Análisis prueba cuatro (final)

In Figure 4.17, three new deployments, i.e. CB8, DG6 and Load 4 are added to Figure 4.15. The following three commands are realized for this change:

Relay8.Connect(Relay6) Load4.Connect(Relay8) DG6.Connect(Relay8)

Consequently, a new relay, i.e. Relay 8, is connected to Relay 6 while a new load, load 4, and a new generator, DG6, are connected to Relay 8.

Figure 4.17. Dijkstra‟s Algorithm run after new deployments, Path from CB2 to DG6

Dijkstra‟s algorithm is run on the graph and the new deployments are successfully identified

in grid hierarchy. It is shown that with this simple arrangement, the path from the known origin to known destinations can be found for any possible network structure. It is sufficient to track the connection of nodes with the preceding and following nodes. Thanks to this feature, a centralized monitoring approach is not required and de-centralized automated

method is made possible. The shortest paths and the distances updated after new deployments have been given in Table 4.6.

The OO modeling and Automated Structure Detection can easily be implemented inside the MCPU which is explained in Chapter 3. The microgrid control center is already in communication with all grid components. Their parameters and services required for OO modeling are reported to MCPU via communication lines. In this way, every new deployment can report its parameters to MCPU. After receiving these details, MCPU can create an object to represent this new device in terms of its parameters and services. The central protection unit and the communication lines proposed in Chapter 3 are sufficient for the implementation of OO modeling for microgrids.

TABLE 4.6. THE PATH FROM “CIRCUIT BREAKER 2”AFTER NEW DEPLOYMENTS Case 1

Node Dist Path

CB3 1 CB2-CB3 CB4 1 CB2-CB4 *DG1 2 CB2-CB3-DG1 *DG2 2 CB2-CB3-DG2 *Load1 2 CB2-CB3-Load1 CB5 - - CB6 2 CB2-CB4-CB6 CB7 2 CB2-CB4-CB7 CB8 3 CB2-CB4-CB6-CB8 *DG3 3 CB2-CB4-CB6-DG3 *Load2 3 CB2-CB4-CB6-Load2 *DG4 3 CB2-CB4-CB7-DG4 *DG5 3 CB2-CB4-CB7-DG5 *Load3 3 CB2-CB4-CB7-Load3 *Load4 4 CB2-CB4-CB6-CB8-Load4 *DG6 4 CB2-CB4-CB6-CB8-DG6

* denotes the leaf nodes

Once all of the microgrid components and their connections are represented with OO models, as explained above, MCPU runs Dijkstra‟s algorithm over this graph and extracts the

microgrids, this is feature is very important since it can extract new structures without any prior knowledge.

4.6. Conclusion

A microgrid modeling scheme based on OO methods has been developed due to the fact that recent developments in the electrical networks and microgrids necessitate a modeling system which will help manage the electrical network in a fast and dynamic manner. This OO modeling is aimed at representing microgrids in the virtual world for dynamic monitoring and control. The former management and protection methods used in utility grid (passive grid) systems are no longer valid for rapidly changing microgrids which can receive multiple connections simultaneously.

This type of modeling is based on the electrical nodes and the connections between the nodes being extracted from the pointers pointing to/from the nodes. In this manner, the changing structure is followed by the model and the new operating points can be calculated, then updated. The ability to follow dynamic nature of microgrid is a crucial asset provided by OO modeling of the network and Automated Structure Detection. Consequently, the modeling of electrical networks with the OO models presented in this chapter will make microgrid management easier from power flow, generation, load sharing and/or protection aspects.

Microgrids have dynamic structures which change more often than the conventional large networks. Supplying power through alternative paths, new deployments and other factors hinder the selective operation in case of a fault. This requires that a new method should be implemented which updates the selective operation of relays in parallel with the existing microgrid structure. However, in order to achieve this goal a robust method is required to extract the relay hierarchy for a specific microgrid structure and assign suitable selective levels

(or time delays). Some of the previous publications incorporate look-up tables with predetermined network structure data. This approach cannot respond to the dynamic changing structure of the network.

Therefore, a new method for determining relay hierarchy and appointing selective levels has been presented in this chapter. The method models the microgrid according to graph theory where relays are represented as nodes and connections are represented as edges. In order to find the path from the point of common coupling to the relays at lowest level, Dijkstra‟s algorithm is used. This algorithm extracts the relay hierarchy for any network structure. The run time is short since the hierarchy for all relays is extracted with a single execution. The algorithm allows for new deployments and automatically includes them in the calculations. This feature is very crucial for plug and play purposes in electrical networks. It also makes the protection system developed in this research to be generic and implementable on a diverse set of power networks.

Chapter 5

Fault Current and Time Delay Assignment for Relays

Publications pertaining to this chapter:

1) Taha Selim Ustun, Cagil Ozansoy, Aladin Zayegh, "Fault Current Coefficient and Time Delay

Assignment for Microgrid Protection System with Central Protection Unit," IEEE Transactions on Power Systems, vol. PP, pp. 1-1, 2012 (accepted-early access).

5.1. Introduction

Chapter 4 focuses on the automatic adaptation of the microgrid to changing conditions such as new deployments or equipment connections. As mentioned therein, this chapter reveals the details of the concept developed for the calculation and setting of protection device parameters. Chapter 4 proposed a unique approach for the detection of a microgrid structure. Once the microgrid structure is appropriately detected, then two key settings can be accurately determined and set for the protection devices participating in the protection of the microgrid. These are crucial for safe and reliable operation and are the relay triggering current and time delay for selectivity. These parameters have been introduced in Chapters 3 and 4; and their relevance has been touched upon. The calculation approach which can be implemented in a central real time automation and protection controller such as the MCPU is presented in the following sections.

In the case of a fault, DG systems contribute to the fault currents and the transient characteristics of the network become completely different [3]. Since the Inverter Interfaced DGs (IIDGs) have highly variable characteristics, they alter the grid structure and jeopardize safe and reliable operation of the microgrid [4] . How to calculate the new fault currents and fault levels for any change occurring in the system is a major concern. Current systems use some sort of database or event tables to search the current status and take pre-determined precautions [73, 90]. These systems necessitate the knowledge of microgrid conditions beforehand so that certain precautions can be assigned in the event tables. However, since microgrids are designed to accommodate new generators and loads, these schemes are not practical.

Some sort of algorithm which dynamically calculates fault currents and manages to adjust the protection settings and scheme as appropriate to the new state of microgrid is direly needed. When coupled with the automated grid structure detection approach presented in Chapter 4, the dynamic parameter calculation method presented in this chapter contributes to the literature by satisfying this demand.