M. Socorro García-Cascales

Evaluation of photovoltaic cells in a multi-criteria decision making process

The requirements to satisfy the energy needs of today without compromising those of future generations have forced humans to adopt rules that permit a better use of the available resources, of which the sun is an inexhaustible energy source. Amongst the energy sources that offer the possibility of exploiting the resources offered by the Earth, solar energy has acquired great strength. Photovoltaic energy has presented a major evolution and it is forecasted as being an important contributor to power generation and an alternative to other non-renewable energy sources. The high cost of solar electricity is today the main reason why electricity from photovoltaic systems has not been introduced in a more widespread way. In this context, the aim of this paper is the study and analysis of the decision criteria to be used when searching for the best photovoltaic cell, studying both the criteria that exert most influence or their manufacture (defined by quantitative and qualitative values) and the alternatives which will be the decision problem to be solved; each alternative will correspond to one type of photovoltaic cell. Thus, relevant information has been provided by three experts and the TOPSIS method has been used to aggregate all the information combined with the use of fuzzy sets which will model the use of linguistic labels in the process.

Exploring Innovative and Successful Applications of Soft Computing

Antonio D. Masegosa received a degree in Computer Engineering in 2005 and a PhD degree in Computer Sciences in 2010 from the School of Computer and Telecommunications Engineering, University of Granada, Spain. From 2010 he has been working as a post-doc researcher in the Center for ICT of the University of Granada. He has published one book and more than 20 papers in leading scientific journals, international and national conferences. He has participated in a wide variety of research projects and he is currently involved in two: Applicability of the Soft Computing in Advance Technology Environments: Sustainability and Intelligent Software Platform for Unification of Police Services. He has attended to numerous national and international conferences and he has been member of the organizing committee of the VI Nature Inspired Cooperative Strategies for Optimization Conference (NICSO2013). His research interest includes Intelligent Systems, Soft Computing, Metaheuristics, Cooperative Strategies for Optimization and Technology Foresight among others. Released: November 2013 An Excellent Addition to Your Library!

Decision Criteria for Optimal Location of Solar Plants: Photovoltaic and Thermoelectric

This chapter deals with the study and evaluation of decision criteria that should be considered for the optimal location of solar photovoltaic plants and solar thermal plants with high temperature and which are to be connected to the electricity distribution network. Criteria and subcriteria to be regarded will be of different nature, since environmental, geomorphologic, location, and strictly climatic criteria will all be considered, some of which are dependent on the technology being installed. Thus, we consider as possible alternatives the optimal locations and we will begin with a set of criteria, which must be evaluated for each of the possible alternatives for such a purpose, and includes both quantitative as well as qualitative information. As vaguely implied linguistic variables and numeric values have to be employed due to this disparity in the nature of the information, we will model the weights of the criteria by triangular fuzzy numbers. In order to reflect this and to carry out the extraction of knowledge a survey based on the fuzzy AHP methodology will be elaborated and sent to experts. In this way it will be possible to obtain the weights of the considered criteria for further evaluation of the alternatives.

An Analysis of Decision Criteria for the Selection of Military Training Aircrafts

The Spanish Minister of Defense needs to replace the current military training aircrafts by other models to meet current training needs in the Spanish Air Force Academy. In order to know the main features that the candidate aircrafts should have, there is a need to take into account the knowledge and experience of experts in this specific field, such as trained test pilots and flight instructors. In this way, it will be possible to recognize the main technical criteria to consider. This study shows a case study that allowed obtaining not only the preferences of an expert’s group, but also the importance of the considered criteria. Given that the criteria information provided by the experts has different nature, with qualitative criteria (human factors, flying and handling qualities, etc.) coexisting with quantitative criteria (service ceiling, stalling speed, endurance, etc.), the joint use of linguistic labels and numerical values is needed. Therefore, a survey focused on the fuzzy AHP (Analytic Hierarchy Process) methodology is proposed to extract the knowledge from the experts group and finally obtain a unique set of weights for the criteria.

Selection of a fuzzy AHP-TOPSIS electrification system for an isolated rural area in southern México

At present, there is a figure of more than 500 thousand houses and 42 thousand classrooms of public schools without electricity in rural and indigenous zones in Mexico. This is due to the fact that they are not connected to the electricity distribution network and as a consequence are the ones that are 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 who selected a survey were 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.

Geographic Information System for Optimization and Integration of Photovoltaic Solar Energy in Agricultural Areas with Energy Deficiency and Water Scarcity

The high cost of fossil fuels and the energy dependence of agriculture, primarily for use in irrigation groundwater, has been a serious challenge to agriculture in Spain. Other factors, such as the shortage of rainfall in the Mediterranean climate, increase the problem of water scarcity for farming in these areas. In response to this scenario, a sustainable development in rural areas is necessary, seeking to optimize the water and energy resources. As a useful tool to optimize and analyze natural resources, Geographic Information Systems (GIS) are proposed. GIS allow to provide crucial information, both physical and meteorological, of the study area and help in optimizing water resources and reducing energy consumption. Furthermore, the integration of renewable energy with GIS tools offer great potential in reducing greenhouse gas emissions (mainly CO2). This can be seen in the paper with an example of optimization in the integration of photovoltaic solar facilities in the rural and agricultural sector through the use of GIS.

Predictive Probabilistic Functions for Energy Prices as an Input in Monte Carlo Simulations

The continuous increase in energy costs and the volatility of energy prices are enforcing the implementation of energy efficiency measures (EEM) in companies. The choice of EEM in most cases is based on Pay-Back (PB) criteria, and in several cases on NPV and IRR criteria. In all these cases, it is necessary to estimate the price of energy in the following years so as to be able to study the profitability of the proposed EEM. Energy prices: electricity, biomass, petroleum, natural gas… change greatly throughout the period of a project, and their values are not easy to predict. If probabilistic functions are used to define the evolution of energy prices, in the period of the project, the economic parameters (PB, IRR, NPV) could also be obtained as probabilistic functions, by applying Monte Carlo Simulation Methods. This paper shows how to obtain the probabilistic functions that best describe the variation of energy prices in the period of a project, and how to apply the Monte Carlo Simulation Method to obtain a better approach to predicting future energy prices.

Obtaining the Decision Criteria and Evaluation of Optimal Sites for Renewable Energy Facilities Through a Decision Support System

In projects regarding renewable energy facilities, decision making is an essential activity that provides greater consistency and viability to the project. The first step that any promoter of such facilities should face is to select an optimal location. To do so, it is necessary to consider all the criteria that influence the decision. However, not all the criteria are equally important, which means that determining their weights is extremely important. The objective of this chapter is to obtain the weights of the decision criteria that influence the location problems of wind farms and solar photovoltaic and thermoelectric plants. For this, a Decision Support System (DSS) has been designed that allows to carry out the extraction of knowledge from an expert group by Fuzzy AHP methodology. Finally, DSS will sort the viable locations based on the importance of the criteria that influence the decision.

The TOPSIS Method and Its Application to Linguistic Variables

Most of the time, the input of the decision process is linguistic, but this is not the case for the output. For that reason, we have modified the TOPSIS model to make it so that the output of the process is the same as the input, that is to say linguistic. This proposal will be applied to the process of quality assessment and accreditation of the Industrial Engineering Schools within the Spanish university system.