电力市场交易是影响我国未来电力体制改革走向的重要落地措施之一。通过对电力市场交易背景下水电站优化调度特点分析，构建了分时电价下水电站优化调度模型。在粒子群算法基础上，提出了改进惯性因子、加速因子以及迭代速度的改进策略，并将其运用于模型求解，以广东省梅州市青溪水电站为实例进行了研究，验证了模型和算法的有效性和适用性，该研究成果为电力市场背景下的水电站优化调度提供了新思路。

Electric power market transaction is one of the important measures for the reform of the electric power system in China. In this paper, the characteristics of the optimal reservoir scheduling in the electric power market transaction model were analyzed, and the optimal operation model of the reservoir was established. Based on the standard particle swarm optimization, the improved particle swarm optimization algorithm was proposed, which was based on the improvement of the inertia factor, the acceleration factor and the iteration speed. Taking Qingxi Reservoir, which locates in Meizhou City, Guangdong Province, as an example, the validity and applicability of the model and algorithm were verified. This research provides a new idea for reservoir optimization scheduling in the background of electric power market.

国家自然科学基金（51279047）；江苏省自然科学基金（BK20130849）；江苏省水利科技项目（2014064）