New configurations of power converters for grid interconnection systems

The increased penetration of renewable energy sources and other distributed energy sources has been seen nowadays. In this scenario power converters play a crucial role by providing the interconnection of these energy sources. This paper presents new configurations of power converters for grid interconnection systems. Several topologies are analyzed which are based on isolated ac-ac matrix converters

A bi-layer multi-time coordination method for optimal generation and reserve schedule and dispatch of a grid-connected microgrid

With the integration of more microgrids in distribution networks, its optimal autonomous operation becomes more important to reduce its operating cost and its influence on the main grid. This paper proposes a bi-layer multi-time coordination method for optimal generation and reserve schedule and dispatch of a grid-connected microgrid to reduce the impact of uncertainties of renewable sources, loads, and random component failures on power balance, operating costs, and system reliability. The reserve is refined into positive and negative reserves related to power shortage and power surplus. In the days ahead schedule layer, generating units are committed, and relaxed bidirectional reserve boundaries are predicted for the next day. In the real-time dispatch layer, generation output is dynamically adjusted and the reserve is dispatched using a successive approximation based on real-time data. A test microgrid is analyzed to illustrate the effectiveness of the proposed approach

Sistema de gestión de energía para una microrred con almacenamiento en baterías e incorporación de biomasa

This paper presents a quantitative dynamic model that can assess the response of a set of users to different Demand-Side Management strategies that are available. The main objective is to conceptualize, implement, and validate said model. As a result of a literature review, the model includes classical demand response techniques and proposes new customer actions and other novel aspects, such as energy culture and energy education. Based on the conceptualization of the model, this paper presents the structure that interrelates customer actions, demand proposals, cost-benefit analysis, and customer response. It also details the main aspects of the mathematical model, which was implemented in the Modelica modeling language. This paper includes simulations of intra-day and inter-day load shifting strategies using real data from the electricity sector in Colombia and different tariff factors. Finally, the results obtained show changes in daily consumption profiles, energy cost, system power peak, and load duration curve. Three conclusions are drawn: (i) Energy culture and pedagogy are essential to accelerate customer response time. (ii) The amount of the bill paid by customers decreases more quickly in the intra-day strategy than in its inter-day counterpart; in both cases, the cost reduction percentage is similar. (iii) Tariff increases accelerate customer response, and this relationship varies according to the Demand-Side Management strategies that are available.La implementación de fuentes no convencionales de generación de energía eléctrica se ha realizado por medio de microrredes, en las cuales los sistemas de gestión de energía juegan un papel importante, ya que, por medio de estos, se busca el suministro económico de potencia a la carga. El objetivo de este estudio fue el desarrollo de un sistema de gestión de energía que considera el comportamiento de un sistema gasificador-generador mediante el uso de modelos matemáticos en la generación de electricidad basada en biomasa en una microrred con inclusión de fuentes convencionales y no convencionales de generación de energía eléctrica, almacenamiento en baterías, respuesta a la demanda y conexión a la red para el suministro económico de potencia a la carga. Para ello, se realizó la formulación matemática, tanto de la función objetivo de optimización, como de las restricciones de las fuentes y cargas que componen la microrred, y se implementó un algoritmo en Matlab para la ejecución de simulaciones y obtención de resultados, los cuales mostraron que el sistema de gestión opera satisfactoriamente a la microrred aislada y conectada a la red, aprovechando la fuente de biomasa para atender a la carga en un entorno de operación económica, combinando cada una de las fuentes y almacenamiento que componen el sistema. Finalmente, el uso de modelos matemáticos permite la incorporación del comportamiento de fuentes como la biomasa en la generación de potencia para diferentes valores de parámetros como la humedad de la biomasa y el factor de aire en esquemas de gestión económica de microrredes

Two stages hybrid model of fuzzy linear regression with support vector machines for colorectal cancer

Fuzzy linear regression analysis has become popular among researchers and standard model in analyzing data in vagueness phenomena. However, the factor and symptoms to predict tumor size of colorectal cancer still ambiguous and not clear. The problem in using a linear regression will arise when uncertain data and not precise data were presented. Since the fuzzy set theory‟s concept can deal with data not to a precise point value (uncertainty data), fuzzy linear regression was applied. In this study, two new models for hybrid model namely the multiple linear regression clustering with support vector machine model (MLRCSVM) and fuzzy linear regression with symmetric parameter with support vector machine (FLRWSPCSVM) were proposed to analyze colorectal cancer data. Other than that, the parameter, error and explanation of the five procedures to both new models were included. These models applying five statistical models such as multiple linear regression, fuzzy linear regression, fuzzy linear regression with symmetric parameter, fuzzy linear regression with asymmetric parameter and support vector machine model. At first, the proposed models were applied to the 1000 simulated data. Furthermore, secondary data of 180 colorectal cancer patients who received treatment in general hospital with twenty five independent variables with different combination of variable types were considered to find the best models to predict the tumor size of CRC. The main objective of this study is to determine the best model to predicting the tumor size of CRC and to identify the factors and symptoms that contribute to the size of CRC. The comparisons among all the models were carried out to find the best model by using statistical measurements of mean square error (MSE), root mean square error (RMSE), mean absolute error (MAE) and mean absolute percentage error (MAPE). The results showed that the FLRWSPCSVM was found to be the best model, having the lowest MSE, RMSE, MAE and MAPE value by 100.605, 10.030, 7.556 and 14.769. Hence, the size of colorectal cancer could be predicted by managing twenty five independent variables

Robust Energy Management System Based on Interval Fuzzy Models

Artículo de publicación ISIEnergy management systems (EMSs) are used for operators to optimize, monitor, and control the performance of a power system. In microgrids, the EMS automatically coordinates the energy sources aiming to supply the demand. The coordination is carried out considering the operating costs, the available energy, and the generation and transmission capabilities of the grid. With this purpose, the available energy of the sources is predicted, and the operating costs are minimized. Thereby, an optimal operation of the microgrid is achieved. Often, the optimization procedure is executed throughout a receding horizon (model predictive control approach). Such approach provides some robustness to the microgrid operation. But, the high variability of the nonconventional energy sources makes the prediction task very complex. As a consequence, the reliable operation of the microgrid is compromised. In this paper, a scenario-based robust EMS is proposed. The scenarios are generated by means of fuzzy interval models. These models are used for solar power, wind power, and load forecasting. Since interval fuzzy models provide a range rather than a trajectory, upper and lower boundaries for these variables are obtained. Such boundaries are used to formulate the EMS as a robust optimization problem. In this sense, the solution obtained is robust against any realization of the uncertain variables inside the intervals defined by the fuzzy models. In addition, the original robust optimization problem is transformed into an equivalent second-order cone programming problem. Hence, desired mathematical properties such as the convexity of the optimization problem might be guaranteed. Therefore, efficient algorithms, based, e.g., on interior-point methods, could be applied to compute its solution. The proposed EMS is tested in the microgrid installed in Huatacondo, a settlement located at the north of Chile.Solar Energy Research Center SERC-Chile, CONICYT/FONDAP/ Project 15110019 National Fund for Science and Technology Project 1140775 Complex Engineering Systems Institute ICM: P-05-004-F CONICYT: FBO1