李佳瑶,刘伟娜
LI Jiayao,LIU Weina

• 1:北方工业大学电气与控制工程学院

摘要(Abstract)：

随着电力系统低碳经济不断发展,碳交易的引入和风电并网促进了电力低碳化发展,为此,建立了考虑碳交易和风荷预测误差的电力系统低碳经济调度模型。首先,在经济目标函数中引入碳交易成本,构建了根据碳排放量计算碳交易成本的阶梯型模型,通过碳排放权裕度控制碳交易成本。其次,建立了风电和负荷预测误差模型,采用高斯混合模型拟合风电功率预测误差的概率密度分布,通过含有机会约束规划理论的旋转备用约束处理风电和负荷预测误差的不确定性,采用混合粒子群算法对模型进行求解。最后,通过对比3种调度模型的计算结果,验证了模型的有效性。
With the development of low-carbon economy in power system, the introduction of carbon trading and wind power integration into power grid promote the low-carbon development of power system. Therefore,a low-carbon economic dispatching(LCED) model of power system considering carbon trading and wind power and load forecast errors was established. Firstly, the carbon trading cost was introduced into the economic objective function to construct a ladder-type calculation model for carbon trading according to carbon emissions, and carbon trading cost was controlled by carbon emission margin. Secondly, a model of wind power and load forecast error was established, and Gaussian mixture model was employed to fit the probability density distribution of the output power forecast errors. The uncertainty of wind power and load forecasting error was handled by spinning reserve constraints with chance-constrained programming. A hybrid particle swarm optimization(HPSO) algorithm was proposed to solve the model. Finally, the validity of the proposed model is verified by comparing the calculation results of the three dispatch models.

关键词(KeyWords)： 碳交易;风荷预测误差;高斯混合模型;机会约束规划理论;混合粒子群算法
carbon trading;wind power and load forecast error;Gaussian mixture model;chance-constrained programming;HPSO

Abstract:

Keywords:

基金项目(Foundation): 北京市教委项目（110052972027/067）

作者(Author): 李佳瑶,刘伟娜
LI Jiayao,LIU Weina

DOI: 10.19585/j.zjdl.202105001

参考文献(References)：

• [1]张敏思，张昕.对《全国碳排放权交易市场建设方案（发电行业）》的分析[J].中国经贸导刊，2018(6):71-72.
• [2]赵书强，王扬，徐岩.基于风电预测误差随机性的火储联合相关机会规划调度[J].中国电机工程学报，2014,34（增刊1）:9-16.
• [3]CASTRONUOVO E D,LOPES J A P.On the optimization of the daily operation of a wind-hydro power plant[J].IEEE Transactions on Power Systems,2004,19(3):1599-1606.
• [4]DOHERTY R,MALLEY M O.A new approach to quantify reserve demand in systems with significant installed wind capacity[J].IEEE Transactions on Power Systems,2005,20(2):587-595.
• [5]杨宏，苑津莎，张铁峰.一种基于Beta分布的风电功率预测误差最小概率区间的模型和算法[J].中国电机工程学报，2015,35(9):2135-2142.
• [6]王成福，王昭卿，孙宏斌，等.考虑预测误差时序分布特性的含风电机组组合模型[J].中国电机工程学报，2016,36(15):4081-4090.
• [7]叶林，张亚丽，巨云涛，等.用于含风电场的电力系统概率潮流计算的高斯混合模型[J].中国电机工程学报，2017,37(15):4379-4387.
• [8]张程飞，袁越，张新松，等.考虑碳排放配额影响的含风电系统日前调度计划模型[J].电网技术，2014,38(8):2114-2120.
• [9]张晓辉，闫柯柯，卢志刚，等.基于场景概率的含风电系统多目标低碳经济调度[J].电网技术，2014,38(7):1835-1841.
• [10]张刚，张峰，张利，等.考虑碳排放交易的日前调度双阶段鲁棒优化模型[J].中国电机工程学报，2018,38(18):5490-5499.
• [11]马燕峰，范振亚，刘伟东，等.考虑碳权交易和风荷预测误差随机性的环境经济调度[J].电网技术，2016,40(2):412-418.
• [12]张晓辉，刘小琰，钟嘉庆.考虑奖惩阶梯型碳交易和电-热转移负荷不确定性的综合能源系统规划[J].中国电机工程学报，2020,40(19):6132-6142.
• [13]秦婷，刘怀东，王锦桥，等.基于碳交易的电-热-气综合能源系统低碳经济调度[J].电力系统自动化，2018,42(14):8-13.
• [14]卢志刚，郭凯，闫桂红，等.考虑需求响应虚拟机组和碳交易的含风电电力系统优化调度[J].电力系统自动化，2017,41(15):58-65.
• [15]Elia.电网风电数据[EB/OL].(2018-09-01)[2021-01-05].http://www.elia.be/en/grid-data/．
• [16]盛四清，李亮亮，刘梦.考虑多重不确定因素的含风电场低碳经济调度[J].现代电力，2016,33(2):77-83.
• [17]易明月，童晓阳.考虑风荷预测误差不确定性的动态经济调度[J].电网技术，2019,43(11):4050-4057.