Decision making under uncertainty in energy systems: state of the art
By Alireza Soroudi, Turaj Amraee. arXiv.org, 2013
405 citations recorded by the source corpus.
The energy system studies include a wide range of issues from short term (e.g. real-time, hourly, daily and weekly operating decisions) to long term horizons (e.g. planning or policy making). The decision making chain is fed by input parameters which are usually subject to uncertainties. The art of dealing with uncertainties has been developed in various directions and has recently become a focal point of interest. In this paper, a new standard classification of uncertainty modeling techniques for decision making process is proposed. These methods are introduced and compared along with demonstrating their strengths and weaknesses. The promising lines of future researches are explored in the shadow of a comprehensive overview of the past and present applications. The possibility of using the novel concept of Z-numbers is introduced for the first time.
Subfields: Electrical and Electronic Engineering
View Paper: https://www.semanticscholar.org/paper/52b371f92cfd41e0695f1b1abc6e281ee29c8fe5
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Electrical and Electronic Engineering
- Behnam Mohammadi-Ivatloo
- A. Knight
- Soroush Shafiee
- H. Zareipour
- Nima Amjady
- Rafal Weron
- Mohamed A. El-Sharkawi
- Eric Sortomme
Citations in the corpus
- Risk-Constrained Bidding and Offering Strategy for a Merchant Compressed Air Energy Storage Plant (2017, methodology): “Compared to probabilistic methods where the computational burden could sometimes be problematic [37], [38], the IGDT method can handle high uncertainty levels with lower computational burden.”