Summary and Conclusions 120 

The main goal of this thesis was allowing seamless integration of high DG penetration into the ADN paradigm by developing new DG control algorithms from both SCL and PCL perspectives. From the SCL perspective, new control algorithms were proposed in Chapters 3 and 4 in order to guarantee proper voltage regulation and relaxed tap operation for OLTCs by dispatching DG active and reactive power references. It was shown in Chapter 5 that DG dynamic performance is dependent on its operating condition as well as grid/load impedance. A change in the DG operating condition can be triggered by changing the DG active and reactive power references or DG loading. Also, the grid/load is time-varying and uncertain, and thus a DG primary controller should be adaptively tuned to mitigate such uncertainties. To achieve that purpose, a new grid admittance identification algorithm was proposed in Chapter 5 and utilized in Chapter 6 to develop DG adaptive controllers from a PCL perspective. A detailed summary of the content of each chapter is given below.

In Chapter 3, a coordinated fuzzy-based voltage regulation scheme was proposed for OLTC and DGs. The main motivation of applying fuzzy logic is that it can deal with environments of imperfect information, and thus can reduce communication requirements. The proposed regulation scheme consists of three fuzzy-based control algorithms. The first control algorithm is proposed for the OLTC such that it can mitigate the effect of DGs on the voltage profile. The second control algorithm is proposed to provide DG reactive power sharing to relax the OLTC tap operation. The third control algorithm aims to partially curtail DG active powers to restore a feasible solution from the OLTC perspective. The proposed fuzzy algorithms have the advantage of providing proper voltage regulation with relaxed tap operation, utilizing only the estimated system minimum and maximum voltages. In addition, it avoids numerical instability and convergence problems associated with centralized approaches, as it does not require an optimization algorithm to be run. Real-time simulations were developed to show the success of the proposed fuzzy algorithms on a typical distribution network using OPAL RTS. The results demonstrated the success of the proposed fuzzy algorithms under various operating conditions and system configurations.

In Chapter 4, a V2GQ support strategy was proposed for optimal coordinated voltage regulation in distribution networks with high DG and PEV penetration. The proposed algorithm employs PEVs, DGs, OLTCs to satisfy PEV charging demand and grid voltage requirements with relaxed tap operation and minimum DG active power curtailment. The voltage regulation problem is formulated as non-linear programming and consists of three consecutive stages, in which the outputs of the preceding stages are applied as constraints. The first stage aims to maximize the energy delivered to PEVs to assure PEV owner satisfaction; the second stage maximizes the DG-extracted active power; and the third stage minimizes the voltage deviation from its nominal value utilizing the available PEV and DG reactive powers. The main implicit objective of the third stage problem is relaxing the OLTC tap operation.

In addition, the conventional OLTC control is replaced by a proposed centralized controller that utilizes the output of the third stage to set its tap position. The effectiveness of the proposed algorithm, in a typical distribution network, is validated in real time using OPAL RTS in an HiL application. The results demonstrated the ability of the proposed coordination to provide proper voltage regulation with maximized PEV demand power, maximized DG extracted power, and relaxed OLTC tap operation.

In Chapter 5, a new multivariable grid admittance identification algorithm was proposed with adaptive model order selection, as an ancillary function within the inverter-based DG controllers. It was shown that DG controllers with fixed gains can suffer from instability issues when the grid admittance changes. Due to cross-coupling between the d-axis and q-axis grid admittances, a multivariable estimation is essential. First, controlled voltage pulses are injected by the DG, based on a sensitivity analysis, to ensure a persistence of excitation for the grid admittance. Then, the extracted grid dynamics are processed by the RIVC algorithm to estimate the grid admittance. The theoretical background of the RIVC algorithm was explained, accompanied by its integration within the proposed adaptive model order selection method. Unlike non-parametric identification algorithms, the proposed RIVC provides a parametric multivariable model for the grid admittance which is essential for designing DG adaptive controllers. The proposed algorithm was validated by OPAL RTS in both grid-connected and isolated ADNs, via an HiL application. The results confirmed the accuracy and convergence of the proposed identification in estimating both passive and active grid admittances, without extra hardware.

In Chapter 6, an adaptive DG control algorithm was proposed to optimally reshape the DG output impedance in order to maximize the system damping and bandwidth. The adaptation is essential to cope with variations in grid impedance and changes in DG operating conditions. The proposed algorithm is generic, i.e., can be applied in grid-connected and islanded DGs, and involves three design stages. In the first stage, the multivariable DG output impedance is mathematically derived and verified using a frequency sweep identification method. The grid impedance is also estimated using the proposed identification algorithm presented in Chapter 5 to formulate the impedance stability criteria. In the second stage, a multi-objective programming is formulated using the - constraint method to maximize the system damping and bandwidth. Finally, in the third stage, the solutions provided by the optimization stage are employed to train a NN-based adaptation scheme which tunes the DG control parameters online. The proposed algorithm is validated by OPAL RTS in both grid-connected and isolated ADNs, via HiL applications. It was shown that the proposed control algorithm can maintain system stability, increase system bandwidth, and improve system damping under various grid impedances and load natures.