In the medium voltage direct current (MVDC) shipboard grid, the inherent inertial support from the DC capacitors is too small to resist step changes or fluctuations from the high power pulse load and propulsion load, which results in lower DC voltage quality. This study proposes a decentralised control algorithm for the MVDC shipboard hybrid energy storage system (HESS) to enhance the onboard survivability. This algorithm adjusts the droop control coefficient based on the bus voltage change rate adaptively, meanwhile the voltage differential signal processing and filtering are implemented by the trace differentiator. In addition, the proposed algorithm also has state-of-charge (SOC) balancing and SOC recovery abilities between multiple groups of energy storage devices. The parameter selection principle are analysed, and a variety of working conditions are simulated and verified in PSCAD. Theoretical analysis and simulation show that, HESS can achieve good power distribution and SOC management performance without communication compared to fixed droop coefficient control strategies, and the dynamic characteristics of bus voltage have been significantly improved.

Doubly-fed induction generators (DFIGs) have drawn prominent interest in the field of wind power generation, but they are vulnerable to grid faults. Grid codes mandate DFIGs to employ a sort of fault ride-through (FRT) technique during faults. Fault current limiters (FCLs) always help to augment the FRT capability of DFIGs and a non-linear controller boosts their performances. In this study, a non-linear auto-regressive moving average-L2 (NARMA-L2) controller-based bridge-type flux coupling non-superconducting FCL (BFC-NSFCL) is proposed to enhance the FRT capability of the wind farm. The authors analysed the performance of the proposed NARMA-L2-based BFC-NSFCL (NL2-BFC-NSFCL) against that of the conventionally used series dynamic braking resistor (SDBR), bridge-type FCL (BFCL), and proportional–integral (PI) controller-based BFC-NSFCL (PI-BFC-NSFCL). They tested the performance of the NL2-BFC-NSFCL through multiple temporary and permanent fault scenarios and carried out the mathematical and graphical analysis in MATLAB/Simulink platform. They found that the proposed NL2-BFC-NSFCL's performance surpasses the performances of the SDBR, the BFCL, and the PI-BFC-NSFCL. Moreover, the NL2-BFC-NSFCL has faster system recovery capability after the occurrence of any fault than other competitors.

Fossil fuel-fired power plants are still the principal power producers in most power systems. Retrofitting these pollutant generators with carbon capture and storage (CCS) technology can be a key solution to decarbonisation, especially for power systems with low expansion potential for renewable and hydroelectric energy resources. This study presents a coordinated generation and transmission expansion planning (G&TEP) and CCS expansion planning model for carbon emission constrained power systems. The proposed model determines the optimal order and time of retrofitting carbon emitter generators with CCS technology coordinated with the G&TEP. The limits on renewable resources capacity expansion potential and the yearly emission reduction targets are considered. Additionally, the proposed model allows for determining the incentives that are to be offered by the central planning authority to the pollutant generators to incentivise their participation in emission reduction through CCS retrofitting. The problem is formulated as a mixed-integer linear programming model and is decomposed into a master and three subproblems to tackle the large-scale nature of the developed optimisation problem. Numerical results demonstrate that a coordinated G&TEP and CCS expansion planning is a least-cost planning solution for emission constrained power systems with low expansion capacity potential for renewable and hydroelectric resources.

A novel islanding detection technique by hybridising empirical mode decomposition (EMD) and multi-scale mathematical morphology (MMM) is proposed to detect the islanding condition in a distributed generation system to ensure personnel and equipment safety. The proposed method first uses EMD to efficiently separate the collected raw signal into the number of intrinsic mode functions (IMFs) with different frequency scales and the signal is reconstructed considering important IMFs which carry transient features for further analysis using their correlation coefficients. MMM is used for determining a ratio index named as MMMRI, the threshold value of the proposed MMMRI decides islanding and other power quality (PQ) disturbances. The proposed hybrid method name coined as EMD-MMMRI. The main motivation behind hybridising two signal processing techniques is to reduce detection time and improve accuracy. The efficacy of the method is demonstrated for different PQ disturbances and islanding events simulated on a grid-connected, heavily wind energy penetrated distributed generation system using MATLAB/Simulink environment. The test bench validation of the proposed technique is obtained through TMS 320C6713 Starter Kit (DSK) in digital signal processor platform. The efficacy of proposed work is demonstrated with large number of simulation studies.

Microgrid inverters in the presence of faults, unavoidable modelling uncertainties, disturbance and harmonic current resulting from nonlinear loads should have small steady state tracking error, small THD and high robustness hence this subject has turned one of the motivations of this investigation. To achieve the stated goals, fractional adaptive sliding mode controller (FASMC) is proposed in this paper. The proposed controller increases the robustness, flexibility and degree of freedom. As far as in practice it is not easy to define the bounds of disturbances and guarantee the system stability, hence in next step, to overcome this challenge the adaptation laws are suggested. Then for the problem of determining the controller parameters, Particle Swarm Optimization (PSO) algorithm is used. The performance of the proposed technique is investigated for an islanded microgrid under different disturbances, also to verify the advantages of the proposed controller, the results are compared with other controllers. Finally, the proposed controller and PID controller are implemented experimentally on Arduino mega 2560 microcontroller.