含CSP及WTE的虚拟电厂低碳优化调度

The Low-Carbon Optimal Scheduling of the Virtual Power Plant with CSP and WTE

中文关键词:光热电站  垃圾焚烧电厂  蜉蝣优化K-means聚类  阶梯碳交易机制  改进水循环算法

keywords:concentrating solar power plant  waste to energy plant  mayfly-optimized K-means clustering algorithm  stepped carbon trading mechanism  improved water cycle algorithm

中文摘要:针对传统机组运行约束挤压风电并网空间及固体废弃物堆存量激增造成的环境污染问题，配置光热电站与电加热联合运行促进风电消纳，引入垃圾焚烧电厂与电转气联合运行实现CO2再利用，提出一种含光热电站（concentrating solar power plant，CSP）及垃圾焚烧电厂（waste to energy plant，WTE）的虚拟电厂低碳优化调度模型。基于非参数核密度估计和Frank-Copula 函数构建风电和光热电站出力联合分布模型，并利用蜉蝣优化K-means聚类算法得到典型场景；构建电加热与光热电站联合运行模型，并在垃圾焚烧-电转气精细化碳利用模型的基础上，引入阶梯碳交易机制进一步约束系统碳排放；以虚拟电厂总运行成本最低为目标，提出一种基于混合策略改进的水循环算法进行求解。仿真结果表明，所建立模型能够有效促进风电消纳并降低系统碳排放。

Abstract:Focusing on the problem that the traditional unit operation constraints squeeze the grid-connected space of wind power and the surge of solid waste storage causes environmental pollution， a low-carbon optimal scheduling model of the virtual power plant with CSP and WTE is proposed by configuring the combined operation of concentrating solar power plants and electric heaters to realize thermal electrolysis coupling to promote the consumption of wind power， and a combined operation of waste-to-energy plants （WTE） and power-to-gas is introduced to realize CO2 reuse. Firstly， based on nonparametric kernel density estimation and Frank-Copula function， a joint distribution model of the output of wind power and concentrating solar power plants is constructed， and typical scenes are obtained by using mayfly-optimized K-means clustering algorithm. Secondly， the combined operation model of electric heaters and concentrating solar power plants is constructed， and the stepped carbon trading mechanism is introduced to further restrict the carbon emission of the system on the basis of establishing the fine carbon utilization model of waste-to-energy plants and power to gas systems. Finally， a hybrid strategy-based water cycle algorithm is proposed to solve the objective of minimizing the total operating cost of the virtual power plant. The results show that the established model can effectively promote wind power consumption and reduce carbon emissions of the system.