考虑风电不确定性的短期合同电量协同分解优化模型及算法

doi:10.11930/j.issn.1004-9649.202305031

摘要/Abstract

摘要：

现有合同电量分解方法大多没有考虑风电不确定性的影响及未与发电计划协同优化，导致到期合同电量往往未能够得到充分执行。提出一种考虑风电不确定性和检修计划影响的短期合同电量协同分解优化新模型及算法，使得到期时合同电量能够公平合理地充分执行。首先，以发电成本、合同偏差成本及风电品质风险成本最小为目标，构建短期合同电量分解到天的优化模型及算法，得到每天预计完成的合同电量。然后，基于日前及日内短期及超短期负荷及风功率预测信息，分别构建考虑合同完成度的日前鲁棒发电计划及日内重调度优化模型及算法，在保证对负荷尽可能供电及系统安全约束满足的前提下，实现风功率充分消纳及每日合同电量的充分执行。在此基础上，对每日未完成的合同电量，通过后续日合同电量的滚动修正进一步加以实现，从而保证到期时短期合同电量能够得到充分执行。算例证实了该模型及算法的可行性和先进性。

关键词: 风电不确定性, 检修计划, 分解优化模型, 鲁棒发电计划, 滚动修正

Abstract:

Most of the existing contract electricity decomposition methods do not take into account the impact of wind power uncertainty and do not coordinate with the generation plan for optimization, resulting in their insufficient execution when the contract is due. A new cooperative optimization decomposition model and algorithm of short-term contract electricity is therefore proposed with consideration of the wind power uncertainty and maintenance plans. Firstly, a cooperative optimization decomposition model and algorithm of short-term contract electricity is constructed with the objective of minimization of the generation cost, contract deviation cost and low-quality wind power risk cost, to obtain the decomposed daily contract electricity. And then, based on the day-ahead and intraday short-term and ultra-short-term load and wind power forecast information, the day-ahead robust generation plan model and algorithm and the intraday redispatch model and algorithm are constructed respectively with consideration of the contract completion degree, to realize the full accommodation of wind power and full execution of the daily contract electricity with the premise of power load to be fully supplied and the security constraints to be met. Furthermore, the uncompleted daily contract electricity is fulfilled through rolling updating the subsequent daily contract electricity to ensure the full execution of the short contract electricity when the contract is due. The results of case study have demonstrated the feasibility and superiority of the proposed model and algorithm.

Key words: wind power uncertainty, maintenance plan, decomposition optimization model, robust generation plan, rolling update

刘凌杰, 林济铿. 考虑风电不确定性的短期合同电量协同分解优化模型及算法[J]. 中国电力, 2023, 56(12): 227-237.

Lingjie LIU, Jikeng LIN. Model and Algorithm of Cooperative Optimization Decomposition for Short-Term Contract Electricity Considering Wind Power Uncertainty[J]. Electric Power, 2023, 56(12): 227-237.

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链接本文: https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202305031

https://www.electricpower.com.cn/CN/Y2023/V56/I12/227

图/表 9

图 1 短期合同电量优化分解整体框架

Fig.1 Framework for optimal decomposition of short-term contract electricity

图 2 考虑风电不确定性的短期合同电量协同优化分解流程

Fig.2 Flowchart for cooperative optimization decomposition of short-term contract electricity considering wind power uncertainty

表 1 签订合同的火电机组基本数据

Table 1 Parameters of thermal power units

编号	火电机组出力/MW		a	b	c	检修日期
编号	最小	最大	a	b	c	检修日期
1	40	200	0	54.82	105.18
2	40	200	0	55.95	103.96
3	50	250	0	43.68	116.02	2014-01-02

图 3 6658号风电场分位数回归曲线

Fig.3 The quantile regression curve of No.6658 wind farm

图 4 6658号风电场2014年1月1日风功率预测误差带

Fig.4 The wind power forecast error band of No.6658 wind farm on January 1st, 2014

表 2 短期合同电量分解结果对比

Table 2 Comparison of the decomposition results of short-term contract electricity by different methods

模型	总成本/ 美元	低品质风功率成本/美元	弃风率/ %	风电场、火电机组合同完成率
1	3319207	42050	21，8	1、0.99；1、1、1
2	4615299	622000	0，0	1.25、1.09； 0.92、0.92、0.92

图 5 1月1日签订合同的火电机组及风电场日前预计出力情况

Fig.5 The day-ahead expected output of thermal power units and wind farms on January 1 st

图 6 1月1日签订合同的火电机组及风电场日内实际出力

Fig.6 The intraday real output of thermal power units and wind farms on January 1 st

表 3 签订合同的火电机组、风电场7天的日合同电量

Table 3 The daily contract electricity of thermal power units and wind farms in 7 days

日期	电量类型	日合同电量/(MW·h)
日期	电量类型	火电机组1	火电机组2	火电机组3	6658号风电场	6661号风电场
1月1日	初始	2809	960	5100	2611	867
	修正	2809	960	5100	2611	867
	实际	2809	967	5100	2357	698
1月2日	初始	4800	2957	0	3704	1085
	修正	4800	2956	0	3746	1113
	实际	4760	2956	0	3746	1113
1月3日	初始	1197	4800	6000	300	291
	修正	1205	4797	6000	342	319
	实际	1205	4197	5616	320	267
1月4日	初始	960	1748	6000	1907	875
	修正	967	1897	6095	1954	916
	实际	967	1897	6000	1954	916
1月5日	初始	960	960	5253	2939	910
	修正	967	1109	5380	2986	951
	实际	967	1109	5380	2964	943
1月6日	初始	4691	4800	1200	1330	467
	修正	4699	4949	1327	1388	511
	实际	3224	4452	1327	1443	460
1月7日	初始	4385	3576	1200	2793	897
	修正	5868	4222	1327	2796	993
	实际	3622	4222	1327	2796	963

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