Abstract
Electricity has become a key to modern society. The selection of multiple technologies to satisfy our energy needs is unavoidable where thorough planning necessitates the inclusion of conventional, renewable and nuclear generation sources in an integrated manner considering public policies and regulations, the availability of resources, and technological developments. In this study, we propose a hybrid modular simulation based decision making framework for the capacity planning problem of nuclear generation resources while considering the aspects of the reverse logistics chain of nuclear energy, nuclear fuel reprocessing, storage, and disposal. The proposed integrated framework also takes into account the electricity generated by conventional and renewable sources that are currently in place. The proposed framework is composed of a hybrid modular simulation to evaluate the performance of a specific capacity plan in terms of costs, emissions and nuclear waste and a particle filtering based optimization that estimates the state of the distributed electricity network and proposes candidate scenarios for the simulation. The framework has been successfully demonstrated for the capacity planning of nuclear energy generation in Florida. [PUBLICATION ABSTRACT]