The Linkage Between Income Distribution and Clean Energy Investments: Addressing Financing Cos

With a focus on alternative methods for accelerating clean energy policy adoption, this study introduces an innovative financing scheme for renewable and energy efficiency deployment. Financing barriers represent a notable obstacle for energy improvements and this is particularly the case for low-income households. Limited access to credit, due to socio-economic status and the lack of guarantees, are key issues related to financing barriers. Implementing a policy such as PACE – Property Assessed Clean Energy – allows for the provision of up-front funds for residential property owners to install electric and thermal solar systems and make energy-efficiency improvements to their buildings. This paper will inform the design of better policies tailored to the creation of the appropriate conditions for such investments to occur, especially when the lack of access to capital tends to stall them.Financing Barriers, Energy Efficiency, Solar PV, Energy Investments

NaNet: a Low-Latency, Real-Time, Multi-Standard Network Interface Card with GPUDirect Features

While the GPGPU paradigm is widely recognized as an effective approach to high performance computing, its adoption in low-latency, real-time systems is still in its early stages. Although GPUs typically show deterministic behaviour in terms of latency in executing computational kernels as soon as data is available in their internal memories, assessment of real-time features of a standard GPGPU system needs careful characterization of all subsystems along data stream path. The networking subsystem results in being the most critical one in terms of absolute value and fluctuations of its response latency. Our envisioned solution to this issue is NaNet, a FPGA-based PCIe Network Interface Card (NIC) design featuring a configurable and extensible set of network channels with direct access through GPUDirect to NVIDIA Fermi/Kepler GPU memories. NaNet design currently supports both standard - GbE (1000BASE-T) and 10GbE (10Base-R) - and custom - 34~Gbps APElink and 2.5~Gbps deterministic latency KM3link - channels, but its modularity allows for a straightforward inclusion of other link technologies. To avoid host OS intervention on data stream and remove a possible source of jitter, the design includes a network/transport layer offload module with cycle-accurate, upper-bound latency, supporting UDP, KM3link Time Division Multiplexing and APElink protocols. After NaNet architecture description and its latency/bandwidth characterization for all supported links, two real world use cases will be presented: the GPU-based low level trigger for the RICH detector in the NA62 experiment at CERN and the on-/off-shore data link for KM3 underwater neutrino telescope

Stochastic optimization model for coordinated operation of natural gas and electricity networks

Renewable energy sources will anticipate significantly in the future energy system paradigm due to their low cost of operation and low pollution. Considering the renewable generation (e.g., wind) intermittency, flexible gas-fired power plants will continue to play their essential role as the main linkage of natural gas and electricity networks, and hence coordinated operation of these networks is beneficial. Furthermore, uncertainty is always found in gas demand prediction, electricity demand prediction, and output power of wind generation. Therefore, in this paper, a two-stage stochastic model for operation of natural gas and electricity networks is implemented. In order to model uncertainty in these networks, Monte Carlo simulation is applied to generate scenarios representing the uncertain parameters. Afterwards, a scenario reduction algorithm based on distances between the scenarios is applied. Stochastic and deterministic models for natural gas and electricity networks are optimized and compared considering integrated and iterative operation strategies. Furthermore, the value of flexibility options (i.e., electricity storage systems) in dealing with uncertainty is quantified. A case study is presented based on a high pressure 15-node gas system and the IEEE 24-bus reliability test system to validate the applicability of the proposed approach. The results demonstrate that applying the stochastic model of gas and electricity networks as well as considering integrated operation strategy in the presence of flexibility provides different benefits (e.g., 14% cost savings) and enhances the system reliability in the case of contingency

Investing in flexibility in an integrated planning of natural gas and power systems

The growing interdependencies between natural gas and power systems, driven by gas-fired generators and gas compressors supplied by electricity, necessitates detailed investigation of the interactions between these vectors, particularly in the context of growing penetration of renewable energy sources. In this research, an expansion planning model for integrated natural gas and power systems is proposed. The model investigates optimal investment in flexibility options such as battery storage, demand side response, and gas-fired generators. The value of these flexibility options is quantified for gas and electricity systems in GB in 2030. The results indicate that the flexibility options could play an important role in meeting the emission targets in the future. However, the investment costs of these options highly impact the future generation mix as well as the type of reinforcements in the natural gas system infrastructure. Through deployment of the flexibility options up to £24.2b annual cost savings in planning and operation of natural gas and power systems could be achieved, compared to the case that no flexibility option is considered

NEMO: A Project for a km3^3 Underwater Detector for Astrophysical Neutrinos in the Mediterranean Sea

The status of the project is described: the activity on long term characterization of water optical and oceanographic parameters at the Capo Passero site candidate for the Mediterranean km$^3$ neutrino telescope; the feasibility study; the physics performances and underwater technology for the km$^3$; the activity on NEMO Phase 1, a technological demonstrator that has been deployed at 2000 m depth 25 km offshore Catania; the realization of an underwater infrastructure at 3500 m depth at the candidate site (NEMO Phase 2).Comment: Proceeding of ISCRA 2006, Erice 20-27 June 200

Measurement of the atmospheric muon flux with the NEMO Phase-1 detector

The NEMO Collaboration installed and operated an underwater detector including prototypes of the critical elements of a possible underwater km3 neutrino telescope: a four-floor tower (called Mini-Tower) and a Junction Box. The detector was developed to test some of the main systems of the km3 detector, including the data transmission, the power distribution, the timing calibration and the acoustic positioning systems as well as to verify the capabilities of a single tridimensional detection structure to reconstruct muon tracks. We present results of the analysis of the data collected with the NEMO Mini-Tower. The position of photomultiplier tubes (PMTs) is determined through the acoustic position system. Signals detected with PMTs are used to reconstruct the tracks of atmospheric muons. The angular distribution of atmospheric muons was measured and results compared with Monte Carlo simulations.Comment: Astrop. Phys., accepte

SHAPS-C: the Snaith-Hamilton pleasure scale modified for clinician administration

Anhedonia, a diminished or lack of ability to experience and anticipate pleasure represents a core psychiatric symptom in depression. Current clinician assessment of anhedonia is generally limited to one or two all-purpose questions and most well-known psychometric scales of anhedonia are relatively long, self-administered, typically not state sensitive, and are unsuitable for use in clinical settings. A user-friendly tool for a more in-depth clinician assessment of hedonic capacity is needed. The present study assessed the validity and reliability of a clinician administered version of the Snaith-Hamilton Pleasure Scale, the SHAPS-C, in 34 depressed subjects. We compared total and specific item scores on the SHAPS-C, SHAPS (self-report version), Montgomery-Åsberg Depression Rating Scale (MADRS), and the Inventory of Depressive Symptomatology-Self Rating version (IDS-SR). We also examined construct, content, concurrent, convergent, and discriminant validity, internal consistency, and split-half reliability of the SHAPS-C. The SHAPS-C was found to be valid and reliable. The SHAPS and the SHAPS-C were positively correlated with one another, with levels of depression severity, as measured by the MADRS, and the IDS-SR total scores, and with specific items of the MADRS and IDS-SR sensitive to measuring hedonic capacity. Our investigation indicates that the SHAPS-C is a user friendly, reliable, and valid tool for clinician assessment of hedonic capacity in depressed bipolar and unipolar patients

Climate Vulnerability and the Cost of Debt

We use indices from the Notre Dame Global Adaptation Initiative to investigate the impact of climate vulnerability on bond yields. Our methodology invokes panel ordinary least squares with robust standard errors and principal component analysis. The latter serves to address the multicollinearity between a set of vulnerability measures. We find that countries with higher exposure to climate vulnerability, such as the member countries of the V20 climate vulnerable forum, exhibit 1.174 percent higher cost of debt on average. This effect is significant after accounting for a set of macroeconomic controls. Specifically, we estimate the incremental debt cost due to higher climate vulnerability, for the V20 countries, to have exceeded USD 62 billion over the last ten years. In other words, for every ten dollars they pay in interest cost, they pay another dollar for being climate vulnerable. We also find that a measure of social readiness, which includes education and infrastructure, has a negative and significant effect on bond yields, implying that social and physical investments can mitigate climate risk related debt costs and help to stabilize the cost of debt for vulnerable countries