The Slow Search for Solutions: Lessons from Historical Energy Transitions by Sector and Service

28 p.

Long Run Demand for Energy Services: the Role of Economic and Technological Development

36 p.

Sustainable IT and IT for sustainability

Energy and sustainability have become one of the most critical issues of our generation. While the abundant potential of renewable energy such as solar and wind provides a real opportunity for sustainability, their intermittency and uncertainty present a daunting operating challenge. This thesis aims to develop analytical models, deployable algorithms, and real systems to enable efficient integration of renewable energy into complex distributed systems with limited information.

The first thrust of the thesis is to make IT systems more sustainable by facilitating the integration of renewable energy into these systems. IT represents the fastest growing sectors in energy usage and greenhouse gas pollution. Over the last decade there are dramatic improvements in the energy efficiency of IT systems, but the efficiency improvements do not necessarily lead to reduction in energy consumption because more servers are demanded. Further, little effort has been put in making IT more sustainable, and most of the improvements are from improved "engineering" rather than improved "algorithms". In contrast, my work focuses on developing algorithms with rigorous theoretical analysis that improve the sustainability of IT. In particular, this thesis seeks to exploit the flexibilities of cloud workloads both (i) in time by scheduling delay-tolerant workloads and (ii) in space by routing requests to geographically diverse data centers. These opportunities allow data centers to adaptively respond to renewable availability, varying cooling efficiency, and fluctuating energy prices, while still meeting performance requirements. The design of the enabling algorithms is however very challenging because of limited information, non-smooth objective functions and the need for distributed control. Novel distributed algorithms are developed with theoretically provable guarantees to enable the "follow the renewables" routing. Moving from theory to practice, I helped HP design and implement industry's first Net-zero Energy Data Center.

The second thrust of this thesis is to use IT systems to improve the sustainability and efficiency of our energy infrastructure through data center demand response. The main challenges as we integrate more renewable sources to the existing power grid come from the fluctuation and unpredictability of renewable generation. Although energy storage and reserves can potentially solve the issues, they are very costly. One promising alternative is to make the cloud data centers demand responsive. The potential of such an approach is huge.

To realize this potential, we need adaptive and distributed control of cloud data centers and new electricity market designs for distributed electricity resources. My work is progressing in both directions. In particular, I have designed online algorithms with theoretically guaranteed performance for data center operators to deal with uncertainties under popular demand response programs. Based on local control rules of customers, I have further designed new pricing schemes for demand response to align the interests of customers, utility companies, and the society to improve social welfare.

Distributed Load Control in Multiphase Radial Networks

The current power grid is on the cusp of modernization due to the emergence of distributed generation and controllable loads, as well as renewable energy. On one hand, distributed and renewable generation is volatile and difficult to dispatch. On the other hand, controllable loads provide significant potential for compensating for the uncertainties. In a future grid where there are thousands or millions of controllable loads and a large portion of the generation comes from volatile sources like wind and solar, distributed control that shifts or reduces the power consumption of electric loads in a reliable and economic way would be highly valuable.

Load control needs to be conducted with network awareness. Otherwise, voltage violations and overloading of circuit devices are likely. To model these effects, network power flows and voltages have to be considered explicitly. However, the physical laws that determine power flows and voltages are nonlinear. Furthermore, while distributed generation and controllable loads are mostly located in distribution networks that are multiphase and radial, most of the power flow studies focus on single-phase networks.

This thesis focuses on distributed load control in multiphase radial distribution networks. In particular, we first study distributed load control without considering network constraints, and then consider network-aware distributed load control.

Distributed implementation of load control is the main challenge if network constraints can be ignored. In this case, we first ignore the uncertainties in renewable generation and load arrivals, and propose a distributed load control algorithm, Algorithm 1, that optimally schedules the deferrable loads to shape the net electricity demand. Deferrable loads refer to loads whose total energy consumption is fixed, but energy usage can be shifted over time in response to network conditions. Algorithm 1 is a distributed gradient decent algorithm, and empirically converges to optimal deferrable load schedules within 15 iterations.

We then extend Algorithm 1 to a real-time setup where deferrable loads arrive over time, and only imprecise predictions about future renewable generation and load are available at the time of decision making. The real-time algorithm Algorithm 2 is based on model-predictive control: Algorithm 2 uses updated predictions on renewable generation as the true values, and computes a pseudo load to simulate future deferrable load. The pseudo load consumes 0 power at the current time step, and its total energy consumption equals the expectation of future deferrable load total energy request.

Network constraints, e.g., transformer loading constraints and voltage regulation constraints, bring significant challenge to the load control problem since power flows and voltages are governed by nonlinear physical laws. Remarkably, distribution networks are usually multiphase and radial. Two approaches are explored to overcome this challenge: one based on convex relaxation and the other that seeks a locally optimal load schedule.

To explore the convex relaxation approach, a novel but equivalent power flow model, the branch flow model, is developed, and a semidefinite programming relaxation, called BFM-SDP, is obtained using the branch flow model. BFM-SDP is mathematically equivalent to a standard convex relaxation proposed in the literature, but numerically is much more stable. Empirical studies show that BFM-SDP is numerically exact for the IEEE 13-, 34-, 37-, 123-bus networks and a real-world 2065-bus network, while the standard convex relaxation is numerically exact for only two of these networks.

Theoretical guarantees on the exactness of convex relaxations are provided for two types of networks: single-phase radial alternative-current (AC) networks, and single-phase mesh direct-current (DC) networks. In particular, for single-phase radial AC networks, we prove that a second-order cone program (SOCP) relaxation is exact if voltage upper bounds are not binding; we also modify the optimal load control problem so that its SOCP relaxation is always exact. For single-phase mesh DC networks, we prove that an SOCP relaxation is exact if 1) voltage upper bounds are not binding, or 2) voltage upper bounds are uniform and power injection lower bounds are strictly negative; we also modify the optimal load control problem so that its SOCP relaxation is always exact.

To seek a locally optimal load schedule, a distributed gradient-decent algorithm, Algorithm 9, is proposed. The suboptimality gap of the algorithm is rigorously characterized and close to 0 for practical networks. Furthermore, unlike the convex relaxation approach, Algorithm 9 ensures a feasible solution. The gradients used in Algorithm 9 are estimated based on a linear approximation of the power flow, which is derived with the following assumptions: 1) line losses are negligible; and 2) voltages are reasonably balanced. Both assumptions are satisfied in practical distribution networks. Empirical results show that Algorithm 9 obtains 70+ times speed up over the convex relaxation approach, at the cost of a suboptimality within numerical precision.

Reutilización de escoria negra de acería como soporte en biofiltros para la eliminación de H2S del biogás.

[EN]Due to the limitations associated with fossil fuels it is necessary to promote energy sources that are renewable as well as eco-friendly, such as biogas generated in anaerobic digesters. The biogas, composed principally of methane and CO2, is the result of the biodegradation of organic matter under anaerobic conditions. Its use as fuel is limited by the presence of minority compounds such as hydrogen sulphide (H2S); therefore, its pre-treatment is necessary. Currently there are various technologies for the removal of H2S from a gas stream, but most of them are based on physic-chemical treatments which have a number of drawbacks as reactive consumption, generation of secondary flows, etc. Biofiltration has been used as an efficient and low cost alternative to conventional purification processes, and excellent results for the degradation of H2S have been obtained. However process can be limited due to the progressive ageing of the support material, along with the loss of nutrients and other specific characteristics necessary for the good development of biomass. The purpose of this project is to develop a mixed support consisting of a mixture of an organic material and an inorganic support for its application in the removal of the H2S from biogas. This support material helps to optimize the characteristics of the bed and extend its lifespan. The development of such material will contribute to the implementation of biofiltration for treating biogas from anaerobic digesters for its use as biofuel. The inorganic material used is electric arc furnace (EAF) black slag, a by-product generated in large quantities in the production of steel in the Basque Country. Although traditionally the slag has been used in civil engineering, its physicochemical characteristics make it suitable for reuse as a filter medium in biofiltration. The main conclusion drawn from the experimental results is that EAF black slag is a suitable co-packing material in organic biofilters treating H2S-polluted gaseous streams. High pollutant removal rates have been achieved during the whole experimental period. The removal capacity recorded in biofilters with less inorganic material was higher than in those with higher slag portion. Nevertheless, all the biofilters have shown a satisfactory response even at high inlet loads (48 g·m-3·h-1), where the RE has not decreased over 82%.

Aporte adicional de energía renovable geotérmica a instalación con cogeneración en hospital existente.

[ES]Este proyecto tiene como objetivo apoyar a la generación de energía por cogeneración mediante una fuente de energía renovable. Se pretende plantear una solución que satisfaga parte de las necesidades básicas del Hospital Universitario de Álava, en su sede del Hospital de Santiago, de una forma económicamente rentable. Este proyecto se enmarca dentro de los esfuerzos en la promoción de energías renovables que comenzaron con el protocolo Kioto, al que le siguieron los objetivos Europa 20/20/20. Se realizará un acercamiento a la utilización de la energía renovable geotérmica como fuente de energía que disminuye el impacto ambiental. El edificio hospitalario considerado ya cuenta con un sistema de generación energética con cogeneración, considerada dentro del régimen especial, por la utilización de energía residual para procesos que de otra manera hubieran requerido consumo de combustible. Se plantearán diferentes alternativas para la generación de energía térmica con geotermia, que al ser de origen renovable, es una fuente de energía de combustibles no fósiles, y se demostraran sus beneficios analizando cómo mejora la huella de carbono del hospital con la propuesta. Finalmente, para valorar si se trata de un proyecto viable se planteará el estudio económico analizando el presupuesto y análisis de rentabilidad.

Influencia del vehículo eléctrico en la red eléctrica, en función del comportamiento social.

[ES]En la actualidad, el modelo de transporte apenas ha avanzado en el intento de frenar el Cambio Climático o en el cuidado del medio ambiente. Además, el gran negocio que existe detrás del petróleo hace que este tipo de transporte sea poco sostenible. Es por eso que se está desarrollando, a nivel nacional e internacional, una solución a dicho problema que es el uso del vehiculó eléctrico (VE). La introducción masiva del VE permitirá el uso extensivo de fuentes de energía no contaminantes e intermitentes, como son las energías renovables. Sin embargo, los VEs están lejos de ser una tecnología probada. Existen aún muchos problemas en torno a él que deben ser resueltos, entre ellos se encuentra el desarrollo de las baterías, su modelo de negocio y coste o la influencia de la conexión del VE sobre la red eléctrica. Este último problema, estará muy influenciado por el comportamiento social del futuro conductor, lo cual es el eje central del proyecto.

Energy retrofits in social housing. Analysis of its thermal behaviour.

468 p.

Estudo da previsão de propriedades do biodiesel utilizando espectros de infravermelho e calibração multivariada

O biodiesel tem sido amplamente utilizado como uma fonte de energia renovável, que contribui para a diminuição de demanda por diesel mineral. Portanto, existem várias propriedades que devem ser monitoradas, a fim de produzir e distribuir biodiesel com a qualidade exigida. Neste trabalho, as propriedades físicas do biodiesel, tais como massa específica, índice de refração e ponto de entupimento de filtro a frio foram medidas e associadas a espectrometria no infravermelho próximo (NIR) e espectrometria no infravermelho médio (Mid-IR) utilizando ferramentas quimiométricas. Os métodos de regressão por mínimos quadrados parciais (PLS), regressão de mínimos quadrados parciais por intervalos (iPLS), e regressão por máquinas de vetor de suporte (SVM) com seleção de variáveis por Algoritmo Genético (GA) foram utilizadas para modelar as propriedades mencionadas. As amostras de biodiesel foram sintetizadas a partir de diferentes fontes, tais como canola, girassol, milho e soja. Amostras adicionais de biodiesel foram adquiridas de um fornecedor da região sul do Brasil. Em primeiro lugar, o pré-processamento de correção de linha de base foi usado para normalizar os dados espectrais de NIR, seguidos de outros tipos de pré-processamentos que foram aplicados, tais como centralização dos dados na média, 1 derivada e variação de padrão normal. O melhor resultado para a previsão do ponto de entupimento de filtro a frio foi utilizando os espectros de Mid-IR e o método de regressão GA-SVM, com alto coeficiente de determinação da previsão, R2Pred=0,96 e baixo valor da Raiz Quadrada do Erro Médio Quadrático da previsão, RMSEP (C)= 0,6. Para o modelo de previsão da massa específica, o melhor resultado foi obtido utilizando os espectros de Mid-IR e regressão por PLS, com R2Pred=0,98 e RMSEP (g/cm3)= 0,0002. Quanto ao modelo de previsão para o índice de refração, o melhor resultado foi obtido utilizando os espectros de Mid-IR e regressão por PLS, com excelente R2Pred=0,98 e RMSEP= 0,0001. Para esses conjuntos de dados, o PLS e o SVM demonstraram sua robustez, apresentando-se como ferramentas úteis para a previsão das propriedades do biodiesel estudadas

Energy analysis of the ring seine operations, off Cochin, Kerala

Ring seines are lightly constructed purse seines adapted for operation in the traditional sector. Fish production and energy requirement in the ring seine operations, off Cochin, Kerala, India are discussed in this paper, based on data collected during 1997- 1998. The results reflect the Gross Energy Requirement (GER) situation that existed during 1997-1998. Mean catch per ring seiner per year worked out to be 211.9 t of which sardines (Sardinella spp.) constituted 44.3%, followed by Indian mackerel (Rastrelliger kanagurta) 29.7%, carangids 11.4%, penaeid prawns 2.2%, pomfrets 1.1% and miscellaneous fish 11.3%. Total energy inputs into the ring seine operations were estimated to be 1300.8 GJ. Output by way of fish production was determined to be 931.85 GJ. GER is the sum of all non-renewable energy resources consumed in making available a product or service and is a measure of intensity of non-renewable resource use. GER per tonne of fish landed by ring seiners was estimated to be 6.14. Among the operational inputs, kerosene constituted 73.4% of the GER, followed by petrol (12.7%), diesel (6.7%) and lubricating oil (2.4%). Fishing gear contributed 3.8%, engine 0.8% and fishing craft 0.3% of the GER. Energy ratio for ring seining was 0.72 and energy intensity 1.40.

Estudo Comparativo de Controladores Fuzzy Aplicados a um Sistema Solar Fotovoltaico.

Neste trabalho apresenta-se o modelo de um controlador baseado em Lógica Fuzzy para um sistema de energia baseado em fonte renovável solar fotovoltaica (photovoltaic - PV) multi-string em operação isolada, para o aproveitamento da máxima potência desta fonte. O sistema é composto por painéis solares, conversor CC-CC tipo elevador de tensão (boost), armazenamento por banco de baterias, inversor trifásico e carga trifásica variável. O sistema fotovoltaico foi modelado no MATLAB/Simulink de forma a representar a curva característica V-I do módulo PV, e que é baseado nos dados disponíveis em data-sheets de painéis fotovoltaicos comerciais. Outros estudos de natureza elétrica tais como o cálculo dos valores eficazes das correntes no conversor CC-CC, para avaliação das perdas, indispensáveis para o dimensionamento de componentes eletrônicos, foram realizados. O método tradicional Perturb and Observe de rastreamento do ponto de máxima potência (Maximum Power Point Tracking MPPT) de painéis foi testado e comparado com métodos que usam a Lógica Fuzzy. Devido ao seu desempenho, foi adotado o método Fuzzy que realiza o MPPT por inferência do ciclo de trabalho de um modulador por largura de pulso (Pulse Width Modulation - PWM) através da variação da potência pela variação da corrente do painel solar. O modelo Fuzzy adotado neste trabalho foi testado com sucesso. Os resultados mostraram que ele pode ser robusto e atende à aplicação proposta. Segundo alguns testes realizados, este controlador pode realizar o MPPT de um sistema PV na configuração multi-string onde alguns arranjos fotovoltaicos são usados. Inclusive, este controle pode ser facilmente adaptado para realizar o MPPT de outras fontes de energia baseados no mesmo princípio de controle, como é o caso do aerogerador.

Gross energy requirement in fishing operations

Energy is a key input into the fish harvesting process. Efficient use of energy helps in reducing operational costs and environmental impact, while increasing profits. Energy optimisation is an important aspect of responsible fishing as enunciated in the Code of Conduct for Responsible Fisheries. Gross Energy Requirement (GER) is the sum of all non-renewable energy resources consumed in making available a product or service and is expressed in energy units per physical unit of product or service delivered. GER is a measure of intensity of non-renewable resource use and it reflects the amount of depletion of earth’s inherited store of non-renewable energy in order to create and make available a product or service. In this study, GER in fish harvesting up to the point of landing is estimated in selected fish harvesting systems in the small-mechanised sectors of Indian fisheries and compared with reported results from selected non mechanised and motorised fishing systems to reflect the situation during 1997-1998. Among the fish harvesting systems studied, GER t fish-1 ranged from 5.54 and 5.91 GJ, respectively, for wooden and steel purse seiners powered by 156 hp engines; 6.40 GJ for wooden purse seiner with 235 hp engine; 25.18 GJ for mechanised gillnet/line fishing vessel with 89 hp engines; to 31.40 and 36.97 GJ, respectively, for wooden and steel trawlers powered by 99-106 hp engines.

Minimize frequency fluctuations of isolated power system with wind farm by using superconducting magnetic energy storage

Wind power generation as one of the most popular renewable energy applications is absorbing more and more attention all over the world. However, output power fluctuations of wind farm due to random variations of wind speed can cause network frequency and voltage flicker in power systems. The power quality consequently declines, particularly in an isolated power system such as the power system in a remote community or a small island. This paper proposes an application of superconducting magnetic energy storage (SMES) to minimize output fluctuations of an isolated power system with wind farm. The isolated power system is fed by a diesel generator and a wind generator consisting of a wind turbine and squirrel cage induction machine. The control strategy is detailed and the proposed system is evaluated by simulation in Matlab/Simulink.

Ecological limits of high-density milkfish farming

In the Philippines at present, milkfish farming in ponds includes a wide range of intensities, systems and practices. To make aquaculture possible, ecosystems are used as sources of energy and resources and as sinks for wastes. The growth of aquaculture is limited by the life-support functions of the ecosystem, and sustainability depends on matching the farming techniques with the processes and functions of the ecosystems, for example, by recycling some degraded resources. The fish farm has many interactions with the external environment. Serious environmental problems may be avoided if high-intensity farms are properly planned in the first place, at the farm level and at the level of the coastal zone where it can be integrated with other uses by other sectors. It is believed that the key to immediate success in the mass production of milkfish for local consumption and for export of value-added forms may be in semi-intensive farming at target yields of 3 tons per ha per year, double the current national average. Intensive milkfish farming will be limited by environmental, resource and market constraints. Integrated intensive farming systems are the appropriate long-term response to the triple needs of the next century: more food, more income, and more jobs for more people, all from less land, less resources, and less non-renewable energy.

Thermodynamic analysis of pumped thermal electricity storage

The increasing use of renewable energy technologies for electricity generation, many of which have an unpredictably intermittent nature, will inevitably lead to a greater need for electricity storage. Although there are many existing and emerging storage technologies, most have limitations in terms of geographical constraints, high capital cost or low cycle life, and few are of sufficient scale (in terms of both power and storage capacity) for integration at the transmission and distribution levels. This paper is concerned with a relatively new concept which will be referred to here as Pumped Thermal Electricity Storage (PTES), and which may be able to make a significant contribution towards future storage needs. During charge, PTES makes use of a high temperature-ratio heat pump to convert electrical energy into thermal energy which is stored as ‘sensible heat’ in two thermal reservoirs, one hot and one cold. When required, the thermal energy is then converted back to electricity by effectively running the heat pump backwards as a heat engine. The paper focuses on thermodynamic aspects of PTES, including energy and power density, and the various sources of irreversibility and their impact on round-trip efficiency.