Daily Cost Research Articles

Optimization Operation Strategy for Comprehensive Energy System Considering Multi-Mode Hydrogen Transportation

The transformation from a fossil fuel economy to a low-carbon economy has reshaped the way energy is transmitted. As most renewable energy is obtained in the form of electricity, using green electricity to produce hydrogen is considered a promising energy carrier. However, most studies have not considered the transportation mode of hydrogen. In order to encourage the utilization of renewable energy and hydrogen, this paper proposes a comprehensive energy system optimization operation strategy considering multi-mode hydrogen transport. Firstly, to address the shortcomings in the optimization operation of existing systems regarding hydrogen transport, modeling is conducted for multi-mode hydrogen transportation through hydrogen tube trailers and pipelines. This model reflects the impact of multi-mode hydrogen delivery channels on hydrogen utilization, which helps promote the consumption of new energy in electrolysis cells to meet application demands. Based on this, the constraints of electrolyzers, combined heat and power units, hydrogen fuel cells, and energy storage systems in integrated energy systems (IESs) are further considered. With the objective of minimizing the daily operational cost of the comprehensive energy system, an optimization model for the operation considering multi-mode hydrogen transport is constructed. Lastly, based on simulation examples, the impact of multi-mode hydrogen transportation on the operational cost of the system is analyzed in detail. The results indicate that the proposed optimization strategy can reduce the operational cost of the comprehensive energy system. Hydrogen tube trailers and pipelines will have a significant impact on operational costs. Properly allocating the quantity of hydrogen tube trailers and pipelines is beneficial for reducing the operational costs of the system. Reasonable arrangement of hydrogen transportation channels is conducive to further promoting the green and economic operation of the system.

Effects of Inpatient Hospice Care on Cost and Medication Use in Patients with Lung Cancer: A Population-Based Retrospective Study in South Korea.

Background: Inpatient hospices (IHs) can alleviate distress and address economic burdens on patients with terminal cancer. However, there have been inconsistent findings regarding IHs in terms of cost savings and medication use. Objective: We aimed to examine cost savings associated with IHs, according to the timing of first hospitalization before death, and analyze their use of medication, among Korean patients with terminal lung cancer. Methods: Using the South Korean national health insurance claim database, we identified 31,139 patients with lung cancer who died between 2017 and 2020. Their daily hospitalization costs were analyzed using a generalized linear model stratified by time of first hospitalization before death. Medication use was examined using a negative binomial model. Results: IHs spent $134, and $21 less on patients during days 1-7, and 8-30 before death, but $18, $44, $36, and $54 more during days 31-60, 61-90, and 91-180, respectively, compared with non-IHs (all p < 0.05). However, total hospitalization costs in the year preceding death did not differ (relative risk: 0.990, 95% confidence interval [CI]: 0.972-1.007, p > 0.05). IHs used 2.103 times more opioid analgesics (95% CI: 1.980-2.233, p < 0.001). They also used more antiemetics, delirium medications, and antianxiety agents, as well as fewer antidepressive agents, systemic steroids, diuretics, total parenteral nutrition, and antibiotics (all p < 0.05). Conclusions: Patients with terminal lung cancer in IHs in Korea were more likely to receive symptom-oriented medications and experienced reduced hospitalization costs only during the 30 days preceding death.

A novel two-stage energy sharing method for data center cluster considering ‘Carbon-Green Certificate’ coupling mechanism

The energy consumption of data centers is on a sharp upward trend, and how to achieve joint optimal scheduling and energy management of multiple data centers is the key to the economic and low-carbon operation of data center prosumers (DCPs). This study introduces shared electric-hydrogen energy storage (SEHES) for DCPs, constructs a data center cluster (DCC) framework, and proposes a two-stage energy sharing model for DCC considering the ‘Carbon-Green Certificate’ coupling mechanism (C-GCCM). First, the DCC framework containing DCC operator (DCCO) and DCPs is established, and the C-GCCM based on conversion coefficients is designed to improve the energy saving and emission reduction level of DCC. In the day-ahead optimization stage, a stochastic multi-objective scheduling model for SEHES considering economy and environmental protection is developed. In the real-time optimization stage, considering the C-GCCM and the difference in on-grid prices, the Stackelberg game model of DCC is constructed according to the internal energy price set by DCCO and the trading strategies of DCPs. Finally, the proposed model is solved using the normal boundary intersection algorithm, the particle swarm algorithm and CPLEX. Simulation results demonstrate that the proposed DCC framework can reduce the daily operating cost of DCPs by 67.05%. The introduction of C-GCCM has resulted in a shift from negative to positive benefits on carbon emission trading for DCC and a 42.33% increase in benefits on green certificate trading.

Cost awareness among intensivists in their daily clinical practice: a prospective multicentre study.

Better cost-awareness is a prerogative in achieving the best benefit/risk/cost ratio in the care. We aimed to assess the cost-awareness of intensivists in their daily clinical practice and to identify factors associated with accurate estimate of cost (50-150% of the real cost). We performed a prospective observational study in seven French ICUs. We compared the estimate of intensivists of the daily costs of caring with the real costs on a given day. The estimates covered five categories (drugs, laboratory tests, imaging modalities, medical devices, and waste) whose sum represented the overall cost. Of the 234 estimates made by 65 intensivists, 70 (29.9%) were accurate. The median overall cost estimate (€330 [170; 620]) was significantly higher than the real cost (€178 [124; 239], p < 0.001). This overestimation was found in four categories, in particular for waste (€40 [15; 100] vs. €1.1 [0.6; 2.3], p < 0.001). Only the laboratory tests were underestimated (€65 [30; 120] vs. €106 [79; 138], p < 0.001). Being aware of the financial impact of prescriptions was factor associated with accurate estimate (OR: 5.05, 95%CI:1.47-17.4, p = 0.01). However, feeling able to accurately perform estimation was factor negatively associated with accurate estimate (OR: 0.11, 95%CI: 0.02-0.71, p = 0.02). French intensivists have a poor awareness of costs in their daily clinical practice. Raising awareness of the financial impact of prescriptions, and of the cost of laboratory tests and waste are the main areas for improvement that could help achieve the objective of the best care at the best cost.

Association of transplant recipient status with clinical and financial outcomes among patients undergoing major surgery

BackgroundTransplant recipients undergoing surgery may represent a vulnerable population because of transplant-related comorbidities as well as reliance on immunosuppressive medications. We sought to characterize the association of prior transplant status on postoperative outcomes among patients undergoing major non–transplant-related surgical procedures. MethodsData on patients who underwent a major surgical procedure (pneumonectomy, coronary artery bypass graft, abdominal aortic aneurysm repair, Whipple, colectomy) between 2016 and 2020 were obtained from the Nationwide Readmission Database. After balancing the 2 cohorts using entropy balancing, multivariable regression models were used to assess the relationship between post-transplant status and patient outcomes. ResultsAmong 1,818,973 patients, 0.45% (n = 8,212) had a history of solid organ transplantation (liver: n = 1,773, 21.6%; heart/lung: n = 1,087, 13.2%; kidney/pancreas: n = 4,891, 59.6%; and multiple: n = 461, 5.6%). In the unmatched cohort, patients who had a history of organ transplant were more likely to be male (64.1% vs 57.7%) and have Medicare insurance (71.7% vs 59.3%) (both P < .001). On multivariable analysis, prior transplant recipient status was associated with higher odds of postoperative complications (odds ratio 1.30, 95% confidence interval 1.22–1.38), 30-day readmission (odds ratio 1.42, 95% confidence interval 1.31–1.54), and in-hospital mortality (odds ratio 1.20, 95% confidence interval 1.03–1.40) (all P < .05). Moreover, organ transplantation was associated with higher index hospitalization costs (14.4% difference, 95% confidence interval 14.1%–14.6%) and 30-day postdischarge costs (16.2% difference, 95% confidence interval 15.3%–17.0%) (both P < .001). ConclusionsPrior transplant recipient status was associated with adverse clinical and financial outcomes following subsequent major surgery. Prior history of transplant may be an important factor to incorporate into risk stratification of patients undergoing subsequent major surgical procedures.

Research on the Operation Optimization of Public Building Systems in Extremely Cold Areas Based on Flexible Loads

The heating energy consumption in public buildings in cold regions is notably significant, presenting substantial scope for energy savings and emission reductions. Flexible loads can actively participate in controlling the operation of the power grid, improving the energy utilization and the economy of the system. This study introduces flexible loads into the operation optimization of energy systems, establishing mathematical models for flexible thermal and electrical loads. A two-stage operation optimization method is proposed: the first stage simulates the starting and stopping control conditions of equipment at varying temperatures and times, selecting the optimal time period to regulate the thermal loads; the second stage employs a multi-objective particle swarm optimization algorithm to optimize the scheduling of the system’s electrical load. Finally, an empirical analysis is carried out in a public building in Shenyang City as an example, and the results indicate that optimal scheduling of flexible thermal and electrical loads reduces the daily operating cost of the energy supply system by RMB 124.12 and decreases carbon emissions by 22.7%.

Impact of COVID-19 on Rickshaw Puller of Dhaka City

Bangladesh have been experiencing overwhelming population growth and extreme poverty. This is, in part, a result of rural poverty, which has led to the migration of poor people from rural to urban areas in search of a better life, better job opportunities and better social services. To assess the impact of COVID 19 on the rickshaw puller. Methods: Cross sectional quantitative analysis on rickshaw pullers. Rickshaw pullers daily income declines 64.375%. Depend on their income they decrease their daily cost and expenses as well. Those who are staying back in Dhaka might observe stable or increased income due to reduced number of rickshaw pullers on the street; as such the impact of COVID 19 on those who have left Dhaka need to be assessed separately.

Patient Profile and Cost Savings of Long-Term Care in a Spanish Hospital: Retrospective Observational Study.

Long-term care hospitals have been considered an efficient response to the health care needs of an increasingly aging population. These centers are expected to contribute to better hospital bed management and more personalized care for patients needing continuous care. The evaluation of their outcomes is necessary after a sufficient period to assess their impact. Hospitals for Acute and Chronic Long-Term Extended Stay (HACLES) emerged in Spain in the late 20th century as a response to the aging population and the increase in chronic diseases. This study aimed to analyze the profile of patients treated in a HACLES, particularly analyzing gender differences, and evaluate the cost savings associated with using these centers. A retrospective study was conducted based on data from patients 65 years old or older admitted to a HACLES between 2022 and 2023. Gender, age, household cohabitation data, diagnosis and comorbidity, daily medication intake, and degree of dependency were obtained to describe the profile of patients who attended the HACLES. Data coded in SIA-Abucasis (version 37.00.03; Consellería Sanitat, Generalitat Valenciana; a digital medical record system used in the Valencian region) were reviewed, and descriptive statistics and comparison tests were used. The direct cost savings of HACLES admissions were calculated by comparing the daily cost of a general hospital bed with that of a HACLES bed. Data from 123 patients with a mean age of 77 years were analyzed. Most (n=81, 65.9%) had a cohabiting family member as their primary caregiver. Palliative care was the most frequent reason for admission (n=75, 61%). The mortality rate (odds ratio [OR] 61.8, 95% CI 53.2-70.5) was similar between men and women (OR 54.1, 95% CI 47.8-71.5 vs OR 59.7, 95% CI 42.2-66.0; P=.23). The cognitive assessment, using the Pfeiffer scale, improved at discharge (mean 3.2, SD 3.2 vs mean 2.5, SD 3.1; P=.003). The length of stay was significantly larger for patients who returned home compared with patients discharged to other facilities (mean 89.8, SD 58.2 versus mean 33.1, SD 43.1 days; P<.001). The direct cost savings were estimated at US $42,614,846 per 1000 admissions. Patients typically treated in HACLES are older, with a high level of cognitive impairment and physical dependency, and a significant proportion are in palliative care, highlighting the importance of adapting care to the individual needs of the admitted patients. The HACLES model contributes to the sustainability of the public health system.

Cost Analysis of Penitentiary Systems and Comparison Between the Countries of the Council of Europe

Background: The objective was to analyze the budgets invested in prisons by the member states of the Council of Europe (CoE) and the relationships between the global cost, the cost incurred per single inmate, the number of inmates per 100,000 inhabitants (PPR), the gross domestic product (GDP) and per capita GDP. Methods: The data relating to the variables considered for the year 2020 were obtained from the SPACE-I 2021 of the CoE, the World Bank/OECD, and Eurostat. Regression models were used to evaluate the relationships between the PPR and the GDP, the daily cost per prisoner and per capita GDP, and between the PPR and the per capita GDP. A multiple correspondence analysis was performed to evaluate associations between the PPR, EU membership, cost per day, cost rate, geographical area, and inmate gender. Results: The daily expenditure per inmate in northern European countries reaches very high values, respectively: EUR 330.6 (Norway) and EUR 303 (Sweden), while, in the eastern countries, the values drop sharply (EUR 6.50 in Bulgaria and EUR 8.08 in Azerbaijani). The lowest PPR values are found in northern European countries, and the highest in the following countries: Russia, Turkey, Georgia, and Azerbaijan. Conclusions: Countries with a higher GDP per capita tend to have lower prison population rates and to invest larger amounts of funds for prison systems.

Soft Colloidal Electrode Enabled by Water Distribution Control for Ultra-Stable Aqueous Zn-I Batteries.

Designing effective electrode material is crucial for developing ultra-long lifetime batteries, thereby reducing daily battery costs. Current electrode materials are typically solid or liquid state, with an intermediate colloidal state offering the advantages of fixed redox-active species, akin to solid-state materials, and the absence of rigid atomic structure, akin to liquid-state materials, while avoiding the particle pulverization and uncontrolled migration. Herein, an aqueous Zn||Pluronic F127 (PF127)/ZnI2 colloid battery is developed utilizing the inherent water molecular control effect of ZnSO4. In this system, ZnSO4 in the electrolyte acts as a water molecular valve, regulating the water content within the PF127 polymer to form a PF127 colloid. The resulting aqueous Zn||PF127/ZnI2 colloid battery exhibits an ultra-long cycling lifetime and compatibility with various simulated and practical operating conditions, highlighting its potential for practical applications. Additionally, this battery design concept offers a platform for constructing ultra-stable aqueous batteries.

Optimizing shared charging services at sustainable bus charging hubs: A queue theory integration approach

Integrating solar photovoltaic (PV) systems into bus charging infrastructure offers a promising solution to mitigate carbon emissions and reduce grid loads. However, a mismatch between the output of solar PV energy and the electric bus (EB) charging demand can arise due to the instability and intermittency of solar PV energy. To address this issue, this study introduces a novel shared charging business mode that allocates charging facilities to private electric vehicles (PEVs), leveraging idle infrastructure to maximize solar PV utilization. We develop an optimization framework to jointly determine the EB charging schedules and the allocation of charging facilities between EBs and PEVs within an EB network integrated with solar PV systems. Additionally, a loss queue model with time-dependent arrival rates is proposed to model the stochastic nature of PEV charging demand. A case study is conducted on a bus network in Beijing to validate our proposed operational strategy. The findings demonstrate that integrating shared charging in bus depots equipped with solar PV systems improves solar PV utilization from 79.30 % to 92.91 %. This integration reduces CO2 emissions and overall daily system costs by 7.93 % and 14.82 %, respectively, without negatively impacting the grid load during peak periods.

The Impact of Socioeconomic Factors on 90-day Postoperative Readmissions and Cost in Shoulder Arthroplasty Patients

Understanding the impact of Social Drivers of Health (SDOH) on shoulder arthroplasty is pivotal for the development of equitable value-based payment models that enhance the quality of patient care. This investigation aims to understand the influence of Area Deprivation Index (ADI) on hospital admissions, readmissions, and associated costs post-shoulder arthroplasty. We conducted an analysis using US Medicare claims data from 2019 to 2021, identifying patients who received shoulder arthroplasty in either an inpatient or outpatient setting using Current Procedural Terminology (CPT) codes. Our primary outcomes were 90-day unplanned readmissions and post-procedure 90-day care costs. The ADI was our primary exposure variable, calculated at the census block level. Our analysis adjusted for multiple factors using a stepwise modeling approach including patient demographics, 29 Elixhauser comorbid conditions, Medicaid-dual eligibility, and end-stage renal disease status using logistic regression models. A total of 145,435 patients were included in our study. The average age of patients in our cohort was 74.5 years old, with 59.5% being female. Patients in the high ADI group had a higher readmission rate than the lowest ADI group (8.5% vs. 6.0%, p<0.001).When controlling for confounding factors, there was an indepdentent association between high ADI and readmission (OR: 1.28 [95% CI 1.12, 1.46]). Overall, we saw a dose-dependent relationship between ADI and readmission, with the association growing stronger as ADI increased. Conversely, we found a negative association with ADI and high-costs. (High ADI Group OR: 0.80 [95% CI 0.70, 0.91]). Patients in the high SES group had higher healthcare contact days during the 90-day follow-up period, with a median of 16 visits (IQR 8, 23), compared to 13 visits (IQR 6, 22) in the middle SES group and 10 visits (IQR 5, 20) in the low SES group (p<0.001). Socioeconomic disparities significantly influence the outcomes of primary shoulder arthroplasty, as indicated by higher readmission rates for low SES patients. Notably, our analysis shows a strong, independent association between ADI and readmission. Moreover, patients with higher SES incurred greater costs within a 90-day period potentially due to increased resource utilization.

Enhancing the Reliability of Weak-Grid-Tied Residential Communities Using Risk-Based Home Energy Management Systems under Market Price Uncertainty

This paper evaluates the reliability of smart home energy management systems (SHEMSs) in a residential community with an unreliable power grid and power shortages. Unlike the previous works, which mainly focused on cost analysis, this research assesses the reliability of SHEMSs for different backup power sources, including photovoltaic systems (PVs), battery storage systems (BSSs), electric vehicles (EVs), and diesel generators (DGs). The impact of these changes on the daily cost and the balance of energy source contribution in providing electrical energy to household loads, particularly during power outage hours, is also evaluated. To address the uncertainty of electricity market prices, a risk management approach based on conditional value at risk is applied. Additionally, the study highlights the impact of community size on energy costs and reliability. The proposed model is formulated as a mixed-integer nonlinear programming problem and is solved using GAMS. The effectiveness of the proposed risk-based optimization approach is demonstrated through comprehensive cost and reliability analysis. The results reveal that when electric vehicles are used as backup power sources, the energy index of reliability (EIR) is not affected by market price variations and shows significant improvement, reaching approximately 99.9% across all scenarios.

Everyday household costs of raising a child with cerebral palsy

Abstract Background Caring for a child with a disability can be costly in terms of time and energy, and it is also associated with lower incomes and higher direct costs, such as costs for assistive technologies, transport, food, clothing and leisure activities. However, few studies that have focused on households’ everyday costs associated with raising a child with disability. This study is based on the capability approach. The economic costs of a child with cerebral palsy are defined as the economic costs associated with achieving the same capabilities, or functionings, as a child without cerebral palsy. The purpose of this study is to explore the needs and economic costs in households raising a child with cerebral palsy. The results are important to inform, plan and justify targeted policies and interventions. Methods Digital in-depth interviews with caregivers from 15 Norwegian households raising children with cerebral palsy (aged 4-17 years, GMFCS levels 1-5). 12 women, 2 men and a couple were interviewed two times (1-2 hours each). Results The caregivers who took part in the interviews described their demanding role and that they spend a lot of time organizing daily routines, activities, health services, assistive technologies and assistants. Many of them initially reported that they do not have many daily extra costs, but when discussing the different areas of consumption, it emerged that households have extra housing costs because they need to make adaptations, remodeling and maintenance to their homes. An adapted car, which requires service, insurance and fuel, is often used for transport. The washing machine runs regularly and towels, sheets and clothes need to be frequently changed. Sometimes they also end up buying food, clothes or toys that are not used. Conclusions Households caring for children with cerebral palsy have additional costs for several types of expenses, including especially high costs for housing and transportation. Key messages • Households raising a child with cerebral palsy have needs that generate additional costs. • The costs vary and it is important to cover a broad range of cost areas.

Barriers to a sustainable living in Italy: results of a national survey

Abstract Background Sustainable living plays a crucial role in creating a fairer society, but various constraints prevent consumers from adopting sustainable behaviours. This study investigated the reasons for non-adoption of sustainable products or behaviours among the Italian population. Methods From January to June 2023, we surveyed the Italian population using a 40-question online survey that asked about knowledge, awareness, and attitudes toward sustainable behaviours and products. Participants were asked about the reasons why they did not engage in a certain behaviour or did not use a selected product. Descriptive statistics, t-test and chi-square tests were performed to assess association with participant characteristics. Results The 420 participants had a median age of 39 years (interquartile range: 32-56), 66% were female. The largest discrepancy between knowledge of sustainability impacts and implementation was in the personal care (92% knowledge, 31% implementation) and transportation (85% knowledge, 48% implementation) domains. In general, the main reasons for not using the surveyed products were practical complications in everyday life (25%), the difficulty of finding or producing them (23%) and their cost (13%). Specifically, practical complications (42%) were the main reason for not adopting sustainable behaviours in the transport domain. In the personal care domain, low confidence in product quality or ignorance of their existence accounted for only 26% of reasons for non-use, while supply problems, practical complications in everyday life and existence unawareness accounted for 61%. Conclusions Targeted measures are needed to address the reasons for non-use or adoption of sustainable products and behaviours. In this way, these actions will help to promote healthy living, protect our planet, support socio-economic development, and ensure global prosperity. Key messages • A greater sustainability- implementation awareness gap was found in personal care and transportation domains. • The main reasons for not implementing sustainable living were practical complications in daily life, supply difficulties and product cost.

Modelling the cost differential between current and healthy diets according to household education level in Belgium

This study aims to estimate the cost differential between current and healthy diets, overall and by household education level. Data from the 2014–2015 Belgian National Food Consumption Survey and food prices from the 2014 GfK ConsumerScan panel were linked. The DIETCOST programme was used to model healthy, isocaloric healthy and current diets. For the reference household, the average daily diet cost was 20.1€ (95%CI: 19.9–20.4) for current diets, 20.9€ (95%CI: 20.6–21.2) for healthy isocaloric diets (+3.9% vs. the current diets) and 22.5€ (95%CI: 22.3–22.8) for healthy diets (+12.0%). In low-educated households, the cost of current and of healthy isocaloric diets was similar (19.2€ (95%CI: 19.0–19.5) vs. 19.3€ (95%CI: 19.0–19.6)), whereas in high-educated households, the cost of healthy isocaloric diets (22.0€; 95%CI: 21.8–22.3) was higher than the cost of current diets (21.2€; 95%CI: 20.9–21.4)). Though needing validation, this finding is valuable for interventions aimed at improving dietary habits in disadvantaged populations.

Implementation of the Critical Chain Project Management (CCPM) Model for Improving Time and Cost in a Project for House Type 36

Purpose: This study was conducted on a housing project in Type 36 Housing using the Critical Chain Project Management (CCPM) approach. The objective of this research was to achieve a more effective project timeline and a more efficient total project cost. Research methodology: By eliminating 50% of the safety time, the method minimizes the safe time to achieve a 50% probability of completion without additional safety time using Critical Chain Project Management or CCPM in this project. Results: This approach results in a reduction of the project completion time from the original 18 working days to 15 working days. Additionally, this implementation leads to cost savings, with the calculated daily cost amounting to Rp.10,907,170.03. Through the application of Critical Chain Project Management, a 4-day Feeding Buffer and an 11-day Project Buffer were established. As a result, the completion time for the Type 36 house construction is reduced to 15 days, which is 3 days shorter than the initial project schedule of 18. Limitations: This analyzing just focus on critical process but not for opportunity job can be reduce for more improvement. And this research only focus in Construction Project. Contribution: This research can be use for practical in the project that have critical job need to prepare and control to achive project target, with cost reduction for Rp.10,907,170.03 and project time reduction for 3 days

Multi-objective energy management using a smart charging technique of a microgrid with the charging impact of plug-in hybrid electric vehicles

The Microgrid (MG) concept is being developed to better integrate renewable energy sources and automate distribution networks. Microgrids combine distributed generating units (DGs) and energy storage systems to achieve this. This research paper aims to simultaneously minimize the daily operational cost and net environmental pollution of a small MG system, factoring in the charging demand from Plug-in-Hybrid Electric Vehicles (PHEVs) and consumer load demands. The proposed energy management process not only minimizes operational costs and emissions, but also determines the optimal battery size for the energy storage system. The analysis also explores the importance of two critical variables - the operation and maintenance costs of the DGs, and the total daily cost of the battery energy storage system. The demand for PHEV charging is managed using an intelligent charging approach. Given the complexity of the optimization, a recently developed metaheuristic algorithm, Slime Mould Algorithm (SMA), is applied. The performance of SMA is compared against the Grasshopper Optimization Algorithm and Sine Cosine Algorithm. To solve the multi-objective problem, a weighted sum method maintaining non-dominance and a fuzzy decision-maker technique are employed alongside the suggested algorithms. Three different scenarios verify the proposed method's effectiveness.

Energy management system for multi interconnected microgrids during grid connected and autonomous operation modes considering load management

This study focuses on improving power system grid performance and efficiency through the integration of distributed energy resources (DERs). The study proposes an artificial intelligence (AI) based effective approach for economic dispatch and load management for three linked microgrids (MGs) that operate in both grid-connected and autonomous modes. A day-ahead scheduling method is suggested to calculate the optimal set points for various energy sources in MGs considering various system constraints for safe operation. In addition, a load management approach that shifts the controllable loads from one interval to another is applied to reduce the operating cost of MG. To handle the optimization challenges of energy scheduling and load shifting such complexity and non-linearity, an advanced meta-heuristic method known as the one-to-one based optimizer (OOBO) is used. Overall, the paper proposes a viable and efficient methodology for economical distribution in linked microgrids, which takes advantage of renewable energy resources and incorporates scheduling optimization via the OOBO algorithm. The proposed energy management strategy enhances the system performance, increases energy efficiency, and reduces the daily operational cost by 1.6% for grid connected mode and by 0.47% for islanded operation mode.

Optimal Energy Storage Allocation for Combined Wind-PV-EVs-ES System Based on Improved Triangulation Topology Aggregation Optimizer

To determine the ES allocation based on a specific number of EVs connected to a combined WPESS, this paper develops an ESS allocation model that considers the impact of EV charging behavior on LSD, ES allocation cost, new energy utilization rate, and self-power rate. First, several scenarios are generated using Monte Carlo sampling (MCS), and a typical day is selected through Backward Reduction (BR). Next, the Monte Carlo method is employed to generate conventional EV charging curves and optimize EV charging behavior by considering LSD and user charging costs. Subsequently, an ES capacity allocation model is developed, considering system costs, new energy utilization rate, and self-power rate. Finally, an improved triangulation topology aggregation optimizer (TTAO) is proposed, incorporating the logistic map, Golden Sine Algorithm (Gold-SA) strategy, and lens inverse imaging learning strategy. These enhancements improve the algorithm’s ability to identify global optimal solutions and facilitate its escape from local optima, significantly enhancing the optimization effectiveness of TTAO. The analysis of the calculation example indicates that after optimizing the charging behavior of EVs, the average daily cost is reduced by 204.94, the self-power rate increases by 2.25%, and the utilization rate of new energy sources rises by 2.50%, all while maintaining the same ES capacity.