In this paper, we present a comprehensive and innovative framework for optimizing planning in power distribution systems. Firstly, we introduce various types of planning involved in power ...distribution systems, and subsequently, we provide a detailed presentation of each planning type. The different types of Power Distribution System Planning (PDSP) can be classified as follows: Asset plan, Network plan, Process plan, Energy plan, Data plan, Facility plan, Economic plan, Regulation plan, and Customer relation plan. These classifications effectively demonstrate the influential factors, conditions, and objectives of PDSP. Furthermore, this paper investigates the management strategies for different PDSP classifications. Within each classification, we list and categorize relevant studies. By utilizing the framework proposed in this paper, readers can gain a comprehensive understanding of PDSP planning measures and make more optimal decisions within power distribution companies. Additionally, this paper identifies research gaps and presents a roadmap for future PDSP studies. Based on the findings of this paper, it is evident that the majority of research in this field has focused on expansion, while process-related studies have received relatively less attention. These findings should be taken into consideration when formulating the future research roadmap.
Introduction
Cerebrovascular diseases are known to cause significant morbidity and mortality to the general population. In patients with cerebrovascular disease, prompt clinical evaluation and ...radiographic interpretation are both essential in optimizing clinical management and in triaging patients for critical and potentially life-saving neurosurgical interventions. With recent advancements in the domains of artificial intelligence (AI) and machine learning (ML), many AI and ML algorithms have been developed to further optimize the diagnosis and subsequent management of cerebrovascular disease. Despite such advances, further studies are needed to substantively evaluate both the diagnostic accuracy and feasibility of these techniques for their application in clinical practice. This review aims to analyze the current use of AI and MI algorithms in the diagnosis of, and clinical decision making for cerebrovascular disease, and to discuss both the feasibility and future applications of utilizing such algorithms.
Methods
We review the use of AI and ML algorithms to assist clinicians in the diagnosis and management of ischemic stroke, hemorrhagic stroke, intracranial aneurysms, and arteriovenous malformations (AVMs). After identifying the most widely used algorithms, we provide a detailed analysis of the accuracy and effectiveness of these algorithms in practice.
Results
The incorporation of AI and ML algorithms for cerebrovascular patients has demonstrated improvements in time to detection of intracranial pathologies such as intracerebral hemorrhage (ICH) and infarcts. For ischemic and hemorrhagic strokes, commercial AI software platforms such as RapidAI and
Viz.
AI have bene implemented into routine clinical practice at many stroke centers to expedite the detection of infarcts and ICH, respectively. Such algorithms and neural networks have also been analyzed for use in prognostication for such cerebrovascular pathologies. These include predicting outcomes for ischemic stroke patients, hematoma expansion, risk of aneurysm rupture, bleeding of AVMs, and in predicting outcomes following interventions such as risk of occlusion for various endovascular devices. Preliminary analyses have yielded promising sensitivities when AI and ML are used in concert with imaging modalities and a multidisciplinary team of health care providers.
Conclusion
The implementation of AI and ML algorithms to supplement clinical practice has conferred a high degree of accuracy, efficiency, and expedited detection in the clinical and radiographic evaluation and management of ischemic and hemorrhagic strokes, AVMs, and aneurysms. Such algorithms have been explored for further purposes of prognostication for these conditions, with promising preliminary results. Further studies should evaluate the longitudinal implementation of such techniques into hospital networks and residency programs to supplement clinical practice, and the extent to which these techniques improve patient care and clinical outcomes in the long-term.
In this paper, the simulation and optimization of a combined supercritical carbon dioxide Brayton cycle, an organic Rankine cycle and multi-effect distillation system driven by solar energy have been ...applied for power and freshwater generation. In this cycle, the solar collector, the central receiver reflected the sun’s light by heliostats, enters the storage system and then enters the fluid stream according to the amount of heat required to initiate the cycle. The working fluid of solar receiver is a mixture of the 60% NaNO3 and 40% KNO3, supercritical carbon dioxide is working fluid of the Brayton cycle and R600 is the working fluid of the organic Rankine cycle. The innovation of this article is using power and fresh water cycle without fuel consumption (with solar system and storage tanks). The simulation of this combined cycle was carried out by engineering equation solver software and energy and exergy efficiency changes in terms of different parameters are obtained. Then, a multi objective optimization of this system considering exergy efficiency and cost of system as objective functions is performed by genetic algorithm in Matlab software. Decision variables of the whole cycles are including Compressor inlet temperature, Turbine inlet temperature, Number of MED effect, The temperature of the water fed the desalination, Evaporator pinch point, Mass flow (Critical Carbon Dioxide), Turbine inlet pressure, Compressor inlet pressure and Pressure drop. The two objective functions optimization including exergy and economic parameters of this cycle is carried out for achieving reduction of electricity generation cost and increase of the exergy efficiency. The results of this optimization showed, the maximum exergy efficiency of this combined system is 61.78% and the minimum cost of electricity production is 0.2617 $/kWh. In this regard, the multiple effect distillation system produces 530.9 KgS freshwater in 15 stages.
Spare transformers (STs) are required at every distribution substation to guarantee reliability in those substations. In the absence of an ST in a substation, an error in a working transformer may ...disrupt the load connected to it. On the other hand, the presence of an ST at every substation is costly. Hence, the present paper will address the location of STs. Three methods are used for this purpose: the Euclidean distance, the square of the Euclidean distance, and the orthogonal distance. The objective is to find a location to minimize the determined total cost function. Furthermore, the storage locations of spare and mobile transformers are assumed to be the same but can also be considered different. In determining the optimal location of STs, factors such as transformer aging level, preventive repairs, random errors, and aging-induced errors will be deemed to enable modeling and managing the uncertainty.
Optimizing aging assets replacement in power systems Shaghaghi, Aidin; Taghitahooneh, Mohammad; Dashti, Reza
International journal of system assurance engineering and management,
03/2024, Letnik:
15, Številka:
3
Journal Article
Recenzirano
The electrical distribution system comprises various assets with limited lifespans. The operational range of these assets is determined based on influential factors in the electrical distribution ...systems. Additionally, as the age of the assets, their performance becomes compromised and susceptible to disruptions. The major challenges in managing aging assets revolve around cost and cost-effectiveness. Replacing aging assets requires substantial capital investment. Failure to replace these assets leads to significant disruptions in the continuity and quality of power supply, imposing high costs on the electrical distribution system. This article aims to strike a balance between the costs of replacing aging assets and the costs incurred due to asset deterioration in electrical distribution systems to achieve the minimum capital investment cost. The main advantage of the proposed algorithm is its comprehensive consideration of all factors influencing the cost–benefit trade-off of aging assets. This algorithm determines the optimal time for replacing aging assets to achieve the most economical state possible. The investigations in this study reveal that the replacement time for aging assets varies between 39 to 42 years, depending on the different conditions examined.
With the diminution of fossil fuel sources and the substantial importance of CO2 and other greenhouse gasses emission, the usage of enhanced thermal power plants coupled with renewable energies, such ...as solar, becomes more vital and promising. This paper proposes a novel configuration of the power generation system, featuring a solar collector to supply the heat for a two-stage steam turbine with inter heating and an Organic Rankine cycle as bottoming cycle of the steam turbine. The proposed system has been simulated and optimized using the particle swarm optimization algorithm. A heat storage system with NaNO3 and KNO3 in 3:2 ratios is used to store the extra heat in daylight to extend the operation at nighttime. For achieving the best working conditions for the proposed hybrid system, we employed a multi-objective optimization to maximizing the exergy efficiency while minimizing the levelized cost of electricity production. The simulation was performed using the Engineering Equation Solver (EES), and MATLAB software which is used for receiving the simulation results from EES and optimizing the key design parameters of the system using the PSO algorithm to select the best design variables. The optimization showed that at the optimum point, the exergy efficiency of the system and the levelized cost of electricity production reach to be 63.89% and 0.1529 USD/kWh, respectively. Results also showed that in the proposed system, the solar collector is the most important source of exergy destruction, in which more than 59% of the total destructed exergy happens in it.
Sensitivity analysis also revealed that decreasing the turbine's inlet temperature will increase the production cost of electricity due to lower efficiency. Also, any changes (deviation from design point) in the back pressure of the low-pressure turbine will decrease the efficiency; while the production cost of electricity increases if this back pressure increases and vice versa.
•Combining steam and organic Rankine power cycles with a solar collector.•Optimizing combined cycle in three scenarios.•Two-objective optimization with exergy and levelized cost of electricity.
The rational failure rate estimation has always been a great challenge in electric power distribution companies' regulatory. To prevent risk creation for companies and guarantee their encouragement ...to improve the distribution system's reliability, companies should calculate the failure rate by approximation and low error. Several factors influence the failure rate, including asset life, geographical factors, clash culture with installations, urban planning, etc. On the other hand, the history of investing in this system can also cause high exhaustion in assets. It is virtually impossible to consider all these factors and achieve a rational failure rate. Also, insufficient investment in the past years of electricity distribution companies is an important factor in asset aging and determining the failure rate. On the other hand, the company's investment trend is affected by the accepted failure rate of the regulator for each distribution company. In this paper, using the investment process and the total worth of assets of power distribution companies in each year, a model is presented to estimate the failure rate of the network. The failure rate calculated with this model can divide the budget between power distribution companies by the regulator and determine the rewards and penalties.
Introduction Chronic subdural hematomas are a common neurovascular condition that involve the gradual and continual exudation of fluid from a compromised cell layer lining the dura 1. Embolization of ...the middle meningeal artery (MMAE) results in lower recurrence rates as compared to traditional surgical burr hole evacuation 2‐4. Liquid embolic agents such as cyanoacrylates or ethylene vinyl alcohol copolymers can potentially provide a distinct advantage with greater distal penetration resulting in faster hematoma resolution 5. Their inherent radiopacity (after pre‐mixing) also allows for accurate visualization and control over embolization. The hypothesis of this study is that liquid embolic surface area would correlate with more effective cSDH volume resolution in patients. Methods Under IRB approval, we retrospectively analyzed non‐contrast head CTs and immediate post‐embolization flat‐detector CTs from 45 patients who underwent first‐line MMAE with a liquid embolic. Patients who received any neurosurgical intervention were excluded. 3D‐Slicer was used to segment and calculate hematoma volumes pre‐embolization, as well as at 1‐month, 3‐months, and 6‐months post‐embolization. The flat‐detector CT scans were also segmented to calculate the surface area of the liquid embolic. Results There was significant reduction in hematoma volume at 1‐, 3‐ and 6‐months with respect to the preoperative cSDH volume (Figure A, Pre: pre‐treatment, mo: month). The liquid embolic surface area significantly correlated with (a) pre‐embolization hematoma volume (R2 = 0.27, p = 0.0002, n = 45), (b) the reduction in volume at 1‐month post‐embolization (R2 = 0.16, p = 0.007, n = 41), (c) volume reduction at 3‐months post‐embolization (R2 = 0.29, p = 0.0015, n = 32), (d) hematoma volume resorption rate (cc/day) calculated at 1‐month post‐embolization (R2 = 0.16, p = 0.011, n = 39), and (e) hematoma volume resorption rate calculated at 3‐months post‐embolization (R2 = 0.34, p = 0.0003, n = 34, Figure B). The liquid embolic surface area was not correlated to the volume reduction at 6‐months (p = 0.3, n = 26). Conclusions The luminal surface area of MMA vasculature embolized with liquid embolics may be correlated to the reduction in cSDH volumes. The liquid embolic segmentation method used here needs further refinement to improve accuracy. Additional data sets are required to confirm the correlations reported here.
Nowadays, optimizing wind farm configurations is one of the biggest concerns for energy communities. The ongoing investigations have so far helped increasing power generation and reducing ...corresponding costs. The primary objective of this study is to optimize a wind farm layout in Manjil, Iran. The optimization procedure aims to find the optimal arrangement of this wind farm and the best values for the hubs of its wind turbines. By considering wind regimes and geographic data of the considered area, and using the Jensen’s method, the wind turbine wake effect of the proposed configuration is simulated. The objective function in the optimization problem is set in such a way to find the optimal arrangement of the wind turbines as well as electricity generation costs, based on the Mossetti cost function, by implementing the particle swarm optimization (PSO) algorithm. The results reveal that optimizing the given wind farm leads to a 10.75% increase in power generation capacity and a 9.42% reduction in its corresponding cost.
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