Advanced energy efficient coordinated multi-point transmission for OFDMA

The ever-growing energy consumption in mobile networks stimulated by the expected growth in data tra ffic has provided the impetus for mobile operators to refocus network design, planning and deployment towards reducing the cost per bit, whilst at the same time providing a signifi cant step towards reducing their operational expenditure. As a step towards incorporating cost-eff ective mobile system, 3GPP LTE-Advanced has adopted the coordinated multi-point (CoMP) transmission technique due to its ability to mitigate and manage inter-cell interference (ICI). Using CoMP the cell average and cell edge throughput are boosted. However, there is room for reducing energy consumption further by exploiting the inherent exibility of dynamic resource allocation protocols. To this end packet scheduler plays the central role in determining the overall performance of the 3GPP longterm evolution (LTE) based on packet-switching operation and provide a potential research playground for optimizing energy consumption in future networks. In this thesis we investigate the baseline performance for down link CoMP using traditional scheduling approaches, and subsequently go beyond and propose novel energy e fficient scheduling (EES) strategies that can achieve power-e fficient transmission to the UEs whilst enabling both system energy effi ciency gain and fairness improvement. However, ICI can still be prominent when multiple nodes use common resources with di fferent power levels inside the cell, as in the so called heterogeneous networks (Het- Net) environment. HetNets are comprised of two or more tiers of cells. The rst, or higher tier, is a traditional deployment of cell sites, often referred to in this context as macrocells. The lower tiers are termed small cells, and can appear as microcell, picocells or femtocells. The HetNet has attracted signiffi cant interest by key manufacturers as one of the enablers for high speed data at low cost. Research until now has revealed several key hurdles that must be overcome before HetNets can achieve their full potential: bottlenecks in the backhaul must be alleviated, as well as their seamless interworking with CoMP. In this thesis we explore exactly the latter hurdle, and present innovative ideas on advancing CoMP to work in synergy with HetNet deployment, complemented by a novel resource allocation policy for HetNet tighter interference management. As system level simulator has been used to analyze the proposed algorithm/protocols, and results have concluded that up to 20% energy gain can be observed.

Combined heat and power and consumption optimization in a SCADA-based system

The operation of power systems in a Smart Grid (SG) context brings new opportunities to consumers as active players, in order to fully reach the SG advantages. In this context, concepts as smart homes or smart buildings are promising approaches to perform the optimization of the consumption, while reducing the electricity costs. This paper proposes an intelligent methodology to support the consumption optimization of an industrial consumer, which has a Combined Heat and Power (CHP) facility. A SCADA (Supervisory Control and Data Acquisition) system developed by the authors is used to support the implementation of the proposed methodology. An optimization algorithm implemented in the system in order to perform the determination of the optimal consumption and CHP levels in each instant, according to the Demand Response (DR) opportunities. The paper includes a case study with several scenarios of consumption and heat demand in the context of a DR event which specifies a maximum demand level for the consumer.

Optimization techniques for power distribution planning with uncertainties: a comparative study

Important research effort has been devoted to the topic of optimal planning of distribution systems. The non linear nature of the system, the need to consider a large number of scenarios and the increasing necessity to deal with uncertainties make optimal planning in distribution systems a difficult task. Heuristic techniques approaches have been proposed to deal with these issues, overcoming some of the inherent difficulties of classic methodologies. This paper considers several methodologies used to address planning problems of electrical power distribution networks, namely mixedinteger linear programming (MILP), ant colony algorithms (AC), genetic algorithms (GA), tabu search (TS), branch exchange (BE), simulated annealing (SA) and the Bender´s decomposition deterministic non-linear optimization technique (BD). Adequacy of theses techniques to deal with uncertainties is discussed. The behaviour of each optimization technique is compared from the point of view of the obtained solution and of the methodology performance. The paper presents results of the application of these optimization techniques to a real case of a 10-kV electrical distribution system with 201 nodes that feeds an urban area.

Reactive power compensation by EPSO technique

This paper presents a methodology to address reactive power compensation using Evolutionary Particle Swarm Optimization (EPSO) technique programmed in the MATLAB environment. The main objective is to find the best operation point minimizing power losses with reactive power compensation, subjected to all operational constraints, namely full AC power flow equations, active and reactive power generation constraints. The methodology has been tested with the IEEE 14 bus test system demonstrating the ability and effectiveness of the proposed approach to handle the reactive power compensation problem.

A probabilistic methodology for distributed generation location in isolated electrical service area

Distributed generation unlike centralized electrical generation aims to generate electrical energy on small scale as near as possible to load centers, interchanging electric power with the network. This work presents a probabilistic methodology conceived to assist the electric system planning engineers in the selection of the distributed generation location, taking into account the hourly load changes or the daily load cycle. The hourly load centers, for each of the different hourly load scenarios, are calculated deterministically. These location points, properly weighted according to their load magnitude, are used to calculate the best fit probability distribution. This distribution is used to determine the maximum likelihood perimeter of the area where each source distributed generation point should preferably be located by the planning engineers. This takes into account, for example, the availability and the cost of the land lots, which are factors of special relevance in urban areas, as well as several obstacles important for the final selection of the candidates of the distributed generation points. The proposed methodology has been applied to a real case, assuming three different bivariate probability distributions: the Gaussian distribution, a bivariate version of Freund’s exponential distribution and the Weibull probability distribution. The methodology algorithm has been programmed in MATLAB. Results are presented and discussed for the application of the methodology to a realistic case and demonstrate the ability of the proposed methodology for efficiently handling the determination of the best location of the distributed generation and their corresponding distribution networks.

Offshore wind turbine simulation: multibody drive train. Bacl-to-back NPC (Neutral Point Clamped) converters: Fractional-order control

This paper is on offshore wind energy conversion systems installed on the deep water and equipped with back-to-back neutral point clamped full-power converter, permanent magnet synchronous generator with an AC link. The model for the drive train is a five-mass model which incorporates the dynamic of the structure and the tower in order to emulate the effect of the moving surface. A three-level converter and a four-level converter are the two options with a fractional-order control strategy considered to equip the conversion system. Simulation studies are carried out to assess the quality of the energy injected into the electric grid. Finally, conclusions are presented. (C) 2014 Elsevier Ltd. All rights reserved.

Assessment of heavy metals in the surroundings of coal-fired power plant

This paper aims to survey metal concentrations in soils in the vicinity of a coal-firedpower plant located in southwest of Portugal. Two annual sampling campaigns were carried out to measure a hypothetical soil contamination around the coal plant. The sampling area was divided into two subareas, both centered in the emission source, delimited by two concentric circles with radius of 6 km and 20 km. About 40 samplings points were defined in the influence area. Metals measurements were performed with a portable analytical X-ray dispersive energy fluorescence spectrometer identifying about 20 different elements in each sampling point. The most relevant elements measured included As, Cu, Fe, Hg, Pb, Ti and Zn in both sampling areas. Considering the results obtained in the first sampling campaign, arsenic is predominantly higher within the 6-20 km sampling area. The second sampling campaign showed that both sampling areas presented relatively similar metal concentrations except for Fe, Mn, Sr and Zn which concentration is higher within the 6-20 km sampling area. Also, As, Fe, Mn and Ti concentrations decreased significantly from the first to the second sampling campaign and their concentration were predominately higher in the NE-E and E-SE directions.

Evaluation of the Electric Vehicle Impact in the Power Demand Curve in a Smart Grid Environment

Smart grids with an intensive penetration of distributed energy resources will play an important role in future power system scenarios. The intermittent nature of renewable energy sources brings new challenges, requiring an efficient management of those sources. Additional storage resources can be beneficially used to address this problem; the massive use of electric vehicles, particularly of vehicle-to-grid (usually referred as gridable vehicles or V2G), becomes a very relevant issue. This paper addresses the impact of Electric Vehicles (EVs) in system operation costs and in power demand curve for a distribution network with large penetration of Distributed Generation (DG) units. An efficient management methodology for EVs charging and discharging is proposed, considering a multi-objective optimization problem. The main goals of the proposed methodology are: to minimize the system operation costs and to minimize the difference between the minimum and maximum system demand (leveling the power demand curve). The proposed methodology perform the day-ahead scheduling of distributed energy resources in a distribution network with high penetration of DG and a large number of electric vehicles. It is used a 32-bus distribution network in the case study section considering different scenarios of EVs penetration to analyze their impact in the network and in the other energy resources management.

Reliable and Fast Hand-Offs in Low-Power Wireless Networks

Hand-off (or hand-over), the process where mobile nodes select the best access point available to transfer data, has been well studied in wireless networks. The performance of a hand-off process depends on the specific characteristics of the wireless links. In the case of low-power wireless networks, hand-off decisions must be carefully taken by considering the unique properties of inexpensive low-power radios. This paper addresses the design, implementation and evaluation of smart-HOP, a hand-off mechanism tailored for low-power wireless networks. This work has three main contributions. First, it formulates the hard hand-off process for low-power networks (such as typical wireless sensor networks - WSNs) with a probabilistic model, to investigate the impact of the most relevant channel parameters through an analytical approach. Second, it confirms the probabilistic model through simulation and further elaborates on the impact of several hand-off parameters. Third, it fine-tunes the most relevant hand-off parameters via an extended set of experiments, in a realistic experimental scenario. The evaluation shows that smart-HOP performs well in the transitional region while achieving more than 98 percent relative delivery ratio and hand-off delays in the order of a few tens of a milliseconds.

DC Fuzzy Multicriteria Approach to Increase the Probability of Delivering Power in Distribution Networks

This paper proposes a methodology to increase the probability of delivering power to any load point through the identification of new investments. The methodology uses a fuzzy set approach to model the uncertainty of outage parameters, load and generation. A DC fuzzy multicriteria optimization model considering the Pareto front and based on mixed integer non-linear optimization programming is developed in order to identify the adequate investments in distribution networks components which allow increasing the probability of delivering power to all customers in the distribution network at the minimum possible cost for the system operator, while minimizing the non supplied energy cost. To illustrate the application of the proposed methodology, the paper includes a case study which considers an 33 bus distribution network.

Decision support tool for Virtual Power Players: Hybrid Particle Swarm Optimization applied to Day-ahead Vehicle-To-Grid Scheduling

This paper presents a decision support tool methodology to help virtual power players (VPPs) in the Smart Grid (SGs) context to solve the day-ahead energy resource scheduling considering the intensive use of Distributed Generation (DG) and Vehicle-To-Grid (V2G). The main focus is the application of a new hybrid method combing a particle swarm approach and a deterministic technique based on mixedinteger linear programming (MILP) to solve the day-ahead scheduling minimizing total operation costs from the aggregator point of view. A realistic mathematical formulation, considering the electric network constraints and V2G charging and discharging efficiencies is presented. Full AC power flow calculation is included in the hybrid method to allow taking into account the network constraints. A case study with a 33-bus distribution network and 1800 V2G resources is used to illustrate the performance of the proposed method.

Increase of the Delivered Power Probability in Distribution Networks using Pareto DC Programming

A methodology to increase the probability of delivering power to any load point through the identification of new investments in distribution network components is proposed in this paper. The method minimizes the investment cost as well as the cost of energy not supplied in the network. A DC optimization model based on mixed integer non-linear programming is developed considering the Pareto front technique in order to identify the adequate investments in distribution networks components which allow increasing the probability of delivering power for any customer in the distribution system at the minimum possible cost for the system operator, while minimizing the energy not supplied cost. Thus, a multi-objective problem is formulated. To illustrate the application of the proposed methodology, the paper includes a case study which considers a 180 bus distribution network

Power to Gas - sähköenergiasta luonnonkaasua, liiketoimintamahdollisuudet Suomessa

Uusiutuvan sähköntuotannon osuuden kasvaessa kasvaa tarve tasata sähköntuotannon ja kulutuksen vaihteluita varastoimalla sähköä. Power to Gas (PtG) - sähköenergiasta luonnonkaasua tarjoaa yhden mahdollisuuden varastoida sähköä. Sähköä käytetään veden elektrolyysiin, jossa syntynyt vety käytetään metanoinissa yhdessä hiilidioksidin kanssa muodostamaan korvaavaa luonnonkaasua. Näin syntynyttä korvaava luonnonkaasua sähköstä kutsutaan e-SNG-kaasuksi. Tässä työssä tutkitaan PtG-laitoksen investointi, käyttö- ja kunnossapitokuluja. Työssä luodaan laskentamalli, jolla lasketaan PtG-laitoksen neljälle käyttötapaukselle kannattavuuslaskelma. Käyttötapauksille lasketaan myös herkkyystarkasteluja. Kannattavuuslaskelmien perusteella päätellään PtG-laitoksen liiketoimintamahdollisuudet Suomessa. Työssä laskettujen kannattavuuslaskelmien perusteella PtG-laitoksen perustapausten liiketoimintamahdollisuudet ovat huonot. Laskettujen herkkyystarkastelujen perusteella havaittiin, että investointikulut, laitoksen ajoaika ja lisätulot hapesta ja lämmöstä ovat kannattavuuden kannalta kriittisimmät menestystekijät.

A maximum likelihood framework for protein design

Affiliation: Claudia Kleinman, Nicolas Rodrigue & Hervé Philippe : Département de biochimie, Faculté de médecine, Université de Montréal

Promoting while checking self-interest : a conflict-based governance approach to rebalance corporate power disequilibria in Canada and the United States

La délégation du pouvoir de gestion aux administrateurs et aux gestionnaires, une caractéristique intrinsèque à la gestion efficace de grandes entreprises dans un contexte de capitalisme, confère une grande discrétion à l’équipe de direction. Cette discrétion, si elle n’est pas surveillée, peut mener à des comportements opportunistes envers la corporation, les actionnaires et les autres fournisseurs de capital qui n’ont pas de pouvoir de gestion. Les conflits entre ces deux classes d’agents peuvent émerger à la fois de décisions de gouvernance générale ou de transactions particulières (ie. offre publique d’achat). Dans les cas extrêmes, ces conflits peuvent mener à la faillite de la firme. Dans les cas plus typiques, ils mènent l’extraction de bénéfices privés pour les administrateurs et gestionnaires, l’expropriation des actionnaires, et des réductions de valeur pour la firme. Nous prenons le point de vue d’un petit actionnaire minoritaire pour explorer les méchanismes de gouvernance disponibles au Canada et aux États‐Unis. Après une synthèse dans la Partie 1 des théories sous‐jacentes à l’étude du pouvoir dans la corporation (séparation de la propriété et du contrôle et les conflits d’agence), nous concentrons notre analyse dans la Partie 2 sur les différents types de méchanismes (1) de gouvernance interne, (2) juridiques et (3) marchands, qui confèrent du pouvoir aux deux classes d’agents. Nous examinons comment les intérêts de ces deux classes peuvent être réalignés afin de prévenir et résoudre les conflits au sein de la firme. La Partie 3 explore un équilibre dynamique de pouvoir corporatif qui cherche à minimiser le potentiel d’opportunisme toute en préservant une quantité de discrétion suffisante pour la gestion efficace de la firme. Nous analysons des moyens pour renforcer les protections des actionnaires minoritaires et proposons un survol des pistes de réforme possibles.