A Virtual Micro-Islanding-Based Control Paradigm for Renewable Microgrids

Abstract

Improvements in control of renewable energy-based microgrids are a growing area of interest. A hierarchical control structure is popularly implemented to regulate key parameters such as power sharing between generation sources, system frequency and node voltages. A distributed control infrastructure is realized by means of a communication network that spans the micro-distribution grid. Measured and estimated values, as well as corrective signals are transmitted across this network to effect required system regulation. However, intermittent latencies and failures of component communication links may result in power imbalances between generation sources, deviations in node voltages and system frequency. This paper proposes a hierarchical control structure to regulate the operation of an islanded AC microgrid experiencing communication link failures. The proposed strategy aims to virtually sub-divide the microgrid into controllable "islands". Thereafter, active power sharing, frequency and voltage restoration is achieved by competing converter systems through multi-agent consensus. The effectiveness of the proposed methodology has been verified through stability analyses using system wide mathematical small signal models and case study simulations in MATLAB, Simpower systems.

A Hierarchical Control Methodology for Renewable DC Microgrids Supporting a Variable Communication Network Health

“…In this scenario, operating reference points for the disconnected communication nodes and other nodes will be different. This will stress the connected nodes [5,30,31]. To overcome this problem, a non-uniform convergence algorithm has been proposed for the secondary control level, which maintains the look-up table of the DC microgrid communication network at every node.…”

“…Every node checks for a priority signal to re-evaluate the look-up table of connectivity and generates a new connected graph table using that information. It detects a link failure in time to take corrective measures, by searching through the look-up table [30][31][32][33].…”

“…After detecting islanding, all the nodes work on a modified current sharing control to match the reference point with the disconnected node reference to increase system stability. In order to detect the connected nodes and update the look-up table, a graph theory searching algorithm is used, such as depth-first search (DFS) [31,34,35].…”

“…A graph can have many adjacency structures because every edge around the vertex creates a direct adjacency structure and every structure leads to a unique arrangement of edges at each vertex. The depth-first search method (DFS) described in Algorithm 1 [31,32] works more efficiently using the adjacency structure. The output from this algorithm consists of edges (E).…”

“…The main drawback in constant reference is that every node has a constant reference which may be different. This constant reference approach is also limited to ring-connected control [30,31]. However, for higher communication reliability, more complex communication networks are normally used in practical systems.…”