thus verified.

Sustainable energy transition: A steam system optimization case study from a Moroccan food industry

Industrial steam systems account for approximately 30 % of energy use in the manufacturing industry worldwide. In the context of energy transition, improving the energy efficiency of these systems is crucial, as it can significantly reduce energy losses, costs, and greenhouse gas (GHG) emissions. This study presents a comprehensive analysis of the steam system in a Moroccan agri-food plant, aiming to identify and quantify energy optimization opportunities. Initially, the Steam System Scoping Tool (SSST) benchmark revealed a score of 42.4 %, highlighting key areas for improvement. The study proceeded by diagnosing and modeling the baseline steam system, identifying major energy losses based on thermodynamic equations and Manufacturing Energy Assessment Software for Utility Reduction (MEASUR). Our study distinctively employs a systems-based approach, proposing eight energy-saving measures that holistically address all aspects of the steam system —generation, distribution, end-use, and recovery—rather than examining each component in isolation. These measures include optimizing boiler combustion, repairing insulation and leaks, reducing idle operations, and enhancing heat recovery through a feedwater economizer. Implementing these measures is projected to achieve annual energy savings of 5096 GJ, reduce CO2 emissions by 319 tons, and save $93,764, representing a 53 % reduction in the plant's thermal bill. This significant cost-saving potential should inspire optimism about the financial benefits of energy optimization, with payback periods ranging from immediate to a few months. This research marks a pioneering effort in Morocco's industrial sector, offering a replicable model that aligns with global sustainable development goals (SDGs) by reducing energy losses and enhancing production performance.

Exploring Alternative Behavioural Trajectories in Entrepreneurship Education in Universities

This Paper explored alternative behavioural trajectories navigable to address entrepreneurship education issues in Nigeria's public universities. Entrepreneurship education's current viability and capacity utilization have not gained the impetus to drive students’ practical application development and add significant value to economic development. This work relied on ethnography using the participant observer method to get relevant contextual specifics to give insights on traversable alternatives that culminate in the much-desired economic development and growth of individuals and the nation at large. It was concluded that behavioural alterations that gravitate towards trajectories that deviate significantly from the dismal state of affairs obtainable in the current pedagogy are the panacea to the apparent quagmire. It was suggested amongst others that driving emotional attachment, improvisation, and the use of alternative sources of funding are avenues of attaining optimal level benefits of entrepreneurship education. This paper contributes to the body of knowledge of entrepreneurship development and knowledge efficiency.

Development of a Progressive Web Application for Optimizing Solid Waste Management in Urban Contexts: a Case Study in the Coelhos Neighborhood, Recife

Objective: Develop a Progressive Web Application (PWA) to optimize solid waste management in the Coelhos neighborhood in Recife, promoting sustainable practices. Literature Review: The study is based on emerging technologies for waste management, such as IoT and optimization algorithms, addressing challenges and benefits. Method: It includes participatory diagnosis, data collection, and development of the "Limpa+Coelhos" application, integrating technologies like Angular and Google Maps to facilitate waste collection. Results and Discussion: The application significantly increased collection efficiency and community awareness, improving interaction between users and waste management services. Research Implications: The study highlights the potential of PWAs to promote more sustainable and interactive waste management practices in urban contexts. Originality/Value: The research demonstrates the effectiveness of PWAs in improving solid waste management, contributing to the development of innovative technological solutions in urban areas.

Perioperative Nutritional, Functional, and Bone Health Optimization in Spine Surgery: A National Investigation of Spine Surgeons' Perceptions and Practices.

While perioperative nutritional, functional, and bone health status optimization in spine surgery is supported with ample evidence, the implementation and surgeon perception regarding such efforts in clinical practice remain largely unexplored. This study sought to assess the current perception of spine surgeons and implementation regarding the nutritional, functional status, and bone health perioperative optimization. An anonymous 30-question survey was distributed to orthopaedic spine fellowship and neurosurgery program directors identified through the North American Spine Society and American Association of Neurological Surgeons contact databases. The questionnaire was completed by 51 surgeon survey respondents. Among those, 62% reported no current formal nutritional optimization protocols with 14% not recommending an optimization plan, despite only 10% doubting benefits of nutritional optimization. While 5% of respondents perceived functional status optimization as nonbeneficial, 68% of respondents reported no protocol in place and 46% noted a functional status assessment relying on patient dependency. Among the respondents, 85% routinely ordered DEXA scan if there was suspicion of osteoporosis and 85% usually rescheduled surgery if bone health optimization goals were not achieved while 6% reported being suspicious of benefit from such interventions. While most responding spine surgeons believe in the benefit of perioperative nutritional and functional optimization, logistical and patient compliance challenges were noted as critical barriers toward optimization. Understanding surgeon perception and current practices may guide future efforts toward advancement of optimization protocols.

Role of Platelet-Rich Plasma in the Management of Non-obstructive Azoospermia.

Non-obstructive azoospermia (NOA) is a common cause of infertility in males, which is characterized by the absence of sperm in the ejaculate, resulting from impaired spermatogenesis. The primary therapeutic approaches for the management of NOA include testicular sperm extraction, varicocelectomy in case of clinical varicoceles, and hormonal manipulation. While traditional treatments are found to have a limited role in the management of NOA, recent studies have explored the potential of platelet-rich plasma (PRP) as a safer and promising therapeutic option. Autologous PRP preparations are derived from the patient's blood and comprise growth factors and cytokines, promoting tissue repair and regeneration. PRP has a wide range of applications in the medical field, including managing infertility in males and females. This literature review aimed to evaluate the existing evidence on the efficacy and safety of PRP in the management of NOA. After a thorough review of relevant data from observational and experimental studies, the findings of this study suggested that PRP may positively influence spermatogenesis, sperm quality, DNA integrity, and sperm retrieval during assisted reproductive procedures. Further research is needed to establish the optimal PRP preparation, administration method, and long-term benefits. The newer studies shall include a diverse patient population and employ long-term follow-up to assess the durability of any positive effects of PRP treatment. The growing body of evidence regarding the therapeutic potential for NOA in humans offers greater opportunities for men seeking fertility treatment, informing clinical practice, and optimizing the use of PRP.

Impact Of International Trade On Regional Economic Growth

This study aims to analyze the impact of international trade on regional economic growth through literature studies. International trade is one of the main drivers of economic growth in the era of globalization. Despite a significant increase in the volume of global trade, the distribution of benefits is not always evenly distributed across regions. Some regions with adequate infrastructure access and supportive economic policies experience rapid economic growth, while other less developed regions face limitations in taking advantage of international trade opportunities. This study shows that international trade contributes significantly to increasing Gross Regional Domestic Product (GRDP), investment, and job creation, although these impacts depend on the readiness of infrastructure and the competitiveness of each region. Factors such as government policies and access to global markets also play a role in influencing the benefits obtained. This study recommends policies for infrastructure development and strengthening the competitiveness of local products to ensure that all regions can feel the optimal benefits of international trade. The results of this study provide direction for the government in formulating policies that encourage inclusive and sustainable economic growth at the regional level.

Elastic contribution of polymeric fluids augments salinity-gradient-induced electric potential across a microfluidic channel

HypothesisHarnessing electrical energy from salinity gradients, particularly for powering micro and nanoscale devices, has become a focal point of recent research attention, due to its renewable and biocompatible nature. Much of the reported research in that direction revolves around optimizing the membrane architecture and the charge distribution to maximize the induced electric potential, with no particular emphasis on the fluid rheology. However, many of the modern miniature systems, typically the bio-inspired ones, concern fluids with complex rheological characteristics, where the results for Newtonian solvents may not trivially apply. Here, we hypothesize that the interplay between interfacial electro-mechanics and the fluid rheology can influence the effectiveness of salinity-gradient-modulated electrokinetics significantly – an aspect that has largely remained overlooked. Theory and experimentsHere we report the first experiments supplemented by a theoretical model that unveil how that the addition of polymers in a solvent modulates the salinity gradient – induced electric potential in a microfluidic channel. Our theoretical framework considers the simplified Phan-Thien Tanner (sPTT) constitutive model, which represents the viscoelastic characteristics of fluids. Experiments were conducted with combined pressure driven and salinity gradient driven flow through microchannel involving dilute solutions of polyethylene oxide (PEO) of different molecular weights and concentrations to successfully validate the theoretical approach. FindingsOur findings indicate that the induced electrical potential increased non-linearly with the saline concentration ratio across the microchannel, as compared traditional linear response. Our results demonstrate how the elasticity of fluid may enable realizing an optimal benefit to this effect, by arresting the viscous resistance and uplifting the elastic response via utilizing polymeric inclusions of high relaxation times. These results provide specific insights on preferential windows of augmenting the induced streaming potential by harnessing the viscoelastic nature of the solution and the imposed salt concentration, bearing critical implications in miniature energy harvesting and desalination technology.

Court-ordered forensic psychiatry treatment in prison: determinants of outcome and risk mitigation.

Court-ordered forensic psychiatry treatments (COT) are specifically designed to reduce the risk of violence in mentally disordered offenders. Given their high costs and ethical issues, mental health professionals need admission criteria to be able to select those candidates with optimal benefit. This study analyses offender-related and treatment-related determinants of COT outcome and risk mitigation. This two-year longitudinal study assessed the evolution of 117 adult offenders admitted to a specialized medium-security forensic psychiatry clinic. Treatment outcome included court-ordered discharge locations and the Historical Clinical Risk Management (HCR) score evolution. Treatment progress was assessed every six months across five time-points including measures of protective factors, work rehabilitation and security. Outcome determinants included psychiatric diagnosis and type of offence. Discharge locations are predicted by pre-treatment risk level. Lower HCR scores are associated with discharge into low-security psychiatry wards independently of the psychiatric diagnosis. Risk reduction follows diagnosis-specific and offense-related patterns and reveals that mentally disordered offenders with Cluster B personality disorders or those sentenced for drug crimes are significantly less prone to benefit from COT. Our findings indicate that criminological characteristics at baseline as well as diagnosis of personality disorders are the main determinants of treatment outcome in our care setting. Inmates with concomitant higher violence risk at baseline and presence of Cluster B personality disorders might benefit the least from court-ordered forensic inpatient psychiatric care in prison.

Tuned mass dampers ‐ evaluation of the effect on two real footbridges

AbstractPedestrian comfort, subtle design, minimizing the number of fixed supports of the footbridge or material saving. These are the key arguments for integrating tuned mass dampers into the bridge project. The goal is to protect people and structure from vibrations and damage. The following paper presents findings from the design, production and tuning of mass dampers, their optimization possibilities and benefits for bridge engineering. The validity of damper design was verified on two footbridges in the Czech Republic and Slovakia. It concerns the footbridge over the Svitava River in Bílovice nad Svitavou and the footbridge over the high‐speed road in Banská Bystrica. Dynamic tests including measurement were carried out on both bridges before and after the installation of the dampers. The dynamic monitoring of the compliance of modal parameters was conducted using operational modal analysis (OMA). The evaluation of the dynamic tests also includes the response to pedestrian effects (comfort criteria) and the determination of the logarithmic decrement of the damping.

Indole-3-propionic acid enhances growth performance and reduces diarrhea via modulating redox status and intestinal inflammation in weaned piglets

Indole-3-propionic acid (IPA) has anti-inflammatory properties, which can be beneficial for weaned piglets with underdeveloped immune systems. The study explores the impact of IPA supplementation on growth performance, oxidative stress, and inflammation response in weaned piglets. In experiment (Exp.) 1, ninety weaned piglets were divided into six groups (five replicates per group, three pigs per replicate), with each group receiving a basal diet with varying amounts of IPA (0, 50, 100, 200, 400, or 600 mg/kg) for 42 d. Piglets fed the diets with 50, 100, and 200 mg/kg of IPA exhibited reduced feed conversion ratios (F: G) compared to the control piglets (P = 0.035). Notably, 50 and 100 mg/kg IPA treatments significantly reduced diarrhea incidence and serum interleukin (IL)-6 content (P < 0.05). Conversely, a high dosage of 600 mg/kg IPA led to increased serum contents of tumor necrosis factor (TNF)-α, and IL-6 (P < 0.05). Optimal antioxidant benefits were observed at 100 mg/kg IPA supplementation, which significantly reduced malondialdehyde levels while enhancing serum total antioxidant capacity and total superoxide dismutase activity on d 14 (P < 0.05). Exp. 2 investigated the effects of IPA on lipopolysaccharide (LPS) challenge in weaned piglets. The study consisted of 32 weaned piglets allocated into 4 groups, with 8 replicates per group and 1 piglet per replicate: a control group, a LPS challenge group, a LPS challenge group supplemented with 100 mg/kg IPA, and a group supplemented with 100 mg/kg IPA alone. Upon administration of LPS or saline injection, the results indicated that dietary IPA supplementation in challenged piglets enhanced villus height: crypt depth, modulated IL-8 and IL-22 mRNA relative expression, and increased the tight junction protein claudin-1 mRNA relative expression in the intestinal mucosa (P < 0.05). These findings suggest that dietary supplementation of IPA at specific concentrations significantly improves growth performance, reduces diarrhea incidence, and mitigates inflammation and oxidative stress in weaned piglets. It may be concluded that incorporating IPA into the diet of weaned piglets can effectively improve their health and development.

A carbon integrated energy pricing strategy based on non-cooperative game for energy hub in seaport energy system

Seaports are significant energy consumers and sources of carbon emissions within the maritime industry. To address this problem, an energy hub (EH) can be established as an intensive energy interconnection center. This paper proposes a carbon emission flow (CEF) model based on the energy hub in seaport, which monitors the carbon emissions generated by the internal energy conversion unit operating within the hub. Additionally, a carbon integrated energy pricing strategy based on non-cooperative game theory is proposed. Based on duality theory and gradient descent method, an iterative algorithm is designed to seek the global optimal solution satisfying the Nash equilibrium point. The aim of the strategy is to encourage seaport energy consumers to adjust their energy consumption strategy according to the optimal benefits and reduce carbon emissions. A comparative study of three different strategy cases are conducted to evaluate the effectiveness of the proposed strategy. Numerical simulation results show the reduction of the total energy consumption and carbon emissions of the system, which is conducive to realizing the low-carbon operation of the seaport energy system.

Diagnostic laparoscopy for pre-operative selection of patients with known peritoneal carcinomatosis for CRS-HIPEC: A systematic review and meta-analysis

BackgroundPreoperative selection of patients with Peritoneal Carcinomatosis (PC) for Cytoreductive surgery (CRS) with hyperthermic intraperitoneal chemotherapy (HIPEC) is challenging due to associated risks. Diagnostic laparoscopy (DL), an emerging alternative to conventional radiological imaging, has uncertain efficacy. This study aims to evaluate DL's diagnostic performance through a systematic review of available literature. MethodsA comprehensive search of MEDLINE and SCOPUS databases from January 1987 to September 2023 identified studies investigating DL's diagnostic accuracy in selecting PC patients for CRS-HIPEC. Methodological bias assessment and analysis of performance metrics such as positive predictive value (PPV), sensitivity, specificity, and diagnostic odds ratio (DOR) were conducted. Subgroup analyses were performed for primary ovarian cancer studies, and false positive sites were identified. The summary receiver operating characteristic curve (sROC) was plotted to assess overall diagnostic efficacy, with meta-regression conducted to identify sources of heterogeneity across studies. ResultsThis study included 25 studies comprising 3820 patients. Pooled PPV was 93.04 %, with a complication rate of 1.61 %. Pooled sensitivity was 98.26 % and pooled specificity was 83.67 %. The pooled DOR was 139.18, and sROC plot yielded an area under the curve of 0.96. Meta-regression found the ovarian subgroup as a strong source of heterogeneity. Subgroup analysis indicated similar findings in primary ovarian cancer studies, while false positives were commonly observed in the celiac axis, mesentery, ureters and para-aortic lymph nodes. ConclusionDL demonstrates robust diagnostic accuracy in selecting PC patients for CRS-HIPEC, with potential benefits in patient outcomes and resource optimization. Further multicenter investigations are warranted to validate DL's efficacy across diverse primary cancer types.

Reliability–flexibility integrated optimal sizing of second‐life battery energy storage systems in distribution networks

AbstractSecond‐life batteries (SLBs), which are batteries retired from electric vehicles (EVs), can be used as energy storage systems to enhance the performance of distribution networks. Two issues should be addressed particularly for the optimal sizing of SLBs. Compared with fresh batteries, the failure rate of SLBs is relatively high, and timely and preventive replacement is needed. In addition, the flexibility introduced by EVs and installed SLBs should be coordinated to achieve optimal economic benefits. This paper focuses on the efficient utilization of SLBs by highlighting reliability‐flexibility concerns in optimal sizing. The model is formulated as a bi‐level model. On the upper‐level, considering the operational reliability constraints of SLBs, decisions regarding the investment and replacement of SLBs are optimized. Distribution network operations are improved on the lowerlevel, with an effective spatiotemporal flexible dispatch strategy for EVs. Finally, a linearized process for the optimal sizing of SLBs is presented and efficiently implemented. The Sioux Falls network and IEEE 69‐node distribution network are coupled as the test system. According to the simulation results, when the state of health of the SLBs decreased to 70%, the conditions were unreliable. The differences in the optimal SLB size and costs considering reliability and flexibility are highlighted.

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.