Computational algorithms to predict Gene Ontology annotations

Background Gene function annotations, which are associations between a gene and a term of a controlled vocabulary describing gene functional features, are of paramount importance in modern biology. Datasets of these annotations, such as the ones provided by the Gene Ontology Consortium, are used to design novel biological experiments and interpret their results. Despite their importance, these sources of information have some known issues. They are incomplete, since biological knowledge is far from being definitive and it rapidly evolves, and some erroneous annotations may be present. Since the curation process of novel annotations is a costly procedure, both in economical and time terms, computational tools that can reliably predict likely annotations, and thus quicken the discovery of new gene annotations, are very useful. Methods We used a set of computational algorithms and weighting schemes to infer novel gene annotations from a set of known ones. We used the latent semantic analysis approach, implementing two popular algorithms (Latent Semantic Indexing and Probabilistic Latent Semantic Analysis) and propose a novel method, the Semantic IMproved Latent Semantic Analysis, which adds a clustering step on the set of considered genes. Furthermore, we propose the improvement of these algorithms by weighting the annotations in the input set. Results We tested our methods and their weighted variants on the Gene Ontology annotation sets of three model organism genes (Bos taurus, Danio rerio and Drosophila melanogaster ). The methods showed their ability in predicting novel gene annotations and the weighting procedures demonstrated to lead to a valuable improvement, although the obtained results vary according to the dimension of the input annotation set and the considered algorithm. Conclusions Out of the three considered methods, the Semantic IMproved Latent Semantic Analysis is the one that provides better results. In particular, when coupled with a proper weighting policy, it is able to predict a significant number of novel annotations, demonstrating to actually be a helpful tool in supporting scientists in the curation process of gene functional annotations

Flexibility From Distributed Multienergy Systems

Multienergy systems (MES), in which multiple energy vectors are integrated and optimally operated, are key assets in low-carbon energy systems. Multienergy interactions of distributed energy resources via different energy networks generate the so-called distributed MES (DMES). While it is now well recognized that DMES can provide power system flexibility by shifting across different energy vectors, it is essential to have a systematic discussion on the main features of such flexibility. This article presents a comprehensive overview of DMES modeling and characterization of flexibility applications. The concept of ``multienergy node'' is introduced to extend the power node model, used for electrical flexibility, in the multienergy case. A general definition of DMES flexibility is given, and a general mathematical and graphical modeling framework, based on multidimensional maps, is formulated to describe the operational characteristics of individual MES and aggregate DMES, including the role of multienergy networks in enabling or constraining flexibility. Several tutorial examples are finally presented with illustrative case studies on current and future DMES practical applications

Analysis of the Steinmetz compensation circuit with distorted waveforms through symmetrical component-based indicators

This paper deals with the use of a set of indicators defined within a symmetrical component-based framework to study the characteristics of the Steinmetz compensation circuit in the presence of waveform distortion. The Steinmetz circuit is applied to obtain balanced currents in a three-phase system supplying a single-phase load. The circuit is analyzed without and with harmonic distortion of the supply voltages. The compensation effect is represented by the classical unbalance factor and by the Total Phase Unbalance (TPU) indicator defined in the symmetrical component-based framework. Comparing the two indicators, it is shown that the classical unbalance factor is insufficient to represent the effect of voltage distortion and fails to detect the lack of total unbalance compensation occurring with distorted waveforms. Correct information is provided by calculating the TPU indicator. © 2009 IEEE

Tools for optimal operation and planning or urban distribution systems

This paper reports on the results of the implementation of a set of software tools for the comprehensive analysis and optimisation of distribution systems, developed jointly by Azienda Energetica Metropolitana (AEM) Torino S.p.A. and Dipartimento di Ingegneria Elettrica Industriale - Politecnico di Torino. The software tools cover several aspects of distribution system analysis, fault current calculation, reliability assessment, total operating cost evaluation, optimal reconfiguration, optimal planning and service restoration

Technical Solutions and Standards Upgrade for Photovoltaic Systems Operated over 1500 Vdc

This paper deals with photovoltaic (PV) systems with operating voltage increased over the value 1500 V in DC, which represents the limit of the current solutions and the actual standard for the PV plant at utility-scale level. The increase of the DC voltage is aimed at reducing the cable energy losses, the number of components and to optimise the layout of the plants, increasing the competitiveness of Medium Voltage PV (MVPV) solutions with rated powers of hundreds of megawatt. The analysis carried out has identified the possible solutions to adopt in order to reach this target and has remarked that today the International Standards are not covering all the aspects of the technical solutions to be introduced in a MVPV plant. This paper indicates the key issues to be addressed by new Standards on some components in order to enable the deployment of MVPV solutions. Finally, the characteristics of an installation at 1500 V DC and some results of tests carried out on the isolation system of a 1500 V PV plant are discussed

Modeling Local Energy Market for Energy Management of Multi-Microgrids

The diffusion of distributed energy resources (DERs) has changed the supply-demand balance of power systems. One option to modernize the management of the electricity distribution is to operate the distribution system with interconnected micro-grids (MGs). However, the MG participation in wholesale energy and ancillary service markets creates several challenges in the interactions among the energy market managing entities. To solve these problems, local energy markets (LEMs) have been proposed, where the MGs can trade energy with each other under the management of the LEM manager (LEMM) to minimize their operation cost. In this paper, a local energy market is modeled for multi-MGs (MMGs) to minimize the operation cost of MGs individually and their social welfare in cooperation with each other. In such model, the optimal scheduling of the DERs in each MG is done through the market clearing process. To investigate the effectiveness of the proposed approach, the local energy market is applied to a distribution network with three MGs

Creation of Representative Gas Distribution Networks for Multi-vector Energy System Studies

The recent evolution of the electrical systems has seen the introduction of large shares of renewable energy sources connected to the electrical distribution networks, and the coupling of the electricity and gas distribution systems. The exploitation of power-to-gas technologies enables stronger coupling between the electricity and gas networks. However, a limiting factor is that the gas quality should be maintained. This paper introduces a procedure to create a representative natural gas network based on a predefined electrical system topology. Furthermore, by using a detailed gas system model, the paper addresses the suitability of the coupling between gas and electrical systems through the power-to-gas technology, in terms of gas quality targets

A Risk-Based Decision Framework for the Distribution Company in Mutual Interaction with the Wholesale Day-ahead Market and Microgrids

One of the emergent prospects for active distribution networks ( DN ) is to establish new roles to the distribution company ( DISCO ). The DISCO can act as an aggregator of the resources existing in the DN , also when parts of the network are structured and managed as microgrids ( MG s). The new roles of the DISCO may open the participation of the DISCO as a player trading energy in the wholesale markets, as well as in local energy markets. In this paper, the decision making aspects involving the DISCO are addressed by proposing a bilevel optimization approach in which the DISCO problem is modeled as the upper-level problem and the MG s problems and day-ahead wholesale market clearing process are modeled as the lower-level problems. To include the uncertainty of renewable energy sources, a risk-based two-stage stochastic problem is formulated, in which the DISCO 's risk aversion is modeled by using the conditional value at risk. The resulting nonlinear bilevel model is transformed into a linear single-level one by applying the Karush–Kuhn–Tucker conditions and the duality theory. The effectiveness of the model is shown in the application to the IEEE 33-bus DN connected to the IEEE RTS 24-bus power system