An evolutionary computation approach to electricity trade negotiation

This paper presents an evolutionary negotiation process for power generating and power consuming companies in a distributed electricity market environment. The process is implemented within an electricity agent to best select a negotiation strategy that meets the underlying company objectives and interests. The negotiating agent generates a sequence of improving strategy population as the outcome of a search method modeled by the selection, crossover, and mutation genetic operators. Agents use a content specification language based on an extended object model to specify the requirements, constraints, and negotiation strategic rules, which are used by the negotiation server to conduct a negotiation. A design architecture and a framework for negotiation is presented with detailed KQML communication primitives that make up the negotiation protocol. Various software technologies have been used for implementation and tested in a C++ environment.