Abstract
AbstractThis paper addresses the problem of generation planning in the competitive power market with uncertainty of demand growth. The distributed generator (DG) is given attention against a large‐scale generator to correspond to uncertain demand growth. Optimization consists of minimizing the average cost and hedging risk over the scenario trees of demand growth. At first, based on the idea of a Real Option, Dynamic Programming using the utility function is applied to generation planning. Utility functions can model investor's risk‐return profile. The decisions in the first stage indicate that they are influenced by the type of utility functions and demand growth scenarios, and data of generators. Next, a Monte Carlo simulation is applied to a Brownian motion model of demand growth. This model can increase the possible number of demand levels. With this simulation, the case that the distributed generator has an advantage over the large‐scale generator is quantitatively discussed. © 2003 Wiley Periodicals, Inc. Electr Eng Jpn, 146(3): 17–25, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/eej.10276
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
