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Cleantech SMEs’ Expectations and Perceptions of an Established Community-based Intermediary Moving into their SectorDahiya, Sushil January 2013 (has links)
Innovation intermediaries provide a range of services to assist firms during the process of innovation. How SMEs perceive innovation intermediaries is an area of investigation that would provide important information on how innovation intermediaries’ assist small and medium enterprises (SMEs). This study focuses on the cleantech industry and explores SMEs’ expectations and perceptions of an established community-based intermediary (CBI) moving into their sector. A qualitative research methodology was adopted to collect data from 15 sample SMEs. In regards to SMEs, the findings show that cleantech companies face financing, partnerships, marketing, sales, regulatory and bureaucratic challenges. In regards to innovation intermediaries, the findings showcase how CBI, a regional intermediary, is not effective in supporting cleantech SMEs with their sector specific needs or challenges.
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Přenosová soustava ČR po roce 2040 / Transmission system of the Czech Republic after 2040Gabrys, Dominik January 2020 (has links)
This master thesis is focused on issue transimission system of Czech republic after 2040. Thesis is divided in two parts, teoretical and practical. Teoretical part contains present trends of transmission sytem and the most probably changes in the future decade. Practical part contains simulation of Czech transmission system and various scenarios with idea of open source.
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Time Series forecasting of the SP Global Clean Energy Index using a Multivariate LSTMLarsson, Klara, Ling, Freja January 2021 (has links)
Clean energy and machine learning are subjects that play significant roles in shaping our future. The current climate crisis has forced the world to take action towards more sustainable solutions. Arrangements such as the UN’s Sustainable Development Goals and the Paris Agreement are causing an increased interest in renewable energy solutions. Further, the EU Taxonomy Regulation, applied in 2020, aims to scale up sustainable investments and to direct cash flows toward sustainable projects and activities. These measures create interest in investing in renewable energy alternatives and predicting future movements of stocks related to these businesses. Machine learning models have previously been used to predict time series with promising results. However, predicting time series in the form of stock price indices has, throughout previous attempts, proved to be a difficult task due to the complexity of the variables that play a role in the indices’ movements. This paper uses the machine learning algorithm long short-term memory (LSTM) to predict the S&P Global Clean Energy Index. The research question revolves around how well the LSTM model performs on this specific index and how the result is affected when past returns from correlating variables are added to the model. The researched variables are crude oil price, gold price, and interest. A model for each correlating variable was created, as well as one with all three, and one standard model which used only historical data from the index. The study found that while the model with the variable which had the strongest correlation performed best among the multivariate models, the standard model using only the target variable gave the most accurate result of any of the LSTM models. / Den pågående klimatkrisen har tvingat allt fler länder till att vidta åtgärder, och FN:s globala hållbarhetsmål och Parisavtalet ökar intresset för förnyelsebar energi. Vidare lanserade EU-kommissionen den 21 april 2021 ett omfattande åtgärdspaket, med syftet att öka investeringar i hållbara verksamheter. Detta skapar i sin tur ett ökat intresse för investeringar i förnyelsebar energi och metoder för att förutspå aktiepriser för dessa bolag. Maskininlärningsmodeller har tidigare använts för tidsserieanalyser med goda resultat, men att förutspå aktieindex har visat sig svårt till stor del på grund av uppgiftens komplexitet och antalet variabler som påverkar börsen. Den här uppsatsen använder sig av maskininlärningsmodellen long short-term memory (LSTM) för att förutspå S&P:s Global Clean Energy Index. Syftet är att ta reda på hur träffsäkert en LSTM-modell kan förutspå detta index, och hur resultatet påverkas då modellen används med ytterligare variabler som korrelerar med indexet. De variabler som undersöks är priset på råolja, priset på guld, och ränta. Modeller för var variabel skapades, samt en modell med samtliga variabler och en med endast historisk data från indexet. Resultatet visar att den modell med den variabel som korrelerar starkast med indexet presterade bäst bland flervariabelmodellerna, men den modell som endast användes med historisk data från indexet gav det mest träffsäkra resultatet.
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Public policy and clean energy venture capital private equity investments in South AfricaDzenga, Bruce 03 1900 (has links)
Thesis (MDF)--Stellenbosch University, 2013. / ENGLISH ABSTRACT: In 2007, Bürer and Wüstenhagen (2009) conducted a survey amongst European and United States venture capital and private equity investors (VC/PE) to ascertain their public clean energy policy preference and concluded that VC/PE investors view the feed-in tariff (FIT) scheme to be the most preferred policy option.
In this research study, the author re-conducted part of the Bürer and Wüstenhagen (2009) survey with thirty South African VC/PE investors to determine their perceptions on clean energy public policy preference. It is evident from the survey, that opinions are varied and at times even contradictory. This in itself demonstrates an important feature of the South African VC/PE and clean energy industry: it is young, dynamic, changing rapidly and can look very different, depending on the vantage point.
The investors surveyed were mainly optimistic about the long-term development of the South African renewable energy industry led by private investors. VC/PE investors in South Africa have mixed views on various investment options, and are concerned about both the regulatory and macro-economic trends. The interviews and survey results show a number of recurring issues. Altogether, the survey results indicate that VC/PE investors consider FITs to be the best public clean energy policy instrument in leveraging private investment and finance for renewable energy in South Africa.
This study serves to illustrate and confirm, in line with empirical studies, that VC/PE investors in South Africa believe that clean energy market-pull policies provide an impetus and indeed spur private investor participation in clean energy in developing countries. While it is true that most VC/PE investors would prefer the price certainty associated with a FIT regime, this is almost an irrelevant question in South Africa since constitutionally the state is bound to procure through competitive tendering. This study also serves to highlight the need for more active research and attention in this field.
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Pellet PowerVice President Research, Office of the January 2009 (has links)
Wood pellets are offering opportunities for a cleaner-burning biofuel but major concerns are overshadowing their potential. Tony Bi and UBC’s Clean Energy Research Centre are engineering solutions.
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Beyond the market fix: shaping emerging climate strategies.Biggar, Jamie 17 December 2010 (has links)
This thesis offers a critique of the dominant strategy to prevent catastrophic climate change, which I call the market fix, and starting points for developing an alternative strategy, which I call the common transition. To prevent catastrophic climate change GHG emissions must both peak by around 2015 and be reduced to near zero by 2050. I will argue that it is unlikely that the market fix will be able to reduce GHG emissions sufficiently because there is a powerful and resilient drive for destructive kinds of economic growth embedded in the relationship between states and the global economy. For this reason, the market fix relies on unrealistically rapid technological development to reduce GHG emissions sufficiently without threatening general economic growth or powerful economic interests. I will argue that self organizing networks and commons institutions, the two key elements of the common transition, can be woven together to change the relationship between societies and their economies in order to weaken the drive for destructive kinds of economic growth, directly reduce GHG emissions, and create a new context for climate action in which societies have a greater ability to achieve zero GHG emissions by 2050.
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Investigating the introduction of e-mobility in South AfricaOtto, Willem Liebrecht 12 1900 (has links)
Thesis (MEng)--Stellenbosch University, 2014. / ENGLISH ABSTRACT: See PDF for abstract. / AFRIKAANSE OPSOMMING: Sien die PDF vir die opsomming.
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The relationships of alternative energies with the technology sector and non-renewable energiesBarão, Ricardo January 2015 (has links)
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Previous issue date: 2015 / Este trabalho tem como objectivo compreender de que forma os investidores veem as energias renováveis: se as veem como parte do sector tecnológico, à espera de novos desenvolvimentos, ou como uma alternativa aos métodos existentes de produção de energia. Para responder a esta questão, foi desenvolvido um modelo de vectores autoregressivos com quatro variáveis de forma a se poder aplicar um Granger causality test e Impulse Response function. Os resultados sugerem que para o período de 2002-2007 à escala global ambas as hipóteses se confirmam, porém de 2009-2014 os resultados sugerem que os investidores não reconhecem as energias renováveis como um ramo do sector tecnológico, neste período. Para além disso, durante o período de 2009-2014, e quando comparados investidores Americanos com Europeus, os resultados sugerem que apenas o último identifica as energias renováveis como uma fonte viável para a produção energética. / This work aimed to understand the investor perception on clean energy: if it is seen as part of the technology sector, awaiting new developments, or as an alternative to the existing energy production methods. To answer this question, a four variable vector autoregression model was developed so that a Granger causality test and Impulse response function could be applied. The results suggest that while both hypotheses were confirmed worldwide for the period 2002-2007, from 2009 to 2014 results suggest that investors do not recognize the field of clean energy as part of the technology sector. Moreover, during the period that ranges from 2009 to 2014, and when comparing the American investor with the European investor, only the latter identifies renewable energy as a viable source of energy production.
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Essays in Environmental Economics and Human CapitalKuate Fotue, Landry 20 January 2023 (has links)
Chapter 1: This paper offers new causal evidence on how the timing of prenatal temperature shocks affects fetal health, sex ratio at birth, and early-age human capital. Analyzing data on nearly 2 million live births from sub-Saharan African countries and exploiting exogenous spatial and temporal variation in monthly temperature, we uncover three findings. First, we find that a cold temperature shock decreases the likelihood of a male birth. This effect is non-linear, being larger in the first and third trimesters of pregnancy. It is also highly heterogeneous, being larger for older women, higher parity births, and rural areas. Second, combining our empirical estimates with a climate model, we find that the number of fetal deaths caused by climate change will rise from 200 to 400 per 100,000 live births by 2050 throughout sub-Saharan Africa. Third, in contrast to their differential effect on fetal mortality, prenatal temperature shocks increase infant mortality more for females than for males, suggesting that only healthier male fetuses survive to adverse in utero conditions. Our analysis implies that the design of policies to avert the negative impacts of climate change on children should account for stages of fetal development.
Chapter 2: Despite its enormous individual and social costs; the fundamental and long- run causes of cognitive aging remain understudied. We study the causal effect of in-utero temperature exposure on cognition during old age. Combining unique data on South African adults between 40 and 99 years of age with geospatial information on historical temperatures, our identification strategy exploits exogenous, within-municipality-of-birth, month-to-month variations in temperature, and controls for contemporaneous weather and location at the time of survey administration. We find that temperature in the first trimester of pregnancy negatively affects the cognitive function score later in life, but temperature in the second and third trimesters has a positive effect on adults cognitive function score. These differing effects result in an overall U-shaped relationship between prenatal exposure to temperature and cognition. This non-linear relationship is robust across measures of memory, reasoning, and information processing speed. Our findings are consistent with the fetal programming theory, which holds that the first trimester of pregnancy is the most crucial window of brain formation. In accordance with this theory, brain development occurring in the first trimester of pregnancy would therefore have the highest vulnerability to external shocks. Heterogeneity analysis reveals that the effect of prenatal temperature on cognition is larger for men, individuals over 75 years of age, and individuals with low social capital. Analyzing causal mechanisms, we find that prenatal temperature affects key determinants of individuals' cognitive reserve. We also find that exposure to drought during the first trimester of pregnancy and reduced sleep during adulthood are other potential channels through which the effects of prenatal exposure to temperature operate.
Chapter 3: A large literature seeking to understand the labor market impacts associated with the clean energy transitions broadly finds opposite effects. On the one hand, a net positive impact on the workforce i.e. the new green jobs created in renewable energy sectors will compensate for the jobs lost in fossil-fuel sectors, while on the other hand, the so-called regulated dirty energy sector will reduce the fraction of workers hired. However, empirical and simulation models typically ignore transitional impacts associated with environmental regulations on labour. These relate to how workers adjust over time to environmental regulations, not just the steady state impact that is the focus of prior studies. We evaluate an environmental regulation (Ontario coal-fired electricity generating plants phase-out) regarding its transitional and long-term impacts on employee's outcomes including (i) wages; (ii) unemployment insurance; (iii) sector mobility; and (iv) geographic location. Using the Longitudinal Worker File (LWF) and Postal Codes Conversion File (PCCF) maintained by Statistics Canada, we estimate the labor market impacts of clean energy policy by comparing employees from affected coal plants to a comparable group of employees from non-affected plants. We find that, workers exposed to Ontario phase-out coal policy have earned on average 7000 $ CAD yearly less compared to those who weren't exposed. Our findings are consistent across a set of alternative specifications and robustness checks. Moreover, results from the event study approach suggest that the regulation leads to labor costs with the de- cline of wages just in transition. We provide supportive evidence on large labor costs due to environmental regulation policy and shed lights on the importance of reforms and training programs to support workers during the transition.
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Toward the Industrial Application of a Solid-Oxide Fuel Cell Power Plant with Compressed Air Energy Storage / Design, Simulation, Optimization, Techno-Economic Analyses and Life-Cycle Analyses of Solid-Oxide Fuel Cell Power PlantsNease, Jacob January 2016 (has links)
The global electricity generation industry is very reliant on the use of fossil fuels, particularly natural gas and coal. However, it is quickly becoming a reality that the over-consumption of these resources will continue to lead to significant global damage via global warming, ecosystem destruction, and the depletion of these so-called non-renewable re-sources. To combat this issue, renewable sources such as wind, biofuels and solar are be-coming much more prevalent in the power generation industry, but significant economic, reliability and availability barriers to entry will prevent these sources from being major contributors to the power industry for decades.
To this end, this thesis focuses on the design, operation, optimization and life cycle analysis of an integrated solid-oxide fuel (SOFC) cell power plant integrated with com-pressed air energy storage (CAES). This plant, fueled by either natural gas or coal, can make much more efficient use of their limited non-renewable fuel sources, and are capable of achieving nearly 100% carbon capture at the plant boundary. This plant is intended to serve as a more efficient and environmentally responsible alternative to current power generation methods while still exploiting remaining fossil fuels to their fullest extent.
This thesis details the design, sizing and simulation of integrated SOFC/CAES plants in Aspen Plus so that full feasibility and techno-economic analyses may be performed, the results of which are then compared to the current state-of-the-art (SOTA) options. In order to compare the plants on an environmental level, full cradle-to-grave life-cycle analyses using the ReCiPe 2008 method are completed for each SOFC-based plant and all comparable SOTA options under a wide range of assumptions and plant configurations, such as the use of carbon capture strategies. Furthermore, detailed reduced-order dynamic models of the integrated SOFC/CAES plants are developed and simulated with a newly developed rolling-horizon optimization method to assess the load-following capabilities of the integrated plant. Real scaled demand data for the market of Ontario, Canada for the years 2013 and 2014 are used as the demand data for the simulations.
This thesis takes strides in proving the feasibility of an integrated SOFC/CAES power plant for providing clean, efficient, reliable and cost-effective power using fossil fuels. The next steps for this project involve the development of a lab-scale pilot plant, which would be used to validate simulation results and provide an opportunity for the real-time application and assessment of the potential of this plant design. / Thesis / Doctor of Philosophy (PhD)
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