A distributed multi-agent linear biobjective algorithm for energy flow optimization in microgrids

A distributed linear bi-objective optimization algorithm for management of energy flow in a microgrid with individual agents is introduced. In contrast to widely used centralized approaches for energy management a distributed multi-agent scheme for optimization of energy flow within a microgrid consisting of local energy resources and storage capacities is presented which is based on the auction algorithm for assignment problems originally introduced by Bertsekas in 1979 [1]. It is shown that the topology of a microgrid can be represented as a bipartite graph and mathematically be described as a classical transportation problem. This allows applying an auction algorithm scheme in a distributed way where each energy supply system node is either a source or a sink and is represented by an individual acting agent. The single-objective approach is extended towards bi-objectivity to build a framework which gives each agent freedom and authority to intelligently influence the global decision making (optimization) with respect to its own individual objectives and therefore a distributed bi-objective optimization for the energy flow in the microgrid with individual agent objectives is achieved. In the introduced framework computational intelligent agents enhance the intelligence of the global decision making based on their individual agents intelligence.