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X-WR-CALNAME:Computational Optimisation Group
X-ORIGINAL-URL:https://optimisation.doc.ic.ac.uk
X-WR-CALDESC:Events for Computational Optimisation Group
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DTSTART:20110101T000000
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BEGIN:VEVENT
DTSTART;TZID=UTC:20120106T150000
DTEND;TZID=UTC:20120106T150000
DTSTAMP:20260405T142049
CREATED:20170124T102151Z
LAST-MODIFIED:20170124T102151Z
UID:618-1325862000-1325862000@optimisation.doc.ic.ac.uk
SUMMARY:Seminar: Robust Optimization of Dynamic Systems and Its Applications.
DESCRIPTION:Title: Robust Optimization of Dynamic Systems and Its Applications.Speaker: Dr. Boris Houska Affiliation: Location: CPSE Seminar room (C616 Roderic Hill)Time: 3:00pm \nAbstract. This talk gives an introduction to numerical methods for the robust optimization of uncertain dynamic systems. In contrast to standard differential equations\, which describe the propagation of a single vector-valued trajectory in time\, uncertain dynamic systems propagate a set valued function: the uncertainty tube. For the case that control inputs are available this uncertainty tube can be influenced and optimized such that certain robustness criteria are met. The aim of the first part of the talk is to explain how to formulate and solve such tube-based robust optimal control problems.The second part of the talk is about the software environment and algorithm collection ACADO Toolkit\, which implements tools for automatic control and dynamic optimization. It provides a general framework for using a great variety of algorithms for direct optimal control\, including robust optimal control and model predictive control. The ACADO Toolkit is implemented as a selfcontained C++ code\, while the object-oriented design allows for convenient coupling of existing optimization packages and for extending it with user-written optimization routines. We present numerical examples from the field of mechanics and biochemical engineering. \nAbout the speaker.
URL:https://optimisation.doc.ic.ac.uk/event/seminar-robust-optimization-of-dynamic-systems-and-its-applications/
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BEGIN:VEVENT
DTSTART;TZID=UTC:20120112T140000
DTEND;TZID=UTC:20120112T140000
DTSTAMP:20260405T142049
CREATED:20170124T102151Z
LAST-MODIFIED:20170124T102151Z
UID:617-1326376800-1326376800@optimisation.doc.ic.ac.uk
SUMMARY:Seminar: Steam Engines Jet Fighters and Credit Crises
DESCRIPTION:Title: Steam Engines Jet Fighters and Credit Crises Speaker: Dr George CooperAffiliation: BlueCrest Capital Location: Room 217-218 Huxley BuildingTime: 2:00pm \nAbstract. The talk will discuss some of the underlying causes of the financial crisis with particular focus on financial market instability\, monetary policy and the influence of the Efficient Market Hypothesis. \nAbout the speaker. George Cooper is a fund manager at BlueCrest Capital in London. Prior to joining BlueCrest George was the head of European interest rate research at JP Morgan and has also worked for both Deutsche Bank and Goldman Sachs. George’s book “The Origin of Financial Crises: Central Banks\, Credit Bubbles and the Efficient Market Fallacy” was published in August 2008 and has now been translated into over a dozen languages. George holds a PhD in engineering from Durham University.
URL:https://optimisation.doc.ic.ac.uk/event/seminar-steam-engines-jet-fighters-and-credit-crises/
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BEGIN:VEVENT
DTSTART;TZID=UTC:20120125T170000
DTEND;TZID=UTC:20120125T170000
DTSTAMP:20260405T142049
CREATED:20170124T102151Z
LAST-MODIFIED:20170124T102151Z
UID:616-1327510800-1327510800@optimisation.doc.ic.ac.uk
SUMMARY:Seminar: Universal decision rule approximations for dynamic decision-making under uncertainty
DESCRIPTION:Title: Universal decision rule approximations for dynamic decision-making under uncertaintySpeaker: Phebe VayanosAffiliation: Department of Computing – Imperial College LondonLocation: Room 217-218 Huxley BuildingTime: 5:00pm \nAbstract.  \nAbout the speaker.
URL:https://optimisation.doc.ic.ac.uk/event/seminar-universal-decision-rule-approximations-for-dynamic-decision-making-under-uncertainty/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20120126T170000
DTEND;TZID=UTC:20120126T170000
DTSTAMP:20260405T142049
CREATED:20170124T102151Z
LAST-MODIFIED:20170124T102151Z
UID:615-1327597200-1327597200@optimisation.doc.ic.ac.uk
SUMMARY:Seminar: Multistage Stochastic Portfolio Optimisation in Deregulated Electricity Markets Using Linear Decision Rules
DESCRIPTION:Title: Multistage Stochastic Portfolio Optimisation in Deregulated Electricity Markets Using Linear Decision RulesSpeaker: Paula RochaAffiliation: Department of Computing – Imperial College LondonLocation: Room 217-218 Huxley BuildingTime: 5:00pm \nAbstract. The deregulation of electricity markets often poses great financial risks to retailers who procure electric energy on the spot market to satisfy their customers’ electricity demand. To hedge against this risk exposure\, retailers often hold a portfolio of electricity derivative contracts. In this talk\, we present a multistage stochastic mean-variance optimisation model for the management of such a portfolio. To reduce computational complexity\, we perform two approximations: stage-aggregation and linear decision rules (LDR). The LDR approach consists of restricting the space of recourse decisions to those affine in the history of the random parameters. When applied to mean-variance optimisation models\, it leads to convex quadratic programs. Since their size grows typically only polynomially with the number of decision stages\, they are amenable to efficient numerical solution. Our numerical experiments highlight the value of adaptivity inherent in the LDR method and its potential for enabling scalability to portfolio optimisation problems with many decision stages. \nAbout the speaker.
URL:https://optimisation.doc.ic.ac.uk/event/seminar-multistage-stochastic-portfolio-optimisation-in-deregulated-electricity-markets-using-linear-decision-rules/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20120126T173000
DTEND;TZID=UTC:20120126T173000
DTSTAMP:20260405T142049
CREATED:20170124T102151Z
LAST-MODIFIED:20170124T102151Z
UID:614-1327599000-1327599000@optimisation.doc.ic.ac.uk
SUMMARY:Seminar: A Stochastic Capacity Expansion Model for the UK Electricity System
DESCRIPTION:Title: A Stochastic Capacity Expansion Model for the UK Electricity SystemSpeaker: Angelos GeorghiouAffiliation: Department of Computing – Imperial College LondonLocation: Room 217-218 Huxley BuildingTime: 5:30pm \nAbstract. Energy markets are currently undergoing one of their most radical changes in history. On one hand\, market liberalisation leads to a shift from state-owned utilities with a focus on failure resilience towards competitive markets where reliability is traded off with costs. This will result in a much higher utilisation of generation and transmission facilities\, which in turn leads to a less predictable system behaviour and more frequent outages. Moreover\, predictions about climate change dictate the gradual replacement of non-renewable energy sources with renewable alternatives such as solar or wind power. Contrary to non-renewable energy\, the electricity delivered from renewable sources is highly uncertain due to the intermittency of solar radiation\, wind etc. Both developments highlight the need to accommodate uncertainty in the design and management of future energy systems. This work aims to identify the most cost-efficient expansion of the UK energy grid\, given a growing future demand for energy and the target to move towards a more sustainable energy system. To this end\, we develop a multi-stage stochastic program where the investment decisions (generation units and transmission lines that should be built) are taken here-and-now\, whereas the operating decisions are taken in hourly time stages over a horizon of 30 years. The resulting problem contains several thousand time stages and is therefore severely intractable. We develop a novel problem reformulation\, based on the concept of time randomization\, that allows us to equivalently reformulate the problem as a two-stage stochastic program. By taking advantage of the simple structure of the decision rule approximation scheme\, we can model and solve a problem that optimises the entire UK energy grid with nearly 400 generators and 1000 transmission lines. \nAbout the speaker.
URL:https://optimisation.doc.ic.ac.uk/event/seminar-a-stochastic-capacity-expansion-model-for-the-uk-electricity-system/
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