An MILP model for the thermal unit commitment problem with feasible energy delivery and start-up & shut-down power trajectories

被引:0
作者
Deng, Jun [1 ]
Wei, Hua [1 ]
Li, Jinghua [1 ]
机构
[1] Guangxi Key Laboratory of Power System Optimization and Energy Technology, (Guangxi University), Nanning, 530004, Guangxi Zhuang Autonomous Region
来源
Dianwang Jishu/Power System Technology | 2015年 / 39卷 / 10期
基金
中国国家自然科学基金;
关键词
Feasible energy delivery; Mixed-integer linear programming; Start-up and shut-down power trajectories; Unit commitment;
D O I
10.13335/j.1000-3673.pst.2015.10.030
中图分类号
学科分类号
摘要
This paper proposes a mixed-integer linear programming (MILP) model for thermal unit commitment problem with feasible energy delivery and start-up & shut-down power trajectories. The aim is to solve problems of unrealizable generation schedule in terms of energy delivery and system frequency deviation due to excessive simplification of traditional model. This model introduces a set of binary variables to represent operating states of coal-fired units, which facilitate logical judgment and electricity production calculation in four phases, i.e. warm-up, start-up ramp, dispatchable, and shut-down ramp. According to characteristics of rapid start-up and shut-down of gas-fired and oil-fired units, new operating states are modeled. This model also supports various start-up types of cold, warm and hot start and various dispatching time span of each interval such as 1 hour and 15 minutes. The results for systems ranging from 10 to 1000 units during 24 periods show that the proposed model fits actual running situation better and can not only solve unrealizable generation schedule in terms of energy delivery, but also is featured with higher solving efficiency. ©, 2015, Power System Technology Press. All right reserved.
引用
收藏
页码:2882 / 2888
页数:6
相关论文
共 19 条
  • [1] Wood A.J., Wollenberg B.F., Power Generation, Operation, and Control, pp. 131-166, (1996)
  • [2] Yang P., Han X., Unit decommitment based on improved Lagrangian multiplier modification method, Power System Technology, 30, 9, pp. 40-45, (2006)
  • [3] Carrion M., Arroyo J.M., A computationally efficient mixed-integer linear formulation for the thermal unit commitment problem, IEEE Transactions on Power Systems, 21, 3, pp. 1371-1378, (2006)
  • [4] Li J., Wei H., Xia X., Improved general pattern search filter algorithm for unit commitment problems, Proceedings of the CSEE, 31, 28, pp. 33-41, (2011)
  • [5] Wang N., Zhang L., Yuan Z., Et al., A method for security constrained unit commitment based on benders algorithm, Power System Technology, 36, 10, pp. 203-208, (2012)
  • [6] Ostrowski J., Anjos M.F., Vannelli A., Tight mixed integer linear programming formulations for the unit commitment problem, IEEE Transactions on Power Systems, 27, 1, pp. 39-46, (2012)
  • [7] Wei H., Long D., Li J., Policy iteration-approximate dynamic programming for large scale unit commitment problems, Proceedings of the CSEE, 34, 25, pp. 4420-4429, (2014)
  • [8] Xie M., Yan Y., Liu M., Et al., A vector ordinal optimization method forlarge-scale multi-objective unit commitment considering stochastic wind power generation, Power System Technology, 39, 1, pp. 215-222, (2015)
  • [9] Yang Y., Tian H., Guan X., Et al., Model of economic dispatch for thermal power plant with feasible energy delivery and its solution, Proceedings of the CSEE, 30, 16, pp. 98-103, (2010)
  • [10] Guan X.H., Gao F., Svoboda A.J., Energy delivery capacity and the generation scheduling in the deregulated electric power market, IEEE Transactions on Power Systems, 15, 4, pp. 1275-1280, (2000)