Thesis (M.S.)--California Polytechnic State University, 2010. / Title from PDF title page; viewed on May 15, 2010. Major professor: Robert S. Crockett, Ph.D. "Presented to the faculty of California Polytechnic State University, San Luis Obispo." "In partial fulfillment of the requirements for the degree [of] Master of Science in Engineering." "March 2010." Includes bibliographical references (p. 64-65).

The energy-planning involves finding a set of sources and conversion devices so as to meet the energy requirements/demands of all the activities in an optimal manner. This could occur at centralized or decentralized level. The current pattern of commercial energy oriented development, particularly focused on fossil fuels and centralized electricity, has resulted in inequities, external debt and environmental degradation. The current status is largely a result of adoption of centralized energy planning (CEP), which ignores the energy needs of rural areas and the poor and has further contributed to environmental degradation due to fossil fuel consumption and forest degradation. CEP does not pay attention to the variations in socio-economic and ecological factors of a region, which influence success of any intervention. Decentralized energy planning (DEP) provides an opportunity to address the energy needs of poor as well as promote efficient utilization of resources. The DEP mechanism takes into account various available resources and demands in a region. DEP, in the Indian context, could be at several scales namely district, block, panchayats (cluster of villages) and village level. Energy planning at the village level is the lowest level of the application of decentralized planning principle. A village constitutes a cluster of households with distinct geographic boundary consisting of settlement, agricultural land, water bodies and any other land category, in most parts of India. Further, the village level plans must be prepared within the limits set by a panchayat, a block or a district level plans, for the sum total of various village plans must correspond to a panchayat (local council), block (or taluka), or district level plan. A panchayat is the lowest administrative unit consisting of a cluster of villages and an elected body to administer developmental activities. A block (or taluka) consists of a cluster of panchayats and a district consists of a cluster of blocks. The main hypothesis for this study is that centralized energy planning has lead to excessive dependence on fossil fuels and import of petroleum, leading to concerns on environment and energy security and finally neglect of the energy needs of the rural communities and poor in particular. DEP could meet the local energy needs particularly in rural areas, protect environment and promote a self reliant and sustainable energy path. In this study, methodology for adopting energy planning from grassroot or village to district level is explored. The study adopts and compares the DEP approach of moving from village (Ungra), to panchayat (Yedavani), to block (Kunigal) and finally to district (Tumkur) level. Aims and objectives of research . • To review energy planning approaches adopted in India . • To evaluate models and methods for DEP at different scales; Village, Panchayat, District and State levels . • To develop a sustainable and decentralized energy planning approach . • To analyze the sustainable decentralized planning approach using multiple objective goal programming model and develop sustainable energy mix for meeting energy needs at village, panchayat, block and district level . • To assess the implications of sustainable and decentralized energy planning from the context of socio-economic and environmental concerns. The central theme of the research work is to prepare an optimized area-based decentralized energy plan to meet the energy needs, incorporating all potential alternate energy sources and end-use devices at least-cost to the economy and environment. One of the environmental goals addressed is to minimize or avoid CO2 emissions to address climate change. Study area selected for DEP is Tumkur district of Karnataka state, India and the DEP is carried out for the year 2005 and 2020. Advanced operation research technique, goal programming, is used to solve the large and complicated energy system problem having multiple conflicting goals.

The end of Cold War and collapse of the Soviet Union created new dynamics in international arena. The events of the new restructured world show us decline and rise of powers’ capabilities on the global and regional levels. Powers such as China and Russia started to reconsider their global and regional capabilities to define their position in international arena. The new sovereign states of Central Asian region have strengthened their capabilities with those powers who maneuver in the region in the fields of economy, politics and security. They all try to improve their interstate relations in the framework of mutual understanding, mutual trust, interaction and mutual profits. China, Russia and Central Asian Republics are pursuing the peace and stability as their strategic interests. Overall, the challenges of instability and contradictions in the region still exist. This should be an important question for future research of security studies of Central Asia region.

An assessment of the thermal resource in the Straits of Florida was performed to estimate the Ocean Thermal Energy Conversion (OTEC) potential. Direct measurements of the temperature profile across the Florida Straits were taken from nearshore Southeast Florida to the Exclusive Economic Zone boundary along four evenly spaced transects perpendicular to Florida's Southeast coast, spanning 160 km. Along the southern transects in summer, nearshore cold and warm water resources meet or exceed the average 20ÀC temperature difference required for OTEC. In winter, the nearshore average DT of 17.76ÀC can produce 59-75% design net power and 70-86% in spring with DT averaging 18.25ÀC. Offshore along the southern transects, a high steady DT from 18.5- 24ÀC creates an annual average net power of 120-125MW. Along the northern transects, the nearshore resource does not exist, but a consistent OTEC resource is present offshore, providing 70-80% design net power in winter, and 100-158% in spring and summer. / by Anna E. Leland. / Thesis (M.S.C.S.)--Florida Atlantic University, 2009. / Includes bibliography. / Electronic reproduction. Boca Raton, Fla., 2009. Mode of access: World Wide Web.

The following study explores the worldwide spatial and temporal distributions of electrical power that can be extracted from the ocean's stored solar energy via the process of closed-cycle ocean thermal energy conversion (OTEC). Special emphasis is placed on resources surrounding the state of Florida. The study combines oceanographic input from a state-of-the-art ocean circulation model, the Hybrid Coordinate Ocean Model, with a state-of-the-industry OTEC plant model to predict achievable power values across the world. These power predictions are then constrained by local replenishment rates of cold deep sea water to provide an upper limit to the sustainable OTEC resource. Next, the geographic feasibility of OTEC-coupled and OTEC-independent sea water cooling (air conditioning and refrigeration) are explored. Finally, the model data is validated against in situ oceanic measurements to ensure the quality of the predictions. / by Lynn Rauchenstein. / Thesis (M.S.C.S.)--Florida Atlantic University, 2012. / Includes bibliography. / Mode of access: World Wide Web. / System requirements: Adobe Reader.

O objetivo deste trabalho é analisar e desenvolver um modelo para seleção completa de recursos energéticos com base na teoria de tomada de decisão para classificação de Recursos do lado da Oferta e do lado da Demanda. Sendo que a seleção completa, circunscrita em elementos de auxílio tipo atributos e sub-atributos, implica na consideração das dimensões do desenvolvimento, relativos a metodologia do Planejamento Integrado de Recursos Energéticos (PIR). Estes elementos são descritos através de algoritmos demonstrados a partir de uma escala matemática qualitativa e quantitativa distribuídos em quatro grandes dimensões: Técnico-econômica, Ambiental, Social e Política (dimensões do desenvolvimento energético e humano). Os algoritmos dos atributos e sub-atributos que caracterizam cada um dos Recursos Energéticos (REs) podem ser dados através de um valor numérico (mais comuns nos algoritmos das dimensões Técnico-econômica e Ambiental, onde o valor pode ser medido ou estimado) ou através de um valor na escala não numérica (escala utilizada com mais frequência nas dimensões Social e Política). Posteriormente a caracterização de cada um dos REs, estes passam por uma etapa denominada padronização, que consiste em converter diferentes unidades de caracterização para uma mesma base, dando a possibilidade de comparação entre os diferentes elementos de caracterização dos REs. A ferramenta matemática de comparação entre diferentes elementos utilizada no auxílio à tomada de decisão foi desenvolvida por Thomas L. Saaty e chama-se Processo Analítico Hierárquico (AHP do significado em inglês) A partir deste ponto é possível calcular os Ranqueamentos dos REs. São três Ranqueamentos: Padrão, dos En-In e o Final. O cálculo dos dois primeiros Ranqueamentos é equivalente, e é feito através da somatória da multiplicação dos dados convertidos pelos pesos dos atributos e subatributos correspondentes. O cálculo do Ranqueamento Final é feito através da média dos resultados dos dois Ranqueamentos citados. O valor final obtido deste processo, para cada um dos REs, é chamado de Custo Completo. Portanto, para este caso, quanto maior o Custo Completo, mais bem ranqueado estará o RE. Um estudo de caso foi feito para consolidação dos resultados deste trabalho. A região do estudo foi a Região Administrativa de Araçatuba (RAA) que engloba 43 municípios do Estado de São Paulo. Foram caracterizados e ranqueados 182 REs, e obteve-se como resultado do Ranqueamento Final, as 58 primeiras melhores colocações sendo ocupadas em sua integridade por Recursos Energéticos de Demanda e as 22 últimas posições ocupadas por algum Recurso Energético que tem como característica a termo-geração (nuclear ou pela queima direta de combustíveis). / The objective of this study is to analyze and develop a model for full selection of energy resources on the theory of decision making for classification of Supply Side and Demand Side Energy Resources. Considering the full selection limited aid elements in type attributes and sub-attributes, implies the consideration of development dimensions concerning the methodology of Energy Integrated Resource Planning (PIR acronym in Portuguese of the Planejamento Integrado de Recursos). These elements are described algorithmically shown from a qualitative and quantitative mathematical scale distributed into four main dimensions: Technical-Economic, Environmental, Social and Policy (dimensions of development energy and development human). The algorithms of the attributes and sub-attributes that characterize each of Energy Resources (REs) can be given by a numerical value (most common in the algorithms of Technical-Economic and Environmental Dimensions, where the value can be measured or estimated) or through a value in the no numeric scale (scale used more often in Social and Policy dimensions). Subsequent characterization of each of the REs, they undergo a step called \"standardization\", which consists in converting units of different characterization for a single base, giving the possibility of comparison between the different elements of characterization of REs. A mathematical tool for comparing different elements used in assisting decision making was developed by Thomas L. Saaty and called Analytic Hierarchy Process (AHP). From this point its possible to calculate the Energy Resources Ranks. There are three Ranks: Padrão, dos En-In and Final (names in Portuguese). The calculation of the first two Ranks is equivalent and is done by the sum of the multiplying of weights of the converted data attributes and sub-attributes thereof. The calculation of the final ranking is done by averaging the results of both Ranks mentioned. The final value obtained from this process for each of REs is called full cost. Therefore, in this case, the higher the Full Cost Account ranked will be better RE. A case study was done to consolidate the results of this work. The study region was Araçatuba Administrative Region (RAA) that encompasses 43 municipalities in the state of São Paulo. Were characterized and ranked 182 REs, and was obtained as a result of final ranking, the 58 best placements being occupied in its entirety by Demand Side Energy Resources and 22 last positions occupied by some Energy Resource that is characterized by the thermal generation (nuclear or by direct burning of fuels).

O objetivo deste trabalho é analisar e desenvolver um modelo para seleção completa de recursos energéticos com base na teoria de tomada de decisão para classificação de Recursos do lado da Oferta e do lado da Demanda. Sendo que a seleção completa, circunscrita em elementos de auxílio tipo atributos e sub-atributos, implica na consideração das dimensões do desenvolvimento, relativos a metodologia do Planejamento Integrado de Recursos Energéticos (PIR). Estes elementos são descritos através de algoritmos demonstrados a partir de uma escala matemática qualitativa e quantitativa distribuídos em quatro grandes dimensões: Técnico-econômica, Ambiental, Social e Política (dimensões do desenvolvimento energético e humano). Os algoritmos dos atributos e sub-atributos que caracterizam cada um dos Recursos Energéticos (REs) podem ser dados através de um valor numérico (mais comuns nos algoritmos das dimensões Técnico-econômica e Ambiental, onde o valor pode ser medido ou estimado) ou através de um valor na escala não numérica (escala utilizada com mais frequência nas dimensões Social e Política). Posteriormente a caracterização de cada um dos REs, estes passam por uma etapa denominada padronização, que consiste em converter diferentes unidades de caracterização para uma mesma base, dando a possibilidade de comparação entre os diferentes elementos de caracterização dos REs. A ferramenta matemática de comparação entre diferentes elementos utilizada no auxílio à tomada de decisão foi desenvolvida por Thomas L. Saaty e chama-se Processo Analítico Hierárquico (AHP do significado em inglês) A partir deste ponto é possível calcular os Ranqueamentos dos REs. São três Ranqueamentos: Padrão, dos En-In e o Final. O cálculo dos dois primeiros Ranqueamentos é equivalente, e é feito através da somatória da multiplicação dos dados convertidos pelos pesos dos atributos e subatributos correspondentes. O cálculo do Ranqueamento Final é feito através da média dos resultados dos dois Ranqueamentos citados. O valor final obtido deste processo, para cada um dos REs, é chamado de Custo Completo. Portanto, para este caso, quanto maior o Custo Completo, mais bem ranqueado estará o RE. Um estudo de caso foi feito para consolidação dos resultados deste trabalho. A região do estudo foi a Região Administrativa de Araçatuba (RAA) que engloba 43 municípios do Estado de São Paulo. Foram caracterizados e ranqueados 182 REs, e obteve-se como resultado do Ranqueamento Final, as 58 primeiras melhores colocações sendo ocupadas em sua integridade por Recursos Energéticos de Demanda e as 22 últimas posições ocupadas por algum Recurso Energético que tem como característica a termo-geração (nuclear ou pela queima direta de combustíveis). / The objective of this study is to analyze and develop a model for full selection of energy resources on the theory of decision making for classification of Supply Side and Demand Side Energy Resources. Considering the full selection limited aid elements in type attributes and sub-attributes, implies the consideration of development dimensions concerning the methodology of Energy Integrated Resource Planning (PIR acronym in Portuguese of the Planejamento Integrado de Recursos). These elements are described algorithmically shown from a qualitative and quantitative mathematical scale distributed into four main dimensions: Technical-Economic, Environmental, Social and Policy (dimensions of development energy and development human). The algorithms of the attributes and sub-attributes that characterize each of Energy Resources (REs) can be given by a numerical value (most common in the algorithms of Technical-Economic and Environmental Dimensions, where the value can be measured or estimated) or through a value in the no numeric scale (scale used more often in Social and Policy dimensions). Subsequent characterization of each of the REs, they undergo a step called \"standardization\", which consists in converting units of different characterization for a single base, giving the possibility of comparison between the different elements of characterization of REs. A mathematical tool for comparing different elements used in assisting decision making was developed by Thomas L. Saaty and called Analytic Hierarchy Process (AHP). From this point its possible to calculate the Energy Resources Ranks. There are three Ranks: Padrão, dos En-In and Final (names in Portuguese). The calculation of the first two Ranks is equivalent and is done by the sum of the multiplying of weights of the converted data attributes and sub-attributes thereof. The calculation of the final ranking is done by averaging the results of both Ranks mentioned. The final value obtained from this process for each of REs is called full cost. Therefore, in this case, the higher the Full Cost Account ranked will be better RE. A case study was done to consolidate the results of this work. The study region was Araçatuba Administrative Region (RAA) that encompasses 43 municipalities in the state of São Paulo. Were characterized and ranked 182 REs, and was obtained as a result of final ranking, the 58 best placements being occupied in its entirety by Demand Side Energy Resources and 22 last positions occupied by some Energy Resource that is characterized by the thermal generation (nuclear or by direct burning of fuels).

The amount of distributed generation (DG) is increasing worldwide, and it is located in distribution networks close to consumers or even in the consumers¡¦ side of the meter. Therefore, the net demand to be supplied through transmission and distribution networks may decrease, allowing to postpone reinforcement of existing networks. This thesis presents a methodology for assessing the potential benefits of using non--constructional reinforcement strategies to relieve distribution network congestion and increase the utilization of the network assets. Due to the randomness of involved variables (load demand patterns, DG hourly production, DG availability, etc.), a simulation approach is used to model the uncertainties. The benefits of DG, energy storage (ES), and demand response (DR) on congestion relief and investment deferment are evaluated. The analyzed items include: the distribution network investment avoided cost, levelized annual cost, hourly overload probability, and hourly overload risk. Simulation results indicate the potential benefits of non--traditional strategies in increasing the distribution network utilization and relieving network congestion.

China's flourishing economy depends upon access to and greater use of energy resources, especially oil. Consequently, energy security has become of paramount importance to the Chinese government. China, however, perceives a reliance on international oil markets as dangerous and also considers itself vulnerable to the United States, which could conceivably restrict oil imports to China in a time of conflict. In order to enhance China's energy security, Chinese oil companies have sought to obtain oil resources throughout the world, and Beijing has cultivated closer relations with various oil-producing nations. China's heightened demand for oil and its efforts to secure access to oil resources are worrisome to the United States. Fears largely stem from the idea that increased consumption by both the United States and China will inevitably lead to fiercer competition between the two nations and result in a zero-sum game in which a gain for one country comes at the expense of the other country. Anxiety in the United States also is based upon the notion that, as China exerts greater influence around the world through its economic expansion and as it establishes closer bonds with oil-producing nations, China will undermine American interests and foreign policy objectives. Not all concerns regarding China are inflated, but many of them are. Indeed, China's rise will pose certain challenges to American influence and supremacy in some regions, and China's relationships with states that the United States would like to isolate are troublesome. It is important, however, for the United States to be selective in its criticisms of China. Unsubstantiated apprehension will lead to counter-productive policies with respect to China, which, in turn, will alienate China and render other attempts to support American interests fruitless. China's acquisitions of oil resources do not inherently contravene American energy security interests. Thus, the United States should not fret about China's pursuit of oil. The United States should continually reaffirm its professed faith in free markets, including their ability to provide energy security, and in that way allay Chinese concerns about its own vulnerability. If the United States can set aside its uneasiness about China's quest for oil, it can more effectively address Chinese actions that directly and negatively affect American interests and also recognize that opportunities for mutual gain and cooperation abound. / text

Thesis (M.S.)--Montana State University--Bozeman, 2004. / Typescript. Chairperson, Graduate Committee: Joseph Seymour. Includes bibliographical references (leaves 69-70).