Decision Making under Uncertainty and Competition for Sustainable Energy Technologies

This dissertation addresses the main challenges faced in the transition to a more sustainable energy sector by applying modelling tools that could design more effective managerial responses and provide policy insights. To mitigate the impact of climate change, the electric power industry needs to reduce markedly its emissions of greenhouse gases. As energy consumption is set to increase in the foreseeable future, this can be achieved only through costly investments in more efficient conventional generation or in renewable energy resources. While more energy-efficient technologies are commercially available, the deregulation of most electricity industries implies that investment decisions need to be taken by private investors with government involvement limited to setting policy measures or designing market rules. Thus, it is desirable to understand how investment and operational decisions are to be made by decentralised entities that face uncertainty and competition. One of the most efficient thermal power technologies is cogeneration, or combined heat and power (CHP), which can recover heat that otherwise would be discarded from conventional generation. Cogeneration is particularly efficient when the recovered heat can be used in the vicinity of the combustion engine. Although governments are supporting on-site CHP generation through feed-in tariffs and favourable grid access, the adoption of small-scale electricity generation has been hindered by uncertain electricity and gas prices. While deterministic and real options studies have revealed distributed generation to be both economical and effective at reducing CO2 emissions, these analyses have not addressed the aspect of risk management. In order to overcome the barriers of financial uncertainties to investment, it is imperative to address the decision-making problems of a risk-averse energy consumer. Towards that end, we develop a multi-stage, stochastic mean-risk optimisation model for the long-term and medium-term risk management problems of a large consumer. We first show that installing a CHP unit not only results in both lower CO2 emissions and expected running cost but also leads to lower risk exposure. In essence, by investing in a CHP unit, a large consumer obtains the option to use on-site generation whenever the electricity price peaks, thereby reducing significantly its financial risk over the investment period. To provide further insights into risk management strategies with on-site generation, we examine also the medium-term operational problem of a large consumer. In this model, we include all available contracts from electricity and gas futures markets, and analyse their interactions with on-site generation. We conclude that by swapping the volatile electricity spot price for the less volatile gas spot price, on-site generation with CHP can lead to lower risk exposure even in the medium term, and it alters a risk-averse consumer’s demand for futures contracts. While extensive subsidies have triggered investments in renewable generation, these installations need to be accompanied by transmission expansion. The reason for this is that solar and wind energy output is intermittent, and attractive solar and wind sites are often located far away from demand centres. Thus, to integrate renewable generation into the grid system and to maintain a reliable and secure electricity supply, a vastly improved transmission network is crucial. Finding the optimal transmission line investments for a given network is already a very complex task since these decisions need to take into account future demand and generation configurations, too, which now depend on private investors. To address these concerns, our third study models the problem of wind energy investment and transmission expansion jointly through a stochastic bi-level programming model under different market designs for transmission line investment. This enables the game-theoretic interaction between distinct decision makers, i.e., those investing in power plants and those constructing transmission lines, to be addressed directly. We find that under perfect competition only one of the wind power producers, the one with lower capital cost, makes investment and to a lower degree under a profit-maximising merchant investor (MI) than under a welfare-maximising transmission system operator (TSO), as the MI reduces the transmission capacity to increase congestion rent. In addition, we note that regardless of whether the grid expansion is carried out by the TSO or by the MI, a higher proportion of wind energy is installed when power producers exercise market power. In effect, strategic withholding of generation capacity by producers prompts more transmission investment since the TSO aims to increase welfare by subsidising wind and the MI creates more flow to maximise profit. Under perfect competition, a higher level of wind generation can be achieved only through mandating renewable portfolio standards (RPS), which in turn results also in increased transmission investment

Optimal Operation of Combined Heat and Power under Uncertainty and Risk Aversion

Despite the proven benefits of combined heat and power (CHP) and recently introduced subsidies to support it, CHP adoption has not met its targets. One of the possible reasons for this is risk from uncertain electricity and gas prices. To gain insights into the risk management of a CHP unit, we develop a multi-stage stochastic mean-risk optimisation model for the medium-term management of a distributed generation system with a gas-fired microturbine with heat recovery and a boiler. The model adopts the perspective of a large consumer that procures gas (for on-site generation) and electricity (for consumption) on the spot and futures markets. The consumer's risk aversion is incorporated into the model through the conditional value-at-risk (CVaR) measure. We show that CHP not only decreases the consumer's expected cost and risk exposure by 10% each but also improves expected energy efficiency by 4 percentage points and decreases expected CO2 emissions by 16%. The risk exposure can be further mitigated through the use of financial contracts

Optimal Selection of Distributed Energy Resources under Uncertainty and Risk Aversion

The adoption of small-scale electricity generation has been hindered by uncertain electricity and gas prices. In order to overcome this barrier to investment, we develop a mean-risk optimization model for the long-term risk management problem of an energy consumer using stochastic programming. The consumer can invest in a number of generation technologies, and also has access to electricity and gas futures to reduce its risk. We examine the role of on-site generation in the consumer’s risk management strategy, as well as interactions between on-site generation and financial hedges. Our study shows that by swapping electricity (with high price volatility) for gas (with low price volatility), even relatively inefficient technologies reduce risk exposure and CO _2 emissions. The capability of on-site generation is enhanced through the use of combined heat and power (CHP) applications. In essence, by investing in a CHP unit, a consumer obtains the option to use on-site generation whenever the electricity price peaks, thereby reducing its financial risk. Finally, in contrast to the extant literature, we demonstrate that on-site generation affects the consumer’s decision to purchase financial hedges. In particular, while on-site generation and electricity futures may act as substitutes, on-site generation and gas futures can function as complements

Bentall procedure: quarter century of clinical experiences of a single surgeon

BACKGROUND: We retrospectively analyzed 25 years of experiences with the button Bentall procedure in patients with aortic root pathologies. Even though this procedure has become widespread, there are only a few very long term follow-ups available in the clinical literature, especially regarding single surgeon results. METHODS: Between 1988 and 2013, a total of 147 patients underwent the Bentall procedure by the same surgeon. Among them there were 62 patients with Marfan syndrome. At the time of the surgery the mean age was 46.5 +/- 17.6 years. The impact of surgical experience on long-term survival was evaluated using a cumulative sum analysis chart. RESULTS: The Kaplan-Meier estimated overall survival rates for the 147 patients were 91.8 +/- 2.3 %, 84.3 +/- 3.1 %, 76.3 +/- 4.9 % and 59.5 +/- 10.7 % at 1,5,10 and 20 years, respectively. Multivariate Cox regression analysis identified EuroSCORE II over 3 % (OR 4.245, 95 % CI, 1.739-10.364, p = 0.002), acute indication (OR 2.942, 95 % CI, 1.158-7.480, p = 0.023), use of deep hypothermic circulatory arrest (OR 3.267, 95 % CI, 1.283-8.323, p = 0.013), chronic kidney disease (OR 6.865, 95 % CI, 1.339-35.189, p = 0.021) and early complication (OR 3.134, 95 % CI, 1.246-7.883, p = 0.015) as significant risk factors for the late overall death. The survival rate for freedom from early complication was 94.3 +/- 2.2 %, 88.0 +/- 3.3 %, 82.9 +/- 4.7 % and 69.2 +/- 8.4 % at 1,5,10 and 20 years. The main pathological findings of the aortic wall were cystic medial degeneration in 75 %, fibrosis in 6 %, atherosclerosis in 13 % and no pathological alteration in 6 % of the samples. The overall survival rate was significantly lower in patients operated in first 15 years compared to patients operated in the last decade (log-rank p = 0.011). CONCLUSION: According to our long-term follow-up the Bentall operation provides an appropriate functional result by resolving the lesions of the ascending aorta. Based on our results, 25-30 operations done is necessary to gain such a level of confidence and experince to aquire better results on long-term survival. In addition, we discussed that there were no co-morbidities affecting on the survival of Marfan patients and prophylactic aortic root replacement ensures a longer survival among patients with Marfan syndrome

Classification of human coronary atherosclerotic plaques with T1, T2 and Ultrashort TE MRI

Multicontrast MRI with T1, T2 and Ultrashort TE (UTE) sequences is used to image atherosclerotic plaque in human coronary arteries. MRI classification of the plaques is compared with their histological classification and found to correlate extremely well. The addition of UTE MRI adds significant value to the imaging of human coronary artery plaque by MRI

Laterality of deep white matter hyperintensities correlates with basilar artery bending and vertebral artery dominance

Aim To investigate whether vertebrobasilar geometry contributes to the presence, severity, and laterality of white matter hyperintensities (WMH). Methods We retrospectively reviewed 290 cerebral scans of patients who underwent time-of-flight and fluid-attenuated inversion recovery (FLAIR) magnetic resonance imaging (MRI) between 2017 and 2018. WMH were counted, localized, and grouped according to laterality on the FLAIR sequence. A 3D mesh of the posterior circulation was reconstructed (with ITK SNAP software) and the morphology of the vertebrobasilar system analyzed with an in-house software written in Python. Results Patients were assigned into a group with WMH (n=204) and a group without WMH (n=86). The severity of WMH burden was mainly affected by age and hypertension, while the localization of the WMH (or laterality) was mainly affected by the vertebrobasilar system morphology. Basilar artery morphology only affected the parietooccipital region significantly if both posterior communicating arteries were hypoplastic or absent. The dominant vertebral artery and basilar artery curve had an opposite directional relationship. Conclusions An unequal vertebral artery flow is an important hemodynamic contributor to basilar bending. Increased basilar artery curvature and increased infratentorial WMH burden may signal inadequate blood flow and predict cerebrovascular events

Rising utilization of coronary CT angiography across Europe over the last decade: insights from a large prospective European registry

Abstract Background/Introduction The recently updated 2019 ESC guidelines for the diagnosis and management of chronic coronary syndromes endorse the use of coronary computed tomography angiography (CCTA) for exclusion of obstructive coronary artery disease in patients with a low clinical likelihood (Class I, LOE B). Higher demand for CCTA requires broad availability, inevitably involving smaller healthcare providers, such as non-academic hospitals and private practices. Nevertheless, most published data on CCTA image quality and safety rely on exams performed in high-volume academic centers, and little is known about CCTA in non-academic settings. Purpose To investigate the utilization of CCTA across Europe over the last decade, focusing on differences between academic and non-academic centers. Methods We included patients with stable chest pain and suspected coronary artery disease (CAD) who received CCTA and were included in the European Society of Cardiovascular Radiology MR/CT registry 01/2010–01/2020. We compared CT equipment, image quality, radiation dose, the incidence of periprocedural adverse events, patient characteristics, and CCTA findings between academic (high volume university hospitals) and non-academic centers (non-academic hospitals and private practices). Results Overall, 64,317 patients (41.2% women; age 60±13 years) from 212 sites across 19 European countries were included. Academic centers submitted most cases in 2010—2014 (51.6%), whereas non-academic centers accounted for 71.3% of records in 2015–2020. While non-academic centers used less advanced technology, radiation dose remained low (4.54 [interquartile range (IQR) 2.28–6.76] mSv) with a 30% decline of high-dose scans (>7 mSv) over time. Diagnostic image quality was reported in 97.7% of cases, and the rate of acute scan-related events was low (0.4%) (Figure 1). From 2010–2014 to 2015–2020, CCTA nearly doubled in patients with low to intermediate pretest-probability, women >50, and 40–60 years old men (Figure 2). CAD presence and extent decreased slightly over time (prevalence: 2010–2014: 41.5% vs. 2015–2020: 40.6%), (multi-vessel disease in those with CAD: 2010–2014: 61.9% vs. 2015–2020: 55.9%; all p<0.01). Conclusion CCTA expands rapidly to non-academic centers across Europe, increasing availability while maintaining relatively low radiation dose, high diagnostic image quality, and safety. Broad availability of high-quality CCTA is essential for a successfully implementation of the recently updated guidelines for the diagnosis and management of chronic coronary syndromes. Funding Acknowledgement Type of funding sources: None. Changes in CCTA utilizationChanges in patient characteristic

Prediction of incident cardiovascular events using machine learning and CMR radiomics.

OBJECTIVES: Evaluation of the feasibility of using cardiovascular magnetic resonance (CMR) radiomics in the prediction of incident atrial fibrillation (AF), heart failure (HF), myocardial infarction (MI), and stroke using machine learning techniques. METHODS: We identified participants from the UK Biobank who experienced incident AF, HF, MI, or stroke during the continuous longitudinal follow-up. The CMR indices and the vascular risk factors (VRFs) as well as the CMR images were obtained for each participant. Three-segmented regions of interest (ROIs) were computed: right ventricle cavity, left ventricle (LV) cavity, and LV myocardium in end-systole and end-diastole phases. Radiomics features were extracted from the 3D volumes of the ROIs. Seven integrative models were built for each incident cardiovascular disease (CVD) as an outcome. Each model was built with VRF, CMR indices, and radiomics features and a combination of them. Support vector machine was used for classification. To assess the model performance, the accuracy, sensitivity, specificity, and AUC were reported. RESULTS: AF prediction model using the VRF+CMR+Rad model (accuracy: 0.71, AUC 0.76) obtained the best result. However, the AUC was similar to the VRF+Rad model. HF showed the most significant improvement with the inclusion of CMR metrics (VRF+CMR+Rad: 0.79, AUC 0.84). Moreover, adding only the radiomics features to the VRF reached an almost similarly good performance (VRF+Rad: accuracy 0.77, AUC 0.83). Prediction models looking into incident MI and stroke reached slightly smaller improvement. CONCLUSIONS: Radiomics features may provide incremental predictive value over VRF and CMR indices in the prediction of incident CVDs. KEY POINTS: • Prediction of incident atrial fibrillation, heart failure, stroke, and myocardial infarction using machine learning techniques. • CMR radiomics, vascular risk factors, and standard CMR indices will be considered in the machine learning models. • The experiments show that radiomics features can provide incremental predictive value over VRF and CMR indices in the prediction of incident cardiovascular diseases

Anatomical characteristics of the left atrium and left atrial appendage in relation to the risk of stroke in patients with versus without atrial fibrillation

Background: The left atrial appendage (LAA) has been regarded as an important source of cardiac thrombus formation and appears important in the contribution to thromboembolism in patients with atrial fibrillation (AF). Our aim was to evaluate the relationship between LAA morphology and previous stroke or transient ischemic attack in 2 large and distinct patient cohorts with and without known AF. Methods: The study population consisted of patients with and without drug-refractory AF who underwent computed tomography before transcatheter AF ablation or clinically indicated for suspected coronary artery disease. The computed tomography data were used for volumetric assessment of the left atrium and LAA and to determine LAA morphology. The LAA was classified by 3 readers in consensus as chicken wing, swan, cauliflower, or windsock, based on predefined morphology classification criteria. Results: In total, 1813 patients (mean age 59 +/- 11 years, 42% female) who underwent computed tomography were included in this analysis (908 patients with AF and 905 patients without known AF). Swan LAA morphology was independently associated with prior stroke/transient ischemic attack in the overall study population (odds ratio, 3.40, P<0.001), and in patients with (odds ratio, 2.88, P=0.012) and without known AF (odds ratio, 3.96, P=0.011). Conclusions: Swan morphology of the LAA is independently associated with prior stroke or transient ischemic attack in patients with known AF, as well as in patients not previously diagnosed with AF.Cardiolog

Heritability of Coronary Artery Disease: Insights From a Classical Twin Study

Genetics have a strong influence on calcified atherosclerotic plaques; however, data regarding the heritability of noncalcified plaque volume are scarce. We aimed to evaluate genetic versus environmental influences on calcium (coronary artery calcification) score, noncalcified and calcified plaque volumes by coronary computed tomography angiography in adult twin pairs without known coronary artery disease. METHODS: In the prospective BUDAPEST-GLOBAL (Burden of Atherosclerotic Plaques Study in Twins—Genetic Loci and the Burden of Atherosclerotic Lesions) classical twin study, we analyzed twin pairs without known coronary artery disease. All twins underwent coronary computed tomography angiography to assess coronary atherosclerotic plaque volumes. Structural equation models were used to quantify the contribution of additive genetic, common environmental, and unique environmental components to plaque volumes adjusted for age, gender, or atherosclerotic cardiovascular disease risk estimate and statin use. RESULTS: We included 196 twins (mean age±SD, 56±9 years, 63.3% females), 120 monozygotic and 76 same-gender dizygotic pairs. Using structural equation models, noncalcified plaque volume was predominantly determined by environmental factors (common environment, 63% [95% CI, 56%–67%], unique environment, 37% [95% CI, 33%–44%]), while coronary artery calcification score and calcified plaque volumes had a relatively strong genetic heritability (additive genetic, 58% [95% CI, 50%–66%]; unique environmental, 42% [95% CI, 34%–50%] and additive genetic, 78% [95% CI, 73%–80%]; unique environmental, 22% [95% CI, 20%–27%]), respectively. CONCLUSIONS: Noncalcified plaque volume is mainly influenced by shared environmental factors, whereas coronary artery calcification score and calcified plaque volume are more determined by genetics. These findings emphasize the importance of early lifestyle interventions in preventing coronary plaque formation. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT01738828