双向可逆的集中式电氢耦合系统容量优化配置

Capacity Optimization Configuration of a Bidirectional Reversible Centralized Electrohydrogen Coupling System

针对风光富集地区大型新能源发电厂的弃风弃光问题,利用可逆固体氧化物燃料电池(reversible solid oxide fuel cell,RSOC)结合氢储能的双向转换特性消纳多余风光资源,提出一种双向可逆的集中式RSOC电氢耦合系统容量优化配置方法。首先构建集中式RSOC电氢耦合系统架构,建立发电系统、电氢转换系统等模型;其次考虑燃料电池特性建立RSOC性能衰减模型,考虑特高压通道可用传输能力不确定性生成典型场景;进而建立集中式RSOC双层容量规划模型,上层以运营期收益最大为目标优化RSOC、储氢库容量配置,下层以综合成本最低为目标优化各设备出力,联合粒子群算法与Cplex求解器进行求解。最后通过算例分析,验证RSOC的加入提高了系统经济性及环境效益,同时投资灵敏度分析表明电池单位容量成本是制约系统经济运行的重要因素。

In response to the problem of wind and light abandonment in large-scale new energy power plants in areas with abundant wind and solar energy,a bidirectional reversible centralized RSOC electric hydrogen coupling system capacity optimization configuration method is proposed by utilizing the reversible solid oxide fuel cell(RSOC)combined with the bidirectional conversion characteristics of hydrogen energy storage to absorb excess wind and solar resources.Firstly,construct a centralized RSOC electric hydrogen coupling system architecture,and establish models for power generation systems,electric hydrogen conversion systems,etc;Secondly,considering the characteristics of fuel cells,establish an RSOC performance degradation model,and generate typical scenarios considering the uncertainty of available transmission capacity of ultra-high voltage channels;Furthermore,a centralized RSOC double-layer capacity planning model is established.The upper layer optimizes the capacity configuration of RSOC and hydrogen storage with the goal of maximizing revenue during the operation period,while the lower layer optimizes the output of each equipment with the goal of minimizing comprehensive cost.The solution is solved by combining particle swarm optimization algorithm and CPLEX solver.Finally,through case analysis,it was verified that the addition of RSOC improved the system's economic and environmental benefits.At the same time,investment sensitivity analysis showed that the unit capacity cost of batteries is an important factor restricting the economic operation of the system.