Stochastic Programming for Hub Energy Management Considering Uncertainty Using Two-Point Estimate Method and Optimization Algorithm

To maximize energy profit with the participation of electricity,natural gas,and district heating networks in the day-ahead market,stochastic scheduling of energy hubs taking into account the uncertainty of photovoltaic and wind resources,has been carried out.This has been done using a new meta-heuristic algorithm,improved artificial rabbits optimization(IARO).In this study,the uncertainty of solar and wind energy sources is modeled using Hang’s two-point estimating method(TPEM).The IARO algorithm is applied to calculate the best capacity of hub energy equipment,such as solar and wind renewable energy sources,combined heat and power(CHP)systems,steamboilers,energy storage,and electric cars in the day-aheadmarket.The standard ARO algorithmis developed to mimic the foraging behavior of rabbits,and in this work,the algorithm’s effectiveness in avoiding premature convergence is improved by using the dystudynamic inertia weight technique.The proposed IARO-based scheduling framework’s performance is evaluated against that of traditional ARO,particle swarm optimization(PSO),and salp swarm algorithm(SSA).The findings show that,in comparison to previous approaches,the suggested meta-heuristic scheduling framework based on the IARO has increased energy profit in day-ahead electricity,gas,and heating markets by satisfying the operational and energy hub limitations.Additionally,the results show that TPEM approach dependability consideration decreased hub energy’s profit by 8.995%as compared to deterministic planning.

Reproductive disturbances among Saudi adolescent girls and young women with type 1 diabetes mellitus

AIM To identify reproductive disturbances among adolescent girls and young women with type 1 diabetes mellitus(T1 DM) in Saudi Arabia.METHODS This cross sectional study was conducted among 102 female with T1 DM,(aged 13-29 years) who attended the Diabetes Clinic at Diabetes Treatment Center, Prince Sultan Military Medical City, Saudi Arabia between April 2015 to March 2016. Clinical history, anthropometric characteristics and reproductive disturbance were collected through a questionnaire.RESULTS Of 102 patients included in this analysis, 26.5%(27/102) were reported that they experienced an irregular menses. Of these patients, when compared to whose diabetes was diagnosed before menarche(35.4%, 17/48), patients diagnosed with diabetes after menarche(18.5%, 10/54) showed significantly less irregular menses(difference 16.9%, P = 0.04). Similarly, compared to patients diagnosed with diabetes prior to menarche(mean age 12.9 years; n = 48), patients diagnosed with diabetes after menarche(meanage 12.26 years; n = 54) were found to have 0.64 years delay in the age of menarche(P = 0.04). Among the studied patients, 15.7%(16/102) had polycystic ovary syndrome(PCOS). Of these PCOS patients, 37.5%(6/16) had irregular menses, 6.3%(1/16) had Celiac disease, 37.5%(6/16) had Hashimoto thyroiditis and 18.7%(3/16) had acne.CONCLUSION More than one fourth of the study population with T1 DM experiencing an irregular menses. Adolescent girls and young women diagnosed with diabetes prior to menarche showed higher menstrual irregularity and a delay in the age of menarche.