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CN108876196B - Alternate Iterative Optimal Scheduling Method Based on Non-salient Force Characteristics of Cogeneration Units - Google Patents

Alternate Iterative Optimal Scheduling Method Based on Non-salient Force Characteristics of Cogeneration Units Download PDF

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CN108876196B
CN108876196B CN201810788403.5A CN201810788403A CN108876196B CN 108876196 B CN108876196 B CN 108876196B CN 201810788403 A CN201810788403 A CN 201810788403A CN 108876196 B CN108876196 B CN 108876196B
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陈建华
皇甫成
汪鸿
梁吉
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State Grid Corp of China SGCC
State Grid Jibei Electric Power Co Ltd
Qinhuangdao Power Supply Co of State Grid Jibei Electric Power Co Ltd
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Abstract

本发明公开了一种基于热电联产机组非凸出力特性的交替迭代优化调度方法，上述方法将每台热电联产机组的非凸出力区域划分为多个子区域，将各子区域的分段约束转化为连续的线性约束，进而建立热电联产机组非凸出力特性的有功经济调度模型，化简上述模型为针对单台热电联产机组的优化调度模型，进一步分解为供热优化调度及有功优化调度两个子模型，分别采用混合整数二次规划算法及二次规划算法求解，同时采用交替迭代法进行迭代优化，根据优化结果控制热电联产机组工作，使其有功经济调度最优，本申请适用于热电联产机组的非凸性运行特性区域，可实现热电联产机组实时在线调度。

Figure 201810788403

The invention discloses an alternate iterative optimization scheduling method based on the non-salient force characteristics of cogeneration units. The method divides the non-salient force area of each cogeneration unit into a plurality of sub-areas, and constrains the segmentation of each sub-area. Convert it into a continuous linear constraint, and then establish an active economic dispatch model with non-salient force characteristics of cogeneration units. The above model is simplified as an optimal dispatch model for a single cogeneration unit, and further decomposed into heat supply optimization dispatch and active power optimization. Scheduling two sub-models, respectively using mixed integer quadratic programming algorithm and quadratic programming algorithm to solve, at the same time using alternate iteration method for iterative optimization, control the work of the cogeneration unit according to the optimization results, so that the active power economic dispatch is optimal, this application It is suitable for the non-convex operating characteristic area of cogeneration units, and can realize real-time online scheduling of cogeneration units.

Figure 201810788403

Description

基于热电联产机组非凸出力特性的交替迭代优化调度方法Alternate Iterative Optimal Scheduling Method Based on Non-salient Force Characteristics of Cogeneration Units

技术领域technical field

本发明属于热电技术领域，特别涉及一种基于热电联产机组非凸出力特性的交替迭代优化调度方法。The invention belongs to the technical field of thermoelectricity, and in particular relates to an alternate iterative optimal scheduling method based on the non-protruding force characteristic of a cogeneration unit.

背景技术Background technique

热电联产机组不仅能够同时满足用户的热力和电力需求，而且比火电机组具有更高的能源利用效率，因此热电联产机组在电力系统中得到了大规模应用，尤其在有供暖需求的华北、东北、西北“三北”地区发展迅速，基本上所有的大型火电机组均为热电联产机组，随着热电联产机组在我国电力系统调度运行中的影响越来越大，对其电、热生产进行快速调度的要求也越来越高。Cogeneration units can not only meet the heat and power needs of users at the same time, but also have higher energy utilization efficiency than thermal power units. Therefore, cogeneration units have been widely used in power systems, especially in North China, where there is heating demand. The Northeast and Northwest "Three North" regions are developing rapidly. Basically, all large thermal power units are cogeneration units. The requirements for rapid scheduling of production are also increasing.

热电联产机组的运行特性区域既包括凸性运行特性区域，也存在大量非凸性运行特性区域，而广泛使用的优化调度方法和商用生产优化软件包只能针对凸性运行特性区域进行优化，无法适用于热电联产机组供热出力及发电出力之间存在的非凸、非线性耦合关系等特征，给现有的有功经济调度模型带来了较大挑战。The operating characteristic area of the cogeneration unit includes both convex operating characteristic areas and a large number of non-convex operating characteristic areas, while the widely used optimal scheduling methods and commercial production optimization software packages can only optimize for the convex operating characteristic areas. It cannot be applied to the non-convex and nonlinear coupling relationship between the heat supply output and the power generation output of the cogeneration unit, which brings great challenges to the existing active power economic dispatch models.

目前尚无有效方法处理这一问题，一般采用的遗传方法等人工智能方法包含以下缺陷：计算时间太长、不能达到最优结果、计算过程不可复现，无法满足实际调度应用。At present, there is no effective method to deal with this problem. Generally, artificial intelligence methods such as genetic methods have the following defects: the calculation time is too long, the optimal results cannot be achieved, the calculation process cannot be reproduced, and it cannot meet the actual scheduling application.

综上所述，已有优化调度方法和现有的人工智能方法均不能完全适用于热电联产机组供热出力及发电出力之间存在的非凸、非线性耦合关系等特征，不能满足运行结果稳定、响应速度快的调度需求。To sum up, the existing optimal scheduling methods and the existing artificial intelligence methods are not fully applicable to the non-convex and nonlinear coupling relationship between the heat supply output and the power generation output of the cogeneration unit, and cannot meet the operating results. Stable and fast-response scheduling requirements.

发明内容SUMMARY OF THE INVENTION

本发明的目的在于提供一种基于热电联产机组非凸出力特性的交替迭代优化调度方法，该方法能够适用于热电联产机组的非凸性运行特性区域，实现电力生产的快速、准确调度，达到在线调度应用的水准，具体技术方案为：The purpose of the present invention is to provide an alternate iterative optimization scheduling method based on the non-convex force characteristics of the cogeneration unit, which can be applied to the non-convex operating characteristic area of the cogeneration unit, and realizes the rapid and accurate scheduling of power production, To achieve the level of online scheduling application, the specific technical solutions are:

一种基于热电联产机组非凸出力特性的交替迭代优化调度方法，包括以下步骤：An alternate iterative optimization scheduling method based on the non-salient force characteristics of a cogeneration unit, comprising the following steps:

S1，根据每台热电联产机组的出力特性曲线，将所述出力特性曲线中的非凸出力区域划分为多个子区域；S1, according to the output characteristic curve of each cogeneration unit, divide the non-protruding force area in the output characteristic curve into a plurality of sub-areas;

S2，根据每台热电联产机组在各子区域的出力特性，将每个热电联产机组在各子区域的分段约束转化为所在区域的连续线性约束；S2, according to the output characteristics of each cogeneration unit in each subregion, transform the segmental constraints of each cogeneration unit in each subregion into a continuous linear constraint in the region;

S3，基于转化后的连续线性约束，建立热电联产机组非凸出力特性的有功经济调度模型；S3, based on the transformed continuous linear constraints, establish an active power economic dispatch model for the non-salient force characteristics of the cogeneration unit;

Figure BDA0001734235910000021
Figure BDA0001734235910000021

其中，

Figure BDA0001734235910000022
为火电机组的运行成本，in,
Figure BDA0001734235910000022
is the operating cost of the thermal power unit,

Figure BDA0001734235910000023
为热电联产机组的运行成本；pi为火电机组i的有功出力；pj、hj分别为热电联产机组j的有功出力及供热出力；n、m分别代表火电机组及热电联产机组的总台数；ai,bi,ci为火电机组i的成本系数；aj,bj,cj,dj,ej,fj,gj为热电联产机组j的成本系数；D为系统负荷需求；S为系统供热需求；
Figure BDA0001734235910000024
pi分别为火电机组i的有功出力上下限；
Figure BDA0001734235910000025
TLα分别为输电断面α传输容量的上下限；L为输电断面总个数；kαi为火电机组i对输电断面α的灵敏度系数；kαj为热电联产机组j对输电断面α的灵敏度系数；表达式(6.1)表示有功经济调度模型以系统中火电机组及热电联产机组的运行成本之和最小为目标，表达式(6.2)表示系统发电负荷平衡约束；表达式(6.3)表示系统供热平衡约束；表达式(6.4)表示发电机组出力上下限约束；表达式(6.5)表示输电断面传输容量约束；表达式(6.6)表示热电联产机组的出力特性约束，即表达式(5)；
Figure BDA0001734235910000023
is the operating cost of the cogeneration unit; p i is the active power output of the thermal power unit i; p j and h j are the active power output and heat supply output of the cogeneration unit j, respectively; n and m represent the thermal power unit and the cogeneration unit, respectively The total number of units; a i , b i , c i are the cost coefficients of thermal power unit i; a j , b j , c j , d j , e j , f j , g j are the cost coefficients of cogeneration unit j ; D is the system load demand; S is the system heating demand;
Figure BDA0001734235910000024
p i are the upper and lower limits of active power output of thermal power unit i, respectively;
Figure BDA0001734235910000025
TL α are the upper and lower limits of transmission capacity of transmission section α; L is the total number of transmission sections; k αi is the sensitivity coefficient of thermal power unit i to transmission section α; k αj is the sensitivity coefficient of cogeneration unit j to transmission section α ; Expression (6.1) indicates that the active power economic dispatch model takes the minimum sum of the operating costs of thermal power units and cogeneration units in the system as the goal, expression (6.2) indicates the system power generation load balance constraint; expression (6.3) indicates that the system supply The heat balance constraint; expression (6.4) represents the upper and lower limit constraints of the output of the generator set; expression (6.5) represents the transmission capacity constraint of the transmission section; expression (6.6) represents the output characteristic constraint of the cogeneration unit, that is, the expression (5) ;

S4，采用拉格朗日松弛法将有功经济调度模型转换为各台热电联产机组的单机调度模型之和；S4, using the Lagrangian relaxation method to convert the active power economic dispatch model into the sum of the single-unit dispatch models of each cogeneration unit;

S5，对每一个所述单机调度模型，将其分解为供热优化调度模型及有功优化调度模型，分别采用混合整数二次规划法和二次规划法求解，并通过迭代过程获得最优供热出力值和最优有功出力值；S5, for each of the single-machine scheduling models, decompose it into a heating optimal scheduling model and an active power optimal scheduling model, use the mixed integer quadratic programming method and the quadratic programming method to solve the problem, and obtain the optimal supply through an iterative process. Thermal output value and optimal active power output value;

S6，利用所述最优供热出力值和所述最优有功出力值控制各台热电联产机组进行供热出力和有功出力工作，获得热电联产机组有功经济调度最优曲线。S6, using the optimal heat supply output value and the optimal active power output value to control each cogeneration unit to perform heat supply output and active power output work, and obtain an optimal curve for active economic dispatch of the cogeneration unit.

优选的，步骤S1具体为：Preferably, step S1 is specifically:

S11、建立热电联产机组的非凸非线性区域表达式：S11. Establish the non-convex nonlinear region expression of the cogeneration unit:

Figure BDA0001734235910000031
Figure BDA0001734235910000031

Figure BDA00017342359100000313
Figure BDA00017342359100000313

其中，

Figure BDA0001734235910000032
分别为热电联产机组j的有功出力上下限；
Figure BDA0001734235910000033
分别为热电联产机组j的供热出力上下限；in,
Figure BDA0001734235910000032
are the upper and lower limits of the active power output of the cogeneration unit j, respectively;
Figure BDA0001734235910000033
are the upper and lower limits of the heating output of the cogeneration unit j, respectively;

S12、将热电联产机组j的出力区域划分为nj个子区域；其中，各子区域均视为凸区域；对第l个区域来说，热电联产机组的出力特性表示为如下形式：S12. Divide the output area of the cogeneration unit j into n j sub-areas; among them, each sub-area is regarded as a convex area; for the lth area, the output characteristic of the cogeneration unit is expressed as the following form:

Figure BDA0001734235910000034
Figure BDA0001734235910000034

其中，k、

Figure BDA0001734235910000035
β、
Figure BDA0001734235910000036
分别为热电耦合关系系数；
Figure BDA0001734235910000037
分别为第l个区域供热出力的上、下限；Among them, k,
Figure BDA0001734235910000035
β,
Figure BDA0001734235910000036
are the thermoelectric coupling coefficients, respectively;
Figure BDA0001734235910000037
are the upper and lower limits of the heating output of the lth district, respectively;

对所有nj个子区域来说，热电联产机组j的出力特性表示为如下形式：For all n j sub-regions, the output characteristics of cogeneration unit j are expressed as follows:

Figure BDA0001734235910000038
Figure BDA0001734235910000038

优选的，步骤S2具体为：Preferably, step S2 is specifically:

将表达式(4)所示的分段线性约束进一步转化为连续线性约束：The piecewise linear constraint shown in expression (4) is further transformed into a continuous linear constraint:

Figure BDA0001734235910000039
Figure BDA0001734235910000039

其中，M为一个大正数，取值为

Figure BDA00017342359100000310
xj,l为0-1二进制变量。Among them, M is a large positive number, and the value is
Figure BDA00017342359100000310
x j,l is a 0-1 binary variable.

优选的，所述S4具体为：Preferably, the S4 is specifically:

将表达式(6)进行简化：Simplify expression (6):

Figure BDA00017342359100000311
Figure BDA00017342359100000311

其中，inf{}为表达式的下确界；De代表单机约束，包括约束表达式(6.4)和(6.6)；

Figure BDA00017342359100000312
wα ,v,η为拉格朗日松弛因子；C为常数；Among them, inf{} is the infimum of the expression; D e represents the stand-alone constraint, including constraint expressions (6.4) and (6.6);
Figure BDA00017342359100000312
w α , v, η are Lagrangian relaxation factors; C is a constant;

表达式(8)右侧为各台热电联合机组优化目标函数之和的形式，热电联合机组有功经济调度模型最终等效为对多台热电联产机组的优化调度。The right side of expression (8) is the form of the sum of the optimization objective functions of each combined heat and power unit. The economic dispatch model of active power of combined heat and power units is ultimately equivalent to the optimal scheduling of multiple combined heat and power units.

优选的，步骤S5具体为：Preferably, step S5 is specifically:

火电机组及热电联产机组的优化调度模型分别表示为表达式(9)和(10)：The optimal scheduling models of thermal power units and cogeneration units are expressed as expressions (9) and (10), respectively:

Figure BDA0001734235910000041
Figure BDA0001734235910000041

Figure BDA0001734235910000042
Figure BDA0001734235910000042

对表达式(9)，利用二次规划法，通过比较目标函数对称轴及机组有功出力上下限的方式直接求解最优解，即：For expression (9), the quadratic programming method is used to directly solve the optimal solution by comparing the symmetry axis of the objective function and the upper and lower limits of the active power output of the unit, namely:

Figure BDA0001734235910000043
Figure BDA0001734235910000043

表达式(10)中的f(pj,hj)函数中含有双线性项pjhj，将其分解为表达式(12)和(13)两个子优化模型：The f(p j , h j ) function in expression (10) contains bilinear term p j h j , which is decomposed into two sub-optimization models of expressions (12) and (13):

Figure BDA0001734235910000044
Figure BDA0001734235910000044

Figure BDA0001734235910000045
Figure BDA0001734235910000045

其中，表达式(12)为供热优化调度子模型，表达式(13)为有功优化调度子模型；对表达式(12)、(13)采用如下交替迭代方法进行求解：Among them, expression (12) is the heating optimization scheduling sub-model, and expression (13) is the active power optimization scheduling sub-model; expressions (12) and (13) are solved by the following alternate iteration method:

在第k次迭代过程中，机组j的有功出力设定为第k-1次优化结果

Figure BDA0001734235910000046
采用混合整数二次规划方法求解优化模型表达式(12)，获得机组j的最优供热出力
Figure BDA0001734235910000047
及变量xj,l的值
Figure BDA0001734235910000048
然后，将机组的最优供热出力及二进制变量xj,l分别设定为
Figure BDA0001734235910000049
对优化模型表达式(13)，采用二次规划法，通过比较目标函数对称轴及机组有功出力上下限的方式直接求解最优解，求解最优供热出力和求解最优有功出力的迭代过程反复进行，直到优化目标函数不再下降为止。In the kth iteration process, the active power output of unit j is set as the k-1th optimization result
Figure BDA0001734235910000046
The mixed integer quadratic programming method is used to solve the optimization model expression (12), and the optimal heating output of unit j is obtained.
Figure BDA0001734235910000047
and the value of the variables x j,l
Figure BDA0001734235910000048
Then, the optimal heating output of the unit and the binary variables x j, l are respectively set as
Figure BDA0001734235910000049
For the optimization model expression (13), the quadratic programming method is used to directly solve the optimal solution by comparing the symmetry axis of the objective function and the upper and lower limits of the active power output of the unit, and the iterative process of solving the optimal heating output and solving the optimal active power output Iterate until the optimization objective function no longer decreases.

优选的，步骤S6具体为：Preferably, step S6 is specifically:

根据所述有功经济调度模型最终迭代优化结果控制各台热电联产机组进行工作，使得热电联产机组有功经济调度最优。According to the final iterative optimization result of the active power economic dispatch model, each cogeneration unit is controlled to work, so that the active power economic dispatch of the cogeneration unit is optimized.

本发明的有益效果是：The beneficial effects of the present invention are:

本发明将交替迭代方法应用于热电联产机组有功经济调度中，能适用于热电联产机组供热出力及发电出力之间存在的非凸、非线性耦合特性，解决了现有方法运行过程中所存在的计算时间太长、不能获得最优结果、计算过程不可复现问题，既提高了求解效率，又能获得可验证的最优结果，实现在线应用的目标。The invention applies the alternate iterative method to the active power economic dispatch of the cogeneration unit, can be applied to the non-convex and nonlinear coupling characteristics existing between the heat supply output and the power generation output of the cogeneration unit, and solves the problem of the existing method in the operation process. The existing problems are that the calculation time is too long, the optimal results cannot be obtained, and the calculation process cannot be reproduced, which not only improves the solution efficiency, but also obtains verifiable optimal results, and achieves the goal of online application.

附图说明Description of drawings

图1为热电联产机组非凸出力特性的交替迭代优化调度方法的流程图；Fig. 1 is the flow chart of the alternate iterative optimal scheduling method of the non-salient force characteristic of the cogeneration unit;

图2为250MW热电联产机组的出力特性示意图。Figure 2 is a schematic diagram of the output characteristics of the 250MW cogeneration unit.

具体实施方法Specific implementation method

下面结合附图对本发明做进一步说明。The present invention will be further described below with reference to the accompanying drawings.

如图1所示，本发明提供一种基于热电联产机组非凸出力特性的交替迭代优化调度方法，包括以下步骤：As shown in FIG. 1 , the present invention provides an alternate iterative optimization scheduling method based on the non-protruding force characteristics of a cogeneration unit, including the following steps:

步骤(1)：根据每台热电联产机组的出力特性曲线，将出力特性曲线中的非凸出力区域划分为多个子区域。Step (1): According to the output characteristic curve of each cogeneration unit, the non-protruding force area in the output characteristic curve is divided into a plurality of sub-areas.

本步骤中，图2为某型250MW热电联产机组的典型出力特性曲线，其出力特性为非凸非线性区域，建立热电联产机组的非凸非线性区域表达式：In this step, Figure 2 is a typical output characteristic curve of a certain type of 250MW cogeneration unit. Its output characteristic is a non-convex nonlinear region. The non-convex nonlinear region expression of the cogeneration unit is established:

Figure BDA0001734235910000051
Figure BDA0001734235910000051

Figure BDA0001734235910000052
Figure BDA0001734235910000052

其中，pj、hj分别为热电联产机组j的有功出力及供热出力。

Figure BDA0001734235910000053
分别为热电联产机组j的有功出力上下限；
Figure BDA0001734235910000054
分别为热电联产机组j的供热出力上下限。Among them, p j and h j are the active power output and heating output of the cogeneration unit j, respectively.
Figure BDA0001734235910000053
are the upper and lower limits of the active power output of the cogeneration unit j, respectively;
Figure BDA0001734235910000054
are the upper and lower limits of the heat output of the cogeneration unit j, respectively.

由表达式(1)、(2)两式可见，热电联产机组j的有功出力限值为供热出力的函数，同时，供热出力限值也为有功出力的函数。It can be seen from the expressions (1) and (2) that the active power output limit of the cogeneration unit j is a function of the heating output, and at the same time, the heating output limit is also a function of the active power output.

将热电联产机组j的出力区域进行分段，划分为nj个子区域。其中，视各子区域为凸区域。对第l个区域来说，热电联产机组的出力特性表示为如下形式：The output area of cogeneration unit j is segmented and divided into n j sub-areas. Among them, each sub-region is regarded as a convex region. For the lth area, the output characteristics of the cogeneration unit are expressed as follows:

Figure BDA0001734235910000061
Figure BDA0001734235910000061

其中，k、

Figure BDA0001734235910000062
β、
Figure BDA0001734235910000063
分别为热电耦合关系系数。
Figure BDA0001734235910000064
分别为第l个区域供热出力的上、下限。Among them, k ,
Figure BDA0001734235910000062
β ,
Figure BDA0001734235910000063
are the thermoelectric coupling coefficients, respectively.
Figure BDA0001734235910000064
are the upper and lower limits of the heating output of the lth district, respectively.

对所有nj个子区域来说，热电联产机组j的出力特性表示为如下形式：For all n j sub-regions, the output characteristics of cogeneration unit j are expressed as follows:

Figure BDA0001734235910000065
Figure BDA0001734235910000065

步骤(2)：根据每台热电联产机组在各子区域的出力特性，将每个热电联产机组在各子区域的分段约束转化为所在区域的连续线性约束。Step (2): According to the output characteristics of each cogeneration unit in each subregion, transform the segmental constraints of each cogeneration unit in each subregion into a continuous linear constraint in the region.

本步骤中，基于大M法，将表达式(4)中的分段线性约束进一步转化为连续线性约束：In this step, based on the big M method, the piecewise linear constraints in expression (4) are further transformed into continuous linear constraints:

Figure BDA0001734235910000066
Figure BDA0001734235910000066

其中，M为一个大正数，取值为

Figure BDA0001734235910000067
xj,l为0-1二进制变量。Among them, M is a large positive number, and the value is
Figure BDA0001734235910000067
x j,l is a 0-1 binary variable.

步骤(3)：基于转化后的连续线性约束，建立热电联产机组非凸出力特性的有功经济调度模型。Step (3): Based on the transformed continuous linear constraints, establish an active power economic dispatch model with non-salient force characteristics of the cogeneration unit.

本步骤中，考虑电力系统发电负荷平衡约束、供热负荷平衡约束、发电机出力上下限约束、系统断面潮流安全约束及表达式(5)所述的热电联产机组出力特性约束，同时，以系统运行成本最小为目标函数，建立如下考虑热电联产机组非凸出力特性的有功经济调度模型，该模型类型为混合整数非线性规划模型：In this step, the power generation load balance constraints, heating load balance constraints, generator output upper and lower limit constraints, system cross-section power flow safety constraints and the cogeneration unit output characteristic constraints described in Expression (5) are considered. The minimum operating cost of the system is the objective function, and the following active economic dispatch model considering the non-salient force characteristics of the cogeneration unit is established. The model type is a mixed integer nonlinear programming model:

Figure BDA0001734235910000071
Figure BDA0001734235910000071

其中，

Figure BDA0001734235910000072
为火电机组的运行成本，
Figure BDA0001734235910000073
为热电联产机组的运行成本；pi为火电机组i的有功出力；pj、hj分别为热电联产机组j的有功出力及供热出力；n、m分别代表火电机组及热电联产机组的总台数；ai,bi,ci为火电机组i的成本系数；aj,bj,cj,dj,ej,fj,gj为热电联产机组j的成本系数；D为系统负荷需求；S为系统供热需求；
Figure BDA0001734235910000074
pi分别为火电机组i的有功出力上下限；
Figure BDA0001734235910000075
TLα分别为输电断面α传输容量的上下限；L为输电断面总个数；kαi为火电机组i对输电断面α的灵敏度系数；kαj为热电联产机组j对输电断面α的灵敏度系数；表达式(6.1)表示有功经济调度模型以系统中火电机组及热电联产机组的运行成本之和最小为目标，表达式(6.2)表示系统发电负荷平衡约束；表达式(6.3)表示系统供热平衡约束；表达式(6.4)表示发电机组出力上下限约束；表达式(6.5)表示输电断面传输容量约束；表达式(6.6)表示热电联产机组的出力特性约束，即表达式(5)。in,
Figure BDA0001734235910000072
is the operating cost of the thermal power unit,
Figure BDA0001734235910000073
is the operating cost of the cogeneration unit; p i is the active power output of the thermal power unit i; p j and h j are the active power output and heat supply output of the cogeneration unit j, respectively; n and m represent the thermal power unit and the cogeneration unit, respectively The total number of units; a i , b i , c i are the cost coefficients of thermal power unit i; a j , b j , c j , d j , e j , f j , g j are the cost coefficients of cogeneration unit j ; D is the system load demand; S is the system heating demand;
Figure BDA0001734235910000074
p i are the upper and lower limits of active power output of thermal power unit i, respectively;
Figure BDA0001734235910000075
TL α are the upper and lower limits of transmission capacity of transmission section α; L is the total number of transmission sections; k αi is the sensitivity coefficient of thermal power unit i to transmission section α; k αj is the sensitivity coefficient of cogeneration unit j to transmission section α ; Expression (6.1) indicates that the active power economic dispatch model takes the minimum sum of the operating costs of thermal power units and cogeneration units in the system as the goal, expression (6.2) indicates the system power generation load balance constraint; expression (6.3) indicates that the system supply The heat balance constraint; expression (6.4) represents the upper and lower limit constraints of the output of the generator set; expression (6.5) represents the transmission capacity constraint of the transmission section; expression (6.6) represents the output characteristic constraint of the cogeneration unit, that is, the expression (5) .

步骤(4)：采用拉格朗日松弛法将有功经济调度模型转换为各台热电联产机组的单机调度模型之和。Step (4): Using the Lagrangian relaxation method to convert the active power economic dispatch model into the sum of the single-unit dispatch models of each cogeneration unit.

本步骤中，建立表达式(6)的拉格朗日对偶表达式如下：In this step, the Lagrangian dual expression of Expression (6) is established as follows:

Figure BDA0001734235910000076
Figure BDA0001734235910000076

其中，inf{}为表达式的下确界；De代表单机约束，包括约束(6.4)及(6.6)；

Figure BDA0001734235910000077
wα,v,η为拉格朗日松弛因子。Among them, inf{} is the infimum of the expression; D e represents the stand-alone constraint, including constraints (6.4) and (6.6);
Figure BDA0001734235910000077
w α , v, η are Lagrangian relaxation factors.

进一步将表达式(7)表示为如下形式：The expression (7) is further expressed as the following form:

Figure BDA0001734235910000081
Figure BDA0001734235910000081

其中，C为常数。表达式(8)右侧为各台热电联合机组优化目标函数之和的形式。最终，将热电联产机组非凸出力特性的有功经济调度模型分解为对多台热电联产机组的优化调度。where C is a constant. The right side of expression (8) is the form of the sum of the optimization objective functions of each combined heat and power unit. Finally, the active power economic dispatch model of non-salient force characteristics of cogeneration units is decomposed into optimal dispatching of multiple cogeneration units.

步骤(5)：对每一个单机调度模型，将其分解为供热优化调度模型及有功优化调度模型，分别采用混合整数二次规划法和二次规划法求解，并通过迭代过程获得最优供热出力值和最优有功出力值。Step (5): For each single-machine scheduling model, it is decomposed into a heating optimal scheduling model and an active power optimal scheduling model, which are solved by the mixed integer quadratic programming method and the quadratic programming method respectively, and the optimal scheduling model is obtained through an iterative process. Heating output value and optimal active power output value.

本步骤中，火电机组及热电联产机组的优化调度模型分别表示为表达式(9)和(10)：In this step, the optimal scheduling models of thermal power units and cogeneration units are expressed as expressions (9) and (10), respectively:

Figure BDA0001734235910000082
Figure BDA0001734235910000082

Figure BDA0001734235910000083
Figure BDA0001734235910000083

对表达式(9)，利用二次规划法，通过比较目标函数对称轴及机组有功出力上下限的方式直接求解最优解，即：For expression (9), the quadratic programming method is used to directly solve the optimal solution by comparing the symmetry axis of the objective function and the upper and lower limits of the active power output of the unit, namely:

Figure BDA0001734235910000084
Figure BDA0001734235910000084

表达式(10)的f(pj,hj)函数中含有双线性项pjhj，现有优化算法无法直接求解，在本步骤中，将其分解为表达式(12)和(13)两个子优化模型：The f(p j , h j ) function of expression (10) contains bilinear term p j h j , which cannot be solved directly by existing optimization algorithms. In this step, it is decomposed into expressions (12) and ( 13) Two sub-optimization models:

Figure BDA0001734235910000085
Figure BDA0001734235910000085

Figure BDA0001734235910000086
Figure BDA0001734235910000086

其中，表达式(12)为供热优化优化调度子模型，表达式(13)为有功优化调度子模型；对表达式(12)、(13)采用如下交替迭代方法进行求解：Among them, expression (12) is the optimal scheduling sub-model for heating optimization, and expression (13) is the optimal scheduling sub-model for active power; expressions (12) and (13) are solved by the following alternate iteration method:

在第k次迭代过程中，机组j的有功出力设定为第k-1次优化结果

Figure BDA0001734235910000091
优化模型表达式(12)将变为混合整数二次优化模型，采用混合整数二次规划方法求解获得机组j的最优供热出力
Figure BDA0001734235910000092
及变量xj,l的值
Figure BDA0001734235910000093
然后，将机组的最优供热出力及二进制变量xj,l分别设定为
Figure BDA0001734235910000094
优化模型表达式(13)将变为二次规划模型，通过比较目标函数对称轴及机组有功出力上下限的方式直接求解最优解，求解最优供热出力和求解最优有功出力的迭代过程反复进行，直到优化目标函数不再下降为止。In the kth iteration process, the active power output of unit j is set as the k-1th optimization result
Figure BDA0001734235910000091
The optimization model expression (12) will become a mixed integer quadratic optimization model, and the mixed integer quadratic programming method is used to obtain the optimal heating output of unit j.
Figure BDA0001734235910000092
and the value of the variables x j,l
Figure BDA0001734235910000093
Then, the optimal heating output of the unit and the binary variables x j, l are respectively set as
Figure BDA0001734235910000094
The optimization model expression (13) will become a quadratic programming model, and the optimal solution is directly solved by comparing the symmetry axis of the objective function and the upper and lower limits of the active power output of the unit, and the iterative process of solving the optimal heating output and solving the optimal active power output Iterate until the optimization objective function no longer decreases.

步骤(6)：利用最优供热出力值和所述最优有功出力值控制各台热电联产机组进行供热出力和有功出力工作，获得热电联产机组有功经济调度最优曲线。Step (6): using the optimal heat supply output value and the optimal active power output value to control each cogeneration unit to perform heat supply and active power output work, and obtain the optimal curve of active economic dispatch of the cogeneration unit.

本步骤中，按照本发明所提方法进行求解完毕后，控制每一台热电联产机组根据优化结果进行调度工作，在满足供热出力和有功出力要求的前提下，合理利用能源和设备，实现成本最低化。In this step, after the solution is completed according to the method of the present invention, each cogeneration unit is controlled to perform scheduling work according to the optimization results, and on the premise of satisfying the requirements of heat supply output and active power output, rationally use energy and equipment to achieve Cost minimization.

对本发明所提方法优化效果验证如下：The optimization effect of the proposed method is verified as follows:

验证系统包括一台火电机组、两台热电联产机组、一台纯供热机组。调度过程所需满足的条件为系统负荷需求200MW、供热需求115MWth，M取值为106。本发明计算结果如表1所示。The verification system includes one thermal power unit, two cogeneration units, and one pure heating unit. The conditions to be satisfied in the dispatching process are that the system load demand is 200MW, the heating demand is 115MWth, and the value of M is 10 6 . The calculation results of the present invention are shown in Table 1.

表1本发明方法与遗传算法计算结果比较Table 1 Comparison of the method of the present invention and the calculation result of genetic algorithm

Figure BDA0001734235910000095
Figure BDA0001734235910000095

由上表可见，本发明方法与遗传算法相比，系统运行成本更低；同时，本发明方法在计算时间上也明显快于遗传算法，证明了本发明方法的有效性，本发明方法可实现在线实时调度。It can be seen from the above table that the system operation cost of the method of the present invention is lower than that of the genetic algorithm; at the same time, the calculation time of the method of the present invention is also significantly faster than that of the genetic algorithm, which proves the effectiveness of the method of the present invention, and the method of the present invention can realize Online real-time scheduling.

以上所述是本申请的优选实施方式，应当指出，对于该技术领域的普通技术人员来说，在不脱离本技术原理前提下，还可以做出若干改进和润饰，这些改进和润饰也应视为本申请的保护范围。The above are the preferred embodiments of the present application. It should be pointed out that for those of ordinary skill in the technical field, some improvements and modifications can be made without departing from the principles of the present technology, and these improvements and modifications should also be regarded as The protection scope of this application.

Claims (5)

1. An alternating iteration optimization scheduling method based on the non-protrusion force characteristic of a cogeneration unit is characterized by comprising the following steps:
s1, dividing a non-protrusion force area in the output characteristic curve into a plurality of sub-areas according to the output characteristic curve of each cogeneration unit;
s2, converting the segmented constraint of each cogeneration unit in each subregion into continuous linear constraint of the region according to the output characteristic of each cogeneration unit in each subregion;
s3, establishing an active economic dispatching model of the non-protrusion force characteristic of the cogeneration unit based on the converted continuous linear constraint;
Figure FDA0003160443900000011
wherein,
Figure FDA0003160443900000012
in order to reduce the operating cost of the thermal power generating unit,
Figure FDA0003160443900000013
the running cost of the cogeneration unit; p is a radical ofiThe power output is the active power output of the thermal power generating unit i; p is a radical ofj、hjRespectively the active output and the heat supply output of the cogeneration unit j; n and m respectively represent the total number of the thermal power generating units and the cogeneration units; a isi,bi,ciThe cost coefficient is the cost coefficient of the thermal power generating unit i; a isj,bj,cj,dj,ej,fj,gjThe cost coefficient of the cogeneration unit j; d is the system load requirement; s is the heat supply requirement of the system;
Figure FDA0003160443900000014
p irespectively representing the upper limit and the lower limit of the active output of the thermal power generating unit i;
Figure FDA0003160443900000015
αTLrespectively the upper and lower limits of the alpha transmission capacity of the transmission section; l is the total number of the transmission sections; k is a radical ofαiThe sensitivity coefficient of the thermal power generating unit i to the power transmission section alpha is obtained; k is a radical ofαjThe sensitivity coefficient of the cogeneration unit j to the transmission section alpha is shown; the expression (6.1) represents that the active economic dispatching model aims at minimizing the sum of the operating costs of a thermal power unit and a cogeneration unit in the system, and the expression (6.2) represents the system power generation load balance constraint; expression (6.3) tableShowing the heat supply balance constraint of the system; an expression (6.4) represents the upper and lower output limit constraints of the generator set; the expression (6.5) represents transmission capacity constraint of a power transmission section; the expression (6.6) represents the output characteristic constraint of the cogeneration unit;
s4, converting the active economic dispatching model into the sum of the single dispatching models of all the cogeneration units by adopting a Lagrange relaxation method;
s5, decomposing each single machine scheduling model into a heat supply optimization scheduling model and an active optimization scheduling model, respectively solving by adopting a mixed integer quadratic programming method and a quadratic programming method, and obtaining an optimal heat supply output value and an optimal active output value through an iteration process;
the optimal scheduling models of the thermal power generating unit and the cogeneration unit are respectively expressed as expressions (9) and (10):
Figure FDA0003160443900000021
Figure FDA0003160443900000022
and (3) directly solving the optimal solution of the expression (9) by utilizing a quadratic programming method and comparing the target function symmetry axis with the upper limit and the lower limit of the active output of the unit, namely:
Figure FDA0003160443900000023
f (p) in expression (10)j,hj) The function containing bilinear terms pjhjIt is decomposed into two sub-optimization models of expressions (12) and (13):
Figure FDA0003160443900000024
Figure FDA0003160443900000025
the expression (12) is a heat supply optimization scheduling submodel, and the expression (13) is an active optimization scheduling submodel; solving the expressions (12) and (13) by adopting the following alternative iteration method:
in the k iteration process, the active output of the unit j is set as the k-1 suboptimal result
Figure FDA0003160443900000026
Solving an optimized model expression (12) by adopting a mixed integer quadratic programming method to obtain the optimal heat supply output of the unit j
Figure FDA0003160443900000027
And variable xj,lValue of (A)
Figure FDA0003160443900000028
Then, the optimal heat supply output of the unit and the binary variable xj,lAre respectively set as
Figure FDA0003160443900000029
For the optimization model expression (13), a quadratic programming method is adopted, an optimal solution is directly solved by comparing the symmetry axis of the objective function with the upper limit and the lower limit of the active output of the unit, and the iterative process of solving the optimal heat supply output and the optimal active output is repeatedly carried out until the optimization objective function is not reduced any more;
and S6, controlling each cogeneration unit to perform heating output and active output work by using the optimal heating output value and the optimal active output value, and obtaining an optimal active economic dispatching curve of the cogeneration unit.
2. The alternating iterative optimization scheduling method based on the non-protrusion force characteristic of the cogeneration unit according to claim 1, wherein the step S1 specifically comprises:
s11, establishing a non-convex non-linear region expression of the cogeneration unit:
Figure FDA0003160443900000031
Figure FDA0003160443900000032
wherein,
Figure FDA0003160443900000033
respectively the upper and lower limits of the active output of the cogeneration unit j;
Figure FDA0003160443900000034
respectively the upper and lower limits of the heat output of the cogeneration unit j;
s12, dividing the output area of the cogeneration unit j into njA sub-region; wherein each subregion is regarded as a convex region; for the l-th zone, the output characteristics of the cogeneration unit are expressed in the form:
Figure FDA0003160443900000035
wherein,k、
Figure FDA0003160443900000036
β、
Figure FDA0003160443900000037
are the coefficients of the thermoelectric coupling relationship, respectively;
Figure FDA0003160443900000038
the upper limit and the lower limit of the heating output of the first area are respectively set;
for all njOutput characteristic table of cogeneration unit j for sub-regionShown in the following form:
Figure FDA0003160443900000039
3. the alternating iterative optimization scheduling method based on the non-protrusion force characteristic of the cogeneration unit according to claim 1, wherein the step S2 specifically comprises:
the piecewise linear constraint shown in expression (4) is further converted into a continuous linear constraint:
Figure FDA00031604439000000310
wherein M is a large positive number, and takes the value of
Figure FDA00031604439000000311
xj,lIs a binary variable from 0 to 1.
4. The alternating iterative optimization scheduling method based on the non-protrusion force characteristic of the cogeneration unit according to claim 1, wherein the step S4 specifically comprises:
expression (6) is simplified:
Figure FDA0003160443900000041
wherein inf { } is the infimum boundary of the expression; deRepresenting a standalone constraint, including constraint expressions (6.4) and (6.6);
Figure FDA0003160443900000042
αwv, η are lagrangian relaxation factors; c is a constant;
the right side of the expression (8) is a form of the sum of the optimization objective functions of all the combined heat and power units, and the active economic dispatching model of the combined heat and power units is finally equivalent to the optimal dispatching of a plurality of combined heat and power units.
5. The alternating iterative optimization scheduling method based on the non-protrusion force characteristic of the cogeneration unit according to claim 1, wherein the step S6 specifically comprises:
and controlling each cogeneration unit to work according to the final iterative optimization result of the active economic scheduling model, so that the active economic scheduling of the cogeneration units is optimal.
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