a poor load growth may reflect a poor economic scenario â which may be ..... [8] D.S. Kirschen, G. Strbac, Fundamentals of Power System Economics,. Wiley ...
> Powertech 2007 Paper 504
Powertech 2007 Paper 504
Powertech 2007 Paper 504
Powertech 2007 Paper 504 < Finally, Figure 4 presents the total contracted volumes against marginal prices and expected total load. Reflecting this agent’s conservative requirements, the total contracts are mostly above the expected load, absorbing possible scenario variations. The only exposure moments correspond to significant price reductions, where it was, without any doubt, more attractive to buy in the spot than to use reserve.
4 The overall mathematical formulation for the optimal portfolio mixes different variables: the independent (“hereand-now”) contract decisions and the consequences of those decisions (“wait-and-see”) energy deficits or surplus. The introduction of risk management variables makes the complete portfolio building a mixed-integer stochastic programming problem, solved by a customized algorithm able to yield the desired solution within minutes in an ordinary microcomputer. Finally, a real trader’s case study illustrates the application of the proposed approach and associated potentiality. REFERENCES
Figure 4 – Optimum Portfolio, Total Load and Short-term costs
VI. COMPUTATIONAL ASPECTS The overall model is implemented into a customized algorithm, able to accommodate all required scenarios and time steps. The presented case study leads to a roughly 8000 constraints mixed integer model solved in less than four minutes in an ordinary microcomputer. VII. CONCLUSIONS Although a popular investigation theme [7-12], optimal trading in energy markets is still a challenge. This work aims to offer an innovative approach target for young, evolutionary markets, where uncertainties are a tough challenge. The paper presents an integrated model for the construction of a portfolio of energy contracts under uncertainties, corresponding to the minimization of the contract costs plus spot-market clearances and penalties. It was shown that these uncertainties are not probabilistic; therefore, a realistic solution requires the use of specialized algorithms based on a wide range of models based on different techniques – climatological propagation, functional analysis, fuzzy sets.
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