The National Academy of Engineering has selected the US Electric Power Grid as the supreme engineering achievement of the 20th century. Yet, this same grid is struggling to keep up with the increasing demand for electricity, its quality and cost. A growing recognition of the need to modernize the grid to meet future challenges has found articulation in the vision of a Smart Grid in using new control strategies that are intelligent, distributed, and adaptive. The objective of this work is to develop smart control systems inspired from the biological Human Immune System to better manage the power grid at the both generation and distribution levels. The work is divided into three main sections. In the first section, we addressed the problem of Automatic Generation Control design. The Clonal Selection theory is successfully applied as an optimization technique to obtain decentralized control gains that minimize a performance index based on Area Control Errors. Then the Immune Network theory is used to design adaptive controllers in order to diminish the excess maneuvering of the units and help the control areas comply with the North American Electric Reliability Corporation\u27s standards set to insure good quality of service and equitable mutual assistance by the interconnected energy balancing areas. The second section of this work addresses the design and deployment of Multi Agent Systems on both terrestrial and shipboard power systems self-healing using a novel approach based on the Immune Multi-Agent System (IMAS). The Immune System is viewed as a highly organized and distributed Multi-Cell System that strives to heal the body by working together and communicating to get rid of the pathogens. In this work both simulation and hardware design and deployment of the MAS are addressed. The third section of this work consists in developing a small scale smart circuit by modifying and upgrading the existing Analog Power Simulator to demonstrate the effectiveness of the developed technologies. We showed how to develop smart Agents hardware along with a wireless communication platform and the electronic switches. After putting together the different designed pieces, the resulting Multi Agent System is integrated into the Power Simulator Hardware. The multi Agent System developed is tested for fault isolation, reconfiguration, and restoration problems by simulating a permanent three phase fault on one of the feeder lines. The experimental results show that the Multi Agent System hardware developed performed effectively and in a timely manner which confirms that this technology is very promising and a very good candidate for Smart Grid control applications