Optimal management of wind and solar energy resources Articles uri icon

authors

publication date

  • February 2016

start page

  • 284

end page

  • 291

volume

  • 66

International Standard Serial Number (ISSN)

  • 0305-0548

Electronic International Standard Serial Number (EISSN)

  • 1873-765X

abstract

  • This paper presents a portfolio-based approach to the harvesting of renewable energy (RE) resources. Our examined problem setting considers the possibility of distributing the total available capacity across an array of heterogeneous RE generation technologies (wind and solar power production units) being dispersed over a large geographical area. We formulate the capacity allocation process as a bi-objective optimization problem, in which the decision maker seeks to increase the mean productivity of the entire array while having control on the variability of the aggregate energy supply. Using large-scale optimization techniques, we are able to calculate - to an arbitrary degree of accuracy - the complete set of Pareto-optimal configurations of power plants, which attain the maximum possible energy delivery for a given level of power supply risk. Experimental results from a reference geographical region show that wind and solar resources are largely complementary. We demonstrate how this feature could help energy policy makers to improve the overall reliability of future RE generation in a properly designed risk management framework.

keywords

  • renewable energy harvesting; energy supply risk management; multi-criteria mathematical programming; pareto-optimal set; markowitz's portfolio theory; numerical weather prediction; portfolio selection; baseload power; optimization; variability; plants; farms