技术领域technical field
本发明涉及电力系统经济调度技术领域，特别涉及一种针对大规模经济调度问题的粒计算方法。The invention relates to the technical field of power system economic dispatching, in particular to a granular computing method for large-scale economic dispatching problems.
背景技术Background technique
经济调度以全网的供电成本或能耗最低为目标函数，按照等微增率法和协调方程式进行调度，是实现电力系统经济运行的重要工具，是运行环节中的一种科学方法，也是迄今为止世界各个国家所普遍采用的一种调度原则。目前，对于大电网的在线经济调度研究主要遇到的问题是数据量大，采集运算的时间周期长，难以实时反映电网运行情况从而使实现经济调度变得困难。电力系统经济调度是一个高维、非凸、非线性的有约束优化问题，因此对该问题的求解尤其是相互耦合约束条件的处理十分困难。我国电力系统长期坚持集中调度。集中调度将使电力系统经济调度的求解更加困难，亟需找出一种大电网经济调度求解的有效方法。所以，对大电网经济调度的求解问题的研究具有重要意义。Economic dispatch takes the lowest power supply cost or energy consumption of the whole network as the objective function, and dispatches according to the equal micro-increase rate method and the coordination equation. It is an important tool to realize the economic operation of the power system and a scientific method in the operation link. It is a scheduling principle generally adopted by various countries in the world. At present, the main problems encountered in the online economic dispatching research of large power grids are the large amount of data, the long time period of acquisition and calculation, and the difficulty of reflecting the operation of the power grid in real time, which makes it difficult to realize economic dispatching. Power system economic dispatch is a high-dimensional, non-convex, nonlinear constrained optimization problem, so it is very difficult to solve this problem, especially to deal with the mutual coupling constraints. my country's power system has long insisted on centralized dispatching. Centralized dispatch will make it more difficult to solve the economic dispatch of the power system, and it is urgent to find an effective method to solve the economic dispatch of large power grids. Therefore, it is of great significance to study the solution problem of large power grid economic dispatching.
发明内容Contents of the invention
本发明目的在于提供一种采用分层方法将经济调度问题分解为多层以减少计算复杂程度、缩短计算时间、提高潮流计算精度和效率的针对电网大规模经济调度问题的粒计算方法。The purpose of the present invention is to provide a granular calculation method for large-scale economic dispatching problems of power grids by adopting a layered method to decompose the economic dispatching problem into multiple layers to reduce computational complexity, shorten computing time, and improve power flow calculation accuracy and efficiency.
为实现上述目的，采用了以下技术方案：本发明所述方法包括如下步骤：In order to achieve the above object, the following technical solutions are adopted: the method of the present invention comprises the steps:
步骤1，建立经济调度模型，包括其目标函数和约束条件；Step 1, establish an economic dispatch model, including its objective function and constraints;
步骤2，将电网进行分层粒化；Step 2, layering and granulating the grid;
步骤3，参数的等效；Step 3, the equivalent of parameters;
步骤4，粒度的划分；Step 4, the division of granularity;
步骤5，约束条件的处理；Step 5, processing of constraints;
步骤6，采用粒计算方法优化网络潮流。Step 6, optimize the network power flow by using the granular computing method.
进一步的，步骤1中，建立经济调度模型的具体过程如下：Further, in step 1, the specific process of establishing the economic dispatch model is as follows:
步骤1-1，建立目标函数Step 1-1, establish the objective function
在满足约束条件的情况下，以发电机的总发电成本最低为目标函数，其数学表达式具体如下：In the case of satisfying the constraint conditions, the objective function is to take the minimum total power generation cost of the generator, and its mathematical expression is as follows:
式中PG，i是第i台发电机的输出功率；ai，bi，ci是发电机组i的费用系数；N是全部发电机的数量；In the formula,PG, i is the output power of generator i; ai , bi , ci are the cost coefficients of generator set i; N is the number of all generators;
步骤1-2，设置模型的约束条件，约束条件包括系统功率平衡约束、常规机组出力上下限约束；Step 1-2, set the constraint conditions of the model, the constraint conditions include the system power balance constraints, the upper and lower limit constraints of conventional unit output;
具体约束条件为：The specific constraints are:
1)系统功率平衡约束1) System power balance constraints
式中PD总的负荷需求；PLoss是线路损耗。In the formula, PD is the total load demand; PLoss is the line loss.
忽略线路损耗，公式(2)修改为：Neglecting the line loss, formula (2) is modified as:
2)常规机组出力上下限2) The upper and lower limits of conventional unit output
式中是发电机i的最小和最大的输出功率。In the formula are the minimum and maximum output power of generator i.
进一步的，所述步骤2的具体过程如下：Further, the specific process of the step 2 is as follows:
根据分层商空间方法，把电力网络进行粒化，收集若干性质相似的细粒子，形成粗粒子作为等效机组，或者收集一些粗粒子以形成较粗的粒子作为等效机组；所有的粗粒子被分成多个层构成一个分层商空间；粗粒子由上层逐层细化为细粒子，每层计算完后能得出他们的输出功率并且分别传递给他们相应的细粒子作为下一层的负荷需求，最后一层的细粒子的结果就是经济调度的结果。According to the hierarchical quotient space method, the power network is granulated, and several fine particles with similar properties are collected to form coarse particles as equivalent units, or some coarse particles are collected to form coarser particles as equivalent units; all coarse particles It is divided into multiple layers to form a layered quotient space; coarse particles are refined from the upper layer to fine particles layer by layer, and after each layer is calculated, their output power can be obtained and passed to their corresponding fine particles as the next layer. Load demand, the result of fine particles in the last layer is the result of economic dispatch.
进一步的，所述步骤3的具体过程如下：Further, the specific process of step 3 is as follows:
步骤3-1，等效参数计算Step 3-1, equivalent parameter calculation
在经济调度模型中，费用系数ai、bi、ci最小输出功率最大输出功率需要计算，在粒计算中，他们被等效参数替代；In the economic dispatch model, the cost coefficients ai , bi ,ci minimum output power Maximum output power need to be calculated, in granular computing, they are replaced by equivalent parameters;
在第j个粒子中假设机组号是m，其等效原理为：Assuming that the unit number is m in the jth particle, the equivalent principle is:
(5)式中，是第j个粒子的等效成本系数；(6)式中PG，j是第j个粒子的输出功率；(5) where, is the equivalent cost coefficient of the jth particle; (6) wherePG, j is the output power of the jth particle;
等效参数可以计算如下：The equivalent parameters can be calculated as follows:
式中，是第j个粒子的等效最小和等效最大输出功率；In the formula, is the equivalent minimum and equivalent maximum output power of the jth particle;
然而，在解决经济调度问题之前，PG，i是未知的。但是在粒计算之前必须准备等效参数。因此提出了一种近似的方法来初始化PG，i。However,PG,i is unknown until the economic dispatch problem is solved. But equivalent parameters must be prepared before granular computation. Therefore an approximate method is proposed to initializePG,i .
步骤3-2，初始化过程Step 3-2, initialization process
PG，i的初始化对粒度计算方法是关键，因为它决定了等效参数；初始输出功率越接近就越接近最优值，就会表现出更好的结果；有三步对PG，i进行初始化：The initialization of PG,i is the key to the granularity calculation method, because it determines the equivalent parameters; the closer the initial output power is to The closer to the optimal value, the better the results; there are three steps to initializePG,i :
第一步，初始化每个机组的输出功率The first step is to initialize the output power of each unit
P″G，i＝σP′G，i (14)P″G, i = σP′G, i (14)
P′G，i是机组i的平均输出功率；σ是负荷水平系数；,P″G，i是机组i的输出功率；P′G, i is the average output power of unit i; σ is the load level coefficient; , P″G, i is the output power of unit i;
该过程使各机组的输出功率接近平均功率，满足功率平衡约束；This process makes the output power of each unit close to the average power and satisfies the power balance constraint;
第二步，正向迁移The second step, forward migration
λ′i＝2aiP″G，i+bi (15)λ′i =2ai P″G, i +bi (15)
PD′＝αPD (16)PD '=αPD (16)
λ′i是第i个机组的微增率；α是一个正数；PD′是负荷补偿；P″′G，i是第i个机组迁移后的输出功率；λ′i is the micro-increase rate of the i-th unit; α is a positive number; PD ′ is load compensation; P″′G, i is the output power of the i-th unit after migration;
上述过程使机组具有更小的λ′i，得到相对较大的正偏差量；The above process makes the unit have a smaller λ′i and a relatively larger positive deviation;
第三步，负向迁移The third step, negative transfer
(18)式中，是第i个机组的初始化输出功率；(18) where, is the initial output power of the i-th unit;
这个过程使机组具有更大的λ′i和得到一个相对较大的负偏差量；根据增量原理，第二步和第三步能够保证输出功率接近最优解；This process makes the unit have a larger λ′i and obtains a relatively large negative deviation; according to the incremental principle, the second and third steps can ensure that the output power is close to the optimal solution;
第四步，平衡约束The fourth step, balance constraints
上述偏移调整可能导致不平等的功率约束，所以有必要约束处理过程来修正修正过程在步骤5部分。The above offset adjustments may result in unequal power constraints, so it is necessary to constrain the process to correct The correction process is in step 5.
步骤3-3，粒度计算模型Step 3-3, Granular Computing Model
等价后，粒度计算的成本函数公式如下：After equivalence, the cost function formula of granular computing is as follows:
(19)式中，M是主粒子的亚粒子数量；(19) In the formula, M is the number of sub-particles of the main particle;
粒计算的功率平衡约束修正如下：The power balance constraints of granular computing are modified as follows:
(20)式中，PGD主粒子的输出功率，是下一层亚粒子的负荷需求；In formula (20), the output power of PGD main particles is the load requirement of the next layer of sub-particles;
粒子的功率约束如下：The power constraints of the particles are as follows:
在粒度计算方法中，一个粒子被认为是一个等效的机组；带有一个机组的粒子(M＝1)叫做细粒子；细粒子的等效参数等于它所包含的机组的参数；带有不止一个机组的粒子(M＞1)称为粗粒子。In the particle size calculation method, a particle is considered as an equivalent unit; a particle with one unit (M=1) is called a fine particle; the equivalent parameter of a fine particle is equal to the parameter of the unit it contains; Particles of one unit (M>1) are called coarse particles.
进一步的，所述步骤4如下：Further, the step 4 is as follows:
粒度是一个粒尺寸的平均测量值；当描述信息时，粒度主要用来衡量数据信息和知识的抽象程度；粒度由粒子包含的机组数量决定；Granularity is the average measurement of a particle size; when describing information, granularity is mainly used to measure the degree of abstraction of data information and knowledge; granularity is determined by the number of units contained in the particle;
微增率的显著波动点把机组分成粒子，微增率的计算公式是：The significant fluctuation point of the slight increase rate divides the unit into particles, and the calculation formula of the slight increase rate is:
(22)式中，λi是第i个机组的微增率；In formula (22), λi is the micro-increase rate of the i-th unit;
计算后，所有机组的微增率需要小到大进行排序；根据显著波动点对机组进行分离；After calculation, the micro-increasing rates of all units need to be sorted from small to large; the units are separated according to significant fluctuation points;
(23)式中，θs是微增率波动点，是排序微增率；s是微增率升序排列的序列号；In formula (23), θs is the fluctuation point of slight increase rate, is the sorting micro-increment rate; s is the sequence number arranged in ascending order of the micro-increase rate;
θs反应了和的差别；如果θs的值明显地大于其他值，那么θs就是显著波动点。θs respond to and The difference; if the value of θs is significantly greater than other values, then θs is a significant fluctuation point.
进一步的，所述步骤5的具体过程如下：Further, the specific process of step 5 is as follows:
步骤5-1，检查每个调整所有元素以满足不等式约束如下：Step 5-1, check each All elements are adjusted to satisfy the inequality constraints as follows:
(24)式中，如果或者则过渡变量Tj设置成0，否则k是当前的迭代次数；In formula (24), if or Then the transition variable Tj is set to 0, otherwise k is the current number of iterations;
步骤5-2，通过计算PR，如果|PR|＞ε，转到步骤5-3，如果|PR|≤ε，则转到步骤4，ε是精度要求；Step 5-2, by Calculate PR , if |PR |＞ε, go to step 5-3, if |PR |≤ε, go to step 4, ε is the precision requirement;
步骤5-3，修改的值以满足一下等式约束：Step 5-3, Modify The value satisfies the following equality constraints:
步骤5-4，检查所有的修正值，如果违反不等式约束，回到步骤5-1；如果不违反不等式约束则进入步骤5-5；Step 5-4, check all If it violates the inequality constraint, go back to step 5-1; if it does not violate the inequality constraint, go to step 5-5;
步骤5-5，停止约束处理过程；Step 5-5, stop the constraint processing process;
按以上步骤计算，等效参数的初始输出功率接近实际功率水平，使等效参数更精确；然后把放到公式(7)和(8)中，替代PG，j来计算和Calculated according to the above steps, the initial output power of the equivalent parameters is close to the actual power level, making the equivalent parameters more accurate; then put Put it into formulas (7) and (8), replacePG, j to calculate and
进一步的，所述步骤6具体如下：Further, the step 6 is specifically as follows:
步骤6-1，参数准备。所有机组的基本参数需要输入，即ai、bi、ci、和计算初始输出功率Step 6-1, parameter preparation. The basic parameters of all units need to be input, namely ai , bi , ci , and Calculate the initial output power
步骤6-2，确定粗粒子的分层结构和参数计算；根据电力系统规模确定合适的分层数量；尽管分层的方法能够提高搜索效率和减少计算时间，但是等效的过程会造成偏差；如果分层太多会降低准确性；第一层M1的粒子数量和第二层最大机组数量nmax在计算前需要设置，以指导机组的划分过程；当完成机组划分时，下一部分是计算等效参数；Step 6-2, determine the hierarchical structure and parameter calculation of coarse particles; determine the appropriate number of layers according to the scale of the power system; although the layered method can improve search efficiency and reduce calculation time, the equivalent process will cause deviations; If there are too many layers, the accuracy will be reduced; the number of particles in thefirst layer M1 and the maximum number of units nmax in the second layer need to be set before calculation to guide the division process of units; when the division of units is completed, the next part is the calculation Equivalent parameters;
步骤6-3，计算粒子的输出功率；将结果相应地转移到他们的亚粒子作为下一层的负荷需求；Step 6-3, calculate the output power of the particles; transfer the results accordingly to their sub-particles as the load requirements of the next layer;
当底层粒子计算完成时，将得到最终的优化解。When the underlying particle calculation is completed, the final optimized solution will be obtained.
与现有技术相比，本发明具有如下优点：Compared with prior art, the present invention has following advantage:
1、考虑因素全面，提高了计算精度；1. Comprehensive consideration of factors improves calculation accuracy;
2、提出分层商空间，应用层次分析法，将求解问题分层粒化求解，能降低求解时间，提高求解效率；2. Propose a layered quotient space, apply the AHP, and solve the problem in layers and granules, which can reduce the solution time and improve the solution efficiency;
3、对于大规模电力网络，如果采用合理的分层粒计算方法，可以解决收敛困难的问题，还能提高计算速度。3. For large-scale power networks, if a reasonable hierarchical granular calculation method is adopted, the problem of difficult convergence can be solved and the calculation speed can be improved.
附图说明Description of drawings
图1是本发明列举10机组系统的3层体系结构。Fig. 1 is the 3-layer architecture of the present invention enumerating 10 unit systems.
图2是本发明列举10机组系统的微增率波动情况。Fig. 2 is the micro-increase rate fluctuation of the 10-unit system listed in the present invention.
图3是本发明方法的粒计算流程图。Fig. 3 is a flowchart of granular computing of the method of the present invention.
图4是本发明方法的流程图。Fig. 4 is a flowchart of the method of the present invention.
具体实施方式Detailed ways
下面结合附图对本发明做进一步说明：The present invention will be further described below in conjunction with accompanying drawing:
如图4所示，本发明所述方法包括如下步骤：As shown in Figure 4, the method of the present invention comprises the following steps:
步骤1，建立经济调度模型，包括其目标函数和约束条件；Step 1, establish an economic dispatch model, including its objective function and constraints;
步骤1-1，建立经济调度模型的具体过程如下：Step 1-1, the specific process of establishing the economic dispatch model is as follows:
在满足约束条件的情况下，以发电机的总发电成本最低为目标函数，其数学表达式具体如下：In the case of satisfying the constraint conditions, the objective function is to take the minimum total power generation cost of the generator, and its mathematical expression is as follows:
式中PG，i是第i台发电机的输出功率；ai，bi，ci是发电机组i的费用系数；N是全部发电机的数量；In the formula,PG, i is the output power of generator i; ai , bi , ci are the cost coefficients of generator set i; N is the number of all generators;
步骤1-2，设置模型的约束条件，约束条件包括系统功率平衡约束、常规机组出力上下限约束；Step 1-2, set the constraint conditions of the model, the constraint conditions include the system power balance constraints, the upper and lower limit constraints of conventional unit output;
具体约束条件为：The specific constraints are:
1)系统功率平衡约束1) System power balance constraints
式中PD总的负荷需求；PLoss是线路损耗；In the formula, PD is the total load demand; PLoss is the line loss;
忽略线路损耗，公式(2)修改为：Neglecting the line loss, formula (2) is modified as:
2)常规机组出力上下限2) The upper and lower limits of conventional unit output
式中是发电机i的最小和最大的输出功率。In the formula are the minimum and maximum output power of generator i.
步骤2，将电网进行分层粒化；Step 2, layering and granulating the grid;
将电网进行分层粒化的具体过程如下：The specific process of layering and granulating the power grid is as follows:
按层次分析法，本文对经济调度问题提出了一种建立分层商空间的方法。为了阐明分层的结构，以10机组的电力系统为例。编号是#1-#10。假设系统可以分为三层，如图1，每层各自的特点如下：According to the Analytic Hierarchy Process, this paper proposes a method to establish a hierarchical quotient space for the economic dispatch problem. To clarify the layered structure, a power system with 10 units is taken as an example. The numbers are #1-#10. Assuming that the system can be divided into three layers, as shown in Figure 1, the characteristics of each layer are as follows:
1)第一层：这里有三个粗粒子V11，V12，V13,在本层中。V11包含四个机组(#1，#3，#6，#7)，如图1所示，V12(#2，#9)和V13(#4，#5，#8，#10)与V11一样。V11，V12，V13是三个等效的机组。这样就减少了经济调度问题的维度，进而提高了优化效率。在这层计算完后，V11，V12，V13能得出它们的输出功率并且分别传递给他们的亚颗粒作为下一层的负荷需求。1) The first layer: There are three coarse particles V11 , V12 , and V13 in this layer. V11 contains four units (#1, #3, #6, #7), as shown in Figure 1, V12 (#2, #9) and V13 (#4, #5, #8, #10 ) same as V11 . V11 , V12 and V13 are three equivalent units. In this way, the dimension of the economic dispatch problem is reduced, and the optimization efficiency is improved. After the calculation of this layer, V11 , V12 , V13 can get their output power and pass it to their sub-particles respectively as the load demand of the next layer.
2)第二层：本层有六个粒子V21，V22，V23，V24，V25，V26。V21和V22是V11的子粒子，认为它们是等价的机组，并且V21和V22从V11获得负荷需求。主粒子V11负责计算V21和V22的功率输出。其他两个粒子的计算过程与V11的转化相似。如图1所示，在V23，V24，V26中只有一个机组，因此，这三个粒子的结果正好分别是#9，#2,和#5的最终功率输出。然而，V21、V22、V25仍然能够在第三层被分成几个子粒子。2) The second layer: There are six particles V21 , V22 , V23 , V24 , V25 , and V26 in this layer. V21 and V22 are child particles of V11 , they are considered as equivalent units, and V21 and V22 get load demand from V11 . The master particle V11 is responsible for calculating the power output of V21 and V22 . The calculation process of the other two particles is similar to the transformation of V11 . As shown in Figure 1, there is only one unit in V23 , V24 , and V26 , so the results of these three particles are just the final power outputs of #9, #2, and #5 respectively. However, V21 , V22 , V25 can still be divided into several sub-particles in the third layer.
3)第三层：这一层是底层，它包括七个粒子，分别是V31，V32，V33，V34，V35，V36，V37。每个粒子只有一个机组。其计算过程与第二层的方法相似，包括V21等效为V31和V32，V22等效为V33和V34，V25等效为V35、V36和V37。当所有的计算过程完成，V31，V32，V33，V34，V35，V36，V37和V23，V24，V26的结果就是最终10机组的机组出力结果。3) The third layer: This layer is the bottom layer, which includes seven particles, namely V31 , V32 , V33 , V34 , V35 , V36 , and V37 . Each particle has only one unit. The calculation process is similar to that of the second layer, including that V21 is equivalent to V31 and V32 , V22 is equivalent to V33 and V34 , and V25 is equivalent to V35 , V36 and V37 . When all the calculation process is completed, the results of V31 , V32 , V33 , V34 , V35 , V36 , V37 and V23 , V24 , V26 are the output results of the final 10 units.
在这种分层模型的设计中，找到一种合理的计算机组等效参数的方法是关键的，对最终结果有显著的影响。In the design of such hierarchical models, it is critical to find a reasonable method of calculating the equivalent parameters of the group, which has a significant impact on the final result.
步骤3，参数的等效；Step 3, the equivalent of parameters;
步骤3-1，等效参数计算Step 3-1, equivalent parameter calculation
在经济调度模型中，费用系数ai、bi、ci最小输出功率最大输出功率需要计算，在粒计算中，他们被等效参数替代；In the economic dispatch model, the cost coefficients ai , bi ,ci minimum output power Maximum output power need to be calculated, in granular computing, they are replaced by equivalent parameters;
在第j个粒子中假设机组号是m，其等效原理为：Assuming that the unit number is m in the jth particle, the equivalent principle is:
(5)式中，是第j个粒子的等效成本系数；(6)式中PG，j是第j个粒子的输出功率；(5) where, is the equivalent cost coefficient of the jth particle; (6) wherePG, j is the output power of the jth particle;
等效参数可以计算如下：The equivalent parameters can be calculated as follows:
式中，是第j个粒子的等效最小和等效最大输出功率；In the formula, is the equivalent minimum and equivalent maximum output power of the jth particle;
步骤3-2，初始化过程Step 3-2, initialization process
PG，i的初始化对粒度计算方法是关键，因为它决定了等效参数；初始输出功率越接近就越接近最优值，就会表现出更好的结果；有三步对PG，i进行初始化：The initialization of PG,i is the key to the granularity calculation method, because it determines the equivalent parameters; the closer the initial output power is to The closer to the optimal value, the better the results; there are three steps to initializePG,i :
第一步，初始化每个机组的输出功率The first step is to initialize the output power of each unit
P″G，i＝σP′G，i (14)P″G, i = σP′G, i (14)
P′G，i是机组i的平均输出功率；σ是负荷水平系数；,P″G，i是机组i的输出功率；P′G, i is the average output power of unit i; σ is the load level coefficient; , P″G, i is the output power of unit i;
该过程使各机组的输出功率接近平均功率，满足功率平衡约束；This process makes the output power of each unit close to the average power and satisfies the power balance constraint;
第二步，正向迁移The second step, forward migration
λ′i＝2aiP″G，i+bi (15)λ′i =2ai P″G, i +bi (15)
PD′＝αPD (16)PD '=αPD (16)
λ′i是第i个机组的微增率；α是一个正数；PD′是负荷补偿；P″′G，i是第i个机组迁移后的输出功率；λ′i is the micro-increase rate of the i-th unit; α is a positive number; PD ′ is load compensation; P″′G, i is the output power of the i-th unit after migration;
上述过程使机组具有更小的λ′i，得到相对较大的正偏差量；The above process makes the unit have a smaller λ′i and a relatively larger positive deviation;
第三步，负向迁移The third step, negative transfer
(18)式中，是第i个机组的初始化输出功率；(18) where, is the initial output power of the i-th unit;
这个过程使机组具有更大的λ′i和得到一个相对较大的负偏差量；根据增量原理，第二步和第三步能够保证输出功率接近最优解；This process makes the unit have a larger λ′i and obtains a relatively large negative deviation; according to the incremental principle, the second and third steps can ensure that the output power is close to the optimal solution;
第四步，平衡约束The fourth step, balance constraints
上述偏移调整可能导致不平等的功率约束，所以有必要约束处理过程来修正The above offset adjustments may result in unequal power constraints, so it is necessary to constrain the process to correct
步骤3-3，粒度计算模型Step 3-3, Granular Computing Model
等价后，粒度计算的成本函数公式如下：After equivalence, the cost function formula of granular computing is as follows:
(19)式中，M是主粒子的亚粒子数量；(19) In the formula, M is the number of sub-particles of the main particle;
粒计算的功率平衡约束修正如下：The power balance constraints of granular computing are modified as follows:
(20)式中，PGD主粒子的输出功率，是下一层亚粒子的负荷需求；In formula (20), the output power of PGD main particles is the load requirement of the next layer of sub-particles;
粒子的功率约束如下：The power constraints of the particles are as follows:
在粒度计算方法中，一个粒子被认为是一个等效的机组；带有一个机组的粒子(M＝1)叫做细粒子；细粒子的等效参数等于它所包含的机组的参数；带有不止一个机组的粒子(M＞1)称为粗粒子。In the particle size calculation method, a particle is considered as an equivalent unit; a particle with one unit (M=1) is called a fine particle; the equivalent parameter of a fine particle is equal to the parameter of the unit it contains; Particles of one unit (M>1) are called coarse particles.
步骤4，粒度的划分；Step 4, the division of granularity;
粒度是一个粒尺寸的平均测量值。当描述信息时，粒度主要用来衡量数据信息和知识的抽象程度。在本文中，粒度由粒子包含的机组数量决定。Particle size is an average measurement of the size of a particle. When describing information, granularity is mainly used to measure the degree of abstraction of data information and knowledge. In this paper, the granularity is determined by the number of units the particle contains.
微增率的显著波动点把机组分成粒子，微增率的计算公式是：The significant fluctuation point of the slight increase rate divides the unit into particles, and the calculation formula of the slight increase rate is:
(22)式中，λi是第i个机组的微增率。In formula (22), λi is the micro-increase rate of unit i.
计算完之后，所有机组的微增率需要小到大进行排序。根据显著波动点对机组进行分离。After the calculation, the micro-increasing rates of all units need to be sorted from small to large. Separation of units based on significant fluctuation points.
(23)式中，θs是微增率波动点，是排序微增率；s是微增率升序排列的序列号。In formula (23), θs is the fluctuation point of slight increase rate, is the sorting micro-increment rate; s is the sequence number arranged in ascending order of the micro-increment rate.
θs反应了和的差别。如果θs的值明显地大于其他值，那么θs就是显著波动点。θs respond to and difference. If the value of θs is significantly larger than other values, then θs is a significant fluctuation point.
在表1中列举10机组系统的粒度划分情况，列出了10机组的电力系统划分方案，有序增长率的波动图如图2，其显示了显著波动点是如何波动的。Table 1 lists the granularity division of the 10-unit system, and lists the power system division scheme of the 10-unit power system. The fluctuation diagram of the ordered growth rate is shown in Figure 2, which shows how the significant fluctuation points fluctuate.
表1Table 1
1)第一层划分：1) The first layer division:
在图2中，我们观察到θ5和θ7明显大于平均值，这意味着#9和#4的增长率是明显不同于他们之前的机组，然后这些机组被分成三组从而形成(V11，V12，V13)三个粒子。In Figure 2, we observed that θ5 and θ7 were significantly larger than the average value, which meant that the growth rates of #9 and #4 were significantly different from their previous units, and then these units were divided into three groups to form (V11 , V12 , V13 ) three particles.
在实际例子中，θs需要在降序排列中列出来。然后，根据在第一层设置的粒子数量M1挑出之前的M1-1的点。如果有太多粒子，则计算的效率会降低。因此M1的范围是2～9。In the practical example, θs need to be listed in descending order. Then, pick out the previous M1 -1 points according to the number M1 of particles set in the first layer. If there are too many particles, the calculation becomes less efficient. Therefore, the range of M1 is2-9 .
2)第二层划分：2) The second layer division:
在V11中，θ3是显著波动点，并且V11被分成V21和V22。同样地，V12和V13也分别分成V23，V24，V25，V26，它们构成图1所示的第二层。In V11 , θ3 is a significant fluctuation point, and V11 is divided into V21 and V22 . Similarly, V12 and V13 are also divided into V23 , V24 , V25 and V26 respectively, which constitute the second layer shown in FIG. 1 .
在实际应用中，该层的划分过程是独立地在每个主颗粒中实现的。在本层第j个主粒子中，亚粒子的数量是由设定最大机组数量nmax决定的，公式如下：In practical applications, the division process of this layer is realized independently in each primary particle. In the jth main particle of this layer, the number of sub-particles It is determined by setting the maximum number of units nmax , the formula is as follows:
式中，mj是第j个主粒子的总机组数量。In the formula, mj is the total unit number of the jth main particle.
然后根据之前的波动点把第j个粒子分成个亚粒子。如果一个主粒子的总机组数量比nmax小，那么这个主粒子不能分成亚粒子。如nmax果太小，这将会有太多的亚粒子，这些亚粒子会提高GrC方法的维度并且会降低计算效率。如果nmax太大，这将会没有减少GrC方法时间效益的亚粒子。因此nmax的范围是10～30。Then according to the previous The fluctuation point divides the jth particle into a subparticle. If the total group number of a main particle is smaller than nmax , then this main particle cannot be divided into sub-particles. If nmax is too small, there will be too many subparticles, which will increase the dimensionality of the GrC method and reduce computational efficiency. If nmax is too large, there will be no subparticles reducing the time efficiency of the GrC method. Therefore, the range of nmax is 10-30.
在第一层和第二层划分中，如果粒子中只有一个唯一的机组，则该粒子将与先前的粒子结合，以提高GrC方法的全局搜索能力。In the division of the first and second layers, if there is only one unique group in a particle, the particle will be combined with the previous particles to improve the global search ability of the GrC method.
3)底层分区：3) Bottom partition:
本层中，所有的粗颗粒都必须被分解成细颗粒，以获得每个机组的最终功率输出。In this layer, all coarse particles must be broken down into fine particles to obtain the final power output of each unit.
步骤5，约束条件的处理；Step 5, processing of constraints;
步骤5-1，检查每个调整所有元素以满足不等式约束如下：Step 5-1, check each All elements are adjusted to satisfy the inequality constraints as follows:
(24)式中，如果或者则过渡变量Tj设置成0，否则k是当前的迭代次数；In formula (24), if or Then the transition variable Tj is set to 0, otherwise k is the current number of iterations;
步骤5-2，通过计算PR，如果|PR|＞ε，转到步骤5-3，如果|PR|≤ε，则转到步骤4，ε是精度要求；Step 5-2, by Calculate PR , if |PR |＞ε, go to step 5-3, if |PR |≤ε, go to step 4, ε is the precision requirement;
步骤5-3，修改的值以满足一下等式约束：Step 5-3, Modify The value satisfies the following equality constraints:
步骤5-4，检查所有的修正值，如果违反不等式约束，回到步骤5-1；如果不违反不等式约束则进入步骤5-5；Step 5-4, check all If it violates the inequality constraint, go back to step 5-1; if it does not violate the inequality constraint, go to step 5-5;
步骤5-5，停止约束处理过程；Step 5-5, stop the constraint processing process;
按以上步骤计算，等效参数的初始输出功率接近实际功率水平，使等效参数更精确；然后把放到公式(7)和(8)中，替代PG，j来计算和Calculated according to the above steps, the initial output power of the equivalent parameters is close to the actual power level, making the equivalent parameters more accurate; then put Put it into formulas (7) and (8), replacePG, j to calculate and
步骤6，采用粒计算方法优化网络潮流，其粒计算过程的流程图如图3所示。In step 6, the network power flow is optimized using the granular computing method, and the flowchart of the granular computing process is shown in Figure 3 .
步骤6-1，参数准备。所有机组的基本参数需要输入，即ai、bi、ci、和计算初始输出功率Step 6-1, parameter preparation. The basic parameters of all units need to be input, namely ai , bi , ci , and Calculate the initial output power
步骤6-2，确定粗粒子的分层结构和参数计算。根据电力系统规模确定合适的分层数量。尽管分层的方法能够提高搜索效率和减少计算时间，但是等效的过程会造成偏差。如果分层太多会降低准确性。第一层M1的粒子数量和第二层最大机组数量nmax在计算前需要设置，以指导机组的划分过程。当完成机组划分时，下一部分是计算等效参数。Step 6-2, determining the hierarchical structure of the coarse particles and calculating the parameters. Determine the appropriate number of layers according to the scale of the power system. Although a layered approach can improve search efficiency and reduce computation time, the equivalent process introduces bias. If there are too many layers, the accuracy will be reduced. The number of particles in thefirst layer M1 and the maximum number of units nmax in the second layer need to be set before calculation to guide the division process of the units. When unit division is complete, the next part is to calculate the equivalent parameters.
步骤6-3，计算粒子的输出功率。一种新的智能优化算法可以应用于优化的粒子的输出功率，并将结果相应地转移到他们的亚粒子作为下一层的负荷需求。Step 6-3, calculating the output power of the particles. A new intelligent optimization algorithm can be applied to optimize the output power of the particles and transfer the result accordingly to their sub-particles as the load demand of the next layer.
当底层粒子计算完成时，将得到最终的优化解。When the underlying particle calculation is completed, the final optimized solution will be obtained.
为了更加全面的验证本发明的有效性，通过粒子群算法与均值方差映射方法的比较来说明本发明能够提供一个满意的全局最优解且具有较好的时间效益。两种结果对比如下：In order to verify the effectiveness of the present invention more comprehensively, the comparison between the particle swarm optimization algorithm and the mean-variance mapping method shows that the present invention can provide a satisfactory global optimal solution and has better time efficiency. The two results are compared as follows:
表2两种算法的发电成本与时间结果比较Table 2 Comparison of power generation cost and time results of the two algorithms
很显然，本发明的发电成本的优势不太明显，但是对于计算时间来说，效率提高很大，随着电网规模的扩大，粒计算的优越性会更加明显。以上结果验证了本发明的优越性。Obviously, the advantage of the power generation cost of the present invention is not obvious, but the efficiency of the calculation time is greatly improved. With the expansion of the grid scale, the advantages of granular computing will be more obvious. The above results have verified the superiority of the present invention.
以上所述的实施例仅仅是对本发明的优选实施方式进行描述，并非对本发明的范围进行限定，在不脱离本发明设计精神的前提下，本领域普通技术人员对本发明的技术方案做出的各种变形和改进，均应落入本发明权利要求书确定的保护范围内。The above-mentioned embodiments are only descriptions of preferred implementations of the present invention, and are not intended to limit the scope of the present invention. All such modifications and improvements should fall within the scope of protection defined by the claims of the present invention.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108400617A (en)* | 2018-03-19 | 2018-08-14 | 燕山大学 | A kind of constraint processing method of economic load dispatching |
| CN108565900A (en)* | 2018-05-14 | 2018-09-21 | 南京邮电大学 | A kind of distributed energy optimizing operation method based on game theory |
| CN109193807A (en)* | 2018-11-13 | 2019-01-11 | 燕山大学 | A kind of Economic Dispatch method and system |
| CN112052322A (en)* | 2020-09-03 | 2020-12-08 | 哈尔滨工业大学 | Intelligent robot conversation strategy generation method based on particle calculation |
| CN112231926A (en)* | 2020-10-29 | 2021-01-15 | 高小翎 | A node-optimized method for measuring harmonic impedance in large power systems |
| CN113469566A (en)* | 2021-07-21 | 2021-10-01 | 燕山大学 | Method and system for determining initial distribution scheme of generator |
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20040128564A1 (en)* | 2002-12-30 | 2004-07-01 | Dubinsky Dean V. | Power management system |
| CN103678889A (en)* | 2013-12-02 | 2014-03-26 | 国家电网公司 | Photovoltaic power generation accommodating capacity calculation method taking static voltage stability into consideration |
| CN106505575A (en)* | 2016-12-09 | 2017-03-15 | 燕山大学 | A Granular Computing Based Economic Dispatch Method of Line Power Flow |
| CN107171365A (en)* | 2017-06-23 | 2017-09-15 | 国网山东省电力公司经济技术研究院 | Multiple target stochastic and dynamic economic load dispatching method with asynchronous iteration is decoupled based on scene |
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20040128564A1 (en)* | 2002-12-30 | 2004-07-01 | Dubinsky Dean V. | Power management system |
| CN103678889A (en)* | 2013-12-02 | 2014-03-26 | 国家电网公司 | Photovoltaic power generation accommodating capacity calculation method taking static voltage stability into consideration |
| CN106505575A (en)* | 2016-12-09 | 2017-03-15 | 燕山大学 | A Granular Computing Based Economic Dispatch Method of Line Power Flow |
| CN107171365A (en)* | 2017-06-23 | 2017-09-15 | 国网山东省电力公司经济技术研究院 | Multiple target stochastic and dynamic economic load dispatching method with asynchronous iteration is decoupled based on scene |
| Title |
|---|
| 张鹏 等: ""粒计算在电力系统优化调度中的应用探索"", 《东北电力技术》* |
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108400617A (en)* | 2018-03-19 | 2018-08-14 | 燕山大学 | A kind of constraint processing method of economic load dispatching |
| CN108400617B (en)* | 2018-03-19 | 2021-05-28 | 燕山大学 | A Constraint Handling Method for Economic Scheduling |
| CN108565900A (en)* | 2018-05-14 | 2018-09-21 | 南京邮电大学 | A kind of distributed energy optimizing operation method based on game theory |
| CN108565900B (en)* | 2018-05-14 | 2021-09-14 | 南京邮电大学 | Distributed energy optimization operation method based on game theory |
| CN109193807A (en)* | 2018-11-13 | 2019-01-11 | 燕山大学 | A kind of Economic Dispatch method and system |
| CN112052322A (en)* | 2020-09-03 | 2020-12-08 | 哈尔滨工业大学 | Intelligent robot conversation strategy generation method based on particle calculation |
| CN112231926A (en)* | 2020-10-29 | 2021-01-15 | 高小翎 | A node-optimized method for measuring harmonic impedance in large power systems |
| CN113469566A (en)* | 2021-07-21 | 2021-10-01 | 燕山大学 | Method and system for determining initial distribution scheme of generator |
| Publication number | Publication date |
|---|---|
| CN107657392B (en) | 2021-01-08 |
| Publication | Publication Date | Title |
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