Real-time generation market has to complete the bidding and clearing in short time. It is more urgent in time, more fluctuating in price and more likely to be affected by participants’ behavior. In the trading process, if the market clears merely according to the total purchasing cost, it may result in a minority of participants seize most of the market share or residual capacity where the market is highly concentrated. A few units can gain abnormal return through market manipulation and market efficiency and stability will be reduced. To avoid the above situation, this paper proposes a multi-objective model for the real-time generation market considering market concentration, limits the market concentration into appropriate level through monitoring the HHI static index and the DHHI dynamic index. When solving the model, the improved multi-objective generation algorithm (MOGA) achieves the quick convergence and finite schemes choosing. At last, the IEEE standard system of 30 nodes is applied to the simulation. Simulation result confirms the model’s availability and the algorithm’s efficiency. This work is supported by National Natural Science Foundation of China (No.61472136).