Contribution for bidding of wind-photovoltaic on grid farms based on NBI-EFA-SNR method

Abstract Methods for supporting the bidding processes of hybrid wind-photovoltaic (W-PV) farms are scarce, especially when numerous goals are included in the optimization problem. Therefore, the primary objective of this study is to develop a novel model that can help bidding of W-PV farms considering a range of objectives that maximize the environmental and welfare benefits. This new approach contributes to energy planning for any type of hybrid farm through multi-objective programming, even in cases where the optimization of several correlated outputs is desired. Using the proposed approach the optimal system configuration can be obtained in these cases with low computational costs. A non-linear multi-objective optimization (NL-MO) is proposed to optimize the area occupied by the W-PV farm, minimum feasibility price, electricity production expected, and standard-deviation of the electricity produced. The model has been elaborated from non-linear optimization using the normal-boundary intersection (NBI) method, exploratory factor analysis (EFA), and Taguchi signal-to-noise ratio (SNR). The optimal values for the response variables are an area of 132.92 km2, minimum price of 182.95 R$/MWh, annual electricity production of 72.17 GWh, with a standard deviation of 1.74 GWh and the ideal share is 41% wind power and 59% PV power.

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