Optimal Microgrid Topology Design and Siting of Distributed Generation Sources Using a Multi-Objective Substrate Layer Coral Reefs Optimization Algorithm

n this work, a problem of optimal placement of renewable generation and topology design for a Microgrid (MG) is tackled. The problem consists of determining the MG nodes where renewable energy generators must be optimally located and also the optimization of the MG topology design, i.e., deciding which nodes should be connected and deciding the lines’ optimal cross-sectional areas (CSA). For this purpose, a multi-objective optimization with two conflicting objectives has been used, utilizing the cost of the lines, C, higher as the lines’ CSA increases, and the MG energy losses, E, lower as the lines’ CSA increases. To characterize generators and loads connected to the nodes, on-site monitored annual energy generation and consumption profiles have been considered. Optimization has been carried out by using a novel multi-objective algorithm, the Multi-objective Substrate Layers Coral Reefs Optimization algorithm (Mo-SL-CRO). The performance of the proposed approach has been tested in a realistic simulation of a MG with 12 nodes, considering photovoltaic generators and micro-wind turbines as renewable energy generators, as well as the consumption loads from different commercial and industrial sites. We show that the proposed Mo-SL-CRO is able to solve the problem providing good solutions, better than other well-known multi-objective optimization techniques, such as NSGA-II or multi-objective Harmony Search algorithm.This research was partially funded by Ministerio de Economía, Industria y Competitividad, project number TIN2017-85887-C2-1-P and TIN2017-85887-C2-2-P, and by the Comunidad Autónoma de Madrid, project number S2013ICE-2933_02

Simulation of the behavior of bidders in first-price sealed-bid auctions on communication networks

Auction mechanisms have arisen as very efficient methods for scarce resource allocations. For this reason there is a current research topic based on the application of these economics mechanisms to the design of communication networks, mainly in the provision of QoS to new multimedia services. The main research works are oriented to the assignment and pricing rules, that is, the network resource assigned to the user (the bandwidth on a link, or the route of a traffic demand) and the amount of money it is going to cost to him respectively. However, as far as we know, there is a little research focused in the analysis of the behaviour of the user. Note that an auction is in fact a competition where the user will behave selfishly in order to obtain the greater profit. In this paper we present the first results of a simulator which analyzes the behaviour of the user in an auction over a communication link. They obtain the revenue of the auctioneer that is the network provider, and the resource allocation under different schemes of user behaviour, from a very conservative character up to most risky behaviours

A genetic algorithm for solving the first price sealed bid auction in communication networks

This paper shows the first result obtained in the application of economic mechanisms for the efficient assignment of resources in communication networks. The final objective is to determine which Service Provider will carry their traffic over the network of a Network Provider, which will be the most profitable route and which price the ISPs will pay for it to the Network provider. As the price is a key driver a good approach to select the ISP may be an auction mechanism. The implementation of these kind of auction mechanisms becomes a NP complete problem which is solved in this paper using novel metaheuristics, specifically a genetic algorithm

Novel heuristics for cell radius determination in WCDMA systems and their application to strategic planning studies

We propose and compare three novel heuristics for the calculation of the optimal cell radius in mobile networks based on Wideband Code Division Multiple Access (WCDMA) technology. The proposed heuristics solve the problem of the load assignment and cellular radius calculation. We have tested our approaches with experiments in multiservices scenarios showing that the proposed heuristics maximize the cell radius, providing the optimum load factor assignment. The main application of these algorithms is strategic planning studies, where an estimation of the number of Nodes B of the mobile operator, at a national level, is required for economic analysis. In this case due to the large number of different scenarios considered (cities, towns, and open areas) other methods than simulation need to be considered. As far as we know, there is no other similar method in the literature and therefore these heuristics may represent a novelty in strategic network planning studies. The proposed heuristics are implemented in a strategic planning software tool and an example of their application for a case in Spain is presented. The proposed heuristics are used for telecommunications regulatory studies in several countries

Desarrollo de un simulador celular a nivel de llamada para WCDMA

This article deals with the development of a cell simulator for WCDMA systems. The objective of this tool is to test the results of different algorithms for the cell radius calculation. This simulation tool is conceived on a call/connection level rather than on a packet level. This means that each user connection is considered as a single event independently of the type of service. The article also shows an independent tool for the cell radius calculation which results over different service scenarios are tested with the simulator. Finally the future enhancements of the simulator are presented

DIDERO 3G: herramienta para la planificación estratégica de redes móviles híbridas 2G/3G

This paper presents the project DIDERO 3G that the Telematic Engineering Group of the University of Cantabria is going to develop. The aim of DIDERO is to perform strategic network planning for an hybrid 2G/3G Mobile network to provide as a\ud result of this planning tecno-economical reports that could guide a mobile operator to take decissions about when and where to deploy 3G. DIDERO 3G can also serve the National Regulatory Atuhtorities as an objetvive basis to perform mobile regulatory issues. The structure and implementation of this project is discussed in this article

Ingeniería y Medicina: cuando uno más uno suma más que dos

La historia de los avances médicos está ligada al desarrollo de la ingeniería. No en pocas ocasiones, los avances en el conocimiento científico-médico han ido por delante de lo que la tecnología podía ofrecer y ha sido sólo, después de años de desarrollo, cuando se ha podido implementar el instrumento que satisfacía las necesidades concretas. En este artículo se pone de manifiesto la simbiosis entre la ingeniería y la medicina a lo largo de la historia y se centra en los avances significativos que han ocurrido en tres tecnologías clave en los últimos años: la robótica, las comunicaciones móviles 5G y la inteligencia artificial. Todo ello con aplicación, principalmente, al ámbito de la cirugía por ser, quizás, uno de los ámbitos donde ésta resulta más impactante. Además, se proporcionarán las claves fundamentales para poder entender el impacto actual y futuro de estas tecnologías.The history of medical advances is inevitably linked to the developments achieved in engineering. On many occasions, advances in scientific-medical knowledge have gone ahead of what technology could offer, and it has only been, after years of development, that it has been possible to implement the instrument that satisfies the specific needs. This article highlights the symbiosis between engineering and medicine throughout history and focuses on the significant advances that have occurred in three key technologies in recent years: robotics, 5G mobile communications, and artificial intelligence. All this mainly applied to the field of surgery as it is, perhaps, one of the fields where it is most impressive. In addition, fundamental keys to understand the current and future impact of these technologies will be outlined

Modelos de costes y regulación en redes y servicios de telecomunicación

This paper outlines the basis of the cost models applied to telecommunication networks. These models are mainly applied for three different purposes, interconnection tariffs, call terminating services and wholesale and retail service prices. Additionally a specific model, which is widely applied in traditional fixed networks like RDSI, named FL-LRIC is further explained and some applications and practical examples are exposed

Proyecto INEDAC: una herramienta para el cálculo de tarifas de interconexión basándose en un método bottom-up

This paper outlines the INEDAC (Interconnection to the network design, dimensioning and tariff and cost analysis) project. The aim of this project is to proporcionate to the NRA or to network operator a powerful tool to configure their networks, to calculate traffic tariff, to calculate interconnection tariff, or to optimize an implemented network

One-year-ahead energy demand estimation from macroeconomic variables using computational intelligence algorithms

This paper elaborates on a problem of one-year ahead estimation of energy demand based on macroeconomic variables. To this end, two different Computational Intelligence approaches are herein evaluated: (1) a modified Harmony Search (HS) optimization algorithm with an exponential prediction model and (2) an Extreme Learning Machine (ELM). In the case of the HS, a feature selection of the best set of features for the prediction is carried out jointly with the optimization of the model’s parameters. On the other hand, the ELM will be tested with and without the feature selection carried out by the HS approach. We describe several modifications on the proposed HS, which include a hybrid encoding with a binary part for the feature selection, and a real part to tune the parameters of the prediction model. Other adaptations focused on the HS operators are also introduced. The performance of both approaches has been assessed in a real application scenario, corresponding to the total energy demand estimation in Spain, in which we have 14 macroeconomic variables with history values for the last 30 years, including the recent crisis period starting in 2008. The performance of the proposed HS and ELM models incorporating feature selection is shown to provide an accurate one-year-ahead forecast at a higher prediction’s accuracy when compared to previous proposals in the literature. Specifically, the HS and ELM approaches are able to improve the results of a previous approach (based on a genetic algorithm), obtaining an improvement over 15% in this problem of energy demand estimation. As a final experimental evaluation of the proposed algorithm, a similar problem of one-year ahead CO 2 emissions estimation from macro-economic variables is also tackled, and also in this case the HS and ELM are able to obtain significant improvements over a previous approach based on evolutionary computation, over 10% of improvement in this problem.This work has been partially supported by the Spanish Ministry of Science and Innovation under Project Number ECO2010-22065-C03-02