利用电化学储能追踪风电预测曲线的风储联合调度经济性分析

Economic Analysis of Wind Storage Joint Scheduling Using Battery Energy Storage to Track Wind Power Prediction Curve

针对风电场上报给调度中心的超短期功率误差较为严重,给风电大规模并网带来了巨大阻碍,严重影响风电竞争力的问题,提出利用储能系统追踪风电功率预测曲线的风储联合出力模型。首先通过长短期神经网络进行风电功率超短期预测;然后通过风储联合出力,同时考虑储能系统全寿命周期建设成本以及引入储能系统后风电场上报预测曲线误差惩罚成本的经济性影响;最终确定风储联合调度计划。在吉林省某风电场实测数据的基础上,对比不同追踪模式下的风储电场经济成本和风电利用率。仿真结果表明,运用所提风储联合发电模型发电度电成本为0.2316元/kWh,相对于无储能模式降低22.67%,同时风电利用率提高17.48%,均方根误差降低0.07,平均绝对误差降低0.08,说明所提策略可以在保证风储电站的经济性的同时有效减少风电并网功率误差,提高风电利用率。

When the ultra-short term power error reported by wind farms to the dispatching center is relatively serious,a huge obstacle is brought to large-scale grid connection of wind power and the competitiveness of wind power is seriously affected.A wind storage combined output model is proposed that uses the energy storage system to track the wind power prediction curve.Firstly,the ultra-short term prediction of wind power is carried out through long and short term neural network.Furthermore,the economic impact of the construction cost of the whole life cycle of the energy storage system and the penalty cost of the error of the forecast curve reported by the wind farm after the introduction of the energy storage system is considered through the combined output of wind and energy storage.Finally,the wind storage joint dispatching plan is determined.Based on the measured data of a wind farm in Jilin Province,this paper compares the economic cost and wind power utilization of wind storage farms under different tracking modes.The simulation results show that the power generation cost of the wind storage joint generation model proposed in this paper is 0.2316 yuan/kWh,which is 22.67%lower than that of the non-storage mode.At the same time,the wind power utilization rate is increased by 17.48%.The root mean square error is reduced by 0.07 and the mean absolute error is reduced by 0.08.The results show that the strategy proposed can effectively reduce the wind power grid-connected power error and improve the wind power utilization rate while ensuring the economy of the wind storage power station.