Event
Civil Systems Seminar: Mel Devine, "Tariff Specification"; "The UK Natural Gas Market"
Tuesday, April 29, 2014
5:00 p.m.
1202 Engineering Laboratory Building (EGL)
Andrew Blohm
andymd26@umd.edu
Civil Systems Seminar
Incorporating Aversion to Market Price Risk In Efficient Feed-In Tariff Specification
—and—
Rolling optimisation applied to the UK natural gas market
Mel Devine
Postdoctoral researcher
Mathematics Applications Consortium for Science & Industry (MACSI)
University of Limerick, Ireland
Light refreshments will precede the lecture from 4:30 – 5:00 pm
Abstract 1: Incorporating Aversion to Market Price Risk In Efficient Feed-In Tariff Specification
Ireland’s Renewable Energy Feed-in Tariff (REFIT) provides investors with a guaranteed price per unit of electricity generated, whilst also allowing them receive the market price should it exceed the minimum agreed amount. However, this is one of many tariff designs in existence. It is the purpose of this work to compare the efficiency of a number of Renewable Energy Feed-in Tariff designs to identify under what conditions a given design may be preferred. This preference is identified by incorporating both investor and policymaker exposure to risk into the decision to implement a given tariff. The interactions between policymakers and investors are modelled using a bi-level non-linear stochastic optimisation model. Numerical simulations are used to identify the conditions under which a given tariff may be preferred which also facilitates a more in-depth analysis of the conditions of tariff preference. This talk shall present the methodologies employed, findings obtained to date, and further work to be carried out.
Abstract 2: Rolling optimisation applied to the UK natural gas market
Gas demand in the UK is variable. This is partly due to weather patterns and the changing nature of electricity markets. This uncertainty makes it difficult for traders to analyse the market. As a result, there is an increasing need for models of natural gas markets that include stochastic demand. In this work, a Rolling Optimisation Model (ROM) of the UK natural gas market is described. It takes as an input demand scenarios simulated from a stochastic process of UK gas demand. The outputs of ROM are the flows of gas, i.e., how the different sources of supply meet demand, as well as how gas flows in to and out of gas storage facilities, and the daily System Average Price of gas. The model was found to fit reasonably well to historic data from the UK National Grid. These results allow ROM to be used to predict future flows and prices of gas and to investigate various `What-if' scenarios in the UK natural gas market.
Biography
Mel Devine received a B. Sc. in Mathematical Sciences and a Ph. D. in Applied Mathematics from the University of Limerick (UL) in 2009 and 2013 respectively. Currently he is a post-doctoral researcher in the Mathematics Applications Consortium for Science & Industry (MACSI) in UL, with responsible for liaising between MACSI and its engineering and economics partners within the Strategic Research Cluster “Sustainable Electrical Energy Systems”. These partners include the Economic & Social Research Institute and Electricity Research Centre in University College Dublin. His research interests include the mathematical modeling of energy markets as well as stochastic and risk modeling.
