The ability of liberalised electricity markets to trigger investment in the generation capacity requiredudto maintain an acceptable level of security of supply risk has been - and will continue toudbe - a topic of much debate. Like many capital intensive industries, generation investment suffersudfrom long lead and construction times, lumpiness of capacity change and high uncertainty.udAs a result, the ‘boom-and-bust’ investment cycle phenomenon, characterised by overcapacityudand low prices, followed by power shortages and high prices, is a prominent feature in the debate.udModelling the dynamics of generation investment in market environments can provideudinsights into the complexities involved and address the challenges of market design.udFurther, many governments who preside over liberalised energy markets are developing policiesudaimed at promoting investment in renewable generation. Of particular interest is the mix andudamount of generation investment over time in response to policies promoting high penetrationsudof variable output renewable power such as wind. Consequently, improved methods to calculateudexpected output, costs and revenue of thermal generation subject to varying load and randomudindependent thermal outages in a power system with a high wind penetration are needed.udIn this interdisciplinary project engineering tools are applied to an economic problem togetherudwith knowledge from numerous other disciplines. A dynamic simulation model of the aggregatedudGreat Britain (GB) generation investment market has been developed. Investment isudviewed as a negative feedback control mechanism with current and future energy prices actingudas the feedback signal. Other disciplines called upon include the use of stochastic processesudto address uncertainties such as future fuel prices, and economic theory to gain insights intoudinvestor behaviour. An ‘energy-only’ market setting is used where generation companies useuda classical NPV approach together with the Value at Risk criterion for investment decisions.udMarket price mark-ups due to market power are also accounted for.udThe model’s ability to simulate the market trends witnessed in GB since early 2001 is scrutinisedudwith encouraging findings reported. A reasonably good agreement of the model withudreality, gives a degree of confidence in the realism of future projections. An advancement toudthe dynamic model to account for expected high wind penetrations is also included. Buildingudon the initial model iteration, the short-term energy market is simulated using probabilisticudproduction costing based on theMix of Normals distribution technique with a residual load calculationud(load net of wind output). Wind speed measurement data is combined with the outputsudof atmospheric models to assess the availability of the GB wind resource and its relationshipudwith aggregate load.udSimulation results for 2010-40 suggest that the GB system may experience increased generationudadequacy risk during the mid to late the 2020s. In addition, many new investments are unable toudrecover their fixed costs. This triggered an investigation into the design of a capacity mechanismudwithin the context of the modelling environment. In light of the ongoing GB market electricityudmarket reform debate, two mechanisms are tested; a strategic reserve tender and a marketwideudcapacity market. The goal of these mechanisms is to mitigate generation adequacy riskudconcerns by achieving a target winter peak de-rated capacity margin.
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