基于信息间隙决策理论的受端电网电压稳定多源协同优化调度

doi:10.11930/j.issn.1004-9649.202407094

摘要/Abstract

摘要：

为解决双碳背景下的新能源消纳问题，以及直流输电接入下的多源协同优化调度问题，提出基于信息间隙决策理论的受端电网电压稳定多源协同优化调度策略。首先，构建电压稳定指标，反映电力系统当前状态与电压稳定极限状态之间的距离。然后，以最小化系统运行成本和弃风惩罚为目标，提出考虑火电、梯级水电、风电、储能、直流输入的多源协同优化调度模型，对系统内各种可控电源建立模型，并通过泰勒级数展开、三角形近似等方法线性化交流潮流和水电转换约束。在此基础上，通过电压稳定裕度阈值生成电压稳定约束，通过每次迭代在受端电网多源协同优化问题中添加电压稳定约束，实现电压稳定裕度指标的改善。考虑风电出力和系统负荷需求的不确定性，提出基于信息间隙决策理论的受端电网电压稳定多源协同优化调度模型。最后，通过算例验证了所提出模型的有效性。

关键词: 梯级水电, 新能源, 直流受端, 信息间隙决策, 电压稳定

Abstract:

To improve renewable energy consumption under the background of dual carbon, and solve problem of multi-source coordinated scheduling with DC transmission, a multi-source coordinated scheduling of receiving power system considering voltage stability based on information gap decision theory (IGDT) is proposed. Firstly, the voltage stability indicator is constructed, which indicates distance between the system voltage state and the voltage stability limit state. Then, aim at minimizing the system operation cost and wind curtailment penalty, a multi-source power receiving ability promotion model considering thermal/ cascade hydro/wind power generation, energy storage and DC transmission coordination is proposed. The models of multi-sources in the system are established, and the AC power flow and hydropower conversion constraints are linearized by Taylor series expansion and triangle approximation. On this basis, voltage stability constraints are generated through voltage stability margin threshold, and voltage stability constraints are added to multi-source coordinated optimization problem for the receiving power system through each iteration to achieve the improvement of voltage stability indicator. To consider uncertainty of wind power output and load demand, a multi-source coordinated scheduling of receiving power system considering voltage stability based on IGDT is proposed. Finally, the effectiveness of the proposed model is verified by case studies.

Key words: cascade hydro power, renewable energy, DC receiving-end, IGDT, voltage stability

叶希, 黄格超, 王曦, 王彦沣, 朱童, 何川, 张瑜祺. 基于信息间隙决策理论的受端电网电压稳定多源协同优化调度[J]. 中国电力, 2025, 58(5): 121-136.

YE Xi, HUANG Gechao, WANG Xi, WANG Yanfeng, ZHU Tong, HE Chuan, ZHANG Yuqi. Multi-source Coordinated Scheduling of Receiving Power System Considering Voltage Stability Based on Information Gap Decision Theory[J]. Electric Power, 2025, 58(5): 121-136.

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链接本文: https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202407094

https://www.electricpower.com.cn/CN/Y2025/V58/I5/121

图/表 22

图 1 直流受端系统示意

Fig.1 Schematic diagram of DC receiving-end system

图 2 水电转换线性化

Fig.2 Linearization of hydro-power conversion

图 3 考虑电压稳定约束的信息间隙决策优化调度模型求解示意

Fig.3 Flow of IGDT-based scheduling optimization model considering voltage stability

表 2 梯级水电机组参数

Table 2 Parameter of cascade hydro power unis

机组	水电转换系数	初始水头	最大出力/MW
H1	6.197	0.82679	220
H2	7.182	0.71359	190

表 3 储能设备参数

Table 3 Parameter of energy storage equipment

充放电功率上限/MW		容量上限/MW		充放电效率
30		150		0.9

图 4 修改后的6节点算例系统

Fig.4 Modified 6-bus test system

图 5 负荷与风电出力预测

Fig.5 Forecast active/reactive load and wind power output

表 1 火电机组参数

Table 1 Parameter of thermal unis

机组	最小有功出力/ MW	最大有功出力/ MW	最小无功出力/ (MW·A)	最大无功出力/ (MW·A)	爬坡率/ (MW·h^–1)	最小开机时间/ h	最小关机时间/ h
G1	25	100	0	300	50	8	4
G2	25	200	0	100	150	5	4

表 4 传输线路参数

Table 4 Parameter of transmission lines

传输线路编号	首端节点	末端节点	电阻	电抗	有功潮流限制/ MW	无功潮流限制/ (MV·A)
1	1	2	0.0370	0.010	400	400
2	1	4	0.0160	0.004	500	500
3	2	3	0.1015	0.025	500	500
4	2	4	0.1170	0.027	500	500
5	3	6	0.0355	0.010	500	500
6	4	5	0.0370	0.010	500	500
7	5	6	0.1270	0.040	500	500

表 5 方案设置

Table 5 Settings of cases

方案	储能设备	直流功率调节	电压稳定	IGDT
1	×	×	×	×
2	√	×	×	×
3	√	√	×	×
4	√	√	√	×
5	√	√	√	√

表 6 方案1-5成本与计算时间对比

Table 6 Comparison cost and computational time of case 1-5

方案	系统成本/元	运行成本/元	弃风惩罚/元	计算时间/s
1	162605.4	130579.7	32025.7	5.4
2	123987.1	109961.4	14025.7	5.7
3	83514.1	81106.4	2407.7	6.5
4	81965.1	81575.9	389.2	17.0
5	100216.9	100216.9	0	61.9

图 6 方案1中水电、火电机组出力

Fig.6 Output of generators of case 1

图 7 方案1~3弃风量

Fig.7 Wind curtailment of case 1~3

图 8 方案2~3储能充放电状况

Fig.8 ESS charge/discharge status of case 2~3

图 9 方案2~3直流功率

Fig.9 DC infeed power of case 2~3

图 10 敏感性分析

Fig.10 Sensitivity analysis

图 11 方案4的电压稳定指标

Fig.11 Voltage stability indicator in case 4

图 12 不同迭代次数下G1机组出力与直流线路传输功率

Fig.12 G1 output and DC infeed power under different iteration

图 13 方案5的电压稳定指标

Fig.13 Voltage stability indicator in case 5

表 7 方案5，5.1，5.2计算结果对比

Table 7 Comparison computational results of case 5, 5.1, 5.2

方案	偏差系数	不确定度β	系统总成本/元
5.1	0.05	0.0042	87689.8
5.2	0.10	0.0143	91865.5
5	0.20	0.0207	100216.9

表 8 方案1~5成本与计算时间对比

Table 8 Comparison cost and computational time of case 1~5

方案	系统成本/万元	运行成本/万元	弃风惩罚/万元	计算时间/s
1	273.58	161.79	111.79	162.04
2	259.27	159.39	99.88	168.32
3	205.11	149.03	56.08	865.97
4	224.75	176.76	47.99	1726.15
5	246.13	246.13	0.00	2446.99

表 9 IGDT、RO、SO方法的成本对比

Table 9 Comparison cost of IGDT, RO and SO

不确定性方法	系统成本/万元	运行成本/万元	弃风惩罚/万元
IGDT	246.13	246.13	0.00
RO	358.80	358.80	0.00
SO	221.29	174.72	46.57

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