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Devine, Mel T.
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Devine, Mel T.
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Devine, Mel T.
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Now showing 1 - 10 of 20
- PublicationWhen to invest in carbon capture and storage technology: A mathematical modelWe present two models of the optimal investment decision in carbon capture and storage technology (CCS)—one where the carbon price is deterministic (based on the newly introduced carbon floor price in Great Britain) and one where the carbon price is stochastic (based on the ETS permit price in the rest of Europe). A novel feature of this work is that in both models investment costs are time dependent which adds an extra dimension to the decision problem. Our deterministic model allows for quite general dependence on carbon price and consideration of time to build and simple calculus techniques determine the optimal time to invest. We then analyse the effect of carbon price volatility on the optimal investment decision by solving a Bellman equation with an infinite planning horizon. We find that increasing the carbon price volatility increases the critical investment threshold and that adoption of this technology is not optimal at current prices, in agreement with other works. However reducing carbon price volatility by switching from carbon permits to taxes or by introducing a carbon floor as in Great Britain would accelerate the adoption of carbon abatement technologies such as CCS.
410Scopus© Citations 28 - PublicationThe effect of Demand Response and wind generation on electricity investment and operationWe present a novel method of determining the contribution of load-shifting Demand Response (DR) to energy and reserve markets. We model DR in an Mixed Complementarity Problem (MCP) framework with high levels of wind penetration. Investment, exit and operational decisions are optimized simultaneously. We examine the potential for DR to participate in both energy and reserve markets. DR participation in the energy market reduces costs and prices and gives rise to lower equilibrium levels of investment in conventional generation. DR and wind generation are strongly complementary, due to the ability of DR to mitigate against the variability of wind generation, with the highest reduction of consumer costs seen at high levels of wind penetration. The total impact of DR is highly dependent on specific system characteristics.
455Scopus© Citations 11 - PublicationA rolling horizon approach for stochastic mixed complementarity problems with endogenous learning: Application to natural gas marketsIn this paper we present a new approach for solving energy market equilibria that is an extension of the classical Nash-Cournot approach. Specifically, besides allowing the market participants to decide on their own decision variables such as production, flows or the like, we allow them to compete in terms of adjusting the data in the problem such as scenario probabilities and costs, consistent with a dynamic, more realistic approach to these markets. Such a problem in its original form is very hard to solve given the product of terms involving decision-dependent data and the variables themselves. Moreover, in its more general form, the players can affect not only each others׳ objective functions but also the constraint sets of opponents making such a formulation a more complicated instance of generalized Nash problems. This new approach involves solving a sequence of stochastic mixed complementarity (MCP) problems where only partial foresight is used, i.e., a rolling horizon. Each stochastic MCP or roll, involves a look-ahead for a fixed number of time periods with learning on the part of the players to approximate the extended Nash paradigm. Such partial foresight stochastic MCPs also offer a realism advantage over more traditional perfect foresight formulations. Additionally, the rolling-horizon approach offers a computational advantage over scenario-reduction methods as is demonstrated with numerical tests on a natural gas market stochastic MCP. Lastly, we introduce a new concept, the Value of the Rolling Horizon (VoRH) to measure the closeness of different rolling horizon schemes to a perfect foresight benchmark and provide some numerical tests on it using a stylized natural gas market.
330Scopus© Citations 23 - PublicationWho Pays for Renewables? Increasing Renewable Subsidisation due to Increased Datacentre Demand in Ireland(WERI Education Research Development Printing Publication, Ltd., 2019-06-01)
; Demand from datacentres makes up a rapidly growing portion of electricity demand in Ireland. Increased demand in turn gives rise to increased renewable generation, mandated by government targets, and a corresponding increase in subsidisation levels. The current method of apportioning renewable subsidy costs may lead to consumers other than datacentres bearing this excess cost of subsidisation. This letter calculates the expected impact on these consumers.264 - PublicationExamining the benefits of load shedding strategies using a rolling-horizon stochastic mixed complementarity equilibrium modelAs a result of government policies increasing the amount of electricity generated from fluctuating renewable sources in many countries, the requirement for flexibility in the corresponding electricity systems increases. On the demand side, load shedding is one demand response mechanism contributing to an increased flexibility. Traditionally, load shedding was based on rather static or rotational strategies, whereby the system operator chooses the consumers for load shedding. However, ongoing technological developments provide the basis for smarter and more efficient load shedding strategies. We therefore examine the costs and strategies associated with such mechanisms by modelling an electricity market with different types of generators and consumers. Some consumers provide flexibility through load shedding only while others additionally have the ability to generate their own electricity. Focussing on the impacts of how and to whom consumers with own generation ability can supply electricity, the presence of market power and generator uncertainty, we propose a rolling horizon stochastic mixed complementarity equilibrium model, where the individual optimisation problems of each player are solved simultaneously and in equilibrium. We find that a non-static strategy reduces consumer costs while allowing consumers to provide own generation to the whole market results in minimal benefits. The presence of market power was found to increase costs to consumers.
239Scopus© Citations 12 - PublicationA Rolling Optimisation Model of the UK Natural Gas Market(Springer Science and Business Media LLC, 2014-06)
; ; ; Daily gas demand in the UK is variable. This is partly due to weather patterns and the changing nature of electricity markets, where intermittent wind energy levels lead to variations in the demand for gas needed to produce electricity. This uncertainty makes it difficult for traders in the market to analyse the market. As a result, there is an increasing need for models of the UK natural gas market that include stochastic demand. In this paper, a Rolling Optimisation Model (ROM) of the UK natural gas market is introduced. It takes as an input stochastically generated scenarios of 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. The outputs also include the daily System Average Price of gas in the UK. The model was found to fit reasonably well to historic data (from the UK National Grid) for the years starting on the 1st of April for both 2010 and 2011. These results allow ROM to be used to predict future flows and prices of gas and to investigate various stress-test scenarios in the UK natural gas market.405Scopus© Citations 15 - PublicationOptimising feed-in tariff design through efficient risk allocationMany Feed-in Tariff designs exist. This paper provides a framework to determine the optimal design choice through an efficient allocation of market price risk. Feed-in Tariffs (FiTs) incentivise the deployment of renewable energy technologies by subsidising remuneration and transferring market price risk from investors, through policymakers, to a counterparty. This counterparty is often the electricity consumer. Using Stackelberg game theory, we contextualise the application of different FiT policy designs that efficiently divide market price risk between investors and consumers, conditional on risk preferences and market conditions. Explicit consideration of policymaker/consumer risk burden has not been incorporated in FiT analyses to date. We present a simulation-based modelling framework to carry this out. Through an Irish case study, we find that commonly employed flat-rate FiTs are only optimal when policymaker risk aversion is extremely low whilst constant premium policies are only optimal when investor risk aversion is extremely low. When both policymakers and investors are risk averse, an intermediate division of risk is optimal. We provide evidence to suggest that the contextual application of many FiT structures is suboptimal, assuming both investors and policymakers are at least moderately risk averse. Efficient risk allocation in FiT design choice will be of increasing policy importance as renewables deployment grows.
722Scopus© Citations 13 - Publication
133Scopus© Citations 2 - PublicationA simulation model for the management and expansion of extended port terminal operationsThis study introduces a discrete event simulation model for the analysis of bulk carrier unloading and material transport, storage and discharge at Europe’s largest alumina refinery, RUSAL Aughinish Alumina. With novel features such as the integration of additional unloading functionality, auxiliary infrastructure units, as well as efficient maintenance scheduling into the material processing chain, the model is used to predict and evaluate the performance gain in the port system in the context of long-term investment and planning scenarios. Promising strategic directions in terms of large scale performance indicators such as berth occupancy and costs have been identified.
416Scopus© Citations 29 - PublicationLiquefied natural gas and gas storage valuation: Lessons from the integrated Irish and UK marketsTo guarantee European countries greater access to competitive energy sources, the European Union has identified new infrastructures as Projects of Common Interest (PCIs). This paper aims to evaluate the implications for consumers of new investments in liquefied natural gas (LNG) import capacity and gas storage capacity. We utilise a stochastic mixed complementarity problem model with daily timesteps, incorporating stochastic natural gas supply cost and demand scenarios. Therefore, we assess the expected benefits for consumers of a diversified natural gas supply, and their sensitivity to changing market conditions. We use the integrated UK-Ireland gas system, which represents an ideal framework to evaluate new energy routes. We underscore the complementary of LNG and gas storage investments to manage short-term peak loads and long-term seasonal loads, and reduce energy bills. This study has implications for decision- and policy-makers when addressing new gas infrastructure development and the flexibility of energy systems.
433Scopus© Citations 13