Interconnected Autonomous Microgrids in Smart Grids with Self-Healing Capability

Abstract

In order to minimize the number of load shedding in a Microgrid during autonomous operation, islanded neighbour microgrids can be interconnected if they are on a self-healing network and an extra generation capacity is available in Distributed Energy Resources (DER) in one of the microgrids. In this way, the total load in the system of interconnected microgrids can be shared by all the DERs within these microgrids. However, for this purpose, carefully designed self-healing and supply restoration control algorithm, protection systems and communication infrastructure are required at the network and microgrid levels. In this chapter, first a hierarchical control structure is discussed for interconnecting the neighbour autonomous microgrids where the introduced primary control level is the main focus. Through the developed primary control level, it demonstrates how the parallel DERs in the system of multiple interconnected autonomous microgrids can properly share the load in the system. This controller is designed such that the converter-interfaced DERs operate in a voltage-controlled mode following a decentralized power sharing algorithm based on droop control. The switching in the converters is controlled using a linear quadratic regulator based state feedback which is more stable than conventional proportional integrator controllers and this prevents instability among parallel DERs when two microgrids are interconnected. The efficacy of the primary control level of DERs in the system of multiple interconnected autonomous microgrids is validated through simulations considering detailed dynamic models of DERs and converters.

Appendices

Appendix A

As described in Sect. 15.3.1, the DERs considered in this chapter were modeled in detail. The technical data for these models are summarized below.

15.1.1 Fuel Cell

Based on experimental validations, a typical Proton exchange membrane fuel cell (PEMFC) has an output V–I characteristic of

$$ V(i) = 371.3 - 12.38\log (i) - 0.2195i - 0.2242e^{0.025i} $$

(A.1)

reported and utilized in [55].

15.1.2 Photovoltaic Cell (PV)

In [55], the simplified equivalent circuit of a PV was utilized where its output voltage was a function of its output current and its output current was a function of load current, ambient temperature and radiation level. In this model, the voltage output of PV is calculated by

$$ V_{PV} = \frac{{AkT_{c} }}{e}Ln\left( {\frac{{I_{ph} + I_{o} - I_{c} }}{{I_{o} }}} \right) - R_{s} I_{c} $$

(A.2)

where

A :

Constant value for curve fitting

e :

Electron charge (1.602 × 10⁻19 C)

k :

Boltzmann constant (1.38 × 10⁻23 J/^ok)

I _c :

Output current of PV cell

I _ph :

Photocurrent (1 A)

I _o :

Diode reverse saturation current (0.2 mA)

R _s :

Series resistance of PV cell (1 mΩ)

V _PV :

Output voltage of PV cell

T _c :

PV cell reference temperature (25 °C).

A Maximum Power Point Tracking (MPPT) method was also used to achieve maximum power from the PV based on the load or ambient condition changes. The MPPT algorithm was presented in [55].

15.1.3 Battery

The battery is assumed to be a constant voltage source with fixed amount of energy and modeled as a constant DC voltage source with series internal resistance [55].

Appendix B

The technical data (Tables B.1, B.2) of the microgrid network under consideration in Fig. 15.2 is provided.

Table B.1 Technical data of the considered network

Table B.2 Technical data of the DERs and droop control coefficients