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Incorporating a Multi-Criteria Decision Procedure into the Combined Dynamic Programming/Production Simulation Algorithm for Generation Expansion Planning

A multi-objective optimization approach to utility generation expansion planning (GEP) is proposed. The approach is designed by adding a new multi-criteria decision (MCD) procedure to the conventional algorithm [1, 2] of Dynamic Programming (DP) combined with production simulation (DP/ production-simulation) using Cumulant method [3]. Section I of this paper gives a brief review of the presently existing multi-objective optimization approaches to GEP, showing that all these approaches use rough reserve margin and over-simplified merit-order techniques to calculate system reliability and estimate power production. In contrast, our approach using Cumulant method can simulate system production probabilistically. Section II presents our model formulation and derives the DP forward recursive formula for this model. Three MCD problems embedded within the model are identified: one decides the production order of system generating units for each DP state before production simulation; the other two select the near-best compromise state transition path for the GEP problem. Section III presents the proposed MCD procedure which combining a specially designed questionnaire, the Eigenvector method [4], and the Technique for Order Preference by Similarity to Ideal Solution [5], can help DM's distinguish the relative importance of multiple attributes associated with decisions of these three MCD problems, and thereby find their near-best compromise solutions. The new approach has been practically applied to a GEP study conducted within a project for feasibility evaluation of the fourth nuclear power plant of Taiwan, comprising the system's seventh and eighth nuclear units.