Distributed energy resources in an electricity retailer’s short-term profit optimization

Liberalization of electricity markets has resulted in a competed Nordic electricity market, in which electricity retailers play a key role as electricity suppliers, market intermediaries, and service providers. Although these roles may remain unchanged in the near future, the retailers’ operation may change fundamentally as a result of the emerging smart grid environment. Especially the increasing amount of distributed energy resources (DER), and improving opportunities for their control, are reshaping the operating environment of the retailers. This requires that the retailers’ operation models are developed to match the operating environment, in which the active use of DER plays a major role. Electricity retailers have a clientele, and they operate actively in the electricity markets, which makes them a natural market party to offer new services for end-users aiming at an efficient and market-based use of DER. From the retailer’s point of view, the active use of DER can provide means to adapt the operation to meet the challenges posed by the smart grid environment, and to pursue the ultimate objective of the retailer, which is to maximize the profit of operation. This doctoral dissertation introduces a methodology for the comprehensive use of DER in an electricity retailer’s short-term profit optimization that covers operation in a variety of marketplaces including day-ahead, intra-day, and reserve markets. The analysis results provide data of the key profit-making opportunities and the risks associated with different types of DER use. Therefore, the methodology may serve as an efficient tool for an experienced operator in the planning of the optimal market-based DER use. The key contributions of this doctoral dissertation lie in the analysis and development of the model that allows the retailer to benefit from profit-making opportunities brought by the use of DER in different marketplaces, but also to manage the major risks involved in the active use of DER. In addition, the dissertation introduces an analysis of the economic potential of DER control actions in different marketplaces including the day-ahead Elspot market, balancing power market, and the hourly market of Frequency Containment Reserve for Disturbances (FCR-D).

Optimization of Transportation System by Tailored Logistics Network: A Case Study in Automotive Industry

This thesis aims to redesign the supply chain system in an automotive industry in order to obtain space reduction in the inventory by using tailored logistics network. The redesigning process by tailored supply chain will combine all possible shipment methods including direct shipment, milk-run, milk-run via distribution center and Kanban delivery. The current supply chain system in Nissan goes rather well when the production volume is in moderate level. However, when the production volume is high, there is a capacity problem in the warehouse to accommodate all delivered parts from suppliers. Hence, the optimization of supply chain system is needed in order to obtain efficient logistics process and effective inventory consumption. The study will use primary data for both qualitative and quantitative approach as the research methods. Qualitative data will be collected by conducting interviews with people related to procurement and inventory control. Quantitative data consists of list of suppliers with their condition in several parameters which will be evaluated and analyzed by using scoring method to assign the most suitable transportation network to each suppliers for improvement of inventory reduction in a cost efficient manner.

Content-centered method for search engine optimization

Value of online business has grown to over one trillion USD. This thesis is about search engine optimization, which focus is to increase search engine rankings. Search engine optimization is an important branch of online marketing because the first page of search engine results is generating majority of the search traffic. Current articles about search engine optimization and Google are indicating that with the proper use of quality content, there is potential to improve search engine rankings. However, the existing search engine optimization literature is not noticing content at a sufficient level. To decrease that difference, the content-centered method for search engine optimization is constructed, and content in search engine optimization is studied. This content-centered method consists of three search engine optimization tactics: 1) content, 2) keywords, and 3) links. Two propositions were used for testing these tactics in a real business environment and results are suggesting that the content-centered method is improving search engine rankings. Search engine optimization is constantly changing because Google is adjusting its search algorithm regularly. Still, some long-term trends can be recognized. Google has said that content is growing its importance as a ranking factor in the future. The content-centered method is taking advance of this new trend in search engine optimization to be relevant for years to come.

GIS-based approach for optimization of onshore wind park infrastructure alignment in Finland

Wind power is a rapidly developing, low-emission form of energy production. In Fin-land, the official objective is to increase wind power capacity from the current 1 005 MW up to 3 500–4 000 MW by 2025. By the end of April 2015, the total capacity of all wind power project being planned in Finland had surpassed 11 000 MW. As the amount of projects in Finland is record high, an increasing amount of infrastructure is also being planned and constructed. Traditionally, these planning operations are conducted using manual and labor-intensive work methods that are prone to subjectivity. This study introduces a GIS-based methodology for determining optimal paths to sup-port the planning of onshore wind park infrastructure alignment in Nordanå-Lövböle wind park located on the island of Kemiönsaari in Southwest Finland. The presented methodology utilizes a least-cost path (LCP) algorithm for searching of optimal paths within a high resolution real-world terrain dataset derived from airborne lidar scannings. In addition, planning data is used to provide a realistic planning framework for the anal-ysis. In order to produce realistic results, the physiographic and planning datasets are standardized and weighted according to qualitative suitability assessments by utilizing methods and practices offered by multi-criteria evaluation (MCE). The results are pre-sented as scenarios to correspond various different planning objectives. Finally, the methodology is documented by using tools of Business Process Management (BPM). The results show that the presented methodology can be effectively used to search and identify extensive, 20 to 35 kilometers long networks of paths that correspond to certain optimization objectives in the study area. The utilization of high-resolution terrain data produces a more objective and more detailed path alignment plan. This study demon-strates that the presented methodology can be practically applied to support a wind power infrastructure alignment planning process. The six-phase structure of the method-ology allows straightforward incorporation of different optimization objectives. The methodology responds well to combining quantitative and qualitative data. Additional-ly, the careful documentation presents an example of how the methodology can be eval-uated and developed as a business process. This thesis also shows that more emphasis on the research of algorithm-based, more objective methods for the planning of infrastruc-ture alignment is desirable, as technological development has only recently started to realize the potential of these computational methods.

Content-centered method for search engine optimization

Value of online business has grown to over one trillion USD. This thesis is about search engine optimization, which focus is to increase search engine rankings. Search engine optimization is an important branch of online marketing because the first page of search engine results is generating majority of the search traffic. Current articles about search engine optimization and Google are indicating that with the proper use of quality content, there is potential to improve search engine rankings. However, the existing search engine optimization literature is not noticing content at a sufficient level. To decrease that difference, the content-centered method for search engine optimization is constructed, and content in search engine optimization is studied. This content-centered method consists of three search engine optimization tactics: 1) content, 2) keywords, and 3) links. Two propositions were used for testing these tactics in a real business environment and results are suggesting that the content-centered method is improving search engine rankings. Search engine optimization is constantly changing because Google is adjusting its search algorithm regularly. Still, some long-term trends can be recognized. Google has said that content is growing its importance as a ranking factor in the future. The content-centered method is taking advance of this new trend in search engine optimization to be relevant for years to come.

The investigation of the reduction mechanism of the 5a-reductase enzyme of Penicillium decumbens /

The 5a-reductase of Penicillium decumbens ATCC 10436 was used as a model for the mammalian enzyme to investigate the mechanism of reduction of testosterone to 5adihydrotestosterone . The purpose of this study was to search for specific 5a-reductase inhibitors which antagonize prostate cancer . In a whole-cell biotransformation mode, this organism reduced testosterone (1) to 5a-dihydrosteroids (8) and 5aandrostane- 3, 17-dione (9) in yields of 28% and 37% respectively. Control experiments have shown that 5aandrostane- 3, 17-dione (9) can be produced from the corresponding alcohol (8) in a subsequent reaction separate from that catalysed by the 5a-reductase enzyme . Androst-4- ene-3, 17-dione (2) is reduced to give only (9) with a recovery of 80% The stereochemistry of the reduction was determined by 500 MHz ^H NMR analysis of the products resulting from the deuterium labelled substrates. The results were obtained by an analysis of the NOE difference spectra, double-quantum filtered phase sensitive COSY 2-D spectra, and ^^c-Ir 2-D shift correlation spectra of deuterium labelled products. According to the unambiguous assignment of the signals due to H-4a and H-4Ii in 5a-dihydro steroids, the NMR data show clearly that addition of hydrogen to the 4{5)K bond has occurred in a trans manner at positions 413 and 5a. To Study the reduction mechanism of this enzyme, several substrates were prepared as following; 3-methyleneandrost-4-en- 17fi-ol(3), androst-4-en-17i5-ol(5) , androst-4-en-3ii, 17fi-diol (6) and 4, 5ii-epoxyandrostane-3, 17-dione (7) . Results suggest that this enzyme system requires an oxygen atom at the 3-position of the steroid in order to bind the substrate. Furthermore, the mechanism of this 5a-reductase may proceed via direct addition of hydrogen at the 4,5 position without involvement of a carbonyl group as an intermediate.

Histogram filtering as a tool in variational Monte Carlo optimization

Optimization of wave functions in quantum Monte Carlo is a difficult task because the statistical uncertainty inherent to the technique makes the absolute determination of the global minimum difficult. To optimize these wave functions we generate a large number of possible minima using many independently generated Monte Carlo ensembles and perform a conjugate gradient optimization. Then we construct histograms of the resulting nominally optimal parameter sets and "filter" them to identify which parameter sets "go together" to generate a local minimum. We follow with correlated-sampling verification runs to find the global minimum. We illustrate this technique for variance and variational energy optimization for a variety of wave functions for small systellls. For such optimized wave functions we calculate the variational energy and variance as well as various non-differential properties. The optimizations are either on par with or superior to determinations in the literature. Furthermore, we show that this technique is sufficiently robust that for molecules one may determine the optimal geometry at tIle same time as one optimizes the variational energy.

Molecular cloning restriction enzyme analysis, bovine adenovirus type 2 genome

Adenoviruses are non-enveloped icosahedral-shaped particles which possess a double-stranded DNA genome. Currently, nearly 100 serotypes of adenoviruses have been identified, 48 of which are of human origin. Bovine adenoviruses (BAVs), causing both mild respiratory and/or enteral diseases in cattle, have been reported in many countries all over the world. Currently, nine serotypes of SAVs have been isolated which have been placed into two subgroups based on a number of characteristics which include complement fixation tests as well as the ability to replicate in various cell lines. Bovine adenovirus type 2 (BAV2), belonging to subgroup I, is able to cause pneumonia as well as pneumonic-like symptoms in calves. In this study, the genome of BAV2 (strain No. 19) was subcloned into the plasmid vector pUC19. In total, 16 plasmids were constructed; three carry internal San fragments (spanning 3.1 to 65.2% ), and 10 carry internal Pstl fragments (spanning 4.9 to 97.4%), of the viral genome. Each of these plasmids was analyzed using twelve restriction endonucleases; BamHI, CiaI, EcoRl, HiOOlll, Kpnl, Noll, NS(N, Ps~, Pvul, Saj, Xbal, and Xhol. Terminal end fragments were also cloned and analyzed, sUbsequent to the removal of the 5' terminal protein, in the form of 2 BamHI B fragments, cloned in opposite orientations (spanning 0 to 18.1°k), and one Pstll fragment (spanning 97.4 to 1000/0). These cloned fragments, along with two other plasmids previously constructed carrying internal EcoRI fragments (spanning 20.6 to 90.5%), were then used to construct a detailed physical restriction map using the twelve restriction endonucleases, as well as to estimate the size of the genome for BAV2(32.5 Kbp). The DNA sequences of the early region 1 (E1) and hexon-associated gene (protein IX) have also been determined. The amino acid sequences of four open reading frames (ORFs) have been compared to those of the E1 proteins and protein IX from other Ads.

Optimization of the valence energy variance of the CuH molecule

We developed the concept of split-'t to deal with the large molecules (in terms of the number of electrons and nuclear charge Z). This naturally leads to partitioning the local energy into components due to each electron shell. The minimization of the variation of the valence shell local energy is used to optimize a simple two parameter CuH wave function. Molecular properties (spectroscopic constants and the dipole moment) are calculated for the optimized and nearly optimized wave functions using the Variational Quantum Monte Carlo method. Our best results are comparable to those from the single and double configuration interaction (SDCI) method.

Optimization of trial wave functions for use in quantum Monte Carlo with application to LiH

Methods for both partial and full optimization of wavefunction parameters are explored, and these are applied to the LiH molecule. A partial optimization can be easily performed with little difficulty. But to perform a full optimization we must avoid a wrong minimum, and deal with linear-dependency, time step-dependency and ensemble-dependency problems. Five basis sets are examined. The optimized wavefunction with a 3-function set gives a variational energy of -7.998 + 0.005 a.u., which is comparable to that (-7.990 + 0.003) 1 of Reynold's unoptimized \fin ( a double-~ set of eight functions). The optimized wavefunction with a double~ plus 3dz2 set gives ari energy of -8.052 + 0.003 a.u., which is comparable with the fixed-node energy (-8.059 + 0.004)1 of the \fin. The optimized double-~ function itself gives an energy of -8.049 + 0.002 a.u. Each number above was obtained on a Bourrghs 7900 mainframe computer with 14 -15 hrs CPU time.

The regulation of oat coleoptile phosphoenolpyruvate carboxylase and malic enzyme by Hâ ½ and metabolites : kinetic evidence for and against a cytosolic pH-stat

Phosphoenolpyruvate carboxylase (PEPC) and malic enzyme activities in soluble protein extracts of Avena coleoptiles were investigated to determine whether their kinetics were consistent with a role in cytosol pH regulation. Malic enzyme activity was specific for NADP+ and Mn2+. Maximal labelled product formation from [14C]-substrates required the presence of all coenzymes, cofactors and substrates. Plots of rate versus malate concentration, and linear transformations there- 2 of, indicated typical Michaelis-Menten kinetics at non-saturating malate levels and substrate inhibition at higher malate levels. pH increases between 6.5 and 7.25 increased near-optimal activity, decreased the degree of substrate inhibition and the Kmapp(Mn2+) but did not affect the Vmax or Kmapp(malate). Transformed data of PEPC activity demonstrated non-linear plots indicative of non-Michaelian kinetics. pH increases between 7.0 and 7.6 increased the Vmax and decreased the Km app (Mg2+) but did not affect the Kmapp(PEP). Various carboxylic acids and phosphorylated sugars inhibited PEPC and malic enzyme activities, and these effects decreased with pH increases. Metabolite inhibited malic enzyme activity was non-competitive and resulted mainly from Mn2+ chelation. In contrast, metabolite inhibited PEPC activity was unique for each compound tested, being variously dependent on the PEP concentration and the pH employed. These results indicate that fluctuations in pH and metabolite levels affect PEPC and malic enzyme activities similarly and that 3 the in vitro properties of PEPC are consistent with its proposed role in a pH-stat, whereas the in vitro properties of the malic enzyme cannot be interpreted in terms of a role in pH regulation.

Particle swarm optimization for two-connected networks with bounded rings

The Two-Connected Network with Bounded Ring (2CNBR) problem is a network design problem addressing the connection of servers to create a survivable network with limited redirections in the event of failures. Particle Swarm Optimization (PSO) is a stochastic population-based optimization technique modeled on the social behaviour of flocking birds or schooling fish. This thesis applies PSO to the 2CNBR problem. As PSO is originally designed to handle a continuous solution space, modification of the algorithm was necessary in order to adapt it for such a highly constrained discrete combinatorial optimization problem. Presented are an indirect transcription scheme for applying PSO to such discrete optimization problems and an oscillating mechanism for averting stagnation.

Bio-inspired optimization & sampling technique for side-chain packing in MCCE

The prediction of proteins' conformation helps to understand their exhibited functions, allows for modeling and allows for the possible synthesis of the studied protein. Our research is focused on a sub-problem of protein folding known as side-chain packing. Its computational complexity has been proven to be NP-Hard. The motivation behind our study is to offer the scientific community a means to obtain faster conformation approximations for small to large proteins over currently available methods. As the size of proteins increases, current techniques become unusable due to the exponential nature of the problem. We investigated the capabilities of a hybrid genetic algorithm / simulated annealing technique to predict the low-energy conformational states of various sized proteins and to generate statistical distributions of the studied proteins' molecular ensemble for pKa predictions. Our algorithm produced errors to experimental results within .acceptable margins and offered considerable speed up depending on the protein and on the rotameric states' resolution used.

(A) Optimization of solid body phase synthesis of RNA using the Cpep chemistry. (B) Synthesis of BODIPY labeled oligonucleotides

(A) Solid phase synthesis of oligonucleotides are well documented and are extensively studied as the demands continue to rise with the development of antisense, anti-gene, RNA interference, and aptamers. Although synthesis of RNA sequences faces many challenges, most notably the choice of the 2' -hydroxy protecting group, modified 2' -O-Cpep protected ribonucleotides were synthesized as alternitive building blocks. Altering phosphitylation procedures to incorporate 3' -N,N-diethyl phosphoramidites enhanced the overall reactivity, thus, increased the coupling efficiency without loss of integrety. Furthermore, technical optimizations of solid phase synthesis cycles were carried out to allow for successful synthesis of a homo UIO sequences with a stepwise coupling efficiency reaching 99% and a final yield of 91 %. (B) Over the past few decades, dipyrrometheneboron difluoride (BODIPY) has gained recognition as one of the most versatile fluorophores. Currently, BODIPY labeling of oligonucleotides are carried out post-synthetically and to date, there lacks a method that allows for direct incorporation of BODIPY into oligonucleotides during solid phase synthesis. Therefore, synthesis of BODIPY derived phosphoramidites will provide an alternative method in obtaining fluorescently labelled oligonucleotides. A method for the synthesis and incorporation of the BODIPY analogues into oligonucleotides by phosphoramidite chemistry-based solid phase DNA synthesis is reported here. Using this approach, BODIPY-labeled TlO homopolymer and ISIS 5132 were successfully synthesized.

Generating Aesthetically Pleasing Images in a Virtual Environment using Particle Swarm Optimization

This research focuses on generating aesthetically pleasing images in virtual environments using the particle swarm optimization (PSO) algorithm. The PSO is a stochastic population based search algorithm that is inspired by the flocking behavior of birds. In this research, we implement swarms of cameras flying through a virtual world in search of an image that is aesthetically pleasing. Virtual world exploration using particle swarm optimization is considered to be a new research area and is of interest to both the scientific and artistic communities. Aesthetic rules such as rule of thirds, subject matter, colour similarity and horizon line are all analyzed together as a multi-objective problem to analyze and solve with rendered images. A new multi-objective PSO algorithm, the sum of ranks PSO, is introduced. It is empirically compared to other single-objective and multi-objective swarm algorithms. An advantage of the sum of ranks PSO is that it is useful for solving high-dimensional problems within the context of this research. Throughout many experiments, we show that our approach is capable of automatically producing images satisfying a variety of supplied aesthetic criteria.