Mixed integer non linear programming and artificial neural network based approach to ancillary services dispatch in competitive electricity markets

Ancillary services represent a good business opportunity that must be considered by market players. This paper presents a new methodology for ancillary services market dispatch. The method considers the bids submitted to the market and includes a market clearing mechanism based on deterministic optimization. An Artificial Neural Network is used for day-ahead prediction of Regulation Down, regulation-up, Spin Reserve and Non-Spin Reserve requirements. Two test cases based on California Independent System Operator data concerning dispatch of Regulation Down, Regulation Up, Spin Reserve and Non-Spin Reserve services are included in this paper to illustrate the application of the proposed method: (1) dispatch considering simple bids; (2) dispatch considering complex bids.

Neighbour list optimization for real LTE radio network

With the increasing complexity of current networks, it became evident the need for Self-Organizing Networks (SON), which aims to automate most of the associated radio planning and optimization tasks. Within SON, this paper aims to optimize the Neighbour Cell List (NCL) for Long Term Evolution (LTE) evolved NodeBs (eNBs). An algorithm composed by three decisions were were developed: distance-based, Radio Frequency (RF) measurement-based and Handover (HO) stats-based. The distance-based decision, proposes a new NCL taking account the eNB location and interference tiers, based in the quadrants method. The last two algorithms consider signal strength measurements and HO statistics, respectively; they also define a ranking to each eNB and neighbour relation addition/removal based on user defined constraints. The algorithms were developed and implemented over an already existent radio network optimization professional tool. Several case studies were produced using real data from a Portuguese LTE mobile operator. © 2014 IEEE.

Testing of Access Network's Internet Protocol Television Features

Testaus on tänä päivänä olennainen osa tuotekehitysprosessia koko tuotteen elinkaaren ajan, myös tietoliikennetekniikassa. Tietoverkoille asetetut tiukat vaatimukset ympärivuorokautisen toimivuuden suhteen nostavatmyös niiden testauksen tason ja laadun merkitystä. Erityisesti verkkojen uudet toiminnallisuudet, joilla ei ole vielä vuosia kestäneen käytön ja kehityksen tuomaa varmuus- ja laatutasoa, tuovat haasteita testauksen toteutukselle. Televisiokuvan välityksen Internetin yli mahdollistavat ominaisuudet ovat esimerkki tällaisista toiminnallisuuksista. Tässä diplomityössä käsitellään Tellabs Oy:n tuotekehitysosastolla vuosina 2005 ja 2006 toteutetun, erään operaattorin laajakaistaliityntäverkon päivitysprojektin testausosuutta. Kattavamman tarkastelun kohteena ovat erityisesti verkkoon lisättyjen laajakaistatelevisio- eli IPTV-toiminnallisuuksien integraatio- ja systeemitestausmenetelmät.

Artificial evolution on network structures : how time and space influence dynamics

Abstract The main objective of this work is to show how the choice of the temporal dimension and of the spatial structure of the population influences an artificial evolutionary process. In the field of Artificial Evolution we can observe a common trend in synchronously evolv¬ing panmictic populations, i.e., populations in which any individual can be recombined with any other individual. Already in the '90s, the works of Spiessens and Manderick, Sarma and De Jong, and Gorges-Schleuter have pointed out that, if a population is struc¬tured according to a mono- or bi-dimensional regular lattice, the evolutionary process shows a different dynamic with respect to the panmictic case. In particular, Sarma and De Jong have studied the selection pressure (i.e., the diffusion of a best individual when the only selection operator is active) induced by a regular bi-dimensional structure of the population, proposing a logistic modeling of the selection pressure curves. This model supposes that the diffusion of a best individual in a population follows an exponential law. We show that such a model is inadequate to describe the process, since the growth speed must be quadratic or sub-quadratic in the case of a bi-dimensional regular lattice. New linear and sub-quadratic models are proposed for modeling the selection pressure curves in, respectively, mono- and bi-dimensional regu¬lar structures. These models are extended to describe the process when asynchronous evolutions are employed. Different dynamics of the populations imply different search strategies of the resulting algorithm, when the evolutionary process is used to solve optimisation problems. A benchmark of both discrete and continuous test problems is used to study the search characteristics of the different topologies and updates of the populations. In the last decade, the pioneering studies of Watts and Strogatz have shown that most real networks, both in the biological and sociological worlds as well as in man-made structures, have mathematical properties that set them apart from regular and random structures. In particular, they introduced the concepts of small-world graphs, and they showed that this new family of structures has interesting computing capabilities. Populations structured according to these new topologies are proposed, and their evolutionary dynamics are studied and modeled. We also propose asynchronous evolutions for these structures, and the resulting evolutionary behaviors are investigated. Many man-made networks have grown, and are still growing incrementally, and explanations have been proposed for their actual shape, such as Albert and Barabasi's preferential attachment growth rule. However, many actual networks seem to have undergone some kind of Darwinian variation and selection. Thus, how these networks might have come to be selected is an interesting yet unanswered question. In the last part of this work, we show how a simple evolutionary algorithm can enable the emrgence o these kinds of structures for two prototypical problems of the automata networks world, the majority classification and the synchronisation problems. Synopsis L'objectif principal de ce travail est de montrer l'influence du choix de la dimension temporelle et de la structure spatiale d'une population sur un processus évolutionnaire artificiel. Dans le domaine de l'Evolution Artificielle on peut observer une tendence à évoluer d'une façon synchrone des populations panmictiques, où chaque individu peut être récombiné avec tout autre individu dans la population. Déjà dans les année '90, Spiessens et Manderick, Sarma et De Jong, et Gorges-Schleuter ont observé que, si une population possède une structure régulière mono- ou bi-dimensionnelle, le processus évolutionnaire montre une dynamique différente de celle d'une population panmictique. En particulier, Sarma et De Jong ont étudié la pression de sélection (c-à-d la diffusion d'un individu optimal quand seul l'opérateur de sélection est actif) induite par une structure régulière bi-dimensionnelle de la population, proposant une modélisation logistique des courbes de pression de sélection. Ce modèle suppose que la diffusion d'un individu optimal suit une loi exponentielle. On montre que ce modèle est inadéquat pour décrire ce phénomène, étant donné que la vitesse de croissance doit obéir à une loi quadratique ou sous-quadratique dans le cas d'une structure régulière bi-dimensionnelle. De nouveaux modèles linéaires et sous-quadratique sont proposés pour des structures mono- et bi-dimensionnelles. Ces modèles sont étendus pour décrire des processus évolutionnaires asynchrones. Différentes dynamiques de la population impliquent strategies différentes de recherche de l'algorithme résultant lorsque le processus évolutionnaire est utilisé pour résoudre des problèmes d'optimisation. Un ensemble de problèmes discrets et continus est utilisé pour étudier les charactéristiques de recherche des différentes topologies et mises à jour des populations. Ces dernières années, les études de Watts et Strogatz ont montré que beaucoup de réseaux, aussi bien dans les mondes biologiques et sociologiques que dans les structures produites par l'homme, ont des propriétés mathématiques qui les séparent à la fois des structures régulières et des structures aléatoires. En particulier, ils ont introduit la notion de graphe sm,all-world et ont montré que cette nouvelle famille de structures possède des intéressantes propriétés dynamiques. Des populations ayant ces nouvelles topologies sont proposés, et leurs dynamiques évolutionnaires sont étudiées et modélisées. Pour des populations ayant ces structures, des méthodes d'évolution asynchrone sont proposées, et la dynamique résultante est étudiée. Beaucoup de réseaux produits par l'homme se sont formés d'une façon incrémentale, et des explications pour leur forme actuelle ont été proposées, comme le preferential attachment de Albert et Barabàsi. Toutefois, beaucoup de réseaux existants doivent être le produit d'un processus de variation et sélection darwiniennes. Ainsi, la façon dont ces structures ont pu être sélectionnées est une question intéressante restée sans réponse. Dans la dernière partie de ce travail, on montre comment un simple processus évolutif artificiel permet à ce type de topologies d'émerger dans le cas de deux problèmes prototypiques des réseaux d'automates, les tâches de densité et de synchronisation.

Design of User Authentication System for Multi-operator wireless LANs

Langattomat lähiverkot ovat viime vuosikymmeninä saavuttaneet suuren suosion. Tässä työssä käsitellään käyttäjien todentamisjärjestelmän suunnittelua ja kehitystä langattomaan monioperaattoriverkkoon. Langattomassa monioperaattoriverkossa käyttäjillä on mahdollisuus käyttää eri operaattoreiden palveluita. Aluksi käsitellään olemassa olevia todentamismenetelmiä ja -järjestelmiä. minkä jälkeen kuvaillaan todentamisjärjestelmä langattomille monioperaattoriverkoille. Todentamisjärjestelmän ratkaisuvaihtoehtoja esitellään kaksi, niin sanotut moni- istunto - ja yksittäisistuntomalli. Moni-istuntomalli on normaali lähestymistapa käyttäjien todentamiseen tietokonejärjestelmissä. Siinä käyttäjän pitää tunnistautua ja todentaa itsensä jokaiselle verkon palvelulle erikseen. Yksittäisistuntomallissa pyritään parempaan luotettavuuteen ja käytettävyyteen. Siinä käyttäjä todentaa itsensä vain kerran ja voi sen jälkeen päästä useisiin palveluihin. Työn loppuosassa kuvaillaan suunnitellun järjestelmän toteutusta. Lisäksi ehdotetaan vaihtoehtoisia toteutustapoja, analysoidaan järjestelmän heikkouksia ja kerrotaan jatkokehitysmahdoillisuuksista.

The Role of Universities in the Triple Helix model of innovation management within the biotechnology industry, Case example: Turku Science Park Network

Biotechnology has been recognized as the key strategic technology for industrial growth. The industry is heavily dependent on basic research. Finland continues to rank in the top 10 of Europe's most innovative countries in terms of tax-policy, education system, infrastructure and the number of patents issued. Regardless of the excellent statistical results, the output of this innovativeness is below acceptable. Research on the issues hindering the output creation has already been done and the identifiable weaknesses in the Finland's National Innovation system are the non-existent growth of entrepreneurship and the missing internationalization. Finland is proven to have all the enablers of the innovation policy tools, but is lacking the incentives and rewards to push the enablers, such as knowledge and human capital, forward. Science Parks are the biggest operator in research institutes in the Finnish Science and Technology system. They exist with the purpose of speeding up the commercialization process of biotechnology innovations which usually include technological uncertainty, technical inexperience, business inexperience and high technology cost. Innovation management only internally is a rather historic approach, current trend drives towards open innovation model with strong triple helix linkages. The evident problems in the innovation management within the biotechnology industry are examined through a case study approach including analysis of the semi-structured interviews which included biotechnology and business expertise from Turku School of Economics. The results from the interviews supported the theoretical implications as well as conclusions derived from the pilot survey, which focused on the companies inside Turku Science Park network. One major issue that the Finland's National innovation system is struggling with is the fact that it is technology driven, not business pulled. Another problem is the university evaluation scale which focuses more on number of graduates and short-term factors, when it should put more emphasis on the cooperation success in the long-term, such as the triple helix connections with interaction and knowledge distribution. The results of this thesis indicated that there is indeed requirement for some structural changes in the Finland's National innovation system and innovation policy in order to generate successful biotechnology companies and innovation output. There is lack of joint output and scales of success, lack of people with experience, lack of language skills, lack of business knowledge and lack of growth companies.

The obstacles for cross-border transmission network investments in the Nordic electricity market: Case South-West link

The Nordic electricity market is often seen as an example of how to create a working, developed and integrated electricity market. Nevertheless, this thesis studies the obstacles of transmission network investments and the market integration challenges in the Nordic electricity market. The main focus is in the Nordic Transmission system operators (TSOs), which have a key role in grid development. This study introduces a case study of cancellation of South-West link, Western part, which was seen as essential grid investment in order to improve the Nordic electricity market functioning but ended up with cancellation in 2013. This study includes semi-structured theme interviews of the experts among Nordic electricity industry stakeholders. Despite the political will to create more equal prices for electricity in the Nordic market, the differing national regulation, mixed incentives created by bottleneck income and the focus moving from Nordic integration to European integration may create challenges to the Nordic electricity market integration in the future.

Evaluation of Machine Learning Classifiers for Mobile Network Intrusion Detection Systems

Mobile malwares are increasing with the growing number of Mobile users. Mobile malwares can perform several operations which lead to cybersecurity threats such as, stealing financial or personal information, installing malicious applications, sending premium SMS, creating backdoors, keylogging and crypto-ransomware attacks. Knowing the fact that there are many illegitimate Applications available on the App stores, most of the mobile users remain careless about the security of their Mobile devices and become the potential victim of these threats. Previous studies have shown that not every antivirus is capable of detecting all the threats; due to the fact that Mobile malwares use advance techniques to avoid detection. A Network-based IDS at the operator side will bring an extra layer of security to the subscribers and can detect many advanced threats by analyzing their traffic patterns. Machine Learning(ML) will provide the ability to these systems to detect unknown threats for which signatures are not yet known. This research is focused on the evaluation of Machine Learning classifiers in Network-based Intrusion detection systems for Mobile Networks. In this study, different techniques of Network-based intrusion detection with their advantages, disadvantages and state of the art in Hybrid solutions are discussed. Finally, a ML based NIDS is proposed which will work as a subsystem, to Network-based IDS deployed by Mobile Operators, that can help in detecting unknown threats and reducing false positives. In this research, several ML classifiers were implemented and evaluated. This study is focused on Android-based malwares, as Android is the most popular OS among users, hence most targeted by cyber criminals. Supervised ML algorithms based classifiers were built using the dataset which contained the labeled instances of relevant features. These features were extracted from the traffic generated by samples of several malware families and benign applications. These classifiers were able to detect malicious traffic patterns with the TPR upto 99.6% during Cross-validation test. Also, several experiments were conducted to detect unknown malware traffic and to detect false positives. These classifiers were able to detect unknown threats with the Accuracy of 97.5%. These classifiers could be integrated with current NIDS', which use signatures, statistical or knowledge-based techniques to detect malicious traffic. Technique to integrate the output from ML classifier with traditional NIDS is discussed and proposed for future work.

Multi-Objective Pipe Smoothing Genetic Algorithm For Water Distribution Network Design

This paper describes the formulation of a Multi-objective Pipe Smoothing Genetic Algorithm (MOPSGA) and its application to the least cost water distribution network design problem. Evolutionary Algorithms have been widely utilised for the optimisation of both theoretical and real-world non-linear optimisation problems, including water system design and maintenance problems. In this work we present a pipe smoothing based approach to the creation and mutation of chromosomes which utilises engineering expertise with the view to increasing the performance of the algorithm whilst promoting engineering feasibility within the population of solutions. MOPSGA is based upon the standard Non-dominated Sorting Genetic Algorithm-II (NSGA-II) and incorporates a modified population initialiser and mutation operator which directly targets elements of a network with the aim to increase network smoothness (in terms of progression from one diameter to the next) using network element awareness and an elementary heuristic. The pipe smoothing heuristic used in this algorithm is based upon a fundamental principle employed by water system engineers when designing water distribution pipe networks where the diameter of any pipe is never greater than the sum of the diameters of the pipes directly upstream resulting in the transition from large to small diameters from source to the extremities of the network. MOPSGA is assessed on a number of water distribution network benchmarks from the literature including some real-world based, large scale systems. The performance of MOPSGA is directly compared to that of NSGA-II with regard to solution quality, engineering feasibility (network smoothness) and computational efficiency. MOPSGA is shown to promote both engineering and hydraulic feasibility whilst attaining good infrastructure costs compared to NSGA-II.

An Efficient Codification to Solve Distribution Network Reconfiguration for Loss Reduction Problem

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

An efficient codification to solve distribution network reconfiguration for loss reduction problem

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Advanced network reconfiguration system applied to CEMIG-D system

In the network reconfiguration context, the challenge nowadays is to improve the system in order to get intelligent systems that are able to monitor the network and produce refined information to support the operator decisions in real time, this because the network is wide, ramified and in some places difficult to access. The objective of this paper is to present the first results of the network reconfiguration algorithm that has been developed to CEMIG-D. The algorithm's main idea is to provide a new network configuration, after an event (fault or study case), based on an initial condition and aiming to minimize the affected load, considering the restrictions of load flow equations, maximum capacity of the lines as well as equipments and substations, voltage limits and system radial operation. Initial tests were made considering real data from the system, provided by CEMIG-D and it reveals very promising results. © 2013 IEEE.

An emergy-based evaluation of a reverse logistics network for steel recycling

Efficient implementation of recycling networks requires appropriate logistical structures for managing the reverse flow of materials from users to producers. The steel sheet distributor studied had established a protocol for scrap recovery with the steel plant and its customers. The company invested in producing containers, hiring a specialized labor force and in purchasing trucks for container transportation to implement the logistics network for recycling. That network interconnected the company with two kinds of customers: the ones returning scrap and the ones who preferred to continue business-as-usual. The logistical network was analyzed using emergy synthesis, and the data obtained were used to evaluate and compare the system's environmental costs and benefits from the perspective of the distributor and the steel plant operator. The use of emergy ternary diagrams provided a way to assess recycle strategies to compare the relative economic and environmental benefits of the logistical network implemented. The minimum quantity of scrap that the distributor must recover to improve environmental benefits was determined allowing decision on whether it is worth keeping the system running. The new assessment method proposed also may help policy-makers to create strategies to reward or incentive users of reverse logistics, and help to establish regulations, by decreasing taxes or stimulating innovation, for effectively implement the National Policy on Solid Waste. (C) 2013 Elsevier Ltd. All rights reserved.

Decomposition Methods and Network Design Problems

Decomposition based approaches are recalled from primal and dual point of view. The possibility of building partially disaggregated reduced master problems is investigated. This extends the idea of aggregated-versus-disaggregated formulation to a gradual choice of alternative level of aggregation. Partial aggregation is applied to the linear multicommodity minimum cost flow problem. The possibility of having only partially aggregated bundles opens a wide range of alternatives with different trade-offs between the number of iterations and the required computation for solving it. This trade-off is explored for several sets of instances and the results are compared with the ones obtained by directly solving the natural node-arc formulation. An iterative solution process to the route assignment problem is proposed, based on the well-known Frank Wolfe algorithm. In order to provide a first feasible solution to the Frank Wolfe algorithm, a linear multicommodity min-cost flow problem is solved to optimality by using the decomposition techniques mentioned above. Solutions of this problem are useful for network orientation and design, especially in relation with public transportation systems as the Personal Rapid Transit. A single-commodity robust network design problem is addressed. In this, an undirected graph with edge costs is given together with a discrete set of balance matrices, representing different supply/demand scenarios. The goal is to determine the minimum cost installation of capacities on the edges such that the flow exchange is feasible for every scenario. A set of new instances that are computationally hard for the natural flow formulation are solved by means of a new heuristic algorithm. Finally, an efficient decomposition-based heuristic approach for a large scale stochastic unit commitment problem is presented. The addressed real-world stochastic problem employs at its core a deterministic unit commitment planning model developed by the California Independent System Operator (ISO).

Robust rolling stock in rapid transit network

This paper focuses on the railway rolling stock circulation problem in rapid transit networks, in which frequencies are high and distances are relatively short. Although the distances are not very large, service times are high due to the large number of intermediate stops required to allow proper passenger flow. The main complicating issue is the fact that the available capacity at depot stations is very low, and both capacity and rolling stock are shared between different train lines. This forces the introduction of empty train movements and rotation maneuvers, to ensure sufficient station capacity and rolling stock availability. However, these shunting operations may sometimes be difficult to perform and can easily malfunction, causing localized incidents that could propagate throughout the entire network due to cascading effects. This type of operation will be penalized with the goal of selectively avoiding them and ameliorating their high malfunction probabilities. Critic trains, defined as train services that come through stations that have a large number of passengers arriving at the platform during rush hours, are also introduced. We illustrate our model using computational experiments drawn from RENFE (the main Spanish operator of suburban passenger trains) in Madrid, Spain. The results of the model, achieved in approximately 1 min, have been received positively by RENFE planners