Dynamic and scenario based elicitation of genetic algorithms of agents for control of distributed power system networks and renewable energy resources

The paper proposes an agent system for distributed generation setup identifying role and requirements of each agent. Genetic algorithms, due to their applicability for optimization solutions of nonlinear and stochastic scenarios, can find place in development of agents for distributed control. Advantages and special features of genetic algorithms for optimization are discussed, identifying some input and output variables. Requirement of compensator as an agent/sub-agent is also proposed. The use case model is proposed showing assigned role of each agent. Each use case has been elaborated with its purpose, data handling, stimuli and responses. A lay out of the sub-systems of each of the proposed main agents has also been included. Finally, the state machine model is proposed showing behaviour of system in real time scenarios.