CN112054504B - Economic dispatch method for wind power system based on improved affine reserve allocation - Google Patents

Economic dispatch method for wind power system based on improved affine reserve allocation Download PDF

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CN112054504B
CN112054504B CN201910492478.3A CN201910492478A CN112054504B CN 112054504 B CN112054504 B CN 112054504B CN 201910492478 A CN201910492478 A CN 201910492478A CN 112054504 B CN112054504 B CN 112054504B
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wind power
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CN112054504A (en
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唐程辉
张凡
薛松
马莉
胡源
梁才
廖建辉
杨素
曲昊源
张晓萱
宋海旭
张笑峰
李景
徐杨
宋海云
范孟华
陈珂宁
林晓斌
高国伟
武泽辰
赵铮
冯昕欣
李维
李睿
李晓冬
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State Grid Energy Research Institute Co Ltd
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for AC mains or AC distribution networks
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for AC mains or AC distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E10/00—Energy generation through renewable energy sources
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Abstract

本发明公开了一种基于改进仿射备用分配的含风电电力系统经济调度方法，步骤包括确定系统内发电机组参数、线路参数和风电功率场景；基于改进仿射备用方法，以实际风电功率与风电调度功率之间的差异为基准，确定在实时的实际风电功率得到后的常规机组实际备用功率，建立电力系统经济调度模型；基于线性规划求解器求解模型，确定并输出常规机组的调度结果。本发明通过以实际风电功率与风电调度功率之间的差异为基准，确定在实时的实际风电功率得到后的常规机组实际备用功率，以此建立电力系统经济调度模型，基于线性规划求解器求解模型，确定并输出常规机组的调度结果，且通过本发明方法的总体系统调度成本明显低于常规仿射备用分配方法。

Figure 201910492478

The invention discloses an economic dispatch method for a power system including wind power based on improved affine backup allocation. The steps include determining parameters of generator sets, line parameters and wind power scenarios in the system; based on the improved affine backup method, the actual wind power and wind power The difference between dispatched powers is used as a benchmark to determine the actual standby power of conventional units after the real-time actual wind power is obtained, and establish an economic dispatch model of the power system; solve the model based on a linear programming solver, and determine and output the dispatching results of conventional units. The invention determines the actual standby power of the conventional unit after the real-time actual wind power is obtained by taking the difference between the actual wind power and the wind power dispatching power as a benchmark, thereby establishing an economic dispatch model of the power system, and solving the model based on a linear programming solver , determine and output the scheduling results of conventional units, and the overall system scheduling cost through the method of the present invention is significantly lower than the conventional affine reserve allocation method.

Figure 201910492478

Description

基于改进仿射备用分配的含风电电力系统经济调度方法Economic dispatch method for wind power system based on improved affine reserve allocation

技术领域technical field

本发明涉及电力系统中运行与控制的技术领域，具体涉及一种基于改进仿射备用分配的含风电电力系统经济调度方法。The invention relates to the technical field of operation and control in a power system, in particular to an economic dispatch method for a power system containing wind power based on improved affine reserve allocation.

背景技术Background technique

电力系统调度运行包括静态经济调度和动态经济调度。动态经济调度考虑了各时间段之间的相互影响，更加能够切实反映系统的运行要求，目前已有很多相关研究，风能作为一种重要的可再生能源，研究含有并网风电场的动态经济调度问题是一个十分重要的问题；同时，区别于火电等常规能源，由于风能具备有别于常规机组的间歇性和不可预测性，也给这一问题的解决带来了困难和挑战。电力系统中需要预留一定的备用功率来平抑风电出力的随机性。具体来说，通过在经济调度中预留一部分常规机组的备用功率，在实时的实际风电功率得到后，通过调用常规机组的备用来平衡风电出力的偏差。The power system dispatch operation includes static economic dispatch and dynamic economic dispatch. Dynamic economic dispatch takes into account the interaction between various time periods, and can more effectively reflect the operating requirements of the system. At present, there have been many related studies. As an important renewable energy source, wind energy has studied dynamic economic dispatch including grid-connected wind farms. The problem is a very important one; at the same time, different from conventional energy sources such as thermal power, wind energy has the intermittency and unpredictability different from conventional units, which also brings difficulties and challenges to the solution of this problem. A certain amount of backup power needs to be reserved in the power system to suppress the randomness of wind power output. Specifically, by reserving a part of the backup power of conventional units in economic dispatch, after the real-time actual wind power is obtained, the deviation of wind power output is balanced by calling the backup of conventional units.

仿射备用分配方法是考虑风电功率实际分配的经典方法。在仿射备用分配方法中，通常以实际风电功率与预测风电功率之间的差值为基准，通过相应的参与因子将风电的不平衡功率分配给每个常规机组，如果实际风电功率大于预测风电功率，则需要系统的向下备用，即常规机组需要降低出力来调用预留的备用功率。如果实际风电功率小于预测风电功率，则需要系统的向上备用，即常规机组需要增加出力来调用预留的备用功率。在更糟糕的情况下，如果系统备用不能平衡风电出力的随机性导致的系统功率不平衡，会导致因风电出力率的低估和高估产生的弃风或切负荷。然而，由于弃风和切负荷带了的社会成本相差很大，故仅以实际风电功率与预测风电功率之间的差异为基准的传统方法得到的调度结果并非经济最优解。The affine reserve allocation method is a classical method that considers the actual allocation of wind power. In the affine reserve allocation method, the difference between the actual wind power and the predicted wind power is usually used as the benchmark, and the unbalanced power of the wind power is allocated to each conventional unit through the corresponding participation factor. If the actual wind power is greater than the predicted wind power power, the system needs to be backed down, that is, the conventional unit needs to reduce the output to call the reserved backup power. If the actual wind power is less than the predicted wind power, the upward backup of the system is required, that is, the conventional unit needs to increase the output to call the reserved backup power. In a worse case, if the system backup cannot balance the power imbalance caused by the randomness of wind power output, it will lead to wind curtailment or load shedding due to the underestimation and overestimation of the wind power output rate. However, due to the great difference between the social cost of wind curtailment and load shedding, the dispatching results obtained by the traditional method only based on the difference between the actual wind power and the predicted wind power are not economical optimal solutions.

发明内容SUMMARY OF THE INVENTION

为了解决上述技术问题，本发明所采用的技术方案是提供了一种基于改进仿射备用分配的含风电电力系统经济调度方法，包括以下步骤：In order to solve the above technical problems, the technical solution adopted in the present invention is to provide an economic dispatch method for a power system containing wind power based on improved affine reserve allocation, which includes the following steps:

确定系统内发电机组参数、线路参数和风电功率场景；Determine the generator set parameters, line parameters and wind power scenarios in the system;

基于改进仿射备用方法，以实际风电功率与风电调度功率之间的差异为基准，确定在实时的实际风电功率得到后的常规机组实际备用功率，建立电力系统经济调度模型；Based on the improved affine backup method, the difference between the actual wind power and the wind power dispatching power is used as the benchmark to determine the actual standby power of conventional units after the real-time actual wind power is obtained, and establish the economic dispatch model of the power system;

基于线性规划求解器求解模型，确定并输出常规机组的调度结果。The model is solved based on a linear programming solver, and the scheduling results of conventional units are determined and output.

在上述方法中，所述系统内发电机组参数包括：出力上下限、燃料成本系数、备用成本系数、最大向上和向下爬坡功率和最大向上和向下备用能力；In the above method, the parameters of the generator set in the system include: output upper and lower limits, fuel cost coefficient, backup cost coefficient, maximum upward and downward climbing power and maximum upward and downward reserve capacity;

线路参数包括：拓扑结构、最大传输容量、直流潮流分配系数。Line parameters include: topology, maximum transmission capacity, and DC power flow distribution coefficient.

在上述方法中，所述经济调度问题的目标函数是：In the above method, the objective function of the economic dispatch problem is:

Figure BDA0002087494900000021
Figure BDA0002087494900000021

式中，f为系统总成本；fc为系统常规机组的总成本，在第一阶段中建模，由here-and-now决策变量pi,t、ru,i,t和rd,i,t决定；pi,t为常规机组i在调度周期t的调度功率，ru,i,t和rd,i,t分别为常规机组i在调度周期t的向上和向下备用功率；In the formula, f is the total cost of the system; f c is the total cost of the conventional unit of the system, modeled in the first stage, by the here-and-now decision variables p i,t , r u,i,t and r d, i,t is decided; pi ,t is the dispatching power of the conventional unit i in the dispatching period t, r u,i,t and r d,i,t are the up and down standby power of the conventional unit i in the dispatching period t, respectively ;

fu为在第二阶段对应的所有由风电随机性引起的系统随机性成本，由wait-and-see变量

Figure BDA0002087494900000022
决定，
Figure BDA0002087494900000023
是风电出力的随机变量。f u is all the system randomness costs caused by the randomness of wind power in the second stage, which is determined by the wait-and-see variable
Figure BDA0002087494900000022
Decide,
Figure BDA0002087494900000023
is a random variable of wind power output.

在上述方法中，所述第一阶段建模具体如下：In the above method, the first stage modeling is as follows:

系统常规机组的总成本由下式可得：The total cost of the conventional unit of the system can be obtained by the following formula:

Figure BDA0002087494900000031
Figure BDA0002087494900000031

式中，T为调度时间域为调度周期的数量，其中t＝1,2…T；I为系统内常规机组的数量，i＝1,2…I；bf,i和cf,i分别为常规机组i的燃料成本的一次项和常数项系数；cur,i和cdr,i分别为常规机组i的向上和向下备用预留成本系数；In the formula, T is the number of scheduling cycles in the scheduling time domain, where t=1,2...T; I is the number of conventional units in the system, i=1,2...I; b f,i and c f,i respectively are the primary term and constant term coefficients of the fuel cost of the conventional unit i; cur,i and cdr,i are the reserve cost coefficients for the upward and downward reserve of the conventional unit i, respectively;

约束条件为：The constraints are:

①常规机组出力累加备用约束后功率约束①Power constraint after accumulative reserve constraint of conventional unit output

Figure BDA0002087494900000032
Figure BDA0002087494900000032

Figure BDA0002087494900000033
Figure BDA0002087494900000033

②常规机组备用能力上限约束②The upper limit of the reserve capacity of conventional units is restricted

Figure BDA0002087494900000034
Figure BDA0002087494900000034

Figure BDA0002087494900000035
Figure BDA0002087494900000035

③常规机组的爬坡约束③Climbing constraints of conventional units

Figure BDA0002087494900000036
Figure BDA0002087494900000036

Figure BDA0002087494900000037
Figure BDA0002087494900000037

④功率平衡约束④ Power balance constraints

Figure BDA0002087494900000038
Figure BDA0002087494900000038

⑤风电功率随机性能被系统备用平衡对应的出力上下限的与系统备用的关系约束⑤ The random performance of wind power is constrained by the relationship between the upper and lower output limits corresponding to the system backup balance and the system backup

Figure BDA0002087494900000039
Figure BDA0002087494900000039

Figure BDA00020874949000000310
Figure BDA00020874949000000310

⑥风电功率随机性能被系统备用平衡对应的出力上下限约束⑥ The random performance of wind power is constrained by the upper and lower output limits corresponding to the system backup balance

Figure BDA0002087494900000041
Figure BDA0002087494900000041

式中，

Figure BDA0002087494900000042
和p i分别为常规机组i的出力上限和下限；In the formula,
Figure BDA0002087494900000042
and p i are the upper and lower output limits of conventional unit i, respectively;

Figure BDA0002087494900000043
和
Figure BDA0002087494900000044
分别为常规机组i的向上和向下备用的上限；
Figure BDA0002087494900000043
and
Figure BDA0002087494900000044
are the upper and lower reserve upper limits of conventional unit i, respectively;

Figure BDA0002087494900000045
和
Figure BDA0002087494900000046
分别为常规机组i的最大向上和向下爬坡功率；
Figure BDA0002087494900000045
and
Figure BDA0002087494900000046
are the maximum upward and downward climbing power of the conventional unit i, respectively;

wt为风电调度功率，Lt为调度周期t下系统预测功率；w t is the dispatching power of wind power, L t is the predicted power of the system under dispatching period t;

Figure BDA0002087494900000047
出力上限为，w t出力下限为；
Figure BDA0002087494900000047
The upper limit of output is, and the lower limit of w t output is;

wr是风电装机容量。 wr is the installed capacity of wind power.

在上述方法中，所述第二阶段建模具体如下：In the above method, the second stage modeling is as follows:

风电功率随机性成本由下式可得：The random cost of wind power can be obtained by the following formula:

E[fu(wt)]＝cwcEwc+clsEls E[f u (w t )]=c wc E wc +c ls E ls

式中，其中fu(wt)是第二阶段风电随机性的惩罚成本期望；Ewc和Els分别是弃风和切负荷的功率期望值；cwc和cls分别是弃风和切负荷的惩罚系数。where f u (w t ) is the expected penalty cost of wind power randomness in the second stage; E wc and E ls are the expected power values of wind curtailment and load shedding, respectively; c wc and c ls are wind curtailment and load shedding, respectively penalty factor.

在上述方法中，所述第二阶段中的风电功率随机性成本根据风电功率场景模型写为：In the above method, the random cost of wind power in the second stage is written as:

Figure BDA0002087494900000048
Figure BDA0002087494900000048

Figure BDA0002087494900000049
Figure BDA0002087494900000049

Figure BDA00020874949000000410
Figure BDA00020874949000000410

Figure BDA00020874949000000411
Figure BDA00020874949000000411

式中，πs是风电功率场景s的概率；

Figure BDA00020874949000000412
是调度周期t下场景s的风电功率之和；
Figure BDA00020874949000000413
和
Figure BDA00020874949000000414
分别是场景s的切负荷和弃风功率；S为风电功率场景数量；where π s is the probability of wind power scenario s;
Figure BDA00020874949000000412
is the sum of wind power in scenario s under dispatch period t;
Figure BDA00020874949000000413
and
Figure BDA00020874949000000414
are the load shedding and wind curtailment power of scenario s, respectively; S is the number of wind power scenarios;

Figure BDA0002087494900000051
为风电功率总和的场景，
Figure BDA0002087494900000052
为风电场j的风力功率场景，J为系统内风电场的数量；
Figure BDA0002087494900000051
is the scene of the sum of wind power,
Figure BDA0002087494900000052
is the wind power scenario of wind farm j, and J is the number of wind farms in the system;

常规机组i按照一定的比例因子确定调度周期t下场景s的实际备用功率：The conventional unit i determines the actual standby power of the scenario s under the scheduling period t according to a certain scaling factor:

Figure BDA0002087494900000053
Figure BDA0002087494900000053

Figure BDA0002087494900000054
Figure BDA0002087494900000054

Figure BDA0002087494900000055
Figure BDA0002087494900000055

Figure BDA0002087494900000056
Figure BDA0002087494900000056

式中，ai即常规机组i承担由风电随机性导致的系统备用的比例因子；In the formula, a i is the proportional factor for the conventional unit i to undertake the system backup caused by the randomness of wind power;

对于每个场景s的调度周期t下的输电线路l，传输容量约束如下：For the transmission line l under the scheduling period t of each scenario s, the transmission capacity constraints are as follows:

Figure BDA0002087494900000057
Figure BDA0002087494900000057

式中：Nb为系统中节点数量；l是输电线路索引；b为节点索引；

Figure BDA0002087494900000058
是输电线路l的传输容量限制；kl,b是直流潮流中的分配系数；I(b)为连接到母线b上的常规机组数量；J(b)为连接到母线b上的风电场数量；Lb,t是调度周期t下节点b的负荷需求；
Figure BDA0002087494900000059
是调度周期t下场景s的常规机组i的实际备用功率。In the formula: N b is the number of nodes in the system; l is the transmission line index; b is the node index;
Figure BDA0002087494900000058
is the transmission capacity limit of transmission line l; k l,b is the distribution coefficient in DC power flow; I(b) is the number of conventional units connected to busbar b; J(b) is the number of wind farms connected to busbar b ; L b,t is the load demand of node b under scheduling period t;
Figure BDA0002087494900000059
is the actual standby power of conventional unit i in scenario s in scheduling period t.

本发明通过以实际风电功率与风电调度功率之间的差异为基准，确定在实时的实际风电功率得到后的常规机组实际备用功率，以此建立电力系统经济调度模型，基于线性规划求解器求解模型，确定并输出常规机组的调度结果，且通过本发明方法的总体系统调度成本明显低于常规仿射备用分配方法。The invention determines the actual standby power of the conventional unit after the real-time actual wind power is obtained by taking the difference between the actual wind power and the wind power dispatching power as a benchmark, thereby establishing an economic dispatch model of the power system, and solving the model based on a linear programming solver , determine and output the scheduling results of conventional units, and the overall system scheduling cost through the method of the present invention is significantly lower than the conventional affine reserve allocation method.

附图说明Description of drawings

图1为本发明提供的流程图；Fig. 1 is the flow chart provided by the present invention;

图2为本发明提供的风电出力随机性对系统影响的说明图；FIG. 2 is an explanatory diagram of the influence of the randomness of wind power output on the system provided by the present invention;

图3为本发明提供的预测风电功率、风电功率场景和风电调度功率算例结果曲线图。FIG. 3 is a graph showing the results of a calculation example of predicted wind power, wind power scenarios and wind power dispatching power provided by the present invention.

具体实施方式Detailed ways

本发明针对现有仿射备用分配方法中以实际风电功率与预测风电功率之间的差值为基准造成社会成本提高的缺陷，提出一种基于改进仿射备用分配的含风电电力系统经济调度方法，通过以实际风电功率与风电调度功率之间的差异为基准，确定在实时的实际风电功率得到后的常规机组实际备用功率，以此建立电力系统经济调度模型，基于线性规划求解器求解模型，确定并输出常规机组的调度结果。下面结合具体实施方式和说明书附图对本发明做出详细的说明。Aiming at the defect of increasing social cost in the existing affine reserve allocation method based on the difference between the actual wind power and the predicted wind power, the invention proposes an economic dispatch method for a power system including wind power based on improved affine reserve allocation , by taking the difference between the actual wind power and the wind power dispatching power as the benchmark to determine the actual standby power of the conventional units after the real-time actual wind power is obtained, so as to establish the economic dispatch model of the power system, and solve the model based on the linear programming solver, Determine and output the scheduling results of conventional units. The present invention will be described in detail below with reference to the specific embodiments and the accompanying drawings.

一种基于改进仿射备用分配的含风电电力系统经济调度方法，包括以下步骤：An economic dispatch method for a power system with wind power based on improved affine reserve allocation, comprising the following steps:

S1、确定系统内发电机组参数、线路参数和风电功率场景；其中，S1. Determine the generator set parameters, line parameters and wind power scenarios in the system; wherein,

系统内发电机组参数包括：出力上下限、燃料成本系数、备用成本系数、最大向上和向下爬坡功率和最大向上和向下备用能力；The parameters of the generator set in the system include: output upper and lower limits, fuel cost coefficient, backup cost coefficient, maximum upward and downward climbing power and maximum upward and downward reserve capacity;

线路参数包括拓扑结构、最大传输容量、直流潮流分配系数；Line parameters include topology, maximum transmission capacity, and DC power flow distribution coefficient;

风电功率场景主要基于采用由Chenghui Tang、Yishen Wang等人于1 July 2018在Applied Energy期刊提出《Efficient scenario generation of multiple renewablepower plants considering spatial and temporal correlations》(考虑时空相关性的多可再生能源电站高效出力场景生成技术)中的风电功率场景生成方法；The wind power scenario is mainly based on the "Efficient scenario generation of multiple renewable power plants considering spatial and temporal correlations" proposed by Chenghui Tang, Yishen Wang et al. in the Applied Energy journal on 1 July 2018. Wind power scene generation method in scene generation technology);

S2、基于改进仿射备用方法，以实际风电功率与风电调度功率之间的差异为基准，确定在实时的实际风电功率得到后的常规机组实际备用功率，建立电力系统经济调度模型，具体包括：S2. Based on the improved affine backup method, taking the difference between the actual wind power and the wind power dispatching power as the benchmark, determine the actual standby power of the conventional units after the real-time actual wind power is obtained, and establish an economic dispatch model of the power system, which specifically includes:

电力系统经济调度模型如下：The economic dispatch model of the power system is as follows:

本实施例以滚动经济调度问题为例，决策常规机组的出力、系统储备以及弃风功率和切负荷功率。采用两阶段模型来建模决策变量和风电随机性成本。经济调度问题的目标函数是：In this embodiment, the rolling economic dispatch problem is taken as an example to decide the output, system reserve, wind curtailment power and load shedding power of conventional units. A two-stage model is used to model decision variables and wind power stochastic costs. The objective function of the economic dispatch problem is:

Figure BDA0002087494900000071
Figure BDA0002087494900000071

式中，f为系统总成本；fc为系统常规机组的总成本，在第一阶段中建模，由here-and-now决策变量pi,t、ru,i,t和rd,i,t决定；pi,t为常规机组i在调度周期t的调度功率，ru,i,t和rd,i,t分别为常规机组i在调度周期t的向上和向下备用功率；fu为在第二阶段对应的所有由风电随机性引起的系统随机性成本，由wait-and-see变量

Figure BDA0002087494900000072
决定，
Figure BDA0002087494900000073
是风电出力的随机变量。In the formula, f is the total cost of the system; f c is the total cost of the conventional unit of the system, modeled in the first stage, by the here-and-now decision variables p i,t , r u,i,t and r d, i,t is decided; pi ,t is the dispatching power of the conventional unit i in the dispatching period t, r u,i,t and r d,i,t are the up and down standby power of the conventional unit i in the dispatching period t, respectively ; f u is all the system randomness costs caused by wind power randomness in the second stage corresponding to the wait-and-see variable
Figure BDA0002087494900000072
Decide,
Figure BDA0002087494900000073
is a random variable of wind power output.

第一阶段：The first stage:

系统常规机组的总成本由下式可得：The total cost of the conventional unit of the system can be obtained by the following formula:

Figure BDA0002087494900000074
Figure BDA0002087494900000074

式中，T为调度时间域为调度周期的数量，其中t＝1,2…T；I为系统内常规机组的数量，i＝1,2…I；bf,i和cf,i分别为常规机组i的燃料成本的一次项和常数项系数；cur,i和cdr,i分别为常规机组i的向上和向下备用预留成本系数。In the formula, T is the number of scheduling cycles in the scheduling time domain, where t=1,2...T; I is the number of conventional units in the system, i=1,2...I; b f,i and c f,i respectively are the primary term and constant term coefficients of the fuel cost of the conventional unit i; cur,i and cdr,i are the reserved cost coefficients for the up and down reserve of the conventional unit i, respectively.

约束条件为：The constraints are:

①常规机组出力累加备用约束后功率约束①Power constraint after accumulative reserve constraint of conventional unit output

Figure BDA0002087494900000075
Figure BDA0002087494900000075

②常规机组备用能力上限约束②The upper limit of the reserve capacity of conventional units is restricted

Figure BDA0002087494900000081
Figure BDA0002087494900000081

③常规机组的爬坡约束③Climbing constraints of conventional units

Figure BDA0002087494900000082
Figure BDA0002087494900000082

④功率平衡约束④ Power balance constraints

Figure BDA0002087494900000083
Figure BDA0002087494900000083

⑤风电功率随机性能被系统备用平衡对应的出力上下限的与系统备用的关系约束⑤ The random performance of wind power is constrained by the relationship between the upper and lower output limits corresponding to the system backup balance and the system backup

Figure BDA0002087494900000084
Figure BDA0002087494900000084

⑥风电功率随机性能被系统备用平衡对应的出力上下限约束⑥ The random performance of wind power is constrained by the upper and lower output limits corresponding to the system backup balance

Figure BDA0002087494900000085
Figure BDA0002087494900000085

式中，

Figure BDA0002087494900000086
和p i分别为常规机组i的出力上限和下限；In the formula,
Figure BDA0002087494900000086
and p i are the upper and lower output limits of conventional unit i, respectively;

Figure BDA0002087494900000087
和
Figure BDA0002087494900000088
分别为常规机组i的向上和向下备用的上限；
Figure BDA0002087494900000087
and
Figure BDA0002087494900000088
are the upper and lower reserve upper limits of conventional unit i, respectively;

Figure BDA0002087494900000089
和
Figure BDA00020874949000000810
分别为常规机组i的最大向上和向下爬坡功率；
Figure BDA0002087494900000089
and
Figure BDA00020874949000000810
are the maximum upward and downward climbing power of the conventional unit i, respectively;

wt为风电调度功率，Lt为调度周期t下系统预测功率；w t is the dispatching power of wind power, L t is the predicted power of the system under dispatching period t;

Figure BDA00020874949000000811
出力上限为，w t出力下限为；
Figure BDA00020874949000000811
The upper limit of output is, and the lower limit of w t output is;

wr是风电装机容量。 wr is the installed capacity of wind power.

第二阶段：second stage:

风电功率随机性成本由下式可得：The random cost of wind power can be obtained by the following formula:

E[fu(wt)]＝cwcEwc+clsEls (9)E[f u (w t )]=c wc E wc +c ls E ls (9)

式中，其中fu(wt)是第二阶段风电随机性的惩罚成本期望；Ewc和Els分别是弃风和切负荷的功率期望值；cwc和cls分别是弃风和切负荷的惩罚系数。where f u (w t ) is the expected penalty cost of wind power randomness in the second stage; E wc and E ls are the expected power values of wind curtailment and load shedding, respectively; c wc and c ls are wind curtailment and load shedding, respectively penalty factor.

如图2所示，在较坏的情况下，如果实际风电功率之和落在

Figure BDA0002087494900000098
外部，则系统备用不能平衡风电功率的随机性；此时，为保证系统的功率平衡将不得不采用切负荷或弃风。然而，考虑系统输电阻塞的处理难度来自于风电场连接在不同的系统节点上，为了更好地考虑风电随机性对系统功率平衡和输电阻塞的影响，更好的方法是能够获得每个风电场的实际风电功率；风力场景即为用于此目的的经典模型。基于风电场j的风力功率场景
Figure BDA0002087494900000099
还可以得到风电功率总和的场景，即
Figure BDA0002087494900000091
J为系统内风电场的数量。风电功率随机性对系统备用和输电阻塞的影响可以通过风电场景中的相关性来考虑。As shown in Figure 2, in the worst case, if the actual wind power sum falls within
Figure BDA0002087494900000098
Outside, the system backup cannot balance the randomness of wind power; at this time, in order to ensure the power balance of the system, load shedding or wind abandonment will have to be adopted. However, considering the difficulty of handling transmission congestion in the system comes from the fact that the wind farms are connected to different system nodes. In order to better consider the influence of the randomness of wind power on the system power balance and transmission congestion, a better method is to obtain each wind farm. actual wind power; a wind scenario is a classic model for this purpose. Wind power scenario based on wind farm j
Figure BDA0002087494900000099
The scene of the sum of wind power can also be obtained, namely
Figure BDA0002087494900000091
J is the number of wind farms in the system. The impact of wind power randomness on system backup and transmission congestion can be considered through correlations in wind power scenarios.

这样，在第二阶段中的风电功率随机性成本E[fu(wt)]可以根据风电功率场景模型写为：In this way, the wind power randomness cost E[f u (w t )] in the second stage can be written as:

Figure BDA0002087494900000092
Figure BDA0002087494900000092

Figure BDA0002087494900000093
Figure BDA0002087494900000093

式中，πs是风电功率场景s的概率；

Figure BDA0002087494900000094
是调度周期t下场景s的风电功率之和；
Figure BDA0002087494900000095
和
Figure BDA0002087494900000096
分别是场景s的切负荷和弃风功率；S为风电功率场景数量。where π s is the probability of wind power scenario s;
Figure BDA0002087494900000094
is the sum of wind power in scenario s under dispatch period t;
Figure BDA0002087494900000095
and
Figure BDA0002087494900000096
are the load shedding and wind curtailment power of scenario s, respectively; S is the number of wind power scenarios.

本实施例提出的改进仿射备用分配即以实际风电功率与风电调度功率之间的差异为基准，常规机组i按照一定的比例因子确定调度周期t下场景s的实际备用功率：The improved affine reserve allocation proposed in this embodiment is based on the difference between the actual wind power and the dispatched wind power, and the conventional unit i determines the actual reserve power of the scenario s under the dispatch period t according to a certain scaling factor:

Figure BDA0002087494900000097
Figure BDA0002087494900000097

Figure BDA0002087494900000101
Figure BDA0002087494900000101

Figure BDA0002087494900000102
Figure BDA0002087494900000102

Figure BDA0002087494900000103
Figure BDA0002087494900000103

式中，ai即常规机组i承担由风电随机性导致的系统备用的比例因子。In the formula, a i is the proportional factor for the conventional unit i to undertake the system backup caused by the randomness of wind power.

对于每个场景s的调度周期t下的输电线路l，传输容量约束如下：For the transmission line l under the scheduling period t of each scenario s, the transmission capacity constraints are as follows:

Figure BDA0002087494900000104
Figure BDA0002087494900000104

式中：Nb为系统中节点数量；l是输电线路索引；b为节点索引；

Figure BDA0002087494900000105
是输电线路l的传输容量限制；kl,b是直流潮流中的分配系数；I(b)为连接到母线b上的常规机组数量；J(b)为连接到母线b上的风电场数量；Lb,t是调度周期t下节点b的负荷需求；
Figure BDA0002087494900000106
是调度周期t下场景s的常规机组i的实际备用功率。约束条件(16)即保证了所有场景下所有调度周期均不发生输电阻塞。In the formula: N b is the number of nodes in the system; l is the transmission line index; b is the node index;
Figure BDA0002087494900000105
is the transmission capacity limit of transmission line l; k l,b is the distribution coefficient in DC power flow; I(b) is the number of conventional units connected to busbar b; J(b) is the number of wind farms connected to busbar b ; L b,t is the load demand of node b under scheduling period t;
Figure BDA0002087494900000106
is the actual standby power of conventional unit i in scenario s in scheduling period t. Constraint (16) ensures that transmission congestion does not occur in all scheduling periods in all scenarios.

这样，常规机组成本(包括燃料成本和备用成本)和风电随机性成本分别在第一阶段和第二阶段考虑。本实施例所提出的基于改进仿射备用分配的含风电电力系统经济调度方法即：In this way, conventional unit costs (including fuel costs and backup costs) and wind power random costs are considered in the first and second stages, respectively. The economic dispatch method of wind power system based on improved affine reserve allocation proposed in this embodiment is as follows:

目标函数：式(1)，(2)，(9)，(10)和(11)组成。Objective function: consists of formulas (1), (2), (9), (10) and (11).

约束条件：(3)～(8)，(12)～(16)。Constraints: (3) to (8), (12) to (16).

S3、基于线性规划求解器求解模型，确定并输出常规机组的调度结果，即调度功率和系统备用曲线。S3. Solve the model based on the linear programming solver, determine and output the dispatching result of the conventional unit, that is, dispatching power and system standby curve.

下面通过具体算例说明本实施例。The present embodiment is described below through a specific calculation example.

本算例在IEEE 118标准节点系统中验证所提出的基于改进仿射备用分配的含风电电力系统经济调度方法，系统中有2个风电场，每个容量为400MW，分别连接在第59和80节点。风电场的数据来自于美国国家可再生能源实验室(NREL)，调度时间域是一个小时，由12个调度周期组成，每个调度周期长度为5分钟。风电功率分布使用20个风电功率场景进行表征。切负荷和弃风的惩罚系数分别为1000$/MWh和80$/MWh。系统向上和向下备用预留成本系数均为10$/MWh。This example verifies the proposed economic dispatch method for power systems with wind power based on improved affine reserve allocation in the IEEE 118 standard node system. There are two wind farms in the system, each with a capacity of 400MW, which are connected to the 59th and 80th wind farms respectively. node. The data of the wind farm comes from the National Renewable Energy Laboratory (NREL) of the United States. The dispatch time domain is one hour, which consists of 12 dispatch periods, and each dispatch period is 5 minutes in length. The wind power distribution is characterized using 20 wind power scenarios. The penalty coefficients for load shedding and wind curtailment are 1000$/MWh and 80$/MWh, respectively. The reserve reserve cost factor for both the upward and downward reserve of the system is 10$/MWh.

图3展示了预测风电功率(黑色粗线)和风电功率场景(黑色细线)。基于matlab环境下的CPLEX工具箱求解所提出的基于改进仿射备用分配的含风电电力系统经济调度方法，得到风电调度功率(黑色虚线)。可以看到，所有调度周期内的风电调度功率通常低于预测风电功率，主要原因为切负荷惩罚成本系数远远大于弃风惩罚系数。Figure 3 shows the predicted wind power (thick black line) and the wind power scenario (thin black line). Based on the CPLEX toolbox in the matlab environment, the proposed economic dispatch method for wind power systems based on improved affine reserve allocation is solved, and the wind power dispatch power (black dotted line) is obtained. It can be seen that the dispatching power of wind power in all dispatching periods is usually lower than the predicted wind power power, mainly because the load shedding penalty cost coefficient is much larger than the wind abandonment penalty coefficient.

基于相同的20个风电功率场景，求解基于常规仿射备用分配的含风电电力系统经济调度方法。使用上述的20个风电功率场景，基于蒙特卡罗测试本实施例的改进仿射备用分配方法和常规仿射备用分配方法的常规机组调度功率和预留备用。如下表1所示，展示了这两种方法对应的实际系统成本。可以看到所提出的方法具备较高的燃料成本，这是因为风电调度功率通常低于风电预测功率，故在本实施例的改进仿射备用分配方法中常规机组调度功率更高，燃料成本较高，然而，由于本实施例具有低得多的切负荷和弃风损失成本，所以本实施例方法的总体系统成本明显低于常规仿射备用分配方法。Based on the same 20 wind power scenarios, the economic dispatch method of wind power system based on conventional affine reserve allocation is solved. Using the above 20 wind power scenarios, the improved affine reserve allocation method and the conventional affine reserve allocation method of the present embodiment are tested based on Monte Carlo to dispatch power and reserve reserve for conventional units. As shown in Table 1 below, the actual system costs corresponding to these two methods are shown. It can be seen that the proposed method has a higher fuel cost, because the dispatching power of wind power is usually lower than the predicted power of wind power, so in the improved affine reserve allocation method of this embodiment, the dispatching power of conventional units is higher, and the fuel cost is higher. However, since this embodiment has much lower cost of load shedding and wind curtailment losses, the overall system cost of the method of this embodiment is significantly lower than that of the conventional affine reserve allocation method.

表1、本实施例方法和常规仿射备用分配方法的社会成本算例结果Table 1. The social cost calculation example results of the method of this embodiment and the conventional affine alternate allocation method

本实施例方法The method of this embodiment 常规仿射备用分配方法Conventional Affine Alternate Allocation Method 燃料成本/$fuel cost/$ 3663536635 3595135951 备用预留成本/$Standby reservation cost/$ 26342634 26432643 切负荷成本/$Load Shed Cost/$ 31203120 41654165 弃风成本/$Wind curtailment cost/$ 52105210 62136213 总成本/$total cost/$ 4759947599 4897248972

本发明不局限于上述最佳实施方式，任何人应该得知在本发明的启示下作出的结构变化，凡是与本发明具有相同或相近的技术方案，均落入本发明的保护范围之内。The present invention is not limited to the above-mentioned best embodiment, and anyone should be aware of the structural changes made under the inspiration of the present invention, and all technical solutions that are identical or similar to the present invention fall within the protection scope of the present invention.

Claims (1)

1.一种基于改进仿射备用分配的含风电电力系统经济调度方法，其特征在于，包括以下步骤：1. an economic dispatch method for a power system containing wind power based on improved affine reserve allocation, is characterized in that, comprises the following steps: 确定系统内发电机组参数、线路参数和风电功率场景；Determine the generator set parameters, line parameters and wind power scenarios in the system; 基于改进仿射备用方法，以实际风电功率与风电调度功率之间的差异为基准，确定在实时的实际风电功率得到后的常规机组实际备用功率，建立电力系统经济调度模型；Based on the improved affine backup method, the difference between the actual wind power and the wind power dispatching power is used as the benchmark to determine the actual standby power of conventional units after the real-time actual wind power is obtained, and establish the economic dispatch model of the power system; 基于线性规划求解器求解模型，确定并输出常规机组的调度结果；Solve the model based on a linear programming solver, determine and output the scheduling results of conventional units; 系统内发电机组参数包括：出力上下限、燃料成本系数、备用成本系数、最大向上和向下爬坡功率和最大向上和向下备用能力；The parameters of the generator set in the system include: output upper and lower limits, fuel cost coefficient, backup cost coefficient, maximum upward and downward climbing power and maximum upward and downward reserve capacity; 线路参数包括：拓扑结构、最大传输容量、直流潮流分配系数；Line parameters include: topology, maximum transmission capacity, DC power flow distribution coefficient; 所述经济调度模型的目标函数是：The objective function of the economic dispatch model is: minE[f]＝fc(pi,t,ru,i,t,rd,i,t)+E[fu(wt)]minE[f]=f c (pi ,t ,r u,i,t ,r d,i,t )+E[f u (w t )] 式中，f为系统总成本；fc为系统常规机组的总成本，在第一阶段中建模，由here-and-now决策变量pi,t、ru,i,t和rd,i,t决定；pi,t为常规机组i在调度周期t的调度功率，ru,i,t和rd,i,t分别为常规机组i在调度周期t的向上和向下备用功率；In the formula, f is the total cost of the system; f c is the total cost of the conventional unit of the system, modeled in the first stage, by the here-and-now decision variables p i,t , r u,i,t and r d, i,t is decided; pi ,t is the dispatching power of the conventional unit i in the dispatching period t, r u,i,t and r d,i,t are the up and down standby power of the conventional unit i in the dispatching period t, respectively ; fu(wt)是第二阶段风电随机性的惩罚成本期望，由变量wt决定，wt为风电调度功率；f u (w t ) is the expected penalty cost of wind power randomness in the second stage, which is determined by the variable w t , which is the wind power dispatching power; 第一阶段建模具体如下：The first stage of modeling is as follows: 系统常规机组的总成本由下式可得：The total cost of the conventional unit of the system can be obtained by the following formula:
Figure FDA0003478742850000011
Figure FDA0003478742850000011
 式中，T为调度时间域为调度周期的数量，其中t＝1,2…T；I为系统内常规机组的数量，i＝1,2…I；bf,i和cf,i分别为常规机组i的燃料成本的一次项和常数项系数；cur,i和cdr,i分别为常规机组i的向上和向下备用预留成本系数；In the formula, T is the number of scheduling cycles in the scheduling time domain, where t=1,2...T; I is the number of conventional units in the system, i=1,2...I; b f,i and c f,i respectively are the primary term and constant term coefficients of the fuel cost of the conventional unit i; cur,i and cdr,i are the reserve cost coefficients for the upward and downward reserve of the conventional unit i, respectively; 约束条件为：The constraints are: ①常规机组出力累加备用约束后功率约束①Power constraint after accumulative reserve constraint of conventional unit output
Figure FDA0003478742850000021
Figure FDA0003478742850000021
Figure FDA0003478742850000022
Figure FDA0003478742850000022
 ②常规机组备用能力上限约束②The upper limit of the reserve capacity of conventional units is restricted
Figure FDA0003478742850000023
Figure FDA0003478742850000023
Figure FDA0003478742850000024
Figure FDA0003478742850000024
 ③常规机组的爬坡约束③Climbing constraints of conventional units
Figure FDA0003478742850000025
Figure FDA0003478742850000025
Figure FDA0003478742850000026
Figure FDA0003478742850000026
 ④功率平衡约束④ Power balance constraints
Figure FDA0003478742850000027
Figure FDA0003478742850000027
 ⑤风电功率随机性能被系统备用平衡对应的出力上下限的与系统备用的关系约束⑤ The random performance of wind power is constrained by the relationship between the upper and lower output limits corresponding to the system backup balance and the system backup
Figure FDA0003478742850000028
Figure FDA0003478742850000028
Figure FDA0003478742850000029
Figure FDA0003478742850000029
 ⑥风电功率随机性能被系统备用平衡对应的出力上下限约束⑥ The random performance of wind power is constrained by the upper and lower output limits corresponding to the system backup balance
Figure FDA00034787428500000210
Figure FDA00034787428500000210
 式中，
Figure FDA00034787428500000211
和pi分别为常规机组i的出力上限和下限；In the formula,
Figure FDA00034787428500000211
and pi are the upper and lower output limits of conventional unit i, respectively;
Figure FDA00034787428500000212
和
Figure FDA00034787428500000213
分别为常规机组i的向上和向下备用的上限；
Figure FDA00034787428500000212
and
Figure FDA00034787428500000213
are the upper and lower reserve upper limits of conventional unit i, respectively;
Figure FDA00034787428500000214
和
Figure FDA00034787428500000215
分别为常规机组i的最大向上和向下爬坡功率；
Figure FDA00034787428500000214
and
Figure FDA00034787428500000215
are the maximum upward and downward climbing power of the conventional unit i, respectively; wt为风电调度功率，Lt为调度周期t下系统预测功率；w t is the dispatching power of wind power, L t is the predicted power of the system under dispatching period t;
Figure FDA0003478742850000031
出力上限为，wt出力下限为；
Figure FDA0003478742850000031
The upper limit of output is, and the lower limit of wt output is; wr是风电装机容量； wr is the installed capacity of wind power; 第二阶段建模具体如下：The second stage modeling is as follows: 风电功率随机性成本由下式可得：The random cost of wind power can be obtained by the following formula: E[fu(wt)]＝cwcEwc+clsEls E[f u (w t )]=c wc E wc +c ls E ls 式中，其中fu(wt)是第二阶段风电随机性的惩罚成本期望；Ewc和Els分别是弃风和切负荷的功率期望值；cwc和cls分别是弃风和切负荷的惩罚系数；where f u (w t ) is the expected penalty cost of wind power randomness in the second stage; E wc and E ls are the expected power values of wind curtailment and load shedding, respectively; c wc and c ls are wind curtailment and load shedding, respectively The penalty coefficient of ; 所述第二阶段中的风电功率随机性成本根据风电功率场景模型写为：According to the wind power scenario model, the random cost of wind power in the second stage is written as:
Figure FDA0003478742850000032
Figure FDA0003478742850000032
Figure FDA0003478742850000033
Figure FDA0003478742850000033
Figure FDA0003478742850000034
Figure FDA0003478742850000034
Figure FDA0003478742850000035
Figure FDA0003478742850000035
 式中，πs是风电功率场景s的概率；
Figure FDA0003478742850000036
是调度周期t下场景s的风电功率之和；
Figure FDA0003478742850000037
和
Figure FDA0003478742850000038
分别是场景s的切负荷和弃风功率；S为风电功率场景数量；where π s is the probability of wind power scenario s;
Figure FDA0003478742850000036
is the sum of wind power in scenario s under dispatch period t;
Figure FDA0003478742850000037
and
Figure FDA0003478742850000038
are the load shedding and wind curtailment power of scenario s, respectively; S is the number of wind power scenarios;
Figure FDA0003478742850000039
为风电功率总和的场景，
Figure FDA00034787428500000310
为风电场j的风力功率场景，J为系统内风电场的数量；
Figure FDA0003478742850000039
is the scene of the sum of wind power,
Figure FDA00034787428500000310
is the wind power scenario of wind farm j, and J is the number of wind farms in the system; 常规机组i按照一定的比例因子确定调度周期t下场景s的实际备用功率：The conventional unit i determines the actual standby power of the scenario s under the scheduling period t according to a certain scaling factor:
Figure FDA00034787428500000311
Figure FDA00034787428500000311
Figure FDA00034787428500000312
Figure FDA00034787428500000312
Figure FDA00034787428500000313
Figure FDA00034787428500000313
Figure FDA0003478742850000041
Figure FDA0003478742850000041
 式中，ai即常规机组i承担由风电随机性导致的系统备用的比例因子；In the formula, a i is the proportional factor for the conventional unit i to undertake the system backup caused by the randomness of wind power; 对于每个场景s的调度周期t下的输电线路l，传输容量约束如下：For the transmission line l under the scheduling period t of each scenario s, the transmission capacity constraints are as follows:
Figure FDA0003478742850000042
Figure FDA0003478742850000042
 式中：Nb为系统中节点数量；l是输电线路索引；b为节点索引；Pl是输电线路l的传输容量限制；kl,b是直流潮流中的分配系数；I(b)为连接到母线b上的常规机组数量；J(b)为连接到母线b上的风电场数量；Lb,t是调度周期t下节点b的负荷需求；
Figure FDA0003478742850000043
是调度周期t下场景s的常规机组i的实际备用功率。In the formula: N b is the number of nodes in the system; l is the transmission line index; b is the node index; P l is the transmission capacity limit of the transmission line l; k l, b are the distribution coefficients in the DC power flow; I(b) is The number of conventional units connected to the busbar b; J(b) is the number of wind farms connected to the busbar b; Lb ,t is the load demand of node b in the dispatch period t;
Figure FDA0003478742850000043
is the actual standby power of conventional unit i in scenario s in scheduling period t.
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