The power systems economic and safety operation considering large-scale wind power penetration are now facing great challenges, which are based on reliable power supply and predictable load demands in the past. A roll...The power systems economic and safety operation considering large-scale wind power penetration are now facing great challenges, which are based on reliable power supply and predictable load demands in the past. A rolling generation dispatch model based on ultra-short-term wind power forecast was proposed. In generation dispatch process, the model rolling correct not only the conventional units power output but also the power from wind farm, simultaneously. Second order Markov chain model was utilized to modify wind power prediction error state (WPPES) and update forecast results of wind power over the remaining dispatch periods. The prime-dual affine scaling interior point method was used to solve the proposed model that taken into account the constraints of multi-periods power balance, unit output adjustment, up spinning reserve and down spinning reserve.展开更多
A generalized formulation for short-term scheduling of steam power system in iron and steel industry under the time-of-use（TOU）power price was presented,with minimization of total operational cost including fuel cos...A generalized formulation for short-term scheduling of steam power system in iron and steel industry under the time-of-use（TOU）power price was presented,with minimization of total operational cost including fuel cost,equipment maintenance cost and the charge of exchange power with main grid.The model took into account the varying nature of surplus byproduct gas flows,several practical technical constraints and the impact of TOU power price.All major types of utility equipments,involving boilers,steam turbines,combined heat and power（CHP）units,and waste heat and energy recovery generators（WHERG）,were separately modeled using thermodynamic balance equations and regression method.In order to solve this complex nonlinear optimization model,a new improved particle swarm optimization（IPSO）algorithm was proposed by incorporating time-variant parameters,a selfadaptive mutation scheme and efficient constraint handling strategies.Finally,a case study for a real industrial example was used for illustrating the model and validating the effectiveness of the proposed approach.展开更多
近年来,建设清洁低碳安全高效的能源体系,发展可再生能源替代,构建以新能源为主体的新型电力系统成为我国能源发展的必然趋势。在风光资源富集地区,随着新能源装机不断增加,大型综合能源基地得到快速发展。该文基于主客观赋权法建立多...近年来,建设清洁低碳安全高效的能源体系,发展可再生能源替代,构建以新能源为主体的新型电力系统成为我国能源发展的必然趋势。在风光资源富集地区,随着新能源装机不断增加,大型综合能源基地得到快速发展。该文基于主客观赋权法建立多能互补综合能源基地评估体系,对我国“三北”、西南及东部沿海区域发展布局多能互补基地进行评估。为进一步提升多能互补基地经济效益,建立基于长短期记忆神经网络(long short term memory,LSTM)的电价预测模型及多能互补日前优化调度模型,利用粒子群优化算法进行寻优,以实现能源基地综合收益最大化的日前优化调度目标。最后,以甘肃陇东千万kW级多能互补综合能源基地为例,分别开展夏季及冬季典型日的优化调度算例仿真,结果表明,该优化调度方法能够促进基地内新能源消纳的同时最大化能源基地综合收益,为大型综合能源基地的日前优化调度提供技术支撑。展开更多
文摘The power systems economic and safety operation considering large-scale wind power penetration are now facing great challenges, which are based on reliable power supply and predictable load demands in the past. A rolling generation dispatch model based on ultra-short-term wind power forecast was proposed. In generation dispatch process, the model rolling correct not only the conventional units power output but also the power from wind farm, simultaneously. Second order Markov chain model was utilized to modify wind power prediction error state (WPPES) and update forecast results of wind power over the remaining dispatch periods. The prime-dual affine scaling interior point method was used to solve the proposed model that taken into account the constraints of multi-periods power balance, unit output adjustment, up spinning reserve and down spinning reserve.
基金Sponsored by National Natural Science Foundation of China(51304053)International Science and Technology Cooperation Program of China(2013DFA10810)
文摘A generalized formulation for short-term scheduling of steam power system in iron and steel industry under the time-of-use（TOU）power price was presented,with minimization of total operational cost including fuel cost,equipment maintenance cost and the charge of exchange power with main grid.The model took into account the varying nature of surplus byproduct gas flows,several practical technical constraints and the impact of TOU power price.All major types of utility equipments,involving boilers,steam turbines,combined heat and power（CHP）units,and waste heat and energy recovery generators（WHERG）,were separately modeled using thermodynamic balance equations and regression method.In order to solve this complex nonlinear optimization model,a new improved particle swarm optimization（IPSO）algorithm was proposed by incorporating time-variant parameters,a selfadaptive mutation scheme and efficient constraint handling strategies.Finally,a case study for a real industrial example was used for illustrating the model and validating the effectiveness of the proposed approach.
文摘近年来,建设清洁低碳安全高效的能源体系,发展可再生能源替代,构建以新能源为主体的新型电力系统成为我国能源发展的必然趋势。在风光资源富集地区,随着新能源装机不断增加,大型综合能源基地得到快速发展。该文基于主客观赋权法建立多能互补综合能源基地评估体系,对我国“三北”、西南及东部沿海区域发展布局多能互补基地进行评估。为进一步提升多能互补基地经济效益,建立基于长短期记忆神经网络(long short term memory,LSTM)的电价预测模型及多能互补日前优化调度模型,利用粒子群优化算法进行寻优,以实现能源基地综合收益最大化的日前优化调度目标。最后,以甘肃陇东千万kW级多能互补综合能源基地为例,分别开展夏季及冬季典型日的优化调度算例仿真,结果表明,该优化调度方法能够促进基地内新能源消纳的同时最大化能源基地综合收益,为大型综合能源基地的日前优化调度提供技术支撑。
