Profit based unit commitment problem (PBUC) from power system domain is a high-dimensional, mixed variables and complex problem due to its combinatorial nature. Many optimization techniques for solving PBUC exist in the literature. However, they are either parameter sensitive or computationally expensive. The quality of PBUC solution is important for a power generating company (GENCO) because this solution would be the basis for a good bidding strategy in the competitive deregulated power market. In this paper, the thermal generators of a GENCO is modeled as a system of intelligent agents in order to generate the best profit solution. A modeling for multi-agents is done by decomposing PBUC problem so that the profit maximization can be distributed among the agents. Six communication and negotiation stages are developed for agents that can explore the possibilities of profit maximization while respecting PBUC problem constraints. The proposed multi-agent modeling is tested for different systems having 10–100 thermal generators considering a day ahead scheduling. The results demonstrate the superiority of proposed multi-agent modeling for PBUC over the benchmark optimization techniques for generating the best profit solutions in substantially smaller computation time. profit of GENCO profit of GENCO in iteration ‘it’ revenue of GENCO total operation cost of GENCO profit generated by generator i at hour t power generation of generator i at hour t reserve generation of generator i at hour t ON/OFF status of generator i at hour t forecast demand at hour t forecast reserve at hour t demand left at hour t reserve left at hour t minimum generation limit of generator i maximum generation limit of generator i number of generator units number of hours forecast spot prices at hour t forecast reserve prices at hour t start-up cost of generator i probability that reserve is called and generated minimum up/down time of generator i duration during which unit i is continuously ON/OFF cost coefficients of generator i 
Multi-agent modeling for solving profit based unit commitment problem