Low Carbon Economic Dispatch of Rural Distribution Network under High Photovoltaic Penetration

To promote the low-carbon development of the power grid, the penetration rate of distribution photovoltaics in power systems has greatly increased. Some distribution networks may switch roles between energy producers and energy consumers multiple times a day. Especially in rural areas with low loads and abundant land resources, a large number of distributed photovoltaics may increase the energy balancing burden of the transmission system. To address this, the optimal operation of local resources is the key to the local accommodation of photovoltaics. In rural distribution networks, the light industrial load and agricultural load in rural distribution networks have similar electricity consumption behavior, and are suitable for centralized load management. This article proposes a low-carbon economic dispatch model of rural distribution networks under high photovoltaic penetration.. In specific, the light industrial load and the agricultural load are modeled considering their production requirements. Carbon emission costs and photovoltaic consumption costs are incorporated into the dispatch model of the distribution network. The case study is conducted based on a rural distribution network. The results of the case study indicated that the proposed model could increase the photovoltaic absorption rate by 10.96% and reduce carbon emissions by 3.4% for the test system.


Introduction
With the increase of the distributed photovoltaic generations, excess power may feed back into the substation and transmission grid [1,2], which may increase the energy balancing burden of the power system.When the penetration rate of distributed power sources exceeds 100%, it will cause power backflow in the area [3].To address this, local resources in rural distribution networks can be utilized to increase the consumption of local photovoltaics.
The proportion of light industrial load and agricultural load in rural distribution networks is relatively large, which is an important resource for participating in low-carbon dispatch of rural distribution networks.On the one hand, light industrial loads have the characteristics of flexible electricity consumption and great potential for regulation and development [4,5].Reference [6] proposed a typical industrial load optimization model and constructed an environmental and economic dispatch model for wind power systems with source load coordination.Reference [7] evaluated the multi-energy flexibility of distributed systems considering the adjustability of production processes.Reference [8] estimated the flexible region considering the operational requirements of internal energy devices.On the other hand, the agricultural loads have the characteristics of extensive management and strong seasonality [9].Reference [10] proposed a control strategy for micro energy networks based on blockchain technology, utilizing the time-varying characteristics of agricultural loads.
The references above respectively consider the participation of industrial loads or agricultural loads in the scheduling of distribution networks.In this paper, a low-carbon economic dispatch model of rural distribution networks under high photovoltaic penetration is proposed.In the low-carbon dispatch model, the light industrial load and the agricultural load that can be scheduled are included.and the photovoltaic consumption costs and carbon emission costs are added to the objective function.Finally, a modified IEEE 33-bus distribution system is used to demonstrate the effectiveness of the proposed model.

Modeling of rural distribution network load
The rural distribution network mainly includes light industrial load, agricultural load, and residential electricity load.Below, the light industrial load and the agricultural load are modeled considering their production requirements and load characteristics.

Light industry load modeling
Compared to the residential load, the rural light industrial load is mostly used for the processing of various raw materials and agricultural and sideline products.Taking theload of an automatic production line as an example, based on its operating characteristics, a light industry load model is constructed as follows.
The modeling of automatic production line load mainly needs to consider the time requirements of the entire production process [11].Once the automatic production line is started, its continuous working time should be greater than or equal to the duration of one production demand.The start/stop state of the automatic production line load is expressed as: where , i t E is the working status of the automatic production line i during the time period t .If the automatic production line is in production during the time period t , its value is 1, otherwise it is 0; i DT is the duration of the automatic production line i meeting a production demand; on T and off T respectively represent the working hours and off hours of local light industry.To indicate that the working time of the production line is exactly equal to the duration of production demand, the working time of the automatic production line should be less than or equal to the duration of a production.The following constraint is established.
Therefore, Equations (1) and (2) indicate that if the production line starts working, it will continue to work during the duration of one production demand.There will be a rest scheduling period after completion, which is the rest time between the two productions.
The active and reactive power consumed by the production line i during the time period t can be represented by the following equations: , , , , , , q are the active and reactive power consumed by the automatic production line i during the time period t ., i p R and , i q R respectively represent the rated active and reactive power of the automatic production line i .
15 minutes as a scheduling period, so one day is divided into 96 scheduling periods.The output of the automatic production line i within a scheduling cycle can be expressed as: where , i t U represents the unit output of the automatic production line i within a scheduling cycle., represents the output of the automatic production line i within a scheduling cycle.

Agricultural load modeling
The main agricultural load in rural areas is planting.The electrical equipment for planting agriculture generally comes from the water pump required for drainage and irrigation.At present, most water pumps can control the water flow rate of the pumps by adjusting the angle of the blades, which provides conditions for clustered management of electric drainage and irrigation.
For electric drainage and irrigation, the electrical load can be approximately calculated using the flow rate and head.The active and reactive power consumed by electric drainage and irrigation at any time can be represented by the following equation [9]: , , , , , where , pg i t p and , pg i t q respectively represent the active power and the reactive power consumed by the electric drainage and irrigation i during the time period t .g is the acceleration of gravity, taken as 2 9.81 / m s ., i t Q and , i t H are respectively the water flow rate and the total head of the electric drainage and irrigation i during the time period t .K is the total efficiency of the water pump, motor, and transmission device, a single stage water pump can be taken as 0.7.pg O is the ratio of reactive power to active power of electric drainage and irrigation, and it is generally taken as 0.5.

Power flow model of distribution network
Considering that the distribution network is radial, the DistFlow model is usually used to describe the power flow distribution.In addition, the model can be linearized under reasonable assumptions [12].The linearized DistFlow model can be shown as: where , j t P and , j t Q are the active and reactive power from node j to node 1 j at time t respectively; , j t p and , j t q are the active power demand and reactive power demand of the node j at time t respectively; , j t V is the voltage of the node j at time t ; j R and j X are the resistance and reactance of the branch from node j to node i respectively.The operational constraints of the distribution network are node steady-state voltage constraints, as shown in the following equation: where min V and max

V
are the lower and upper limits of the node voltage, which can generally be set to 0.95 p.u. and 1.05 p.u. respectively.
Each node is connected to light industrial automatic production line loads, agricultural electricity drainage and irrigation loads, residential loads and distributed photovoltaics.The power balance constraints are as follows: The difference W ' between the given distributed photovoltaic consumption requirements and the actual consumption of distributed photovoltaic is shown in the following equation: where r W represents the distributed photovoltaic consumption requirements.Therefore, the distributed photovoltaic consumption cost of rural distribution networks can be represented by the following equation: where gc C represents the distributed photovoltaic consumption cost of rural distribution network; gc [ indicates the price of the green certificate.

Low carbon dispatch model for distribution network
The optimization goal of the low-carbon dispatch model is to minimize all operating costs of the rural distribution network, which includes electricity purchase costs, carbon emission costs, distributed photovoltaic consumption costs, and possible production loss costs, as shown in the following equation: where f is all operating costs of the rural distribution network; buy C is the cost of purchasing electricity from the superior power grid.C C is the cost of carbon emissions; y C is the potential cost of production loss.
The cost of purchasing electricity from the superior power grid is expressed as follows: 1, 1 where t [ is the electricity price at time t .The cost of carbon emissions caused by purchasing electricity from the superior power grid and distributed photovoltaic consumption are expressed as follows: where C E is the carbon emissions of rural distribution networks; C [ is unit price for carbon emissions.
PV D and grid D respectively represent the conversion coefficients of distributed photovoltaic power generation and electricity from the superior power grid.
The possible cost of production loss only considers the load of the light industry.If the total output of the light industry automatic production line is less than the required output value in one day, it will result in a loss of output value, as shown in the following equation: where , i tar Y represents the total required output value given by the automatic production line within one day.U [ is the value per unit output.The function max represents taking the maximum value of subsequent elements.

Case setting
The test system is a modified IEEE-33 distribution network, as shown in Figure 1. 6 PV generators, 16 automatic production lines, and 6 electric drainage and irrigations are added to the distribution network.In the case study, the duration of a single production on the automatic production line is an hour; The working hours and off hours are 7 am and 8 pm respectively.The rated active power of the automatic production line is 170 kW; A node can have up to 5 automatic production lines working simultaneously.The unit time output of one automatic production line is 100 kg/h, and the daily target output is 2000 kg.
The electricity prices and average head of electric drainage and irrigation at different time periods are shown in Table 1.The parameters of average head of electric drainage and irrigation come from reference [9].283. 5 7 In the case study, the distributed photovoltaic consumption requirement given in the high proportion photovoltaic rural distribution network area is 1000 MWh; The photovoltaic output data comes from the modified typical daily output curve.The green certificate price is 100 yuan/MWh.
The unit price of carbon emissions is 50 yuan/ton; The conversion coefficients for distributed photovoltaic power generation and electricity from the superior power grid are 0.040 kg/(kWh) and 0.5246 kg/(kWh) respectively.The required total output of the automatic production line within one day is 32000 kg; The value of unit production is 50 yuan/kg.
In scenario 1, the light industrial load is produced according to the schedule set by the company, while the agricultural electricity drainage and irrigation load is operated according to the wishes of farmers.In scenario 2, the limitations of production time and yield value are considered for the light industrial load, and the water demand and the head of electric drainage and irrigation are considered for the agricultural load.

Case analysis
The low-carbon dispatch of rural distribution networks was carried out using the proposed method, and the results are shown in Figure 2 and Table 2.In terms of photovoltaic consumption: From Figure 2, it can be seen that the proposed low-carbon dispatch model can effectively improve the photovoltaic consumption rate.The photovoltaic grid capacity is 1073.7 MW.In scenario 1, the photovoltaic consumption capacity is 780.945MW, and the photovoltaic consumption rate is 72.73%.In scenario 2, the photovoltaic consumption capacity is 898.533MW, and the photovoltaic consumption rate is 83.69%.The photovoltaic consumption rate in scenario 2 increased by 10.96% compared to that in scenario 1.
In terms of carbon emissions: From Table 2, it can be seen that the proposed low-carbon dispatch model can effectively reduce carbon emissions.In scenario 1, the carbon emissions are 94.13 tons, and the carbon emission cost is 4706.5 yuan.In scenario 2, the carbon emissions are 91.05tons, and the carbon emission cost is 4552.3yuan.The carbon emissions in scenario 2 decreased by 3.4% compared to that in scenario 1.
From Figure 2 and Table 2, it can be seen that in scenario 2, between 10:00 and 16:00 in a day, the photovoltaic grid capacity is the highest.Compared with scenario 1, light industrial load and agricultural load in scenario 2 can effectively improve the photovoltaic consumption rate of the local distribution network.Besides, it could reduce carbon emissions and the total operating cost of the rural distribution network.

Conclusion
To promote the low-carbon operation of rural distribution networks and the consumption of distributed photovoltaics, this paper proposes a low-carbon scheduling model for rural distribution networks under high photovoltaic penetration.The light industrial load and the agricultural load are modeled considering their production requirements.Carbon emission costs and photovoltaic consumption costs are incorporated into the optimization objective function.A case study of the modified IEEE-33 distribution system validate the results.Compared to before scheduling, the photovoltaic consumption rate after scheduling increased by 10.96% and carbon emissions decreased by 3.4%.The proposed model not only effectively improves the consumption of photovoltaic of the local distribution network, but also reduces carbon emissions and the operating costs of the distribution network.

Figure 1 .
Figure 1.Diagram of the modified distribution network.

Figure 2 .
Figure 2. Comparison diagram of photovoltaic consumption before and after scheduling.

Table 1 .
Electricity prices and average head at different time periods.

Table 2 .
Comparison of costs in scenario 1 and scenario 2.