| 引用本文: | 吴刚,刘俊勇,向月,沈晓东,马宇航.计及中长期合同电量分解和风电不确定性的电-气综合能源系统日前优化调度[J].电力自动化设备,2019,39(8): |
| WU Gang,LIU Junyong,XIANG Yue,SHEN Xiaodong,MA Yuhang.Day-ahead optimal scheduling of integrated electricity and natural gas system with medium-and long-term electricity contract decomposition and wind power uncertainties[J].Electric Power Automation Equipment,2019,39(8): |
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| 摘要: |
| 将中长期合同电量分解模型引入电-气综合能源系统日前调度决策过程中，实现了合同电量分解和调度计划制定的嵌套优化。针对合同电量分解结果可能在实际调度计划中不可执行的情况，提出了一种基于拉格朗日乘子的机组日分解电量越限因素定位方法，并通过中长期合同电量分解模型与日前调度模型的协调迭代消除越限电量，保证了中长期交易的有效性。此外，在模型中考虑了天然气网络约束和风电随机性对中长期交易计划的影响，并利用机会约束规划理论构建含风电不确定性的优化调度随机模型。基于风电等效随机输出样本矩阵和随机模拟技术实现机会约束向确定性表达式转化。通过仿真算例验证了所提方法的有效性。 |
| 关键词: 电-气综合能源系统 中长期交易 不确定性 拉格朗日乘子 日前调度 机会约束规划 |
| DOI：10.16081/j.epae.201908032 |
| 分类号:TM73 |
| 基金项目:国家重点研发计划资助项目(2017YFB0903300)；国家电网公司科技项目(521999180005) |
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| Day-ahead optimal scheduling of integrated electricity and natural gas system with medium-and long-term electricity contract decomposition and wind power uncertainties |
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WU Gang, LIU Junyong, XIANG Yue, SHEN Xiaodong, MA Yuhang
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College of Electrical Engineering, Sichuan University, Chengdu 610065, China
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| Abstract: |
| The medium-and long-term contract electric quantity decomposition model is introduced in the day-ahead optimal scheduling of integrated electricity and natural gas system to realize the nested optimization of contract energy decomposition and scheduling planning. For the case that the decomposed electric quantity may be non-executable in actual scheduling plan, a method based on Lagrange multiplier is proposed to find the infeasible factor of daily decomposed electric quantity of units. The infeasible power quantities are eliminated by the coordinated iteration between the decomposition model of medium-and long-term electricity contract and day-ahead scheduling model, which guarantees the effectiveness of medium-and long-term transactions. In addition, the influences of wind power uncertainties and natural gas network constraints on the medium-and long-term trading plan are considered in the optimization model. The chance-constrained programming theory is used to construct the stochastic optimal scheduling model considering wind power uncertainties. The chance constraints are transformed into deterministic forms based on equivalent stochastic output sample matrix of wind power and stochastic simulation method. Case study results verify the efficiency of proposed method. |
| Key words: integrated electricity and natural gas system medium-and long-term transaction uncertainty Lagrange multiplier day-ahead scheduling chance-constrained programming |
