Stochastic sensing of organic analytes by a pore-forming protein containing a molecular adapter

The rollout of smart grid solutions has already started and new methods are deployed to the power systems of today. However, complexity is still increasing as focus is moving from a single system, to a system of systems perspective. The results are increasing engineering efforts and escalating costs. For this reason, new and automated engineering methods are necessary. This paper addresses these needs with a rapid engineering methodology that covers the overall engineering process for smart grid applications—from use case design to deployment. Based on a model-driven development approach, the methodology consists of three main parts: use case modeling, code generation, and deployment. A domain-specific language is introduced supporting the use case design according to the Smart Grid Architecture Model. It is combined with the IEC 61499 distributed control model to improve the function layer design. After a completed use case design, executable code and communication configurations (e.g., IEC 61850) are generated and deployed onto compatible field devices. This paper covers the proposed rapid engineering methodology and a corresponding prototypical implementation which is validated in a laboratory experiment. Compared to other methods the proposed methodology decreases the number of engineering steps and reduces the use case design and implementation complexity.

Engineering Smart Grids: Applying Model-Driven Development from Use Case Design to Deployment

Optimization in waste landfilling partitioning in Paraná State, Brazil

In order to handle the increasing complexity of smart grid systems, detailed use case and requirements engineering has become indispensable. For this purpose the Smart Grid Reference Architecture Model (SGAM) has emerged as the major methodology. This paper presents a textual Domain Specific Language (DSL) based on SGAM, optimized for rapid prototyping of smart grid applications using a model-driven engineering approach with automatic code generation. The goal of this approach is to support the development process of smart Grid applications, from use case description to implementation. The paper presents a use case described by the DSL and shows how an IEC 61499 control application and an IEC 61850 communication configuration can be automatically generated.

Applying the SGAM methodology for rapid prototyping of smart Grid applications

A driving force for the realization of a sustainable energy supply is the integration of renewable energy resources. Due to their stochastic generation behaviour, energy utilities are confronted with a more complex operation of the underlying power grids. Additionally, due to technology developments, controllable loads, integration with other energy sources, changing regulatory rules, and the market liberalization, the system’s operation needs adaptation. Proper operational concepts and intelligent automation provide the basis to turn the existing power system into an intelligent entity, a cyber-physical energy system. The electric energy system is therefore moving from a single system to a system of systems. While reaping the benefits with new intelligent behaviors, it is expected that system-level developments, architectural concepts, advanced automation and control as well as the validation and testing will play a significantly larger role in realizing future solutions and technologies. The implementation and deployment of these complex systems of systems are associated with increasing engineering complexity resulting also in increased engineering costs. Proper engineering and validation approaches, concepts, and tools are partly missing until now. Therefore, this paper discusses and summarizes the main needs and requirements as well as the status quo in research and development related to the engineering and validation of cyber-physical energy systems. Also research trends and necessary future activities are outlined.

Engineering and Validating Cyber-Physical Energy Systems: Needs, Status Quo, and Research Trends

A huge set of Smart Grid related standards already exist and is continuously being updated in various technical working groups in various parts of the world. Ongoing EU-funded ELECTRA Integrated Research Programme (IRP) on Smart Grids [1] aims to re-use the existing standards within its in progress activities considering to be in compliance with the standardization groups like CEN/CENELEC/ETSI, NIST and others. Moving towards the implementation of the functional architecture, it is important to be aware of the information to be exchanged and how communication protocols can be used in support of Smart Grid information exchange. Therefore, a reference method needs to be developed for assessing and classifying the ICT interoperability standards and specifications. The existing Common Assessment Method for Standards and Specifications (CAMSS) is thought to be a tool for Public Administration choices of standards, especially for e-government and e-procurement in EU. Despite CAMSS defines an evaluation schema for standards and specifications via an Excel tool, this paper shows that the CAMSS approach needs to be modified and adapted for the goals of ELECTRA IRP. Moreover, the elaborated tool would not only be useful for ELECTRA purposes but it would be used in a broader Smart Grid (SG) perspective as well and also, with some slight adaptations, more in general, for all complex contexts involving a high number of standards (e.g. the Smart City context).

Looking for the unified classification and evaluation approach of SG interface standards for the purposes of ELECTRA IRP

Even if energy efficiency represents a crucial issue for the sustainability of the manufacturing industry, the companies need to be encouraged in investing their resources for this goal. One of the means to facilitate this effort is the comparison of the energy performances with similar factories. Nevertheless, since the enterprises are very heterogeneous, these performance values have, even within a specified manufacturing sector, a high variability and therefore risk not to be representative. The dispersion of these data has to be decisively decreased. This goal is pursued here by means of an energy consumption characterization model based on: 1. a self-analysis software tool collecting energy consumption data in a simple and homogeneous way; 2. the clustering of the factories; 3. the separation of the auxiliary energy uses from the production process energy consumption. The method is here applied to textile industry with a focus on the electrical consumption in yarn factories. The outcomes show a correlation with some production variables, such as the raw materials, and allow to reduce the relative errors of the energy performances of different factories from about 80% to about 25-40%. In this way, energy reference indicators can be built in an acceptable and representative way.

Energy Consumption Characterization based on a Self-analysis Tool: A Case Study in Yarn Manufacturing.

The integrated use of ion channels and electronics is a promising approach to develop rapid, sensitive and reliable biosensors able to detect low concentration of target molecules, with applications that range from pharmacology to diagnostic tools. Several reports on stochastic sensors have been published [2-4], however all are based on bulky and expensive instruments. This paper presents a compact (two credit cards size) and low-cost integrated system able to record and process signals in the typical single-channel recording bandwidths. To test the approach, we used signals derived from non-covalent bonds between single alpha-hemolysin pores, embedded into an artificial lipid bilayer, and beta-cyclodextrin molecules. The system is based on a DeltaSigma converter implemented on a PCB using discrete components technology to readout ion currents in the order of pA. The digitized output is sent to a DSP for decimation and filtering and then to a PC for storage, visualization and stochastic data processing.

A Compact System for Single Ion Channel Recording

The problem of Energy Efficiency in industry is a hot topic but companies are not still implementing, on a mass scale, energy efficiency actions. One of the most important barriers is that companies are scarcely aware of their consumptions and consider energy as a fixed cost and not as a resource to be managed. In this paper it is proposed a model, based on self-analysis of consumptions, for facing this barrier. On the base of this model, a software tool, Energy Saving and Efficiency Tool (ESET), was designed as a starting point of an energy diagnosis path for SMEs. ESET was developed for textile/clothing sector but the model is general and, starting from it, similar sectorial tools can be developed. The tool provides different kinds of outputs: best practices, for helping companies to improve its own energy performances; energy efficiency indices, compared with reference values; energy use behaviours. Particularly, best practices are selected using a large set of rules, distilled from the experience of professional energy auditors. The analysis of the accuracy and completeness of ESET results was performed on six companies selected among all those involved in ESET testing and application. The results of this evaluation are very encouraging.

Energy saving and efficiency tool: A sectorial decision support model for energy consumption reduction in manufacturing SMEs

Energy efficiency in the industry sector represents a crucial issue for the sustainable development, but manufacturing companies are not still implementing, on a mass scale, energy saving actions One of the most important barriers is that many companies are scarcely aware about their consumptions and need reference values to compare their energy performances with similar factories Nevertheless, since the enterprises are very heterogeneous and the production chains is often fragmented, these values have a high variability The dispersion of these data has to be decisively decreased, but keeping generality to be representative This goal is pursued here for the textile sector analysing datasets regarding 140 European factories The datasets were retrieved by means of a self-analysis software tool, collecting energy consumption data in a simple and homogeneous way The analysis of the data was performed using energy efficiency indicators and by clustering the factories The method is here applied to textile industry and the outcomes show a correlation with some production variables, such as the raw materials, the kind of process and the price of the final products The approach based on a regression analysis between energy consumptions and production has allowed to reduce the relative errors of the energy performances of different categories of factories from more than 100% to about 25–40% in many cases In this way, energy efficiency indicators can be adopted as acceptable and representative references

Samuele Branchetti

Papers

Looking for the unified classification and evaluation approach of SG interface standards for the purposes of ELECTRA IRP

Energy Consumption Characterization based on a Self-analysis Tool: A Case Study in Yarn Manufacturing.

A Compact System for Single Ion Channel Recording

Energy saving and efficiency tool: A sectorial decision support model for energy consumption reduction in manufacturing SMEs

Energy Efficiency Indicators for Textile Industry Based on a Self-analysis Tool