Stochastic Simulation in Risk Analysis of Energy Trade
Successful trade in the newly deregulated European electricity market requires both maximising the net profits and maintaining an optimal portfolio of energy sales and purchase contracts. Energy is acquired from multiple multi-tariff contracts, thermal and hydro power plants, cogeneration facilities and the spot market. Minimisation of the procurement costs results in a time dependent resource allocation problem which can be solved efficiently using decomposition techniques. To maximise the net profits in trade, the feasibility and profitability of different types of contracts can be analysed using for instance marginal cost analysis and scenarios.
Taking into account the uncertainties involved in load forecasts, availability and prices of future short term contracts and the spot market, we obtain a stochastic multi-criteria programming problem. The decision maker (DM) not only wants to maximise the expected profits, but also to minimise the risks. We apply Monte Carlo simulation (MCS) for analysing the risks involved in energy trade. By using parametric analysis on the MCS model the DM can then explore the dependencies between the profits and risks and choose an acceptable risk level. The mathematical models and algorithms have been implemented as part of the commercial EHTO NEXUS software, which is used by several energy companies in Finland.
KeywordsMonte Carlo simulation risk analysis energy management energy market optimisation
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