技术领域technical field
本发明涉及工业负荷优化调度领域，具体来说是一种基于需求响应的工业负荷优化调度建模方法。The invention relates to the field of optimal scheduling of industrial loads, in particular to a modeling method for optimal scheduling of industrial loads based on demand response.
背景技术Background technique
随着经济和社会的发展，电力的需求日益增长。工业用户相比较于居民和商业用户，具有更高的电力消费水平，它已占到世界电力消费的40％以上。发电侧为了满足不断增长的电力消费需要进一步的扩建发电容量，这给电力系统的运行带来了巨大的成本负担。而从需求侧管理的角度，需求响应是指电力用户对价格信号或激励机制做出响应，改变原有的一些电力消费行为，从而促进电力系统的优化运行。因此对工业企业实施需求响应具有重要的意义和较大的潜力。With the development of economy and society, the demand for electricity is increasing day by day. Compared with residential and commercial users, industrial users have a higher level of power consumption, which has accounted for more than 40% of the world's power consumption. In order to meet the growing power consumption, the power generation side needs to further expand the power generation capacity, which brings a huge cost burden to the operation of the power system. From the perspective of demand side management, demand response means that power users respond to price signals or incentive mechanisms to change some of the original power consumption behaviors, thereby promoting the optimal operation of the power system. Therefore, it is of great significance and great potential to implement demand response to industrial enterprises.
对于工业负荷的优化调度问题，现有模型大多采用负荷转移的方法，即将峰时段的负荷转移到谷时段或平时段，但现有的工业负荷优化调度模型对工业生产相关的约束条件考虑的不是很完善，如往往没有考虑工业产品的储存容量限制，这不利于负荷调度模型在实际中的应用。同时现有的工业负荷优化调度模型往往没有考虑能量储能单元，这削弱了工业负荷优化调度对主电网削峰填谷的作用；另外现有的工业负荷优化调度模型大多没有考虑分布式发电单元对工业负荷优化调度的影响，分布式发电单元能更灵活地为工业企业提供电能，因此现有技术无法进一步的降低工业企业的生产能耗成本。For the optimal dispatching of industrial loads, most of the existing models adopt the method of load transfer, that is, the load in the peak period is transferred to the valley period or the normal period, but the existing industrial load optimal dispatching model does not consider the constraints related to industrial production. It is very perfect, such as the storage capacity limitation of industrial products is often not considered, which is not conducive to the application of the load scheduling model in practice. At the same time, the existing industrial load optimal dispatching models often do not consider energy storage units, which weakens the role of industrial load optimal dispatching in peak-shaving and valley-filling of the main power grid; in addition, most of the existing industrial load optimal dispatching models do not consider distributed power generation units Influenced by the optimal scheduling of industrial loads, distributed power generation units can provide power to industrial enterprises more flexibly, so the existing technology cannot further reduce the production and energy consumption costs of industrial enterprises.
发明内容Contents of the invention
本发明针对现有技术中存在的不足之处，提出来一种基于需求响应的工业负荷优化调度建模方法，以期将能量储能单元和分布式发电单元纳入调度模型中，建立更加完善的工业负荷优化调度模型，从而降低工业企业的负荷运行成本，对主电网来说能够达到削峰填谷的作用，继而提高分时电价环境下主电网运行的安全性和稳定性。Aiming at the deficiencies in the prior art, the present invention proposes a demand-response-based industrial load optimization scheduling modeling method in order to incorporate energy storage units and distributed power generation units into the scheduling model and establish a more complete industrial The load optimization scheduling model can reduce the load operation cost of industrial enterprises, and can achieve the effect of peak shaving and valley filling for the main grid, and then improve the safety and stability of the main grid operation under the time-of-use electricity price environment.
本发明为解决技术问题采用如下技术方案：The present invention adopts following technical scheme for solving technical problems:
本发明一种基于需求响应的工业负荷优化调度建模方法，是应用于包含能量储能单元、分布式发电单元和主电网构成的工业企业生产环境中，其特点包括以下步骤：A demand-response-based industrial load optimization scheduling modeling method of the present invention is applied to an industrial enterprise production environment composed of an energy storage unit, a distributed power generation unit and a main power grid, and its characteristics include the following steps:
步骤一、根据工业负荷特性，将工业负荷分为可调度负荷和不可调度负荷；并将所述可调度负荷分为可转移负荷和可控制负荷，所述可转移负荷有开和关两种运行点，所述可控制负荷有多种不同功率的运行点；Step 1. According to the characteristics of industrial loads, divide industrial loads into dispatchable loads and non-dispatchable loads; divide the dispatchable loads into transferable loads and controllable loads, and the transferable loads have two types of operation: on and off point, the controllable load has a variety of operating points with different power;
步骤二、对所述可调度负荷的运行过程进行建模，得到工业生产的储存模型和电力需求量；对所述能量储能单元进行建模，得到储电量模型；对所述分布式发电单元进行建模，得到发电量；Step 2: Modeling the operation process of the schedulable load to obtain the storage model and power demand of industrial production; modeling the energy storage unit to obtain a power storage model; Carry out modeling to obtain power generation;
步骤三、建立分时电价环境下所述工业负荷优化调度模型的目标函数；Step 3, establishing the objective function of the industrial load optimal dispatching model under the time-of-use electricity price environment;
步骤四、确定所述工业负荷优化调度模型的约束条件，并与所述目标函数构成基于需求响应的工业负荷优化调度模型。Step 4: Determine the constraints of the industrial load optimal dispatch model, and form a demand response-based industrial load optimal dispatch model with the objective function.
本发明所述的基于需求响应的工业负荷优化调度建模方法的特点也在于，所述步骤二中的工业生产的储存模型如式(1)所示：The characteristic of the demand response-based industrial load optimal scheduling modeling method of the present invention is also that the storage model of industrial production in the second step is shown in formula (1):
式(1)中,t为时段编号，k为生产任务编号，s为工业产品的储存编号；Ss,t为第s个储存编号的工业产品在第t个时段的储存数量；Ss,t-1为第s个储存编号的工业产品在第t-1个时段的储存数量；Tp,s为所有生产第s个储存编号的工业产品的生产任务集合，Tc,s为所有消耗第s个储存编号的工业产品的生产任务集合；Ps,k,t为第k个编号的生产任务在第t个时段生产所述第s个储存编号的工业产品的数量，并由式(2)获得；Cs,k,t为第k个编号的生产任务在第t个时段消耗所述第s个储存编号的工业产品的数量，并由式(3)获得：In formula (1), t is the period number, k is the production task number, s is the storage number of the industrial product; Ss,t is the storage quantity of the industrial product with the sth storage number in the tth time period; Ss, t-1 is the storage quantity of the industrial product with the sth storage number in the t-1 period; Tp,s is the set of production tasks for all the industrial products with the sth storage number, and Tc,s is all consumption The production task set of the industrial product with the sth storage number; Ps, k, t is the quantity of the industrial product with the sth storage number produced by the kth numbered production task in the tth period, and is determined by the formula ( 2) Obtain; Cs, k, t is the quantity of the industrial product of the s storage number consumed by the production task of the kth number in the tth time period, and obtained by formula (3):
式(2)中,pk,m,s为所述第k个编号的生产任务在第m个运行点运行时生产所述第s个储存编号的工业产品的速率；zk,m,t为二进制变量，表示所述第k个编号的生产任务在第t个时段的第m个运行点的运行状态；In formula (2), pk, m, s is the rate at which the production task of the kth number produces the industrial product of the sth storage number when the production task of the kth number runs at the mth operation point; zk , m, t is a binary variable, representing the running state of the kth numbered production task at the mth running point in the tth time period;
式(3)中,ck,m,s为所述第k个编号的生产任务在第m个运行点运行时消耗所述第s个储存编号的工业产品的速率；In the formula (3), ck, m, s is the rate at which the k-th numbered production task consumes the s-th stored numbered industrial product when it runs at the m-th operating point;
所述步骤二中的电力需求量是由式(4)得到：The power demand in the step 2 is obtained by formula (4):
式(4)中，Et为工业生产中第t个时段的电力需求量；ek,t为所述第k个编号的生产任务在第t个时段的耗电量，并由式(5)获得：In the formula (4), Et is the power demand of the tth period in industrial production; ek,t is the power consumption of the kth numbered production task in the tth period, and is determined by the formula (5 )get:
式(5)中,ek,m为所述第k个编号的生产任务在第m个运行点运行时单位时间的耗电量；In the formula (5), ek, m is the power consumption per unit time when the production task of the kth number is running at the mth operating point;
所述步骤二中的能量储能单元的储电量模型为：The storage capacity model of the energy storage unit in the step 2 is:
式(6)中，和分别为所述能量储能单元在第t个时段结束时和第t-1个时段结束时的储电量；和分别为所述能量储能单元在第t时段内的充电量和放电量；ηch和ηdis分别为所述能量储能单元的充电效率和放电效率；In formula (6), with are respectively the energy storage capacity of the energy storage unit at the end of the tth period and at the end of the t-1th period; with Respectively, the charge and discharge capacity of the energy storage unit in the tth period; ηch and ηdis are the charging efficiency and discharge efficiency of the energy storage unit respectively;
所述步骤二中的发电量是利用式(7)得到：The power generation in the said step 2 is obtained by using formula (7):
式(7)中，EDER,t为所述分布式发电单元在第t个时段的发电量；i为所述分布式发电单元中分布式电源的编号，N为所述分布式发电单元中分布式电源的总数；Pi,t为第i个分布式电源在第t个时段的发电量。In the formula (7), EDER,t is the power generation of the distributed power generation unit in the tth time period; i is the number of the distributed power source in the distributed power generation unit, and N is the number of the distributed power generation unit in the distributed power generation unit The total number of distributed power generation; Pi,t is the power generation of the i-th distributed power generation in the t-th period.
所述步骤三中，基于需求响应的工业负荷优化调度模型的目标函数如式(8)所示：In the third step, the objective function of the optimal scheduling model of industrial load based on demand response is shown in formula (8):
式(8)中，C为所述工业负荷优化调度后的总成本；T为所述工业负荷优化调度在一个周期内的总时段数；ppt和pst分别为分时电价环境下第t个时段的购电价格和售电价格；Ep,t和Es,t分别为第t个时段的购电量和售电量；CDER为所述分布式发电单元的电力生产成本，并由式(9)获得：In formula (8), C is the total cost after optimal scheduling of the industrial load;Tis the total time period of the optimal scheduling of the industrial load in one cycle; The electricity purchase price and electricity sale price of the first time period; Ep,t and Es,t are the electricity purchase and sales electricity of the tth time period respectively; CDER is the power production cost of the distributed generation unit, and is expressed by the formula (9) Get:
式(9)中，Pi,t为第i个分布式电源在第t个时段内的输出功率；Fi(Pi,t)为第i个分布式电源在第t个时段内的燃料成本，并由式(10)获得；OMi(Pi,t)为第i个分布式电源在第t个时段内的运行维护成本，并由式(11)获得：In formula (9), Pi,t is the output power of the i-th distributed power generation in the t-th time period; Fi (Pi,t ) is the fuel consumption of the i-th distributed power generation in the t-th time period The cost is obtained by formula (10); OMi (Pi,t ) is the operation and maintenance cost of the i-th distributed power generation in the t-th period, and it is obtained by formula (11):
Fi(Pi,t)＝ai+biPi,t+ci(Pi,t)2 (10)Fi (Pi,t )＝ai +bi Pi,t +ci (Pi,t )2 (10)
式(10)中，ai，bi和ci为第i个分布式电源的燃料成本系数；In formula (10), ai , bi and ci are the fuel cost coefficients of the ith distributed power generation;
式(11)中，为第i个分布式电源的运行维护成本系数。In formula (11), is the operation and maintenance cost coefficient of the i-th distributed power generation.
所述步骤四中，工业负荷优化调度模型的约束条件如式(12)-式(21)所示：In the step 4, the constraints of the industrial load optimal dispatching model are shown in formula (12) - formula (21):
zch,t+zdis,t≤1 (17)zch,t +zdis,t ≤1 (17)
Pimin≤Pi≤Pimax (18)Pimin ≤Pi ≤Pimax (18)
|Pi,t-Pi,t-1|≤ri (19)|Pi,t -Pi,t-1 |≤ri (19)
式(12)表示所述第s个储存编号的工业产品的储存容量约束，和分别为所述第s个储存编号的工业产品的最小和最大储存容量；Formula (12) represents the storage capacity constraint of the industrial product of the sth storage number, with The minimum and maximum storage capacities of the industrial products with the sth storage number respectively;
式(13)表示所述第k个编号的生产任务的运行点的约束，第k个编号的生产任务在第t个时段内只能在一种运行点上运行；Formula (13) represents the constraint of the operating point of the kth numbered production task, and the kth numbered production task can only run on one kind of operating point in the tth time period;
式(14)表示所述能量储能单元的容量约束，0和分别为所述能量储能单元的最小和最大储存容量限制；Equation (14) represents the capacity constraint of the energy storage unit, 0 and are the minimum and maximum storage capacity limits of the energy storage unit, respectively;
式(15)表示所述能量储能单元的最大充电速率限制，为所述能量储能单元的最大充电速率；zch,t为二进制变量，表示所述能量储能单元在第t个时段是否充电；Formula (15) represents the maximum charging rate limit of the energy storage unit, is the maximum charging rate of the energy storage unit; zch, t is a binary variable, indicating whether the energy storage unit is charged in the tth period;
式(16)表示所述能量储能单元的最大放电速率限制，为所述能量储能单元的最大放电速率；zdis,t为二进制变量，表示所述能量储能单元在第t个时段是否放电；Formula (16) represents the maximum discharge rate limit of the energy storage unit, is the maximum discharge rate of the energy storage unit;zdis,t is a binary variable, indicating whether the energy storage unit is discharged in the tth period;
式(17)表示所述能量储能单元在第t个时段不能同时充电和放电约束；Equation (17) represents that the energy storage unit cannot be simultaneously charged and discharged during the tth period;
式(18)表示所述第i个分布式电源自身发电能力的约束，Pimax和Pimin分别为所述第i个分布式电源的输出功率的上限和下限；Formula (18) represents the constraints of the i-th distributed power generation capacity itself, and Pimax and Pimin are the upper and lower limits of the output power of the i-th distributed power source, respectively;
式(19)表示所述第i个分布式电源的爬坡速率限制，Pi,t-1为所述第i个分布式电源在第t-1个时段内的输出功率；ri为所述第i个分布式电源的最大爬坡速率；Equation (19) represents the climbing rate limit of the i-th distributed power supply, Pi,t-1 is the output power of the i-th distributed power supply in the t-1 period; ri is the The maximum climbing rate of the i-th distributed power supply;
式(20)表示能量平衡约束；为工业企业与主电网在第t个时段的实际交互电量；Equation (20) represents the energy balance constraint; is the actual interactive power between the industrial enterprise and the main power grid in the tth period;
式(21)为工业企业与主电网间的传输容量约束；L1为工业企业向所述主电网输送电力的功率下限，L2为所述主电网向工业企业输送电力的功率上限。Equation (21) is the transmission capacity constraint between the industrial enterprise and the main grid; L1 is the lower limit of the power that the industrial enterprise transmits to the main grid, and L2 is the upper limit of the power that the main grid transmits to the industrial enterprise.
与已有技术相比，本发明有益效果体现在：Compared with the prior art, the beneficial effects of the present invention are reflected in:
1、本发明通过实施需求响应将峰时段的工业负荷向谷时段和平时段转移，达到了削峰填谷的作用，提高了分时电价环境下主电网运行的安全性和稳定性，并降低了工业企业的用电成本。1. The present invention transfers the industrial load in the peak period to the valley period and the peace period through the implementation of demand response, thereby achieving the effect of peak shaving and filling the valley, improving the safety and stability of the operation of the main power grid under the time-of-use electricity price environment, and reducing the industrial load. Enterprise electricity costs.
2、本发明将能量储能单元纳入到调度模型中，考虑了能量储能单元的储电量模型，能量储能单元通过谷时段充电和峰时段放电，使削峰填谷的效果更加显著，并有助于降低工业企业的用电成本。2. The present invention incorporates the energy storage unit into the scheduling model, and considers the storage capacity model of the energy storage unit. The energy storage unit is charged during the valley period and discharged during the peak period, so that the effect of peak shaving and valley filling is more significant, and It helps to reduce the electricity cost of industrial enterprises.
3、本发明考虑了分布式发电单元对工业负荷优化调度的影响，将分布式发电单元的发电成本纳入到调度目标中，分布式发电单元能更灵活地为工业企业提供电能，这能进一步的减少工业企业的用电成本。3. The present invention considers the influence of the distributed power generation unit on the optimal scheduling of industrial loads, and incorporates the power generation cost of the distributed power generation unit into the scheduling target. The distributed power generation unit can provide electric energy for industrial enterprises more flexibly, which can further improve Reduce the electricity cost of industrial enterprises.
4、本发明考虑了工业生产中工业产品的储存容量约束和生产任务的运行点约束，并将能量储能单元和分布式发电单元的相关约束条件纳入到调度模型中，使调度模型的约束条件更加完善，更符合实际情况。4. The present invention considers the storage capacity constraints of industrial products and the operating point constraints of production tasks in industrial production, and incorporates the relevant constraints of energy storage units and distributed power generation units into the scheduling model, so that the constraints of the scheduling model It is more perfect and more in line with the actual situation.
附图说明Description of drawings
图1为本发明的整体结构图；Fig. 1 is the overall structural diagram of the present invention;
图2为本发明的粒子群算法流程图。Fig. 2 is a flow chart of the particle swarm algorithm of the present invention.
具体实施方式detailed description
本实施例中，一种基于需求响应的工业负荷优化调度建模方法，如图1所示，是应用于包含能量储能单元、分布式发电单元和主电网构成的工业企业生产环境中，包括以下步骤：In this embodiment, a demand response-based industrial load optimization scheduling modeling method, as shown in Figure 1, is applied to an industrial enterprise production environment composed of an energy storage unit, a distributed power generation unit and a main power grid, including The following steps:
步骤一、根据工业负荷特性，将工业负荷分为可调度负荷和不可调度负荷；并将可调度负荷分为可转移负荷和可控制负荷，可转移负荷有开和关两种运行点，可控制负荷有多种不同功率的运行点；某汽车制造业的零部件生产系统中的生产任务和运行点如表一所示；其中零部件生产任务1为不可调度负荷；零部件生产任务2为可转移负荷；零部件生产任务3为可调度负荷，有3种不同功率的运行点；Step 1. According to the characteristics of industrial loads, industrial loads are divided into dispatchable loads and non-dispatchable loads; dispatchable loads are divided into transferable loads and controllable loads. Transferable loads have two operating points, on and off, which can be controlled The load has a variety of operating points with different powers; the production tasks and operating points in the parts production system of an automobile manufacturing industry are shown in Table 1; among them, the parts production task 1 is a non-schedulable load; the parts production task 2 is a schedulable load. Transfer load; parts production task 3 is a schedulable load, with 3 operating points of different power;
表一Table I
步骤二、对可调度负荷的运行过程进行建模，得到工业生产的储存模型和电力需求量；对能量储能单元进行建模，得到储电量模型；对分布式发电单元进行建模，得到发电量；Step 2: Model the operation process of the schedulable load to obtain the storage model and power demand of industrial production; model the energy storage unit to obtain the power storage model; model the distributed generation unit to obtain the power generation quantity;
工业生产的储存模型如式(1)所示：The storage model of industrial production is shown in formula (1):
式(1)中,t为时段编号，k为生产任务编号，s为工业产品的储存编号；Ss,t为第s个储存编号的工业产品在第t个时段的储存数量；Ss,t-1为第s个储存编号的工业产品在第t-1个时段的储存数量；Tp,s为所有生产第s个储存编号的工业产品的生产任务集合，Tc,s为所有消耗第s个储存编号的工业产品的生产任务集合；Ps,k,t为第k个编号的生产任务在第t个时段生产第s个储存编号的工业产品的数量，并由式(2)获得；Cs,k,t为第k个编号的生产任务在第t个时段消耗第s个储存编号的工业产品的数量，并由式(3)获得：In formula (1), t is the period number, k is the production task number, s is the storage number of the industrial product; Ss,t is the storage quantity of the industrial product with the sth storage number in the tth time period; Ss, t-1 is the storage quantity of the industrial product with the sth storage number in the t-1 period; Tp,s is the set of production tasks for all the industrial products with the sth storage number, and Tc,s is all consumption The production task set of the industrial product with the sth storage number; Ps,k,t is the quantity of the industrial product with the sth storage number produced by the kth numbered production task in the tth time period, and is expressed by formula (2) Obtained; Cs, k, t is the quantity of industrial products with the s storage number consumed by the production task of the kth number in the tth time period, and obtained by formula (3):
式(2)中,pk,m,s为第k个编号的生产任务在第m个运行点运行时生产第s个储存编号的工业产品的速率；zk,m,t为二进制变量，表示第k个编号的生产任务在第t个时段的第m个运行点的运行状态；In formula (2), pk, m, s is the production rate of the production task of the kth serial number at the mth operation point to produce the industrial product of the sth serial number; zk, m, t is a binary variable, Indicates the running status of the k-th numbered production task at the m-th running point in the t-th time period;
式(3)中,ck,m,s为第k个编号的生产任务在第m个运行点运行时消耗第s个储存编号的工业产品的速率；In formula (3), ck, m, s is the rate at which the production task of the kth number consumes the industrial product of the sth storage number when it runs at the mth operating point;
工业生产的电力需求量是由式(4)得到：The power demand of industrial production is obtained by formula (4):
式(4)中，Et为工业生产中第t个时段的电力需求量；ek,t为第k个编号的生产任务在第t个时段的耗电量，并由式(5)获得：In formula (4), Et is the power demand in the t-th period of industrial production; ek,t is the power consumption of the k-th numbered production task in the t-th period, and is obtained by formula (5) :
式(5)中,ek,m为第k个编号的生产任务在第m个运行点运行时单位时间的耗电量；In formula (5), ek,m is the power consumption per unit time when the k-th numbered production task is running at the m-th operating point;
能量储能单元的储电量模型为：The storage capacity model of the energy storage unit is:
式(6)中，和分别为能量储能单元在第t个时段结束时和第t-1个时段结束时的储电量；和分别为能量储能单元在第t时段内的充电量和放电量；ηch和ηdis分别为能量储能单元的充电效率和放电效率，充电效率和放电效率通常都取0.9；In formula (6), with are the storage capacity of the energy storage unit at the end of the t-th period and at the end of the t-1th period, respectively; with Respectively, the charging capacity and discharging capacity of the energy storage unit in the tth period; ηch and ηdis are the charging efficiency and discharging efficiency of the energy storage unit respectively, and the charging efficiency and discharging efficiency are usually 0.9;
分布式发电单元的发电量是利用式(7)得到：The power generation of the distributed generation unit is obtained by using formula (7):
式(7)中，EDER,t为分布式发电单元在第t个时段的发电量；i为分布式发电单元中分布式电源的编号，N为分布式发电单元中分布式电源的总数；Pi,t为第i个分布式电源在第t个时段的发电量。In formula (7), EDER,t is the power generation of the distributed generation unit in the tth time period; i is the number of the distributed generation in the distributed generation unit, and N is the total number of distributed generation in the distributed generation unit; Pi,t is the power generation of the i-th distributed power generation in the t-th period.
步骤三、建立分时电价环境下工业负荷优化调度模型的目标函数；Step 3, establishing the objective function of the industrial load optimal dispatching model under the time-of-use electricity price environment;
基于需求响应的工业负荷优化调度模型的目标函数如式(8)所示：The objective function of the optimal scheduling model of industrial load based on demand response is shown in formula (8):
式(8)中，C为工业负荷优化调度后的总成本；T为工业负荷优化调度在一个周期内的总时段数；ppt和pst分别为分时电价环境下第t个时段的购电价格和售电价格，某分时电价环境下的购售电价格如表二所示：In formula (8), C is the total cost after optimal dispatching of industrial load;Tis the total time period of industrial load optimal dispatching in one cycle; The price of electricity and the price of electricity sales, the purchase and sale of electricity prices under a time-of-use electricity price environment are shown in Table 2:
表二Table II
Ep,t和Es,t分别为第t个时段的购电量和售电量；CDER为分布式发电单元的电力生产成本，并由式(9)获得：Ep,t and Es,t are the purchased electricity and sold electricity in the t-th time period respectively; CDER is the electricity production cost of the distributed generation unit, which is obtained by formula (9):
式(9)中，Pi,t为第i个分布式电源在第t个时段内的输出功率；Fi(Pi,t)为第i个分布式电源在第t个时段内的燃料成本，并由式(10)获得；OMi(Pi,t)为第i个分布式电源在第t个时段内的运行维护成本，并由式(11)获得：In formula (9), Pi,t is the output power of the i-th distributed power generation in the t-th time period; Fi (Pi,t ) is the fuel consumption of the i-th distributed power generation in the t-th time period The cost is obtained by formula (10); OMi (Pi,t ) is the operation and maintenance cost of the i-th distributed power generation in the t-th period, and it is obtained by formula (11):
Fi(Pi,t)＝ai+biPi,t+ci(Pi,t)2 (10)Fi (Pi,t )＝ai +bi Pi,t +ci (Pi,t )2 (10)
式(10)中，ai，bi和ci为第i个分布式电源的燃料成本系数；In formula (10), ai , bi and ci are the fuel cost coefficients of the ith distributed power generation;
式(11)中，为第i个分布式电源的运行维护成本系数，表三为常见的分布式电源的运行维护成本系数。In formula (11), is the operation and maintenance cost coefficient of the i-th distributed power supply, and Table 3 shows the operation and maintenance cost coefficient of the common distributed power supply.
表三Table three
步骤四、确定工业负荷优化调度模型的约束条件，并与目标函数构成基于需求响应的工业负荷优化调度模型。Step 4: Determine the constraint conditions of the industrial load optimal dispatch model, and form an industrial load optimal dispatch model based on demand response with the objective function.
工业负荷优化调度模型的约束条件如式(12)-式(21)所示：The constraints of the industrial load optimal dispatching model are shown in formula (12) - formula (21):
zch,t+zdis,t≤1 (17)zch,t +zdis,t ≤1 (17)
Pimin≤Pi≤Pimax (18)Pimin ≤Pi ≤Pimax (18)
|Pi,t-Pi,t-1|≤ri (19)|Pi,t -Pi,t-1 |≤ri (19)
式(12)表示第s个储存编号的工业产品的储存容量约束，和分别为第s个储存编号的工业产品的最小和最大储存容量；Equation (12) represents the storage capacity constraint of the industrial product with the sth storage number, with The minimum and maximum storage capacities of industrial products with the sth storage number respectively;
式(13)表示第k个编号的生产任务的运行点的约束，第k个编号的生产任务在第t个时段内只能在一种运行点上运行；Equation (13) expresses the constraint of the operating point of the kth numbered production task, and the kth numbered production task can only run on one kind of operating point in the tth time period;
式(14)表示能量储能单元的容量约束，0和分别为能量储能单元的最小和最大储存容量限制；Equation (14) represents the capacity constraint of the energy storage unit, 0 and are the minimum and maximum storage capacity limits of the energy storage unit, respectively;
式(15)表示能量储能单元的最大充电速率限制，为能量储能单元的最大充电速率，zch,t为二进制变量，表示能量储能单元在第t个时段是否充电；Equation (15) represents the maximum charging rate limit of the energy storage unit, is the maximum charging rate of the energy storage unit, zch,t is a binary variable, indicating whether the energy storage unit is charged in the tth time period;
式(16)表示能量储能单元的最大放电速率限制，为能量储能单元的最大放电速率，zdis,t为二进制变量，表示能量储能单元在第t个时段是否放电；Equation (16) represents the maximum discharge rate limit of the energy storage unit, is the maximum discharge rate of the energy storage unit, zdis,t is a binary variable, indicating whether the energy storage unit is discharged in the tth time period;
式(17)表示能量储能单元在第t个时段不能同时充电和放电约束；Equation (17) expresses the constraint that the energy storage unit cannot be charged and discharged simultaneously in the tth time period;
式(18)表示第i个分布式电源自身发电能力的约束，Pimax和Pimin分别为第i个分布式电源的输出功率的上限和下限；Equation (18) expresses the constraint of the i-th distributed power generation capacity itself, Pimax and Pimin are the upper limit and lower limit of the i-th distributed power output power respectively;
式(19)表示第i个分布式电源的爬坡速率限制，Pi,t-1为第i个分布式电源在第t-1个时段内的输出功率；ri为第i个分布式电源的最大爬坡速率；Equation (19) represents the climbing rate limit of the i-th distributed generation, Pi,t-1 is the output power of the i-th distributed generation in the t-1 period; ri is the output power of the i-th distributed The maximum ramp rate of the power supply;
式(20)表示能量平衡约束；为工业企业与主电网在第t个时段的实际交互电量；Equation (20) represents the energy balance constraint; is the actual interactive power between the industrial enterprise and the main power grid in the tth period;
式(21)为工业企业与主电网间的传输容量约束；L1为工业企业向主电网输送电力的功率下限，L2为主电网向工业企业输送电力的功率上限。Equation (21) is the transmission capacity constraint between industrial enterprises and the main grid; L1 is the lower limit of the power transmission of industrial enterprises to the main grid, and L2 is the upper limit of power transmission from the main grid to industrial enterprises.
步骤五、通过优化算法对工业负荷优化调度模型进行求解，获得对可调度负荷的最优调度结果；本实施例采用粒子群优化算法，图2为粒子群算法的求解流程图；粒子群算法首先在可行解空间中初始化一群粒子，每个粒子都代表极值优化问题的一个潜在最优解，用位置、速度和适应度值三项指标表示该粒子的特征，适应度值由适应度函数计算得到，其值的好坏表示粒子的优劣。粒子在解空间中运行，通过跟踪个体极值和群体极值更新个体位置。个体极值是指个体粒子搜索到的适应度值最优位置，群体极值是指种群中的所有粒子搜索到的适应度最优位置。粒子每更新一次位置，就计算一次适应度值，并且通过比较新的适应度值和个体极值、群体极值的适应度值更新个体极值和群体极值的位置。Step 5, solve the industrial load optimal dispatching model by an optimization algorithm, and obtain the optimal dispatching result of the schedulable load; this embodiment adopts the particle swarm optimization algorithm, and Fig. 2 is a solution flow chart of the particle swarm algorithm; the particle swarm algorithm first Initialize a group of particles in the feasible solution space, each particle represents a potential optimal solution of the extremum optimization problem, and the characteristics of the particle are represented by the three indicators of position, speed and fitness value, and the fitness value is calculated by the fitness function The quality of its value indicates the quality of the particles. The particles run in the solution space, and update the individual position by tracking the individual extremum and group extremum. The individual extremum refers to the optimal position of fitness value searched by individual particles, and the group extremum refers to the optimal position of fitness searched by all particles in the population. Every time the particle updates its position, it calculates the fitness value, and updates the positions of the individual extremum and the group extremum by comparing the new fitness value with the fitness value of the individual extremum and the group extremum.
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| CN111985157A (en)* | 2020-08-19 | 2020-11-24 | 西华大学 | Power utilization model simulation method based on industrial production process |
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| CN109002910A (en)* | 2018-06-29 | 2018-12-14 | 合肥工业大学 | Industrial load Optimization Scheduling and system |
| CN109167350A (en)* | 2018-09-04 | 2019-01-08 | 南方电网科学研究院有限责任公司 | Construction method of industrial load response model |
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