Emile Chappin

Just released: "Agent-based modelling of energy infrastructure transitions" in the International Journal of Critical Infrastructures (vol 6 nr 2). This article gives an outline of the theoretical framework developed for my PhD project on simulation models of energy transitions. Three examples are given in which the framework is adopted. The paper is accessible here and is published by Inderscience.

Abstract
Shaping energy transitions not only requires technical system innovation and redesign but also new policies, regulations, Research and Development (R&D) and investment strategies – a transition assemblage. Transition management thus equates to designing and implementing such an assemblage. Agent-Based Models (ABMs) may be used for ex-ante assessment of transition assemblage alternatives. To help determine whether the design of a particular model is fit for its purpose, we have developed a typology. Three models were assessed:

1. A model on the impact of CO2 policy on the power production sector
2. A model on the transition of the global Liquefied Natural Gas (LNG) infrastructure
3. A model on the imminent transition caused by the arrival of Light-Emitting Diode (LED) lighting systems.

All three models can be used to compare transition assemblage alternatives and could be adapted to assess regulatory adaptability.

New release: Generating Electricity in a Carbon Constrained World

The book Generating Electricity in a Carbon-Constrained World, in which I wrote chapter 2, Carbon policies: Do they deliver in the long run? has just come available. For more information, check out this book at Amazon.com.

Abstract
Carbon taxation and emission trading are policy instruments for achieving significant CO2 emission reduction by inducing a shift in technology and fuel choice. Simulations with a quantitative agent-based model of a competitive electricity generation sector show that under both policies CO2 emissions increase for 10-15 years due to the long life cycle of power plants. Dramatic reductions materialize after 20-40 years when a tight cap or sufficient tax level is maintained. When taxes are set equivalent to trading prices, taxation induces earlier investment in CO2 abatement, a better balance between capital and operating costs and lower long-run electricity prices.

Design of Simulation Models for Energy Transition Management (Delft Design and Engineering Day)

For the Design and Engineering Day 2009, on 5 november 2009, a poster was presented on the topic of design. As I take a design approach for transitions, this resulted in this poster. More information on this event at http://www.tudelft.nl/ddea.

Abstract
Simulation models are used for designing and managing transitions in the energy domain. With this design approach we demonstrate the usefulness of simulation for assessing the potential of transition management: transitions management principles are tested ex-ante. Agent-Based Models show the potential for policy makers. The first main result shows the effect of carbon policies on CO2 reduction in the power generation sector: A dramatic effect on CO2 levels can only be expected in the long run. Taxation probably leads to more CO2 reduction at a lower cost than emission trading. Simulation models help to understand the dynamics involved.

No Drop in CO2 Emissions Despite Emission Trading (TPM in Focus)

A public magazine article on my work appeared in TPM in Focus (in English and Dutch), a magazine highlighting research results at the Faculty of Technology, Policy and Management at TU Delft. This article highlights the results from an Agent-Based Model

Abstract
For his final thesis in the Energy & Industry section, Emile Chappin carried out research into CO2 emission trading. He examined whether this instrument had prompted electricity producers to adopt low-CO2 production methods. Although in the long term this would appear to be the case, it will not lead to an overall drop in CO2 emissions within the sector.

On the Impact of CO2 Emission-Trading on Power Generation Emissions (Technological Forecasting and Social Change)

An article is publishsed in the highly valued journal on Technological Forecasting and Social Change, with the results from a case study on the impact of emission-trading on power generation emissions. The paper can be downloaded here.

Abstract
Under the Kyoto Protocol, governments agreed on and accepted CO2 reduction targets in order to counter climate change. In Europe one of the main policy instruments to meet the agreed reduction targets is CO2 emission-trading (CET), which was implemented as of January 2005. In this system, companies active in specific sectors must be in the possession of CO2 emission rights to an amount equal to their CO2 emission. In Europe, electricity generation accounts for one-third of CO2 emissions. Since the power generation sector, has been liberalized, reregulated and privatized in the last decade, around Europe autonomous companies determine the sectors’ CO2 emission. Short-term they adjust their operation, long-term they decide on (dis)investment in power generation facilities and technology selection. An agent-based model is presented to elucidate the effect of CET on the decisions of power companies in an oligopolistic market. Simulations over an extensive scenario-space show that there CET does have an impact. A long-term portfolio shift towards less-CO2 intensive power generation is observed. However, the effect of CET is relatively small and materializes late. Under most scenarios the absolute emissions from power generation rise under most scenarios. This corresponds to the dominant character of current capacity expansion planned in the Netherlands (50%) and in Germany (68%), where companies have announced many new coal based power plants. Coal is the most CO2 intensive option available and it seems surprising that even after the introduction of CET these capacity expansion plans indicate a preference for coal. Apparently in power generation the economic effect of CO2 emission-trading is not sufficient to outweigh the economic incentives to choose for coal.