To fully consider the complementary role of different energy sources and reduce the curtailment of renewable energy(RE)in high RE penetration systems,a hierarchical optimization algorithm is proposed to simultaneously...To fully consider the complementary role of different energy sources and reduce the curtailment of renewable energy(RE)in high RE penetration systems,a hierarchical optimization algorithm is proposed to simultaneously optimize the capacity of RE generation and energy storage systems(ESS).Time sequence simulation(TSS)technology is adopted to fully consider the regional RE resource characteristics and make the model more reliable.An optimization model for evaluating ESS capacity is established at a lower level.To overcome the high dimensional complexity of time sequence data,this paper re-formulates this sub-model as a consensus problem,which can be solved by a distributed approach to minimize the system’s total investment costs.At the upper level,the model for assessing the proportion of wind and solar capacity is developed by maximizing the RE generation.The golden section Fibonacci tree optimization(GSFTO)algorithm is utilized to improve the efficiency and solution accuracy.The results show that the algorithm and model are feasible and applicable for the identified purposes,which can provide a useful guidance for the development of power generation and the energy storage capacity in high RE penetration systems.展开更多
基金This work was supported jointly by the National Key R&D Program of China(2017YFB0902200)State Grid Corporation of China Science and Technology Project(5228001700CW)the Qinghai Province Science and Technology Plan(2018-GX-A6).
文摘To fully consider the complementary role of different energy sources and reduce the curtailment of renewable energy(RE)in high RE penetration systems,a hierarchical optimization algorithm is proposed to simultaneously optimize the capacity of RE generation and energy storage systems(ESS).Time sequence simulation(TSS)technology is adopted to fully consider the regional RE resource characteristics and make the model more reliable.An optimization model for evaluating ESS capacity is established at a lower level.To overcome the high dimensional complexity of time sequence data,this paper re-formulates this sub-model as a consensus problem,which can be solved by a distributed approach to minimize the system’s total investment costs.At the upper level,the model for assessing the proportion of wind and solar capacity is developed by maximizing the RE generation.The golden section Fibonacci tree optimization(GSFTO)algorithm is utilized to improve the efficiency and solution accuracy.The results show that the algorithm and model are feasible and applicable for the identified purposes,which can provide a useful guidance for the development of power generation and the energy storage capacity in high RE penetration systems.
