Category Renewable Energy Integration

The distributed control technique is based on frequency partitioning between the central and local controllers [50, 51]. The central controller is responsible for controlling the low-frequency term and the local controllers the high-frequency term. Information on the modules’ voltage references, current references and average feedback voltages is shared among the modules. This scheme presents a control algorithm which combines a low-pass filter (HLF) with a matched high – pass filter (1 —HLF). The filters are used for perfect sharing of the control spectrum between two controllers, as depicted in Fig. 9.10. This control scheme uses a limited bandwidth of the communication signal. Its advantages and disadvantages are [35, 50]:

• Transient load-sharing is improved,

• The system will co...

From the above literature, there are several issues, which have not yet been taken

into consideration by researchers. In this dissertation, some are discussed, with the

main focus being on the following.

• Consideration of PHEV battery dynamics for load calculation and a cussed in the literature.

• Introduction of a novel ancillary service of PHEVs through designing a filter for a power system.

• Designs of virtual FACTS devices using PHEVs, which a few researchers have addressed.

• A complete power quality solution for a benchmark distribution network using V2G technology.

Figure 13.6 shows the proposed aggregated DFIG wind farm model that consists of a mechanical torque compensating factor (MTCF) incorporated into a tradi­tional full aggregated model. The MTCF (a) is a multiplication factor to the mechanical torque (T’magg) of the full aggregated model that minimizes this inaccuracy in approximation. The mechanical torque (Tmagg) of the proposed aggregated DFIG wind farm model is thus calculated by

Tmagg — Tmagg * a (13.12)

The proposed model also involves the calculation of an equivalent internal network and the simplification of the power coefficient (Cp) function.

As mentioned before, the outer-loop control regulates the output power of DERs by adjusting the proper references for the each DER from (15.2) or (15.7). The
inner-loop control will calculate and apply proper switching signals for the IGBTs in the DER converter such that the desired voltage (Vcfref) is perfectly generated across the AC filter capacitor (Cf).

For this, let us consider the equivalent circuit of VSC as shown in Fig. 15.3b. In this figure, u-a-Vdc represents the converter output voltage, where u is the switching function. For a 2-level (bipolar) switching, u can take on ± 1 value which will be used subsequently to turn ON/OFF the IGBTs.

Let us consider the DER converter and its output filter as system for which a controller is to be developed...

Consider a measurement vector z for an n-bus system, where, z 2 RMx1, M > (2n — 1)x 1. Therefore, z should be:

zi

_ Zm _

It is assumed that the measurement vector should contain some error with the exact measurement function value. Therefore, z can be written as:

Here, h(x) is the calculated function values for the state variables. x is the vector of state variables and e is the vector of measurement errors.

Generally, e is a zero-mean Gaussian noise vector where measurement errors are independent. Therefore, E(ej) = 0, where i = 1,2,m. And E^ej = 0 and Cov(e) = E[eeT] = R = diag (a, a2 ,… a2m).

The structure of the proposed hybrid optimization method for optimal siting and sizing of WTs is shown in Fig. 6.2. The method jointly minimizes the total energy losses over a year and maximizes the SW for each scenario.

The WTs’ sizes and locations are represented by the variable of the GA: a vector of integers, called chromosome, in the range [0, Nsizes] with a length equal to the number of candidate buses Nc such that each element of the vector is associated to a candidate bus as shown in Fig. 6.3. In such a way, different vectors allow representing different investments in WTs both in terms of selected locations and sizes.

Different sizes of WTs identified with a label in the range [0, Nsizes] are con­sidered on the basis of their rating power and power coefficients...

AGC plays a key role in maintaining the balance of power grid generation and consumption. Though no research has covered this topic yet, variable-speed wind generators could act to the AGC regulation order from the operator as effeciently as conventional generation. Actually, thanks to the fast response speed of power electronics converters, the active power output of variable-speed wind generators could ramp up/down quickly, which makes wind generators even better candidates for AGC regulation. The only disadvantage is the waste of wind energy during normal conditions due to the reserve.

The following exponential forms are used to represent a static load.

P(V > = p0© ”• (10’8)

Q(V) = e^V) • (10-9)

where P and Q are the active and reactive components of the load, respectively and V is the bus voltage magnitude. The subscript 0 identifies the values of the respective variables at the initial operating condition. The parameters of this model are the exponents a and b. With these exponents equal to 0, 1 or 2, the model represents the constant power, constant current or constant impedance character­istics of load components, respectively.

For composite loads, the load components for the nominal system are aggre­gated assuming that a load delivery point consists of 30 % static loads (space heating, cooking, water heater, etc...