Analysis load forecasting of power system using fuzzy logic and artificial neural network

Load forecasting is a vital element in the energy management of function and execution purpose throughout the energy power system. Power systems problems are complicated to solve because power systems are huge complex graphically widely distributed and are influenced by many unexpected events. This paper presents the analysis of load forecasting using fuzzy logic (FL), artificial neural network (ANN) and ANFIS. These techniques are utilized for both short term and long-term load forecasting. ANN and ANFIS are used to improve the results obtained through the FL. It also studied the effects of humidity, temperature and previous load on Load Forecasting. The simulation is done by the Simulink environment of MATLAB software

Long –term load forecasting of power systems using Artificial Neural Network and ANFIS

Load forecasting is very important for planning and operation in power system energy management. It reinforces the energy efficiency and reliability of power systems. Problems of power systems are tough to solve because power systems are huge complex graphically, widely distributed and influenced by many unexpected events. It has taken into consideration the various demographic factors like weather, climate, and variation of load demands. In this paper, Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) models were used to analyse data collection obtained from the Metrological Department of Malaysia. The data sets cover a seven-year period (2009- 2016) on monthly basis. The ANN and ANFIS were used for long-term load forecasting. The performance evaluations of both models that were executed by showing that the results for ANFIS produced much more accurate results compared to ANN model. It also studied the effects of weather variables such as temperature, humidity, wind speed, rainfall, actual load and previous load on load forecasting. The simulation was carried out in the environment of MATLAB software

Optimum Allocation Of Capacitor And DG In MV Distribution Network Using PSO And OpenDSS

The optimum capacitor and distributed generation (DG) allocation in medium voltage (MV) distribution network utilizing particle swarm optimization (PSO) for selecting the optimum size and placement of (DG) units can significantly affect the distribution network. Capacitor installation is a standard method for reactive power compensation within a distribution network. The placement and sizing of the capacitor have been optimized in the distribution network for a number of capacitors with the objective of the voltage profile improvement and power loss minimization. Maximum and minimum bus voltage and possible maximum capacitor size were the constraints of the optimum capacitor and sizing problems, which take into account as a penalty factor (PF) within the objective function (OF) and the allocation of DG units. To solve the obtained OF, PSO and Open DSS engines were used in this research to analyse power flow results that obtained from the standard IEEE14 Bus system. The performance evaluation of PSO model was carried out by showing the results that the PSO algorithm. PSO can obtain the optimal solution of the size and location also find the optimum DG size for the loss minimization and voltage profile improvement compared to the standard case without DG and capacitor compensation. All simulations had been performed using MATLAB software

Analysis Load Forecasting of Power System Using of Fuzzy Logic and Artificial Neural Network

Load forecasting is a vital element in the energy management of function and execution purpose throughout the energy power system. Power systems problems are complicated to solve because power systems are huge complex graphically widely distributed and are influenced by many unexpected events. This paper presents the analysis of load forecasting using fuzzy logic (FL), artificial neural network (ANN) and ANFIS. These techniques are utilized for both short term and long-term load forecasting. ANN and ANFIS are used to improve the results obtained through the FL. It also studied the effects of humidity, temperature and previous load on Load Forecasting. The simulation is done by the Simulink environment of MATLAB software

Traditional Knowledge Evolution over Half of a Century: Local Herbal Resources and Their Changes in the Upper Susa Valley of Northwest Italy

Abstract: Susa Valley, located in the Italian Western Alps, has served as a meeting point for cultural, spiritual, and commercial exchange for a long period of history. The valley’s role as one of the main connecting routes between south and southwestern Europe resulted in its acquisition of a rich traditional ecological knowledge. However, like other Italian mountainous valleys, this valley has suffered from abandonment and depopulation in the past 50 years. Our study aims to investigate the current ethnobotanical medicinal knowledge in the valley and to compare our findings with a study conducted over 50 years ago in the same area. In 2018, we conducted 30 in-depth semi-structured in�terviews on medicinal plants and food-medicines used in the Susa Valley. We documented 36 species, of which 21 species were used for medical purposes and 15 species were used as food-medicine. The comparison with the previous study on medicinal herbs conducted in 1970 in the valley demonstrated a significant decrease in both the knowledge and use of medicinal plants, which could be attributed to socioeconomic, cultural, and possibly environmental changes that occurred in the past half-century. Our study highlights several promising species for future use as nutraceuticals, food, and medicinal products, such as Taraxacum officinale, Urtica dioica, and Artemisia genipi

Theoretical analysis of triple-pass erbium-doped fiber amplifier

Many configurations of EDFA producing triple pass EDFAs have been used, however, only two configurations are commonly used in the optical fiber communication system due to their high performance. Those two configurations are configured in a double stage EDFA. The first configuration is (configuration A) consists of a single-pass EDFA as the first stage and a double-pass EDFA as the second stage. The second configuration is (Configuration B) which consists of a double-pass EDFA as the first stage and a single-pass EDFA as the second stage. The Literature shows the use of triple pass EDFA is either with configuration A or configuration B and literature also shows there is no theoretical analysis and comparison between the performance of two Triple-pass EDFA configurations A and B. This paper focus on the performance analysis of both configurations A and B. The importantance of this research is the theoretical analyses that analyze the performance of those two configurations and illustrate a comparison between them. This comparison is important to show which of the two configurations is more reliable in amplifying optical signal for the fiber optic communication systems

Investigation of phytochemical components and bioautography of Garcinia mangostana L. methanol leaf extract

The aim of this work to identify chemical components of Garcinia mangostana leaves and test the antibacterial effect on Pseudomonas syringe pv. tomato and Xanthomonas oryzae pv. oryzae using bioautographic procedure. Phytochemical screening of methanolic extract showed that the leaf extract of G. mangostana rich in alkaloids, Flavonoids, Saponins, Tannins, Phenol, Terpenoids, Anthraquinone and Cardiac glycosides. A simple bioautographic procedure, involving spraying suspensions of the bacteria on thin layer chromatography (TLC) plates developed in solvents of varying polarities was used to detect the number of antibacterial compounds present in the extract. This activity was indicated by white spots against a red background on the TLC plates after spraying with 5% TTC aqueous solution. P. syringae and X. oryzae were inhibited by the most compounds separated on the TLC plates from the extract

Review of Erbium-doped fiber amplifier

Data communication systems are increasingly employing optical fiber communication systems (OFCS) as the transmission paths for information. Various types of optical amplifiers have been developed in OFCS to amplify optical signals. In particular, the Erbium-doped fiber amplifier (EDFA) is one example of an optical fiber amplifier that is widely known for use in amplifying optical signals. The most significant points in any optical amplifier design are gain and noise figure (NF). They are closely related to each other. Low NF and high gain are the main features for optimum amplifier (Desurvire, 1987). On the other hand, the gain and NF have very strong impact with EDFA’s configurations. Therefore, changes in EDFA’s configuration play very important role during the designing of optical amplifier. The literature shows that there is no study that has been done to review the EDF configuration. Therefore, in this paper we are presenting an overview of most of the EDFA’s configurations that have been proposed in order to provide the researchers with a clear view of what has been done in this field

Bitter Is Better: Wild Greens Used in the Blue Zone of Ikaria, Greece

The current study reports an ethnobotanical field investigation of traditionally gathered and consumed wild greens (Chorta) in one of the five so-called Blue Zones in the world: Ikaria Isle, Greece. Through 31 semi-structured interviews, a total of 56 wild green plants were documented along with their culinary uses, linguistic labels, and locally perceived tastes. Most of the gathered greens were described as bitter and associated with members of Asteraceae and Brassicaceae botanical families (31%), while among the top-quoted wild greens, species belonging to these two plant families accounted for 50% of the wild vegetables, which were consumed mostly cooked. Cross-cultural comparison with foraging in other areas of the central-eastern Mediterranean and the Near East demonstrated a remarkable overlapping of Ikarian greens with Cretan and Sicilian, as well as in the prevalence of bitter-tasting botanical genera. Important differences with other wild greens-related food heritage were found, most notably with the Armenian and Kurdish ones, which do not commonly feature many bitter greens. The proven role of extra-oral bitter taste receptors in the modulation of gastric emptying, glucose absorption and crosstalk with microbiota opens new ways of looking at these differences, in particular with regard to possible health implications. The present study is also an important attempt to preserve and document the bio-cultural gastronomic heritage of Chorta as a quintessential part of the Mediterranean diet. The study recommends that nutritionists, food scientists, and historians, as well as policymakers and practitioners, pay the required attention to traditional rural dietary systems as models of sustainable health

Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

Background: Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period. Methods: 22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution. Findings: Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5–65·1] decline), and increased during the COVID-19 pandemic period (2020–21; 5·1% [0·9–9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98–5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50–6·01) in 2019. An estimated 131 million (126–137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7–17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8–24·8), from 49·0 years (46·7–51·3) to 71·7 years (70·9–72·5). Global life expectancy at birth declined by 1·6 years (1·0–2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67–8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4–52·7]) and south Asia (26·3% [9·0–44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations. Interpretation: Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic