Repairing an aggregation-based smart metering system

International Journal of Information Security - Smart meters inform the electricity suppliers about the consumption of their clients in short intervals. Fine-grained electricity consumption...     

Mode‐dependent seamless transfer control strategy of a microgrid via a small‐signal stability approach

A microgrid is an effective solution to enhance the integration of distributed renewable energy resources, which can operate both in grid connected mode and islanded mode. In order to reduce the jumps of the system variables within acceptable limits to ensure the system has good transient performance and power quality in multiple operating modes, seamless transfer is the key problem to be considered. In this paper, due to the different multiple equilibrium points for the two operating modes, the dynamics of every operating mode re modeled as a subsystem with all the variables that are needed to be synchronized. Linearization is carried out respectively for the two operation modes on the different equilibriums in a state‐space form based on the small‐signal stability method. To reduce the conservatism of the unified controller, the concept of the relative Lyapunov function is introduced to derive a multiple segmental Lyapunov method and a robust feedback mode‐dependent switching controller is designed to achieve smooth transfer by making the deviation energy of the two modes both converge to the zero point. To rapidly detect the switching signal, a sparse communication network is introduced by the use of low bandwidth communication links to broadcast the switching signal to each distributed controller. Finally, two microgrid test systems were built in SIMULINK to show the feasibility and effectiveness of the proposed seamless transfer control strategies.     

On the selection of variables for qualitative modelling of dynamical systems

Behavioural modelling of physical systems from observations of their input/output behaviour is an important task in engineering. Such models are needed for fault monitoring as well as intelligent control of these systems. The paper addresses one subtask of behavioural modelling, namely the selection of input variables to be used in predicting the behaviour of an output variable. A technique that is well suited for qualitative behavioural modelling and simulation of physical systems is Fuzzy Inductive Reasoning (FIR), a methodology based on General System Theory. Yet, the FIR modelling methodology is of exponential computational complexity, and therefore, it may be useful to consider other approaches as booster techniques for FIR. Different variable selection algorithms: the method of the unreconstructed variance for the best reconstruction, methods based on regression coefficients (OLS, PCR and PLS) and other methods as Multiple Correlation Coefficients (MCC), Principal Components Analysis (PCA) and Cluster analysis are discussed and compared to each other for use in predicting the behaviour of a steam generator. The different variable selection algorithms previously named are then used as booster techniques for FIR. Some of the used linear techniques have been found to be non-effective in the task of selecting variables in order to compute a posterior FIR model. Methods based on clustering seem particularly well suited for pre-selecting subsets of variables to be used in a FIR modelling and simulation effort.     

EOQ Model: The Case in Which the Placing of Orders Is Rewarded

The first models of optimization of inventory management costs have undergone few changes since they were developed at the beginning of the last century. It is only with the passage of time that new scenarios have appeared with the introduction of new systems of production, and consequently of new strategies in the logistics chain. In this article, we analyze and propose a revision of the basic inventory model of economic order quantity first defined by Harris in 1913 for a scenario in which the owner of the stock receives a bonus or reward each time he replenishes his stock. This situation arises when the supplier receives a benefit (which he then shares with the customer) when managing his stock replenishment. An array of nested models is shown to illustrate this scenario, from which the constraints of previous scenarios have been removed. The model provides insights into the negotiation of batch size between supplier and buyer in a win‐win environment in the specific situation in which the supplier gives a bonus to the buyer at each stock replenishment. © 2011 Wiley Periodicals, Inc.     

Analyzing locality over a P2P computing architecture

A characteristic of Peer-to-Peer (P2P) computing networks is their huge number of different computational resources scattered across the Internet. Gathering peers into markets according to their multi-attribute computational resources makes it easier to manage these environments. This solution is known as market overlay. In this context, the closeness of the markets with similar resources, known as locality, is a key feature for ensuring good P2P resource management. Thus, the locality feature over a market overlay allows a lack of resources in a given market to be compensated quickly by any other market with similar resources, whenever these are close to each other. Consequently, locality becomes an essential challenge.This paper addresses the analysis of the locality of P2P market over-lays. According to this, a new procedure for measuring locality is applied together with an extensive analysis of some well-known structured P2P overlays. Based on this analysis, a new P2P computing architecture, named DisCoP, oriented towards optimizing locality is proposed. Our proposal gathers the peers into markets according to their computational resources. A Hilbert function is used to arrange multi-attribute markets in an ordered and mono-dimensional space and the markets are linked by means of a Bruijn graph. In order to maintain the DisCoP locality whenever the overlay is not completed, a solution based on the virtualization of markets is also proposed. Finally, the DisCoP locality is tested together with the proposed virtualization method for approximate searches over uncompleted overlays. The simulation results show that approximate searches exploit the DisCoP locality efficiently.     

Relationships between memory models

There have been many proposals of shared memory systems, each one providing different types of memory coherence for interprocess communication. However, they have usually been defined using different formalisms. This makes it difficult to compare among them the different proposals put forward. In this paper we present a formal framework for specifying memory models with different coherency properties. We specify most of the known shared memory models using our framework, showing some of the relationships that hold among them.     

A Task Model to Reduce Control Delays

Industrial control applications are usually developed in two phases: control design and real-time system implementation. In the control design stage a regulator is obtained and later it is translated into an algorithm in the implementation phase. Traditionally, these two phases have been developed in separate ways. Recently, some works have pointed out the necessity of the integration of the control design and its implementation. One of these works reduce the delay variance of control tasks (defined as the control action interval (CAI) and data acquisition interval (DAI) parameters) splitting every task into three parts. The CAI reduction method highly reduces the delay variance and improves the control performance. This work shows how to evaluate these delays under static and dynamic scheduling policies. A new task model is proposed in order to reduce the CAI and DAI parameters, which implies an improvement in the control performance. The new task model will be implemented in a real process, and the experimental measurements will show how, effectively, the control performance is highly improved with the methods presented in this paper.     

Simulatable certificateless two-party authenticated key agreement protocol

Key agreement (KA) allows two or more users to negotiate a secret session key among them over an open network. Authenticated key agreement (AKA) is a KA protocol enhanced to prevent active attacks. AKA can be achieved using a public-key infrastructure (PKI) or identity-based cryptography. However, the former suffers from a heavy certificate management burden while the latter is subject to the so-called key escrow problem. Recently, certificateless cryptography was introduced to mitigate these limitations. In this paper, we first propose a security model for AKA protocols using certificateless cryptography. Following this model, we then propose a simulatable certificateless two-party AKA protocol. Security is proven under the standard computational Diffie-Hellman (CDH) and bilinear Diffie-Hellman (BDH) assumptions. Our protocol is efficient and practical, because it requires only one pairing operation and five multiplications by each party.     

The necessity of sample quality assessment in 14C AMS dating: The case of Cova des Pas (Menorca – Spain)

The Cova des Pas cave is a karstic cave in the cliffs of the Barranc (canyon) de Trebalúger. It is a small cave only 6.5 m deep, 4.5 m wide and 1.7 m high. Yet more than 70 burials, in foetal position, from the Early Iron Age were found in this small cave. The conservation of the archaeological remains was very unusual. Not only wood, ropes and other plant material was found, but also remains of body tissue, hair and leather. In spite of the remarkable preservation of the bodies and artefacts, the state of conservation of the bone material was very bad. The bones contained little and heavily deteriorated collagen and the organic plant material was very fragile. The special environmental conditions of the cave are the cause of these unusual preservation conditions. Although the cave is situated in a limestone cliff, the soil of the cave is very acid. Unexpectedly bad sample quality seemed to be the major drawback for AMS radiocarbon dating on hair, wood, ropes and bone collagen, as well as on bio-apatite.     

HS-SPME coupled to GC/MS for quality control of Juniperus communis L. berries used for gin aromatization

HS-SPME coupled to GC/MS was applied to the analysis of the volatile fraction of Juniperus communis L. berries, which are the principal ingredient used for gin aromatization. Seventy seven compounds were identified by comparison with reference compounds or tentatively identified by comparing their mass spectra and retention index with those reported in mass spectra libraries and literature, respectively. Seventy four were detected by SPME and sixty eight were detected by solvent distillation extraction (SDE). These were mainly mono- and sesquiterpenic compounds that represented more than the 80% of the gin’s volatile composition. A high percent content was due to monoterpenoids, whose analysis could be important for the assessment of sensory quality control of juniper due to their impact on gin aroma. The main monoterpenoids detected in the headspace of the juniper berries from two periods of collection were terpinen-4-ol, p-cymene, β-myrcene, γ-terpinene, α-pinene and limonene. These represented more than the 70% of the sample’s volatile fraction. The proposed SPME method required short times and the low cost of analysis and enabled to detect a number of compounds comparable with SDE or much higher than the number of compounds reported by other extraction techniques. The results suggested the suitability of this technique for the assessment of the volatile composition of juniper berries intended for gin flavouring.