Unbalanced load flow with hybrid wavelet transform and support vector machine based Error-Correcting Output Codes for power quality disturbances classification including wind energy

Purpose. The most common methods to designa multiclass classification consist to determine a set of binary classifiers and to combine them. In this paper support vector machine with Error-Correcting Output Codes (ECOC-SVM) classifier is proposed to classify and characterize the power qualitydisturbances such as harmonic distortion,voltage sag, and voltage swell include wind farms generator in power transmission systems. Firstly three phases unbalanced load flow analysis is executed to calculate difference electric network characteristics, levels of voltage, active and reactive power. After, discrete wavelet transform is combined with the probabilistic ECOC-SVM model to construct the classifier. Finally, the ECOC-SVM classifies and identifies the disturbance type according tothe energy deviation of the discrete wavelet transform. The proposedmethod gives satisfactory accuracy with 99.2% compared with well known methods and shows that each power quality disturbances has specific deviations from the pure sinusoidal waveform,this is good at recognizing and specifies the type of disturbance generated from the wind power generator.Наиболее распространенные методы построения мультиклассовой классификации заключаются в определении набора двоичных классификаторов и их объединении. В данной статье предложена машина опорных векторов с классификатором выходных кодов исправления ошибок(ECOC-SVM) с целью классифицировать и характеризовать такие нарушения качества электроэнергии, как гармонические искажения, падение напряжения и скачок напряжения, включая генератор ветровых электростанций в системах передачи электроэнергии. Сначала выполняется анализ потока несимметричной нагрузки трех фаз для расчета разностных характеристик электрической сети, уровней напряжения, активной и реактивной мощности. После этого дискретное вейвлет-преобразование объединяется с вероятностной моделью ECOC-SVM для построения классификатора. Наконец, ECOC-SVM классифицирует и идентифицирует тип возмущения в соответствии с отклонением энергии дискретного вейвлет-преобразования. Предложенный метод дает удовлетворительную точность 99,2% по сравнению с хорошо известными методами и показывает, что каждое нарушение качества электроэнергии имеет определенные отклонения от чисто синусоидальной формы волны, что способствует распознаванию и определению типа возмущения, генерируемого ветровым генератором

Optimal Power Flow Solution of the Algerian Electrical Network using Differential Evolution Algorithm

This paper presents solution of optimal power flow (OPF) problem of a power system via differential evolution (DE) algorithm. The purpose of an electric power system is to deliver real power to the greatest number of users at the lowest possible cost all the time. So the objective is to minimize the total fuel cost of the generating units and also maintaining an acceptable system performance in terms of limits on generator reactive power outputs, bus voltages, static VAR compensator (SVC) parameters and overload in transmission lines. CPU times can be reduced by decomposing the problem in two subproblems, the first subproblem minimize the fuel cost of generation and the second subproblem is a reactive power dispatch so optimum bus voltages can be determined and reduce the losses by controlling tap changes of the transformers and the static VAR compensators (SVC). To verify the proposed approach and for comparison purposes, we perform simulations on the Algerian network with 114 buses, 175 branches (lines and transformers) and 15 generators. The obtained results indicate that DE is an easy to use, fast, robust and powerful optimization technique compared to the other global optimization methods such as PSO and GA

Particle Swarm Optimization Applied to the Economic Dispatch Problem

This paper presents solution of optimal power flow (OPF) problem of a power system via a simple particle swarm optimization (PSO) algorithm. The objective is to minimize the fuel cost and keep the power outputs of generators, bus voltages, shunt capacitors/reactors and transformers tap-setting in their secure limits.The effectiveness of PSO was compared to that of OPF by MATPOWER. The potential and superiority of PSO have been demonstrated through the results of IEEE 30-bus syste

SLIME MOULD ALGORITHM FOR PRACTICAL OPTIMAL POWER FLOW SOLUTIONS INCORPORATING STOCHASTIC WIND POWER AND STATIC VAR COMPENSATOR DEVICE

Purpose. This paper proposes the application procedure of a new metaheuristic technique in a practical electrical power system to solve optimal power flow problems, this technique namely the slime mould algorithm (SMA) which is inspired by the swarming behavior and morphology of slime mould in nature. This study aims to test and verify the effectiveness of the proposed algorithm to get good solutions for optimal power flow problems by incorporating stochastic wind power generation and static VAR compensators devices. In this context, different cases are considered in order to minimize the total generation cost, reduction of active power losses as well as improving voltage profile. Methodology. The objective function of our problem is considered to be the minimum the total costs of conventional power generation and stochastic wind power generation with satisfying the power system constraints. The stochastic wind power function considers the penalty cost due to the underestimation and the reserve cost due to the overestimation of available wind power. In this work, the function of Weibull probability density is used to model and characterize the distributions of wind speed. Practical value. The proposed algorithm was examined on the IEEE-30 bus system and a large Algerian electrical test system with 114 buses. In the cases with the objective is to minimize the conventional power generation, the achieved results in both of the testing power systems showed that the slime mould algorithm performs better than other existing optimization techniques. Additionally, the achieved results with incorporating the wind power and static VAR compensator devices illustrate the effectiveness and performances of the proposed algorithm compared to the ant lion optimizer algorithm in terms of convergence to the global optimal solution.Мета. У статті пропонується процедура застосування нового метаеврістіческого методу в реальній електроенергетичній системі для розв’язання задач оптимального потоку енергії, а саме алгоритму слизової цвілі, який заснований на поведінці рою і морфології слизової цвілі в природі. Дане дослідження спрямоване на тестування і перевірку ефективності запропонованого алгоритму для отримання хороших рішень для проблем оптимального потоку потужності шляхом включення пристроїв стохастичною вітрової генерації і статичних компенсаторів VAR. У зв'язку з цим, розглядаються різні випадки, щоб мінімізувати загальну вартість генерації, знизити втрати активної потужності і поліпшити профіль напруги. Методологія. В якості цільової функції завдання розглядається мінімальна сукупна вартість традиційної генерації електроенергії і стохастичної вітрової генерації при задоволенні обмежень енергосистеми. Стохастична функція енергії вітру враховує величини штрафів через недооцінку і резервні витрати через завищену оцінку доступної вітрової енергії. У даній роботі функція щільності ймовірності Вейбулла використовується для моделювання і характеристики розподілів швидкості вітру. Практична цінність. Запропонований алгоритм був перевірений на системі шин IEEE-30 і великий алжирської тестовій енергосистемі зі 114 шинами. У випадках, коли мета полягає в тому, щоб звести до мінімуму традиційне вироблення електроенергії, досягнуті результати в обох тестових енергосистемах показали, що алгоритм слизової цвілі функціонує краще, ніж інші існуючі методи оптимізації. Крім того, досягнуті результати з використанням вітрової енергії і статичного компенсатора VAR ілюструють ефективність і продуктивність запропонованого алгоритму в порівнянні з алгоритмом оптимізатора мурашиних левів з точки зору збіжності до глобального оптимального рішення

Non-invasive risk scores for prediction of type 2 diabetes (EPIC-InterAct) : a validation of existing models

Peer reviewe

Solving Bi-Objective Optimal Power Flow using Hybrid method of Biogeography-Based Optimization and Differential Evolution Algorithm: A case study of the Algerian Electrical Network

This paper proposes a new hybrid metaheuristique algorithm based on the hybridization of Biogeography-based optimization with the Differential Evolution for solving the optimal power flow problem with emission control. The biogeography-based optimization (BBO) algorithm is strongly influenced by equilibrium theory of island biogeography, mainly through two steps: Migration and Mutation. Differential Evolution (DE) is one of the best Evolutionary Algorithms for global optimization. The hybridization of these two methods is used to overcome traps of local optimal solutions and problems of time consumption. The objective of this paper is to minimize the total fuel cost of generation, total emission, total real power loss and also maintain an acceptable system performance in terms of limits on generator real power, bus voltages and power flow of transmission lines. In the present work, BBO/DE has been applied to solve the optimal power flow problems on IEEE 30-bus test system and the Algerian electrical network 114 bus. The results obtained from this method show better performances compared with DE, BBO and other well known metaheuristique and evolutionary optimization methods

Overview of Computerized Dietary Assessment Programs for Research and Practice in Nutrition Education

Computerized dietary assessment programs are often used for nutrition education research and practice. This article provides an informal overview of 29 dietary assessment programs mentioned in the literature covered by MEDLINE from 1996 to 2003, along with the components and capabilities of these programs derived from additional sources as needed. According to the literature, the advantages of using computers for dietary assessment include standardization of the questioning sequence, fast and easy processing, immediate results, and increased flexibility.The disadvantages include the need for typing skills and computer literacy, as well as potential bias in the responses if an interviewer is required

Plasma levels of six carotenoids in nine European countries: report from the European Prospective Investigation into Cancer and Nutrition (EPIC).

BACKGROUND: In addition to their possible direct biological effects, plasma carotenoids can be used as biochemical markers of fruit and vegetable consumption for identifying diet-disease associations in epidemiological studies. Few studies have compared levels of these carotenoids between countries in Europe. OBJECTIVE: Our aim was to assess the variability of plasma carotenoid levels within the cohort of the European Prospective Investigation into Cancer and Nutrition (EPIC). METHODS: Plasma levels of six carotenoids--alpha-carotene, beta-carotene, beta-cryptoxanthin, lycopene, lutein and zeaxanthin--were measured cross-sectionally in 3043 study subjects from 16 regions in nine European countries. We investigated the relative influence of gender, season, age, body mass index (BMI), alcohol intake and smoking status on plasma levels of the carotenoids. RESULTS: Mean plasma level of the sum of the six carotenoids varied twofold between regions (1.35 micromol l(-1) for men in Malm?weden vs. 2.79 micromol l(-1) for men in Ragusa/Naples, Italy; 1.61 micromol l(-1) for women in The Netherlands vs. 3.52 micromol l(-1) in Ragusa/Naples, Italy). Mean levels of individual carotenoids varied up to fourfold (alpha-carotene: 0.06 micromol l(-1) for men in Murcia, Spain vs. 0.25 micromol l(-1) for vegetarian men living in the UK). In multivariate regression analyses, region was the most important predictor of total plasma carotenoid level (partial R(2)=27.3%), followed by BMI (partial R(2)=5.2%), gender (partial R(2)=2.7%) and smoking status (partial R(2)=2.8%). Females had higher total carotenoid levels than males across Europe. CONCLUSIONS: Plasma levels of carotenoids vary substantially between 16 different regions in Italy, Greece, Spain, France, Germany, the UK, Sweden, Denmark and The Netherlands. Compared with region of residence, the other demographic and lifestyle factors and laboratory measurements have limited predictive value for plasma carotenoid levels in Europe

Plasma levels of six carotenoids in nine European countries: report from the European Prospective Investigation into Cancer and Nutrition (EPIC)

BACKGROUND: In addition to their possible direct biological effects, plasma carotenoids can be used as biochemical markers of fruit and vegetable consumption for identifying diet-disease associations in epidemiological studies. Few studies have compared levels of these carotenoids between countries in Europe. OBJECTIVE: Our aim was to assess the variability of plasma carotenoid levels within the cohort of the European Prospective Investigation into Cancer and Nutrition (EPIC). METHODS: Plasma levels of six carotenoids--alpha-carotene, beta-carotene, beta-cryptoxanthin, lycopene, lutein and zeaxanthin--were measured cross-sectionally in 3043 study subjects from 16 regions in nine European countries. We investigated the relative influence of gender, season, age, body mass index (BMI), alcohol intake and smoking status on plasma levels of the carotenoids. RESULTS: Mean plasma level of the sum of the six carotenoids varied twofold between regions (1.35 micromol l(-1) for men in Malmö, Sweden vs. 2.79 micromol l(-1) for men in Ragusa/Naples, Italy; 1.61 micromol l(-1) for women in The Netherlands vs. 3.52 micromol l(-1) in Ragusa/Naples, Italy). Mean levels of individual carotenoids varied up to fourfold (alpha-carotene: 0.06 micromol l(-1) for men in Murcia, Spain vs. 0.25 micromol l(-1) for vegetarian men living in the UK). In multivariate regression analyses, region was the most important predictor of total plasma carotenoid level (partial R(2)=27.3%), followed by BMI (partial R(2)=5.2%), gender (partial R(2)=2.7%) and smoking status (partial R(2)=2.8%). Females had higher total carotenoid levels than males across Europe. CONCLUSIONS: Plasma levels of carotenoids vary substantially between 16 different regions in Italy, Greece, Spain, France, Germany, the UK, Sweden, Denmark and The Netherlands. Compared with region of residence, the other demographic and lifestyle factors and laboratory measurements have limited predictive value for plasma carotenoid levels in Europe