This thesis aims to examine internal and external parameters influencing Russian energy policy between 2000 and 2012. In this respect first energy policy of the Soviet Union and Russian Federation in 1990&rsquo / s are evaluated. In this framework it is assumed that old experiences and structures have influence on 2000&rsquo / s Russian Energy Policy. Russian energy profile is accepted not only a strength of Russia but also a source of limitation in Russian energy policy, it influences domestic and foreign energy policies of the country. Following the energy profile of Russia domestic energy policy of Russia is analyzed. In this respect, elite level perception on energy and use of hydrocarbon rents are important points taken into account. In addition to that, major Russian energy companies are analyzed, because they do not cross border drawn by Russian Administration. About Russian foreign energy policy, important actions and patterns about use of energy rent are evaluated / key countries for Russian energy resources are analyzed. In this respect, it is regarded that contrary to views of some scholars who consider Russian energy policy as the by product of Russian foreign policy, this thesis argues that Russian energy policy has been determined by the characteristics of Russian energy structure and domestic politics in addition to Russian foreign policy priorities. As a result issues like Russian economy, domestic developments in Russia, Russian foreign policy and international developments like emergence of new suppliers and markets, have influence on Russian energy policy and because of harmonization of energy and foreign policy, Russian energy policy carries realist features.

Real options have been widely applied to analyze investment planning and asset valuation under uncertainty in many industries, especially energy markets. Because of their close analogy to financial options, real options can be valued using the classical financial option pricing theories and their extensions. However, as real options valuation often involves complex payoff structures and operational constraints of the underlying real assets or projects, accurate and flexible methods for solving the valuation problem are essential. This thesis investigates three different approaches to real options valuation and contributes to aspects of modeling realism and computational efficiency. The contributions are illustrated through two important applications of real options in energy markets: natural gas storage and power plant valuation. Because spread options are commonly used in basic real options valuation techniques, the first part of the thesis addresses the problems of spread option pricing and hedging. We develop a new closed-form approximation method for pricing two-asset spread options. Numerical analysis shows that our method is more accurate than existing analytical approximations. Our method is also extremely fast, with computing time more than two orders of magnitude shorter than one-dimensional numerical integration. Closed-form approximations for the Greeks of spread options are also developed. In addition, we analyze the price sensitivities of spread options and provide lower and upper bounds for digital spread options. We then further generalize the above results to multi-asset spread options on an arbitrary number of assets. We provide two new closed-form approximation methods for pricing spread options on a basket of risky assets: the extended Kirk approximation and the second-order boundary approximation. Numerical analysis shows that both methods are extremely fast and accurate, with the latter method more accurate than the former. Closed-form approximations for important Greeks are also derived. Because our approximation methods enable the accurate pricing of a bulk volume of spread options on two or more assets in real time, it offers traders a potential edge in a dynamic market environment. In the third part of this thesis, we propose a market-based valuation framework for valuing natural gas storage facility with realistic operational characteristics. The operational process is modeled as a multi-stage stochastic optimization problem. We develop a Gaussian quadrature scheme to solve for the dynamically optimal spot trading strategy and show that the computational efficiency of this method exceeds existing approaches in about two orders of magnitude. Furthermore, with this flexible quadrature scheme, we propose to value a gas storage based on a novel hybrid trading strategy that successfully incorporates both spot and forward trading, thus improving the storage valuation significantly by accounting for both the inter-month and intra-month operational flexibilities and price volatility. In the fourth part of this work, we develop a continuous-time formulation for power plant valuation in infinite time horizon. We propose a real-option-based model for a power plant to account for the embedded operational flexibility. This model incorporates start-up and shut-down costs as two major operational constraints. Under this continuous valuation model, spark spread is modeled directly as a continuous stochastic process to take account of the long term co-integration relationship between electricity and fuel prices. Instead of discretizing the stochastic process, we preserve continuity of the stochastic spark spread process and work directly with the value function. Closed-form of value function under threshold policy is obtained. The corresponding optimal operational strategy can then be solved. The advantage of this approach is that it reduces computational complexity while incorporates major operation characteristics. It enables fast computation of a power plant value that approximates the real market value and sensitivity analysis of the asset value with respect to the cost parameters of a power plant and the distribution parameters of spark spread.

Thesis (Ph.D.)--University of Canterbury, 2009. / Typescript (photocopy). "March 2009." "Supervisors: Professor Les Oxley and Professor John Gibson." Includes bibliographical references (p. 325-359). Also available via the World Wide Web.

Algae are primary producers in aquatic ecosystems and are thus the most important organisms in maintaining ecosystem functioning and stability. The usage of algae by humans is quite extensive; they act as an ingredient in aquaculture feed, a potential biomedical resource, as a fertiliser and as a nutritional source. Recently, algae have been identified as a third generation biofuel feedstock for fuel generation which essentially means that algae are more efficient, net carbon neutral and have less impacts on the environment. Algae as organisms are extremely sensitive to changes in the immediate environment. The interaction of parameters with each other causes minute changes in the environment which may alter the algae biomass present and the lipids that can be extracted from the biomass. The focus of this study is to model and determine which conditions maximise algal biomass and the subsequent lipids that can be extracted from the biomass. This will allow biofuel producers to understand which conditions are the best for harvesting algae in artificial conditions or harvesting algae from the wild. Furthermore, the model developed has broad application for biofuel specialists, pollution remediation specialists and biologists. This model developed is able to determine the present state of the algal bloom and uses the present state to predict the future state of bloom hence determining the optimal conditions to harvest. The model was developed under optimal ranges described by the Food and Agriculture Organisation (FAO) and designed to replicate the most common combinations of parameters present in the wild. For the purposes of this study, various combinations of parameters within their optimal ranges that is temperature (18 – 24°C), salinity (20 – 24 p.p.t.) and photoperiod (25 – 75% light exposure) were assessed. The model was run for 72 hours with sampling every 6 hours. Every six hours, algal growth was measured by the biomass present (chloro-pigments used as estimators); this was done by fluorescence. Lipids were then extracted from algal biomass using the Bligh and Dyer method (1959). Spline curves were fitted to the data and analysis performed using Mathematica 8.0. It was found that photoperiod was the most important variable in controlling algal growth. Furthermore, lipids extracted from biomass were at their highest when algae were exposed to the conditions 75% light exposure, 21°C and 22 p.p.t. These conditions would allow for the highest amount of biofuel to be produced. Generally, algae biomass trend graphs mimic lipid trend graphs over the 72 hour period that is when lipids are at their maximum, biomass concentrations are at their maximum. It can be concluded from time model that the best time to harvest biomass is 48 hours from the initial start time of algal growth to gain the highest amount of lipids for biofuel production. / Thesis (M.Sc.)-University of KwaZulu-Natal, Westville, 2012.

Zugl.: Berlin, Humboldt-Universiẗat, Diss., 2008. / Includes bibliographical references (p. 191-202) and index.

Thesis (Ph. D.)--University of Technology, Sydney, 2005. / Title from PDF title page (viewed on July 12, 2005). Includes bibliographical references (p. 463-499).

No description available.

Thesis (MSc)--Stellenbosch University, 2011. / ENGLISH ABSTRACT: As the world-wide consumption of electricity continually increases, more and more pressure is put on the capabilities of power generating systems to maintain their levels of power provision. The electricity utility companies operating these power systems are faced with numerous challenges with respect to ensuring reliable electricity supply at cost-e ective rates. One of these challenges concerns the planned preventative maintenance of a utility's power generating units. The generator maintenance scheduling (GMS) problem refers to the problem of nding a schedule for the planned maintenance outages of generating units in a power system (i.e. determining a list of dates corresponding to the times when every unit is to be shut down so as to undergo maintenance). This is typically a large combinatorial optimisation problem, subjected to a number of power system constraints, and is usually difficult to solve. A mixed-integer programming model is presented for the GMS problem, incorporating constraints on maintenance windows, the meeting of load demand together with a safety margin, the availability of maintenance crew and general exclusion constraints. The GMS problem is modelled by adopting a reliability optimality criterion, the goal of which is to level the reserve capacity. Three objective functions are presented which may achieve this reliability goal; these objective functions are respectively quadratic, nonlinear and linear in nature. Three GMS benchmark test systems (of which one is newly created) are modelled accordingly, but prove to be too time consuming to solve exactly by means of an o -the-shelf software package. Therefore, a metaheuristic solution approach (a simulated annealing (SA) algorithm) is used to solve the GMS problem approximately. A new ejection chain neighbourhood move operator in the context of GMS is introduced into the SA algorithm, along with a local search heuristic addition to the algorithm, which results in hybridisations of the SA algorithm. Extensive experiments are performed on di erent cooling schedules within the SA algorithm, on the classical and ejection chain neighbourhood move operators, and on the modi cations to the SA algorithm by the introduction of the local search heuristic. Conclusions are drawn with respect to the e ectiveness of each variation on the SA algorithm. The best solutions obtained during the experiments for each benchmark test case are reported. It is found that the SA algorithm, with ejection chain neighbourhood move operator and a local search heuristic hybridisation, achieves very good solutions to all instances of the GMS problem. The hybridised simulated annealing algorithm is implemented in a computerised decision support system (DSS), which is capable of solving any GMS problem instance conforming to the general formulation described above. The DSS is found to determine good maintenance schedules when utilised to solve a realistic case study within the context of the South African power system. A best schedule attaining an objective function value within 6% of a theoretical lowerbound, is thus produced. / AFRIKAANSE OPSOMMING: Met die wêreldwye elektrisiteitsverbruik wat voortdurend aan die toeneem is, word daar al hoe meer druk geplaas op die vermoë van kragstelsels om aan kragvoorsieningsaanvraag te voldoen. Nutsmaatskappye wat elektrisiteit opwek, word deur talle uitdagings met betrekking tot betroubare elektrisiteitsverskaffing teen koste-e ektiewe tariewe in die gesig gestaar. Een van hierdie uitdagings het te make met die beplande, voorkomende instandhouding van 'n nutsmaatskappy se kragopwekkingseenhede. Die generator-instandhoudingskeduleringsprobleem (GISP) verwys na die probleem waarin 'n skedule vir die beplande instandhouding van kragopwekkingseenhede binne 'n kragstelsel gevind moet word ('n lys van datums moet tipies gevind word wat ooreenstem met die tye wanneer elke kragopwekkingseenheid afgeskakel moet word om instandhoudingswerk te ondergaan). Hierdie probleem is tipies 'n groot kombinatoriese optimeringsprobleem, onderworpe aan 'n aantal beperkings van die kragstelsel, en is gewoonlik moeilik om op te los. 'n Gemengde, heeltallige programmeringsmodel vir die GISP word geformuleer. Die beperkings waaruit die formulering bestaan, sluit in: venstertydperke vir instandhouding, bevrediging van die vraag na elektrisiteit tesame met 'n veiligheidsgrens, die beskikbaarheid van instandhoudingspersoneel en algemene uitsluitingsbeperkings. Die GISP-model neem as optimaliteitskriterium betroubaarheid en het ten doel om die reserwekrag wat gedurende elke tydperk beskikbaar is, gelyk te maak. Drie doelfunksies word gebruik om laasgenoemde doel te bereik (naamlik doelfunksies wat onderskeidelik kwadraties, nie-lineêr en lineêr van aard is). Drie GISP-maatstaftoetsstelsels (waarvan een nuut geskep is) is dienooreenkomstig gemodelleer, maar dit blyk uit die oplossingstye dat daar onprakties lank gewag sal moet word om eksakte oplossings deur middel van kommersiële programmatuur vir hierdie stelsels te kry. Gevolglik word 'n metaheuristiese oplossingsbenadering ('n gesimuleerde temperingsalgoritme (GTA)) gevolg om die GISP benaderd op te los. 'n Nuwe uitwerpingsketting-skuifoperator word in die konteks van GISP in die GTA gebruik. Verder word 'n lokale soekheuristiek met die GTA vermeng om 'n basteralgoritme te vorm. Uitgebreide eksperimente word uitgevoer op verskeie afkoelskedules binne die GTA, op die klassieke en uitwerpingsketting-skuifoperators en op die verbasterings van die GTA meegebring deur die lokale soekheuristiek. Gevolgtrekkings word oor elke variasie van die GTA se e ektiwiteit gemaak. Die beste oplossings vir elke toetsstelsel wat gedurende die eksperimente verkry is, word gerapporteer. Daar word bevind dat die GTA met uitwerpingsketting-skuifoperator en lokale soekheuristiek-verbastering baie goeie oplossings vir die GISP lewer. Die verbasterde GTA word in 'n gerekenariseerde besluitsteunstelsel (BSS) geïmplementeer wat 'n gebruiker in staat stel om enige GISP van die vorm soos in die wiskundige programmeringsmodel hierbo beskryf, op te los. Daar word bevind dat die BSS goeie skedules lewer wanneer dit gebruik word om 'n realistiese gevallestudie binne die konteks van die Suid-Afrikaanse kragstelsel, op te los. 'n Beste skedule met 'n doelfunksiewaarde wat binne 6% vanaf 'n teoretiese ondergrens is, word ondermeer bepaal.

CAPES / O objetivo geral deste estudo foi avaliar o potencial de produ;áo energética de ligninas extraídas de subprodutos de diversas culturas agricolas brasileiras, dentre elas: bagaço de cana de açúcar, serragem de madeira, palha de milho, palha de trigo, folhas de capim elefante e casca de arroz. Para isto, foram realizadas caracterizações físico-químicas, dentre elas: análise elementar, análise imediata, determinação do poder calorífico superior, granulometria, e determinação da composição de holocelulose, lignina e extrativos das amostras. A pesquisa foi dividida em três etapas: amostragem e caracterização da matéria prima, processamento dos resultados obtidos e verificação do potencial das biomassas em relação ao rendimento de lignina e suas propriedades. Foi adotado um planejamento experimental fatorial 22 para o tratamento estatístico dos dados obtidos. De acordo com os resultados foi comprovado que, tanto a granulometria dos sólidos na faixa estudada, quanto os métodos de extração Klason e Willstatter não influenciaram no rendimento da extração de lignina, bem como no poder calorífico destas. O rendimento médio de extração de lignina para a serragem de madeira foi ligeiramente superior, como esperado. Adicionalmente, foi verificado que o poder calorífico das ligninas foram significativamente maiores do que das biomassas in natura correspondentes. Por outro lado, foi encontrado que o potencial de energia térmica das ligninas varia principalmente em função dos dados de produção da cultura agrícola e dos coeficientes de disponibilidade dos subprodutos. Dentre as estimativas de potencial de geração de energia térmica das biomassas testadas, destacam-se as ligninas do bagaço de cana e da palha de milho. Estudos ainda se fazem necessários para determinar o potencial das ligninas extraídas no ramo da indústria química através do conhecimento da composição. / The aim of this study was to assess the energetic potential obtained from lignins extracted of several Brazilian biomasses, among them: sugar cane bagasse, sawdust, corn straw, wheat straw, elephant grass leaves and rice husk. To achieve this objective, physicochemical characterization, including: ultimate analysis, proximate analysis, superior calorific value determination, fraction size, and compositional determination of holocellulose, lignin and extractives of samples. The research was divided into three steps: sampling and characterization of the raw material, processing the results and verifying the potential of biomass over the yield of lignin and its properties. It was used a 22 factorial experimental design for the statistical treatment of the obtained data. According to the results, it was confirmed that both the particle size of the solids in the studied range, the extraction methods as Klason and Willstatter no influence on the extraction yield of lignin, as well as the calorific value of these. The average yield of extraction of wood sawdust lignin was slightly higher, as expected. Additionally, it was found that the calorific value of lignin were significantly higher than the corresponding biomass in natura. Moreover, it was found that the potential of thermal energy from the lignins varies mainly depending on the production data and the availability coefficients of crop to byproducts. Among the estimated potential to generate thermal energy from biomasses tested, highlight the lignin from sugar cane bagasse and corn straw. Further studies are needed to determine the potential of the lignins extracted in the field of chemical industry through the knowledge of its composition.

The Southern African Development Community (SADC) region, like most parts of the African continent, faces significant modern energy services access challenges. It is estimated that less than 45% of the SADC region’s populace have access to reliable modern energy forms and the situation is worse in rural areas where access is approximately 30%. Poor energy security is exacerbated by electricity power cuts and load shedding in almost all of the member states in the region. With the advent of battery storage, all forms of green energy have the potential to contribute to the shortfall in the supply of peaking power required to meet the daily (morning and evenings) and seasonal (winter) peaks when most power is required on the grid network. The region is endowed with vast green (renewables/low carbon or clean) energy resources. The purpose of this study is to expand the empirical body of research and knowledge on factors that contribute to widespread access success to green energy in the SADC region. Investments into green energy resources require an understanding of the unique characteristics of the energy sector in the region. In order to achieve this, a conceptual theoretical model was developed and tested empirically. Factors that influence green energy access success were identified through literature reviews and discussions with energy practitioners. All identified factors were then operationalised by carefully defining them in the context of the study. In order to test the proposed theoretical model and the hypothesised relationships, a structured questionnaire was developed and sent to energy practitioners from various sections of the energy sector in the region. STATISTICA 12 was employed to analyse relationships between variables and responses between identified groups. Pearson Product Moment Correlation (Pearson r) was employed to determine correlations between variables. Conclusions about hypotheses six (6) to fifteen (15) were made based on correlations between variables. T-tests were employed to make inferences about the views of various categories of respondents with regard to the twelve (12) identified variables. Multivariate analysis of variance (MANOVA) and Analysis of variance (ANOVA) examined associations between the dependent and independent variables with the identified categories of respondents and conclusions about hypotheses one (1) to five (5) and sixteen (16) were also made. The study finds that policy and the regulatory environment are still the main driving force behind energy access in the region. Power generation is managed by authorities’ power utility companies. Unbundling of power utilities supported by new energy business and operating models to accommodate mini and off grid power plants is found to be a key to green energy access in the region. The energy market is transforming in favour of independent power producers (IPPs) and consumers will significantly influence energy access decisions in the future. Green energy power storage to overcome intermittency will feature prominently in the success of green energy access in the region. Widespread access success to green energy will be attained when green energy access is reliable, affordable, efficient, and socially acceptable, meet the demand and reduces environmental pollution. The study recommends that strategic green energy planning must incorporate green energy infrastructure development, projects finance and human capacity development as priorities amongst SADC region’s member countries. Regional energy access enabling institutions must be strengthened; energy policies implemented with vigour and private sector participation enhanced in an integrated energy market.