Published Papers

Due to the increasing importance of natural gas for modern economic activity, and gas's non-renewable nature, it is extremely important to try to estimate possible trajectories of future natural gas production while considering uncertainties in resource estimates, demand growth,production growth and other factors that might limit production. Inthisstudy, we develop future scenarios for natural gas supply using the ACEGES computational laboratory. Conditionally on the currently estimated ultimate recover-able resources, the 'Collective View' and 'Golden Age' Scenarios suggest that the supply of natural gas is likely to meet the increasing demand for natural gas until at least 2035. The 'Golden Age' Scenario suggests significant 'jumps' of natural gas production - important for testing the resilience of long-term strategies.

The chapter presents a new approach to address energy policy and security based upon the ACEGES (Agent-based Computational Economics of the Global Energy System) model and the SPT (stochastic portfolio theory).

The ACEGES model is an agent-based model for exploratory energy policy by means of controlled computational experiments. The ACEGES model is designed to be the foundation for large custom-purpose simulations of the global energy system by modeling explicitly 216 countries.

This paper illustrates the power of modern statistical modelling in estimating measures of market risk, here applied to the Brent and WTI spot price of oil. Both Value-at-Risk (VaR) and Expected Shortfall (ES) are cast in terms of conditional centiles based upon semiparametric regression models. Using the GAMLSS statistical framework, we stress the important aspects of selecting a highly flexible parametric distribution (skewed Student's t distribution) and of modelling both skewness and kurtosis as nonparametric functions of the price of oil futures. Furthermore, an empirical application characterises the relationship between spot oil prices and oil futures - exploiting the futures market to explain the dynamics of the physical market. Our results suggest that NYMEX WTI has heavier tails compared with the ICE Brent. Contrary to the common platitude of the industry, we argue that 'somebody knows something' in the oil business.

This paper investigates the behaviour of spot prices in eight energy markets that trade futures contracts on NYMEX. We consider two types of models, a mean-reverting model, and a spike model with mean reversion that incorporates two different speeds of mean reversion; one for the fast mean-reverting behaviour of prices after a jump occurs, and another for the slower mean reversion rate of the diffusive part of the model. We also extend these models to incorporate time-varying volatility in their specification, modelled as a GARCH and an EGARCH process. We compare the relative goodness of fit of the different modelling variations both in sample, using Monte Carlo simulations, as well as out-of-sample, in a Value-at-Risk (VaR) setting.

Our results indicate the presence of a "leverage effect" for WTI, Heating Oil and Heating Oil-WTI crack spread, whereas for the remaining energy markets we find the presence of an "inverse leverage" effect. Also, the addition of the EGARCH specification for the volatility process improves both the in-sample fit as well as the out-of-sample VaR performance for most energy markets that we examine.

As the world economy highly depends on crude oil, it is important to understand the dynamics of crude oil production and export capacity of major oil-exporting countries. Since crude oil resources are predominately located in the OPEC Middle East, these countries are expected to have significant leverage in the world crude oil markets by taking into account a range of uncertainties. In this study, we develop a scenario for crude oil export and production using the ACEGES model considering uncertainties in the resource limits, demand growth, production growth, and peak/decline point. The results indicate that the country-specific peak of both crude oil export and production comes in the early this century in the OPEC Middle East countries. On the other hand, they occupy most of the world export and production before and after the peak points. Consequently, these countries are expected to be the key group in the world crude oil markets. We also find that the gap between the world crude oil demand and production broadens over time, meaning that the acceleration of the development of ultra-deep-water oil, oil sands, and extra-heavy oil will be required if the world continuous to heavily rely on oil products.

Multiattribute additive value functions constitute an important class of models for multicriteria decision making. Such models are often used to rank a set of alternatives or to classify them into pre-defined groups. Preference disaggregation techniques have been used to construct additive value models using linear programming techniques based on the assumption of monotonic preferences. This paper presents a methodology to construct non-monotonic value function models, using an evolutionary optimization approach. The methodology is implemented for the construction of multicriteria models that can be used to classify the alternatives in pre-defined groups, with an application to credit rating.

Abstract  

In times of uncertainties scenarios offer a solution. Starting with Royal Dutch Shell by the late 1960s, corporate scenarios are intended to challenge managers' "personal microcosms" and to reflect the present and the past, before structuring the uncertainties of the future. Therefore, scenarios act as 'early warning systems' by focusing on the driving forces that makes a difference to decision-makers.

Keywords

Oil scenarios, ACEGES, energy scenarios, Shell's scenarios, oil strategies

Introduction

1. This evidence is presented to the Select Committee to provide a perspective in terms of the threats, vulnerability and consequences of the UK Energy Supply System within a global-national context characterized by unprecedented uncertainties and increasingly complex intertwines. This contribution is based upon the ACEGES project (www.aceges.org). ACEGES stands for Agent-based Computational  Economics of the Global Energy  System. The ACEGES models the energy demand and supply of 216 countries.

2. The aim is not to present another set of quantifications for policymaking, as there are a number of reports and papers published in recent years. Rather the aim is to provide a coherent overview of i) the assumptions of the energy models used to produce the published quantifications and ii) the approach used to develop energy scenarios for the assessment of the UK's Energy Supply.

3. I am a specialist in the modelling of fuzzy phenomena and complex adaptive systems such as the Energy System. My research work aims to support evidence-based energy policy by means of controlled computational experiments. Currently, I am the Deputy Director of the Centre for International Business and Sustainability (CIBS) at the London Metropolitan Business School. I am also the organise of the "UK Energy Day: Sustainable Supply" which is part of the European network of events led by the Intelligent Energy Europe (IEE) agency of the European Commission (EC).

4. It is evident today that the long-term sustainability of the UK's energy system is under acute strain. Therefore the comments that follow mainly deal with the need to enhance:

a. The existing energy models to assess the sensitivity of the UK's energy supply.

b. The way of developing multidimensional global-national continuous scenarios for long-term assessment of the resilient of the UK energy system to international events.

I will start with the latter.

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This paper reproduces the performance of a geometric average Spot Energy Index by investing only in a subset of stocks from the Dow Jones Composite Average, the FTSE 100 and Bovespa Composite indexes, and in two pools including only stocks of the energy sector from the US and the UK respectively. Daily data are used and the index-tracking problem for passive investment is addressed with two innovative evolutionary algorithms; the differential evolution algorithm and the genetic algorithm, respectively. The performance of the suggested investment strategy is tested under three different scenarios: buy-and-hold, quarterly, and monthly rebalancing;accounting for transaction costs where necessary.

Abstract 

The fusion of agent-based and geospatial models represents an exciting new synthesis for social science and economics. It has the potential to improve the theory and the practice of modelling complex real-world phenomena. Yet, to date, there has been little systematic analysis at the conceptual and logical levels of how to fuse agent-based and geospatial models for the representation and reasoning of socioeconomic phenomena. Here both sets of issues are explored. In particular, it will be argued that the development of synthetic models requires autonomous agents and flexible organisational structures that can complete their objectives while situated in a dynamic and uncertain geoenvironment represented by the concept of Elementary_geoParticle. As an example of the concept, I present a preliminary conceptual model of global energy to demonstrate the validity and possible uses of the proposed technique.

At the 1992 Rio Earth Summit, great emphasis was placed on energy efficiency in the Opening Session. That message, and indeed the subject of energy more generally, largely disappeared in the forty chapters and 600 pages of Agenda 21 that emerged from Rio. This situation has largely remained in subsequent UN deliberations. Closer focus on climate change, deforestation, and poverty has failed to produce significant benefits.

By 2010, world carbon dioxide emissions from the use of fossil fuels had risen over 46% from 1990 levels. Renewable energy projects have been pursued with scant regard for efficiency or costs to users. Still 2.7 billion people-some 40% of the World's population-rely overwhelmingly on traditional biomass; 1.5 billion others have no electricity supply; and a further 1 billion only have sporadic supply. Fossil fuels continue to provide nearly 85% of the World's primary energy, while renewable energy sources provide about 13%-of which traditional biomass accounts for 10.2% and all other renewable resources for only 2.8%. Of this 2.8%, hydropower accounts for 2.3%, wind power for 0.2%, and direct solar energy and geothermal for 0.1% each.

Not one of the eight Millennium Development Goals (MDG) produced in 2000 refers to energy. Then in 2005 UNDP, together with the World Bank and ESMAP, produced "Energy Services for the Millennium Development Goals", which pointed out that "failure to include energy considerations in national MDG strategies and development planning frameworks will severely limit the ability to achieve the MDGs." It also stated: "Increased energy efficiency-whether during generation/production, transport/ transmission, or end-use-can have wide-ranging benefits." In 2010, the UN Advisory Group on Energy and Climate Change (AGECC) report "Energy for a Sustainable Future" referred to improving energy access and strengthening energy efficiency as the "two priorities". AGECC's Chairman (and Head of UNIDO) stated that "a vast potential for energy efficiency improvements across the supply and delivery chain remains largely untapped." Also in 2010, the UN's General Assembly proclaimed 2012 the International Year for Sustainable Energy. Will there be a new, and more effective, focus on energy and efficiency in its provision and use?