综合经济目标下电厂机组负荷优化调度方法研究
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摘要
随着我国社会主义市场经济的深入发展,作为国民经济基础产业的电力工业,体制改革也在逐步展开,改革的基本目标是“厂网分开、竞价上网”,在电力行业实现“公司制改组、商业化经营、法制化管理”。在这样的市场环境下,如何根据发电指标确定厂内机组负荷优化调度方案,对于电厂减少总体的能源消耗,获取最大利润,增强市场竞争力,具有十分重要的作用。
本论文以电厂内机组负荷优化调度为课题,研究的具体对象具有五台机组,其中两台机组燃用该厂内的工业废气,另外三台为燃煤机组;并且具有不同的机型,有一台为燃气轮机机组,另外四台为锅炉机组。本论文针对这种多机型、多燃料发电厂,主要研究了机组间负荷的优化分配和机组的最优投入两方面的问题。
理论分析表明,在参与负荷分配的发电机组确定的情况下,按等微增率原则进行分配所得方案是最优的。论文对等微增率原则在机组负荷分配中的应用进行了分析,并对该电厂5台不同类型机组进行了机组负荷分配计算。结果表明,等微增率原则适用于煤耗特性曲线为凸函数的火电厂内发电机组间负荷优化分配问题。
论文给出了机组最优投入问题的数学模型,分析了动态规划法的基本原理,给出了动态规划法应用于机组最优投入问题的求解模型和算法,并进行了计算流程设计。根据电厂机组的实际运行情况,论文中考虑了机组的启停耗量、机组的最小运行时间和最小停机时间限制、机组启动过程中的寿命损耗等问题,对各种影响计算结果的因素进行了比较分析。
论文将机组启动过程中的寿命损耗引入机组最优投入的计算中,并在程序设计中将机组启动耗量和寿命损耗设为常数,这样的处理确保了计算的合理性,同时也避免了因计算过于复杂而使结果反而不可靠。实际计算结果表明,寿命损耗对机组最优投入问题的求解有着不可忽视的影响。
考虑到为了环境保护而机组必须燃用工业废气的情况,论文提出并实现了机组强制运行和强制停机的处理方法。这样的处理使计算结果满足实际情况要求,同时一定程度上剔除了计算中的一些机组组合状态,减少了寻优计算的计算量。
论文对该电厂5台不同类型的机组进行了负荷优化调度计算,结果表明,应用动态规划法并结合等微增率原则进行机组负荷优化调度计算可以减少电厂煤耗,为电厂带来良好的经济效益。
With the development of China's socialist market economy, the structural reform of electricity industry is going on. The object of the reform is to establish an electric power market. In the market environment, how to make the units’load dispatch optimal is important for a power plant to reduce energy consumption, maximize profits and increase competitiveness.
The topic of this paper is unit load optimal dispatch in power plant, two issues are discussed: load dispatch and unit commitment.
The topic of this paper is unit load optimal dispatch in power plant. there are five units in the power plant which is the specific object this paper studies on. Two of these units use industrial waste gas as thermal, and the other three are coal-fired units. Besides, there units are not the same type, one is gas turbine unit, and the other four are boiler units. Regarding to this multi-type, multi-fuel power plant, this paper mainly studies two issues: load dispatch and unit commitment.
Theoretical analysis indicates that the plan of load allocate according to the equal incremental principle is optimal when the units participate in load allocate is determined. This paper analyses the application of the equal incremental principle in the subject of load allocate, and use the equal incremental principle to calculate the load allocate for a power plant which owns different type units. The results show that the equal incremental principle is applied to the issue of unit load allocate when the functions of the units’coal consumption curves are convex functions.
This paper gives the mathematical model of unit commitment, analysis the basic principle of dynamic programming, gives the algorithm as using dynamic programming method to solve this problem, and designs the calculation program. The practical factors such as the start consumption, the minimum running time and the minimum halt time, the life loss in the process of unit start are considered in this paper, and various factors that influence the result are compared.
This paper introduces the life loss in the process of unit start into the calculation of the optimal dispatch. In the process of calculating, the start consumption and life lose of unit are set constants, such a treatment not only ensures the reasonability of calculation, but also avoids the unreliable caused by the excessive complex of calculation. Actual results indicate that the life loss of unit have a negligible impact on unit load dispatch.
Considering the situation that the power plant must fire the waste gas in order to protect the environment, this paper designs the treatment of compulsory load instruction to make the calculation result meet the requirement of the actual situation. Meanwhile, this treatment shall reject some unreasonable unit commitments, and reduce the calculation complexity.
This paper dose some actual load optimal dispatch calculation for a power plant which owns different type units, and the results show that dynamic programming method combined with the principle of equal incremental is applied to solve the problem of optimal load dispatch, it shall reduce the coal consumption and bring economical benefits for power plants.
本论文以电厂内机组负荷优化调度为课题,研究的具体对象具有五台机组,其中两台机组燃用该厂内的工业废气,另外三台为燃煤机组;并且具有不同的机型,有一台为燃气轮机机组,另外四台为锅炉机组。本论文针对这种多机型、多燃料发电厂,主要研究了机组间负荷的优化分配和机组的最优投入两方面的问题。
理论分析表明,在参与负荷分配的发电机组确定的情况下,按等微增率原则进行分配所得方案是最优的。论文对等微增率原则在机组负荷分配中的应用进行了分析,并对该电厂5台不同类型机组进行了机组负荷分配计算。结果表明,等微增率原则适用于煤耗特性曲线为凸函数的火电厂内发电机组间负荷优化分配问题。
论文给出了机组最优投入问题的数学模型,分析了动态规划法的基本原理,给出了动态规划法应用于机组最优投入问题的求解模型和算法,并进行了计算流程设计。根据电厂机组的实际运行情况,论文中考虑了机组的启停耗量、机组的最小运行时间和最小停机时间限制、机组启动过程中的寿命损耗等问题,对各种影响计算结果的因素进行了比较分析。
论文将机组启动过程中的寿命损耗引入机组最优投入的计算中,并在程序设计中将机组启动耗量和寿命损耗设为常数,这样的处理确保了计算的合理性,同时也避免了因计算过于复杂而使结果反而不可靠。实际计算结果表明,寿命损耗对机组最优投入问题的求解有着不可忽视的影响。
考虑到为了环境保护而机组必须燃用工业废气的情况,论文提出并实现了机组强制运行和强制停机的处理方法。这样的处理使计算结果满足实际情况要求,同时一定程度上剔除了计算中的一些机组组合状态,减少了寻优计算的计算量。
论文对该电厂5台不同类型的机组进行了负荷优化调度计算,结果表明,应用动态规划法并结合等微增率原则进行机组负荷优化调度计算可以减少电厂煤耗,为电厂带来良好的经济效益。
With the development of China's socialist market economy, the structural reform of electricity industry is going on. The object of the reform is to establish an electric power market. In the market environment, how to make the units’load dispatch optimal is important for a power plant to reduce energy consumption, maximize profits and increase competitiveness.
The topic of this paper is unit load optimal dispatch in power plant, two issues are discussed: load dispatch and unit commitment.
The topic of this paper is unit load optimal dispatch in power plant. there are five units in the power plant which is the specific object this paper studies on. Two of these units use industrial waste gas as thermal, and the other three are coal-fired units. Besides, there units are not the same type, one is gas turbine unit, and the other four are boiler units. Regarding to this multi-type, multi-fuel power plant, this paper mainly studies two issues: load dispatch and unit commitment.
Theoretical analysis indicates that the plan of load allocate according to the equal incremental principle is optimal when the units participate in load allocate is determined. This paper analyses the application of the equal incremental principle in the subject of load allocate, and use the equal incremental principle to calculate the load allocate for a power plant which owns different type units. The results show that the equal incremental principle is applied to the issue of unit load allocate when the functions of the units’coal consumption curves are convex functions.
This paper gives the mathematical model of unit commitment, analysis the basic principle of dynamic programming, gives the algorithm as using dynamic programming method to solve this problem, and designs the calculation program. The practical factors such as the start consumption, the minimum running time and the minimum halt time, the life loss in the process of unit start are considered in this paper, and various factors that influence the result are compared.
This paper introduces the life loss in the process of unit start into the calculation of the optimal dispatch. In the process of calculating, the start consumption and life lose of unit are set constants, such a treatment not only ensures the reasonability of calculation, but also avoids the unreliable caused by the excessive complex of calculation. Actual results indicate that the life loss of unit have a negligible impact on unit load dispatch.
Considering the situation that the power plant must fire the waste gas in order to protect the environment, this paper designs the treatment of compulsory load instruction to make the calculation result meet the requirement of the actual situation. Meanwhile, this treatment shall reject some unreasonable unit commitments, and reduce the calculation complexity.
This paper dose some actual load optimal dispatch calculation for a power plant which owns different type units, and the results show that dynamic programming method combined with the principle of equal incremental is applied to solve the problem of optimal load dispatch, it shall reduce the coal consumption and bring economical benefits for power plants.
引文
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[2]崔荣国刘树臣等.我国能源消费现状与趋势.国土资源情报. 2008
[3]国家电力监管委员会.电力监管年度报告(2008). 2009
[4]赵遵廉,电力市场运营系统,北京:中国电力出版社,2001
[5]于良春,中国电力工业的改革与发展,中国工业经济,2000,4:53-57
[6]李志华,郭志忠,樊爱军,电力系统动态优化调度与电力市场,电力系统及其自动化学报,2002,12(3):39-42
[7] Lee F N. Short-Term Unit Commitment-A New Method. IEEE Trans on PWRS,1988,3(2)
[8] Shoults R R, Chang S K, etal. A Practical Approach to Unit Commitment, Economic Dispatch, and Savings Allocation for Multiple-Aiea Pool Operation with Import/Export Consrtaints. IEEE Trnas on PAS, 1980, 99(2)
[9] Fna J Y, Zhang L,Mcdonald J D. Enhanced Techniques on Sequential Unit Commitment with Interchange Transactions. IEEE Trans on PWRS,1966,11(l)
[10]王承民,郭志忠,于尔铿.电力市场中一种基于动态规划法的经济负荷分配算法.电力系统自动化,2000,24(21):19-23
[11]傅宏涛.综合经济目标下的电厂汽轮机组最优负荷分配. [硕士论文].上海:上海交通大学,2001
[12]王德意,南海鹏,刘栋,等.快速动态规划法在运行机组间有功负荷分配中的应用.水利水电技术,2001,32(6):28-30
[13] Snyder W L, Powell H D Jr, Rayburn J G. Dynamic programming Approach to Unit Commitment. IEEE Trans on PWRS, 1987, 2(2)
[14] Lowery P G. Generating Unit Commitment by Dynamic Programming. IEEE Trans on PAS, 1966, 85(5)
[15] Guy J D. Security Constrained Unit Commitment. IEEE Trans on PAS, 1971, 90(3)
[16] Guan X, Luh P B, Yan H, etal. An optimization-based method for unit commitment[J]. International Journal of Electrical Power & Energy Systems, 1992,14(1):9-17.
[17] Guan X, Lai F. Reducing homogeneous oscillations of lagrangian relax-action-based scheduling algorithm[C]. Proceedings of the 14th IFAC World Congress, Beijing, China 1999, L-5a-04-5:309-314.
[18] Wang S J, Shahidehpour S M, Kirschen D S, etal. Short-term generation scheduling with transmission constraints using augmented lagrangian relaxation[J]. IEEE Transon Power Sys-tems,1995,10(3):1294-1301.
[19] Guan X, Luh P B, Zhang L. Nonlinear approximation method in lagrangian relaxation-based algorithms for hydrothermal scheduling[J]. IEEE Trans on Power Systems, 1995, 10(2):772-778.
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[22]蔡兴国,初壮.用遗传算法解算机组组合的研究.电网技术,2003,27(7):36-39
[23]高山,单渊达.遗传算法搜索优化及其在机组启停中的应用.中国电机工程学报,2001,21(3):45-48
[24] Sheble G B, Maifeld T T, Brittigg K, et al. Unit Commitment by Genetic Algorithm
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[26]蔡超豪,蔡元宇.机组优化组合的遗传算法.电网技术,1997,2l(1):44-47
[27]王凌.智能优化算法及其应用[M].北京:清华大学出版社,2001
[28] Dasgupta D,McGregor D R. Thermal unit commitment using genetic algorithms. [J]. IEEE Proc-Gener, Transm, Distrib, 1994, 141(5):459-465
[29] M.Dorigo, G.Di Caro. Ant colony optimization:a new meta-heuristic.IEEE Congress on Evolutionary Computation, 1997, 1470-1477
[30]侯云鹤,熊信良,吴耀武,鲁丽娟.基于广义蚁群算法的电力系统经济负荷分配(J).中国电机工程学报,2003,23(3):59-64
[31]吕勇,赵光宙.蚁群优化算法及其在电力系统中的应用(J).电工技术学报,2003 18(4):70-74
[32]石琦,李承军,王金文.遗传算法在电力系统日有功优化调度中的应用[J].电力系统及其自动化学报,2002,14(2):56 -59
[33]李蔚,刘长东,盛德仁等.基于免疫算法的机组负荷优化分配[J].中国电机工程学报,2004, 24(7):241-246.
[34]舒隽,张粒子,王雁凌等.基于竞价的日发电计划混合智能优化算法.电力系统自动化. 2002,21(11):34-38
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[2]崔荣国刘树臣等.我国能源消费现状与趋势.国土资源情报. 2008
[3]国家电力监管委员会.电力监管年度报告(2008). 2009
[4]赵遵廉,电力市场运营系统,北京:中国电力出版社,2001
[5]于良春,中国电力工业的改革与发展,中国工业经济,2000,4:53-57
[6]李志华,郭志忠,樊爱军,电力系统动态优化调度与电力市场,电力系统及其自动化学报,2002,12(3):39-42
[7] Lee F N. Short-Term Unit Commitment-A New Method. IEEE Trans on PWRS,1988,3(2)
[8] Shoults R R, Chang S K, etal. A Practical Approach to Unit Commitment, Economic Dispatch, and Savings Allocation for Multiple-Aiea Pool Operation with Import/Export Consrtaints. IEEE Trnas on PAS, 1980, 99(2)
[9] Fna J Y, Zhang L,Mcdonald J D. Enhanced Techniques on Sequential Unit Commitment with Interchange Transactions. IEEE Trans on PWRS,1966,11(l)
[10]王承民,郭志忠,于尔铿.电力市场中一种基于动态规划法的经济负荷分配算法.电力系统自动化,2000,24(21):19-23
[11]傅宏涛.综合经济目标下的电厂汽轮机组最优负荷分配. [硕士论文].上海:上海交通大学,2001
[12]王德意,南海鹏,刘栋,等.快速动态规划法在运行机组间有功负荷分配中的应用.水利水电技术,2001,32(6):28-30
[13] Snyder W L, Powell H D Jr, Rayburn J G. Dynamic programming Approach to Unit Commitment. IEEE Trans on PWRS, 1987, 2(2)
[14] Lowery P G. Generating Unit Commitment by Dynamic Programming. IEEE Trans on PAS, 1966, 85(5)
[15] Guy J D. Security Constrained Unit Commitment. IEEE Trans on PAS, 1971, 90(3)
[16] Guan X, Luh P B, Yan H, etal. An optimization-based method for unit commitment[J]. International Journal of Electrical Power & Energy Systems, 1992,14(1):9-17.
[17] Guan X, Lai F. Reducing homogeneous oscillations of lagrangian relax-action-based scheduling algorithm[C]. Proceedings of the 14th IFAC World Congress, Beijing, China 1999, L-5a-04-5:309-314.
[18] Wang S J, Shahidehpour S M, Kirschen D S, etal. Short-term generation scheduling with transmission constraints using augmented lagrangian relaxation[J]. IEEE Transon Power Sys-tems,1995,10(3):1294-1301.
[19] Guan X, Luh P B, Zhang L. Nonlinear approximation method in lagrangian relaxation-based algorithms for hydrothermal scheduling[J]. IEEE Trans on Power Systems, 1995, 10(2):772-778.
[20]杨毅刚,杨期余,杨维汉等.电力系统优化的理论基础,北京:水利电力出版社,1988
[21]赵子臣,相年德,夏清,等.应用启发式与逐步动态规划法进行机组最优组合.清华大学学报,1997,37(1):57-60
[22]蔡兴国,初壮.用遗传算法解算机组组合的研究.电网技术,2003,27(7):36-39
[23]高山,单渊达.遗传算法搜索优化及其在机组启停中的应用.中国电机工程学报,2001,21(3):45-48
[24] Sheble G B, Maifeld T T, Brittigg K, et al. Unit Commitment by Genetic Algorithm
[25] Kazarlis S A, Bakirtzis A G, Petridis V. A Genetic Algorithm Solution to the Unit Commitment Problem. IEEE Trans on PWRS, 1996, 11(1)
[26]蔡超豪,蔡元宇.机组优化组合的遗传算法.电网技术,1997,2l(1):44-47
[27]王凌.智能优化算法及其应用[M].北京:清华大学出版社,2001
[28] Dasgupta D,McGregor D R. Thermal unit commitment using genetic algorithms. [J]. IEEE Proc-Gener, Transm, Distrib, 1994, 141(5):459-465
[29] M.Dorigo, G.Di Caro. Ant colony optimization:a new meta-heuristic.IEEE Congress on Evolutionary Computation, 1997, 1470-1477
[30]侯云鹤,熊信良,吴耀武,鲁丽娟.基于广义蚁群算法的电力系统经济负荷分配(J).中国电机工程学报,2003,23(3):59-64
[31]吕勇,赵光宙.蚁群优化算法及其在电力系统中的应用(J).电工技术学报,2003 18(4):70-74
[32]石琦,李承军,王金文.遗传算法在电力系统日有功优化调度中的应用[J].电力系统及其自动化学报,2002,14(2):56 -59
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