A New Approach to Electricity Market Clearing With Uniform Purchase Price and Curtailable Block Orders

The European market clearing problem is characterized by a set of heterogeneous orders and rules that force the implementation of heuristic and iterative solving methods. In particular, curtailable block orders and the uniform purchase price (UPP) pose serious difficulties. A block is an order that spans over multiple hours, and can be either fully accepted or fully rejected. The UPP prescribes that all consumers pay a common price, i.e., the UPP, in all the zones, while producers receive zonal prices, which can differ from one zone to another. The market clearing problem in the presence of both the UPP and block orders is a major open issue in the European context. The UPP scheme leads to a non-linear optimization problem involving both primal and dual variables, whereas block orders introduce multi-temporal constraints and binary variables into the problem. As a consequence, the market clearing problem in the presence of both blocks and the UPP can be regarded as a non-linear integer programming problem involving both primal and dual variables with complementary and multi-temporal constraints. The aim of this paper is to present a non-iterative and heuristic-free approach for solving the market clearing problem in the presence of both curtailable block orders and the UPP. The solution is exact, with no approximation up to the level of resolution of current market data. By resorting to an equivalent UPP formulation, the proposed approach results in a mixed-integer linear program, which is built starting from a non-linear integer bilevel programming problem. Numerical results using real market data are reported to show the effectiveness of the proposed approach. The model has been implemented in Python, and the code is freely available on a public repository.Comment: 15 pages, 7 figure

A Community Microgrid Architecture with an Internal Local Market

This work fits in the context of community microgrids, where members of a community can exchange energy and services among themselves, without going through the usual channels of the public electricity grid. We introduce and analyze a framework to operate a community microgrid, and to share the resulting revenues and costs among its members. A market-oriented pricing of energy exchanges within the community is obtained by implementing an internal local market based on the marginal pricing scheme. The market aims at maximizing the social welfare of the community, thanks to the more efficient allocation of resources, the reduction of the peak power to be paid, and the increased amount of reserve, achieved at an aggregate level. A community microgrid operator, acting as a benevolent planner, redistributes revenues and costs among the members, in such a way that the solution achieved by each member within the community is not worse than the solution it would achieve by acting individually. In this way, each member is incentivized to participate in the community on a voluntary basis. The overall framework is formulated in the form of a bilevel model, where the lower level problem clears the market, while the upper level problem plays the role of the community microgrid operator. Numerical results obtained on a real test case implemented in Belgium show around 54% cost savings on a yearly scale for the community, as compared to the case when its members act individually.Comment: 16 pages, 15 figure

The discovery of the Higgs boson

The Higgs boson identified at the CERN laboratories.Individuato presso i laboratori del CERN il bosone di Higgs

Sizing distributed energy resources in a renewable energy community with a grid-aware internal market structure

This paper proposes a cooperative approach aimed at distributed energy resources sizing in a renewable energy community, with considerations of the community's optimal operation, impact on the electrical grid and an allocation of the benefits to its members. To this purpose, multiple investment modes are evaluated via a two-step procedure. In the first step, the size of renewable energy sources is determined by solving an optimization problem that maximizes community welfare, considering network and investments. In the second step, an optimization problem maximizing additional community member profit with price regularization is solved. This step shares benefits among community members. The potential of the proposed procedure is illustrated using a benchmark Dickert-LV network. This is a fully cooperative framework where the community operator is ensuring adequate grid operation, operational planning and sizing of new investments

Anaesthetics modulate tumour necrosis factor α: effects of L-carnitine supplementation in surgical patients. Preliminary results.

Both anaesthetics and surgical trauma could strongly affect the production of tumour necrosis factor α (TNFα). During in vitro experiments the authors found that anaesthetics modulate the production of TNFα by peripheral blood mononuclear cells. Notably, Pentothal strongly increased the production of the cytokine as compared to both lipopolysacchride treated and control mononuclear cells, whereas in supernatants from Leptofen driven mononuclear cells TNFα was strongly reduced. On the other hand, Pavulon did not significantly affect the cytokine production. In the in vivo study, in an attempt to ameliorate the metabolic response to surgical trauma, L-carnitine was administered to 20 surgical patients, then the circulating TNFα was measured. The results indicate that the levels of circulating TNFα were strongly increased following surgery and that L-carnitine administration resulted in a strong reduction of TNFα. Thus, the data suggest that L-carnitine could be helpful in protecting surgical patients against dysmetabolism dependent on dysregulated production of TNFα

SiPM and front-end electronics development for Cherenkov light detection

The Italian Institute of Nuclear Physics (INFN) is involved in the development of a demonstrator for a SiPM-based camera for the Cherenkov Telescope Array (CTA) experiment, with a pixel size of 6$\times$6 mm$^2$. The camera houses about two thousands electronics channels and is both light and compact. In this framework, a R&D program for the development of SiPMs suitable for Cherenkov light detection (so called NUV SiPMs) is ongoing. Different photosensors have been produced at Fondazione Bruno Kessler (FBK), with different micro-cell dimensions and fill factors, in different geometrical arrangements. At the same time, INFN is developing front-end electronics based on the waveform sampling technique optimized for the new NUV SiPM. Measurements on 1$\times$1 mm$^2$, 3$\times$3 mm$^2$, and 6$\times$6 mm$^2$ NUV SiPMs coupled to the front-end electronics are presentedComment: In Proceedings of the 34th International Cosmic Ray Conference (ICRC2015), The Hague, The Netherlands. All CTA contributions at arXiv:1508.0589

Enhanced neural network-based polytopic model for large-signal black-box modeling of power electronic converters

We propose a large-signal black-box model of power electronic converters inspired by polytopic models. Small-signal models are identified around different operating points to mimic the converter's local dynamics. The linear models' responses are then weighted using a trained neural network to create a large-signal model. The traditional trial and error weighting function tuning of polytopic models can result in a suboptimal combination of linear models. In this work, we use neural networks to approach an optimal combination. The analysis of the trained neural network can enhance the model's accuracy by suggesting new small-signal models. It also permits removing linear models that do not significantly improve the global model's accuracy while reducing complexity. The methodology is applied to a voltage-regulated DC-DC boost converter and provides accurate models of converter dynamics

Compact high-brightness and highly manufacturable blue laser modules

Blue laser diode sources have already proved to be an effective alternative for material processing, especially of high reflective materials, such as copper; now the challenge is to increase their power while improving brightness and reducing the cost-per-watt. The paper presents the development of a family of blue laser modules that, making use of the same platform and assembly lines of similar 9xx nm modules, can achieve an unprecedented combination of power, brightness, compactness and cost reduction. These modules rely on a proprietary architecture to combine a plurality of chips through spatial and polarization multiplexing, obtaining up to 100W of output power in a 100 μm fiber. Preliminary experimental results for module making use of spatial multiplexing report 35W output power in a 50 μm fiber

The colours of the Higgs boson: a study in creativity and science motivation among high-school students in Italy

AbstractWith the increasing shift from STEM to STEAM education, arts-based approaches to science teaching and learning are considered promising for aligning school science curricula with the development of twenty-first century skills, including creativity. Yet the impact of STEAM practices on student creativity and specifically on how the latter is associated with science learning outcomes have thus far received scarce empirical support. This paper contributes to this line of research by reporting on a two-wave quantitative study that examines the effect of a long-term STEAM intervention on two cognitive processes associated with creativity (act, flow) and their interrelationships with intrinsic and extrinsic components of science motivation. Using pre- and post-survey data from 175 high-school students in Italy, results show an overall positive effect of the intervention both on the act subscale of creativity and science career motivation, whereas a negative effect is found on self-efficacy. Gender differences in the above effects are also observed. Further, results provide support for the mediating role of self-efficacy in the relationship between creativity and science career motivation. Implications for the design of STEAM learning environments are discussed