Optimal Distributed Power Generation Under Network-Load Constraints

In electrical power networks nowadays more and more customers are becoming power-producers, mainly because of the development of novel components for decentralized power generation (solar panels, small wind turbines and heat pumps). This gives rise to the question how many units of each type (solar panel, small wind turbine or central heating power units) can be inserted into any transmission line in the network, such that under given distributions on the typical production and consumption over time, the maximum loads on the lines and components will not be exceeded. In this paper, we present a linear programming model for maximizing the amount of decentralized power generation while respecting the load limitations of the network. We describe a prototype showing that for an example network the maximization problem can be solved efficiently. We also modeled the case were the power consumption and decentralized power generation are considered as stochastic variables, which is inherently more complex

A Methodology for Assessing Eco-efficiency in Logistics Networks

Recent literature on sustainable logistics networks points to two important questions: (i) How to spot the preferred solution(s) balancing environmental and business concerns? (ii) How to improve the understanding of the trade-offs between these two dimensions? We posit that a complete exploration of the efficient frontier and trade-offs between profitability and environmental impacts are particularly suitable to answer these two questions. In order to deal with the exponential number of basic efficient points in the frontier, we propose a formulation that performs in exponential time for the number of objective functions only. We illustrate our findings by designing a complex recycling logistics network in Germany.Eco-efficiency;Environmental impacts;Profitability;Recycling logistics network

From Closed-Loop to Sustainable Supply Chains: The WEEE case

The primary objective of closed-loop supply chains (CLSC) is to reap the maximum economic benefit from end-of-use products. Nevertheless, literature within this stream of research advocates that closing the loop helps to mitigate the undesirable footprint of supply chains. In this paper we assess the magnitude of such environmental gains for Electric and Electronic Equipments (EEE), based on a single environmental metric of Cumulative Energy Demand. We detail our analysis for the different phases of the CLSC, i.e. manufacturing, usage, transportation and end-of-life activities. According to our literature review, within the same group of EEE, results greatly vary. Furthermore, based on the environmental hot-spots, we propose extensions of the existing CLSC models to incorporate the CED.Closed-loop supply chains (CLSC);Cumulative energy demand;Electric and electronic equipments (EEE)

Probabilistic Power Flow Simulation allowing Temporary Current Overloading

This paper presents a probabilistic power flow model subject to connection temperature constraints. Renewable power generation is included and modelled stochastically in order to reflect its intermittent nature. In contrast to conventional models that enforce connection current constraints, short-term current overloading is allowed. Temperature constraints are weaker than current constraints, and hence the proposed model quantifies the overload risk more realistically. Using such a constraint is justified the more by the intermittent nature of the renewable power source. Allowing temporary current overloading necessitates the incorporation of a time domain in our model. This substantially influences the choice of model for the renewable power source, as we explain. Wind power is modelled by use of an ARMA model, and appropriate accelerations of the power flow solution technique are chosen. Several IEEE test case examples illustrate the more realistic risk analysis. An example shows that a current constraint model may overestimate these risks, which may lead to unnecessary over-investments by grid operators in grid connections

Companion detection limits with adaptive optics coronagraphy

We presented a detailed observational study of the capabilities of the Palomar Adaptive Optics System and the PHARO near infrared camera in coronagraphic mode. The camera provides two different focal plane occulting masks consisting of completely opaque circular disks of diameter 0.433 arcsec and 0.965 arcsec, both within the cryogenic dewar. In addition, three different pupil plane apodizing masks (a.k.a. Lyot masks) are provided which downsize the beam. The six different combinations of Lyot mask and focal plane mask provide for different levels of suppression of the point spread function of a bright star centered on the focal plane mask. We obtained images of the bright nearby star Gliese 614 with all six different configurations in the K-band filter. Herein, we provide an analysis of the dynamic range achievable with these configurations. The dynamic range (the ratio of the primary star intensity to the intensity of the faintest point source detectable in the images) is a complicated function of not only the angular separation of the primary star and companion, but also of the azimuthal angle because of the complex point spread function of the primary star, which is also wavelength dependent. However, beyond 2.5 arcseconds from the star, regardless of the wavelength of the observation, the detection limit of a companion is simply the limiting magnitude of the image, as determined by the sensitivity of the PHARO camera. Within that radius, the dynamic range is at least 8 magnitudes at the 5(sigma) level and as high as 12 in a one second exposure. This represents a substantial gain over similar techniques without adaptive optics, which are generally limited to radii beyond two arcsec. We provide a quantitative discussion and recommendation for the optimal configuration along with a detailed comparison with recent theoretical predictions of AO coronagraphic performance

Studies of Herbig-Haro objects with the Palomar adaptive optics system

Herbig-Haro objects are bright optical emission-line sources associated with tightly collimated jets ejected from pre-main- sequence stars. Only a few hundred are known. In optical images, they appear to be dense knots of material at the outer ends of the jets, and often exhibit streaming wake morphologies suggestive of bow shocks. Their optical spectra show characteristics of high-velocity shocks, with line-widths typically 100 km/s. HH objects often occur in pairs consistent with the bipolar morphology of outflows from YSOs; when radio maps of NH3 are made, high-density central regions consistent with collimating disks are seen. HH objects also often appear in a series along a jet, presumably where the jet undergoes a particularly energetic interaction with the ambient medium. Adaptively-corrected near-infrared studies of HH objects can reveal much about their workings at fine spatial scales. Narrow-band NIR filters sensitive to transitions of molecular hydrogen and other selected species are excellent tracers of shock excitation, and many HH objects have been observed to show complex structure in these lines down to the arc second level. By pushing to higher spatial resolution with adaptive optics, much more detailed information about the nature of the shock fronts may be obtained. In this paper we describe our first observations of HH objects with the AO system on the Palomar 200-inch telescope

From Closed-Loop to Sustainable Supply Chains: The WEEE case

The primary objective of closed-loop supply chains (CLSC) is to reap the maximum economic benefit from end-of-use products. Nevertheless, literature within this stream of research advocates that closing the loop helps to mitigate the undesirable footprint of supply chains. In this paper we assess the magnitude of such environmental gains for Electric and Electronic Equipments (EEE), based on a single environmental metric of Cumulative Energy Demand. We detail our analysis for the different phases of the CLSC, i.e. manufacturing, usage, transportation and end-of-life activities. According to our literature review, within the same group of EEE, results greatly vary. Furthermore, based on the environmental hot-spots, we propose extensions of the existing CLSC models to incorporate the CED

A Methodology for Assessing Eco-efficiency in Logistics Networks

Recent literature on sustainable logistics networks points to two important questions: (i) How to spot the preferred solution(s) balancing environmental and business concerns? (ii) How to improve the understanding of the trade-offs between these two dimensions? We posit that a complete exploration of the efficient frontier and trade-offs between profitability and environmental impacts are particularly suitable to answer these two questions. In order to deal with the exponential number of basic efficient points in the frontier, we propose a formulation that performs in exponential time for the number of objective functions only. We illustrate our findings by designing a complex recycling logistics network in Germany

Effect of COVID vaccination on monthly migraine days:a longitudinal cohort study

BACKGROUND: This longitudinal cohort study aimed to investigate changes in migraine-related outcomes following COVID-19 infection and vaccination. METHODS: We identified 547 clinically diagnosed migraine patients from the Leiden Headache Center who kept a headache E-diary during the COVID-19 pandemic (February 2020 to August 2022). We sent a questionnaire to register their COVID-19 infection and/or vaccination dates. After applying inclusion criteria, n = 59 participants could be included in the infection analysis and n = 147 could be included in the vaccination analysis. Primary outcome was the change in monthly migraine days (MMD) between 1 month prior and 1 month post COVID-19 infection or vaccination. Secondary outcome variables were change in monthly headache days (MHD) and monthly acute medication days (MAMD). RESULTS:Vaccination against COVID-19 was associated with an increase in MMD (1.06; 95% confidence interval [CI] = 0.57-1.55; p &lt; 0.001), MHD (1.52; 95% CI = 0.91-2.14; p &lt; 0.001) and MAMD (0.72; 95% CI = 0.33-1.12; p &lt; 0.001) in the first month post-vaccination. COVID-19 infection solely increased the number of MAMD (1.11; 95% CI = 0.10-1.62; p &lt; 0.027), but no statistically significant differences in MMD or MHD were observed. CONCLUSIONS: Our findings imply that vaccination against COVID-19 is associated with an increase in migraine, indicating a possible role of inflammatory mediators in migraine pathophysiology.</p