Strategic Optimization Techniques For FRTU Deployment and Chip Physical Design

Combinatorial optimization is a complex engineering subject. Although formulation often depends on the nature of problems that differs from their setup, design, constraints, and implications, establishing a unifying framework is essential. This dissertation investigates the unique features of three important optimization problems that can span from small-scale design automation to large-scale power system planning: (1) Feeder remote terminal unit (FRTU) planning strategy by considering the cybersecurity of secondary distribution network in electrical distribution grid, (2) physical-level synthesis for microfluidic lab-on-a-chip, and (3) discrete gate sizing in very-large-scale integration (VLSI) circuit. First, an optimization technique by cross entropy is proposed to handle FRTU deployment in primary network considering cybersecurity of secondary distribution network. While it is constrained by monetary budget on the number of deployed FRTUs, the proposed algorithm identi?es pivotal locations of a distribution feeder to install the FRTUs in different time horizons. Then, multi-scale optimization techniques are proposed for digital micro?uidic lab-on-a-chip physical level synthesis. The proposed techniques handle the variation-aware lab-on-a-chip placement and routing co-design while satisfying all constraints, and considering contamination and defect. Last, the first fully polynomial time approximation scheme (FPTAS) is proposed for the delay driven discrete gate sizing problem, which explores the theoretical view since the existing works are heuristics with no performance guarantee. The intellectual contribution of the proposed methods establishes a novel paradigm bridging the gaps between professional communities.

Assessing the contribution of microgrids to the reliability of distribution networks

The emergence of microgeneration has recently lead to the concept of microgrid, a network of LV consumers and producers able to export electric energy in some circumstances and also to work in an isolated way in emergency situations. Research on the organization of microgrids, control devices, functionalities and other technical aspects is presently being carried out, in order to establish a consistent technical framework to support the concept. The successful development of the microgrid concept implies the definition of a suitable regulation for its integration on distribution systems. In order to define such a regulation, the identification of costs and benefits that microgrids may bring is a crucial task. Actually, this is the basis for a discussion about the way global costs could be divided among the different agents that benefit from the development of microgrids. Among other aspects, the effect of microgrids on the reliability of the distribution network has been pointed out as an important advantage, due to the ability of isolated operation in emergency situations. This paper identifies the situations where the existence of a microgrid may reduce the interruption rate and duration and thus improve the reliability indices of the distribution network. The relevant expressions necessary to quantify the reliability are presented. An illustrative example is included, where the global influence of the microgrid in the reliability is commented.

A grouping model for distributed pipeline assets maintenance decision

Distributed pipeline assets systems are crucial to society. The deterioration of these assets and the optimal allocation of limited budget for their maintenance correspond to crucial challenges for water utility managers. Decision makers should be assisted with optimal solutions to select the best maintenance plan concerning available resources and management strategies. Much research effort has been dedicated to the development of optimal strategies for maintenance of water pipes. Most of the maintenance strategies are intended for scheduling individual water pipe. Consideration of optimal group scheduling replacement jobs for groups of pipes or other linear assets has so far not received much attention in literature. It is a common practice that replacement planners select two or three pipes manually with ambiguous criteria to group into one replacement job. This is obviously not the best solution for job grouping and may not be cost effective, especially when total cost can be up to multiple million dollars. In this paper, an optimal group scheduling scheme with three decision criteria for distributed pipeline assets maintenance decision is proposed. A Maintenance Grouping Optimization (MGO) model with multiple criteria is developed. An immediate challenge of such modeling is to deal with scalability of vast combinatorial solution space. To address this issue, a modified genetic algorithm is developed together with a Judgment Matrix. This Judgment Matrix is corresponding to various combinations of pipe replacement schedules. An industrial case study based on a section of a real water distribution network was conducted to test the new model. The results of the case study show that new schedule generated a significant cost reduction compared with the schedule without grouping pipes.

Protection of distributed generation interfaced networks

With the rapid increase in electrical energy demand, power generation in the form of distributed generation is becoming more important. However, the connections of distributed generators (DGs) to a distribution network or a microgrid can create several protection issues. The protection of these networks using protective devices based only on current is a challenging task due to the change in fault current levels and fault current direction. The isolation of a faulted segment from such networks will be difficult if converter interfaced DGs are connected as these DGs limit their output currents during the fault. Furthermore, if DG sources are intermittent, the current sensing protective relays are difficult to set since fault current changes with time depending on the availability of DG sources. The system restoration after a fault occurs is also a challenging protection issue in a converter interfaced DG connected distribution network or a microgrid. Usually, all the DGs will be disconnected immediately after a fault in the network. The safety of personnel and equipment of the distribution network, reclosing with DGs and arc extinction are the major reasons for these DG disconnections. In this thesis, an inverse time admittance (ITA) relay is proposed to protect a distribution network or a microgrid which has several converter interfaced DG connections. The ITA relay is capable of detecting faults and isolating a faulted segment from the network, allowing unfaulted segments to operate either in grid connected or islanded mode operations. The relay does not make the tripping decision based on only the fault current. It also uses the voltage at the relay location. Therefore, the ITA relay can be used effectively in a DG connected network in which fault current level is low or fault current level changes with time. Different case studies are considered to evaluate the performance of the ITA relays in comparison to some of the existing protection schemes. The relay performance is evaluated in different types of distribution networks: radial, the IEEE 34 node test feeder and a mesh network. The results are validated through PSCAD simulations and MATLAB calculations. Several experimental tests are carried out to validate the numerical results in a laboratory test feeder by implementing the ITA relay in LabVIEW. Furthermore, a novel control strategy based on fold back current control is proposed for a converter interfaced DG to overcome the problems associated with the system restoration. The control strategy enables the self extinction of arc if the fault is a temporary arc fault. This also helps in self system restoration if DG capacity is sufficient to supply the load. The coordination with reclosers without disconnecting the DGs from the network is discussed. This results in increased reliability in the network by reduction of customer outages.

A new technique for optimal allocation and sizing of capacitors and setting of LTC

An iterative based strategy is proposed for finding the optimal rating and location of fixed and switched capacitors in distribution networks. The substation Load Tap Changer tap is also set during this procedure. A Modified Discrete Particle Swarm Optimization is employed in the proposed strategy. The objective function is composed of the distribution line loss cost and the capacitors investment cost. The line loss is calculated using estimation of the load duration curve to multiple levels. The constraints are the bus voltage and the feeder current which should be maintained within their standard range. For validation of the proposed method, two case studies are tested. The first case study is the semi-urban 37-bus distribution system which is connected at bus 2 of the Roy Billinton Test System which is located in the secondary side of a 33/11 kV distribution substation. The second case is a 33 kV distribution network based on the modification of the 18-bus IEEE distribution system. The results are compared with prior publications to illustrate the accuracy of the proposed strategy.

Storage - the necessity for a Smart-Grid

Energy policy is driving renewable energy deployment with most of the developed countries having some form of renewable energy portfolio standard and emissions reduction target. To deliver upon these ambitious targets, those renewable energy technologies that are commercially available, such as wind and solar, are being deployed, but inherently have issues with intermittency of supply. To overcome these issues, storage options will need to be introduced into the distribution network with benefits for both demand management and power systems quality. How this can be utilised most effectively within the distribution network will allow for an even greater proportion of our energy demand to be met through renewable resources and meet the aspirational targets set. The distribution network will become a network of smart-grids, but to work efficiently and effectively, power quality issues surrounding intermittency must be overcome, with storage being a major factor in this solution.

A model predictive approach for community battery energy storage system optimization

This paper presents an efficient algorithm for optimizing the operation of battery storage in a low voltage distribution network with a high penetration of PV generation. A predictive control solution is presented that uses wavelet neural networks to predict the load and PV generation at hourly intervals for twelve hours into the future. The load and generation forecast, and the previous twelve hours of load and generation history, is used to assemble load profile. A diurnal charging profile can be compactly represented by a vector of Fourier coefficients allowing a direct search optimization algorithm to be applied. The optimal profile is updated hourly allowing the state of charge profile to respond to changing forecasts in load.

Approximation of Bayesian predictive p-values with regression ABC

In the Bayesian framework a standard approach to model criticism is to compare some function of the observed data to a reference predictive distribution. The result of the comparison can be summarized in the form of a p-value, and it's well known that computation of some kinds of Bayesian predictive p-values can be challenging. The use of regression adjustment approximate Bayesian computation (ABC) methods is explored for this task. Two problems are considered. The first is the calibration of posterior predictive p-values so that they are uniformly distributed under some reference distribution for the data. Computation is difficult because the calibration process requires repeated approximation of the posterior for different data sets under the reference distribution. The second problem considered is approximation of distributions of prior predictive p-values for the purpose of choosing weakly informative priors in the case where the model checking statistic is expensive to compute. Here the computation is difficult because of the need to repeatedly sample from a prior predictive distribution for different values of a prior hyperparameter. In both these problems we argue that high accuracy in the computations is not required, which makes fast approximations such as regression adjustment ABC very useful. We illustrate our methods with several samples.

Infrastructure Disputes Shape Future of Streaming Media

In November 2010, tension between Internet infrastructure companies boiled over in a dispute between content distribution network (CDN) Level 3 and Internet service provider (ISP) Comcast. Level 3, a distribution partner of Netflix, accused Comcast of violating the principles of net neutrality when the ISP increased distribution fees for carrying high bandwidth services. Comcast justified its actions by stating that the price increase was standard practice and argued Level 3 was trying to avoid paying its fair share. The dispute exemplifies the growing concern over the rising costs of streaming media services. The companies facing these inflated infrastructure costs are CDNs (Level 3, Equinix, Limelight, Akamai, and Voxel), companies that host streaming media content on server farms and distribute the content to a variety of carriers, and ISPs (Comcast, Time Warner, Cox, and AT&T), the cable and phone companies that provide “last mile” service to paying customers. Both CDNs and ISPs are lobbying government regulators to keep their costs at a minimum. The outcome of these disputes will influence the cost, quality, and legal status of streaming media.

Ammatillinen osaaminen ja täydennyskoulutus : tiedon ja osaamisen leviäminen osallistujien välillä

The goal of my research was to describe how adult students perceive professional knowledge and know-how, and how these diffuse among a group of students during a continuing education program. The goal was also to research the meaning of shared working life experience in improving the professional know-how of the students. My research is positioned in the field of supporting environments for adult learning with an emphasis on interaction between students in social networks. The participants of my research were 31 adult students taking part in continuing education program at the time of my study. I gathered the research data using quantitative and qualitative research methods. Quantitative network enquiry led me to do 9 theme interviews. I analyzed the data using a network analyzing program and a content analyzing method. I examined the whole community of students, the home groups of four students and the main actors who were central for the community. The analysis focused on the distribution network of professional knowledge and know-how, the distribution network of social support and the network of reciprocal interaction. Professional knowledge and know-how that diffuse between adult students in continuing education, is mostly hands-on tips and occupational experience. The factors that promote the distribution of professional experience and know-how are structural ones and factors that emphasize co-operation relationships. The structural factors are participation in adult education and in home groups and also organizational arrangements of learning. The factors that emphasize co-operation relationships are encouragement and doing learning assignments together. The central distributors of professional know-how are adult students who have long working life experience. The meaning of the diffusion of professional experience and know-how for improving professional know-how of a single adult student is in developing his professional identity and adding his social capital. In the social interaction networks, which I studied, more relations exist inside the home groups than between them, which is congruent with earlier researches. My research can be utilized by using its research methods and emphasizing its results in adult education planning and guidance.

Analysis of cool roof coatings for residential demand side management in tropical Australia

Cool roof coatings have a beneficial impact on reducing the heat load of a range of building types, resulting in reduced cooling energy loads. This study seeks to understand the extent to which cool roof coatings could be used as a residential demand side management (DSM) strategy for retrofitting existing housing in a constrained network area in tropical Australia where peak electrical demand is heavily influenced by residential cooling loads. In particular this study seeks to determine whether simulation software used for building regulation purposes can provide networks with the ‘impact certainty’ required by their DSM principles. The building simulation method is supported by a field experiment. Both numerical and experimental data confirm reductions in total consumption (kWh) and energy demand (kW). The nature of the regulated simulation software, combined with the diverse nature of residential buildings and their patterns of occupancy, however, mean that simulated results cannot be extrapolated to quantify benefits to a broader distribution network. The study suggests that building data gained from regulatory simulations could be a useful guide for potential impacts of widespread application of cool roof coatings in this region. The practical realization of these positive impacts, however, would require changes to the current business model for the evaluation of DSM strategies. The study provides seven key recommendations that encourage distribution networks to think beyond their infrastructure boundaries, recognising that the broader energy system also includes buildings, appliances and people.

Yläsäiliön sijainnin vaikutus verkoston kustannuksiin

Engl. summary: Influence of elevated tank location on costs of water distribution network

Determining Top K Nodes in Social Networks using the Shapley Value

In this paper, we consider the problem of selecting, for any given positive integer k, the top-k nodes in a social network, based on a certain measure appropriate for the social network. This problem is relevant in many settings such as analysis of co-authorship networks, diffusion of information, viral marketing, etc. However, in most situations, this problem turns out to be NP-hard. The existing approaches for solving this problem are based on approximation algorithms and assume that the objective function is sub-modular. In this paper, we propose a novel and intuitive algorithm based on the Shapley value, for efficiently computing an approximate solution to this problem. Our proposed algorithm does not use the sub-modularity of the underlying objective function and hence it is a general approach. We demonstrate the efficacy of the algorithm using a co-authorship data set from e-print arXiv (www.arxiv.org), having 8361 authors.