CN105631533B - 一种考虑p-q-v静态电压稳定裕度约束的多目标动态最优潮流求解方法 - Google Patents

一种考虑p-q-v静态电压稳定裕度约束的多目标动态最优潮流求解方法 Download PDF

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CN105631533B
CN105631533B CN201510961116.6A CN201510961116A CN105631533B CN 105631533 B CN105631533 B CN 105631533B CN 201510961116 A CN201510961116 A CN 201510961116A CN 105631533 B CN105631533 B CN 105631533B
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马瑞
李晅
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Abstract

本发明涉及一种考虑P‑Q‑V静态电压稳定裕度约束的多目标动态最优潮流求解方法，属电力***日前调度计划研究领域，包括以下步骤：获取下一调度周期内***相关数据，拟合节点P‑Q‑V静态电压稳定边界函数参数；以***总发电耗费、污染物排放量和有功网损最小为目标，考虑传统动态最优潮流的静态、动态约束和P‑Q‑V静态电压稳定裕度约束，建立多目标动态最优潮流模型；采用NSGA‑II与最大满意度法混合算法获取多目标动态最优潮流的最优解。本发明将P‑Q‑V静态电压稳定裕度约束引入日前调度问题，基于多目标动态最优潮流建立模型，益于保证和评估电力***调度问题中的静态电压稳定安全性。

Description

一种考虑P-Q-V静态电压稳定裕度约束的多目标动态最优潮 流求解方法
技术领域
本发明属于电力***日前调度计划研究领域，涉及一种考虑P-Q-V静态电压稳定裕度的多目标动态最优潮流求解方法。
背景技术
电力***静态电压稳定域分析属电力***安全性研究领域，传统电压稳定域研究一般基于连续潮流法通过P-V或Q-V曲线描述静态电压稳定域，也有文献采用P-Q曲线描述。基于此，有文献提出用P-Q-V空间曲线描述稳态电压稳定域，可在三维空间兼顾有功、无功、和电压极限三者的关系，并提出了电压稳定裕度(voltage stability region，AVSR)指标，用于评估节点、区域或整个***的静态电压稳定性。在制定电力***调度计划时考虑静态电压稳定约束，对电力***在满足安全性要求下实现优化运行与控制有重要意义。
多目标动态最优潮流是日前调度计划研究的一个分支，旨在机组组合确定的情况下，基于对电力***下一调度周期负荷等情况的合理预测，制定***中可调节手段如机组出力、机端电压、无功补偿投入和需求响应资源等的调度计划，以实现电力***在满足机组爬坡及电压安全等约束下的经济、环保、节能等方面多目标动态优化运行。这类问题是具有大量混合变量和约束条件的复杂多目标非线性优化问题。基于遗传思想的快速非支配排序遗传算法 (non-dominated sorting genetic algorithm-II，NSGA-II)具有良好的非线性优化能力和鲁棒性，可获取多目标Pareto最优解集，保证最优个体多样性从而为决策者提供不同偏好选择，成为求解多目标优化问题的优秀智能算法之一。最大满意度法通过模糊满意度和综合满意度计算从而获取多目标综合最优折衷解，为决策提供一种方法途径。
综上所述，研究考虑P-Q-V静态电压稳定裕度约束的多目标动态最优潮流，保证和评估电力***调度问题中的静态电压稳定安全性，对于提升电力***日前调度水平具有积极意义。
发明内容
针对现有技术的不足，本发明“一种考虑P-Q-V静态电压稳定裕度约束的多目标动态最优潮流求解方法”，提出将P-Q-V静态电压稳定裕度约束引入日前调度问题，基于多目标动态最优潮流建立模型，益于保证和评估电力***调度问题中的静态电压稳定安全性。
本发明采用如下技术方案：一种考虑P-Q-V静态电压稳定裕度约束的多目标动态最优潮流求解方法，该方法包括如下步骤：
步骤1：获取电力***在下一个完整调度周期的数据，并进行负荷预测，拟合节点P-Q-V静态电压稳定边界函数参数。
步骤2：以***总发电耗费、污染物排放量和有功网损最小为目标，考虑传统动态最优潮流的静态、动态约束和P-Q-V静态电压稳定裕度约束，建立多目标动态最优潮流模型。
步骤3：采用NSGA-II与最大满意度法混合算法获取多目标动态最优潮流的最优解。
附图说明
图1：本发明一种考虑P-Q-V静态电压稳定裕度约束的多目标动态最优潮流求解方法的整体实施流程图；
图2：本发明的P-Q-V静态电压稳定曲线示意图；
图3：本发明的偏小型满意度函数曲线；
图4：IEEE30节点***的接线示意图；
图5：IEEE30节点***的典型负荷曲线图。
具体实施方式
下面结合附图及具体实施例，对本发明做进一步详述。
本发明提出的一种考虑P-Q-V静态电压稳定裕度约束的多目标动态最优潮流求解方法，其整体实施流程见图1，下面以IEEE30节点***为具体实施例对其进行详细说明，其接线情况见图4。实施例用于说明但不限于本发明。
步骤1：获取电力***在下一个完整调度周期的数据，并进行负荷预测，拟合节点P-Q-V静态电压稳定边界函数参数。
对于本实施例直接输入IEEE30节点***的数据即可。负荷预测曲线采用图 5典型双峰曲线为例。
基于***各节点的预测负荷，分别以各灵活负荷节点(即有需求响应资源和分布式电源接入的节点)为研究对象，设定负荷功率增长方向集合d＝[d1,…dn]，采用连续潮流算法计算各功率增长方向对应的电压崩溃点集合
Figure GDA0002242662320000031
通过最小二乘法拟合和高斯迭代获取该负荷节点bi的P-Q-V静态电压稳定边界表达式
Γ:QΓbi,t(P)＝abi,tP2+bbi,tP+cbi,t (1)
其中abi,t，bbi,t和cbi,t是拟合系数。IEEE30节点***中节点8的负荷曲线示意图如图2所示。
步骤2：以***总发电耗费、污染物排放量和有功网损最小为目标，考虑传统动态最优潮流的静态、动态约束和P-Q-V静态电压稳定裕度约束，建立多目标动态最优潮流模型。
本发明建立的多目标动态最优潮流模型如下：
决策变量
Figure GDA0002242662320000032
其中PGi,t是火电机组i的有功出力(i＝1,2,…nG)，PDRj,t是负荷侧需求响应资源(或分布式电源等)j的有功出力(j＝1,2,…nDR)，UGi,t是火电机组i所在节点的电压，Bk,t (k＝1,2,…nSC)是无功补偿器k投入量。
目标函数：
Figure GDA0002242662320000033
其中
Figure GDA0002242662320000034
表示火电机组发电耗费，CDRj,t＝ζj,tPDRj,t+λj,tξj表示需求响应资源补偿费用，
Figure GDA0002242662320000035
表示调用需求响应资源作为发电机或负荷，
Figure GDA0002242662320000036
为调用状态。
Figure GDA0002242662320000037
Figure GDA0002242662320000041
约束条件：
1.静态约束
(1)功率平衡约束
Figure GDA0002242662320000042
Figure GDA0002242662320000043
(2)发电约束
Figure GDA0002242662320000045
Figure GDA0002242662320000046
(3)节点电压约束
Figure GDA0002242662320000047
(4)***旋转备用约束
Figure GDA0002242662320000048
一般取μ＝5％。
(5)节点P-Q-V静态电压稳定裕度约束
基于P-Q-V静态电压稳定边界曲线，负荷节点的电压稳定裕度
Figure GDA0002242662320000049
其中(Pbi,t,Qbi,t)是该负荷节点时下运行点，
Figure GDA00022426623200000410
是无功负荷为Qbi,t的电压崩溃点。
本发明的动态最优潮流模型中引入灵活负荷节点的P-Q-V静态电压稳定裕度约束，如下式
Figure GDA00022426623200000411
其中
Figure GDA0002242662320000051
是最大裕度，为节点负荷为0时的AVSR值；η为稳定性裕度。
2.动态约束
火电机组的爬坡约束
Figure GDA0002242662320000052
考虑爬坡约束后的火电机组出力上下限由下式决定
Figure GDA0002242662320000053
步骤3：采用NSGA-II与最大满意度法混合算法获取多目标动态最优潮流的最优解。
采用NSGA-II求取Pareto最优解集，最大满意度法决策最优折衷解，在优化目标函数中加入动态罚函数实现静态等式约束。
采用偏小型模糊满意度计算公式，其示意图如图3。对于Pareto解集中的每个非支配解，计算其每个目标值的满意度，再计算每个非支配解的综合满意度，选取综合满意度最大的非支配解为多目标最优折衷解。
计算负荷节点、区域等的分时段AVSR值与累加AVSR值，分析获取节点和区域在特定时段及整个调度周期的静态电压稳定性特征。
以上实施方式仅用于说明本发明，而并非对本发明的限制，有关技术领域的普通技术人员，在不脱离本发明的精神和范围的情况下，还可以做出各种变化和变型，因此所有等同的技术方案也属于本发明的保护范畴。

Claims (3)

1.一种考虑P-Q-V静态电压稳定裕度约束的多目标动态最优潮流求解方法，其特征是，该方法包括如下步骤：
步骤1：获取电力***在下一个完整调度周期的数据，并进行负荷预测，拟合节点P-Q-V静态电压稳定边界函数参数；
步骤2：以***总发电耗费、污染物排放量和有功网损最小为目标，考虑传统动态最优潮流的静态、动态约束和P-Q-V静态电压稳定裕度约束，建立一种多目标动态最优潮流模型；
步骤3：采用NSGA-II与最大满意度法混合算法获取多目标动态最优潮流的最优解，其中NSGA-II表示快速非支配排序遗传算法。
2.根据权利要求l所述的一种考虑P-Q-V静态电压稳定裕度约束的多目标动态最优潮流求解方法，其特征是，步骤1中的静态电压稳定边界求取是基于***各节点的预测负荷，以有需求响应资源和分布式电源接入的节点为研究对象，在P-Q-V三维空间进行。
3.根据权利要求1和权利要求2中任意一项权利要求所述的一种考虑P-Q-V静态电压稳定裕度约束的多目标动态最优潮流求解方法，其特征是，步骤2中的多目标动态最优潮流模型中，考虑了有需求响应资源和分布式电源接入的节点的P-Q-V静态电压稳定裕度约束
Figure FDA0002274166420000011
其中
Figure FDA0002274166420000012
是最大裕度，为节点负荷为0时的AVSR值；η为稳定性裕度；AVSR为电压稳定裕度；(Pbi,t,Qbi,t)是该负荷节点时下运行点，
Figure FDA0002274166420000013
是无功负荷为Qbi,t的电压崩溃点，abi,t，bbi,t和cbi,t是拟合的静态电压稳定边界系数。
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