Research on collaborative planning model of main distribution network frame structure and distributed power generation

The electric power industry is going through a relatively large transformation period of energy development, and new electric power equipment such as distributed power supply has emerged as the times require. However, there is often a problem of insufficient coordination between the grid frame and distributed power in the main distribution network. This paper starts with the two main stakeholders, namely, the distributed generation operator and the distribution system operator, to build a two-level collaborative planning model for the main distribution network. With the help of particle swarm optimization algorithm and genetic algorithm with improved constraint factors, the model is solved. In the optimization process, two different scenarios are set, including and not including the distributed generation output, for comparative analysis, the comprehensive cost of the collaborative planning model with distributed generation output is less than that of the collaborative planning model with traditional generation output. The results show that the model in this paper can not only optimize the overall line, but also reduce the excessive investment of the main distribution network, which is more in line with the future development of my country’s power industry, can improve the profits of related enterprises, and achieve a win-win effect.

passively receives electric energy has little impact on the transmission network, and it is unnecessary for the dispatch and control center to conduct collaborative analysis and control on the transmission network and distribution network. However, the requirements of social development on environmental protection are constantly improving, and the energy utilization efficiency and resource allocation ability must be improved. New power equipment such as Distributed Generation (DG), Energy Storage System (ESS) came into being [4]. A large number of these new power equipment are connected to the distribution network, which can not only ease the energy tension, but also bring great changes to the traditional distribution network, enhancing the flexibility and controllability of the distribution network operation mode. The traditional passive distribution network is gradually transformed into an active distribution network. While distributed power supply brings convenience to people, it also brings some problems. For example, the output of distributed generation is random, vulnerable to geographical constraints and uncertainties affected by climate and other factors, and its role in the distribution network is correspondingly limited. In the process of the transformation of the power grid system from passive to active, all new energy power generation is also gradually connected to the grid. The grid still has the problem of insufficient coordination between the distributed power generation and the grid, which still needs to be improved through optimization. At the same time, the diversification of interest subjects in the main distribution network also makes the collaborative optimal configuration between the distributed power generation and the grid become the key [5]. At present, the country is in the construction stage of diversified intelligent power industry [6]. For the planning and operation of the main distribution network, there are many stakeholders, such as load users, distributed power supply operators, distribution system operators, etc. In the coordination of the network structure and distributed power supply of the main distribution network, it is necessary to consider multiple interests to promote configuration optimization in order to achieve a coordinated result [7,8]. In this paper, the cost of the distributed power operator and the distribution system operator are taken as the combined interest subjects, and a two-level collaborative planning model of the main distribution network is established. On the principle of ensuring win-win and maximizing benefits, the optimal planning and configuration scheme of the grid and the distributed power is obtained, so as to achieve the goal of the coordination between the grid and the power supply.

Two-layer collaborative planning framework for main distribution network
Based on the primary network structure planning of the main distribution network, combined with the characteristics of multi stakeholders [9], this paper proposes a two-layer model framework for the collaborative planning of the main distribution network structure and distributed generation. The upper and lower levels of the bilevel programming model are mutually affected and interrelated. The lower level carries out optimization simulation under the decision scheme of the upper level, and its simulation results will be returned to the upper level as part of its objective function or constraint conditions, thus affecting the decision scheme of the upper level. Based on the two-layer hybrid optimization theory, this framework establishes a two-layer optimization model with distribution network comprehensive cost as the first layer and distributed generation comprehensive cost as the second layer. The first layer of structure is mainly for the structural planning of distribution network, while the second layer of structure is mainly for the optimization of distributed power configuration. The first layer drives the second layer, and the two-layer linkage is used to obtain the optimal planning and configuration scheme of grid and power under the premise of ensuring a win-win situation and maximizing the benefits, so as to achieve the goal of coordination between the two.

Collaborative planning model of main distribution network structure
The collaborative planning model of the main distribution grid structure takes the minimum system cost at the end of the year as the objective function, and its expression is as follows: F is the objective function of the lower model, and e F is the reduced environmental protection cost after the distributed power generation is connected to the grid. The detailed calculation formulas of various costs in the objective function are as follows: In the formula:  represents the discount rate, 1) The load rate of each line must be within the specified range; 2) The total load of each substation cannot exceed the maximum load limit; 3) The wiring mode is restricted to single connection; 4) The voltage of the load node must be within the specified range; 5) All load nodes are connected with other load nodes and source nodes to prevent the formation of power distribution islands; The second-level planning mainly considers the access location and capacity of distributed power sources, and takes the minimization of operating costs as the objective function. The objective function is as follows: In the formula:

Model solving
The bilevel programming model proposed in this paper has complex integer nonlinearity and cannot be solved directly. At the same time, due to the large amount of calculation, optimization algorithm is required to solve the model, as shown in Figure 1. The first layer of structure is realized by particle swarm optimization algorithm, which transfers the grid line information to the second layer. The second layer of structure is realized by genetic algorithm. The location and access capacity of the planned distributed power supply are transferred back to the upper layer. The first layer selects new grid line information through configuration optimization, and then transfers it back to the second layer for the next round of optimization.

Improvement of Particle Swarm Optimization
The standard form of traditional particle swarm optimization algorithm [10] is as follows： It can be seen that in traditional particle swarm optimization algorithm, constraint factor a is generally used to improve the speed of constrained particles. Formula (17) can be written as

Experimental design
The actual regional main distribution network planning of 28 nodes in a region of Chongqing is analyzed as a case, and the model built in this paper is tested. The planned regional network structure is shown in Figure 2. Node 0 here represents the regional power node, and other nodes are load points, numbered sequentially. Taking wind power generation as an example, the actual location of the structure area can find the access location of five wind turbines, which is represented by a red circle. The solid line represents the new line to be selected. There are 32 lines in the figure. To simplify the calculation example, each line needs to be unified. The impedance parameter is set as (0.25+0.005j) Ω/km, and the total distributed power capacity is 25% of the original maximum system load. The relevant parameter information in the case is set as follows: Table 1 is the relevant parameters of the planning model, and Table 2 is the relevant economic parameters and environmental cost parameters of the distributed power generation output.  Overlap probability between parent and child 0.8 Table 2. Economic and environmental cost parameters related to distributed power output.     After comparative analysis of the data in Table 3 and Table 4, it can be seen that scenario 1 considers DG costs, and its annual comprehensive costs are 2.6783 million yuan lower than scenario 2. For DG operators, it can bring profits of 1.0074 million yuan. It can be seen that reasonable DG access can effectively reduce the construction and operation costs of the main distribution network, thus making both operators profit. In the era of new energy access to the power grid, the main distribution network operators will have more choices in their power purchase channels, which are no longer limited to the superior power grid. When scenario I is adopted for power purchase, their DG power purchase costs and superior power purchase costs are 2237800 yuan and 46.5243 million yuan respectively, which is only 1.4754 million yuan less than scenario II power purchase costs; After the DG is connected, the actual power purchase of the main distribution network is reduced, and some loads can be adaptively balanced, which effectively reduces the power flow in the network and makes it have loss reduction performance. The cost of scenario 1 in terms of network loss is reduced by 1.3269 million yuan compared with scenario 2; In consideration of environmental protection, after the use of DG power generation with clean characteristics, Scenario 1 will spend 123100 yuan less on environmental protection than Scenario 2. It can be seen that after the introduction of new energy, the main distribution network has better environmental protection performance, which is consistent with the green energy strategy proposed by China.

Conclusion
Based on the theory of bilevel programming, this paper constructs a collaborative bilevel programming model of grid structure and distributed generation in the main distribution network. The model is solved by particle swarm optimization algorithm and genetic algorithm with improved constraint factors. Through the actual case, we can draw a conclusion: when planning the main distribution network structure, determining the capacity and location of the distributed power generation can fit the era development background of the future when a large number of distributed power sources are connected to the power grid, making full and reasonable use of new energy, which can not only optimize the overall line, but also reduce the excessive investment in the main distribution network; Considering the design of main distribution network of multiple stakeholders, it is more consistent with the development of China's future power industry, which can improve the income of related enterprises and achieve winwin results; With the increasing elements of the main distribution network, the model planning is becoming more and more complex. Future research needs to consider the collaborative planning of these new elements through a planning method with a multi-layer structure.