Optimal Location of Energy Storage Systems with Robust Optimization

The integration of intermittent sources of energy and responsive loads in distribution system make the traditional deterministic optimization-based optimal power flow no longer suitable for finding the optimal control strategy for the power system operation. This paper presents a tool for energy storage planning in the distribution network based on AC OPF algorithm that uses a convex relaxation for the power flow equations to guarantee exact and optimal solutions with high algorithmic performances and exploits robust optimization approach to deal with the uncertainties related to renewables and demand. The proposed methodology is applied for storage planning on a distribution network that is representative of a class of networks

Data analytics for profiling low‐voltage customers with smart meter readings

The energy transition for decarbonization requires consumers’ and producers’ active par-ticipation to give the power system the necessary flexibility to manage intermittency and non‐pro-grammability of renewable energy sources. The accurate knowledge of the energy demand of every single customer is crucial for accurately assessing their potential as flexibility providers. This topic gained terrific input from the widespread deployment of smart meters and the continuous development of data analytics and artificial intelligence. The paper proposes a new technique based on advanced data analytics to analyze the data registered by smart meters to associate to each customer a typical load profile (LP). Different LPs are assigned to low voltage (LV) customers belonging to nominal homogeneous category for overcoming the inaccuracy due to non‐existent coincident peaks, arising by the common use of a unique LP per category. The proposed methodology, starting from two large databases, constituted by tens of thousands of customers of different categories, clusters their consumption profiles to define new representative LPs, without a priori preferring a specific clustering technique but using that one that provides better results. The paper also proposes a method for associating the proper LP to new or not monitored customers, considering only few features easily available for the distribution systems operator (DSO)

Synthetic models of distribution networks based on open data and georeferenced information

Many planning and operation studies that aim at fully assessing and optimizing the performance of the distribution grids, in response to the current trends, cannot ignore grid limitations. Modelling the distribution system, by including the electrical characteristics of the network (e.g., topology) and end user behaviors, has become complex, but essential, for all conventional and emerging actors/players of power systems (i.e., system and market operators, regulators, new market parties as service providers, aggregators, researchers, etc.). This paper deals with a methodology that, starting from publicly available open data on the energy consumption of a region or wider area, is capable to obtain reasonable load and generation profiles for the network supplied by each primary substation in the region/area. Furthermore, by combining these profiles with territorial and socio-economic information, the proposed methodology is able to model the network in terms of lines, conductors, loads and generators. The results of this procedure are the synthetic networks of the real distribution networks, that do not correspond exactly to the actual networks, but can characterize them in a realistic way. Such models can be used for all the kind of optimization studies that need to check the grid limitations. Results derived from Italian test cases are presented and discussed

Inhibition of MELK Protooncogene as an Innovative Treatment for Intrahepatic Cholangiocarcinoma

Background and Objectives: Intrahepatic cholangiocarcinoma (iCCA) is a pernicious tumor characterized by a dismal outcome and scarce therapeutic options. To substantially improve the prognosis of iCCA patients, a better understanding of the molecular mechanisms responsible for development and progression of this disease is imperative. In the present study, we aimed at elucidating the role of the maternal embryonic leucine zipper kinase (MELK) protooncogene in iCCA. Materials and Methods: We analyzed the expression of MELK and two putative targets, Forkhead Box M1 (FOXM1) and Enhancer of Zeste Homolog 2 (EZH2), in a collection of human iCCA by real-time RT-PCR and immunohistochemistry (IHC). The effects on iCCA growth of both the multi-kinase inhibitor OTSSP167 and specific small-interfering RNA (siRNA) against MELK were investigated in iCCA cell lines. Results: Expression of MELK was significantly higher in tumors than in corresponding non-neoplastic liver counterparts, with highest levels of MELK being associated with patients' shorter survival length. In vitro, OTSSP167 suppressed the growth of iCCA cell lines in a dose-dependent manner by reducing proliferation and inducing apoptosis. These effects were amplified when OTSSP167 administration was coupled to the DNA-damaging agent doxorubicin. Similar results, but less remarkable, were obtained when MELK was silenced by specific siRNA in the same cells. At the molecular level, siRNA against MELK triggered downregulation of MELK and its targets. Finally, we found that MELK is a downstream target of the E2F1 transcription factor. Conclusion: Our results indicate that MELK is ubiquitously overexpressed in iCCA, where it may represent a prognostic indicator and a therapeutic target. In particular, the combination of OTSSP167 (or other, more specific MELK inhibitors) with DNA-damaging agents might be a potentially effective therapy for human iCCA

Strategic decision-making support for distribution system planning with flexibility alternatives

The ongoing power system transformation requires rethinking the planning and operation practices of the different segments to accommodate the necessary changes and take advantage of the forthcoming opportunities. This paper concerns novel approaches for appraising initiatives involving the use of flexibility from grid-connected users. This paper proposes a Decision Theory based Multi-Criteria Cost-Benefit Analysis (DT-MCA-CBA) methodology for smart grid initiatives that capture the complexity of the distribution system planning activities in which flexibility competes with grid expansion. Based on international guidelines, the proposed DT-MCA-CBA methodology systematically assesses tangible and intangible impacts, considering multiple conflicting criteria. The DT-MCA-CBA methodology relies on a novel approach that combines MCA and Decision Theory to identify the most valuable option in a complex decision-making problem by modelling the stakeholder perspective with the MiniMax regret decision rule. The proposed DT-MCA-CBA methodology is applied to a comparative case study concerning four different approaches for distribution system planning. A web-based software which implements the proposed decision-making framework and the DT-MCA-CBA methodology is developed to provide a novel decision-making support tool for strategical smart distribution system planning

Characterization of milk composition, coagulation properties, and cheese-making ability of goats reared in extensive farms

The aims of this study were to explore the variability of milk composition, coagulation properties, and cheese-making traits of the Sarda goat breed, and to investigate the effects of animal and farm factors, and the geographic area (Central-East vs. South-West) of an insular region of Italy, Sardinia. A total of 570 Sarda goats reared in 21 farms were milk-sampled during morning milking. Individual milk samples were analyzed for composition, traditional milk coagulation properties (MCP), modeled curd-firming over time parameters (CFt), and cheese-making traits (cheese yield, %CY; recovery of nutrients, %REC; daily cheese yield, dCY). Farms were classified into 2 categories based on milk energy level (MEL; high or low), defined according to the average net energy of milk daily produced by the lactating goats. Milk yield and composition were analyzed using a mixed model including the fixed effects of MEL, geographic area, days in milk, and parity, and the random effect of farm within MEL and geographic area. Data about MCP, CFt, and the cheese-making process were analyzed using the same model, with the inclusion of the effects of animal and pendulum of the lactodynamograph instrument, allowing the measure of repeatability of these traits. Results showed that animal had greater influence on coagulation and cheese-making traits compared with farm effect. Days in milk influenced milk composition, whose changes partly reflected the modifications of %CY traits. Moreover, large differences were observed between primiparous and multiparous goats: primiparous goats produced less milk of better quality (higher fat, lower somatic cell and bacterial counts) and less cheese, but with higher recovery of fat and protein in the curd, compared with multiparous goats. The repeatability was very high, for both coagulation (84.0 to 98.8%) and cheese-making traits (89.7 to 99.9%). The effect of MEL was significant for daily productions of milk and cheese, coagulation time, and recovery of protein in the curd, which were better in high-MEL farms. As regards geographic area, milk composition and percentage cheese yield were superior in the Central-East area, whereas daily milk and cheese production and MCP were better in the South-West. This result was explainable by the phenomenon of crossbreeding Sarda goats with Maltese bucks, which occurred with greater intensity in the South-West than in the Central-East area of the island. The results provided by this study could be of great interest for the goat dairy sector. Indeed, the methods described in the present study could be applicable for other farming methods, goat breeds, and geographic areas. The collection of a wide range of phenotypes at individual animal level is fundamental for the characterization of local populations and can be used to guarantee breed conservation and the persistence of traditional farming systems, and to increase farmers' profit

Anti-de-Sitter Island-Universes from 5D Standing Waves

We construct simple standing wave solutions in a 5D space-time with a ghost scalar field. The nodes of these standing waves are 'islands' of 4D Minkowski space-time. For the 5D model with increasing (decreasing) warp factor there are a finite (infinite) number of nodes and thus Minkowski island-universes having different parameters, such as gravitational and cosmological constants. This feature is similar to the assumptions of the landscape models, which postulate a large number of universes with different parameters. This standing wave solution also provides a new localization mechanism - matter fields can reside only on Minkowski 'islands', where the background space-time does not oscillate.Comment: 14 page pre-print format. Discussion about connection to Weyl gravity added and "E&M" localization method added. To be published MPL