In view of the high cost of solar thermal power generation in China,it is difficult to realize large-scale production in engineering and industrialization.Non-dominated sorting genetic algorithm II(NSGA-II)is applied ...In view of the high cost of solar thermal power generation in China,it is difficult to realize large-scale production in engineering and industrialization.Non-dominated sorting genetic algorithm II(NSGA-II)is applied to optimize the levelling cost of energy(LCOE)of the solar thermal power generation system in this paper.Firstly,the capacity and generation cost of the solar thermal power generation system are modeled according to the data of several sets of solar thermal power stations which have been put into production abroad.Secondly,the NSGA-II genetic algorithm and particle swarm algorithm are applied to the optimization of the solar thermal power station LCOE respectively.Finally,for the linear Fresnel solar thermal power system,the simulation experiments are conducted to analyze the effects of different solar energy generation capacities,different heat transfer mediums and loan interest rates on the generation price.The results show that due to the existence of scale effect,the greater the capacity of the power station,the lower the cost of leveling and electricity,and the influence of the types of heat storage medium and the loan on the cost of leveling electricity are relatively high.展开更多
Consumers＇ electricity cost keeps increasing over the time in most countries across the world. The main reason is that importing electricity from generation plants far from a load center is relatively expensive, as c...Consumers＇ electricity cost keeps increasing over the time in most countries across the world. The main reason is that importing electricity from generation plants far from a load center is relatively expensive, as costs are paid not only for generation but also for energy loss and network use. To this end, it is more economi- cal to use electricity generated by local distributed generations. In order to reduce customers＇ electricity cost, a new economic dispatch of smart distribution networks is proposed. Economic dispatch of smart distribution network is to meet load demand with the least consumers＇ electricity cost considering distributed generators, while recognizing all operational limits of generation and transmission facilities in a distribution network. Case study shows that consumers＇ electricity cost can be reduced by about 200/o through economic dispatch of distri- bution network. Further, generation cost and emission of distribution network are reduced as well.展开更多
基金National Natural Science Foundation of China(No.519667013)
文摘In view of the high cost of solar thermal power generation in China,it is difficult to realize large-scale production in engineering and industrialization.Non-dominated sorting genetic algorithm II(NSGA-II)is applied to optimize the levelling cost of energy(LCOE)of the solar thermal power generation system in this paper.Firstly,the capacity and generation cost of the solar thermal power generation system are modeled according to the data of several sets of solar thermal power stations which have been put into production abroad.Secondly,the NSGA-II genetic algorithm and particle swarm algorithm are applied to the optimization of the solar thermal power station LCOE respectively.Finally,for the linear Fresnel solar thermal power system,the simulation experiments are conducted to analyze the effects of different solar energy generation capacities,different heat transfer mediums and loan interest rates on the generation price.The results show that due to the existence of scale effect,the greater the capacity of the power station,the lower the cost of leveling and electricity,and the influence of the types of heat storage medium and the loan on the cost of leveling electricity are relatively high.
基金supported in part by The National High Technology Research and Development of China 863 Program(2012AA050201)
文摘Consumers＇ electricity cost keeps increasing over the time in most countries across the world. The main reason is that importing electricity from generation plants far from a load center is relatively expensive, as costs are paid not only for generation but also for energy loss and network use. To this end, it is more economi- cal to use electricity generated by local distributed generations. In order to reduce customers＇ electricity cost, a new economic dispatch of smart distribution networks is proposed. Economic dispatch of smart distribution network is to meet load demand with the least consumers＇ electricity cost considering distributed generators, while recognizing all operational limits of generation and transmission facilities in a distribution network. Case study shows that consumers＇ electricity cost can be reduced by about 200/o through economic dispatch of distri- bution network. Further, generation cost and emission of distribution network are reduced as well.
