Abstract
This chapter describes significant optimization problems such as economic dispatch (ED), unit commitment (UC), energy arbitrage, and energy system design. The solution of the ED problem using a real-coded genetic algorithm (GA) is explained and presented using four different systems reported in the technical literature. Concerning UC, the priority list method is used to initialize a binary-coded GA to enhance computational efficiency and solution quality. Other topics such as the relationship between the system size and the computational burden are discussed. Battery management under a real-time pricing environment is another problem analyzed in this chapter. To this end, an integer-coded GA is implemented to minimize the daily net cost. Rural electrification is also a subject in this chapter. An integer-coded GA is implemented to design a small-scale energy system. This chapter offers a variety of GA applications and structures.
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 callMore From: Genetic Optimization Techniques for Sizing and Management of Modern Power Systems
Disclaimer: 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.
