optimal positioning of storage systems in microgrids based on complex networks centrality measures - ess energy storage system

This paper proposes an optimal location judgment criterion for energy storage system based on central metric of complex network in power network.
To this end, we study the relationship between grid central indicators and voltage fluctuations in the case of high penetration of renewable energy and storage systems.
For the purpose of testing, we consider two typical IEEE networks and calculate the Node centrality (
That is, the feature vector, the degree of proximity, page rank, and the number of intermediaries)
As well as voltage fluctuations in the presence of intermittent renewable energy generators and intermittent loads measured by domestic users.
We show that the topology features of the power grid can identify the optimal position of the active and reactive power compensator (
(Such as energy storage system)
Used to reduce voltage fluctuations according to general service quality standards.
The results show that among the different indicators, the center of the feature vector has a significant exponential correlation with the reduction of voltage fluctuation.
This discovery confirms the technical knowledge.
How to heuristic locate which storage systems are located away from the supply response node.
This is also an advantage in computing time and planning wide elastic networks that require careful positioning of storage systems, especially in an interconnected scheme, microgrids intermittent distributed energy (
Such as wind energy or solar energy)
Fully deployed.
In recent years, energy production is shifting to cleaner and sustainable renewable energy sources (RES).
In emerging technologies, wind and photovoltaic (PV)
From a technical and policy implementation perspective, generators are considered the most promising energy source in the future.
In fact, RES offers a clear advantage in pollution emissions, energy supply, and ease of deployment of energy production facilities.
In addition to these advantages, such energy sources have significant defects in the uncertainty and intermittent aspects of power production, which poses a challenge to the traditional one-way power grid concept based on large fossil energy sources.
Fuel power plants.
In addition, this uncertainty may make the power quality management worse, causing instability in the power system in terms of frequency and voltage control.
In addition, the more uncertainty, the more instability is observed, which makes the increasing penetration of RES a major source of service quality (QoS)disturbances.
To overcome these problems, two complementary approaches are proposed: active control of load and power flow and passive enhancement of grid elasticity.
Through the first method, the power grid is undergoing great technological progress, so that it can be managed and controlled intelligently and in real time.
The increasing implementation of load control functions in smart meters, the possibility of monitoring system operating parameters almost in real time through SCADA systems, and the wide adoption of energy storage systems (ESS)
Implement fine-grained control over these systems.
In particular, ESS is considered critical to the full adoption of RES, as they are able to limit network imbalances due to RES fluctuations by storing the residual energy generated for future use.
In addition, from an economic point of view, ESS is important because they ensure an increase in system stability, even considering the degradation caused by calendar and cycle aging and the limitations of installation costs, depending on the type of use, this may hinder the service life of ESS, thus reducing the return on investment.
On the other hand, more and more attention has been paid to defining grid planning features for enhanced passive elasticity, especially in the past few years, the complex network approach has proven to be a solid framework for capturing and describing complex phenomena in the grid.
For example, complex networks have shown how the topology of the grid strongly affects the network's robustness to attacks and failures, grid sync and its overall voltage regulation, and coordination with the energy needs of electric vehicles.
This in turn also shows how the correct planning of the grid topology can improve the overall elasticity of the network, thus reducing the implementation and maintenance cost of the active control system.
According to the literature, a heuristic method for finding the best position of ESS in the voltage regulation network has been proposed, but this method is limited by the size and topology of the network, resulting in the results of specific case studies, although it still requires a standard that can cope with complex and wide topologies with a lower computational workload and higher accuracy.
In this sense, use more
The disciplinary approach to connecting complex network science and electrical engineering seems promising.
Here we propose a general approach that can demonstrate how the centrality of power network nodes is used as a criterion for the best location of ESS.
We have calculated the effect of ESS on the network through the recent method based on genetic algorithm and optimal power flow, and further improved the steps of reactive power optimization.
The results show that there is a statistically significant correlation between node feature vector centrality and the best position of ESS, which has a positive impact on their voltage regulation capability, and the overall reduction value of voltage fluctuation is as high as 50%, the power quality has been significantly improved.