System Cost Research Articles

The role of hydrogen as long-duration energy storage and as an international energy carrier for electricity sector decarbonization

With countries and economies around the globe increasingly relying on non-dispatchable variable renewable energy (VRE), the need for effective energy storage and international carriers of low-carbon energy has intensified. This study delves into hydrogen’s prospective, multifaceted contribution to decarbonizing the electricity sector, with emphasis on its utilization as a scalable technology for long-duration energy storage and as an international energy carrier. Using Japan as a case study, based on its ambitious national hydrogen strategy and plans to import liquefied hydrogen as a low-carbon fuel source, we employ advanced models encompassing capacity expansion and hourly dispatch. We explore diverse policy scenarios to unravel the timing, quantity, and operational intricacies of hydrogen deployment within a power system. Our findings highlight the essential role of hydrogen in providing a reliable power supply by balancing mismatches in VRE generation and load over several weeks and months and reducing the costs of achieving a zero-emission power system. The study recommends prioritizing domestically produced hydrogen, leveraging renewables for cost reduction, and strategically employing imported hydrogen as a risk hedge against potential spikes in battery storage and renewable energy costs. Furthermore, the strategic incorporation of hydrogen mitigates system costs and enhances energy self-sufficiency, informing policy design and investment strategies aligned with the dynamic global energy landscape.

Robust optimization dispatch for PV rich power systems considering demand response and energy storage systems

In recent years, the ever-rising penetration of distributed photovoltaics (PV) power has presented substantial challenges in power system dispatch due to its inherent randomness and unpredictability. To bridge this gap, this paper proposes a two-stage robust optimization method for power system security dispatch considering traditional generators as well as flexible resources, such as load demand response and energy storage systems. Specifically, a price-based demand response model is established to optimize the system’s load curve during a day. On this basis, a two-stage optimization problem for day-ahead and intra-day power system dispatch model is proposed. The dispatch objective is to minimize the overall cost in worst-case scenarios through properly scheduling unit commitment (UC) as well as flexible resources in each dispatch interval. Column and constraint generation (C&CG) algorithm is adopted for problem solving. The effectiveness of the proposed method is validated by case studies based on a modified 6-node system and a 24-node system. Simulation results indicate that through appropriately scheduling the energy storage system and load demand response, the proposed dispatch method can significantly reduce the total operation cost of a PV rich power system, which in turn facilitates the integration of PV power.

Demonstrating the use of population level data to investigate trends in the rate, radiation dose and cost of Computed Tomography across clinical groups: Are there any areas of concern?

Increases in computed tomography (CT) use may not always reflect clinical need or improve outcomes. This study aimed to demonstrate how population level data can be used to identify variations in care between patient groups, by analysing system-level changes in CT use around the diagnosis of new conditions. Retrospective repeated cross-sectional observational study using West Australian linked administrative records, including 504,723 adults diagnosed with different conditions in 2006, 2012 and 2015. For 90 days pre/post diagnosis, CT use (any and 2+ scans), effective dose (mSv), lifetime attributable risk (LAR) of cancer incidence and mortality from CT, and costs were assessed. CT use increased from 209.4 per 1000 new diagnoses in 2006 to 258.0 in 2015; increases were observed for all conditions except neoplasms. Healthcare system costs increased for all conditions but neoplasms and mental disorders. Effective dose increased substantially for respiratory (+2.5 mSv, +23.1%, P < 0.001) and circulatory conditions (+2.1 mSv, +15.4%, P < 0.001). The LAR of cancer incidence and mortality from CT increased for endocrine (incidence +23.4%, mortality +18.0%) and respiratory disorders (+21.7%, +23.3%). Mortality LAR increased for circulatory (+12.1%) and nervous system (+11.0%) disorders. The LAR of cancer incidence and mortality reduced for musculoskeletal system disorders, despite an increase in repeated CT in this group. Use and costs increased for most conditions except neoplasms and mental and behavioural disorders. More strategic CT use may have occurred in musculoskeletal conditions, while use and radiation burden increased for respiratory, circulatory and nervous system conditions. Using this high-level approach we flag areas requiring deeper investigation into appropriateness and value of care.

Machine learning enhanced control co-design optimization of an immersion cooled battery thermal management system

The development of lithium-ion battery technology has ensured that battery thermal management systems are an essential component of the battery pack for next-generation energy storage systems. Using dielectric immersion cooling, researchers have demonstrated the ability to attain high heat transfer rates due to the direct contact between cells and the coolant. However, feedback control has not been widely applied to immersion cooling schemes. Furthermore, current research has not considered battery pack plant design when optimizing feedback control. Uncertainties are inherent in the cooling equipment, resulting in temperature and flow rate fluctuations. Hence, it is crucial to systematically consider these uncertainties during cooling system design to improve the performance and reliability of the battery pack. To fill this gap, we established a reliability-based control co-design optimization framework using machine learning for immersion cooled battery packs. We first developed an experimental setup for 21700 battery immersion cooling, and the experiment data were used to build a high-fidelity multiphysics finite element model. The model can precisely represent the electrical and thermal profile of the battery. We then developed surrogate models based on the finite element simulations in order to reduce computational cost. The reliability-based control co-design optimization was employed to find the best plant and control design for the cooling system, in which an outer optimization loop minimized the cooling system cost while an inner loop ensured battery pack reliability. Finally, an optimal cooling system design was obtained and validated, which showed a 90% saving in cooling system energy consumption.

A Power System Study on Hydrogen Conversion Pathways for Gas Turbine Power Plants in Vietnam towards Net Zero Target

The potential applications of hydrogen in various fields of the energy sector are attracting attention worldwide, including the use of hydrogen for decarbonizing power systems. In Vietnam, hydrogen is considered to gradually replace natural gas in power generation to achieve the country’s net zero target by 2050 but there is a lack of research about this new subject. This study focuses on the computational simulation of the evolution of Vietnam’s power system in the period 2030–2050 according to non-conversion and slow, moderate, and accelerated scenarios of natural gas-to-hydrogen conversion at gas turbine power plants. Based on a total power system generation capacity of 150.5 GW in 2030, the modeling results show that the system capacity range of the scenarios is between 568.7 GW and 584.6 GW. In terms of economic performance, the slow conversion scenario has the lowest system cost of USD 1269.0 billion, and the accelerated scenario represents the highest system cost of USD 1283.2 billion. As for CO2 emissions of the power system, the accelerated scenario has the lowest cumulative CO2 emissions in the studied period while the non-conversion appears highest, 2933 and 3212 million tons, respectively. Based on the study results, the possible pathway recommendation of natural gas-to-hydrogen conversion for Vietnam’s power system is proposed.

Optimal design of a combined Power-Heating-Oxygen system for plateau hotel buildings

The Qinghai–Tibet Plateau of China is a region of low atmospheric pressure and oxygen deficiency, with a high heating demand in the winter; therefore, plateau hotel buildings have a demand for comprehensive power-heating-oxygen loads. Solar energy resources are particularly abundant in plateau areas, where a combined multi-energy system based on solar energy can be designed to meet the demand of plateau hotel buildings for multiple loads. However, currently, there is a relative lack of methods for the optimal design and performance evaluation of combined power-heating-oxygen (CPHO) systems. Thus, this study proposes a CPHO system model for plateau hotels, and provides two operation strategies, i.e., power priority and oxygen priority. Taking the minimum total annual cost of the combined system as the optimization objective, an optimized CPHO system model for plateau hotels has been proposed, followed by a case study of a hotel in Qilian County, Qinghai Province. Results showed that: 1) Compared with the conventional combined power-heating (CCPH) system, the CPHO system saw reductions of 0.8% and 1.3% in its total annual cost under the operation strategies of power priority and oxygen priority, respectively. 2) The energy self-consumption (SC) rates of the CCPH system and CPHO system under the operation strategies of power priority and oxygen priority were 84.8%, 64.2%, and 89.8%, respectively; with power self-sufficiency (PSS) rates of 8.3%, 49.9%, and 29.5%, and oxygen self-sufficiency (OSS) rates of 0.0%, 3.2%, and 4.7%, respectively. 3) The total annual cost of the CPHO system was affected slightly by the cost of photovoltaics (PVs) and energy storage devices, and significantly by the price of oxygen. When the price of oxygen was 8 yuan per normal cubic meter(Nm3) or above, the CPHO system was economically efficient under the operation strategy of oxygen priority. When the price of oxygen was 10yuan/Nm3 or above, the system was economically efficient under both operation strategies.

Power system investment optimization to identify carbon neutrality scenarios for Italy

In 2021 the European Commission has proposed the Fit-for-55 policy package, requiring European countries to reduce their CO2 emissions by 55% with respect to 1990 by the year 2030, a first step to achieve carbon neutrality by 2050. Energy system modeling can be a valuable tool for national policymakers to choose the most appropriate technologies to achieve these goals efficiently. This article presents a model of the Italian power system realized employing the open energy modeling framework, Oemof. A linear programming optimization is implemented to evaluate how to minimize system costs at decreasing CO2 emissions in 2030. The developed tool is applied to evaluate different research questions: (i) pathway towards full decarbonization and power self-sufficiency of the electricity sector in Italy, (ii) relevance of flexibility assets in power grids: li-ion batteries, hydrogen storage and transmission lines reinforcement. A 55% CO2 emissions reduction for the actual Italian power sector can be achieved through an increase of 30% of the total annual system cost. Achieving complete decarbonization and self-sufficiency increases significatively annual expenditures. However, cost mitigation is plausible through the integration of sector coupling methodologies or the adoption of a broader spectrum of technological solutions. Flexibility measures appear instrumental for decarbonization, particularly transmission lines, demanding a substantial expansion beyond the stated plans for 2030. This infrastructure is crucial in Italy to facilitate the transfer of renewable electricity generated in the Southern regions to the Northern areas, where a large portion of the electricity demand is located.

Exploring the potential of fractionated spacecraft for enhanced satellite connectivity: Application to the satellite-to-cell case

This paper presents a mission concept designed for satellite-to-cell connectivity through a fractionated CubeSat approach, aiming to fulfill the objectives set by the BlueWalker-3 specifications. The envisioned system consists of 41 CubeSats, each adopting a 16U form factor, to provide dedicated coverage across specified sub-regions, as a reasonable solution. The pre-Phase-A design capitalizes on commercially available components with proven flight heritage, ensuring reliability and cost-efficiency. A genetic algorithm (GA)-based method has been introduced to tackle the complex challenge of designing a large antenna's folding pattern, with an analysis on how this design influences the overall system cost. The study conducts an in-depth analysis of system architecture and operational scenarios. Employing Monte-Carlo simulations, it assesses the Life Cycle Cost (LCC) and the system's resilience to failures, comparing it with similar configurations differing in CubeSat size and number. The results demonstrate that a fractionated approach significantly enhances the mission's scalability and robustness, providing substantial operational flexibility. The comparison highlights a cost-effective configuration within fractionated systems, emphasizing the proposed system's potential advantages. Furthermore, the paper addresses the environmental implications of deploying a fractionated spacecraft constellation, especially concerning astronomical studies. It underscores the CubeSats' minimized brightness and their reduced potential to interfere with telescopic observations, positioning the system as a more compatible option with nighttime sky studies. This consideration is particularly pertinent amidst increasing concerns over the impact of satellite constellations on astronomical research and night sky quality.

A novel high-efficient lithium-ion battery serial formation system scheme based on partial power conversion

The formation of the battery is a crucial step in its manufacturing process. The existing battery formation system suffers from low efficiency and high energy consumption costs due to long energy flow paths, high DC bus line losses, and additional balancing circuit applications. Therefore, a novel high-efficient battery series formation system (BSFS) that combines partial power processing architecture (PPPA) with the modular converter is proposed to address this problem in this article. The PPPA-BSFS includes two-stage isolated sub-modules consisting of Buck-Boost converter and LLC converter with input-serial and output-parallel connection. The isolated converter only processes the serial compensation power, about 1/3 of the full power. Consequently, the converter capacity can be shrunk in the PPPA-BSFS, which can reduce the system's cost and power loss. Furthermore, the paper establishes the steady-state mathematical model and energy efficiency model of PPPA-BSFS based on analyzing the power compensation principle, and the key factors affecting the operational efficiency of PPPA-BSFS are studied. Finally, we construct the simulation models with 10 cells and 120 cells to compare and analyze energy efficiency between PPPA-BSFS and existing battery formation topology under various operating conditions. Our simulation results show that the highest operating efficiency of the PPPA-BSFS proposed is 99.37 % when 120 cells are formed normally, where there is an increment of 5.95 %, 2.36 %, and 0.85 % compared with others, respectively. The high efficiency of the PPPA-BSFS is verified, and the PPPA-BSFS shows great potential for application in battery formation scenarios.

Catalytic activity of Zr/CeO2-Al2O3 catalyst for diesel soot oxidation: synthesis, characterization, and performance evaluation.

Diesel soot is a significant contributor to air pollution. Soot particles present in diesel engine exhaust have a negative impact on the environment and human health. Diesel oxidation catalysts (DOCs) and diesel particulate filters (DPFs) currently use noble metal-based catalysts for soot oxidation. Due to the use of noble metals in the catalyst, the cost of diesel after-treatment systems is steadily rising. As a result, diesel vehicles have become commercially less viable than gasoline vehicles and electronic vehicles. The study focuses on an alternative diesel oxidation catalyst with efficiency similar to that of a noble metal catalyst but with a much lower cost. CeO2-Al2O3 catalysts are known for their oxygen storage capacity and high redox activity, making them suitable for soot oxidation. Adding Zr to these catalysts has been shown to influence their structural and chemical properties, significantly affecting their catalytic behavior. Therefore, the current study is focused on using Zr/CeO2-Al2O3 as a substitute for noble metal-based catalysts to enhance its performance for diesel soot oxidation in automotive exhaust. Evaporation-induced self-assembly (EISA) was used to prepare 1, 3, and 5 weight (wt) % Zr supported mesoporous CeO2-Al2O3 catalysts. Morphological, structural, and physicochemical properties of the synthesized catalysts were examined using Brunauer-Emmett-Teller (BET) absolute isotherm, Scanning electron microscopy (SEM), X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), Temperature programmed reduction (TPR), and Temperature-programmed desorption of ammonia (NH3-TPD). XRD, BET, and SEM data confirmed that the catalysts were mesoporous and low-crystalline with a high surface area. The soot oxidation activity of the catalysts was evaluated using a thermogravimetric analysis (TGA) technique. The loose contacts soot oxidation activity test suggested that 50% oxidation of soot occurred at 390°C in the absence of a catalyst. T50 of CeO2-Al2O3 catalyzed soot oxidation was 296°C. Adding Zr to the catalyst significantly improved catalytic activity for diesel soot oxidation. We observed a further drastic change in T50 of soot over 1, 3, and 5% Zr/CeO2-Al2O3, which were 220°C, 210°C, and 193°C, respectively. According to these results, incorporating Zr into the CeO2-Al2O3 catalyst significantly improved the oxidation process of soot.

Теоретико-методологическая идентификация затрат в сфере обычной деятельности хозяйствующего субъекта

The study of existing approaches to structuring the theory of costs during the construction of the information and instrumental space for corporate management of the expenditure of resources of an economic entity showed the absence of a unified concept for identifying the term “costs” in the management accounting system. The purpose of the study is to carry out a comprehensive analysis of existing cost objectification models with the subsequent formulation and justification of the theoretical and methodological identification of costs in the normal activities of an economic entity. To achieve the goal, a terminological analysis of existing theoretical and methodological approaches to the concept under study was carried out according to the studied definitions using a selected set of identification criteria. It is concluded that most scientific sources connect the interpretation of costs with the transformation of resources, use a process approach and the function of measuring resource consumption, and also pay attention to the dynamics of current assets. However, such important criteria as objectification of costs in the management accounting system, explanatory and predictive capabilities and connection with the digital space are not touched upon. The definition of costs formulated as a result of the study, taking into account the specified criteria, serves as a system-forming factor in structuring the information and instrumental environment for corporate management of the expenditure of funds in the value creation stream of the enterprise.

Challenges Faced by The Chemical Industry in Strengthening the Bioeconomy in Brazil

Objective: This study aims to discuss the chemical industry's role in developing new bioeconomic systems in Brazil. Theoretical Framework: The bioeconomy provides significant opportunities for Brazil. By exploring the country's biodiversity and environmental resources, bioeconomic systems can drive the development of innovative technologies and high-value products across various sectors. Additionally, the bioeconomy plays a crucial role in generating quality employment and preserving ecosystems. Achieving this optimistic scenario depends on the efforts of the Brazilian chemical industry in research and development (R&amp;D). Method: This research is documental and descriptive. We reviewed several sectoral reports focusing on the obstacles to using renewable inputs from Brazilian biodiversity in the chemical sector's value chains. Results and Discussion: Brazil's bioeconomy systems face limited R&amp;D investments due to structural bottlenecks related to the national tax system, logistical infrastructure, and high energy costs. These issues have reduced the competitiveness of the Brazilian chemical industry. Furthermore, increased imports of Chinese chemical products following the Ukraine War and the subsequent industry idleness can exacerbate these structural constraints and further erode the chemical sector's R&amp;D funds. Research Implications: The structural problems described in this article can delay the development of renewable energy sources and innovative bioproducts. Originality/Value: We show that the chemical industry possesses the technology and scale necessary to integrate into Federal Government programs in the bioeconomy field. However, the sector's structural problems and low R&amp;D investments tend to inhibit the development of new bioeconomic systems. Brazil must overcome these challenges to establish itself as a global bioeconomy powerhouse.

Healthcare Utilization and Costs in Children Receiving Home Mechanical Ventilation in Ontario: A 14-Year Cohort Study.

Home mechanical ventilation (HMV) is an advanced medical therapy offered to children with medical complexity. Despite the growing pediatric HMV population in North America, there are limited studies describing healthcare utilization and predictors of highest costs using robust health administrative data. To describe patterns of healthcare utilization and costs in children receiving HMV over a 14-year period in Ontario, Canada. We conducted a retrospective population-based cohort study (April 1, 2003 to March 31, 2017) of children aged 0-18 years receiving HMV via invasive mechanical ventilation (IMV) or non-invasive ventilation (NIV). Paired t-tests compared healthcare system utilization and costs two years before and two years after HMV approval. We developed linear models to analyze variables associated with children in the top quartile of health service utilization and costs. We identified 835 children receiving HMV. In the two years after HMV approval compared to the 2 years prior, children had decreased hospitalization days (median 9 (IQR 3-30) versus 29 (6-99), p<0.0001) and ICU admission days (6.6 (1.9-18.0) versus 17.1 (3.3-70.9), p<0.0001) but had increased homecare service approvals (195 (24-522) versus 40 (12-225), p<0.0001) and outpatient Pulmonology visits (3 (1-4) versus 2 (1-3), p<0.0001). Total healthcare costs were higher in the two years after HMV approval (mean $164,892 (SD $214,187) versus $128,941 ($194,199), p<0.0001). However, all-cause hospital admission costs were reduced ($66,546 ($142,401) versus $81,578 ($164,672), p<0.0001). Highest total 2-year costs were associated with IMV (OR 3.45, 95% CI 2.24-5.31; reference NIV), number of medical devices at home (OR 1.63, 95% CI 1.35-1.96; reference no technology), and increased healthcare costs in the year prior to HMV initiation (OR 2.23, 95% CI 1.84-2.69). Children progressing to the need for HMV represent a worsening in their respiratory status that will undoubtedly increase healthcare utilization and costs. We found that the initiation of HMV in these children can reduce inpatient healthcare utilization and costs but can still increase overall healthcare expenditures, especially in the outpatient setting.

Digital Functional Blocks Implementation of PWM and Control for a High-Frequency Interleaved Y-Inverter Motor Drive

This paper is about the development and demonstration of a motor drive for e-transport applications based on an innovative hybrid Si-SiC dual switching frequency interleaved buck–boost Y-inverter and a single-rotor Halbach machine. In particular, the focus is the implementation of the required discontinuous inverter modulation scheme, input voltage feed-forward and motor currents feedback control loops, as well as over-voltage, over-current, and over-temperature protections, using an off-the-shelf commercial hardware platform enabling straightforward Simulink-environment programming of all parts, while ensuring the high switching frequency capability required by wide-band-gap semiconductors. Experimental results showed good inverter efficiency, transient dynamic response to load changes, input voltage regulation, and fully functional protection capability, validating the proposed approach as a powerful option for reducing system development time and cost.

Solar irrigation potential in Sub-Saharan Africa: A crop-specific techno-economic analysis

Abstract In this study, we introduce an integrated modeling framework that combines a hydrologic model, a biophysical crop model, and a techno-economic model to assess solar irrigation potential in Sub-Saharan Africa (SSA) based on seven commonly grown food crops—maize, wheat, sorghum, potato, cassava, tomato, and onion. The study involves determining the irrigation requirements, location-specific capital investment costs, crop-specific profitability, and the cropland area under various cost scenarios (low and high) and soil fertility (low, moderate, near-optimal, and optimal) scenarios. Our research reveals considerable potential for solar irrigation, with profitability and viable cropland areas that vary according to crop type, irrigation system cost scenarios, and soil fertility levels. Our assessment shows that approximately 9.34 million ha of SSA's current rainfed cropland are hydrologically and economically feasible for solar irrigation. Specifically, maize and onion display the lowest and highest viability, spanning 1-4 million ha and 29-33 million ha, respectively, under optimal soil fertility conditions. In terms of profitability, maize and onion rank as the least and most economically viable crops for solar irrigation, yielding average annual returns of $50-\$125/ha and $933-$1450/ha, respectively, under optimal soil fertility conditions. The lower and upper bounds of profitability and cropland range correspond to high-cost and low-cost scenarios, respectively. Furthermore, our study reveals distinct regional differences in the economic feasibility of solar irrigation. Eastern Africa is more economically favorable for maize, sorghum, tomato, and cassava. Central Africa stands out for onion cultivation, whereas West and Southern Africa are more profitable for potato and wheat, respectively. To realize the irrigation benefits highlighted, an energy input of 940-2,168 kWh/ha/yr is necessary, varying by crop and geographic sub-region of the SSA sub-continent. Our model and its results highlight the importance of selecting the right crops, applying fertilizers at the appropriate rates, and considering regional factors to maximize the benefits of solar irrigation in SSA. These insights are crucial for strategic planning and investment in the region's agricultural sector.

Towards sustainable regional energy solutions: An optimized operational model for integrated energy systems with price-responsive planning

With dynamic changes in the energy market and continuous advances in smart energy technology, regional integrated energy systems (RIESs) have emerged as a vital direction in the evolution of energy systems. They are increasingly gaining significance in the realm of energy supply (ES) and demand response initiatives. In this context, this article introduces a novel optimal operational model for an integrated energy system (IES) that incorporates energy price responsiveness. The paper commences by delivering a comprehensive overview of the typical structure of an IES, presenting detailed models for each system module, encompassing the electrical energy supplier, heating, and cooling components. The proposed system model comprises three distinct subsystems, each catering to specific energy requirements. The primary emphasis is on devising an efficient planning scheme tailored to the energy consumption patterns and operational aspects of the IES. Through the presented model, there is substantial potential for significantly reducing the overall system cost without inducing a noteworthy upsurge in environmental pollution. Moreover, the energy efficiency of the system can experience considerable enhancement. The desired optimization problem has been solved using the proposed multi-objective Horse Herd Optimization Algorithm (MOHHOA). Additionally, in this strategy, Pareto front and fuzzy selection are employed to make better decisions among all Pareto solutions. The optimization strategy devised in this research not only enables the integrated operation of the IES but also ensures its compatibility with ongoing energy development initiatives. The proposed method yields a diverse set of Pareto solutions across the objective space, providing various trade-offs between economic, environmental, and reliability considerations. Utilizing MOHHOA, the algorithm efficiently balances exploration and exploitation during optimization, resulting in informed decision-making. In optimal planning, Scenario 2 exhibits lower operational costs (8.2 % reduction) and a dramatic improvement in LESP (1.24 %–1.176 %) compared to Scenario 1. Sensitivity analysis reveals an 11.2 % increase in environmental costs in Scenario 1 with a 36 % rise in electricity prices. Conversely, in Scenario 2, a 10 % reduction in natural gas prices leads to a 24.5 % increase in system running costs. These findings underscore the significance of considering energy price fluctuations for optimizing integrated energy system performance.

Emergency Hospital Admissions of Elderly Patients with Dementia: General Characteristics, Outcome, and Areas of Improvement at an Accident and Emergency Department

Aim: Age-related disorders, such as dementia, are relevant for healthcare services and health systems worldwide. The prevalence of dementia across European countries is estimated to exceed 7 %, and may rise over time. Those patients are at increased risk for hospital admission and prolonged hospitalization, and such care increases the cost for the healthcare system. Less is known regarding patients with dementia in Greece that visit the Accident and Emergency departments (A&amp;E) in general hospitals. The present retrospective study aimed to address this issue. Subjects and methods: The sample of patients and the control group were traced in the A&amp;E department of the University Hospital of Ioannina, Northwest Greece. The study sample consisted of 100 patients with dementia, aged &gt; 65 years and 100 matched controls. The median age of patients with dementia was 85 years, for the control group 83 years, and 63 % were females. In most cases the diagnosis had been made by primary care physicians, and in of patients 21 % by neurologists/psychiatrists. Results: In both groups a median of 2 comorbidities was recorded, with hypertension, heart failure and dyslipidaemia being the most common. Fever and falls were the most common reasons for dementia patients visiting the A&amp;E department. Infection was the most common diagnosis in dementia patients, whereas in 17 % of cases no diagnosis was made and no interventions were needed. The probability of admission after an A&amp;E visit was significantly higher for the dementia group, whereas there were no differences regarding length of hospital stay between patients and controls. Conclusions: The results of the study are in line with international research and highlight the need for the establishment of a national register for patients with dementia, that would enable information exchange between primary and tertiary care and would enable proper diagnosis, management and discharge arrangements.

Shared mooring system designs and cost estimates for wave energy arrays

For floating renewable energy devices to become more cost-efficient and commercially scalable, their mooring system designs must be low-cost and suited for large-scale installations. Large arrays of floating devices, such as wave energy converters (WECs), will likely be designed with an individual mooring system for each device in the array. However, new mooring technology advancements provide options to use shared mooring lines to connect adjacent devices to one another, reducing the total number of anchors in the array, thereby reducing material use and cost. This paper explores the design, modeling, and cost analysis of shared mooring systems for various sizes of arrays consisting of heaving oscillating water column (OWC) WECs. Shared mooring systems for WEC arrays sized in 2×N and N×N grid layouts are designed to meet the relevant design standards, checking their performance with a nonlinear time-domain dynamic simulation, and the costs of each are calculated and compared. Several assumptions are taken in the design process to produce efficient results, providing a preliminary optimization for guidance on design decisions rather than a full, detailed design analysis. Mooring system costs per WEC were found to decrease as the number of WECs in the array increase, up to certain array sizes. The 2 × 3 array had the lowest mooring system cost per WEC out of all arrays considered, with a 60% cost reduction relative to using individual mooring systems. The 3 × 3 and 4 × 4 arrays achieved a 50% cost per WEC reduction. In addition to these significant cost reductions, the shared mooring system designs can provide advantages through smaller mooring system footprints, lower installation times, and less seabed disturbance.

A Hybrid Technique for Impact of Hybrid Renewable Energy Systems on Reliability of Distribution Power System

A hybrid method is proposed for the effect of hybrid renewable energy systems by using photovoltaic and wind turbines based on the reliability of power system distribution. The proposed hybrid technique is the combination of the golden jackal optimization (GJO) and white shark optimization (WSO), and hence, it is named the GJO-WSO technique. The important aim of this proposed technique is to lessen the costs of the distribution system for power outages while meeting the system's needs. The GJO-WSO technique examines how renewable-energy-sources (RESs) affect the dependability of power systems (PSs). The impact of distributed generation (DG) technologies in a power system is analyzed by utilizing reliability measures like energy not supplied and expected interruption cost, (EENS, ECOST). The market pricing, wind and solar system output power, and load uncertainty are analyzed. Next, the proposed technique’s performance is evaluated with other techniques. In this, the proposed technique provides a higher accuracy of 99.68%. So, it concluded that the proposed strategy provides optimum than the present techniques.

Role of power-to-heat and thermal energy storage in decarbonization of district heating

The sector integration of the heat and electricity sectors promotes the flexibility of the energy system. This, together with the already almost carbon dioxide-free electricity supply in Finland, facilitates the environmental transition to a carbon-neutral heating system. In this study, pathways to decarbonize the district heating system in Åland (an autonomous region of Finland) are explored. Especially, the roles of different power-to-heat technologies, e.g., heat pumps and direct electric heating, and thermal energy storage are investigated in the decarbonization of the district heating system. The focus is on studying the impact of varying prices in electricity markets on the operation of climate-neutral district heating systems. For this, three scenarios were modeled over the five years of 2018–2022 with varying demand and electricity market prices by using the modeling software PLEXOS. The study showed that electricity prices, but also reserve market prices, have a very significant impact on the operation cost and profit of a district heating system. Overall, electrification has the strong potential to reduce emissions cost-effectively in a district heating system, but it also makes the system vulnerable to electricity price volatility. It can be concluded that thermal energy storage and reserve market participation are crucial for protecting against cost increases and reducing investment risk.