一种电力市场环境下的电源规划多智能体模型

电源规划一直是电力系统中重要问题之一。在电力市场环境下，这一问题更加复杂、迫切。针对这一问题，基于多智能体技术，提出了电力市场环境下发电集团电源投资规划模型。首先，构建了一个电力市场发电侧的双层优化架构，以实现市场竞价问题与电源规划问题相结合。其次，设计了发电集团、发电市场以及发电厂等智能体，并引入遗传算法、Q-learning算法完善各智能体寻优能力。通过算例验证了所建立的模型是可行的、有效的，可为电站建设决策部门提供有价值的参考。

A multi-agent model of generation expansion planning in electricity market

The generation expansion planning is an important problem in electric system, especially complex and urgent in the background of electric market. To this issue, this paper proposes a generation investment planning model for power companies, which is based on mutli-agent technology. Firstly, a double-layer optimization construction for the generation-side in electric market is developed in order to combine the price competition with generation expansion planning. Secondly, multiple agents such as generation groups, generation market and generation plants are designed with genetic algorithm and Q-learning algorithm applied to improve their optimization ability. The result presents that the model is feasible and effective and could provide support for decision making to plant expansion planning. This work is supported by National Natural Science Foundation of China (No. 61273144 and No. 61533013).