Session Program

Abstract - Solar Photovoltaics is a source of energy very sensitive to climate variations. Therefore, it is very important to apply a forecasting method to a PV system. Solar forecasting provides extremely useful information for tasks such as management of electricity grids and solar energy trading, where good accuracy and good performance are desirable goals for a very short term forecasting model. In this paper, we propose the use of fuzzy time series (FTS) techniques to this problem. Specifically, Chen's first order and high-order FTS methods and the Weighted FTS method are compared with other forecasting models widely used to approach solar irradiance forecasting. We evaluate the performance of FTS methods and different forecasting techniques to solve very short-term solar forecasting problems. The results show that FTS methods are able to achieve significant improvements in forecasting accuracy and performance if compared to other forecasting methods. A discussion on how to improve the forecasting performance of FTS models is also provided.

Abstract - Vendor managed inventory (VMI) is one of the well-known strategies of merchandizing between suppliers and retailers. The essential aspect in VMI model is to fulfill the demand of the retailers by the suppliers. Since, the costs of items are highly volatile, it is not possible to design a VMI model with deterministic demand. In this paper, we have considered one supplier and retailer to perform business of multi-product under VMI model with uncertain demand. Thus, it proposes a novel VMI model, termed as 'interval type-2 fuzzy vendor managed inventory (IT2 FVMI) model' that considers interval type-2 fuzzy number to represent the uncertain demand. The objective is to minimize the total cost of VMI by finding the optimum ordered quantity and backordered level. We develop a particle swarm optimization algorithm based solution approach to solve it. A suitable real-world application is considered to perform the simulation. We have considered different number of instances of the products to obtain the results. By comparing the results with the deterministic demand and type-1 fuzzy number, we show the efficacy of our proposed IT2 FVMI model.

Abstract - This paper proposes positioning control technique for a lab-scale heliostat by application of hybrid stepper motors and fuzzy logic controllers. Steady state tracking error has been kept minimal by micro step drive together with speed control by multi stepping rate adjustment. By supportive video streaming device and image processing, a reflected image of illuminant area on the target is captured and analyzed, an obtaining position error in azimuth and altitude angles are real-time fed to the fuzzy controllers. As a result, the closed loop tracking is formulated and steady state error can then be minimized. Simulation and experimental results confirm the proposed technique.

Abstract - At present there are more than 500 thousand houses and 42 thousand classrooms of public schools without electricity in rural and indigenous zones in Mexico. This is because they are not connected to the electricity distribution network, and as a consequence they are the ones most in need of electrification projects. Taking this problem into account, this work models and applies a Fuzzy AHP-TOPSIS multicriteria decision method to select the most appropriate electrification system in a rural area located in the south of Mexico. The AHP method is used to calculate the weights and the TOPSIS method is used to obtain the ranking of the alternatives. To carry out this study, a group of three experts in the Mexican energy field that responded to a survey have been selected. Data were obtained through the corresponding authorities and the families that make up the community. As a result, it was found that a photovoltaic system of 1 kWp isolated was the best alternative to supply electricity to each of the 300 families that make up the community of Cerro Hermoso.

Abstract - The Personalized Route Problem resembles the so-called multi-criteria Shortest Path Problem where every arc (street) of the graph (map) has a set of costs (values) associated to a set of criteria (features). The personalization of the path comes when the user a) determines how important is each criterion according to personal preferences and b) indicates constraints on the criteria values. The preferences are often uncertain, imprecise or inexact. Also, it seems reasonable to allow some relaxation on the constraints. We propose and define a new model for the Personalized Route Problem with fuzzy constraints. As an example, we show its application to the Shortest Path Route with fuzzy constraints on the slopes values.

Abstract - Selecting and evaluating the suppliers represent a very complex task, because a wide range of attributions must be taken into consideration and many of them are difficult to be made objectively quantified. The aim of this research is to provide a new model based on fuzzy signatures for selecting and evaluating the critical parts for the production.