针对光照强度不均匀造成光伏阵列的输出曲线为多峰曲线,传统最大功率点跟踪(Maximum Power Point Tracking,MPPT)控制算法不能跟踪到全局最大功率的问题,文章提出一种基于改进麻雀搜索算法(Improved the Sparrow Search Algorithm,ISSA...针对光照强度不均匀造成光伏阵列的输出曲线为多峰曲线,传统最大功率点跟踪(Maximum Power Point Tracking,MPPT)控制算法不能跟踪到全局最大功率的问题,文章提出一种基于改进麻雀搜索算法(Improved the Sparrow Search Algorithm,ISSA)和扰动观察法(Perturbation and Observation Method,P&O)的光储发电系统MPPT控制方法。首先,在跟踪前期,采用混沌映射方式增加ISSA种群多样性,提升算法广泛搜索能力。为了防止算法陷入局部最优,利用萤火虫扰动算法对麻雀个体进行扰动更新;其次,在跟踪后期,使用P&O防止系统在最大功率点附近振荡,保证最大功率点稳定输出;最后,经过算例分析,所提MPPT控制方法实现了不同场景下的快速跟踪、精准输出,能够很好应用地于光储混合发电系统中。展开更多
The bidding strategies of power suppliers to maximize their interests is of great importance.The proposed bilevel optimization model with coalitions of power suppliers takes restraint factors into consideration,such a...The bidding strategies of power suppliers to maximize their interests is of great importance.The proposed bilevel optimization model with coalitions of power suppliers takes restraint factors into consideration,such as operating cost reduction,potential cooperation,other competitors’bidding behavior,and network constraints.The upper model describes the coalition relationship between suppliers,and the lower model represents the independent system operator’s optimization without network loss(WNL)or considering network loss(CNL).Then,a novel algorithm,the evolutionary game theory algorithm(EGA)based on a hybrid particle swarm optimization and improved firefly algorithm(HPSOIFA),is proposed to solve the bi-level optimization model.The bidding behavior of the power suppliers in equilibrium with a dynamic power market is encoded as one species,with the EGA automatically predicting a plausible adaptation process for the others.Individual behavior changes are employed by the HPSOIFA to enhance the ability of global exploration and local exploitation.A novel improved firefly algorithm(IFA)is combined with a chaotic sequence theory to escape from the local optimum.In addition,the Shapley value is applied to the profit distribution of power suppliers’cooperation.The simulation,adopting the standard IEEE-30 bus system,demonstrates the effectiveness of the proposed method for solving the bi-level optimization problem.展开更多
文摘针对光照强度不均匀造成光伏阵列的输出曲线为多峰曲线,传统最大功率点跟踪(Maximum Power Point Tracking,MPPT)控制算法不能跟踪到全局最大功率的问题,文章提出一种基于改进麻雀搜索算法(Improved the Sparrow Search Algorithm,ISSA)和扰动观察法(Perturbation and Observation Method,P&O)的光储发电系统MPPT控制方法。首先,在跟踪前期,采用混沌映射方式增加ISSA种群多样性,提升算法广泛搜索能力。为了防止算法陷入局部最优,利用萤火虫扰动算法对麻雀个体进行扰动更新;其次,在跟踪后期,使用P&O防止系统在最大功率点附近振荡,保证最大功率点稳定输出;最后,经过算例分析,所提MPPT控制方法实现了不同场景下的快速跟踪、精准输出,能够很好应用地于光储混合发电系统中。
文摘The bidding strategies of power suppliers to maximize their interests is of great importance.The proposed bilevel optimization model with coalitions of power suppliers takes restraint factors into consideration,such as operating cost reduction,potential cooperation,other competitors’bidding behavior,and network constraints.The upper model describes the coalition relationship between suppliers,and the lower model represents the independent system operator’s optimization without network loss(WNL)or considering network loss(CNL).Then,a novel algorithm,the evolutionary game theory algorithm(EGA)based on a hybrid particle swarm optimization and improved firefly algorithm(HPSOIFA),is proposed to solve the bi-level optimization model.The bidding behavior of the power suppliers in equilibrium with a dynamic power market is encoded as one species,with the EGA automatically predicting a plausible adaptation process for the others.Individual behavior changes are employed by the HPSOIFA to enhance the ability of global exploration and local exploitation.A novel improved firefly algorithm(IFA)is combined with a chaotic sequence theory to escape from the local optimum.In addition,the Shapley value is applied to the profit distribution of power suppliers’cooperation.The simulation,adopting the standard IEEE-30 bus system,demonstrates the effectiveness of the proposed method for solving the bi-level optimization problem.
