Investing in Wind Energy Using Bi-Level Linear Fractional Programming

Adel F. Alrasheedi, Ahmad M. Alshamrani and Khalid A. Alnowibet ()
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Adel F. Alrasheedi: Statistics and Operations Research Department, College of Science, King Saud University, Riyadh 11451, Saudi Arabia
Ahmad M. Alshamrani: Statistics and Operations Research Department, College of Science, King Saud University, Riyadh 11451, Saudi Arabia
Khalid A. Alnowibet: Statistics and Operations Research Department, College of Science, King Saud University, Riyadh 11451, Saudi Arabia

Energies, 2023, vol. 16, issue 13, 1-14

Abstract: Investing in wind energy is a tool to reduce greenhouse gas emissions without negatively impacting the environment to accelerate progress towards global net zero. The objective of this study is to present a methodology for efficiently solving the wind energy investment problem, which aims to identify an optimal wind farm placement and capacity based on fractional programming (FP). This study adopts a bi-level approach whereby a private price-taker investor seeks to maximize its profit at the upper level. Given the optimal placement and capacity of the wind farm, the lower level aims to optimize a fractional objective function defined as the ratio of total generation cost to total wind power output. To solve this problem, the Charnes-Cooper transformation is applied to reformulate the initial bi-level problem with a fractional objective function in the lower-level problem as a bi-level problem with a fractional objective function in the upper-level problem. Afterward, using the primal-dual formulation, a single-level linear FP model is created, which can be solved via a sequence of mixed-integer linear programming (MILP). The presented technique is implemented on the IEEE 118-bus power system, where the results show the model can achieve the best performance in terms of wind power output.

Keywords: bi-level optimization; fractional programming; primal-dual formulation; stochastic programming; wind energy investment (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
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