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The voltage source converter (VSC) based HVDC (high voltage direct current system) offers the possibility to integrate other renewable energy sources (RES) into the electrical grid, and allows power flow reversal capability. These appealing features of VSC technology led to the further development of multi-terminal direct current (MTDC) systems. MTDC grids provide the possibility of interconnection between conventional power systems and other large-scale offshore sources like wind and solar systems. The modular multilevel converter (MMC) has become a popular technology in the development of the VSC-MTDC system due to its salient features such as modularity and scalability. Although, the employment of MMC converter in the MTDC system improves the overall system performance. However, there are some technical challenges related to its operation, control, modeling and protection that need to be addressed. This paper mainly provides a comprehensive review and investigation of the control and protection of the MMC-based MTDC system. In addition, the issues and challenges associated with the development of the MMC-MTDC system have been discussed in this paper. It majorly covers the control schemes that provide the AC system support and state-of-the-art relaying algorithm/ dc fault detection and location algorithms. Different types of dc fault detection and location algorithms presented in the literature have been reviewed, such as local measurement-based, communication-based, traveling wave-based and artificial intelligence-based. Characteristics of the protection techniques are compared and analyzed in terms of various scenarios such as implementation in CBs, system configuration, selectivity, and robustness. Finally, future challenges and issues regarding the development of the MTDC system have been discussed in detail.

The ecological and economical concerns have given rise to the application of solar photovoltaic (PV) system in the community to meet the increased load demands on its own. Owing to the varying output of solar PV modules depending on the weather conditions, the efficiency of system is degraded and thus requires using maximum power point (MPP) tracking technique for utmost power extraction. The MPP methods can be realized both mechanically or electrically using suitable converter topology and appropriate tracking algorithm. However, the mechanical tracker in contrast to electrical circuit is immoderate and inefficient and conversely necessitates to exercise effective and promising power tracking algorithm. This research proposes to implement the perturb and observe (Pand O) algorithm for MPPT in charge controller using buck–boost converter to attain desired and optimized results. The use of buck–boost DC–DC converter helps in stepping up/down the voltage level as per requirements under the control of Pand Oalgorithm. Having optimized tracker designed, its performance has been tested at different levels of irradiance and temperature principally with load and battery. Further, the results obtained from simulated scenarios are compared with real-time experiments, which confirm the robustness and effectiveness of proposed MPPT method in solar PV system using Pand Oalgorithm and buck–boost converter.

Background: Since the distribution networks are passive until Distributed Generation (DG) is not being installed into them, the stability issues occur in the distribution system after the integration of DG. Methods: In order to assure the simplicity during the calculations, many approximations have been proposed for finding the system’s parameters i.e. Voltage, active and reactive powers and load angle, more efficiently and accurately. This research presents an algorithm for finding the Norton’s equivalent model of distribution system with DG, considering from receiving end. Norton’s model of distribution system can be determined either from its complete configuration or through an algorithm using system’s voltage and current profiles. The algorithm involves the determination of derivative of apparent power against the current (dS/dIL) of the system. Results: This work also verifies the accuracy of proposed algorithm according to the relative variations in the phase angle of system’s impedance. This research also considers the varying states of distribution system due to switching in and out of DG and therefore Norton’s model needs to be updated accordingly. Conclusion: The efficacy of the proposed algorithm is verified through MATLAB simulation results under two scenarios, (i) normal condition and (ii) faulty condition. During normal condition, the stability factor near to 1 and change in dS/dIL was near to 0 while during fault condition, the stability factor was higher than 1 and the value of dS/dIL was away from 0.