Abstract
A community integrated energy system can play a key role in alleviating urban energy shortages and environmental degradation, but the presence of multiple participants and links makes the operation of such a system more complicated. How to choose the optimal energy use strategy among different decision makers is a problem that urgently needs to be solved today. Therefore, first, this paper proposes a comprehensive energy multi-objective scheduling model based on the established smart community energy management framework, which considers the utility of decision makers. From the perspective of risk, the model divides decision makers into adventurous, intermediate and conservative types in order to study the impacts of different decision makers on energy use strategies. Second, to prevent the phenomenon of the solution of the intelligent algorithm falling into the local optimum, this paper innovatively uses the Lévy flight to optimize the learning step length of the chicken swarm algorithm to quickly solve the proposed mixed integer nonlinear programming model. Finally, the model is tested through multi-scenario simulation. The results show that decision makers have an important influence on energy use strategies, and different decision makers have different energy use strategies when utility is maximized. In addition, compared with the chicken swarm algorithm, the improved algorithm increases the utility of adventurous, intermediate and conservative decision makers in type-I cases by 0.54 %, 1.2 %, and 1.5 %, respectively; and in type-II cases by 4.5 %, 4.8 %, and 3.6 %, respectively.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
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.