Coordinated optimization of source–storage–load in distribution network based on edge computation

Background: Due to the influence of illumination resources, the output of photovoltaic power generation exhibits intermittency, randomness, and volatility. The large-scale integration of photovoltaic power into the distribution network can cause fluctuations in bus voltage and line flow and, in severe cases, may lead to system voltage and flow limits being exceeded, increasing the risk of system operation. Methods: In response to this, this study proposes an active distribution network flow optimization method based on energy storage regulation. This method takes the total system operation cost, which includes elements such as the cost of photovoltaic power generation, network loss cost, energy storage regulation cost, and curtailment cost, as the optimization objective. It uses the bus voltage, line flow, and transformer load of the active distribution network as the constraint for accommodating space. Additionally, it considers the charging and discharging regulation capacity and sensitivity index of distributed energy storage. Based on this, a flow optimization model for the active distribution network is established, which is driven by the joint cost and sensitivity of the minimum total adjustment amount and the minimum number of control nodes. The model is solved using the path-tracking method. Results: In this paper, the improved IEEE39-bus system is used as an example for analysis, verifying the correctness and effectiveness of the proposed method. Conclusion: Research shows that this method can fully consider the technical and cost factors of high-proportion distributed photovoltaic grid integration. By optimizing the power flow of the distribution network through coordinated control of distributed energy storage, the proposed method achieves the minimum control adjustment amount while minimizing the number of nodes involved in the adjustment. This ensures the safe, reliable, and economical operation of the system.

Aiming at the problems of power flow fluctuation and voltage exceeding standard caused by high permeability distributed power supply access, this paper proposes a load state perception early warning method for distribution networks. Firstly, the random behavior characteristics and voltage early warning mechanisms of power supply and load in distribution networks are analyzed, the dynamic model of distribution networks based on complex network theory is established, and the risk index of voltage exceeding limits under the conditions of high permeability distributed power supply access is put forward. Secondly, the random power flow of distribution networks based on the Monte Carlo method is studied by sampling and analyzing the dynamic model of distribution networks. Then, the risk calculation and safety assessment of voltage exceeding limits are carried out on the currently extracted model, and the risk control strategy of distribution network operation is put forward. Finally, an improved IEEE30-node distribution network topology is proposed. Through simulation analysis, it is proven that the load situation awareness early warning method of distribution networks can effectively predict, improve the security of distribution networks, and provide timely early warning information for maintenance personnel.

The emerging distribution networks are equipped with renewable generation resources, controllable loads and corresponding monitoring and control assets to actively regulate the aggregated demand in the bulk power system. The volume of the energy received from the bulk power system as well as the price of electricity contributes to the operation cost of the distribution network. Distribution system operators balance the demand and supply and compensate for the intermittency and variability of the local renewable generation resources and noncontrollable loads using the controllable generation and demand assets. Data centers are large flexible electrical loads in distribution networks that could help the distribution system operators to manage the operation cost and to mitigate the imbalance between the demand and generation. The introduced uncertainties in the operation horizon provide economic risks in the distribution network operation. Hence, providing efficient measures for risk associated with the uncertainties provides an insight for the decision makers to avoid over conservative operation decisions. The proposed risk averse operation planning framework constrains the volatility of the expected cost through the conditional value at risk (CVaR) assessment.

As large-scale lithium-ion battery energy storage power facilities are built, the issues of safety operations become more complex. The existing difficulties revolve around effective battery health evaluation, cell-to-cell variation evaluation, circulation, and resonance suppression, and more. Based on this, this paper first reviews battery health evaluation methods based on various methods and summarizes the selection of existing health factors in data-driven methods. Secondly, the paper discusses the new research hotspots in the existing battery state evaluation technologies from the perspectives of state evaluation using data fragments and edge computing. Thirdly, we focus and discuss on the safety operation technologies of energy storage stations, including the issues of inconsistency, balancing, circulation, and resonance. To address these issues, we present an intelligent inspection robot, enabling real-time data interaction with the EMS and fulfilling rapid inspection and real-time diagnosis. Above all, we focus on the safety operation challenges for energy storage power stations and give our views and validate them with practical engineering applications, building the foundation of the next-generation techniques that support the development of new power systems.

The postdisaster restoration capabilities for critical loads in distribution networks need to be enhanced. In recent years, electric buses (EBs) have been widely used with the carbon-neutral target, which can be dispatched and discharged for load restoration considering their mobility and the V2G technology. However, the restoration capabilities of EBs are limited by the transportation system while the ac distribution network can hardly achieve power transfer between lines due to the radial constraint. In this article, a coordinated restoration method of hybrid ac–dc distribution network with EBs is proposed, which has flexible power transfer capability. The control modes of voltage source converters (VSCs) during the postdisaster period as well as the EB restoration capability considering transportation system constraints are analyzed in detail. Then, a bilevel programming model is developed to optimize the network reconfiguration, VSC outputs, and the proposed EBs dispatching scheme simultaneously, in order to achieve a better power transfer capability for load restoration considering their coordination. Simulation studies are performed to verify the proposed method.

Summary form only given. This paper presents a probabilistic approach for statistical modelling of the loads in distribution networks. In a distribution network, the Probability Density Functions (pdfs) of loads at different buses show a number of variations and cannot be represented by any specific distribution. The approach presented in this paper represents all the load pdfs through Gaussian Mixture Model (GMM). The Expectation Maximization (EM) algorithm is used to obtain the parameters of the mixture components. The performance of the method is demonstrated on a 95-bus generic distribution network model.

This paper presents a probabilistic approach for statistical modeling of the loads in distribution networks. In a distribution network, the probability density functions (pdfs) of loads at different buses show a number of variations and cannot be represented by any specific distribution. The approach presented in this paper represents all the load pdfs through Gaussian mixture model (GMM). The expectation maximization (EM) algorithm is used to obtain the parameters of the mixture components. The performance of the method is demonstrated on a 95-bus generic distribution network model.

This study examines the effect of wind power availability on the distribution system load behaviors using the K-means clustering algorithm to process the load data following the integration of wind power. First, this article presents the concept of the K-means clustering algorithm and then carries out the preprocessing of the data and the analysis of the clusters using real distribution network load data. The findings of the research are that the volatility of the distribution network load curve increases sharply with the ratio of wind power access, and the voltage quality and the system stability are also affected to some extent. This research verified the feasibility of the K-means clustering algorithm to categorize the load data and to derive characteristics, explored the characteristics of the load under various wind power access modes, and disclosed the relationship between the wind power access and the characteristics of the distribution network load. The conclusions obtained through this research not only promote the theory regarding how the connection of wind power has an effect upon distribution networks but also offer date support and decision making aid to the optimization of the operations of the grid and dispatch in real-world projects, and indicate the way to improve the adaptability and stability of the distribution networks through new concepts and technical means.

To ensure the safe and stable operation of the power system in the power market environment, a transaction model of power reserve ancillary services oriented to interruptible loads is constructed. By analyzing the benefits of interruptible users and power grid enterprises, a transaction model of interruptible load is established based on it. After obtaining the value of the minimum cost of power system to purchase interruptible load, the capacity cost, opportunity cost and standby use cost of power reserve are calculated respectively. The objective function of auxiliary power reserve service transaction model with interruptible load is established and the constraint conditions are set, and then the transaction result of auxiliary power reserve service is obtained by solving the objective function of the model. The experimental results show that the model can effectively calculate the power interruption compensation price of user interruptible load, and obtain the interruptible load transaction results according to the rapid capacity quotation, power quotation, etc. At the same time, the model has the lowest cost of reserve capacity and reserve use cost in a certain period of time, and the application effect is good.

High distributed generations (DGs) penetration connected into the distribution network leads to the fluctuation and uncertainty in distribution network. In order to improve the capability of uncertainty treatment of distribution network, the flexibility enhancement of distribution network with high DG penetration is studied. Firstly, the flexibility demand of distribution network with high DG penetration is explored. Then, five distribution network flexibility evaluation indexes are proposed, which include line capacity margin, transformer capacity margin upward, transformer capacity margin downward, net load fluctuation rate and maximum allowable net load fluctuation rate, what represents the flexibility adequacy of distribution network capacity and the flexibility adaption of the embedded distributed generations, respectively. A multi-objective optimal scheduling model is established to improve the flexibility considering interruptible loads and energy storage. Simulation results show that the flexibility of the distribution network with high DGs proportion can be improved by optimizing the scheduling of the flexible resources, and the hosting capability of distribution network for DG accommodation can be increased.

Summary Because of the widespread application of new energy and power electronic–based residential loads in distribution networks, the impact of collective harmonics cannot be ignored. The harmonic impedance should be evaluated when determining the harmonic responsibilities at the point of common coupling. This paper presents a new noninvasive method to quantify the harmonic current responsibilities of the utility side and customer side on the basis of impedance-gathering trend. The method is compared with another noninvasive resistance-sign–based method. In addition, the emission level of the residential loads is calculated. The presented results of a field test conducted in a typical residential apartment in Shanghai, China, prove that the method works well in practical conditions.

Modern power system can identify component faults, isolate faults and resume operation quickly. In view of the problem that the distribution of line load in distribution network is not reasonable and it is easy to fall into the self-organized critical state, this paper introduces power flow entropy as an evaluation index to measure the robustness of power network reconstruction. Based on the power supply capability and node load level of distributed power supply in the process of network reconstruction, a strategy of island division is proposed. Then, a mathematical model is set up to minimize power flow entropy, network loss and node voltage drop, and the problem of network reconstruction after fault is solved by the improved chaos theory and binary particle swarm optimization algorithm. Finally, an example of IEEE-33 node distribution system is given to verify the feasibility of the proposed strategy and the effectiveness of the algorithm.

In response to the difficulty in finding the characteristics of the changes in the state of power storage in the distribution network, which leads to the difficulty in allocating electricity load output, a collaborative control of power storage in the distribution network considering new energy consumption capacity is proposed to effectively solve the problem. This paper establish an objective function that considers the network loss and voltage deviation of distribution network nodes, divide the power sequence to calculate the state changes of each node during energy access and load output. Use the average method to obtain the fusion objective function of new energy loss and energy storage loss for the distribution network throughout the day. Analyze the synergistic characteristics between energy storage and load during each power change through the function. Based on the balanced distribution relationship between active and reactive power in the distribution network, a weighted directed graph of the distribution network is established. The consistency algorithm is used to calculate the random changes in power and other indicators during each energy distribution, and a random matrix is designed to converge the stored power of the distribution network to the standard interval. At this time, the power change and state shift are solved again to obtain the source storage load droop coefficient, By adjusting the droop coefficient according to the active power command, one or more allocations are achieved until the collaborative goal is achieved.

Methods for solving the problem of selecting optimal switch-off locations in electrical distribution networks and implementing its results are considered. It is shown that in modern electrical distribution systems, in the context of the widespread use of dispersed sources of energy generation and its storage, the traditional approach to solving this problem loses its effectiveness. As an alternative can be the use of remote-controlled switching devices, what is reasonable in the case of cyclic and rather prolonged changes in the load as well as output power of dispersed energy sources, when energy storage devices are turned on or off. New technological solutions are proposed that make it possible to effectively reduce electric energy losses in distribution networks with local sources of energy generation and storage due to the possibility of dynamic management of the network configuration. The expediency of implementing a strategy for rational use of remote-controlled switching devices are substantiated, taking into account their switching resource, and an algorithm for their operation is developed. It is shown that now the universal solution is the use of power electronics devices, which makes it possible to form the so-called “soft points” of opening the distribution network circuits when controlling active and reactive power flows to ensure a minimum of electrical energy losses due to rapid response to changes in electrical load and/or modes of energy generation and storage in the presence of dispersed sources of electricity generation and storage facilities. For the introduction of new technical means on the way to implementing even individual components of the concept of “Smart Grid”, an appropriate methodology for economic justification of such decisions has been developed, which allows one to objectively take into account the positive consequences of their implementation, at least from the point of view of improving the reliability and efficiency of power supply, reducing voltage deviations, etc.

The main challenge of present distribution networks is the huge increase in demand for electricity especially in city center where the demand is increasing vertically for the same geographical area. This work presents the analyses of 5-Mail distribution network in Basra City/Iraq with conventional system 33/11/0.416 kV, at future load by estimating the increase in load 10 years later. The network is analyzed in terms of voltage drop, power losses, and the feeder loading. To improve the network the 33/11/0.416 kV system is re-analyzed at the expected future load using the optimal reconfiguration of the network or adding capacitor placement to reduce losses and voltage drop. The results of these methods are compared with the results of the network re-analyzed using the proposed 33/0.416 kV system at future load. The results show that the proposed method of upgrading the voltage level of distribution network is the best solution. The GIS software is used to locate the distribution transformers and lying of the underground cables. CYME software is used to simulate the electric distribution system and conduct the load flow and other analyses.The GIS software is used to locate the distribution transformers and lying of the underground cables. CYME software is used to simulate the electric distribution system and conduct the load flow and other analyses.