The key role of nitric oxide in hypoxia: hypoxic vasodilation and energy supply-demand matching

Significance: a mismatch between energy supply and demand induces tissue hypoxia with the potential to cause cell death and organ failure. Whenever arterial oxygen concentration is reduced, increases in blood flow - 'hypoxic vasodilation' - occur in an attempt to restore oxygen supply. Nitric oxide is a major signalling and effector molecule mediating the body's response to hypoxia, given its unique characteristics of vasodilation (improving blood flow and oxygen supply) and modulation of energetic metabolism (reducing oxygen consumption and promoting utilization of alternative pathways). Recent advances: this review covers the role of oxygen in metabolism and responses to hypoxia, the hemodynamic and metabolic effects of nitric oxide, and mechanisms underlying the involvement of nitric oxide in hypoxic vasodilation. Recent insights into nitric oxide metabolism will be discussed, including the role for dietary intake of nitrate, endogenous nitrite reductases, and release of nitric oxide from storage pools. The processes through which nitric oxide levels are elevated during hypoxia are presented, namely (i) increased synthesis from nitric oxide synthases, increased reduction of nitrite to nitric oxide by heme- or pterin-based enzymes and increased release from nitric oxide stores, and (ii) reduced deactivation by mitochondrial cytochrome c oxidase. Critical issues: several reviews covered modulation of energetic metabolism by nitric oxide, while here we highlight the crucial role NO plays in achieving cardiocirculatory homeostasis during acute hypoxia through both vasodilation and metabolic suppression Future directions: we identify a key position for nitric oxide in the body's adaptation to an acute energy supply-demand mismatc

Wide area cyclic blackout mitigation by supply-demand matching of HVAC counterpart loads

Many countries around the world are challenged to meet the escalating demand for power often resulting in frequent blackouts. Domestic standby generation and associated running costs are prohibitive and novel strategies to provision measures that manage blackouts are becoming much sought after. Almost all installed standby generation is not fully utilized and certain amounts of surplus power can be identified. The paper presents a strategy that harnesses the aggregated standby superfluous power to fulfil essential demand in residential areas during cyclic blackouts covering wide areas. The solution has at its foundation, a multiagent distributed demand management system with a supply-demand matching capability. Environmental conditions are monitored periodically and power is distributed accordingly to each sub-district. Customers at sub-districts receive a share of power according to two different distribution criteria and although their immediate allocated power is not the same, their overall daily power ration is equal. Air conditioners are backed up with less power demanding counterparts and a group of options is adaptively clustered. Their usage rights are distributed among customers according to available superfluous power. The approach is evaluated through an extensive emulation framework and results show that the proposed system is capable of providing an acceptable Quality-of-Service (QoS) level during cyclic blackout periods

A holistic approach to forecasting wholesale energy market prices

Electricity market price predictions enable energy market participants to shape their consumption or supply while meeting their economic and environmental objectives. By utilizing the basic properties of the supply-demand matching process performed by grid operators, known as Optimal Power Flow (OPF), we develop a methodology to recover energy market's structure and predict th

Design and Realization of a Bidirectional EV Battery Charger for V2G and G2V purposes

The continuous development of electric drive systems and battery technology has made the Electric Vehicle technology (EV) a more competitive option in the market with conventional vehicles. Among other merits, EVs can also provide ancillary services to support the grid (acting as controlled loads or energy storage units) in order to provide supply/demand matching to level the daily load profile and contribute to voltage and frequency controlopenEmbargo per motivi di segretezza e/o di proprietà dei risultati e/o informazioni sensibil

Energy Disaggregation for Real-Time Building Flexibility Detection

Energy is a limited resource which has to be managed wisely, taking into account both supply-demand matching and capacity constraints in the distribution grid. One aspect of the smart energy management at the building level is given by the problem of real-time detection of flexible demand available. In this paper we propose the use of energy disaggregation techniques to perform this task. Firstly, we investigate the use of existing classification methods to perform energy disaggregation. A comparison is performed between four classifiers, namely Naive Bayes, k-Nearest Neighbors, Support Vector Machine and AdaBoost. Secondly, we propose the use of Restricted Boltzmann Machine to automatically perform feature extraction. The extracted features are then used as inputs to the four classifiers and consequently shown to improve their accuracy. The efficiency of our approach is demonstrated on a real database consisting of detailed appliance-level measurements with high temporal resolution, which has been used for energy disaggregation in previous studies, namely the REDD. The results show robustness and good generalization capabilities to newly presented buildings with at least 96% accuracy.Comment: To appear in IEEE PES General Meeting, 2016, Boston, US

A Holistic Approach to Forecasting Wholesale Energy Market Prices

Electricity market price predictions enable energy market participants to shape their consumption or supply while meeting their economic and environmental objectives. By utilizing the basic properties of the supply-demand matching process performed by grid operators, known as Optimal Power Flow (OPF), we develop a methodology to recover energy market's structure and predict the resulting nodal prices by using only publicly available data, specifically grid-wide generation type mix, system load, and historical prices. Our methodology uses the latest advancements in statistical learning to cope with high dimensional and sparse real power grid topologies, as well as scarce, public market data, while exploiting structural characteristics of the underlying OPF mechanism. Rigorous validations using the Southwest Power Pool (SPP) market data reveal a strong correlation between the grid level mix and corresponding market prices, resulting in accurate day-ahead predictions of real time prices. The proposed approach demonstrates remarkable proximity to the state-of-the-art industry benchmark while assuming a fully decentralized, market-participant perspective. Finally, we recognize the limitations of the proposed and other evaluated methodologies in predicting large price spike values.Comment: 14 pages, 14 figures. Accepted for publication in IEEE Transactions on Power System

Adjustment of wind farm power output through flexible turbine operation using wind farm control

When the installed capacity of wind power becomes high, the power generated by wind farms can no longer simply be that dictated by the wind speed.With sufficiently high penetration, it will be necessary for wind farms to provide assistance with supply-demand matching. The work presented here introduces a wind farm controller that regulates the power generated by the wind farm to match the grid requirements by causing the power generated by each turbine to be adjusted. Further benefits include fast response to reach the wind farm power demanded, flexibility, little fluctuation in the wind farm power output and provision of synthetic inertia

Modelling and simulation of small-scale embedded generation systems

Advances in heat and power production are leading to a revolution in how buildings are perceived as an energy system. The rapid development of fuel cells, photovoltaic facades, cogeneration and the evolution of ducted windturbines allows the designer to envisage a building providing much of its own heat and power through local embedded generation (EG). However, the addition of heat and power production to the building increases it complexityas an energy system. New design issues must be addressed such as the integration of EG with traditional HVAC and power systems; optimal demand and supply matching; demand side management and its impact on environmentalperformance; interaction of the EG system with the local electricity network, etc

Austrian higher education institutions' idiosyncrasies and technology transfer system

The aim of this paper is to present the findings of a PhD research (Heinzl, 2007) conducted on the Universities of Applied Sciences in Austria. The research is to establish an idiosyncrasy model for Universities of Applied Sciences in Austria showing the effects of their idiosyncrasies on the ability to successfully conduct technology transfer. Research applied in the study is centred on qualitative methods as major emphasis is placed on theory building. The study pursues a stepwise approach for the establishment of the idiosyncrasy model. In the first step, an initial technology transfer model and list of idiosyncrasies are established based on a synthesis of findings from secondary research. In the second step, these findings are enhanced by the means of empirical research including problem-centred expert interviews, a focus group and participant observation. In the third step, the idiosyncrasies are matched with the factors conducive for technology transfer and focused interviews have been conducted for this purpose. The findings show that idiosyncrasies of Universities of Applied Sciences have remarkable effects on their technology transfer abilities. This paper presents four of the models that emerge from the PhD research: Generic Technology Transfer Model (Section 5.1); Idiosyncrasies Model for the Austrian Universities of Applied Sciences (Section 5.2); Idiosyncrasies-Technology Transfer Effects Model (Section 5.3); Idiosyncrasies-Technology Transfer Cumulated Effects Model (Section 5.3). The primary and secondary research methods employed for this study are: literature survey, focus groups, participant observation, and interviews. The findings of the research contribute to a conceptual design of a technology transfer system which aims to enhance the higher education institutions' technology transfer performance