基于改进多目标遗传算法的实时发电市场优化调度研究

发布时间：2018-08-21 19:48

【摘要】：实时发电市场需在短时间内完成投标与出清,与中长期市场相比时间更紧、价格波动更明显且更容易受到参与者行为的影响。在交易过程中,若单纯采用总购电成本最低进行出清,可能导致少量参与者占有大部分市场份额或剩余资源,造成市场集中度偏大。少量机组可利用其市场力操纵市场并获得超额回报,从而影响市场效率及稳定性。为了防止该类情形,提出一种兼顾市场集中度的实时发电市场多目标优化模型,通过监控HHI静态指标以及DHHI动态指标将市场集中度控制在合理水平。在模型求解过程中,通过改进的多目标遗传算法(Multi-objective Generic Algorithm,MOGA)实现了快速收敛及有限方案筛选。最后采用IEEE30节点标准系统进行仿真,仿真结果证实了模型的有效性及其算法的高效性。
[Abstract]:The real-time power generation market needs to complete the bidding and clearing in a short time. Compared with the medium and long term market, the time is more tight, the price fluctuation is more obvious and more vulnerable to the impact of participants' behavior. In the course of transaction, if only the lowest total purchase cost is used for clearing, it may lead to a small number of participants occupying most of the market share or remaining resources, resulting in a large degree of market concentration. A small number of units can use their market power to manipulate the market and obtain excess returns, thus affecting market efficiency and stability. In order to prevent this kind of situation, a multi-objective optimization model of real-time power generation market considering market concentration is proposed. The market concentration is controlled at a reasonable level by monitoring HHI static index and DHHI dynamic index. In the process of solving the model, the fast convergence and finite scheme selection are realized by the improved Multi-objective Generic algorithm (MOGA). Finally, the IEEE30 node standard system is used to simulate the model. The simulation results show the validity of the model and the high efficiency of the algorithm.
【作者单位】：国网四川省电力公司技能培训中心;南瑞集团公司(国网电力科学研究院);湖南商学院;
【基金】：国家自然科学基金(61472136) 湖南省自然科学基金项目(2016JJ2069) 湖南省教育厅优秀青年基金(16B143)~~
【分类号】：F426.61;TP18

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