This study presents The Smart Power Management Design bringing users preferences into available power sources depending on users comfort and priority in stand-alone renewable energy powered systems. The power management is planned as multi-agent structure being composed of load agents for each consumption unit, source agents for generation unit, and communication agent to make contact with load and source agents. Consumption and generation quantities required for power management are gathered from these agents having wireless communication. The developed smart power management algorithm gathers data from the agents. Users comfort criterion is composed of five levels starting from the most important to the least important for each load, and the users comfort priority is also specified while each load agent is introduced to the software designed for smart power management. The Fuzzy Logic Decision Maker embedded in the software enables certain loads to activate and deactivate together with the decision being made depending on the values of State of Charge (SOC) and consumption units. In this way, it is possible to enable critical load/loads having top priority to activate for a longer time in the cases in which weather becomes overcast for a long time with respect to the user. The top priority load in the model system represented in this study can be active 40% longer time in comparison with the conventional system, while the value of SOC is 42% and longcontinued overcast weather is available. If the value of SOC increases in the process, the postponed missions of the load/loads can be implemented without users follow-up. The designed agents were analyzed in terms of the measurement errors, and the effects of electromagnetic field generated by radio frequencies on human health were also examined. The result is satisfactory with respect to the measurement errors, and electromagnetic value is under the threshold proposed by the Information and Communications Technologies Authority and the International Commission on Non-Ionizing Radiation Protection. The study represents the negotiation process of Fuzzy Logic Decision Maker and main simulation-real results.
Key Words : Renewable Energy Sources, Photovoltaic, Agent, Multi Agent System (MAS), Power Management, Smart Power Management, Fuzzy Logic, Fuzzy Logic, Fuzzy Decision Makers , FDM, RF, Smart Grid, Smart Grid Home