Erythroid-Specific Transcriptional Changes in PBMCs from Pulmonary Hypertension Patients

Gene expression profiling of peripheral blood mononuclear cells (PBMCs) is a powerful tool for the identification of surrogate markers involved in disease processes. The hypothesis tested in this study was that chronic exposure of PBMCs to a hypertensive environment in remodeled pulmonary vessels would be reflected by specific transcriptional changes in these cells.The transcript profiles of PBMCs from 30 idiopathic pulmonary arterial hypertension patients (IPAH), 19 patients with systemic sclerosis without pulmonary hypertension (SSc), 42 scleroderma-associated pulmonary arterial hypertensio patients (SSc-PAH), and 8 patients with SSc complicated by interstitial lung disease and pulmonary hypertension (SSc-PH-ILD) were compared to the gene expression profiles of PBMCs from 41 healthy individuals. Multiple gene expression signatures were identified which could distinguish various disease groups from controls. One of these signatures, specific for erythrocyte maturation, is enriched specifically in patients with PH. This association was validated in multiple published datasets. The erythropoiesis signature was strongly correlated with hemodynamic measures of increasing disease severity in IPAH patients. No significant correlation of the same type was noted for SSc-PAH patients, this despite a clear signature enrichment within this group overall. These findings suggest an association of the erythropoiesis signature in PBMCs from patients with PH with a variable presentation among different subtypes of disease.In PH, the expansion of immature red blood cell precursors may constitute a response to the increasingly hypoxic conditions prevalent in this syndrome. A correlation of this erythrocyte signature with more severe hypertension cases may provide an important biomarker of disease progression

Effect of surgical experience and spine subspecialty on the reliability of the {AO} Spine Upper Cervical Injury Classification System

OBJECTIVE The objective of this paper was to determine the interobserver reliability and intraobserver reproducibility of the AO Spine Upper Cervical Injury Classification System based on surgeon experience (< 5 years, 5–10 years, 10–20 years, and > 20 years) and surgical subspecialty (orthopedic spine surgery, neurosurgery, and "other" surgery). METHODS A total of 11,601 assessments of upper cervical spine injuries were evaluated based on the AO Spine Upper Cervical Injury Classification System. Reliability and reproducibility scores were obtained twice, with a 3-week time interval. Descriptive statistics were utilized to examine the percentage of accurately classified injuries, and Pearson’s chi-square or Fisher’s exact test was used to screen for potentially relevant differences between study participants. Kappa coefficients (κ) determined the interobserver reliability and intraobserver reproducibility. RESULTS The intraobserver reproducibility was substantial for surgeon experience level (< 5 years: 0.74 vs 5–10 years: 0.69 vs 10–20 years: 0.69 vs > 20 years: 0.70) and surgical subspecialty (orthopedic spine: 0.71 vs neurosurgery: 0.69 vs other: 0.68). Furthermore, the interobserver reliability was substantial for all surgical experience groups on assessment 1 (< 5 years: 0.67 vs 5–10 years: 0.62 vs 10–20 years: 0.61 vs > 20 years: 0.62), and only surgeons with > 20 years of experience did not have substantial reliability on assessment 2 (< 5 years: 0.62 vs 5–10 years: 0.61 vs 10–20 years: 0.61 vs > 20 years: 0.59). Orthopedic spine surgeons and neurosurgeons had substantial intraobserver reproducibility on both assessment 1 (0.64 vs 0.63) and assessment 2 (0.62 vs 0.63), while other surgeons had moderate reliability on assessment 1 (0.43) and fair reliability on assessment 2 (0.36). CONCLUSIONS The international reliability and reproducibility scores for the AO Spine Upper Cervical Injury Classification System demonstrated substantial intraobserver reproducibility and interobserver reliability regardless of surgical experience and spine subspecialty. These results support the global application of this classification system

Optimal procurement of contingency and load following reserves by demand side resources under wind-power generation uncertainty

\u3cp\u3eSystem operators must consider events that cause disturbances in the balance between the output of the generators and the load demand in their short-term operations. Transmission line failures, generating unit outages, and intrahour load deviations are such events. The means of confronting them is the scheduling and the deployment of reserves on a market basis. On top of these factors, the increasing penetration of renewables and especially wind-power generation has increased the frequency of deployment and the magnitude of required reserves. Traditionally, reserves have been procured by appropriately adjusting the output of the generating units; however, a broad range of demand-side resources are also qualified to provide ancillary services. The subject of this chapter is the development of a two-stage stochastic joint energy and reserve market structure that incorporates demand-side resources in order to procure the required reserve services in a reliable and economically optimal manner.\u3c/p\u3

Reserve services provision by demand side resources in systems with high renewables penetration using stochastic optimization

It is widely recognized that renewable energy sources are likely to represent a significant portion of the production mix in many power systems around the world, a trend expected to be increasingly followed in the coming years due to environmental and economic reasons. Among the different endogenous renewable sources that may be used in order to achieve reductions in the carbon footprint related to the electricity sector and increase the economic efficiency of the generation mix, wind power generation has been one of the most popular options. However, despite the potential benefits that arise from the integration of these resources in the power system, their large-scale integration leads to additional problems due to the fact that their production is highly volatile. As a result, apart from the typical sources of uncertainty that the System Operators have to face, such as system contingencies and intra-hour load deviations, through the deployment of sufficient levels of reserve generation, additional reserves must be kept in order to maintain the balance between the generation and the consumption. Furthermore, a series of other problems arise, such as efficiency loss because of ramping of conventional units, environmental costs because of increased emissions due to suboptimal unit commitment and dispatch and more costly system operation and maintenance. Recently, it has been recognized that apart from the generation side, several types of loads may be deployed in order to provide system services and especially, different types of reserves, through demand response. The contribution of demand side reserves to accommodate higher levels of wind power generation penetration is likely to be of substantial importance in the future and therefore, the integration of these resources in the system operations needs to be thoroughly studied. This thesis deals with the aspects of demand response as regards the integration of wind power generation in the power system. First, a mapping of the current status of demand response internationally is attempted, followed also by a discussion concerning the opportunities, the benefits and the barriers to the widespread adoption of demand side resources. Then, several joint energy and reserve market structures are developed which explicitly incorporate demand side resources that may contribute to energy and reserve services. Two-stage stochastic programming is employed in order to capture the uncertainty of wind power generation. Moreover, several aspects of demand response are considered such as the capability of providing contingency and load following reserves, the appropriate modeling of industrial consumer processes load and the load recovery effect. Finally, this thesis investigates the effect of demand side resources on the risk that is associated with the decisions of the System Operator through appropriate risk management techniques, proposing also a novel methodology of handling risk as an alternative to the commonly used technique.It is widely recognized that renewable energy sources are likely to represent a significant portion of the production mix in many power systems around the world, a trend expected to be increasingly followed in the coming years due to environmental and economic reasons. Among the different endogenous renewable sources that may be used in order to achieve reductions in the carbon footprint related to the electricity sector and increase the economic efficiency of the generation mix, wind power generation has been one of the most popular options. However, despite the potential benefits that arise from the integration of these resources in the power system, their large-scale integration leads to additional problems due to the fact that their production is highly volatile. As a result, apart from the typical sources of uncertainty that the System Operators have to face, such as system contingencies and intra-hour load deviations, through the deployment of sufficient levels of reserve generation, additional reserves must be kept in order to maintain the balance between the generation and the consumption. Furthermore, a series of other problems arise, such as efficiency loss because of ramping of conventional units, environmental costs because of increased emissions due to suboptimal unit commitment and dispatch and more costly system operation and maintenance. Recently, it has been recognized that apart from the generation side, several types of loads may be deployed in order to provide system services and especially, different types of reserves, through demand response. The contribution of demand side reserves to accommodate higher levels of wind power generation penetration is likely to be of substantial importance in the future and therefore, the integration of these resources in the system operations needs to be thoroughly studied. This thesis deals with the aspects of demand response as regards the integration of wind power generation in the power system. First, a mapping of the current status of demand response internationally is attempted, followed also by a discussion concerning the opportunities, the benefits and the barriers to the widespread adoption of demand side resources. Then, several joint energy and reserve market structures are developed which explicitly incorporate demand side resources that may contribute to energy and reserve services. Two-stage stochastic programming is employed in order to capture the uncertainty of wind power generation. Moreover, several aspects of demand response are considered such as the capability of providing contingency and load following reserves, the appropriate modeling of industrial consumer processes load and the load recovery effect. Finally, this thesis investigates the effect of demand side resources on the risk that is associated with the decisions of the System Operator through appropriate risk management techniques, proposing also a novel methodology of handling risk as an alternative to the commonly used technique

Economic viability of smart charging EVs in the Dutch ancillary service markets

\u3cp\u3eSmart charging of electric vehicles (EVs) could potentially facilitate easing network imbalance and grid over-loading issues that are expected to emerge due to the increase in sustainable energy alternatives in the near future. It has been shown that smart charging is technically possible, however, if there are no positive business cases, it is unlikely to succeed. One of the possible business cases is supplying energy in ancillary services markets. This paper investigates this business case for the Dutch ancillary service markets by determining the investment and operational costs of smart charging a pool of EVs and creating a market participation model that combines EV charging data with market data to calculate the potential profit.\u3c/p\u3

A methodology to generate power profiles of electric vehicle parking lots under different operational strategies

\u3cp\u3eThe electrification of the transportation sector through the introduction of electric vehicles (EV) has recently emerged as a remedy to environmental and economic concerns. For this reason, governments around the world have been offering subsidies and other benefits to drivers that replace their conventional vehicle with an EV in order to facilitate the commercialization of the latter. However, when compared to conventional vehicles, EVs present a key disadvantage that could hinder their widespread uptake: the time that is needed to charge an EV is in the range of hours. For this purpose, EV parking lots have been proposed in order to recharge vehicles at a higher rate. Recent studies indicate that vehicles remain parked for most of the day, implying that different operational strategies may be used in order to achieve operational or economic benefits from the perspective of the EV parking lot owner. The aim of this study is to derive representative load profiles of parking lots under different operational strategies. To perform so, the parameters of the EV fleet are modeled by estimating kernel distributions from available traffic data, while a time series transformation in combination with a clustering approach is used in order to obtain representative price patterns. The examined case studies demonstrate that by performing a reduced number of simulations regarding expected charging profiles of EV fleets, generalized results may be obtained using the proposed methodology.\u3c/p\u3

Implementation of large-scale Li-ion battery energy storage systems within the EMEA region

\u3cp\u3eLarge-scale Lithium-ion Battery Energy Storage Systems (BESS) are gradually playing a very relevant role within electric networks in Europe, the Middle East and Africa (EMEA). The high energy density of Li-ion based batteries in combination with a remarkable round-trip efficiency and constant decrease in the levelized cost of storage have led to the recent boom of the technology. However, many of the potential applications of large-scale battery systems are not economically viable at this point in time. As a result, several BESS projects are being pushed by the industry towards specific niches which are based on revenue streams that can be rather complex than straightforward. The aim of this paper is to provide an overview of how large-scale Li-ion BESS are currently being implemented in the EMEA region, giving an answer to the following questions: what are the main use-cases of large-scale Li-ion batteries that are being implemented? What are the key factors that are enabling the deployment of BESS projects in the present markets? How can current tendencies be extrapolated to the future outlook of Li-ion BESS implementations? The large-scale energy storage market is evolving at a very fast pace, hence this review paper intends to contribute to a better understanding of the current status of Li-ion battery systems focusing on the economic feasibility that is driving the realization of Li-ion BESS projects in the EMEA region.\u3c/p\u3

Coordination for prosumers' electricity trading agents via distributed optimization

\u3cp\u3eIn this paper, the coordinated operation of agents representing residential household energy management systems in the electricity market is considered. Each agent has its local decision vector that may contain both continuous and discrete variables. The problem of minimizing the energy procurement cost of the community of agents is represented by a Mixed Integer Linear Program with local and global constraints. A dual decomposition method with a tightening of the global constraint is applied to solve the problem with guarantees for the feasibility of the obtained solutions. The problem is decomposed and solved in a distributed way with coordination by a community coordinator. The method is applied to a realistic case study of 15 households.\u3c/p\u3

Local energy exchange considering heterogeneous prosumer preferences

\u3cp\u3eTechnological developments in the electricity sector and the shift towards more prosumer-centric market structures enable the emergence of local electricity markets. In this study, the possibility of developing an energy exchange pertaining a network of prosumers belonging to a local community is investigated. In addition, the influence of heterogeneous prosumers' preferences on the feasibility and viability of local market structures is of interest. To this end, a dataset with highly granular measurements of electricity consumption and production of residential end-users is used. Moreover, survey data are used in order to identify behavioral characteristics and preferences regarding electricity and to perform prosumer segmentation. The results of the case study indicate that despite the heterogeneity of preferences, similar participant objectives might emerge, reinforcing the feasibility of local energy exchanges.\u3c/p\u3

Joint day-ahead clearing of energy, active and reactive power reserves for systems with significant RES-related uncertainty

\u3cp\u3eA two-stage stochastic optimization problem is proposed in order to model a day-ahead market in which energy, as well as active and reactive power reserves are jointly scheduled, in the presence of significant uncertain wind power production. In addition, a second order conic programming based AC power flow formulation is used, in order to take into account the active and reactive power losses while maintaining computational efficiency. The energy providers are compensated both in terms of availability payments for scheduling active power reserves and energy payments for actual reserve deployment. Simulations performed on the IEEE 24-bus system are presented and the impact of reactive power requirements on energy, active power reserves and wind integration are discussed.\u3c/p\u3