Multi-objective coordinated optimization of flexible interconnected distribution networks under rainstorm conditions

The scaled access of electric vehicles (EVs) exacerbates load fluctuations in distribution networks, which is not conducive to the stable and economic operation of the distribution networks. At present, user satisfaction degree is generally low. To avoid this problem, this paper proposed a two-layer cooperative optimization of flexible interconnected distribution networks considering EV user satisfaction degree. First, the EV user satisfaction degree model is established by considering EV users’ charging waiting time, charging power, and other indicators. At the same time, an EV charging mode switching model is constructed based on the number of EVs entering the network and their battery charge state. On this basis, the Monte Carlo algorithm is used to generate the results of the daily distribution of EV loads taking into account the user satisfaction degree, so as to improve the load ratio of the transformer in the distribution network. Further, a two-layer cooperative optimization of flexible interconnected distribution networks considering electric vehicle user satisfaction degree is developed with the daily operating cost of each network as the optimization objective. Finally, a flexible interconnected power distribution network consisting of three power distribution networks is used as an example for validation. The results show that this method is effective in improving EV user satisfaction degree and reducing the peak-to-valley ratio of the system load while taking into account the safe and economic operation of the distribution network, which greatly improves the reliability and economy of the operation of the flexible interconnected power distribution network.

The new power system effectively integrates a large number of distributed renewable energy sources, such as solar photovoltaic, wind energy, small hydropower, and biomass energy. This significantly reduces the reliance on fossil fuels and enhances the sustainability and environmental friendliness of energy supply. Compared to distribution networks in traditional power systems, the new-generation distribution network offers notable advantages in improving energy efficiency, reliability, environmental protection, and system flexibility, but it also faces a series of new challenges. These challenges include potential harmonic issues introduced by the widespread use of power electronic devices (such as inverters for renewable energy generation systems and electric vehicle charging stations) and the voltage fluctuations and flickering caused by the intermittency and uncertainty of renewable energy generation, which may affect the normal operation of electrical equipment. To address these challenges, this study proposes an optimization model aimed at minimizing network losses and voltage deviations, utilizing traditional capacitor adjustments and static var compensators (SVCs) as optimization measures. Furthermore, this study introduces an improved version of the multi-objective particle swarm optimization (MOPSO) algorithm, specifically enhanced to address the unique challenges of reactive power optimization in modern distribution networks. The test results show that this algorithm can effectively generate a large number of Pareto optimal solutions. The application of this algorithm on a 33-node network case study demonstrates its advantages in reactive power optimization. The optimization results highlight the effectiveness and feasibility of the proposed improved algorithm in the application of distribution network reactive power optimization, offering users a uniform and diverse range of reactive compensation solutions.

In order to improve the timeliness of logistics distribution, based on the theory of road network smoothness and reliability, the author conducted a study on the optimization of urban logistics distribution and transportation networks based on smoothness and reliability. The concept of logistics distribution and transportation network smoothness and reliability was proposed, and a logistics distribution and transportation network optimization model was established. The solving process of ant colony algorithm was given, and finally, a comparative analysis of a case was conducted. The results showed that: With a 6% increase in total delivery distance, the reliability of the delivery network has increased by 30%. This indicates that when using the model built by the author for distribution network optimization, effective optimization of network smoothness and reliability can be achieved, while only increasing the distance by a small amount. The optimal reliability of a smooth distribution network means that the probability of delivery delays is minimized, which is the most powerful guarantee for the effective accessibility of delivery. Verified the practicality of the constructed model. The proposed logistics distribution network optimization model has practical significance in guiding decision-making for optimizing urban logistics distribution transportation networks and reducing uncertainty in the process of urban logistics distribution.

A fuzzy evaluation based multi-objective optimization model for reactive power optimization in power distribution networks is presented in this paper. The two objectives, reducing active power losses and improving voltage profiles, are evaluated by membership functions respectively, so that the objectives can be compared in a single scale. To facilitate the solving process, a compromised objective is formed by the weighted sum approach. The weights are decided according to the preferences and importance of the objectives. The reactive tabu search algorithm is employed to get global optimization solutions. Simulation results of a practical power distribution network, greatly improved voltage profiles and reduced power losses, demonstrated that the proposed method is effective.

In order to solve the problem of insufficient system operation flexibility caused by the strong uncertainty of renewable energy source and load, taking into account the power-energy timing adjustment characteristics of multi-terminal back-to-back VSC-HVDC and energy storage, an intraday rolling optimization program for flexible interconnected distribution network based on adaptive dynamic update strategy are proposed. First, in order to fully mobilize the flexible adjustment capabilities of energy storage, an energy storage flexibility margin evaluation index has been established. Secondly, energy storage charge and discharge power and state of charge constraints are treated as chance constraints, and adaptively updated in real time to automatically tighten or relax constraints according to the actual deviation probability between the violation level and the desired level during the rolling optimization stage. Then, the goal planning and second-order cone programming are used to process and solve the model to improve the efficiency of the solution. Finally, the results of calculation examples show that the proposed model and algorithm can effectively improve the utilization rate of energy storage, thereby ensuring the safe, flexible and economic operation of the system.

Yang, J. and Guo, L., 2020. Optimization of marine port logistics collection and distribution network: A perspective of supply chain management. In: Gong, D.; Zhang, M., and Liu, R. (eds.), Advances in Coastal Research: Engineering, Industry, Economy, and Sustainable Development. Journal of Coastal Research, Special Issue No. 106, pp. 473–476. Coconut Creek (Florida), ISSN 0749-0208.With the prosperity of financial trade, marine port logistics have become an important part of international logistics, which needs to improve port efficiency by optimizing the collection and distribution network. A collection and distribution network is a kind of system that integrates multiple transportation modes, including railway, highway, waterway, air transport, pipeline, etc. Zhoushan Port in Ningbo is the largest port in China. With the gradual increase in the importance of marine port logistics, the original collection and distribution network has been unable to meet the rapid growth of port cargo throughput. Therefore, the marine port's collection and distribution network system needs to be optimized based on the supply chain. This paper presents an analysis of the optimization of Zhoushan Port's collection and distribution network based on the supply chain. First, this paper forecasts the cargo throughput and container throughput of Zhoushan Port using the Grey method. Then, this paper predicts the capacity of different transportation networks. Finally, some suggestions are put forward.

High proportions of renewable energy place higher requirements on the flexibility of the distribution network. Meanwhile, the communication network is striving to seek ways to save energy. In this regard, this paper proposes a novel collaborative optimization method with interactive balance of flexibility and power for distribution network operator (DNO) and mobile network operator (MNO). First, the flexibility balance mechanism is analyzed and the optimization model integrating flexibility balance and power balance is established for the distribution network. Secondly, a flexibility aggregation method of large-scale base stations with energy storage (ES) devices is proposed, and a virtual ES-based optimization model is built for the mobile network. Then, a Nash bargaining-based optimization method is proposed for the collaboration of DNO and MNO, and a decentralized solution algorithm is designed to obtain the Nash bargaining solution, preserving the personal privacy. Finally, through a comprehensive case study we can draw that, compared with the independent approach, the proposed collaborative optimization method with interactive balance of flexibility and power can improve the operating flexibility of the distribution network while reducing the electricity bills of the mobile network effectively, thus achieving a win-win result.

Development of low-carbon economy and low-carbon logistics is an important part of China's logistics in the long-term development plan. On the basis of the city logistics distribution which is an important part of the logistics system, this paper studies the optimization of distribution network in the city from the perspective of low carbon economy and researches on the two-echelon location-routing problem which considering the external cost of carbon emissions. On the basis of the fixed cost and transportation cost, the optimization model is constructed which is solved by using Lingo software. The objective of the model is to plan the path and minimize the carbon emissions and costs. The analysis of the optimization of BBG multi-level distribution network verifies the effectiveness of the optimization model. Based on the low carbon perspective, this paper puts forward the optimization model of urban multi-level logistics distribution network to improve the efficiency of logistics distribution and reduce carbon emissions. So this paper has a good theoretical value and practical significance.

We studied the reactive power control strategy of distributed energy storage in distribution systems, improved reactive power support capacity, and enhanced system reliability and new energy carrying capacity. Firstly, the principles and methods of reactive power optimization in distribution networks are studied. Then, the principles and mechanisms of distributed energy storage participating in reactive power control in distribution networks are studied. Finally, the genetic algorithm optimization method for reactive power optimization in distribution networks is studied, including parameter setting, target selection, and genetic strategy improvement, providing support for fine control of reactive power and voltage in distribution systems and efficient operation. Through simulation analysis of the IEEE33 node system, it is shown that distributed energy storage can improve the reactive voltage level of the distribution system and promote the consumption of new energy.

With the increase of renewable energy in electricity generation and increased engagement from demand sides, distribution network planning and operation face great challenges in the provision of stable, secure and dedicated service under a high level of uncertainty in network behaviors. Distribution network planning and operation, at the same time, also benefit from the changes of current and future distribution networks in terms of the availability of increased resources, diversity, smartness, controllability and flexibility of the distribution networks. This paper reviews the critical optimization problems faced by distribution planning and operation, including how to cope with these changes, how to integrate an optimization process in a problem-solving framework to efficiently search for optimal strategy and how to optimize sources and flexibilities properly in order to achieve cost-effective operation and provide quality of services as required, among other factors. This paper also discusses the approaches to reduce the heavy computation load when solving large-scale network optimization problems, for instance by integrating the prior knowledge of network configuration in optimization search space. A number of optimization techniques have been reviewed and discussed in the paper. This paper also discusses the changes, challenges and opportunities in future distribution networks, analyzes the possible problems that will be faced by future network planning and operations and discusses the potential strategies to solve these optimization problems.

The reactive power (VAR) optimization in distribution network is one of important measures for loss reduction, voltage profile improvement and power factor correction. This paper classifies the VAR optimization into VAR configuration optimization and VAR operation optimization based on different implementation phases. Meantime, the VAR optimal operation is sorted by static VAR optimization and dynamic VAR optimization. Afterward the article summarizes the research situation of VAR optimization. Eventually the paper presents the future work of VAR optimization according to the research status.

Software defined networking (SDN) decouples control plane functionality from the data plane and features the presence of programmable dumb network devices, which have no or little intelligence and take control commands from a central controller at the control plane. The central controller is responsible for controlling data plane hardware and optimizing network operation. Centralized network optimization and control is impractical or infeasible when the network becomes too large in size or loading. Distributed network optimization comes into play under this circumstance. Fully distributed network optimization requires local intelligence at individual network elements, against the basic concept of SDN. In this paper we consider SDN-friendly zone-based distributed network optimization and studies the integral network zoning problem, that is, how to group network elements into zones such as to minimize the overhead of distributed network optimization. We give a mathematical formulation of the problem and show that it is NP complete. We then present three heuristic solutions and evaluate their performance through simulation.

With the integration of massive distributed resources into the grid, more and more traditional electricity consumers are becoming prosumers with dual identity of producer and consumer. It is of great significance to study the Peer to Peer (P2P) transaction between the prosumers. In this study, a weakly centralized prosumer P2P transaction model considering optimization of distribution network is established. Firstly, we constructed a prosumer P2P transaction model and used ADMM algorithm to solve it. The impact of optimization of distribution network on the model is then taken into consideration based on which we have the two-layer optimization model for prosumer P2P transaction considering the optimization of distribution network. Finally, the model is solved through iteration to minimize the transaction cost of prosumers and the operation cost of the distribution network, thus realizing the P2P transaction between multiple prosumers under the constraints of the distribution network.

With the increasing number of electric vehicles (EVs), the connection of large-scale electric vehicles will affect the stability of the power system. Based on the analysis of electric vehicles travel characteristics, this paper proposes an optimal scheduling model for vehicle to grid (V2G) with the cost of power system operation as the objective function. Then, simulation calculations are carried out through the IEEE 33-node distribution network by MATLAB. Through the results, the scheduling model for vehicles to grid attaches great significance to reducing system cost, flattening the load curve and reducing the wind power curtailment. It is concluded that the optimization of distribution network is beneficial to improve the reliability of the power grid.

In this article applies the Harris Hawks Optimization Algorithm for optimization of the water distribution network of the Homashahr located in Iran for a period of one month (from 30 September 2018 to 30 October 2019). The utilized time-series data included water demand, reservoir storage. In this article, a model based on the Harris Hawks Optimization Algorithm (HHO) was developed for the optimization of the water distribution network. The analysis showed that the best solutions achieved by the Harris Hawks Optimization Algorithm (HHO) were 35,508 $. The results revealed that the HHO algorithm was well in the optimal design of water supply networks problem. At the end, about 12% of the optimization was done by this algorithm.•In this article applied the Harris Hawks Optimization Algorithm for optimization of the water distribution network of the Homashahr located in Iran.•The method presented in this article can be useful for managers of water and wastewater companies, water resource facilities and water distribution system managing director for optimal network design to reduce costs.•The present algorithm performs better than the other algorithms in the discussion of the optimization of water distribution networks.