Economic planning of wind farms from a NBI-RSM-DEA multiobjective programming

Abstract

One of the challenges of energy regulatory-agencies is to guide the agents decision-making process towards maximization of the overall welfare of the electricity sector. However, this is not a simple task since it requires meeting expectations of many stakeholders, from investors to consumers. This paper proposes an optimization methodology aimed at helping define the optimal combination of wind farm layout and type of equipment deployed, so that the electricity sector overall welfare is maximized in the process. The optimization objectives are (i) the energy density and (ii) the Net Present Value (NPV), and the parameters are (a) the power levels and (b) the selling price of the energy. The objective functions are modelled with the aid of a design-of-experiment technique known as Response Surface Methodology, relying on the multi-objective programming method of Normal Boundary Intersection for the optimization. The methodology is applied to four different scenarios arising from the combination of two different locations (Santa Vitória do Palmar-RS and Macau-RN, both in Brazil), and two different wind turbine manufacturers (A and B). The final step comprises the application of the Data Envelopment Analysis technique in order to sort one from the set of optimal solutions identified by the four different scenarios. The results show that the proposed methodology is capable of supporting bidding processes and wind farms certification programs, in line with what should be expected by regulatory agencies, investors and electricity consumers alike. The deployment of the methodology proved discriminant and allowed selection of one final scenario (Macau-RN, brand A equipment) as overall optimal. It was also observed that equipment efficiency is dependent on siting location. © 2020 Elsevier Ltd