Optimization Model Of Distribution Network Research Articles

A two‐stage scheduling model for urban distribution network resilience enhancement in ice storms

AbstractThis paper proposes a two‐stage stochastic scheduling model for urban distribution network resilience enhancement against ice storms, which coordinates mobile deicing equipment routing and distributed energy resources dispatching. An improved line ice thickness prediction model and a photovoltaic power generation prediction method in accordance with conditional generative adversarial networks are proposed to provide data boundaries for scheduling strategy. Facing the uncertainty of line failure, a two‐stage scenario‐based distribution network optimization model is established. At first stage, the mobile deicing equipment routing strategy is decided to mitigate the impact caused by ice storms. The Monte‐Carlo simulation method is introduced to describe the uncertainty of line failure due to ice acceleration. For the second stage, based on the results of photovoltaic forecasting and possible distribution line failure scenario generated by Monte‐Carlo simulation method, the optimal distributed energy resources dispatching strategy can be obtained through the mixed integer programming. The proposed model is simplified to a mixed integer linear programming model that can be solved by a commercial solver. The test results on the modified IEEE 33‐node system and modified 69‐node system demonstrate that the proposed method can effectively improve the resilience performance of urban distribution network under ice storms.

Water Distribution Network Optimization Model with Reliability Considerations in Water Flow (Debit)

Water distribution networks (WDNs) are defined as the planning for the development, distribution, and utilization of water resources. The main challenge of WDNs is to preserve limited water resources while providing effective benefits from these resources in accordance with environmental considerations. Water distribution networks use hydraulic components to connect water resources to consumers. The diameter of each pipe, the layout of the pipe network, and the total length of pipes all contribute to the most effective layout for a water distribution system. This study considers the assurance that the flow (discharge) of water is in accordance with what is expected, with such aspects apt to be described as a particular form of reliability. As a result, this study proposes a stochastic optimization model with non-linear probability constraints for overcoming the challenges of water distribution networks while taking water flow reliability into account. The pressure drop equation causes the non-linear shape. The stochastic model of the opportunity constraint is changed to a deterministic multi-objective model using an approach based on integer programming and sample averaging to solve the resulting model. The direct search approach (neighbourhood search) is then applied to tackle the integer part.

Distribution Network Optimization Model of Industrial Park with Distributed Energy Resources under the Carbon Neutral Targets

Distribution Network Optimization Model of Industrial Park with Distributed Energy Resources under the Carbon Neutral Targets

Hierarchical multi-objective optimal planning model of active distribution network considering distributed generation and demand-side response

Power grid planning is the basis of power system development, the structure of distribution network in China has changed from single source unidirectional network to multi-source multidirectional complex power network, which further increases the uncertainty and complexity of distribution network operation and planning. From the perspective of distributed energy grid connection, this paper constructs a hierarchical optimization model of distribution network planning under active management mode. The relationship among balanced network loss, line investment, power purchase cost, carbon emission cost and policy subsidies are comprehensively considered. To improve the convergence and effectiveness of the algorithm, NSGA-TS hybrid algorithm is applied for example analysis, which has better global search and local search ability. From the calculation and analysis results of an example, it can be seen that the model is effective in practical analysis, and expands the analysis idea of distribution network planning.

Multi-objective distribution network planning method with distributed generation based on non dominated sorting differential evolution algorithm

Combined with the specific problems of distribution network planning with distributed generation, this paper constructs a multi-objective optimization model of distribution network planning with distributed generation. According to the distributed generation distribution network layout planning with distributed generation, under the condition of uncertain load prediction value of distributed generation distribution network, taking the minimum voltage stability index, minimum network loss and minimum investment cost of distributed generation as sub objectives, a multi-objective programming model is established, and the model is solved by non dominated sorting differential evolution (NSDE) algorithm.

Optimal Operation Of Distribution Network With Photovoltaic

As a clean, renewable and abundant new energy, photovoltaic power generation has gradually gained people’s favor after wind power. Affected by weather, light intensity and temperature, the output of photovoltaic power generation has obvious fluctuation and uncertainty, which seriously threatens the safe and stable operation of power system. Therefore, it is of great practical significance to study the optimal operation of distribution network containing photovoltaic. In this paper, the short-term output characteristics of photovoltaic power generation are studied, and the short-term output model of photovoltaic power generation is established by using the probability distribution of “clear sky index”. On this basis, based on the power flow calculation principle of DistFlow, the operation optimization model of distribution network with photovoltaic power plants is established, and the stochastic characteristics of photovoltaic power generation are flexibly handled by the opportunity constraint method. Using this model, the influence of the stochastic characteristics of photovoltaic power generation on the day-ahead dispatching and reserve capacity of distribution network is calculated and analyzed.

An Optimization Model for Logistics Distribution Network of Cross-Border E-Commerce Based on Personalized Recommendation Algorithm

In order to solve the problems of poor timeliness and high service cost caused by international logistics of cross-border e-commerce and to realize the localization of cross-border trade and improve consumers' shopping experience, much cross-border e-commerce has introduced overseas warehouse business. Because the optimization model for the logistics distribution network of cross-border e-commerce cannot solve the problem of high operation cost, the optimization model for the logistics distribution network of cross-border e-commerce based on a personalized recommendation algorithm is designed. Through the analysis of the logistics distribution network of cross-border e-commerce structure and the construction of logistics distribution network of cross-border e-commerce model and multiobjective optimization of logistics distribution network of cross-border e-commerce, the construction process of the logistics distribution network optimization model is completed. The simulation results verify the effectiveness of the model. By comparison, this model can effectively solve the problems that the original model cannot solve and reduce the operation cost of the logistics distribution network.

Research on the Bi-Level Optimization Model of Distribution Network Based on Distributed Cooperative Control

The uncertainty of high-permeability renewable energy output brings about great challenges to the operation control in distribution network. The traditional control mode has lower reliability, higher calculation and greater communication pressure. It is more difficult to realize the technical requirements of “plug and play” of power components. Therefore, a bi-level coordinated control model is proposed for the operation and energy management optimization of active distribution network with multi-microgrid in this paper. The consensus algorithm which exists in the multi-agent system is applied in the upper-level model and the capacity utilization ratio of the different microgrids is set as the consistent variable because the ratio of resistance and reactance is usually larger in distribution network and the interests in the different microgrid entities should be distributed fairly. Moreover, in the lower-level model, the lowest operating cost is the final goal and the model predictive control rolling optimization is utilized to reasonably allocate the output of the equipments in the microgrid according to the changing trend of renewable energy. Thereby the tracking of the upper-level control commands is realized. Finally, the simulations are conducted in the IEEE-33 nodes distribution system connected to a multi-microgrid to verify the feasibility and effectiveness of the proposed method, in which a reference for the optimal operation of higher penetration renewable energy to distribution network is provided.

Robust Optimal Operation of Active Distribution Network Based on Minimum Confidence Interval of Distributed Energy Beta Distribution

With the gradual increase of distributed energy penetration, the traditional optimization model of distribution network can no longer guarantee the stable and efficient operation of the distribution network. In order to deal with the inevitable uncertainty of distributed energy, a new robust optimal operation method is proposed for active distribution network (ADN) based on the minimum confidence interval of distributed energy Beta distribution in this paper. First, an ADN model is established with second-order cone to include the energy storage device, capacitor bank, static var compensator, on-load tap changer, wind turbine and photovoltaic. Then, the historical data of related distributed energy are analyzed and described by the probability density function, and the minimum confidence interval is obtained by interval searching. Furthermore, via taking this minimum confidence interval as the uncertain interval, a less conservative two-stage robust optimization model is established and solved for ADN. The simulation results for the IEEE 33-bus distribution network have verified that the proposed method can realize a more stable and efficient operation of the distribution network compared with the traditional robust optimization method.

Research and Application of Integrated Energy Coordination Optimization Control in Distribution Network

In recent years, China’s new energy industry has developed rapidly, and photovoltaic and wind power installed capacity has ranked first in the world. However, at the same time of rapid development of new energy sources, the problem of consumption has become increasingly prominent, and the phenomenon of abandoning wind and abandoning light is serious. This paper will start from the power generation principle of distributed power supply and the charge and discharge mechanism of energy storage. Through the analysis of the characteristics of distributed power supply, the new energy consumption is the most, the thermal power input is the minimum, and the distributed power supply is established. The cooperative optimization model of distribution network is constructed, and the coordinated optimization control model based on distribution network automation technology is constructed, and the experimental simulation is carried out to obtain the optimal coordinated energy optimization control model for distribution network to realize the safety, high efficiency and high degree of regional distribution network.

Multi objective reactive power and voltage optimization of distribution network based on adaptive genetic annealing algorithm

In this paper, a multi-objective reactive power optimization model of distribution network is established, which takes the minimum of line loss, reactive compensation capacitor switching loss and node voltage deviation as objective, considering the constraints of node voltage, reactive power of wind turbine, capacitor switching times. The improved adaptive genetic annealing algorithm is used to solve the model. IEEE33 system is taken as an example to verify the effectiveness of the reactive power optimization model. When the shunt capacitor and wind turbine are in the optimal reactive power compensation, the line loss of the distribution network can be minimized.

Optimization Strategy for Improving Power Supply Capacity in Distribution Networks with Electric Vehicle Integration

In order to alleviate the heavy air pollution problem in China in recent years, power energy alternative loads, such as electric vehicles, are widely integrated into distribution networks, which has a significant impact on power supply capability of distribution networks. In this paper, considering the randomness of electric vehicles, probabilistic multiple scenarios generation method is proposed based on Latin hypercube sampling method, Cholesky decomposition and synchronous back-off reduction, realizing the quick scenario generation with the balance of scenario number and precision. Based on probabilistic multi-scene, taking the power supply ability of distribution network as the main objective, a robust operation optimization model of distribution network containing electric vehicles is established in order to optimize the opening and closing status of the switches. Ant colony algorithm based on the Pareto optimal is adopted to solve the model. A modified IEEE 33 node system is used to verify the effectiveness of the model and algorithm, and simulation results show that the proposed method can effectively promote the power supply ability of distribution networks, and can greatly improve the computational efficiency of the model in the case that lots of uncertain parameters exist due to large-scale integration of electric vehicles.

配电网中分布式源-荷协同运行多目标优化的机会约束二阶锥规划模型

在双馈风电机组和光伏发电站等多种类型的分布式电源以及电动汽车接入配电网系统的情况下，考虑配电网电源出力和负荷的随机性，建立了含不确定性DG与EV的配电网优化模型。该模型以高置信水平的最小经济运行成本和最小有功网络损耗为目标，同时加入节点电压期望值最大偏差为惩罚函数，用全牛顿步不可行内点法进行求解。对IEEE33节点系统进行仿真计算并对比其他规划及锥规划的其他算法，证明了本文所提出的优化模型计算法的有效性。 In the case of distributed power supply (DG) and electric vehicle (EV) connected to distribution network system such as double-fed wind turbine and photovoltaic power station, considering the randomness of power distribution and load of distribution network, the optimization model of distribution network with DG and EV is established. In the model, the minimum economic operating cost and the minimum active network loss are taken as goals, and the maximum deviation of the expected value of the node voltage is added as the penalty function. Full Newton step infeasible interior point algorithm is used to solve the model. The simulation of the IEEE 33-node system is carried out and compared with other algorithms of other programming, which proves the validity of the optimization model proposed in this paper.