Purchase Cost Research Articles

Analysis of power system scheduling operation mode based on multi-objective optimization algorithm

Abstract Exploring the majorization strategy of the power system (PS) dispatching operation is to achieve economic cost reduction and reduce environmental pollution. In this paper, starting from the PS dispatching model, the adaptive Corsi variance is introduced to get rid of the local optimum using particle swarm majorization procedure, and the adaptive Corsi variance multiple swarm coevolutionary procedure is constructed through coevolutionary strategy and information sharing strategy. The MCPSO-ACPM procedure is used to optimize the PS scheduling operation model, and experiments are conducted on both load and unit for the optimized scheduling model. From the load majorization results, the peak-to-valley variance is concentrated from 176.02KW to 110.51KW compared with the original load, and the peak-to-valley ratio is reduced by 0.718, which saves customers 98.63 yuan in electricity purchase cost. From the scheduling majorization prediction, the PS output power prediction value of 1 min during the day is closest to the actual measured value of output power, and its prediction deviation is about 2.67%. This shows that the use of a multi-objective majorization procedure can realize the optimal dispatch of PS and achieve the reduction of economic cost.

Research on Optimal Scheduling of Multi-Energy Microgrid Based on Stackelberg Game

In recent years, rapid industrialization has driven higher energy demand, depleting fossil-fuel reserves and causing excessive emissions. China’s “dual carbon” strategy aims to balance development and sustainability. This study optimizes microgrid efficiency with a tiered carbon-priced economy. A Stackelberg game establishes microgrid-user equilibrium, solved iteratively with a multi-population algorithm (MPGA). Comparative analysis can be obtained without considering demand response scenarios, and the optimization cost of microgrid operation considering price-based demand response scenarios was reduced by 5%; that is 668.95 yuan. In addition, the cost of electricity purchase was decreased by 23.8%, or 778.6 yuan. The model promotes user-driven energy use, elevating economic and system benefits, and therefore, the scheduling expectation of “peak shaving and valley filling” is effectively realized.

A Systematic Review of UAV Applications for Mapping Neglected and Underutilised Crop Species’ Spatial Distribution and Health

Timely, accurate spatial information on the health of neglected and underutilised crop species (NUS) is critical for optimising their production and food and nutrition in developing countries. Unmanned aerial vehicles (UAVs) equipped with multispectral sensors have significantly advanced remote sensing, enabling the provision of near-real-time data for crop analysis at the plot level in small, fragmented croplands where NUS are often grown. The objective of this study was to systematically review the literature on the remote sensing (RS) of the spatial distribution and health of NUS, evaluating the progress, opportunities, challenges, and associated research gaps. This study systematically reviewed 171 peer-reviewed articles from Google Scholar, Scopus, and Web of Science using the PRISMA approach. The findings of this study showed that the United States (n = 18) and China (n = 17) were the primary study locations, with some contributions from the Global South, including southern Africa. The observed NUS crop attributes included crop yield, growth, leaf area index (LAI), above-ground biomass (AGB), and chlorophyll content. Only 29% of studies explored stomatal conductance and the spatial distribution of NUS. Twenty-one studies employed satellite-borne sensors, while only eighteen utilised UAV-borne sensors in conjunction with machine learning (ML), multivariate, and generic GIS classification techniques for mapping the spatial extent and health of NUS. The use of UAVs in mapping NUS is progressing slowly, particularly in the Global South, due to exorbitant purchasing and operational costs, as well as restrictive regulations. Subsequently, research efforts must be directed toward combining ML techniques and UAV-acquired data to monitor NUS’ spatial distribution and health to provide necessary information for optimising food production in smallholder croplands in the Global South.

Purchase cost based reconfiguration of distribution system under varying loads and renewable generation

Optimal reconfiguration of distribution system is complex process and thus demands high computing power and time. In a competitive market for a distribution system with multiple feeders owned by multiple agencies, the cost of purchasing power for each of those feeds are often different from one another. In such case, reconfiguration of distribution system, exclusively on the basis of loss minimization may not be appropriate. Furthermore, increasing solar PV generation (SPVG) integration is posing new type of operational challenges due to its sudden and high variability. Hence, the conventional approaches of hourly stepwise load curve discretization may not be cost-effective for feeder reconfiguration exercise. In view of these twin objectives, a novel heuristic strategy is proposed for minimizing costs using a two-stage process that takes into account sensitivity. The primary objective of the proposed approach is to reduce the computing load associated with the exercise, while also incorporating the variability of loads and renewable energy sources. This has been achieved without significantly increasing the computational workload, by employing a reconfiguration strategy that best aligns with the specific hour under consideration, which is further divided into four subintervals of fifteen minutes each. Moreover, despite the high variability, the frequency of reconfiguration is not increased in order to extend the lifetime of the gear switches. To show the efficacy of the proposed approach, simulation results for two distinct test systems have been obtained.

Research on the tripartite evolution strategy of prefabricated building promotion based on the deepening of demand-side interests.

Under construction industry upgrading and environmental protection requirements, promoting prefabricated buildings is very important, but its development varies significantly in different regions. For example, it only accounts for 20% of the new construction area in China, and the overall development level is low. The promotion of prefabricated buildings involves multiple interests. Then, how to encourage all stakeholders to work together to promote its development is a crucial issue. This study obtains an evolutionary game model among the government, developers, and purchasers. Then the stability strategies of the stakeholders are given conditions. Finally, numerical simulation is used to validate theoretical findings and determine the sensitivity of key parameters to a subject's behavior. The results show that: (1) There are two key factors that restrict the cooperation of stakeholders to promote prefabricated buildings, including the lack of government subsidies and the weak demand of the purchasers; (2) The government's overall subsidy should not be too high, exceeding the government's expenditure on environmental protection, and the subsidies for developers and purchasers must be reasonably allocated to effectively compensate for development benefits and purchase costs under limited expenditures. (3) Improving the residential environment of prefabricated buildings can significantly enhance the vested interests of purchasers, make up for their purchase costs, increase their willingness to purchase, and thus reduce the sales risk of developers.

Which Laser System is Optimal for Cystolithotripsy of Large Bladder Calculi?

A variety of laser sources are available to treat bladder stones. The aim of this study was to compare time and cost efficiency of the thulium fiber laser (TFL) to four holmium lasers (HLs) with different powers or technologies, including MOSES™ during simulated cystolithotripsy. In a benchtop simulation of laser cystolithotripsy, 25 identical 4-cm BegoStones (calcium oxalate monohydrate consistency) were placed on a grid within a 3D-printed bladder model. Lasers were operated at maximal energy, using a 550 µm fiber. Lasers compared were: 60W TFL, 120W HL with MOSES™, conventional 120W, 100W, and 30W HLs. Five trials were performed for each laser with endpoints of laser time, total time, number of fiber strippings, and total energy. Cost effectiveness was modelled using laser purchase price, fiber, and OR time cost. ANOVA with Tukey's B post hoc was performed to compare outcomes. Spearman's test was used to assess correlation between laser power and procedure time. The laser and total operating times were significantly different between the five systems (p<0.001). The 120W HL with MOSES™ was the fastest with 60.9 min laser and 68.3 min procedure times, while the 30W HL was the slowest with 281.2 min laser and 297.5 min procedure times. The 60W TFL was faster than the 30W HL, but slower than the higher power HLs. Higher laser power was associated with shorter procedure time (Rs=-0.98; p=0.002). When estimating cost per procedure, the MOSES™ HL was the cheapest, but had the highest purchase cost. The TFL was not cost-effective for large bladder stones compared to the 100W HL. When treating large bladder stones, total laser power was highly correlated with laser and procedure times and the TFL was limited by its total power. The most cost-effective laser for use will depend on the case volume.

Optimization model for home energy management system of rural dwellings

In the context of the increasing popularity of distributed energy, this paper proposes a home energy management system method considering the working state of flexible load to deal with the problem of mismatch between home energy supply and demand. Specifically, in this paper, the flexible load in the system is studied, and the model of flexible load and its working state are established. On this basis, combined with the real-time electricity price of the grid, the model of home energy management system is constructed to minimize the electricity purchase cost and improve the utilization rate of renewable energy, the genetic algorithm is used to solve it, and the influence of time step, flexible load ratio and whether to use energy storage equipment on the optimization degree of the model are analyzed. The research results show that, while meeting the requirements of human comfort and electricity demand, the daily electricity purchase cost of the system with flexible load scheduling is 22.5% lower than that of the system without flexible load scheduling, and the utilization rate of renewable energy is increased by 16.5%. In terms of model optimization, shortening the prediction time step, increasing the proportion of flexible load and using energy storage equipment can further reduce the electricity purchase cost. The case study confirms the effectiveness of the proposed home energy management system model, which can provide an efficient optimal scheduling scheme for household energy saving.

Optimal energy management of an integrated energy system with multiple hydrogen sources

Hydrogen is considered a promising alternative to fossil fuels in an integrated energy system (IES). In order to reduce the cost of hydrogen energy utilization and the carbon emissions of the IES, this paper proposes a low-carbon dispatching strategy for a coordinated integrated energy system using green hydrogen and blue hydrogen. The strategy takes into account the economic and low-carbon complementarity between hydrogen production by water electrolysis and hydrogen production from natural gas. It introduces the green hydrogen production–storage–use module (GH-PSUM) and the blue hydrogen production–storage–use module (BH-PSUM) to facilitate the refined utilization of different types of hydrogen energy. Additionally, the flexibility in hydrogen load supply is analyzed, and the dynamic response mechanism of the hydrogen load supply structure (DRM-HLSS) is proposed to further reduce operating costs and carbon emissions. Furthermore, a carbon trading mechanism (CTM) is introduced to constrain the carbon emissions of the integrated energy system. By comprehensively considering the constraints of each equipment, the proposed model aims to minimize the total economic cost, which includes wind power operation and curtailment penalty costs, energy purchase costs, blue hydrogen purification costs, and carbon transaction costs. The rationality of the established scheduling model is verified through a comparative analysis of the scheduling results across multiple operating scenarios.

Optimal Configuration of Power/Thermal Energy Storage for a Park-Integrated Energy System Considering Flexible Load

The park-integrated energy system can achieve the optimal allocation, dispatch, and management of energy by integrating various energy resources and intelligent control and monitoring. Flexible load participation in scheduling can reduce peak and valley load, optimize load curves, further improve energy utilization efficiency, and reduce system costs. Based on this, firstly, a flexible power-load model is established considering the translatable load, transferable load, and reducible load; and a thermal flexible load model is established based on the fuzziness of user perception of temperature in this study; then, the mixed integer linear programming method is adopted, and the sum of the carbon transaction cost, operation and maintenance cost, compensation cost, power purchase cost, gas purchase cost, wind and light abandonment penalty cost and investment cost of the system is minimized as the objective function, and the configuration of the integrated energy system is optimized, and the optimal capacity of each equipment and the output of each period are obtained. Finally, taking an industrial park in Liaoning Province of China as an example, the analysis is carried out. The example results show that by scheduling the flexible electrical load and flexibly adjusting the indoor temperature, renewable energy consumption can be promoted, and electricity load and heat-load curves can be optimized to increase the installed capacity of wind turbines, reduce the capacity of gas turbines, batteries, and heat-storage tanks, improve system economy, and improve the penetration rate of renewable energy.

Costs of purchase, maintenance, microbiological control, and reprocessing of a reusable duodenoscope.

Background and study aims The costs of reusable endoscope reprocessing have been evaluated, yet external validity of the findings remains challenging. The aim of this study was to assess the costs of purchase, maintenance, microbiological control, and reprocessing of a reusable duodenoscope per endoscopic retrograde cholangiopancreatography (ERCP) in France. Study findings exclude the costs of infection, downtime due to breakdown, reprocessing single-use material disposal, and device disposal, all of which should also be considered. Materials and methods The study encompassed both observational and theoretical approaches. Observational data were collected in four hospitals, from December 2019 to December 2020, with an ad hoc survey, based on 2016 and 2018 national guidelines for duodenoscope reprocessing. Costs were modeled, using the same guidelines, assuming a mean workload of 223 ERCP/duodenoscope/year. Results The mean observed cost of purchase, maintenance, microbiological control, reprocessing (human resources and consumables), and overhead (additional 35%) with a reusable duodenoscope was €80.23 (standard deviation €3.77) per ERCP. The corresponding mean theoretical cost was €182.71 for manual reprocessing without endoscope drying cabinet (EDC), €191.36 for manual reprocessing with EDC, €235.25 for automated endoscope reprocessing (AER) without EDC, and €253.62 for AER with EDC. Conclusions Because procedures, equipment, volume activity, number of duodenoscopes, human resources, and internal work organizations are hospital-dependent, observed costs varied between hospitals. Theoretical costs were higher than observed costs, showing that the theoretical approach is not sufficient. Hypotheses to explain the difference between the two approaches include failing to measure some costs in the survey and challenges in guideline implementation.

Optimal placement and coordination of the protection devices simultaneous with optimal allocation of the DGs

AbstractOptimal coordination of the protection devices (PDs) is performed here simultaneous with optimal allocation of them and the DGs. The PDs are a set of directional overcurrent relays (DOCRs) and voltage relays, each with its own fast switch (FS). In previous optimal DG placement studies the coordination of the PDs has been considered as a constraint. So, it was not possible to optimal coordination of the PDs simultaneously. In the present study, the coordination between the PDs is considered in calculating the value of the energy not supplied (ENS) that is a part of an overall cost function. The cost function considered here includes cost of purchase, installation, and maintenance of the DGs and the PDs, cost of the energy losses, cost of the ENS, cost of the purchased energy from the main grid and the DGs, and the penalty cost for emitting environmental pollutants. Here, output of the renewable DGs and the network loads during the year, in a 96‐h model, has been considered as variable. To solve the desired optimization problem, an algorithm based on evolutionary algorithms such as genetic algorithm (GA) is proposed. Finally, various cases have been simulated by considering a standard 33‐bus radial network.

Multi-energy Complementary Power System Economic Dispatch Considering Carbon Emission and Regional User Coordination

The integration of multi-energy complementarity and source-grid-load-storage is an important initiative to promote energy transformation and the high-quality development of power systems. This paper proposes a two-tier day-ahead multi-energy complementary power system economic dispatch model from the perspective of clean and low-carbon, taking into account carbon emissions and multi-regional user synergy. The model optimises the production and purchase of electricity through different decisions between the upper generation side and the lower user side, which minimises the energy production cost in the upper tier and the energy purchase cost in the lower tier, and achieves mutual benefits between the upper and lower tiers. This paper validates the algorithm and model with an improved IEEE 39-node system.

Decision-making for stochastic multi-objective dispatch of integrated electrical and heating systems

In the realm of modern energy systems, addressing the challenges of enhancing flexibility and efficiency under uncertain conditions is of paramount importance. This paper explores the stochastic multi-objective optimal multi-energy flow problem within the context of integrated electrical and heating systems (IEHS). First, the electrical network, the heating network, and the energy hubs were modeled in a completely linearized form. The linear weighted sum method with variable weights was used to transform the multi-objective problem into a single-objective problem and generate a large number of Pareto-optimal solutions. Second, the input stochastic variables were divided into multi-interval scenarios by employing the Cartesian product. For each interval scenario, the interval satisfaction degree level was proposed to convert the constraints involving interval numbers into deterministic ones. Third, a multiple attributes decision analysis (MADA) approach was proposed based on evidential reasoning theory. Six evaluation attributes, namely, the power purchase cost and pollution gas emissions of IEHS, the sum of power loss and sum of voltage deviation in the electrical system, the sum of temperature drop in the heating system, and the interval probability value of the multi-interval scenarios, were considered to rank the Pareto-optimal solutions collected from the multi-interval scenarios and determine the final dispatch solution (called the Utopia solution). Numerical simulations demonstrated that the Utopia solution can comprehensively evaluate various attributes, making it the most suitable option for meeting the operational requirements of IEHS.

Optimal Dispatching of Energy Hub for New Energy Consumption

In recent years, with the continuous increase of wind power installed capacity, due to insufficient flexibility of the system, there has been a serious problem of wind power abandonment. In response to this phenomenon, this article improves the flexibility of the regional energy system by adding various flexible devices. Based on the concept of an energy hub, an energy hub model including wind power, CHP, heat pumps, heat storage, and other equipment is established. On this basis, considering system operating costs, wind abandonment penalty costs, and electricity purchase costs, a multi-objective regional energy system flexibility configuration model based on energy hubs was established to explore the feasibility of this model in improving wind power consumption. Finally, specific examples were combined in two different cases for analysis. The results indicate that the model has a very good effect on improving system flexibility and improving wind power consumption rate.

Hierarchical Vaccine Allocation Based on Epidemiological and Behavioral Considerations.

Vaccines have proven useful in curbing contagion from new strains of the SARS-CoV-2 virus. However, equitable vaccine allocation continues to be a significant challenge worldwide, necessitating a comprehensive allocation strategy incorporating heterogeneity in epidemiological and behavioral considerations. In this paper, we present a hierarchical allocation strategy that assigns vaccines to zones and their constituent neighborhoods cost-effectively, based on their population density, susceptibility, infected count, and attitude towards vaccinations. Moreover, it includes a module that tackles vaccine shortages in certain zones by locally transferring vaccines from zones with surplus vaccines. We leverage the epidemiological, socio-demographic, and social media datasets from Chicago and Greece and their constituent community areas to show that the proposed allocation approach assigns vaccines based on the chosen criteria and captures the effects of disparate vaccine adoption rates. We conclude the paper with a lowdown on future efforts to extend this study to design models for effective public policies and vaccination strategies that curtail vaccine purchase costs.

Low-carbon Economic Scheduling of Combined Cooling, Heating and Power Microgrid Considering Demand Response and Shared Energy Storage

In order to further promote the new energy consumption of combined cooling, heating, and power (CCHP) microgrid, reduce carbon emissions, and optimize the total operating cost of the microgrid, a low-carbon optimal scheduling model of CCHP microgrid was proposed. It considered demand response (DR) and shared energy storage (SES). Firstly, the concept of SES and its operation mode are applied to the microgrid. Secondly, in order to take advantage of the flexible nature of multiple loads, an integrated demand response (IDR) model with a ladder subsidy mechanism was established. Then, the optimal scheduling model introduces a reward and punishment ladder carbon trading mechanism (RPL-CTM). Finally, taking energy purchase cost, load reduction subsidy cost, interaction cost with energy storage station, carbon trading cost, and wind abandoning penalty cost as optimization objectives, a multi-energy coupling, and multi-objective collaborative optimization scheduling model was established. Numerical analysis indicates that the model can efficiently lower the microgrid’s operating cost and encourage the use of clean energy and carbon emission reduction.

Costs of medications used to treat inflammatory bowel disease

Background Inflammatory bowel disease (IBD), mainly Crohn’s disease (CD) and ulcerative colitis (UC) are chronic diseases causing a lifelong burden and often need sustained treatment throughout a patient’s life. Both the incidence and prevalence of IBD has increased in the last decade. Evidence showing the drug costs to IBD patients in Finland is limited. No earlier study has evaluated the drug costs of IBD patients in Finland. Here, we thoroughly assessed these costs. Methods A structured questionnaire, hospital records and national registers were combined to comprehensively assess the actual costs of drug purchases made by IBD patients. The study sample comprised 561 patients. Results Total annual mean drug costs were 1428€ per patient. CD patients had higher annual costs than UC patients at 2369€ and 902€, respectively. CD patients also had higher costs in the immunosuppressant, corticosteroid, and biologic subgroup analyses. In addition, C-reactive protein, serum albumin and fecal calprotectin levels had a correlation with costs if the patient had needed corticosteroids. In addition, women reported having a worse quality of life (QoL) but had lower total costs. Conclusions Pharmaceutical drugs are major factors that affect the costs of IBD treatment, and the increased use of biologics has raised these costs.

Catalyst Application in Three-Dimensional Porous Electrodes for Alkaline Electrolysis

Hydrogen is critical in the green transition, and a key system for producing green hydrogen is through alkaline electrolysis. Although the alkaline electrolyzers are mature and commercially available, vast improvements are still expected in the future 1.Traditional and most commercially applied alkaline electrolyzer electrodes are made from massive nickel plates (or nickel-plated steel plates) with some scattered perforation. With the ongoing development of thin alkaline ion‐conducting membranes with low internal resistance, the benefit of three‐dimensional porous electrodes becomes obvious. With such electrodes, there will be no blind spots and the active catalytic area can be increased significantly. Today, most groups developing such 3D electrodes use commercial nickel foam as substrate. This limits the options to what is available in the market, moreover the purchase cost is high.The present work aims at developing high‐performing three‐dimensional hydrogen and oxygen evolution electrodes for alkaline electrolysis. The focus will be on the application of nanostructured electrocatalysts into three‐dimensional electrode structures, similar to nickel foams.The results obtained, so far, show homogeneous formation of nanoparticles on the surface. The analysed samples show mechanical flexibility as soon as the particles are deposited but samples become rigid after testing in a half cell setup with KOH 1 M electrolyte. Further analysis will explore changes to the microstructure. The roughness factor calculated by non-faradaic cyclic voltammetry is in the range of 75 cm2 ECSA / cm2geometric, showing higher value than the commercial Nickel foam.Initial experiments are carried out on as-prepared samples, but more advanced catalysts are also explored based on state-of-the-art materials. [1] IRENA - Green Hydrogen Cost Reduction: Scaling up Electrolysers to Meet the 1.5 °C Climate Goal, International Renewable Energy Agency, Abu Dhabi (2020)

Residential swimming pools maintenance under an environmental perspective

Swimming pools provides various benefits for users, but their owners need to carry out constant maintenance to ensure water quality and user safety. This paper goal was to assess the maintenance process of residential swimming pools, through Life Cycle Assessment based on NBR ISO 14040:2014 and NBR 14044:2014. The standard steps were followed and primary data on materials and quantities for the treatments were collected during 2022. The purchase costs of the treatment process were obtained, which based the cost analysis. The Impact Assessment Method used was the ReCiPe Endpoint (H) 2016, which assesses damage across three categories. The water, electricity and hypochlorite production processes were the most impactful in the categories of damage to human health, ecosystems and resources availability. These inputs production have an intense natural resources consumption and causes emissions into the environment. The highest expenses in pool maintenance were associated to human resources (worker) and chlorine purchase, followed by electricity. Scenarios were created to identify feasible changes to reduce the impacts. The waiver of water for replacement in the rainy season had greater potential for reducing impacts than the consumption changes in electricity and chlorine.

An optimal allocation model based on the regional ecological water requirements and multi-water supply characteristics: A case study of Shandong Province, China

Study regionShandong Province in China. Study focusMulti-water supply can alleviate regional water scarcity. However, the regional water usage weakens ecological water requirements owing to cost management. And the simplified optimal allocation model usually considers regional external water purchase cost or departmental water consumption cost individually, while neglecting differences of multi-water sources in water quality, quantity, and overall costs, resulting in unreasonable utilization. The present work calculated both rigid and flexible water requirements based on different ecological objectives. Meanwhile, the improved model considering water quantity, cost, and quality was constructed, and in comparison to simplified model and actual allocation scheme. New hydrological insights for the regionTaking Shandong Province in 2020 as a case study, the rigid and flexible ecological water requirements are 1.35 and 1.74 times higher than the actual usage, respectively, reflecting the insufficient actual ecological water use. Compared to the simplified models that do not distinguish water source, the improved model can not only consider departmental water consumption costs, but also regional external water purchase costs, and result in a more reasonable water allocation. Compared to the actual water usage scheme, the present scheme reduces the water usage of the Yellow River and increases the water usage of Eastern Route, resulting in a more reasonable water allocation overall improved efficiency.