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

The evaluation of national accounting matrices with environmental accounts (NAMEA) as a methodology for carrying out a sustainability assessment of the Scottish food and drink sector

This report introduces environmental input-output (IO) accounts for Scotland as an example of a NAMEA framework. It provides an introduction to the use of basic IO multiplier methodology, which can be applied to examine pollution/waste generation and/or resource use under production and consumption accounting principles

Smart Grid for the Smart City

Modern cities are embracing cutting-edge technologies to improve the services they offer to the citizens from traffic control to the reduction of greenhouse gases and energy provisioning. In this chapter, we look at the energy sector advocating how Information and Communication Technologies (ICT) and signal processing techniques can be integrated into next generation power grids for an increased effectiveness in terms of: electrical stability, distribution, improved communication security, energy production, and utilization. In particular, we deliberate about the use of these techniques within new demand response paradigms, where communities of prosumers (e.g., households, generating part of their electricity consumption) contribute to the satisfaction of the energy demand through load balancing and peak shaving. Our discussion also covers the use of big data analytics for demand response and serious games as a tool to promote energy-efficient behaviors from end users

Market Structure Scenarios in International Steam Coal Trade

The seaborne steam coal market changed in recent years. Trade volumes grew dynamically, important players emerged and since 2007 prices increased significantly and remained relatively high since then. In this paper we analyse market equilibria in the years 2006 and 2008 by testing for two possible market structure scenarios in this market: perfect competition and an oligopoly setup with major exporters competing in quantities. We conclude from our results that international steam coal trade is not perfectly competitive as there is a large spread between marginal costs and prices and a low capacity utilisation in 2008. Further, trade flows are generally more diversified in reality than in the competitive scenario. However, also the Cournot scenarios fail to accurately explain real market outcomes. We conclude that only more sophisticated models of strategic behaviour can predict market equilibria in international steam coal trade.Steam coal trade; Mining Costs; Market Structure

Effective Tax Rates in Transition

The paper addresses the question of effective tax rates for Russian economic sectors in transition. It presents a detailed account of fiscal environment for 1995 and compares statutory obligations with reported tax liabilities. The paper finds that taxation did not contribute to recession, as some observors believed at the time. It extends research by questioning the role that inflation played distorting revenue structure. When the costs of intermediate inputs are adjusted for inflation, many sectors have negative residual revenue, which is indicative of recession. Yet, modeling tax changes to correct the situation does not produce positive results, for the tax share in the cost structure of many sectors is small and cannot compensate for inflationhttp://deepblue.lib.umich.edu/bitstream/2027.42/39762/3/wp378.pd

Structural Change and Technology. A Long View

change, technology