<p>Anaerobic digestion uses a mixed, microbial community to convert organic wastes to biogas, thereby generating a clean renewable energy and reducing greenhouse gas emissions. However, few studies have quantified the relationship between waste composition and the subsequent physical and chemical changes in the digester. This Ph.D. dissertation aimed to gain new knowledge about how these differences in waste composition ultimately affect digester function. This dissertation examined three areas of digester function: (1) hydrogen sulfide production, (2) digester foaming, and (3) methane yield. </p> <p>To accomplish these aims, a variety of materials from four different large-scale field digesters were collected at different time points and from different locations within the digester systems, including influent, liquid in the middle of the digesters, effluent, and effluent after solids separation. The materials were used for biochemical methane potential (BMP) tests in 43 lab-scale lab-digester groups, each containing triplicate or duplicate digesters. The materials from field digesters and the effluents from the lab-digesters were analyzed for an extensive set of chemical and physical characteristics. The three areas of digester function were examined with the physical and chemical characteristics of the digester materials and effluents, and the BMP performances. </p> <p>Hydrogen sulfide productions in the lab-digesters ranged from non-detectable to 1.29 mL g VS^-1. Higher H₂S concentrations in the biogas were observed within the first ten days of testing. The initial Fe(II) : S ratio and OP concentrations had important influences on H₂S productions. Important parameters of digester influents related to digester foaming were the ratios of Fe(II) : S, Fe(II) : TP, and TVFA : TALK; and the concentrations of Cu. Digesters receiving mixed waste streams could be more vulnerable to foaming. The characteristics of each waste type varied significantly based on substrate and inoculum type, and digester functioning. The influent chemical characteristics of the waste significantly impacted all aspects of digester function. Using multivariate statistics and machine learning, models were developed and the prediction of digester outcomes were simulated based on the initial characteristics of the waste types. </p>

Du fait de la flexibilité énergétique qu'ils offrent et de leur potentiel de diminution des émissions de GES et de polluants, les réseaux de chaleur (RdC) sont un des leviers d'actions des politiques énergétiques locales en constante progression. Leur déploiement et/ou rénovation n'est pas qu'une question technico-économique classique, dans la mesure où ils sont au cœur d'un ensemble d'acteurs interconnectés, aux objectifs spécifiques, tous parties prenantes des politiques énergétiques locales. Dans ce contexte, les outils permettant à ces différents acteurs l'évaluation des actions liées aux RdC sont très importants. Ils doivent permettre l'évaluation de scénarios de conception, d'actions de rénovation, de performance et de suivi... Parmi les outils permettant ces évaluations, les approches par modélisation sont souvent trop spécifiques à une situation, un type de réseau un acteur... Le travail réalisé consiste à développer un outils de modélisation de RdC, offrant la flexibilité recherchée. "HeatGrid" permet de modéliser des architectures de réseaux variées. A chaque pas de temps, le fonctionnement du réseau est simulé grâce au formalisme de la programmation linéaire. Cet outil peut être utilisé en phase de conception ou d'exploitation d'un réseau. L'approche de modélisation permet d'évaluer et de comparer sous les aspects économiques, énergétiques et techniques d'un RdC sous différents scénarios. Plusieurs exemples sont simulés et analysés dans le but d'illustrer le potentiel du modèle. / Because of the energy flexibility that they offer and their potential to reduce GHG emissions, disctrict heating (DH) networks are a tool of local energy policies in constant progression. Their develpment and/or renovation is not only a classic technico-economical question, insofar as interconnected stakeholders of local energy policies, taking into account specific objectives, are concerned by DH networks. In this context, tools which enable these different stakeholders to evaluate actions related to DH networks are essential. They must be helpful for the assessment of renovation actions, the monitoring and the evaluation of performances....Among the tools that allow theses evaluations, the modelling approaches are often too specific to a situation, a type of network, a stakeholder... The work of the thesis consists in developing a DH modeling tool that has this desired flexibility. The proposed tool "HeatGrid" can model various network architectures. At each time step, the network running is simulated via linear programming formalism. This tool can be applied either at the design stage of a DH or at the operating stage. The model based approach enables the evaluation and comparison of economic, energy and technical aspects of the DH system in different scenarios. Several examples are simulated and analyzed in order to illustrate the potential of the model.

Government officials in the Caribbean are encouraging the production of electricity from renewable energy sources to reduce the impact of high electricity rates to customers due to region's dependency on imported fossil fuel. The purpose of this single-case study was to explore the strategies electric utility managers in the Caribbean used to implement renewable energy technologies. The diffusion of innovation theory served as the conceptual framework for the study. Three managers of an electric utility in the Caribbean, who had created strategies to implement renewable energy technologies, participated in face-to-face semistructured interviews. These managers provided in-depth information on approaches used to implement these technologies. Three themes emerged from the thematic analysis of data that were collected from the semistructured interviews and document reviews: development and integration of renewable energy technologies into utility operations, avoidance of future investments in fossil fuels, and inclusion of key stakeholders in the transition to implementing renewable energy technologies. The implications for social change to the Caribbean region from a successful implementation of the technologies may include employment opportunities through the creation of new industries, eradication of energy poverty, and a healthier and cleaner environment. Also, government officials can save significant foreign exchange by not having to import fossil fuel for electricity generation and use these savings to invest in other sectors that can provide further economic and social growth for the people of the region.

The UK’s decarbonisation strategy to increasingly electrify heating and transport will change the demand requirement on the electricity system. Additionally, under a climate change future, it is projected that the decarbonised grid will need to be able to operate under higher average temperatures in the UK, increasing the need for comfort cooling during summer and leading to additional electricity demand. These new demands will result in greater variation between minimum and peak demand as well as a significant increase in overall demand. Concurrently, supply-side decarbonisation programmes may lead to more intermittent renewables such as wind, PV, tidal and wave, elevating variability in electricity generation. Coupled with the anticipated higher variation in demand this brings on several challenges in operating the electricity grid. In order to characterise these challenges this research develops a bespoke electricity dispatch model which builds on hourly models of demand and generation. The hourly demand profiles are based on a high electrification of heating, transport and cooling coupled with future temperatures premised on the UKCP09 high emission scenario climate projections. The demand profiles show a significant increase in peak demand by 2050 reaching 194 GW, mainly due to summer cooling loads which contribute 70% of the demand. The cumulative CO2 emissions budgets of the GB power sector that are consistent with avoiding global climate change to 2°C are used to develop two low carbon generation scenarios distinguished by the amount of intermittent renewable generation technologies. The dispatch model tests the capability of generation scenarios with the use of hourly generation models in meeting future demand profiles out to 2050.The outputs from dispatch model indicate that there are shortages and excesses of generation relative to demand from 2030 onwards. The variability analysis outlines low and high generation periods from intermittent technologies along with the pace at which intermittent generation increases or decreases within an hour. The characterisation of variability analysis reveals the type of reserve capacity or smart solutions that are required to maintain the security of electricity supply. The solutions that could address the challenges quantified from the model outputs in operating a decarbonised GB electricity grid are explored using expert interviews. The analysis of the stakeholder interviews suggests smart grid solutions that include technologies as well as changes in operational procedures in order to enhance the operational resilience of the grid. Active Network Management through monitoring and control, demand management, storage systems and interconnectors are proposed to address challenges arising from varying demand and generation variability.

Buildings account for up to 40% of the total energy use in the world. Directives from the European Union have pointed out the significance of increasing the energy efficiency in buildings. New regulation in countries like Sweden has established that new buildings should fulfil regulations of Nearly Zero Energy Buildings (NZEB), providing the opportunity for renewable energy technologies to achieve these goals. In this paper, the retrofitting potential of renewable energy technologies for a single-family home in Sweden was investigated.The present work studied the characteristics of several renewable energy technologies and their applications for a single-family home in Sweden, including biomass, solar photovoltaics, solar thermal, heat pump, and small-scale wind turbine. Three renewable energy technologies (solar thermal, heat pump and small-scale wind turbine) and one renovation method (window) were selected to investigate. The analysis was made of the current energy use and the potential energy (and cost) savings from each retrofitting of these facilities by means of simulation models using IDA ICE software. The study results show that the proposed renewable energy technologies are technically feasible and economically viable as a source of alternative renewable energy in order to produce clean energy and reduce electricity bills for an electric-heated single-family home located in Sweden. Moreover, the combined retrofitting scheme consist of solar thermal system and window renovation was also proposed and explored. As a result the energy performance of the single-family home would satisfy the nearly-zero energy building requirements and thermal comfort could be maintained at an acceptable level.

Die Einführung neuartiger Energietechnologien wird allgemein als der Schlüssel zur Senkung klimaschädlicher Treibhausgase angesehen. Allerdings ist die Abbildung derartiger Technologien in numerischen Modellen zur Simulation und ökonomischen Analyse von energie- und klimaschutzpolitischen Maßnahmen vielfach noch rudimentär. Die Dissertation entwickelt neue Ansätze zur Einbindung von technologischen Innovationen in energie-ökonomische allgemeine Gleichgewichtsmodelle, mit dem Ziel den Energiesektor realitätsnäher abzubilden. Die Dissertation adressiert einige der Hauptkritikpunkte an allgemeinen Gleichgewichtsmodellen zur Analyse von Energie- und Klimapolitik: Die fehlende sektorale und technologische Disaggregation, die beschränkte Darstellung von technologischem Fortschritt, und das Fehlen von einem weiten Spektrum an Treibhausgasminderungsoptionen. Die Dissertation widmet sich zwei Hauptfragen: (1) Wie können technologische Innovationen in allgemeine Gleichgewichtsmodelle eingebettet werden? (2) Welche zusätzlichen und politikrelevanten Informationen lassen sich durch diese methodischen Erweiterungen gewinnen? Die Verwendung eines sogenannten Hybrid-Ansatzes, in dem neuartige Technologien für Stromerzeugung und Eisen- und Stahlherstellung in ein dynamisch multi-sektorales CGE Modell eingebettet werden, zeigt, dass technologiespezifische Effekte von großer Bedeutung sind für die ökonomische Analyse von Klimaschutzmaßnahmen, insbesondere die Effekte hinsichtlich von Technologiewechsel und dadurch bedingten Änderungen der Input- und Emissionsstrukturen. Darüber hinaus zeigt die Dissertation, dass Lerneffekte auf verschiedenen Stufen der Produktionskette abgebildet werden müssen: Für regenerative Energien, zum Beispiel, nicht nur bei der Anwendung von Stromerzeugungsanlagen, sondern ebenso auf der vorgelagerten Produktionsstufe bei der Herstellung dieser Anlagen. Die differenzierte Abbildung von Lerneffekten in Exportsektoren, wie zum Beispiel Windanlagen, verändert die Wirtschaftlichkeit und die Wettbewerbsfähigkeit und hat wichtige Implikationen für die ökonomische Analyse von Klimapolitik. / Energy technologies and innovation are considered to play a crucial role in climate change mitigation. Yet, the representation of technologies in energy-economy models, which are used extensively to analyze the economic, energy and environmental impacts of alternative energy and climate policies, is rather limited. This dissertation presents advanced techniques of including technological innovations in energy-economy computable general equilibrium (CGE) models. New methods are explored and applied for improving the realism of energy production and consumption in such top-down models. The dissertation addresses some of the main criticism of general equilibrium models in the field of energy and climate policy analysis: The lack of detailed sectoral and technical disaggregation, the restricted view on innovation and technological change, and the lack of extended greenhouse gas mitigation options. The dissertation reflects on the questions of (1) how to introduce innovation and technological change in a computable general equilibrium model as well as (2) what additional and policy relevant information is gained from using these methodologies. Employing a new hybrid approach of incorporating technology-specific information for electricity generation and iron and steel production in a dynamic multi-sector computable equilibrium model it can be concluded that technology-specific effects are crucial for the economic assessment of climate policy, in particular the effects relating to process shifts and fuel input structure. Additionally, the dissertation shows that learning-by-doing in renewable energy takes place in the renewable electricity sector but is equally important in upstream sectors that produce technologies, i.e. machinery and equipment, for renewable electricity generation. The differentiation of learning effects in export sectors, such as renewable energy technologies, matters for the economic assessment of climate policies because of effects on international competitiveness and economic output.

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<p>As society works to reduce its reliance on fossil fuels, the demand for renewable energy and clean energy technologies continues to grow rapidly. Lessons learned from the ongoing electronics waste crisis necessitate closing material loops to secure supply chains and redirect valuable resources away from the landfills.</p><p> </p><p>Inspired by the principles of industrial ecology, the circularization of renewables is demonstrated by applying the notion of Life Cycle Symbiosis (LCS), an extension of Industrial Symbiosis (IS). This is achieved by identifying waste streams that may have value as potential raw material/feedstock and the subsequent development of industrial synergies in the context of end of life (EoL) photovoltaics (PVs). Per metric ton of EoL PVs, the avoided global warming potential (GWP) and ecotoxicity impacts were calculated to be as high as 2750 kg CO₂ eq and 32,000 CTUe respectively, while the water savings and electricity savings were over 37,000 m³ and 3600 MJ. Building upon this work, a hybrid multi objective optimization (MOO) method was proposed to support the creation of industrial synergistic networks or eco industrial parks (EIPs). The hybrid method addresses the challenges associated with the early design and development stages of EIPs (supply, demand, potential synergies, etc.), and also those in relation to considering multiple conflicting sustainability objectives.</p><p> </p><p>Apart from addressing material scarcity, rising pollution levels and exposure to toxins, recovery and circularization may also contribute towards stabilizing feedstock prices. Supply chains for renewables and clean energy technologies are brittle because of risks associated with possible supply deficits stemming from complex geo-political situations and oligopolies. This can translate to price fluctuations among high-value, critical materials on which clean energy technologies rely. In order to ensure a smooth transition to a clean energy technologies, and one that is also sustainable, it is vital to assess the impact of these very complexities on the market dynamics for the critical material feedstocks. To this end, a system dynamics model has been developed to capture price trends of rare earth elements (REEs) used in EVs under varying market scenarios. The proposed model aims to aid automobile manufacturers in developing effective business strategies as they work towards electrifying their vehicle fleets.</p><p>This thesis reports on the development of some strategies rooted in industrial ecology to prevent renewables and clean energy technologies from themselves becoming environmental liabilities in the future.</p>