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This paper presents a technique to derive the best offering strategy for a wind power producer in an electricity market that includes various trading floors. Uncertainty pertaining to wind availability, market prices at the different trading stages, and balancing energy needs are properly taken into account. Risk on profit variability is suitably controlled at the cost of a small reduction in expected profit. The proposed technique translates into a linear programming problem of moderate size, which is readily solvable using commercially available software. A variety of numerical case studies demonstrate the interest and effectiveness of the proposed technique. Appropriate conclusions are duly drawn.

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This paper proposes a probabilistic power flow model that takes into account spatially correlated power sources and loads. It is particularly appropriate to assess the impact of intermittent generators, such as wind power ones, on a power network. The proposed model is solved using an extended point estimate method that accounts for dependencies among the input random variables, i.e., loads and power sources.The proposed probabilistic power flow model is illustrated through a 24-bus case study. Finally, conclusions are duly drawn.

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