摘要
随着新型电力系统建设不断推进,以风光为代表的可再生能源装机容量进一步增加,源荷双侧的随机性和不确定性为电力系统运行带来极大的挑战。为此,提出一种基于多能源荷预测的区域电热系统储能优化调度方法,利用多能储能灵活调节能力及系统电热耦合特性提高光伏消纳水平。首先,运用改进极限学习机模型和K-means聚类算法对光伏出力及电热负荷进行预测。然后,引入条件风险价值量化光伏出力不确定性对运行成本的影响,以运行成本和条件风险价值加权之和最小为目标,建立含蓄电池、飞轮储能及蓄热罐的区域电热系统优化运行调度模型,通过多能储能响应电热系统灵活运行调节需求。最后,通过算例分析表明了所提方法的有效性。
With the continuous development of the new power system construction,the installed capacity of wind power,photovoltaic and other renewable energies has been further increased.The randomness and uncertainty of source and load bring great challenges to the operation of the power system.Therefore,an optimal dispatch method of energy storage in regional electricity-thermal system based on multi-energy source and load forecasting,which im⁃proves the accommodation level of photovoltaic by the flexible adjustment ability of multi-energy storage and electricity-thermal coupling characteristics of the system.Firstly,the photovoltaic output and electricity-thermal load are forecasted based on the improved extreme learning machine and K-means clustering algorithm.Then,the conditional value at risk is applied to quantize the impact of uncertainty of photovoltaic output on operation cost.With target of minimizing the weighting sum of operation cost and conditional value at risk,the optimized operation scheduling model of district electricity-thermal system,containing battery,flywheel energy storage and heat storage tank,is established.The regulation requirement for flexible operation of the electricity-thermal system can be achieved by multi-energy storage.Finally,the case study is conducted to demonstrate the effectiveness of the pro⁃posed method.
作者
许烽
陶远超
陆翌
裘鹏
李心宇
孙浩
覃洪培
XU Feng;TAO Yuanchao;LU Yi;QIU Peng;LI Xinyu;SUN Hao;QIN Hongpei(State Grid Zhejiang Electric Power Co.,Ltd.Research Institute,Hangzhou 310014,China;College of Electrical Engineering,Zhejiang University,Hangzhou 310027,China)
出处
《浙江电力》
2023年第9期17-26,共10页
Zhejiang Electric Power
基金
国网浙江省电力有限公司科技项目(5211DS200083)。
关键词
源荷预测
多能储能
电热系统
优化调度
条件风险价值
source and load forecasting
multi-energy storage
electricity-thermal system
optimal dispatch
condi⁃tional value at risk
