Search results

Series capacitive compensation in electrical power systems is generally recognized as a very economical and powerful means for increasing the transmission capability of long‐distance transmission lines, resulting in relevant technical advantages in power system behavior: increased steady‐state and transient stability margins, reduced voltage drop in receiving systems during occurrence of severe contingencies and reduction of transmission losses. In this paper, a general method for choosing the series compensation degree is proposed, focusing the attention on the transient stability aspect. The approach, based upon a probabilistic framework, allows to properly select – at the design stage – the optimal degree of series compensation in order to contain the instability risk at an acceptable value. The transient stability problem is formulated by using the transient energy function method. In order to show the feasibility of the proposed approach, a numerical application to the Cigre test network is performed in the final part of the paper.

The purpose of this paper is the investigation of the main aspects of optimal reliability allocation with respect to the design of hybrid electric vehicles. In particular, with reference to the hybrid electric vehicle propulsion system, the problem of data uncertainty, due to a scarce knowledge of the components' reliabilities, is taken into account. This problem is crucial for new technology systems and it is faced with a Bayesian approach: components' reliabilities are considered as random variables, characterised in the paper by negative log‐gamma distributions.

The main aspects of optimal reliability allocation with the design of hybrid electric vehicles are presented, pointing out the opportunity of a reliability evaluation in the planning stage.

The topic of a series hybrid vehicle reliability is addressed, nevertheless results can be easily extended to the parallel configuration. In particular, the opportunity of a reliability evaluation of the propulsion system in the design stage is highlighted, mainly when new technology components are involved.

The value of the paper consists in the methodology allowing to express the system reliability uncertainty as a function of component uncertain data. Then, as far as concern the practical implications, the optimal allocation of the components' reliabilities can be efficiently performed, in order to minimise the system total cost respecting a prefixed value of the system reliability. In the final part of the paper, a numerical application, related to a series hybrid electric vehicle propulsion system, is presented to show the feasibility of the approach.

The goal of this paper is to contribute to the development of both data localization and description techniques in P2P systems.

The approach consists of introducing a novel indexing technique that relies on linguistic data summarization into the context of P2P systems.

The cost model of the approach, as well as the simulation results have shown that the approach allows the efficient maintenance of data summaries, without incurring high traffic overhead. In addition, the cost of query routing is significantly reduced in the context of summaries.

The paper has considered a summary service defined on the APPA's architecture. Future works have to study the extension of this work in order to be generally applicable to any P2P data management system.

This paper has mainly studied the quantitative gain that could be obtained in query processing from exploiting data summaries. Future works aim to implement this technique on real data (not synthetic) in order to study the qualitative gain that can be obtained from approximately answering a query.

The novelty of the approach shown in the paper relies on the double exploitation of the summaries in P2P systems: data summaries allow for a semantic‐based query routing, and also for an approximate query answering, using their intentional descriptions.