Attributes of Big Data Analytics for Data-Driven Decision Making in Cyber-Physical Power Systems

Big data analytics is a virtually new term in power system terminology. This concept delves into the way a massive volume of data is acquired, processed, analyzed to extract insight from available data. In particular, big data analytics alludes to applications of artificial intelligence, machine learning techniques, data mining techniques, time-series forecasting methods. Decision-makers in power systems have been long plagued by incapability and weakness of classical methods in dealing with large-scale real practical cases due to the existence of thousands or millions of variables, being time-consuming, the requirement of a high computation burden, divergence of results, unjustifiable errors, and poor accuracy of the model. Big data analytics is an ongoing topic, which pinpoints how to extract insights from these large data sets. The extant article has enumerated the applications of big data analytics in future power systems through several layers from grid-scale to local-scale. Big data analytics has many applications in the areas of smart grid implementation, electricity markets, execution of collaborative operation schemes, enhancement of microgrid operation autonomy, management of electric vehicle operations in smart grids, active distribution network control, district hub system management, multi-agent energy systems, electricity theft detection, stability and security assessment by PMUs, and better exploitation of renewable energy sources. The employment of big data analytics entails some prerequisites, such as the proliferation of IoT-enabled devices, easily-accessible cloud space, blockchain, etc. This paper has comprehensively conducted an extensive review of the applications of big data analytics along with the prevailing challenges and solutions

From mode choice to modal diversion: A new behavioural paradigm and an application to the study of the demand for innovative transport services

We analyse past research efforts that focus on modal diversion in the transport sector, as opposed to the classical mode choice concept, showing the added value of this alternative framework that emerges from the existing scientific literature. The modal diversion paradigm is then used to assess the relative importance of the technical performances of transport services on one hand and of the subjective factors of its potential users on the other, when forecasting the use of a new means among a group of white-collars working in a French research institute. We quantitatively show that multimodal habits and cognitive attitudes have an importance that is in general not negligible for this group, compared to that of the transport services performances, even if only these latter are routinely considered by engineers and planners. Beyond this, we find that the role of self-related factors further increased when the group was less familiar with the technological background and the subsequent operation of the new system, such as in the case of demand responsive transport service

From supply chains to demand networks. Agents in retailing: the electrical bazaar

A paradigm shift is taking place in logistics. The focus is changing from operational effectiveness to adaptation. Supply Chains will develop into networks that will adapt to consumer demand in almost real time. Time to market, capacity of adaptation and enrichment of customer experience seem to be the key elements of this new paradigm. In this environment emerging technologies like RFID (Radio Frequency ID), Intelligent Products and the Internet, are triggering a reconsideration of methods, procedures and goals. We present a Multiagent System framework specialized in retail that addresses these changes with the use of rational agents and takes advantages of the new market opportunities. Like in an old bazaar, agents able to learn, cooperate, take advantage of gossip and distinguish between collaborators and competitors, have the ability to adapt, learn and react to a changing environment better than any other structure. Keywords: Supply Chains, Distributed Artificial Intelligence, Multiagent System.Postprint (published version

An Evolutionary Computational Approach for the Problem of Unit Commitment and Economic Dispatch in Microgrids under Several Operation Modes

In the last decades, new types of generation technologies have emerged and have been gradually integrated into the existing power systems, moving their classical architectures to distributed systems. Despite the positive features associated to this paradigm, new problems arise such as coordination and uncertainty. In this framework, microgrids constitute an effective solution to deal with the coordination and operation of these distributed energy resources. This paper proposes a Genetic Algorithm (GA) to address the combined problem of Unit Commitment (UC) and Economic Dispatch (ED). With this end, a model of a microgrid is introduced together with all the control variables and physical constraints. To optimally operate the microgrid, three operation modes are introduced. The first two attend to optimize economical and environmental factors, while the last operation mode considers the errors induced by the uncertainties in the demand forecasting. Therefore, it achieves a robust design that guarantees the power supply for different confidence levels. Finally, the algorithm was applied to an example scenario to illustrate its performance. The achieved simulation results demonstrate the validity of the proposed approach.Ministerio de Ciencia, Innovación y Universidades TEC2016-80242-PMinisterio de Economía y Competitividad PCIN-2015-043Universidad de Sevilla Programa propio de I+D+

Smart Grid Technologies in Europe: An Overview

The old electricity network infrastructure has proven to be inadequate, with respect to modern challenges such as alternative energy sources, electricity demand and energy saving policies. Moreover, Information and Communication Technologies (ICT) seem to have reached an adequate level of reliability and flexibility in order to support a new concept of electricity network—the smart grid. In this work, we will analyse the state-of-the-art of smart grids, in their technical, management, security, and optimization aspects. We will also provide a brief overview of the regulatory aspects involved in the development of a smart grid, mainly from the viewpoint of the European Unio

MPM – The Magyar Nemzeti Bank’s monetary policy model

March 2011 marked the introduction of the MNB’s Monetary Policy Model (MPM), representing a paradigm shift in both inflation forecasting and monetary policy decision support. In contrast to the previous conditional projections, the MPM offers an endogenous definition for both the policy rate and the exchange rate. Given the forward-looking nature of this model, expectations by economic agents play a key role in monetary transmission; therefore, instead of one-off interest rate measures, the achievement of inflation target is guaranteed by the entire interest rate path over the forecast horizon. In the following, we discuss the underlying structure and logic behind the MPM, as well as the functioning of key behavioural equations, while also examining how the channels of monetary transmission appear in the model. We also present our motivations regarding the model switch and review how developing and operating this new tool have changed our current processes.forecasting, monetary policy, inflation targeting, macroeconomic model.

A MPC Strategy for the Optimal Management of Microgrids Based on Evolutionary Optimization

In this paper, a novel model predictive control strategy, with a 24-h prediction horizon, is proposed to reduce the operational cost of microgrids. To overcome the complexity of the optimization problems arising from the operation of the microgrid at each step, an adaptive evolutionary strategy with a satisfactory trade-off between exploration and exploitation capabilities was added to the model predictive control. The proposed strategy was evaluated using a representative microgrid that includes a wind turbine, a photovoltaic plant, a microturbine, a diesel engine, and an energy storage system. The achieved results demonstrate the validity of the proposed approach, outperforming a global scheduling planner-based on a genetic algorithm by 14.2% in terms of operational cost. In addition, the proposed approach also better manages the use of the energy storage system.Ministerio de Economía y Competitividad DPI2016-75294-C2-2-RUnión Europea (Programa Horizonte 2020) 76409

Approaches for the anticipation of skill needs in the Transitional Labour Market perspecitve: The Austrian experience

A synthesis of studies regarding anticipation practices in Austria is provided. The theoretical approach combines concepts from transitional labour market theory, the foresight paradigm, institutional approaches to the coordination of education and employment, and the concept of an anticipation system as a social system of knowledge generation and management. The Analysis focuses on four main aspects: (1) the communication structure, (2) the current state of forecasting, (3) anticipation practices at the regional and sector level, and (4) the measurement and matching instruments. The Austrian system is an informal system which emphasises a professionalpolitical approach. It relies mainly on practitioner task forces which work at an informal level. The system also reflects the segmented structure of the education and training system. New developments at the regional level are related to the establishment of the Fachhochschule sector a decade ago. Another strand of development has been regional innovation policy. The regional level serves as a catalyst in setting up more elaborate systems for anticipating skill needs. The criteria for anticipation in a TLM perspective are not fulfilled. In sum, the foresight and transitional labour market approaches could provide several pathways for development. -- Das Paper enthält eine Synthese von Studien über das österreichische Antizipationssystem. Der theoretische Ansatz kombiniert Konzepte der Übergangsarbeitsmärkte, des Vorauschau-Paradigmas, der Koppelung von Bildung und Beschäftigung, und sozialer Wissensproduktion. Vier Aspekte stehen in Vordergrund: (1) die Kommunikationsstruktur, (2) formale Prognosen, (3) Praktiken auf regionaler und sektoraler Ebene, und (4) Mess- und Matching-Instrumente. Das österreichische Antizipationssystem ist ein informelles System auf Basis eines professionell-politischen Ansatzes. Es baut wesentlich auf informellen PraktikerInnen- Arbeitsgruppen auf und reflektiert die segmentierte Struktur des Bildungswesens. Wesentliche Entwicklungsimpulse gehen von der regionalen Ebene aus. Die Kriterien des Ansatzes der Übergangsarbeitsmärkte sind nicht erfüllt und können wichtige Impulse für die Weiterentwicklung geben.

Models in evolutionary economics and environmental policy: Towards an evolutionary environmental economics

In this paper we review evolutionary economic modelling in relation to environmental policy. We discuss three areas in which evolutionary economic models have a particularly high added value for environmental policy-making: the double externality problem, technological transitions and consumer demand. We explore the possibilities to apply evolutionary economic models in environmental policy assessment, including the opportunities for making policy-making endogenous to environmental innovation. We end with a critical discussion of the challenges that remain.