Energy consumption is one of the most important aspects in wireless communications where networks and nodes exchange transmission and reception parameters, that ultimately results in changes in consumption parameters. This is specifically related to the offer and demand profiles seen in the electric supply chain. Said changes are proportional to the number of channels and users that interact in the radio-electric spectrum. Therefore, the present article examines energy-efficient cognitive radio techniques and the optimization of wireless networks fed by non-conventional energy sources. Seeing green energies as an important resource in the future, the performance of the network strongly depends on the spectrum dynamics and the energy available. In contrast with traditional energy sources, the rate of arrival of green energies is dependent on the recollection systems and is marked by randomness and intermittence. To optimize and adapt the use of energy according to the availability of the opportunistic spectrum, the main challenges faced in the design of cognitive radio networks that operate under different storage sources whose applicability is analog to the distributed energy resources.