基于碳交易的含风电系统低碳经济调度

Carbon Trading Based Low-Carbon Economic Dispatching for Power Grid Integrated With Wind Power System

随着"低碳经济"发展的持续升温,经济和社会的可持续发展对电力行业提出了低碳化发展的需求。风电作为最具竞争力的清洁能源之一,促进了电力低碳化的发展进程,同时风电出力的随机性对系统备用提出了更高的要求。建立低碳调度目标并引入碳交易,使碳排放成为赋有经济价值的可调度资源;在经济调度目标中引入旋转备用补偿成本以应对风电预测误差对系统带来的影响,引入风电场负效率运行补偿成本以弥补风电场技术弃风造成的经济损失。应用随机规划理论构建模型,提出了一种同时兼顾电能生产经济性和系统排放低碳性的新型低碳经济调度模型,实现多目标问题的单目标化。利用基于随机模拟的混合粒子群算法进行优化求解,通过算例验证所提模型与算法的合理性。

Along with the continued development of low-carbon economy, the sustainable development of both economy and society rises make a request for low-carbon development of electric power sector. As one of the most competitive clean energy, the wind power generation promotes the development course of low-carbon electricity, meanwhile a higher requirement on grid reserve capacity is drawn due to the randomness of wind power output. To make the carbon emission becoming schedulable resource with economic value, a low-carbon dispatching objective is established and in which the carbon trading is led; the compensation cost of spinning reserve is led into economic dispatching objective to cope with the influences caused by the prediction error of wind power generation, and the compensation cost for negative efficiency operation of wind farm is led in to make up the loss due to technical wind energy curtailment in wind farm. Using stochastic programming theory, a novel low-carbon economic dispatching model, in which the economy of electric energy production and low-carbon emission can be simultaneously considered, is proposed to transform the multi-objective problem into single-objective problem. The stochastic simulation based hybrid particle swarm optimization algorithm is applied to optimize and solve the proposed model. Results of numerical examples show that the proposed model and algorithm are reasonable.