Daniel Gómez-Lorente

A new methodology for calculating roadway lighting design based on a multi-objective evolutionary algorithm

Highlights? The problem of uniformity and installation efficiency in public lighting is optimized. ? The most accurate values of height and spacing have been determined with NSGA-II. ? The results have been successfully compared with a well-known and reliable free software. This paper presents a new method for calculating the design of roadway lighting. Apart from its accuracy, this method, which is based on a multi-objective evolutionary algorithm, has the added advantage of enhancing the energy efficiency of lighting installations. This is positive because the economic use of energy resources is evidently a priority in the world today. In our study, an exhaustive calibration process was used to fine-tune the accuracy and precision of the new method presented. The results obtained were then compared with those of DIALUX, a well-known free software program that is frequently used for the design of lighting installations. In the second phase of this research, the lighting installation was made more complex in order to verify the applicability of this new method to a wide range of different contexts.

A simple method for designing efficient public lighting, based on new parameter relationships

Abstract New parameter relationships for public lighting design (i.e. average illuminance, luminaire spacing, and mounting height) were calculated from a large sample of data sets optimized with a multi-objective evolutionary algorithm. Optimization criteria included maximum energy efficiency and overall uniformity. The relations thus derived are a simple and elegant method for designing any type of public lighting installation without the need to use complex, expensive and/or unavailable software. It would therefore be desirable that manufacturers include such parameters in the product datasheet in order to make the calculation easier.

Evolutionary algorithms for the design of grid-connected PV-systems

The sale of electric energy generated by photovoltaic (PV) plants has attracted much attention in recent years. The installation of PV plants aims to obtain the maximum benefit of captured solar energy. The current methodologies for planning the design of the different components of a PV plant are not completely efficient. This paper addresses the optimization of the design of PV plants with solar tracking, which consists of the optimization of the variables that make up the PV plant to obtain the minimum electric (Joule) losses possible. These variables are the size and distribution of solar modules in the solar tracker, the distribution of the solar trackers in the field and the choice of inverter. Evolutionary algorithms (EAs) are adaptive methods based on natural evolution that may be used for searching and optimization. Four different EAs have been used for optimizing the design of PV plants: steady-state genetic algorithm, generational genetic algorithm, CHC algorithm and DE algorithm. In order to test the performance of these algorithms we have used different proposed fields to mount PV plants. The results obtained show that EAs, and specifically DE with rand mutation schemes, are promising techniques to optimize design of PV plants. Furthermore, the results are contrasted with nonparametric statistical tests to support our conclusions.

New rules of thumb maximizing energy efficiency in street lighting with discharge lamps: The general equations for lighting design

New relationships between energy efficiency, illuminance uniformity, spacing and mounting height in public lighting installations were derived from the analysis of a large sample of outputs generated with a widely used software application for lighting design. These new relationships greatly facilitate the calculation of basic lighting installation parameters. The results obtained are also based on maximal energy efficiency and illuminance uniformity as a premise, which are not included in more conventional methods. However, these factors are crucial since they ensure the sustainability of the installations. This research formulated, applied and analysed these new equations. The results of this study highlight their usefulness in rapid planning and urban planning in developing countries or areas affected by natural disasters where engineering facilities and computer applications for this purpose are often unavailable.

Grid-connected photovoltaic-systems design using evolutionary strategies

This paper addresses the problem of electrical losses that occur in the electrical conductors in photovoltaic (PV) plants with trackers. Thus, we propose a method which makes an optimal sizing and distribution of the elements that compose the PV to make the electrical losses by Joule effect as low as possible. To solve this problem, evolutionary algorithms implemented in matlab, have been used. Specifically the steady-state genetic algorithm (GA), the generational GA and the cross generational elitist selection, heterogeneous recombination and cataclism mutation (CHC) algorithm, which from random initial solutions, possibly far from optimal, will evolve into solutions that are increasingly closer to the desired optimum. Results have been very satisfactory, since all proposed examples have reduced by more than 40%, and CHC algorithm by more than 50%, electrical losses originated by not optimally designing the PV plant.