The intelligent agent-based simulation has become a novel and powerful tool in the study of electricity market. This paper deals with the construction of a simulation system of electricity market. In the investigation, first, the intelligent-agent learning algorithms suitable for simulating the strategic bidding of electricity firms are in- troduced. Next, the applications of the VRE-learning algorithm, the Q-learning algorithm and the greedy algorithm to the simulation system are illustrated, and the corresponding implementation frameworks are proposed. Then, the techniques for the learning algotrithms to handle the convergence of agent bidding are discussed. Finally, an exam- ple is performed to test the effectiveness of the intelligent agent-based simulation. The results indicate that the intel- ligent-agent learning algorithms are capable of simulating the rational bidding behavior of electricity firms.