EMC Working Papers

Are We Creating a Compromise?

Every year in the United Kingdom and Australia, thousands of incidents involving devastating fires linked to batteries in waste management facilities or vehicles are reported. Paradoxically, these are facilities meant to contain such hazardous activities. Furthermore, headlines such as “Batteries Starting Fires at Yellowknife’s Landfill, City Says,” posted by Cabin Radio, report unreported hazardous incidents potentially linked to batteries, and are becoming more common around the globe. These reports and news are increasingly alarming because they come at the cost of life, property damage, and monetary losses, and given the fact that we heavily rely on batteries for the energy transition, they could lead to safety and environmental compromises if not treated properly.

The potential for blockchain technology to profoundly disrupt the world as we know it is enormous. The financial system is often seen as the most vulnerable industry primed for disruption. This technology has the potential to disrupt a variety of industries, including aerospace and defence, supply chain and logistics, and energy management, most notably decentralised micro-grid systems.

Background

• Examine the common misconceptions about the environmental impact of Blockchain mining
• Analyse the options for transitioning blockchain mining away from fossil fuels and towards variable renewable energy sources (vRES)

Energy efficiency is high on the agenda of policy makers because it contributes to the achievements of the three main objectives of energy policy: security, affordability and sustainability. In this paper the focus is placed on efficiency gains arising from the adoption of smart energy technologies by domestic and small corporate users, including smart metering and "beyond the meter" management systems, home area networks and devices. Though the expected benefits are important a lot remains to be done. Condition for smart energy systems to be adopted and barriers to their adoption are discussed. Considering the dominant suspicious attitude toward utilities it appears that a trustworthy independent business entity, building a proper relation between users and technology providers, is needed to assure the deployment of smart energy technologies across the population concerned. 

Growth has been the driving force for most countries and organizations. Global economy has grown over the last thirty years. Although the growth rate varied, but overall the global economy has got a rate of over 2 % as measured by GNP. During the last ten years we are seeing a new phenomenon; the emerging markets have grown at a much faster rate. The balance of global economy has radically changed. But where does energy come in? The growth means demand for energy. Energy production has to grow to sustain the growth.

This paper evaluates the energy efficiency of EU countries over the period 2000-2010. At the first stage, Data Envelopment Analysis (DEA) is employed, combining multiple energy consumption data, economic outputs, structural indicators, and environmental factors. The efficiency estimates obtained from the analysis are evaluated in a second stage through a multiple criteria decision aiding methodology (MCDA). The proposed non-parametric approach combining DEA with MCDA enables the modeling of the problem in an integrated manner, providing not only energy efficiency estimates, but also supporting the analysis of the main contributing factors, as well as the development of a benchmarking model for energy efficiency evaluation in country level.

In this paper we present an empirical study to verify the assertion of a negative impact of economic growth on carbon efficiency using a cross country analysis. More precisely we are concerned with the relation between past growth and CO2 emissions, assuming that rapid growth in the past may explain lower carbon efficiency today. The central idea tested is that hasty growth is likely to slow down the improvement of energy and carbon efficiency. In other words, using an ordinary least square multifactor model to explain carbon intensity, we verify that the coefficient for an exogenous variable measuring the average past growth rate (apgr) for each country in our sample, is significantly positive.

The flame of oil is not eternal. The horizon carries all signs of peak oil.Saudi Arabia, the world's biggest crude oil producer and exporter risks becoming an oil importer probably by 2025 if current economic, demographic and security trends continue into the future. Saudi oil production peaked in 2005 and has been in steady decline since then with domestic oil demand rising at an alarming rate and accounting for 37% of crude production in 2012. As a result, Saudi crude exports have already declined by 32% between 2005 and 2012 and are projected to decline further by 9% by 2015. Population growth and robust economic development and also fuel subsidies drive that demand.

By 2025 Saudi oil consumption is projected to exceed production by 610,000 barrels a day (b/d) and Saudi Arabia would have ceased, to all intents and purposes, to remain a net oil exporter. This paper will argue forcefully that even a drastic cut, if not elimination, of subsidies altogether and a determined shift from oil use in power generation and desalination to nuclear and renewable energy sources starting immediately will not delay the inevitable day when Saudi Arabia will become a net oil importer. The paper will also assess the implications of this eventuality for the global economy, energy security and the price of oil

Most executives know that overarching paints of plausible futures will profoundly affect the competitiveness and survival of their organisation. Initially from the perspective of Shell, this article discuses oil scenarios and their relevance for upstream investments. Scenarios are then incorporated into generative explanation and its principal instrument, namely agent-based computational laboratories, as the new standard of explanation of the past and the present and the new way to structure the uncertainties of the future. The key concept is that the future should not be regarded as 'complicated' but as 'complex', in that there are uncertainties about the driving forces that generate unanticipated futures, which cannot be explored analytically. 

The ACEGES (Agent-based Computational Economics of the Global Energy System) 1.0 model is an agent-based model of conventional oil production for 93 countries. The model accounts for four key uncertainties, namely Estimated Ultimate Recovery (EUR), estimated growth in oil demand, estimated growth in oil production and assumed peak/decline point. This documentation provides an overview of the ACEGES model capabilities and an example of how it can be used for long-term (discrete and continuous) scenarios of conventional oil production.

Keywords:

Oil production, ACEGES, agent-based model, energy scenarios, oil forecasting