An enumerated probabilistic simulation technique and case study: Integrating wind power into utility production cost models
Production cost, generation expansion, and reliability models are used extensively by utilities in the planning process. However, many of these models do not provide adequate means for representing the full range of potential variation in wind power plants. In order to properly account for expected variation in wind-generated electricity in these models, we describe an enumerated probabilistic approach that can be performed outside the production cost model, compare it with a reduced enumerated approach, and present some selected utility results. Our technique can be applied to any model, and can result in a considerable reduction in model runs. We use both a load duration curve model and a chronological model to measure wind plant capacity credit, and also present some other selected results.
In this paper, we develop a dynamic programming algorithm for the scenario-tree-based stochastic uncapacitated lot-sizing problem with random lead times. Our algorithm runs in O(N^2) time, where N is the input size of the scenario tree, and improves the recently developed algorithm that runs in O(N^3) time.