Due to high investment and maintenance costs, the government on Bangladesh is unable to provide sufficient support for grid extension and supplying electricity to remote or rural areas. The deficit in electricity introduces a crisis in powering irrigation systems, which influences negatively the country’s dominant income-generating sector, agriculture. Islanded microgrids with solar photovoltaic (PV) cells is one of the most attractive solutions for providing power to rural areas due to their cost-effectiveness, reliability and environment-friendly attributes. Therefore, a techno-economic feasibility study has been undertaken to investigate the prospects of renewable energy-based islanded microgrids to support rural electrification to power both households and irrigation systems. Three case studies based on the operation time of irrigation pumps during the day are developed using the HOMER Pro Microgrid Analysis Tool to identify the optimised configurations for the proposed system. The optimised configurations are then assessed considering the performance matrices of the cost of electricity (COE), net present cost (NPC), greenhouse gas (GHG) emissions and renewable energy fraction (RF). From the analyses, it is perceived that the operation of irrigation pumps at different times of a day is a significant influence, and the optimum method considering techno-economical evaluation is to run the irrigation pumps during the daytime by solar PV. It is evident that the proposed islanded microgrid has significant potentialities in powering irrigation systems as well as rural electrification with low energy generation costs, a contribution to the reduction of global warming and to ameliorating the energy crisis in Bangladesh in order to achieve a sustainable future.

This paper proposes a management technique which will retain the voltage and frequency of standalone microgrids (MGs), within a predefined safe zone, at least cost, using a multi-layer scheme. The proposed technique considers the sustainability and dynamic supply adequacy aspects, of the MG, whilst considering the operational costs which accrue during the continuous variations of its demand and renewable generation. This technique, takes action immediately following the occurrence of events, that violate the MGs voltage or frequency. It then adjusts the optimal generation levels for the dispatchable sources and determines the best configuration of the MG’s network. It also proceeds to optimize the internal support, by controlling the charge or discharge power of the existing battery storages as well as curtailing the renewable sources and adjusting the loads. The proposed technique, is a short-horizon operation-stage algorithm which uses a metaheuristic optimization at the MG’s central controller, to analyze the status and costs of the MG components, to determine the appropriate actions to implement. The performance of the developed technique, is validated through extensive numerical analyses in MATLAB.

This paper proposes the novel application of a genetic algorithm optimized fuzzy logic controller as a nonlinear controller for capacitive bridge type fault current limiter (CBFCL) to improve the stability performance of the power systems. The proposed controller provides fast convergence for the system and uses data from the system as a feedback in the controller loops. The performance of the proposed genetic algorithm optimized fuzzy logic controlled CBFCL is compared with that of a static nonlinear controller based CBFCL and a static nonlinear controller-based bridge type fault current limiter (BFCL). The detail controller design and stability analysis are carried out on the IEEE 39 bus power system in MATLAB/SIMULINK. To capture a realistic system's response, a wind farm is connected to bus one in the IEEE 39 bus system. From the simulation results and several quantifying parameters, it is shown that the proposed genetic algorithm optimized fuzzy logic controlled CBFCL can effectively improve the stability and the performance of the power system as well as the grid connected wind farm. Further, the proposed controller performs better than the static nonlinear controller based CBFCL and the static nonlinear controller based BFCL.

Conventional RCC uses Type-I compensator or Integrator which cannot track the Maximum Power Point (MPP) for all the operating condition without Adaptive Gain Tuning. The Type-II compensator based closed loop control scheme of the proposed MPPT makes it robust against all types of disturbances, panel and plant parameter variations. The RCC technique is very simple to implement and the total MPPT controller can be easily implemented using analog circuitry only. However, the challenge lies in designing the compensator as the RCC technique, along with PV panel, exhibits highly non-linear dynamics. Conventional Bode plot technique is used for designing the compensator where the plant parameters (Gain and Phase) are obtained by perturbing the panel operation around the MPP at crossover frequency. This paper proposes a compensator based implementation of Dynamic Maximum Power Point Tracking (MPPT) for rapidly changing irradiation and load variation using Ripple Correlation Control (RCC) technique. The proposed control scheme has a very fast convergence and is very prompt in tracking irradiance variation and load disturbance rejection. The efficacy of the proposed MPPT and the compensator are verified by simulation.

Diesel generators are typically used in remote Australian electricity networks to generate power for its consumers. Solar PV systems are one of the most common renewable resources due to their gradual technical advancement, decreasing cost and wide application. This study aims to design and model a PV-Diesel power system for a generic remote town in Australia. The electricity generation philosophy using a centralised PV system along with the existing Diesel capacity is modelled and simulated in Hybrid Optimization of Multiple Energy Resources (HOMER) software. The study considers higher levels of PV penetration and conducts a techno-economic analysis of different network configurations to propose a comprehensive electricity network design and generation philosophy, based on the cost of energy (AU$/kWh), the quantity of excess electricity, fuel savings potential and environmental impacts for a remote Australian town.